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Human Genetics and Childhood Diseases, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Human Genetics and Childhood Diseases

Curator: Larry H. Bernstein, MD, FCAP

 

 

 

Publication Roundup: HGMD

HGMD®, the Human Gene Mutation Database is used by scientists around the world to find information on reported genetic mutations. The papers below use the database to advance our understanding of disease, DNA dynamics, and more.

https://www.qiagenbioinformatics.com/blog/translational/publication-roundup-hgmd

Local DNA dynamics shape mutational patterns of mononucleotide repeats in human genomes
First author: Albino Bacolla

Scientists in the US and UK published results in Nucleic Acids Research of a detailed analysis of single-base substitutions and indels in the human genome. Their findings show that certain base positions are more susceptible to mutagenesis than others. They used HGMD Professional to find mutations in specific genomic regions for analysis; the paper includes charts showing mutation patterns, germline SNPs, and more from HGMD data.

High prevalence of CDH23 mutations in patients with congenital high-frequency sporadic or recessively inherited hearing loss
First author: Kunio Mizutari

This Orphanet Journal of Rare Diseases paper from scientists in Japan sequenced 72 patients with unexplained hearing loss, finding several CDH23 mutations, some of which were novel. Mutations in the gene have been linked to Usher syndrome and other forms of hereditary hearing loss. The scientists used HGMD to find all known CDH23 mutations within nearly 70 coding regions.

Mutation analyses and prenatal diagnosis in families of X-linked severe combined immunodeficiency caused by IL2Rγ gene novel mutation
First author: Q.L. Bai

In Genetics and Molecular Research, scientists report the utility of mutation analysis of the interleukin-2 receptor gamma gene to assess carrier status and perform prenatal diagnosis for X-linked severe combined immunodeficiency. They studied two high-risk families, along with 100 controls, to evaluate the approach. Sequence variation was determined using HGMD Professional and an X-SCID database, and a new mutation was discovered in the project.

Impact of glucocerebrosidase mutations on motor and nonmotor complications in Parkinson’s disease
First author: Tomoko Oeda

Researchers from three hospitals in Japan published this Neurobiology of Aging report that may help stratify Parkinson’s disease patients by prognosis. They sequenced mutations in the GBA gene in 215 patients, finding that those who had mutations associated with Gaucher disease suffered dementia and psychosis much earlier than those who didn’t. The team found previously reported GBA mutations using HGMD Professional.

Comprehensive Genetic Characterization of a Spanish Brugada Syndrome Cohort
First author: Elisabet Selga

In this PLoS One publication, scientists from a number of institutions in Spain examined genetic variation among patients with Brugada syndrome, a rare genetic cardiac arrhythmia. They sequenced 14 genes in 55 patients, identifying 61 variants and finding the subset that appear pathogenic. Variants were filtered against a number of databases, including HGMD.

 

 

Local DNA dynamics shape mutational patterns of mononucleotide repeats in human genomes

Albino Bacolla1Xiao Zhu2Hanning Chen3Katy Howells4David N. Cooper4 and Karen M. Vasquez1

Nucl. Acids Res. (26 May 2015) 43(10): 5065-5080.   http://dx.doi.org:/10.1093/nar/gkv364

Single base substitutions (SBSs) and insertions/deletions are critical for generating population diversity and can lead both to inherited disease and cancer. Whereas on a genome-wide scale SBSs are influenced by cellular factors, on a fine scale SBSs are influenced by the local DNA sequence-context, although the role of flanking sequence is often unclear. Herein, we used bioinformatics, molecular dynamics and hybrid quantum mechanics/molecular mechanics to analyze sequence context-dependent mutagenesis at mononucleotide repeats (A-tracts and G-tracts) in human population variation and in cancer genomes. SBSs and insertions/deletions occur predominantly at the first and last base-pairs of A-tracts, whereas they are concentrated at the second and third base-pairs in G-tracts. These positions correspond to the most flexible sites along A-tracts, and to sites where a ‘hole’, generated by the loss of an electron through oxidation, is most likely to be localized in G-tracts. For A-tracts, most SBSs occur in the direction of the base-pair flanking the tracts. We conclude that intrinsic features of local DNA structure, i.e. base-pair flexibility and charge transfer, render specific nucleotides along mononucleotide runs susceptible to base modification, which then yields mutations. Thus, local DNA dynamics contributes to phenotypic variation and disease in the human population.

INTRODUCTION

Changes in human genomic DNA in the form of base substitutions and insertions/deletions (indels) are essential to ensure population diversity, adaptation to the environment, defense from pathogens and self-recognition; they are also a critical source of human inherited disease and cancer. On a genome-wide scale, base substitutions result from the combined action of several factors, including replication fidelity, lagging versus leading strand DNA synthesis, repair, recombination, replication timing, transcription, nucleosome occupancy, etc., both in the germline and in cancer (14). On a much finer scale [(over a few base pairs (bp)], rates of base substitutions may be strongly influenced by interrelationships between base–protein and base–base interactions. For example, the mutator role of activation-induced deaminase (AID) in B-cells during class-switch recombination and somatic hypermutation (5) targets preferentially cytosines within WRC (W: A|T; R: A|G) sequences (6), whereas apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) overexpression displays a preference for base substitutions at cytosines in TCW contexts (7). Other examples, such as the induction of C→T transitions at CG:CG dinucleotides by cytosine-5-methylation and the role of UV light in promoting base substitutions at pyrimidine dimers have been well documented (reviewed in (4,8)). More recently, complex patterns of base substitution at guanosines in cancer genomes have been found to correlate with changes in guanosine ionization potentials as a result of electronic interactions with flanking bases (9), suggesting a role for electron transfer and oxidation reactions in sequence-dependent mutagenesis. However, despite these advances, the increasing number of sequence-dependent patterns of mutation noted in genome-wide sequencing studies has met with a lack of understanding of most of the underlying mechanisms (10). Thus, a picture is emerging in which mutations are often heavily dependent on sequence-context, but for which our comprehension is limited.

Mononucleotide repeats comprise blocks of identical base pairs (A|T or C|G; hereafter referred to as A-tracts and G-tracts) and display distinct features: they are abundant in vertebrate genomes; mutations within the tracts occur more frequently than the genome-wide average; mutations generally increase with increasing tract length; length instability is a hallmark of mismatch repair-deficiency in cancers; and sequence polymorphism within the general population has been linked to phenotypic diversity (1115). Thus, mononucleotide repeats appear ideal for addressing the question of sequence-dependent mutagenesis since base pairs within the tracts are flanked by identical neighbors. Both historic and recent investigations concur with the conclusion that a major source of mononucleotide repeat polymorphism is the occurrence of slippage (i.e. repeat misalignment) during semiconservative DNA replication, which gives rise to the addition or deletion of repeat units (11,12). An additional and equally important source of mutation has recently been suggested to arise from errors in DNA replication by translesion synthesis DNA polymerases, such as pol η and pol κ (13), also on slipped intermediates, leading to single base substitutions.

A key question that remains unanswered in these studies and which is relevant to the issue of sequence context-dependent mutagenesis is whether all base pairs within mononucleotide repeats display identical susceptibility to single base changes and whether indels (which are consequent to DNA breakage) occur randomly within the tracts.

Herein, we combine bioinformatics analyses on mononucleotide repeat variants from the 1000 Genomes Project and cancer genomes with molecular dynamics simulations and hybrid quantum mechanics/molecular mechanics calculations to address the question of sequence-dependent mutagenesis within these tracts. We show that mutations along both A-tracts and G-tracts are highly non-uniform. Specifically, both base substitutions and indels occur preferentially at the first and last bp of A-tracts, whereas they are concentrated between the second and third G:C base pairs in G-tracts. These positions coincide with the most flexible base pairs for A-tracts and with the preferential localization of a ‘hole’ that results when one electron is lost due to an oxidation reaction anywhere along G-tracts. Thus, despite the uniformity of sequence composition, mutations occur in a sequence-dependent context at homopolymeric runs according to a hierarchy that is imposed by both local DNA structural features and long-range base–base interactions. We also show that the repair processes leading to base substitution must differ between A- and G-tracts, since in the former, but not in the latter, base substitutions occur predominantly in the direction of the base immediately flanking the tracts. Additional sequence-dependent patterns of mutation are likely to arise from studies of more heterogeneous sequence combinations, possibly involving other aspects intrinsic to the structure of DNA.

 

RESULTS

Mononucleotide repeat variation is defined by tract length and flanking base composition

We define mononucleotide repeats in the GRCh37/hg19 (hg19) human genome assembly as uninterrupted runs of A:T and G:C base pairs (hereafter referred to as A-tracts and G-tracts, respectively) from 4 to 13 base pairs in length (Figure 1A). We retrieved a total of 48,767,945 A-tracts and 13,633,781 G-tracts, both of which displayed a biphasic distribution with an inflection point between tract lengths of 8 and 9 (bp) and with the number of runs declining with length more dramatically for G-tracts than for A-tracts (Figure 1B), as noted previously (29). Both the number of short tracts and the extent of decline varied with flanking base composition, TA[n]T runs being two- to three-fold more abundant than CA[n]Cs (Supplementary Figure S1A) and AG[n]As declining the most rapidly (Supplementary Figure S1B). Thus, mononucleotide runs exist as a collection of separate pools of sequences in extant human genomes, each maintained at distinctive rates of sequence stability, as determined by factors such as bp composition (A:T versus G:C), tract length and flanking sequence composition.

Figure 1.

Mononucleotide repeat variation, evolutionary conservation and association with transcription. (A) The search algorithm was designed to retrieve runs of As or Ts (A-tracts) and Gs or Cs (G-tracts) length n (n = 4 to 13), along with their 5′ (n = 0) and 3′ (n = n + 1) nearest neighbors from hg19. Tract bases were numbered 5′ to 3′ with respect to the purine-rich sequence. The panel exemplifies the nomenclature for A- and G-tracts of length 4. (B) Logarithmic plot of the number of A-tracts (closed circles) and G-tracts (open circles) in hg19 as a function of length. (C) Normalized fractions of polymorphic tracts (F SNV) (number of SNVs divided by both hg19 number of tracts and n) from the 1KGP for A-tracts (closed circles) and G-tracts (open circles). (D) Radial plot of SNVs in the 1KGP at the 5′ and 3′ nearest neighbors of A-tracts. Periphery, tract length; horizontal axis, scale for the fraction of SNVs (F SNV). (E) Radial plot of SNVs in the 1KGP at the 5′ and 3′ nearest neighbors of G-tracts. (F) Percent difference in the numbers of A-tracts (closed circles) and G-tracts (open circles) between syntenic regions of hg19 and HN genomes. (G) The exponents of Benjamini-corrected P-values for A-tract-containing genes enriched in transcription-factor binding sites plotted as a function of A-tract length (triangles); each value represents the median of the top 11 USCS_TFBS terms. The percent A-tracts (closed circles) and G-tracts (open circles) intersecting genomic regions pulled-down by chromatin immunoprecipitation using antibodies against transcription factors are plotted as a function of tract length. (H) List of gene enrichment terms with a Benjamini-corrected P-value of <0.05 in common between genes containing A- and G-tracts of lengths 4–13, excluding the UCSC_TFBS terms.

 We examined the extent of sequence variation in the human population by mapping 38,878,546 single nucleotide variants (SNVs) from 1092 haplotype-resolved genomes (the 1000 Genomes Project, 1KGP) (30) to the hg19 A- and G-tracts. The normalized fractions of polymorphic tracts (F SNV) were greater for G-tracts than A-tracts and both displayed Gaussian-type distributions, with maxima of 0.067 for G-tracts of length 8 and 0.017 for A-tracts of length 9 (Figure 1C). CA[n]C and AG[n]A runs displayed the highest F SNV values for A- and G-tracts, respectively (Supplementary Figure S1C and D), with F SNV values for AG[n]As attaining ∼0.10 at length 8. We conclude that flanking base composition influences the rates of SNV within mononucleotide runs and, as a consequence, their representation in the reference human genome.

F SNV values at the flanking 5′ and 3′ bp were similar between A- and G-tracts, except for minor differences for the least represented (i.e. longest) tracts and did not exceed 0.02 (Supplementary Figure S1E). These fractions are expected to be greater than at more distant positions from the tracts, based on previous data (29). SNVs at G-tracts, but not at A-tracts, were more frequent than at flanking base pairs. F SNVs for base pairs flanking short (≤8 bp) tracts were at least twice as high as those flanking long tracts; F SNVs also displayed distinct sequence preference with most (∼0.1) variants occurring at Ts 3′ of G-tracts (Figure 1D and E). In summary, SNVs at mononucleotide runs do not increase monotonically with length but peak at 8–9 bp. This behavior mirrors the genomic distributions, both with respect to the total number of tracts (Figure 1B) and the subsets flanked by specific-sequence combinations (Supplementary Figure S1A–D). Variation at flanking base pairs also displayed a biphasic pattern centered at a length of 8–9 bp, with a greater chance of variation adjacent to G- than A-tracts and with characteristic sequence preferences.

Long tracts are evolutionarily conserved and associated with high transcription

To assess whether more variable monosatellite runs (Figure 1C) might have undergone a greater reduction in number in extant humans relative to extinct hominids, we compared the number of A- and G-tracts between syntenic regions of five individuals comprising hg19 and three Neanderthal (HN) specimens (31). The difference between hg19 and HN was very small (<±2%) for the short tracts, but it displayed more negative values in hg19 with increasing tract length, which reached a maximum of −11.8 and −32.7% for A- and G-tracts, respectively, of length 9. Beyond this threshold, the numbers of tracts converged for A-tracts, whereas they were more abundant in hg19 for G-tracts >11 bp (Figure 1F). In summary, the largest difference in the number of mononucleotide runs between hg19 and HN sequences was centered at 9 bp for both A- and G-tracts, suggesting that the length distributions (Figure 1A and Supplementary Figure S1A and B) reflect distinct rates of evolutionary gains and losses due to differential sequence mutability (Figure 1C) as a function of length and flanking sequence composition (12).

The fact that long (>9 bp) mononucleotide runs display low variability in the human population (Figure 1C) and sequence conservation during evolutionary divergence (Figure 1F) raises the possibility that they might serve functional roles. Through gene enrichment analyses, we found that genes containing A- and G-tracts were enriched for genes associated with the term ‘UCSC_TFBS’, which pertains to transcripts harboring frequent transcription factor binding sites (32,33). For A-tract-containing genes, the median P-values for the top 11 UCSC_TFBS terms decreased from 2.95E-26 for tracts of length 4 to 5.22E-241 for tracts of length 13 (Figure 1G). The percent of A-tracts intersecting genomic fragments amplified from chromatin immunoprecipitation using transcription-factor binding antibodies (32,33) also increased from 8.7 to 9.9 from length 6 to 13, whereas it was constant (mean ± SD, 22.4 ± 1.1) for G-tracts (Figure1G). For gene classes excluding ‘UCSC_TFBS’, a search for categories enriched at P < 0.05 and common to all A- and G-tract-containing genes returned a set of 25 terms, 22 of which were associated with high levels of tissue-specific gene expression (Figure 1H). In summary, these analyses extend prior work (14) supporting a role for mononucleotide tracts in enhancing gene expression, a function that for A-tracts appears to increase with increasing tract length.

Repeat variability is highly skewed

Next we addressed whether bp along A- and G-tracts display equal probability and type of variation. In the 1KGP dataset, the number of SNVs at each position along both A- and G-tracts of length 4 was within a two-fold difference (144,000–240,000); for both types of sequence, transitions (i.e. A→G and G→A) were the predominant (51–78%) type of base substitution (Supplementary Figure S2A and B). However, with increasing length, the number of SNVs decreased up to 30-fold more drastically for G-tracts than for A-tracts, with increasing numbers of transversions (A→T and G→C|T) being predominant. Normalizing the data for the number of tracts genome-wide revealed that the extent of SNV varied by up to 10-fold, depending upon tract length and bp position. Specifically, the highest degree of variation was observed at the first and last A within the A-tracts (i.e. A1 and An), which underwent up to 61% A→T and 43% A→C transversions, respectively, at length 9 (Figure 2A). Likewise, for G-tracts, the most polymorphic sites were G3, followed by G2, for mid-size tracts of 8–10 bp, with 44% G→C transversions at G3 for tracts of length 8 (Figure2B). Thus, the extent of SNV at mononucleotide runs is grossly skewed in human genomes, both along the sequence itself and across tract length, which must account for the bell-shape behavior in F SNV for the tracts as a whole (Figure 1C).

Figure 2.

Population variation spectra. (A) Variation spectra of A-tracts. Percent (number of SNVs at each position divided by the number of tracts in hg19 × 100) of A→T (black), A→C (red) and A→G (green) SNVs in the 1KGP dataset (left). Percent SNVs at A1 as a function of tract length (right). (B) Variation spectra of G-tracts. As in panel A with G→T (black), G→C (red) and G→A (cyan) (left). Percent SNVs at G3 as a function of tract length (right). (C) Percent A→T, A→C and A→G transitions at each position along A-tracts (stars) preceded and followed by a T (TA[n]T, left), C (CA[n]C), center) and G (GA[n]G, right) as a function of tract length. (D) Percent G→T, G→C and G→A transitions at each position along G-tracts (stars) preceded and followed by a T (TG[n]T, left), C (CG[n]C), center) and A (AG[n]A, right) as a function of tract length. (E) Percent transitions at base pairs (stars) preceding or following A-tracts (left) and G-tracts (right) as a function of tract length (n). *, mutated position.

We assessed whether SNV hypervariability was associated with specific combinations of nearest neighbors. For A-tracts flanked 5′ by a T, C or G, the highest percentage of SNVs was observed at A1 when preceded by a T, which reached 7.9% for TA[n] tracts of length 9 (Supplementary Figure S2C). By contrast, for 3′ T, C or G, the greatest effect was elicited by a C, with the highest percentage (7.1%) of SNVs at An for A[n]C tracts of length 9 (Supplementary Figure S2D). Therefore, flanking base pairs play a critical role both in the spectra and frequencies of SNVs at A-tracts. More detailed plots along A-tracts either preceded (Supplementary Figure S2E), followed (Supplementary Figure S2F) or preceded and followed (Figure 2C) by a T, C or G revealed the dramatic and long-range (up to 9–10 bp for the longest tracts, higher than the value of 4 bp predicted by mathematical models of slippage (11)) influence of flanking base pairs on variation spectra, in which up to 95% of the changes were in the direction of the base flanking the tract. Because the number of A-tracts preceded or followed by a specific base varies by up to three-fold (Supplementary Figure S2G), we conclude that for A-tracts, the overall mutation fractions and spectra are the result of at least three variables; length, position along the tract, and base composition of the 5′ and 3′ nearest-neighbors.

For G-tracts flanked 5′ by a T, C or A, high percentages (10–12%) of SNVs were observed at G1 for tracts preceded by a C, an effect that decreased with increasing tract length (Supplementary Figure S3A). This result, together with an exceedingly low number of G→A transitions at G1 for tracts not preceded by a C (Supplementary Figure S3C) relative to all tracts (Supplementary Figure S2B), is consistent with the known high mutability of CG:CG dinucleotides as a result of cytosine-5 methylation (9). The hypermutability at G2 was observed preferentially for tracts preceded by an A, and to a lesser extent T, whereas that at G3 was insensitive to flanking sequence composition. Likewise, G-tracts flanked 3′ by a T, C or A did not display marked sequence-dependent effects (Supplementary Figure S3B). Detailed plots of the SNV spectra along G-tracts either preceded (Supplementary Figure S3D), followed (Supplementary Figure S3E), or preceded and followed (Figure 2D) by a T, C or A revealed a noticeable effect only for 5′ T in association with G→T substitutions at G1for tracts of length ≥8. Thus, despite a consistent over-representation of G-tracts flanked 5′ by a T (Supplementary Figures S3F and S1B), which must account for the high absolute number of SNVs at G1 for TG[n] relative to AG[n] and CG[n] (Supplementary Figure S3G), nearest-neighbor base composition seems to play a lesser role in SNV spectra at G-tracts than at A-tracts.

With respect to SNVs at the flanking 5′ and 3′ nearest positions, no B→A or H→G substitutions (Figure 1A) were found above a length threshold of 9 for A-tracts and 8 for G-tracts (Figure 2E, gray shading) out of 5969 SNVs, implying that tract expansion by recruiting flanking base pairs is disfavored at these lengths. In summary, base substitution along mononucleotide repeats is strongly skewed towards the edges of A-tracts and within the 5′ half of G-tracts, with frequencies that peak at midsize lengths (8–9 bp). For A-tracts ≥7 bp, base substitution occurred almost exclusively in the direction of the flanking nearest-neighbors. Finally, base substitution at flanking bases did not contribute to tract expansion for mononucleotide runs longer than 8–9 bp.

Insertions and deletions display length and positional preference

In addition to SNVs, mononucleotide runs are polymorphic in length as a result of indels. Herein, we consider separately two types of indels: one in which tract length changes by ±1 and flanking bp composition is not altered (slippage); the other comprising all other cases involving the addition or removal of 1–200 bp (indels). Slippage is a widely accepted mutational mechanism (1112,34), whereby DNA replication errors at reiterated DNA motifs cause changes in the number of motifs (most often +/−1). The normalized fractions of slippage in the 1KGP dataset peaked at lengths of 8 bp for A-tracts and 9 bp for G-tracts (Figure 3A), generating bell-shaped curves similar to those observed for SNVs (Figure1C) and with no differences in the highest fraction of ‘slipped’ tracts, which peaked at ∼0.02. By contrast, +1 slippage occurred more frequently than −1 slippage at A-tracts (Figure 3B). These results support recent studies on microsatellite repeats (12) and contrast with previous conclusions that slippage increases monotonically with tract length, and that the extent of slippage differs between A- and G-tracts (35,36).

Figure 3.

Population insertions and deletions. (A) Normalized fractions of A-tracts (closed circles) and G-tracts (open circles) displaying +/−1 bp slippage in the 1KGP dataset as a function of tract length. Data were obtained by dividing the number of events by both the number of hg19 tracts and tract length (n). (B) Ratio of the number of +1 to −1 slippage for A-tracts (closed circles) and G-tracts (open circles). (C) Indels at A-tracts. For positions along the tracts (‘Tract’), ‘F Indel’ is the ratio between the number of indels and the number of tracts in hg19 multiplied by tract length. For the positions immediately flanking the tracts genomic coordinates (‘Before tract’ and ‘After tract’), ‘F Indel’ is the ratio between the number of indels and the number of tracts in hg19. (D) Indels at G-tracts, calculated as described in panel C. (E) Heatmap representation of insertions along A-tracts. The percent insertions (i.e. the number of insertions at each position divided by the number of tracts in hg19) (y-axis) plotted as a function of location (x-axis) from position 0 (insertion between the bp 5′ to the tract and the first bp of the tract) to position n + 1 (insertion between the bp 3′ to the last bp of the tract and the following bp) (see Figure 1A) and as a function of tract length (z-axis). (F) Heatmap representation of insertions along G-tracts.

With respect to indels, the normalized fractions were low (<1 × 10−3) along short (4–6 bp) A- and G-tracts, but rose to a plateau for longer tracts as reported earlier (11); this plateau was 10-fold higher for G-tracts (∼0.03) than for A-tracts (∼0.003) (Figure 3C and D). Indels also occurred more frequently (up to six-fold for A-tracts of length 11) at nearest-neighboring base pairs (‘Before tract’ and ‘After tract’ in Figure 3C and D) than along the tracts. Thus, contrary to SNVs and slippage, indels increased to a plateau with mononucleotide tract length.

We analyzed in detail the locations of insertions along the tracts and the flanking positions with respect to the 5′ to 3′ orientation of the tracts (Figure 1A). The normalized fractions demonstrated that insertions peaked at the 3′, and to a lesser extent 5′, ends of the longest A-tracts (Figure 3E), but remained low. For G-tracts, insertions occurred most efficiently at two locations (G2–3 and G5) (Figure 3F), they increased with tract length (up to ∼0.04), and attained ∼10-fold higher values than for A-tracts. In conclusion, insertion sites at A- and G-tracts followed the patterns observed for SNVs (Figure 2A and B), suggesting that factors associated with local DNA dynamics sensitize specific bases along the tracts to genetic alteration, inducing both SBS and indels.

Base pair flexibility and charge localization map to sites of sequence changes

To elucidate elements of intrinsic DNA dynamics that may be responsible for the biases in SNV and insertion sites, we performed molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) simulations on model A[6], A[9], G[6] and G[9] duplex DNA fragments. We focused on water bridge coordination (Figure 4A), bp step flexibility, and for the G[6] and G[9], charge localization, as these properties are known to impact the susceptibility of DNA to base damage, repair and mutation. The fractions of one water coordination increased along the A[9] and A[6] structures in a 5′ to 3′ direction, irrespective of flanking sequence composition, in concert with a decrease in minor groove width (Figure 4B and Supplementary Figure S4A) as predicted (37). Vstep, a measure of bp structural fluctuation, displayed a prominent peak of ∼40 Å3deg3 at the 5′-TA-3′ step for both structures (Figure 4C and Supplementary Figure S4B), which together with low water occupancy points to 5′-TA-3′ being a preferred location for base modification and mutation. In the G[9] and G[6] structures water coordination involved mostly two-water bridges due to wide (∼14 Å) minor grooves (Figure 4Dand Supplementary Figure S4C), whereas flexibility was modest (∼20–22 Å3deg3, Figure 4E and Supplementary Figure S4D). Thus, bp dynamics are likely to impact mutations at A-tracts to a greater extent than at G-tracts. Guanine has the lowest ionization potential (IP) of all four bases and IP further decreases at guanine runs, rendering them targets for electron loss, charge localization, oxidation and eventually mutation (4,38). Because after electron loss the ensuing charge (hole) can migrate along the DNA double-helix and relocalize at specific guanines, we addressed whether the preferred sites of mutation along G-tracts, i.e. G2–3 and G5, would also be preferred sites for charge localization. The QM/MM determinations indicated that whereas for the short G[6] fragment the difference in the density-derived atomic partial charges (DDAPC) (i.e. the hole) localized most often (∼50%) to the first position (Figure 4F), for the long G[9] fragment charge localization shifted downstream (mostly to the second, but also to positions 6–7, Figure 4G). Importantly, the charge was found exclusively around the guanine rings (Figure 4H). Thus, the two main sites of sequence change along G-tracts, i.e. G2–3 and G5, coincide with positions where charge localization and hence one-electron oxidation reactions is predicted to occur most frequently. In summary, bp flexibility at A-tracts and charge transfer at G-tracts likely represent intrinsic DNA features underlying the bias in SNV and insertions at mononucleotide runs in human genomes.

Figure 4.

MD and QM/MM simulations. (A) Molecular modeling of one (left) and two (right) minor groove water bridge coordination. (B) Fraction of one-water bridge occupancy (left axis) at A[9] DNA sequences flanked 5′ and 3′ by a T (black circles), C (red circles) or G (green circles). Minor groove widths (right axis), as determined from intrastrand phosphate-to-phosphate distances. (C) Vstep for A[9] DNA sequences, determined as the product of the square root of the eigenvalues (λi) described by the six bp step parameters shift, slide, rise, tilt, roll and twist; i.e. Vstep=6i=1λi−−√. (D) Fraction of one- (black circles) and two-water (red circles) bridge occupancy (left axis) at G[9] DNA sequences. Minor groove widths (right axis), as assessed from intrastrand phosphate-to-phosphate distances. (E) Vstep for G9 DNA sequences. (F) Average charge redistribution (open circles and right axis) for G[6] DNA structures upon vertical ionization, examined by calculating the difference on the density-derived atomic partial charges (DDAPC) for the neutral and negatively charged states. Histogram of the number of instances (left axis) in which the largest charge redistribution occurred at a specific position along the G[6] structures. (G) DDAPC for G[9] DNA structures (open circles and right axis) and histogram of the number of instances (left axis) in which the largest charge redistribution occurred at a specific position. (H) VMD rendering of a G[9] DNA structure displaying hole localization at G2. Capped base pairs were removed for clarity.

Position and orientation along nucleosome core particles modulate sequence variation

DNA wrapped around histones in nucleosomes is subject to local deformation (39), which may impact mutation. Thus, we analyzed the 1KGP SNVs at A- and G-tracts predicted to overlap with well-positioned nucleosome core particles (NCPs) (16). In hg19, the percentage of tracts that overlap with NCPs decreased moderately from ∼90% at length of 4 to 81% and 71% for A- and G-tracts of length 13, respectively (Figure 5A), suggesting that mononucleotide runs are not depleted in NCPs in human genomes as previously proposed (40). A-tracts of lengths 4–8 base pairs displayed distinctive peaks along the NCP surface in phase with the helical repeat of DNA (10.5 bp) and with minor grooves facing toward the inner protein core (lengths 4–5) (16) (Figure 5B and Supplementary Figure S5A). A-tracts of length of 9–13 bp exhibited only half (six) the peaks evident for the shorter tracts. For the G-tracts, only small peaks with no clear minor groove-inward-facing regions were detected (Supplementary Figure S5B).

Figure 5.

Positioning along nucleosome core particles. (A) Percent of A-tract (open circles) and G-tract (closed circles) base pairs in hg19 overlapping with well-positioned NCP genomic coordinates as a function of tract length. (B) Counts of base pairs in hg19 A-tracts of length 5 overlapping with NCPs genomic regions as a function of distance from the histone octamer dyad axis. Minor groove-inward-facing regions (gray) were derived from the X-ray crystal structure of NCP147 (41). (C) Percent SNVs in the 1KGP dataset (left axis) at every bp along A-tracts of length 5 for tracts centered at maxima (black) and minima (gray) along NCPs (Figure 5B). Percent increase (right axis) of SNVs at minima relative to maxima (green). P-values for paired t-tests: 0.013 (*), 0.002 (**) and 4.7 × 10−6 (***). (D) Whisker plots of%SNVs (left axis) at A1 for A-tracts of length 5 centered at maxima and minima (black) along NCPs (Figure 5B). Percent difference (right axis) in the number of A-tracts of length 5 in hg19 preceded by C, T or G (red) between those centered at minima and those centered at maxima (Figure5B). (E) C-containing/G-containing ratios (see text) for G-tracts of length 5 in hg19 as a function of distance from the NCP dyad axis (black) and location of core histones (maroon and green). Peaks correspond to negative iSAT (i.e. tilt parameters multiplied by the corresponding sin θ) values (gray) (39). Ratios of%SNV at G1 (upshifted by 0.5 for clarity) between C-containing (5′-CCCCCG-3′ sequences on the hg19 forward strand) and G-containing (5′-CGGGGG-3′ sequences on the hg19 forward strand) (Figure 1A) CG[5] tracts mapping NCP Chip-seq genomic intervals (red) fitted by a non-parametric local regression (loess; sampling proportion, 0.100; polynomial degree, 3). (F) VMD rendering (top) of TATTT residues 34–38 (yellow) and the complementary AAATA residues 672–753 (pink) from the 1EQZ pdb nucleosomal crystal structure, corresponding to peak area from −40 to −36 in Figure 5E. The switch in G-tract (lengths of 5 and 7) orientation along NCPs (bottom) serves to position the C-containing strand on the outside (yellow) and, correspondingly, the G-containing strand on the inside (pink).

 To assess if tract-positioning along NCPs influences SNVs, we selected A-tracts of lengths 5, 7 and 9 bp and G-tracts of lengths 5 and 7 bp whose central positions coincided with either the maxima or minima (41) (Figure 5B and Supplementary Figure S5A and B) and conducted pair-wiset-tests (330 total) between permutations of ‘categories’, including ‘tracts centered at maxima versus minima’, ‘position along the tracts’, ‘flanking sequence composition’, ‘specific NCP locations’ and ‘tract orientation’. For A-tracts, 79/207 (38%) significant pairs were found, 68 (86%) of which were related to differences between tracts centered at maxima versus minima, with a preponderance (63%) of tests displaying increased %SNVs at minima (Supplementary Figure S5C and E). For example, %SNVs at length 5 bp were greater at minima than at maxima at each position along the A-tracts (Figure 5C). A→C substitutions at A1 were more abundant at maxima than at minima (mean ± SD, 18.7 ± 0.7% at max and 17.6 ± 0.8% at min; P-value 0.001), whereas A→T substitutions at the same position displayed the opposite trend (mean ± SD, 18.4 ± 0.5% at max and 19.8 ± 1.1% at min; P-value 0.0005) (Figure 5D). A-tracts of length 7 also exhibited a similar pattern at A7 (Supplementary Figure S5H). The percentages of CA[5] and A[7]C tracts in hg19 centered at maxima were greater than at minima and the reverse was observed for the TA[5] and A[7T] tracts (Figure 5D and Supplementary Figure S5H). Thus, we conclude that positioning along the NCP surface of both the double-helical grooves and junctions with flanking base pairs influence SNVs along A-tracts. However, this influence is complex and for the most part, difficult to predict.

For G-tracts, most pairwise comparisons (18/34, 53%) indicated SNV variation according to sequence orientation (Supplementary Figure S5F and G). In hg19, the ratio of the numbers of G-tracts of lengths 5 and 7 for which the C-containing strand coincided with the forward sequence (downstream example sequence in Figure 1A) to the numbers of G-tracts for which the G-containing strand coincided with the forward sequence (upstream example sequence in Figure 1A) (C-containing/G-containing ratios) displayed a prominent 10.5-bp oscillation in phase with iSAT (Figure 5E), a measure of ‘inside’ and ‘outside’ bases, according to the bp step tilt parameter (39). Analysis of the helical path of a 146-bp DNA fragment wrapped around histones showed that the oscillation in the C-containing/G-containing ratios corresponds to a preference for guanine bases to face the protein core (Figure 5F). We analyzed the subset of G-tracts preceded by a 5′ C (i.e. CG[5]) to assess whether SNVs at G1, the position known to be mutable due to CpG methylation also oscillated with the C-containing/G-containing ratios. Oscillation in SNV-C-containing/SNV-G-containing values was evident, with peaks aligning to the hg19 troughs (Figure 5E) implying that the cytosines facing the protein surface harbor more variants than those facing away. We conclude that A- and G-tracts display preferential positioning (the former) and orientation (the latter) along NCPs, which in turn modulate the rate of sequence variation.

Mutations associated with human disease

Knowing that the first and last As of long A-tracts and G2–3 in G-tracts are the major sites of SNV in the human population, we addressed whether these features are also discernible in mutated mononucleotide tracts associated with human genetic disease. We collected 9,450,456 unique SBSs (both SBSs and SNVs refer to single base changes) from sequenced cancer genomes and normalized the percent mutations along A- and G-tracts to enable a direct comparison with the 1KGP dataset. For A-tracts (Figure 6A and Supplementary Figure S6A), SBSs displayed the same trend as the 1KGP data (Figure 2A) with respect to the bell-shape increase in mutations at A1 and An and the mutation spectra, although the susceptibility to mutation as a function of tract length attained greater values (6.36% for length 11 in cancer versus 4.15% for length 9 in the 1KGP datasets at A1). The first and last 3 bp also harbored more SBSs than in the 1KGP dataset for tracts >7 bp, a feature that we found to be due exclusively to a large cancer dataset (42) containing high-level microsatellite instability (MSI) samples (Supplementary Figure S6B and C), which are known to result from mismatch-repair deficiency (15). Thus, A-tracts display similar patterns of base substitution between the germline and somatic cancer tissues. For G-tracts, mutation spectra were characterized by G→T transversions at tract lengths >7, particularly at G1, the most frequently mutated position for tracts lengths up to 11 bp (Figure 6B and Supplementary Figure S6D). This trend persisted even when the high rates of methylation-mediated deamination mutations at the CG dinucleotide were removed (Supplementary Figure S6E). Thus, mutation patterns in cancer genomes contrast with those observed in the germline, both with respect to the most mutable position (G1 versus G2–3) and the types of base substitution (G→T in cancer genomes versus G→T and G→C in the germline).

Figure 6.

Mutation patterns in cancer genomes. (A) Mutation spectra for SBSs at A-tracts. Percent values were obtained by dividing the total number of SBSs at each position by the number of tracts in hg19 and then multiplying by 3.2516 to equalize the percentage of A-tracts of length 4 between the cancer genomes and the 1KGP datasets. (B) Mutation spectra for SBSs at G-tracts in cancer genomes. Percent values were obtained as in (A) using a multiplication factor of 3.7419. (C) Normalized fractions of A-tracts (closed circles) and G-tracts (open circles) displaying +/−1 bp slippage, obtained by dividing the number of events by both the number of tracts in hg19 and tract length. (D) Indels at A-tracts, calculated as described in Figure 3C. (E) Indels at G-tracts, calculated as described in Figure3C. (F) Heatmap representation of insertions along G-tracts, as described in Figure 3E.

 With respect to slippage, the fractions for A-tracts elicited an excess at lengths 9 and 10 bp relative to the 1KGP dataset, which was also due to the MSI-containing dataset. For G-tracts, the fractions peaked at length 8, as for the 1KGP dataset (Figures 3A and 6C), implying that the propensity to undergo slippage is indistinguishable between the germline and soma. Indels were also more abundant at flanking base pairs than along the tracts (Figure 6D and E), particularly for G-tracts of length >7, similar to the 1KGP dataset (Figure 3C and D). Detailed analyses of insertions revealed that both G1 and the preceding position were the most significant sites of mutation (F-values up to 0.08 at G1 for tracts of length 8) (Figure 6F). Thus, the 5′ end of long G-tracts is the most susceptible site for both SBSs and insertions in cancer genomes, in contrast to the germline where these occur within the runs, typically at G2–3.

We also extracted the mutated A- and G-tracts from the Human Gene Mutation Database (HGMD), a collection of >150,000 germline gene mutations associated with human inherited disease. A total of 1519 genes were mutated at A- or G-tracts out of a total of 3972 (38%); 3480 SBSs and 2866 slippage events were noted within these tracts, 85 and 46% of which were predicted to be disease-causing, respectively (Figure 7A and Supplementary Table S1). Ranking genes by the number of literature reports indicated that among the top 10 entries three were associated with cancer (BRCA1, BRCA2 and APC), two with hemophilia (F8 and F9), four with debilitating lesions of the skin (COL71A), muscle (DMD), lung (CFTR) and kidney (PKD1), with one causing hypercholesterolemia (LDLR) (Figure 7B). Thus, mutations within A- and G-tracts carry a high social burden by contributing to some of the most common human pathological conditions.

Figure 7.

Mutation patterns in HGMD and model for sequence context-dependent changes. (A) Number of germline SBSs and slippage events (Slip.) at A- and G-tracts in HGMD. Gene alterations were classified as disease-causing mutation (DM), likely disease-causing mutation (DM?), disease-associated and putatively functional polymorphism (DFP), disease-associated polymorphism with additional supporting functional evidence (DP) and invitro/laboratory orinvivo functional polymorphism (FP). Codon changes (SIFT predictor) were classified as damaging (d), null (n), tolerated (t) and low-confidence prediction (l). (B) The 10 most commonly reported genes in HGMD with mutations at A- and G-tracts. Various mutated tracts were generally reported for the same gene in different reports. (C) Mutation spectra for SBSs at A- (left) and G-tracts (right) in HGMD. Percent values were obtained by dividing the total number of SBSs at each position by the number of tracts in hg19 exons. A|G→T (black), A|G→C (red), A→G (green), G→A (cyan). (D) Normalized fractions of A-tracts (closed circles) and G-tracts (open circles) displaying +/−1 bp slippage, obtained by dividing the total number of events by the number of tracts in hg19 exons and by tract length. (E) Model for sequence context-dependent changes at A-tracts (left) and G-tracts (right). *, site of base modification.

 For both A- and G-tracts, SBSs occurred mostly at tract lengths of 4–7, with patterns more similar to those in the 1KGP than in the cancer datasets, both with respect to the location of the most mutable positions (first and last As and first/second Gs) and the types of base substitution (A→T and G→H) (Figure 7C and Supplementary Figure S6F). Likewise, slippage events peaked at tract lengths of 7–9 as observed in the 1KGP dataset (Figure 7D). In summary, the patterns of both SBSs and slippage in the HGMD dataset followed the trend observed in the 1KGP dataset, suggesting that germline variants at mononucleotide repeats leading to either population variation or human inherited disease may have arisen through similar mechanisms.
DISCUSSION

Why are specific A:T and G:C base pairs within A- and G-tracts more susceptible to sequence changes than their identical neighbors? For A-tracts, bp flexibility may play a role. Chemical damage to DNA, such as by hydroxyl radicals has been shown to be proportional to the geometrical solvent-accessible surface of the atomic groups, which increases with DNA flexibility (43). Along A-tracts flexibility is restricted, but it is high at both the 5′ and 3′ junctions. Thus, the fact that the highest rates of mutation coincide with the highest degree of flexibility at the 5′-TA-3′ bp step is consistent with the view that this position may be susceptible to DNA damage as a result of flexibility. Other sources of DNA dynamics are also likely to be relevant, such as sugar flexibility at the junctions, which increases with tract length (44). Chemical modification at these junctions may then lead to base substitution and indels, the latter as a result of strand breaks.

With respect to SNV mutation spectra, these were found mostly in the direction of flanking base composition above a length of 7–8 bp. We interpret this behavior in terms of DNA slippage along A-tracts when attempts are made during translesion synthesis (TLS) to bypass a damaged site (Figure 7Ei). Two scenarios may be considered to account for A→T transitions at A1. In the first, the last tract-template base would loop out into the polymerase active site permitting base-pairing and strand elongation (Figure 7Eii) using the tract-flanking base as a template (34,4546). In the second (Figure 7Eiii), slippage would occur behind the polymerase, prompting extension past the newly created A*:T mispair generated by primer/template misalignment. Either pathway would yield a common intermediate (Figure 7Eiv) that contains the base complementary to the junction across from the damaged site upon slippage resolution (34). Following DNA synthesis (S) and/or repair (R) (Figure 7Ev and vi), this mispair will generate a base change that is always identical to the tract-flanking base.

For G-tracts, the high rates of G→T transversions at G1 in cancer genomes are also consistent with preferred chemical attack at this site due to high flexibility (Figure 7F top). Direct chemical attack at a guanine is known to result in stable products, such as 8-oxo-G and Fapy-G, both of which are known to yield G→T transversions (4750). Thus, G1 may be the most susceptible site for such reactions for G-tracts of lengths ≥7 (Figure 7Fright), which in cancer genomes would become a mutation hotspot. In the germline, SNVs peaked inside G-tract base pairs, while mutational spectra were insensitive to flanking base composition; these events are inconsistent with a role for template misalignment and slippage as noted for A-tracts. Rather, the correspondence between hotspot mutations at G2–3 and G5 and the QM/MM simulations suggest a role for charge transfer. A large body of work during the past 20 years using computational, theoretical chemistry and biophysical techniques on short oligonucleotides, has shown that guanine is the most easily oxidizable base in DNA and that indeed a guanine radical cation can be generated through long-range hole transfer from an oxidant via one-electron oxidation mechanisms (5155). GGG triplets were found to act as the most effective traps in hole transfer by both experimental and theoretical work (5659), demonstrating that the resulting guanine radical cation (or its neutral deprotonated form) became rather delocalized, but it preferentially centered at the first and second G. These well-established patterns of chemical reactivity are consistent with our experimental observation of high mutation frequencies at G1 for short G-tracts and the results from QM/MM simulations on G6. For longer tracts, the downstream shift in mutation hotspots, i.e., G2–3 and G5, also correlate well with the charge localization predicted from QM/MM simulations, which explicitly included solvent effects and structural fluctuations. Thus, in conjunction with the constrained density functional theory (60), both the neutral and oxidized forms of a guanine nucleobase can be reliably constructed to infer the accurate determination of mutational patterns of mononucleotide repeats in human genomic DNA.

The compact organization of the sperm genome (61), and presumably low levels of oxidative stress in the germline, may enable guanine oxidization through one-electron oxidation reactions rather than by direct chemical attack, thereby favoring the formation of radical cations. A charge injected at G1 by electron loss would then migrate to neighboring guanines and localize at sites of low IP, such as G2 (Figure 7F left). Guanine radical cations are known to readily undergo further chemical modification leading to products such as 8-oxo-G, oxazolone, imidazolone, guanidinohydantoin, and spiroiminodyhydantoin (62) (M in Figure 7F), to yield G→T, G→C and G→A substitutions (4,63). Our model is in line with recent observations in which mutations at guanines within short G-runs (1–4 bp) correlate with sequence-dependent IPs at the target guanine in cancer genomes (9). Interestingly, these correlations were not observed in the germline (9). We interpret these composite observations as follows. The IP values for G-runs have been shown to decrease asymptotically with tract length, although the absolute values vary according to the methods and assumptions used (we obtained a value of 5.43 eV for both G[6] and G[9]) (64,65). We suggest that short G-runs with high IPs undergo one-electron oxidation reactions in the oxidative environment of cancer cells but would be refractory to such a mechanism in the germline (Figure 7Fright yellow and left white sectors). As length increases and IP values fall, G-runs would be attacked directly by oxidants abundant in tumor cells (Figure 7F orange sector), whereas oxidation will be limited to electron loss in the germline environment (Figure 7F left yellow sector).

These models (template misalignment for A-tracts and charge transfer for G-tracts) suggest a more complex scenario for mechanisms underlying mononucleotide repeat polymorphism in the human population than recently proposed (13), in which nucleotide misincorporation by error-prone polymerases is proposed as a primary source of mutations at both A- and G-tracts. As already stated, the directionality of SNVs toward tract-flanking bases in A-tracts and the hotspot mutations at G2–3, supports multiple and distinct mechanisms of base substitution at mononucleotide repeats.

Our analyses highlight additional information, including the lack of mutations in the direction of tract-base composition for base pairs flanking long tracts, the association with gene expression and the preference of guanines for the inner NCP surface, and extend prior observations (12) such as the bell-shape character of base substitution and slippage, whose mechanisms remain to be fully clarified. Finally, we document the contribution of mononucleotide mutagenesis to key aspects of human pathology beyond the well-established MSI instability in cancer (15), including hemophilia and tissue degeneration. Our collective work supports the conclusion that as the human genome undergoes evolutionary diversification and along the way suffers disease-associated mutations, oxidation reactions including charge transfer may play a prominent role.

SUPPLEMENTARY DATA

Supplementary Data are available at NAR Online.

 

 

Mutation analyses and prenatal diagnosis in families of X-linked severe combined immunodeficiency caused by IL2Rγ gene novel mutation

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Genet. Mol. Res. 14 (2): 6164 – 6172   DOI: 10.4238/2015.June.9.2
Severe combined immunodeficiency diseases (SCIDs) are a group of primary immunodeficiency diseases characterized by a severe lack of T cells (or T cell dysfunction) caused by various gene abnormalities and accompanied by B cell dysfunction (WHO, 1992; Buckley et al., 1997). The incidence rates in infants were 1/75,000-1/10,0000 (WHO, 1992), but no morbidity statistics are available in China. The 2 genetic modes of SCID include X-linked recessive and autosomal recessive genetic inheritance. X-linked severe combined immunodeficiency (X-SCID) is the most common form, accounting for 50-60% of SCID cases (Noguchi et al., 1993). Immune system abnormalities in patients with X-SCID include T-B+NK-, in which T cells (CD3+) and natural killer (NK) cells (CD16+/CD56+) are absent or significantly reduced, and the number of B cells (CD19+) is normal or increased, causing reduced immunoglobulin production and class switching disorder (Buckley, 2004; Fischer et al., 2005). The IL- 2Rg gene mutation has been confirmed to be a major cause of X-SCID (Noguchi et al., 1993). In recent years, great progress has been made in understanding the pathogenesis of primary immunodeficiency disease and its application in clinical treatment, particularly regarding the development of critical care medicine and immune reconstruction technology. With timely control of infection and early bone marrow or stem cell transplantation, X-SCID patients can be treated, prolonging survival time. Therefore, early diagnosis of X-SCID is very important for patient treatment. Gene diagnosis has become a better early diagnosis or differential diagnosis method. In addition, familial X-SCID brings a great psychological burden to the relatives of patients. Ordinary chromosome analysis and immunological evaluation cannot be used for female carrier identification and fetal diagnosis, and gene diagnosis is the most effective method of carrier detection and prenatal diagnosis. In this study, we detected mutations in 2 families with X-SCID and identified 2 novel mutations, confirming the X-SCID pedigrees. Prenatal diagnosis was performed for the pregnant fetus in the mother of one of the probands based on gene diagnosis. Female individuals in this family were subjected to carrier detection.
IL2Rg gene mutation test Direct sequencing of 1-8 exons and the flanking region of the IL2Rg gene by PCR in family 1 showed that the 3rd exon of the proband contained the c.361-363delGAG heterozygous deletion mutation, which led to deletion of the 121st amino acid glutamate (p.E121del) in its coding product. There were no sequence variations in other coding regions or in the shear zone. The proband’s mother carried the same heterozygous mutation, while his father did not carry the mutation site (Figure 2a, b, c). This mutation was not observed in any cases of the control group, and this family was identified as an X-SCID family. The c.510-511insGAACT insertion heterozygous mutation was present in the 4th exon of the proband’s mother in family 2. This mutation was a 5-base repeat of GAACT, resulting in a change in amino acid 173 from tryptophan into a stop codon (p.W173X). While there were no sequence variations in other coding regions or in the shear zone, the patient’s father did not carry the mutation (see Figure 2d, e). We did not find this mutation in the healthy control group. We presumed that the 4th exon of the deceased child in family 2 contained the c.510-511insGAACT insertion mutation, leading to X-SCID symptoms, and thus we speculated that this family was an X-SCID pedigree. Prenatal diagnosis We verified the chorionic villus status of the fetus in family 1 using the PowerPlex 16 HS System kit. The results of prenatal diagnosis showed that the fetal tissue contained no maternal contamination and that this fetus was female. The results of prenatal diagnosis showed that there was no c.361-363delGAG (p.E121del) heterozygous mutation in the female fetus of family 1.
Figure 2. Sequencing graph of IL2Rg gene in 2 pedigrees with X-chain severe combined immunodeficiency. a.-c. Family 1. a. Normal control (rectangle indicates 3 edentulous bases of this patient). b. Proband carrying the c.361- 363delGAG (p.E121del) mutation (arrow indicates deletion of fragment connection sites). c. The proband’s mother contained a c.361-363delGAG (p.E121del) heterozygous mutation (arrow). d.-e. Family 2. d. The proband’s mother carried the c.510-511insGAACT (p.W173X) heterozygous mutation (arrow indicates that the reverse sequencing graph was positive). e. Normal control (rectangular box indicates 2 normal copies of GAACT (the mutation fragment was 3 copies). Carrier detection results For the c.361-363delGAG (p.E121del) site, the gene analysis results of the female individual in family 1 showed that I2 (proband’s grandmother) was a heterozygous carrier and that II3 (proband’s aunt) was a non-carrier and had no mutations.
IL-2 can combine with the IL-2 receptor (IL-2R) of the immune cell membrane. IL-2R is composed of 3 subunits, including the IL-2Ra chain (CD25), IL-2Rb chain (CD122), and IL- 2Rg chain (CD132). IL-2Rg functional units in common with IL-4, IL-7, IL-9, IL-15, IL-21, and other cytokine receptors, and these regions are referred to as the total chain (Li et al., 2000). The IL-2Rg chain can maintain the integrity of the IL-2R complex and is required for the internalization of the IL-2/IL-2R complex; it is also the link that contacts the cell membrane surface factor region and downstream cell signal transduction molecules. Therefore, the integrity of the IL-2Rg chain is vital for the immune function of an organism (Malka et al., 2008; Shi et al., 2009).
Mutations in the IL2Rg gene, which encodes IL-2Rg, were identified to be a major cause of X-SCID in 1993 (Noguchi et al., 1993). The IL2Rg gene is located on chromosome X q21.3-22, is 37.5 kb length, and contains 8 exons, which encode 369 IL-2Rg amino acids. The IL2Rg chain exhibits varying structural regions, such as the signal peptide [amino acids (AA) 1-22], extracellular domain (AA 23-262), transmembrane region (AA 263-283), and intracellular region (AA 284-369). The WSXWS motif is located in the extracellular region (AA 237-241), while Box 1 is located in the intracellular region (AA 286-294).
By the end of 2013, the Human Gene Mutation Database contained a total of 200 mutations in the IL2Rg gene (HGMD Professional 2013.4). The most common mutation types in the IL2Rg gene were the missense or nonsense mutations, which result from single base changes. A total of 100 missense or nonsense mutations have been identified, followed by insertion or deletion mutations in a total of 50 species. The 3rd most common type of mutations includes shear mutations in approximately 30 species. Eight exons contained mutations, and mutations in 3rd or 4th exons were the highest, accounting for a total mutation rate of 43% (86/200). According to the X-SCID gene database (IL2RGbase) (http://research.nhgri. nih.gov/scid/), the gene mutations in IL2Rg mainly occurred in the extracellular region of the IL2Rg chain (Fugmann et al., 1998). Zhang et al. (2013) reported that the IL2Rg gene mutations in 10 patients with X-SCID in China were located in the extracellular region. Two mutations reported in our study were also located in the extracellular region. The mutation of IL2Rg gene in family 1 was a codon mutation in the 3rd exon, resulting in a 3-base deletion. The c.361-363delGAG (p.E121del) mutation was located in the extracellular area of the IL- 2Rg subunit, and we inferred that the 121 glutamate deletion caused by the mutation would lead to changes in the structure of the peptide chain, affecting signal transmission and resulting in serious symptoms. The mutation of family 2 was a GAACT repeat of ILR2g gene; this repeat of 5 bases resulted in 173 codon changes from tryptophan into a stop codon. Generation of the peptide chain with the mutation lacked 196 amino acids compared to the normal chain, including the intracellular, transmembrane, and some extracellular regions, directly affecting the structure and function of receptors and causing disease. No studies have been reported regarding these 2 mutations. We combined with the mutation characteristics and clinical manifestations and diagnosed family 1 as X-SCID pedigrees. Although the patient in family 2 was deceased, it can be speculated that the 2 deceased patients in family 2 were X-SCID pedigrees caused by c.510-511insGAACT (W173X).
Prenatal diagnosis can accurately identify fetal situations and be used to avoid birth defects, which can also ease the anxiety of the pregnant mother. Gene diagnosis for pedigrees of patients based on DNA samples has advanced recently, particularly with the application of high-throughput sequencing technology (Alsina et al., 2013). We can now perform gene analysis for varied clinical infectious diseases for differential diagnosis. However, the effectiveness of prenatal diagnosis for pedigrees in which the proband is dead remains unclear. Because the gene mutations in the proband is unknown in these cases, the patient’s situation was only inferred by his mother’s genotypes. However, we considered that for the deceased, if we can define the mother was a pathogenic gene carrier, even if the proband is not X-SCID, the woman also has a risk of having X-SCID children and this pedigree may be X-linked recessive inheritance. Prenatal diagnosis may provide a choice for preventing the birth of patients in these families in the premise of informed consent.
Gene diagnosis of IL2Rg can also be used for carrier detection of suspected females in the family.
In the present study, we performed carrier detection of the patient’s grandmother and aunt in family 1 and determined that the patient’s pathogenic mutations were from his grandmother. His aunt did not inherit the pathogenic gene, and thus she was a non-carrier and her fertility will not be affected. In this study, we used direct sequencing of PCR products and identified IL2Rg gene mutations in 2 pedigrees with X-SCID. We found 2 unreported mutations in the IL2Rg gene, and prenatal diagnosis and carrier detection were conducted in 1 X-SCID family. Because the incidence rate of X-SCID is extremely low, it is difficult to promote the widespread use and application of genetic diagnosis. However, this study may provide some implications for the diagnosis of infants with immunodeficiency, and gene diagnosis techniques such as conventional or high-throughput sequencing should be used as soon as possible during pregnancy, which can be used to guide treatment. This method can also provide reliable prenatal diagnosis and carrier detection service for these families.
MEF2A gene mutations and susceptibility to coronary artery disease in the Chinese population
J. Li1 , H.-X. Chen2 , J.-G. Yang3 , W. Li3 , R. Du3 and L. Tian3       DOI http://dx.doi.org/10.4238/2014.October.20.15
Coronary artery disease (CAD) has high morbidity and mortality rates worldwide. Thus, the pathogenesis of CAD has long been the focus of medical studies. Myocyte enhancer factor 2A (MEF2A) was first discovered as a CAD-related gene by Wang (2005) and Wang et al. (2003, 2005). Three mutation points in exon 7 of MEF2A were subsequently identified by Bhagavatula et al. (2004); however, Altshuler and Hirschhorn (2005) and Weng et al. (2005) predicted that the MEF2A gene lacked mutations. Zhou et al. (2006a,b) analyzed the mutations and polymorphisms in exons 7 and 11 of the MEF2A gene in the Han population in Beijing, and various rare mutations were found in exon 11 rather than in exon 7. The clinical significance of specific 21-bp deletions in MEF2A was also explored, and previous studies have shown mixed results. In this study, polymerase chain reaction-singlestrand conformation polymorphism (PCR-SSCP) and DNA sequencing were used to detect exon 11 of the MEF2A gene in samples collected from 210 CAD patients and 190 healthy controls and to investigate the function of the MEF2A gene in CAD pathogenesis and their correlation.
CAD, a common disease in China, is induced by multiple factors, such as genetics, the environment, and lifestyle. Thus, a multi-faceted approach is necessary in the study of CAD pathogenesis, particularly in molecular biology research, which is important for developing comprehensive treatment of CAD based on gene therapy. The MEF2A gene was first identified as a CAD-related gene through linkage analysis of a large family with CAD (9 of 13 patients developed MI) in 2003.
In this study, we found the following mutations: 1) codon 451G/T (147191) heterozygous or homozygous mutation; 2) loss of 1 (Q), 2 (QQ), 3 (QQP), 6 (425QQQQQQ430), and 7 (424QQQQQQQ430) amino acids (147108-147131); and 3) codon 435G/A (147143) heterozygous mutation. Among these mutations, the synonymous mutation at locus 147191 was confirmed by reference to the National Center for Biotechnology Information (NCBI) database to be a single nucleotide polymorphism, which was also demonstrated in our study by the extensive presence of this polymorphism in healthy controls. However, the heterozygous mutation at locus 147143 was only found in the genomes of CAD patients, and was therefore identified as a mutation.
Given that MEF2A is a CAD-related gene, the results of various studies are controversial among several countries. Weng et al. (2005) screened gene mutations in exon 11 of the MEF2A gene from 300 CAD patients and 1500 healthy controls. They hypothesized that the changes in 5-12 CAG repeats are genetic polymorphisms and that the 21-base deletion in exon 11 of the MEF2A gene did not induce autosomal dominant genetic CAD. Gonzalez et al. (2006) suggested that the CAG repeat polymorphism was independent of MI susceptibility in Spanish patients. Kajimoto et al. (2005) reported that the CAG repeat sequence was not correlated with MI susceptibility in Japanese patients. Horan et al. (2006) also found that the CAG repeat sequence was not associated with the susceptibility to early-onset familial CAD in an Irish population. Hsu et al. (2010) identified no correlation between the CAG repeat sequence and CAD susceptibility in the Taiwanese population. Dai et al. (2010) found that the structural change in exon 11 was not related to CAD in the Chinese Han population. Lieb et al. (2008) and Guella et al. (2009) hypothesized that MEF2A was independent of CAD. However, Yuan et al. (2006) and Han et al. (2007) suggested that the CAG repeat sequence was correlated with CAD because 9 CAG repeats was an independent predictor of CAD. Elhawari et al. (2010) and Maiolino et al. (2011) suggested that MEF2A is a susceptibility gene for CAD. Dai et al. (2013) showed that mutations in exon 12 are associated with the early onset of CAD in the Chinese population. Liu et al. (2012) failed to demonstrate a correlation between the CAG repeat sequence and CAD through case-control analysis, systematic review, and meta-analysis, but found that the 21- base deletion in exon 11 was strongly associated with CAD, and that genetic variations in MEF2A may be a relatively rare, but specific, pathogenic gene for CAD/MI. Kajimoto et al. (2005) reported 4-15 CAG repeats. However, only 4-11 CAG repeats were observed in our study, possibly because of genetic differences in patients in this study. Eleven CAG repeats were observed in most samples from the control group, and the proportion of 10, 9, and 8 repeats exceeded 1%. The heterozygous mutation at 147143, as well as the 4 and 5 CAG repeats, was only observed in CAD patients. Thus, we speculated that the CAG repeat sequence is correlated with CAD susceptibility, and the presence of 4 or 5 repeats may be a risk factor for CAD, which was inconsistent with the results obtained by Han et al. (2007). The inconsistency in these results may be explained by the differences in subjects and sample sizes among studies.
Impact of glucocerebrosidase mutations on motor and nonmotor complications in Parkinson’s disease

Homozygous and compound heterozygous mutations in GBA encoding glucocerebrosidase lead to Gaucher disease (GD). A link between heterozygous GBAmutations and Parkinson’s disease (PD) has been suggested ( Bembi et al., 2003,Goker-Alpan et al., 2004, Halperin et al., 2006, Machaczka et al., 1999, Neudorfer et al., 1996, Tayebi et al., 2001 and Tayebi et al., 2003). In 2009, a 16-center worldwide analysis of GBA revealed that heterozygous GBA mutation carriers have a strong risk of PD ( Sidransky et al., 2009).

In addition, heterozygote GBA mutations not only carry a risk for PD development but also the possibility of some risk burden on the progression of PD clinical course. In cross-sectional analyses of GBA mutations in PD patients, earlier disease onset, increased cognitive impairment, a greater family history of PD, and more frequent pain were reported in patients with mutations, compared with no mutations ( Chahine et al., 2013,Clark et al., 2007, Gan-Or et al., 2008, Kresojevic et al., 2015, Lwin et al., 2004, Malec-Litwinowicz et al., 2014, Mitsui et al., 2009, Neumann et al., 2009, Nichols et al., 2009,Seto-Salvia et al., 2012, Sidransky et al., 2009, Swan and Saunders-Pullman, 2013 and Wang et al., 2012). Recently, a few prospective studies have investigated clinical features of PD with GBA and showed a more rapid progression of motor impairment and cognitive decline in GBA mutation cases than in PD controls ( Beavan et al., 2015, Brockmann et al., 2015 and Winder-Rhodes et al., 2013). However, in terms of motor complications such as wearing-off and dyskinesia, no studies exist in the longitudinal course of PD with GBA mutations.

Here, we conducted a multicenter retrospective cohort analysis, and the data were investigated by survival time analysis to show the impact of GBA mutations on PD clinical course. We also investigated regional cerebral blood flow (rCBF) and cardiac sympathetic nerve degeneration of subjects with GBA mutations, compared with matched PD controls.

3.1. Subjects

Among the 224 eligible PD patients (the subjects were not related to each other), 9 subjects were excluded from the analysis (4 due to multiple system atrophy findings on subsequent brain MRI and 5 because of insufficient clinical information). Therefore, 215 PD patients [female, 52.1%; age, 66.7 ± 10.8 (mean ± standard deviation)] were analyzed. For non-PD healthy controls, 126 patients’ spouses (female, 58.7%; age, 67.3 ± 10.3) without a family history of PD or GD were enrolled.

3.2. GBA mutations and risk ratios for PD

In the PD subjects, we identified 10 nonsynonymous and 2 synonymous GBA variants. Within the nonsynonymous variants, 7 mutations were previously reported in GD [R120W, L444P-A456P-V460 (RecNciI), L444P, D409H, A384D, D380N, and444L(1447-1466 del 20, insTG)] as GD-associated mutations. Three nonsynonymous mutations have never been reported in GD patients [I(-20)V, I489V, and there was one novel mutation (Y11H)].

GD-associated GBA mutations were found in 19 of the 215 (8.8%) PD patients but none in the healthy controls. The risk of PD development relative to these GD-associated mutations was estimated as an OR of 25.1 [95% confidence interval (CI), 1.50–420,p = 0.0001] with 0-cell correction. The nonsynonymous mutations that were not reported in GD patients had no association with PD development (p = 0.506; OR, 1.3; 95% CI, 0.7–2.6) ( Table 1). Four subjects had double mutations. For subsequent analyses, 2 subjects with double mutations of I (-20)V and K466K were adopted to the group of mutations unreported in GD, and 2 subjects with double mutations of R120W and I(-20)V, and of R120W and L336L were adopted to the group of GD-associated mutations.

Table 1.Frequency of glucocerebrosidase gene allele in Parkinson’s disease patients and controls

Allele name PD (n = 215) Controls (n = 126) p Odds ratio (95% CI)
GD-associated mutations
 R120W 7a 0 0.050 9.1 (0.5–160.8)
 RecNciI (L444P-A456P-V460) 4 0
 L444P 4 0
 D409H 1 0
 A384D 1 0
 D380N 1 0
444L(1447-1466 del 20, insTG) 1 0
 Subtotal, n (%) 19 (8.8%) 0 (0%) <0.001 25.1 (1.5–419.8)b
Nonsynonymous mutations not reported in GD
 I(-20)V 27a 13 0.603 1.3 (0.6–2.5)
 I489V 3 0
 Y11Hc 0 1
 Subtotal, n (%) 30 (14.0%) 14 (11.1%) 0.506 1.3 (0.7–2.6)
Synonymous, n
 K466K 2a 1
 L336L 1a 0
Allele names refer to the processed protein (excluding the 39-residue signal peptide).

Key: CI, confidence interval; GD, Gaucher disease; PD, Parkinson’s disease.

a Four subjects had double mutations; 2 of I(-20)V and K466K, 1 of I(-20)V and R120W, and 1 of R120W and L336L.
b Odds ratio was calculated by adding 0.5 to each value.
c Novel mutation.
3.3. Clinical features of PD patients by GBA mutation groups

The clinical features of PD patients with GD-associated mutations, those with mutations unreported in GD, and those without mutations are shown in Table 2. In the GD-associated mutation group, females, those with a family history and those with dementia (DSM IV) were significantly more frequent than those in the no-mutation group (p = 0.047, 0.012, and 0.020, respectively). The age of PD onset was lower in patients with GD-associated mutations (55.2 ± 9.9 years ± standard deviation), compared with those without mutations (59.3 ± 11.5), although the statistical difference was not significant. There were no differences in clinical manifestations between subjects with mutations unreported in GD and those without mutations, except for dopamine agonist dosage (p = 0.026) ( Table 2).

Table 2.Epidemiological and clinical features of PD patients with Gaucher disease–associated GBA mutations, those with mutations previously unreported in GD and those without mutations

Variables Total n = 215 Mutation (-) GD-associated mutations


Mutations unreported in GD


167 19a pb 29c pd
Sex Female, n (%) 83 (49.7) 14 (73.7) 0.047 15 (51.7) ns
Age Mean (SD) 67.0 (10.8) 62.2 (10.7) 0.063e 67.5 (11.2) nsf
Disease duration (y) Mean (SD) 7.7 (5.5) 6.9 (4.6) nsf 7.2 (4.9) nsf
Onset age Mean (SD) 59.3 (11.5) 55.2 (9.9) ns 60.3 (11.8) ns
Family history Yes, n (%) 17 (11.0)g 6 (31.6) 0.012 0 (0.0) ns
Dementia (DSM-IV) Yes, n (%) 29 (17.4) 9 (47.4) 0.020 5 (17.2) ns
MMSE Mean (SD) 25.8 (5.4)h 23.3 (7.7) nsf 27.0 (3.4)i nsf
Onset symptom (tremor vs. others) Tremor, n (%) 78 (46.8) 9 (47.4) ns 15 (51.7) ns
Modified H-Y on (<3 vs. ≥3) ≥3, n (%) 82 (49.1) 14 (73.7) 0.042 16 (55.2) ns
UPDRS part 3 Mean (SD) 23.6 (12.2)j 28.5 (13.8) nsf 21.9 (8.7) nsf
Wearing off Yes, n (%) 70 (41.9) 9 (47.4) ns 13 (44.8) ns
Dyskinesia Yes, n (%) 49 (29.3) 8 (42.1) ns 8 (27.6) ns
Mood disorder Yes, n (%) 43 (25.7) 8 (42.1) ns 7 (24.1) ns
Orthostatic hypotension symptom Yes, n (%) 21 (12.6) 5 (26.3) ns 7 (24.1) ns
Psychosis history Yes, n (%) 59 (35.3) 10 (52.6) ns 7 (24.1) ns
ICD history Yes, n (%) 8 (4.8) 1 (5.3) ns 1 (3.4) ns
Stereotactic brain surgery for PD Yes, n (%) 4 (2.4) 0 (0.0) ns 0 (0.0) ns
Agonist LED mg/d Mean (SD) 92.8 (114.2) 72.1 (137.7) nse 163.7 (155.6) 0.026e
Levodopa LED mg/d Mean (SD) 400.7 (184.2) 456.7 (206.9) nsf 369.2 (230.3) nse
Total LED mg/d Mean (SD) 496.4 (233.7) 537.9 (258.9) nsf 525.7 (287.4) nsf
Categorical data were examined by Fisher’s exact test.

Key: DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; GBA, glucocerebrosidase gene; GD, Gaucher disease; H-Y, Hoehn and Yahr; ICD, impulse control disorder; LED, levodopa equivalent dose; ns, not significant; MMSE, Mini-Mental State Examination; PD, Parkinson’s disease; SD, standard deviation; UPDRS, Unified Parkinson’s Disease Rating Scale.

a Including a double-mutation subject (with a mutation unreported in GD).
b GD-associated mutations versus mutation (-).
c Two subjects with double mutation, including GD-associated mutations, were assigned to GD-associated mutation group.
d Other mutations versus mutation (-).
e Examined by Student t test after Levene’s test for equality of variances.
f Examined by Mann-Whitney U-test because of non-Gaussian distribution.
g    n = 155 due to 10 missing data.
h    n = 164 due to 3 missing data.
i     n = 28 due to 1 missing datum.
j     n = 165 due to 2 missing data.

3.4. Survival time analyses to develop dementia, psychosis, dyskinesia, and wearing-off

Time to develop clinical outcomes (dementia, psychosis, dyskinesia, and wearing-off) was compared in 19 subjects with GD-associated mutations, 29 with mutations unreported in GD, and 167 without mutation. The median observation time was 6.0 years. The subjects with GD-associated mutations showed a significantly earlier development of dementia and psychosis, compared with subjects without mutation (p < 0.001 and p = 0.017) ( Supplementary Table e-1, Fig. 1A and B). We rereviewed the clinical record of the subject who showed early dementia (defined by DSM IV) ( Fig. 1A) and made sure it did not satisfy the criteria of DLB ( McKeith et al., 2005).

Kaplan–Meier curves of dementia and psychosis in Parkinson's disease (PD) ...

Fig. 1.

Kaplan–Meier curves of dementia and psychosis in Parkinson’s disease (PD) patients with Gaucher disease (GD)-associated glucocerebrosidase gene (GBA) mutations and those without mutations. PD patients with GD-associated GBA mutations and those without GBA mutations were compared to investigate the time taken to develop dementia (A) and psychosis (B). Because of insufficient information in several patients, the numbers in each analysis were different. The patients with and without mutations were 17 and 165 (A), 18 and 165 (B) against a total of 19 and 167. DSM IV, Diagnostic and Statistical Manual of Mental Disorders, revised fourth edition. p-Values were calculated by log-rank tests.

The associations of GBA mutations and these symptoms were estimated as HRs, adjusting for sex and age at PD onset. HRs were 8.3 for dementia (95% CI, 3.3–20.9; p < 0.001) and 3.1 for psychosis (95% CI, 1.5–6.4; p = 0.002). The time until development of wearing-off and dyskinesia complications was not statistically significant, with HRs of 1.5 (95% CI, 0.8–3.1; p = 0.219) and 1.9 (95% CI, 0.9–4.1; p = 0.086) ( Table 3).

Table 3.Hazard ratios of GBA pathogenic mutations for clinical symptoms

Model Clinical feature Hazard ratio 95% CI p
1 Dementia (DSM-IV) 8.3 3.3–20.9 <0.001
2 Psychosis 3.1 1.5–6.4 0.002
3 Wearing-off 1.5 0.8–3.1 0.219
4 Dyskinesia 1.9 0.9–4.1 0.086
Each model was adjusted for sex and age at onset.

Key: CI, confidence interval; DSM-IV; The Diagnostic and Statistical Manual of Mental Disorders part 1IV; GBA, glucocerebrosidase.

Subjects with mutations unreported in GD did not show significant differences in time to develop all 4 outcomes, compared with no mutation subjects. Therefore, subjects with GD-unreported mutations were regarded as subjects without GBA mutations in further analyses.

3.5. rCBF on SPECT in patients with GD-associated GBA mutations

We conducted pixel-by-pixel comparisons of rCBF on SPECT between PD subjects with mutations (cases) and sex-, age-, and disease duration-matched PD subjects without any mutations in GBA (controls). Four controls were adopted for each case (except for a 34-year-old female case who was matched to a control), and in total 12 cases (female 50%, age at SPECT mean ± standard error (SE); 58.9 ± 3.3 years, disease duration at SPECT 7.3 ± 1.5 years) and 45 controls (female 64.4%, age at SPECT mean ± SE; 61.0 ± 1.3 years, disease duration at SPECT 7.1 ± 0.7 years) were analyzed. As a result, a significantly lower rCBF was seen in the cases compared to the controls in the bilateral parietal cortex, including the precuneus ( Fig. 2).

Regional cerebral blood flow in the group with GD-associated mutations compared ...

Fig. 2.

Regional cerebral blood flow in the group with GD-associated mutations compared with the matched Parkinson’s disease group without mutations. Regions with lower regional cerebral blood flow in the group with GD-associated mutations displayed on an anatomic reference map. Abbreviation: GD, Gaucher disease.

3.6. H/M ratios on MIBG scintigraphy in patients with GD-associated GBA mutations

Cardiac MIBG scintigraphy visualizes catecholaminergic terminals in vivo that are reduced as well as brain dopaminergic neurons in PD patients. We also investigated MIBG scintigraphy between 16 cases (female 68.8%, age at examination mean ± SE; 60.2 ± 2.6 years, disease duration at examination 6.2 ± 1.2 years) and sex-, age- and disease duration-matched 61 controls [(63.8 %, age 62.0 ± 1.1 years, disease duration 5.5 ± 0.6 years) (1:4 except for 1 young 34-year-old female case who was matched to a control)]. In the results, both early and late H/M ratios declined in both groups and did not show any significant differences (p = 0.309 and 0.244) ( Supplementary Table e-2).

4. Discussion

4.1. Contributions of GD-associated GBA mutations to the development of PD

In the analysis of 215 PD patients and 126 non-PD controls, we identified 10 nonsynonymous heterozygous GBA mutations, including 1 novel mutation. Among these mutations, 7 were GD-associated, and the patients carrying these mutations represented 8.8% of the PD cohort. No significant association was found between the GD-unreported mutations and PD development, which suggests that only the GD-associated mutations are a genetic risk for PD. According to a worldwide multicenter analysis of 1883 fully sequenced PD patients, 7% of the GD-associated mutations are found in non-Ashkenazi Jewish PD patients ( Sidransky et al., 2009). Although the mutation frequency in the present study was similar to previous results, the OR of GD-associated heterozygous mutations (25.1) was significantly greater than the OR (5.43) of other ethnic cohorts (Sidransky et al., 2009) and was consistent with an OR of 28.0 from a previous Japanese report ( Mitsui et al., 2009). These results, taken together, suggest the possibility thatGBA mutations are at a distinct risk for PD in the Japanese population. However, a larger Japanese cohort study is required to confirm this.

4.2. Cross-sectional clinical figures of PD with GBA mutations

Before the survival time analyses, we investigated clinical features at enrollment between mutation groups. The lower onset age, more frequent family history and dementia, and worse disease severity of PD in patients with GBA mutations, compared with those without mutations, were consistent with previous cross-sectional case-control reports ( Anheim et al., 2012, Brockmann et al., 2011, Chahine et al., 2013, Lesage et al., 2011, Li et al., 2013, Mitsui et al., 2009, Neumann et al., 2009, Seto-Salvia et al., 2012 and Sidransky et al., 2009). In contrast, female-predominance (73.7%, p = 0.047) in patients with mutations observed in the present study is inconsistent ( Neumann et al., 2009 and Seto-Salvia et al., 2012).

4.3. Impact of GBA mutations on the clinical course of PD

To investigate the impact of GBA mutations on the clinical course of PD, a prospective-designed study over a long period is preferred. Although there has been a few longitudinally designed study to date, follow-up clinical data for a median of 6 years of 121 PD cases from a community-based incident cohort was recently reanalyzed; results demonstrate that progression to dementia defined by DSM IV (HR 5.7) and Hoehn and Yahr stage 3 (HR 3.2) are significantly earlier in 4 GBA mutation-carrier patients compared with 117 patients with wild-type GBA ( Winder-Rhodes et al., 2013). A 2-year follow-up clinical report of 28 heterozygous GBA carriers who were recruited from relatives of GD-patients shows slight but significant deterioration of cognition and smelling, compared to healthy controls ( Beavan et al., 2015). Brockmann et al. (2015)assessed motor and nonmotor symptoms including cognitive and mood disturbances for 3 years in 20 PD patients with GBA mutations and showed a more rapid disease progression of motor impairment and cognitive decline in GBA mutation cases comparing to sporadic PD controls. The current long-term retrospective cohort study up to 12 years reinforced these results. It revealed that dementia and psychosis developed significantly earlier in subjects with GD-associated mutations compared with those without mutation, and the HRs of GBA mutations were estimated at 8.3 for dementia and 23.1 for psychosis, with adjustments for sex and PD onset age. In contrast, the results showed no significant difference in developing wearing-off and dyskinesia.

In this study, we also investigated whether GD-unreported mutations affected the clinical course of PD. In both cross-sectional and survival time analyses, the mutations unreported in GD carried no increased burden on clinical symptoms such as dementia, psychosis, wearing-off, and dyskinesia.

4.4. Reduced rCBF in PD with GBA mutations compared with matched PD controls

We found a significantly decreased rCBF, reflecting decreased synaptic activity, in the bilateral parietal cortex including the precuneus, in subjects with GD-associated mutations compared with matched subjects without mutations. The pattern of reduced rCBF was very similar to the pattern of H215O positron-emission tomography that Goker-Alpan et.al. (2012) reported, showing decreased resting rCBF in the lateral parietal association cortex and the precuneus bilaterally in GD subjects with parkinsonism (7 subjects with homozygous or compound heterozygous GBA mutations), compared with 11 PD without GBA mutations. Results suggest that PD with heterozygous GBAmutations and GD patients presenting parkinsonism had a common reduced pattern of rCBF. Interestingly, in their study, rCBF in the precuneus—but not in the lateral parietal cortex—correlated with IQ, suggesting that the involvement of the precuneus is critical for defining GBA-associated patterns.

4.5. Reduced cardiac MIBG H/M ratios as well as matched PD controls

We also showed that cardiac MIBG H/M ratios in subjects with GD-associated mutations were lower than the cutoff point for PD discrimination (Sawada et al., 2009), suggesting that postganglionic sympathetic nerve terminals to the epicardium were denervated, as well as in PD without mutations.

4.6. Mechanisms of impact on PD clinical course by GD-associated GBA mutations

Experimental studies suggesting a bidirectional pathogenic loop between α-synuclein and glucocerebrosidase have been accumulated (Fishbein et al., 2014, Gegg et al., 2012, Mazzulli et al., 2011, Noelker et al., 2015, Schondorf et al., 2014 and Uemura et al., 2015). Loss of glucocerebrosidase function compromises α-synuclein degradation in lysosome, whereas aggregated α-synuclein inhibits normal lysosomal function of glucocerebrosidase. The pathogenic loop may facilitate neurodegeneration in GD-associated PD brain, resulting in early development of dementia or psychosis as shown in the present study. Several recent researches propose the possibility that the similar mechanism as in PD with GBA mutations exists even in idiopathic PD brain ( Alcalay et al., 2015, Chiasserini et al., 2015, Gegg et al., 2012 and Murphy et al., 2014). On the other hand, the impacts of GD-associated GBA mutations for the development of motor complications such as wearing-off and dyskinesia were not statistically significant, suggesting other pathophysiological mechanisms in the striatal circuit brought out after long-term therapy especially by l-dopa.

4.7. Limitations

Our study has several limitations. In the design of the study, we assumed that the sample size was 215 (PD patients) for survival time analyses and investigated 224 PD patients. We assumed that the mutation prevalence would be 9.4%, and in fact, we found 19 patients with mutations (8.5%) of the 224 patients. Based on these figures, we estimated the risk ratios of heterozygous GBA mutations for the risk of PD development and PD clinical symptoms as ORs in the cross-sectional multivariate analyses, although the 95% CIs were broad. More of subject numbers will be needed to determine robust risk ratios.

Comprehensive Genetic Characterization of a Spanish Brugada Syndrome Cohort

PLOS   Published: July 14, 2015   DOI: http://dx.doi.org:/10.1371/journal.pone.0132888

Brugada syndrome (BrS) was identified as a new clinical entity in 1992 [1]. Six years later, the first genetic basis for the disease was identified, with the discovery of genetic variations inSCN5A [2]. Nowadays, more than 300 pathogenic variations in this first gene are known to be associated with BrS [3]. SCN5A encodes for the α subunit of the cardiac voltage-dependent sodium channel (Nav1.5), which is responsible for inward sodium current (INa), and thus plays an essential role in phase 0 of the cardiac action potential (AP). Genetic variations in this gene can explain around 20–25% of BrS cases [3].

Since BrS was classified as a genetic disease, several other genes have been described to confer BrS-susceptibility [47]. Pathogenic variations have been mainly described in: 1) genes encoding proteins that modulate Nav1.5 function, and 2) other calcium and potassium channels and their regulatory subunits. All these proteins participate, either directly or indirectly, in the development of the cardiac AP. Although the incidence of pathogenic variations in these BrS-associated genes is low [6], it is considered that, among all of them, they could provide a genetic diagnosis for up to an extra 5–10% of BrS cases. Hence, altogether, a genetic diagnosis can be achieved approximately in 35% of clinically diagnosed BrS patients.
Other types of genetic abnormalities have been suggested to explain the remaining percentage of undiagnosed patients. Indeed, multiplex ligation-dependent probe amplification (MLPA) has allowed the detection of large-scale gene rearrangements involving one or several exons ofSCN5A in BrS cases. However, the low proportion of BrS patients carrying large genetic imbalances identified to date suggests that this type of rearrangements will provide a genetic diagnosis for a modest percentage of BrS cases [810].
BrS has been associated with an increased risk of sudden cardiac death (SCD), despite the reported variability in disease penetrance and expressivity [11]. The prevalence of BrS is estimated at about 1.34 cases per 100 000 individuals per year, with a higher incidence in Asia than in the United States and Europe [12]. However, the dynamic nature of the typical electrocardiogram (ECG) and the fact that it is often concealed, hinder the diagnosis of BrS. Therefore, an exhaustive genetic testing and subsequent family screening may prove to be crucial in identifying silent carriers. A large percentage of these pathogenic variation carriers are clinically asymptomatic, and may be at risk of SCD, which is, sometimes, the first manifestation of the disease [13].
In the present work, we aimed to determine the spectrum and prevalence of genetic variations in BrS-susceptibility genes in a Spanish cohort diagnosed with BrS, and to identify variation carriers among relatives, which would enable the adoption of preventive measures to avoid SCD in their families.

Results  
Study population 

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Table 1. Demographics of the 55 Spanish BrS patients included in the study.

The table shows the demographic characteristics of all the patients included in the study. Numbers in parentheses represent the relative percentages for each condition. T1 ECG refers to Type 1 BrS diagnostic electrocardiogram (ECG), obtained either spontaneously, or after drug challenge. The information regarding both the electrophysiological studies (EPS) and the treatment was not available for all the patients. Two of the patients that didn’t receive any treatment died, and were not taken into account for the calculations of percentages (+2 dead). ICD, intracardiac cardioverter defibrillator.

http://dx.doi.org:/10.1371/journal.pone.0132888.t001

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Table 2. Characteristics of the Spanish BrS patients carrying rare genetic variations.

The table shows the clinical characteristics of the probands who carried rare genetic variations in SCN5A, SCN2B, or RANGRF. All of them are potentially pathogenic except that found in RANGRF, which is of unknown significance (see discussion). All the potentially pathogenic variations (PPVs) that had been previously reported, except p.P1725L and p.R1898C, had been identified in BrS patients. p.P1725L had been associated with Long QT Syndrome and p.R1898C was found in Exome Variant Server with a MAF of 0.0079%. No rare variations were identified in the control population. Patient’s age is expressed in years. Bold identifies the patients carrying variations that had not been described previously. M, male; F, female; S, syncope; ICD, intracardiac cardioverter defibrillator; UK, unknown; EPS, electrophysiological studies (+, positive response;-, negative response; N/P, not performed). The two patients who carried two PPVs each are identified by a and b, respectively.

http://dx.doi.org:/10.1371/journal.pone.0132888.t002

Sequencing of genes associated with BrS

We performed a genetic screening of 14 genes (SCN5A, CACNA1C, CACNB2, GPD1L,SCN1B, SCN2B, SCN3B, SCN4B, KCNE3, RANGRF, HCN4, KCNJ8, KCND3, and KCNE1L), which allowed the identification of 61 genetic variations in our cohort. Of these, 20 were classified as potentially pathogenic variations (PPVs), one variation of unknown significance, and 40 common or synonymous variants considered benign.

The 20 PPVs were found in 18 of the 55 patients (32.7% of the patients, 83.3% males; Table 2). Sixteen patients (88.9%) carried one PPV, and two patients (11.1%) carried two different PPVs each. Nineteen out of the 20 PPVs identified were localized in SCN5A and one in SCN2B.

The vast majority of the PPVs identified were missense (70%). We also detected 2 nonsense variations (10%), 3 insertions or deletions causing frameshifts (15%), and one splicing variation (5%). The three frameshifts (p.R569Pfs*151, p.E625Rfs*95 and p.R1623Efs*7) were identified in SCN5A. These were not found in any of the databases consulted (see Methods), and were thus considered potentially pathogenic (see below). The other 16 rare variations identified inSCN5A had been previously described, and hence were also considered potentially pathogenic. Fourteen of them had been identified in BrS patients. Of these, 6 had also been identified in individuals diagnosed with other cardiac electric diseases (i.e. Sick Sinus Syndrome, Long QT Syndrome, Sudden Unexplained Nocturnal Death Syndrome or Idiopathic Ventricular Fibrillation [2,15,16,20,21,25]). The other 2, p.P1725L and p.R1898C, had only been associated with Long QT Syndrome or found in Exome Variant Server with a MAF of 0.0079%, respectively. Furthermore, we identified a variation in SCN2B (c.632A>G in exon 4 of the gene, resulting in p.D211G) which was considered pathogenic. This patient was included within our cohort, but the functional characterization of channels expressing SCN2B p.D211G was object of a previous study from our group [7]. We also identified a nonsense variation in RANGRFwhich has been formerly reported as rare genetic variation of unknown significance [29].

Additionally, we screened the relatives of those probands carrying a PPV. We analysed a total of 129 relatives, 69 of which (53.5%) were variation carriers. Genotype-phenotype correlations evidenced that 8 of the families displayed complete penetrance (S3 Table). Additionally, no relatives were available for one of the probands carrying a PPV, thus hampering genotype-phenotype correlation assessment. The other 12 families showed incomplete penetrance.

 

MLPA analysis

The 37 patients with negative results after the genetic screening of the 14 BrS-associated genes underwent MLPA analyses of SCN5A. This technique did not reveal any large exon deletion or duplication in this gene for any of the patients.

 

SCN5A p.R569Pfs*151 (c.1705dupC), a novel PPV

A 41-year-old asymptomatic male presented a type 3 BrS ECG which was suggestive of BrS. Flecainide challenge unmasked a type 1 BrS ECG (Fig 1A, left), which was also spontaneously observed sometimes during medical follow up. Sequencing of SCN5A revealed a duplication of a cytosine at position 1705 (c.1705dupC; Fig 1A, right), which originated a frameshift that lead to a truncated Nav1.5 channel (p.R569Pfs*151). The proband’s sister also carried this duplication, but had never presented signs of arrhythmogenesis. The proband’s twin daughters were also variation carriers, displayed normal ECGs and, to date, are asymptomatic (Fig 1A, middle). Thus, p.R569Pfs*151 represents a novel genetic alteration in the Nav1.5 channel that could potentially lead to BrS, but with incomplete penetrance.

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Fig 1. Characteristics of the probands carrying non-reported potentially pathogenic variations (PPVs) in SCN5A and their families.

Left: Electrocardiograms of the probands: (A) patient carrying the p.R569Pfs*151 variation, showing the ST elevation characteristic of BrS in V1 at the time of the flecainide test; (B) patient carrying the p.E625Rfs*95 variation, showing the spontaneous ST elevation characteristic of BrS in V1 and V2; and (C) patient carrying the p.R1623Efs*7 variation, showing the spontaneous ST elevation characteristic of BrS in V1 and V2. Middle: Family pedigrees. Open symbols designate clinically normal subjects, filled symbols mark clinically affected individuals and question marks identify subjects without an available clinical diagnosis. Plus signs indicate the carriers of the PPVs and minus signs, non-carriers. The crosses mark deceased individuals and arrows identify the proband. Right: Detail of the electropherograms obtained after SCN5Asequence analysis of a control subject (left panels) and of the probands (right panels).

http://dx.doi.org:/10.1371/journal.pone.0132888.g001

SCN5A p.E625Rfs*95 (c.1872dupA), a novel PPV

A 51-year-old asymptomatic male was diagnosed with BrS since he presented a spontaneous ST segment elevation in leads V1 and V2 characteristic of type 1 BrS ECG (Fig 1B, left). The sequencing of SCN5A evidenced an adenine duplication at position 1872 (c.1872dupA, Fig 1B, right). This genetic variation results in a truncated Nav1.5 channel (p.E625Rfs*95). The genetic analysis of the proband’s relatives proved that only her mother carried the variation (Fig 1B, middle). She was asymptomatic, but a BrS ECG was unmasked upon ajmaline challenge. The proband’s sister was found dead in her crib at 6 months of age, which suggests that her death might be compatible with BrS. Therefore, the p.E625Rfs*95 variation in the Nav1.5 channel represents a novel genetic alteration potentially causing BrS.

SCN5A p.R1623Efs*7 (c.4867delC), a novel PPV

The proband, a 31-year-old male, was admitted to hospital after suffering a syncope. His baseline 12-lead ECG showed a ST segment elevation in leads V1 and V2 that strongly suggested BrS type 1 (Fig 1C, left). A deletion of the cytosine at position 4867 (c.4867delC) was observed upon SCN5A sequencing (Fig 1C, right). This base deletion leads to a frameshift that originates a truncated Nav1.5 channel (p.R1623Efs*7). Genetic screening of his parents and sisters evidenced that none of them carried this novel variation (Fig 1C, middle). None of them had presented any signs of arrhythmogenicity, nor had a BrS ECG. Nevertheless, in uterogenetic analysis of one of his daughters proved that she had inherited the variation. She died when she was 1 year of age of non-arrhythmogenic causes. Hence, the p.R1623Efs*7 variation in the Nav1.5 channel is a novel genetic alteration originated de novo in the proband that could potentially lead to BrS.

Synonymous and common genetic variations portrayal

In our cohort, we identified 40 single nucleotide variations which were common genetic variants and/or synonymous variants (S2 Table). Twenty-nine had a minor allele frequency (MAF) over 1%, and were thus considered common genetic variants.

We also identified 11 variants with MAF less than 1%. Of them, 9 were synonymous variants, what made us assume that they were not disease-causing. Four of these synonymous variants were not found in any of the databases consulted, and thus their MAF was considered to be less than 1%. Each of these synonymous variations was identified in 1 patient of the cohort. A similar proportion of individuals carrying these novel variations was detected upon sequencing of 300 healthy Spanish individuals (600 alleles). The remaining 2 variants were missense, and although they had either a MAF of less than 1% or an unknown MAF according to the Exome Variant Server and dbSNP websites, they were common in our cohort (29.2 and 50%, respectively; S2 Table), and a similar MAF was detected in a Spanish cohort of healthy individuals (26.7% and 48.8%, respectively).

Influence of phenotype and age on PPV discovery

To assess if a connection existed between the probands’ phenotype and the PPV detection yield, we classified the patients in our cohort according to their ECG (spontaneous or induced type 1), the presence of BrS cases within their families, and the presence/absence of symptoms. Even though the overall PPV detection yield was 32.7%, it was even higher for symptomatic patients (Fig 2). Indeed, in this group of patients, having a family history of BrS was identified as a factor for increased PPV discovery yield. In the case of absence of BrS in the family, the variation discovery yield was almost double for those patients having a spontaneous type 1 BrS ECG than for patients with drug-induced type 1 ECG (45.5% vs 25%, respectively). In addition, we identified a PPV in 44.4% of the asymptomatic patients who presented family history of BrS and a spontaneous type 1 BrS ECG. When the patient presented drug-induced type 1 ECG or in the absence of family history of BrS, the PPV discovery yield was of around 15%.

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Fig 2. Influence of the phenotype on PPV discovery yield.

Bar graph comparing the PPV detection yield in 8 different clinical categories (stated below the graph). Each bar shows the total number of patients for each clinical category divided in those with a PPV (black) and those without an identified PPV (white). The number of patients (in brackets) and percentages are given. Pos, positive; Neg, negative; Spont, spontaneous type 1 BrS ECG; Drug, drug-induced type 1 BrS ECG; n, number of patients.

http://dx.doi.org/:10.1371/journal.pone.0132888.g002

We also investigated the role of age on the PPV occurrence. No significant age differences were observed between variation carriers and non-carriers (38.6±10.3 and 43.5±14.4, respectively, p = 0.16). However, the PPV discovery yield was higher for patients with ages between 30 and 50 years: out of the total of patients carrying a PPV, 83.3% of the patients were in this age range, while 11.1% were younger and 5.6% were older patients (Fig 3A, upper panel). The PPV discovery yield was significantly higher for symptomatic than for asymptomatic patients (42.3% vs 24.1%, respectively; Fig 3A, lower panels).

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Fig 3. Influence of the age on PPVs discovery yield.

(A) Pie charts showing the distribution of patients in the overall population as well as in the categories of symptomatic and asymptomatic patients regarding PPV discovery. The percentage and the number of patients (in brackets) are given for each group. The small pie charts correspond to the age distribution of patients with an identified PPV. (B) Bar graphs of the PPV detection yields obtained for each of the age groups (< 30 years, 30–50 years and > 50 years). Numbers inside each bar correspond to the number of patients carrying a PPV for each category and the percentages represent the variation detection yield.

http://dx.doi.org:/10.1371/journal.pone.0132888.g003

Noteworthy, in the 30–50 age range, 52.9% (9/17) of the symptomatic patients and 35.3% (6/17) of asymptomatic patients carried one PPV (Fig 3B, middle). Additionally, 40% (2/5) of the symptomatic young patients (< 30 years) were variation carriers, while no PPVs were identified in asymptomatic patients within this age range.

Overall, 55 unrelated Spanish patients clinically diagnosed with BrS were included in our study.Table 1 shows the demographics of this cohort, and Table 2 and S1 Table show the clinical and genetic characteristics of all the patients included in the study. The mean age at clinical diagnosis was of 41.9±13.3 years. Although the majority of patients were males (74.5%), their age at diagnosis was not different than that of females (41.8±12.1 years and 42.3±16.3 years, respectively; p = 0.92). A type 1 BrS ECG was present spontaneously in 37 patients (67.3%), and drug challenge revealed a type 1 BrS ECG for the remaining 18 patients (32.7%). Almost half of the patients had experienced symptoms, including 2 SCD and 4 aborted SCD. Patients who had not previously experienced any signs of arrhythmogenicity despite having a BrS ECG were considered asymptomatic. Comparison of symptomatic vs asymptomatic patients evidenced a similar percentage of males (73.1% and 75.9%, respectively). However, the mean age at diagnosis was different between the two groups of patients (37.7±14.3 and 45.7±11.4, respectively; p<0.05).

Discussion

To the best of our knowledge, this is the first comprehensive genetic evaluation of 14 BrS-susceptibility genes and MLPA of SCN5A in a Spanish cohort. Well delimited BrS cohorts from Japan, China, Greece and even Spain have been genetically studied [24,3032]. Additionally, an international compendium of BrS genetic variations identified in more than 2100 unrelated patients from different countries was published in 2010 [3]. However, all these studies screenedSCN5A exclusively. In 2012, Crotti et al. reported the spectrum and prevalence of genetic variations in 12 BrS-susceptibility genes in a BrS cohort [5]. However, this study included patients of different ethnicity. Here, we report the analysis of 14 genes which has been conducted on a well-defined BrS cohort of the same ethnicity.

Our results confirm that SCN5A is still the most prevalent gene associated with BrS. Indeed,SCN5A-mediated BrS in our cohort (30.9%) is higher than the proportion described in other European reports [3,23], where a potentially causative variation is identified in only 20–25% of BrS patients. The reason for this discrepancy is unclear but could point towards a higher prevalence of SCN5A PPVs in the Spanish population or to selection bias. Additionally, we identified a genetic variation in SCN2B (c.632A>G, which results in p.D211G). We have formerly published the comprehensive electrophysiological characterization of this variation, and showed that indeed this variation could be responsible of the phenotype of the patient, thus linking SCN2B with BrS for the first time [7]. Also, we identified a variation in RANGRF. This variation (c.181G>T leading to p.E61X) had been previously reported in a Danish atrial fibrillation cohort [33]. Surprisingly, the authors reported an incidence of 0.4% for this variation in the healthy Danish population, which brought into question its pathogenicity. Our finding of this variation in an asymptomatic patient displaying a type 2 BrS ECG also points toward considering it as a rare genetic variation with a potential modifier effect on the phenotype but not clearly responsible for the disease [29].

No PPVs were identified in the other genes tested. Certainly, it is well accepted that the contribution of these genes to the disease is minor, and thus should only be considered under special circumstances [13,34]. In addition, recent studies have questioned the causality of variations identified in some of these minority genes [35].

We also used the MLPA technique for the detection of large exon duplications and/or deletions in SCN5A in patients without PPVs, and no large rearrangements were identified. This is in accordance with previous reports, which revealed that such imbalances are uncommon [810].

Kapplinger et al. [3] reported a predominance of PPVs in transmembrane regions of Nav1.5. Indeed, it has been proposed that most rare genetic variations in interdomain linkers may be considered as non-pathogenic [36]. In contrast, PPVs identified in this study are mainly located in extracellular loops and cytosolic linker regions of Nav1.5 (Fig 4). Additionally, 2 of our non-previously reported frameshifts are located in the DI-DII linker. These 2 genetic variations lead to truncated proteins, which would lack around 75% of the protein sequence, and thus are presupposed to be pathogenic.

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Fig 4. Nav1.5 channel scheme showing the relative position of the SCN5A PPVs identified in our cohort.

Open symbols indicate already described variations and closed symbols locate novel variations reported in this study. DI to DIV designate the 4 domains of the protein, and numbers 1–6 identify the different segments within each domain. Crosses mark the voltage sensor.

http://dx.doi.org:/10.1371/journal.pone.0132888.g004

In our cohort, we have identified 40 synonymous or common genetic variations, 4 of which have not been previously reported. These variations are gradually becoming more and more important in the explanation of certain phenotypes of genetic diseases. Only a few common variations identified here are already published as phenotypic modifiers [37,38]. The effect of these and other common variants identified in our cohort on BrS phenotype should be further studied.

Unexpectedly, almost 40% (7/18) of the PPV carriers did not present signs of arrhythmogenicity. We also performed genotype-phenotype correlations of the PPVs identified in the families (S3 Table). These studies uncovered relatives, most of whom were young individuals, who carried a familial variation but had never exhibited any clinical manifestations of the disease. This is in agreement with Crotti et al. and Priori et al. [5,23], who postulated that a positive genetic testing result is not always associated with the presence of symptoms. Indeed, the existence of asymptomatic patients carrying genetic variations described to cause a severe Nav1.5 channel dysfunction has been reported [39]. The identification of silent carriers is of paramount importance since it allows the adoption of preventive measures before any lethal episode takes place. Unknown environmental factors, medication and modifier genes have been suggested to influence and/or predispose to arrhythmogenesis [11]. Hence, this group of patients has to be cautiously followed in order to avoid fatal events.

Our studies on the connection between patients’ phenotype and the PPV detection yield highlighted the presence of symptoms as a factor for an increased variation discovery yield. Within the group of symptomatic individuals, a PPV was identified in a higher proportion of patients displaying a spontaneous type 1 BrS ECG than for patients showing a drug-induced ECG. Likewise, within the asymptomatic patients with family history of BrS, those who presented spontaneous type 1 BrS ECG carried a PPV more often than those with a drug-induced ECG (Fig 2). Referring to age, the vast majority (17/20, 85%) of the PPVs were identified in patients around their fourth decade of age (30–50 years). This is in accordance with the accepted mean age of disease manifestation. Moreover, in this age range, more than 50% of the patients who presented symptoms carried a variation that could be pathogenic (Fig 3). Importantly, 35.3% of asymptomatic patients of around 40 years of age also carried one of such variations. These data highlight the importance of performing a genetic test even in the absence of clinical manifestations of the disease, and particularly when in the 30–50 years range, which is in accordance with consensus recommendations [13,34].

In conclusion, we have analysed for the first time 14 BrS-susceptibility genes and performed MLPA of SCN5A in a Spanish BrS cohort. Our cohort showed male prevalence with a mean age of disease manifestation around 40 years. BrS in this cohort was almost exclusivelySCN5A-mediated. The mean PPV discovery yield in our Spanish BrS patients is higher than that described for other BrS cohorts (32.7% vs 20–25%, respectively), and is even higher for patients in the 30–50 years age range (up to 53% for symptomatic patients). All these evidences support the genetic testing, at least of SCN5A, in all clinically well diagnosed BrS patients.

 

Study Limitations

First of all, drug challenge tests were not performed for all the relatives who were asymptomatic variation carriers. This fact hampered their clinical diagnosis and represents an impediment to definitely assess the link between PPVs and BrS. These patients are nowadays under follow-up.

New PPVs have been identified in our cohort. The clinical information available for the families suggests that these new variations could be pathogenic. Still, in vitro studies of these variations are required in order to evaluate their functional effects and verify their pathogenic role. Additionally, genotyping in an independent cohort would help reduce the likelihood of type I (false positive) error in genetic variant discovery.

We have to acknowledge that the study set is relatively small. Consequently, the classification of patients according to the different clinical categories rendered rather small sub-groups, which may lead to over-interpretation of the results. Future studies will be directed to the genetic screening of additional Spanish BrS patients, which will probably reinforce the significance of the tendencies observed here.

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Diagnostic Revelations

Larry H. Bernstein, MD, FCAP, Curator

LPBI

New Liquid Biopsy Test Uses Platelet RNA as Cancer Diagnostic

  • Click Image To Enlarge +
    Using platelet RNA, scientists have been able to detect the presence of cancer and pinpoint its primary location. [Best et al., 2015, Cancer Cell 28, 1–11]

    The age of fast, accurate, and noninvasive cancer screening is rapidly becoming reality. The power of next-generation sequencing has allowed molecular diagnostic techniques to sample small amounts of blood for the genetic hallmarks of tumorigenesis. These liquid biopsy procedures, as they have been dubbed, typically search for circulating tumor DNA (ctDNA) that has made its way into the systemic circulation from tumor cells that have died or enrich for circulating tumor cells (CTCs) that have broken off from the primary cancer site.

    Now, a team of researchers lead by scientists at Massachusetts General Hospital (MGH), have developed a new diagnostic test that analyzes the tumor RNA picked up in circulating platelets. The investigators believe this new method could become even more useful than other molecular technologies for diagnosing cancer since it can also determine the primary location of the tumor and provide insight to potential therapeutic approaches.

    “By combining next-generation-sequencing gene expression profiles of platelet RNA with computational algorithms we developed, we were able to detect the presence of cancer with 96 percent accuracy,” explains co-senior author Bakhos Tannous, Ph.D., associate professor Harvard Medical School and associate neuroscientist at MGH. “Platelet RNA signatures also provide valuable information on the type of tumor present in the body and can guide the selection of the most optimal treatment for individual patients.

    The findings from this study were published recently in Cancer Cell through an article entitled “RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics.”

    In the current study the research team describes finding that the RNA profiles of tumor-educated platelets (TEPs)—those that have taken up molecules shed by tumors—can distinguish among blood samples of healthy individuals and those of patients with six types of cancer, determine the location of the primary tumor, and identify tumors carrying mutations that can guide therapeutic decision-making.

    Over the past several years, the scientific literature has shown that in addition to their role in promoting blood clotting, platelets take up protein and RNA molecules from tumors, possibly playing a role in tumor growth and metastasis. Dr. Tannous and his colleagues set out to determine whether tumor RNA carried in platelets could be used to diagnose and classify common types of cancer.

    The investigators isolated platelets from blood samples taken from 55 healthy donors, 39 individual with early-stage cancer and 189 patients with advanced, metastatic cancer. Among those patients with cancer, they were diagnosed with non-small-cell lung cancer, colorectal cancer, glioblastoma, pancreatic cancer, hepatobiliary cancer, or breast cancer.

    The comparison of RNA profiles from the healthy donors to those of the cancer patients identified increased levels of approximately 1,500 RNA molecules—many involved in cancer-associated processes—and a reduction of almost 800 in samples from cancer patients. Using their novel algorithm, the MGH group was able to examine close to 1,000 RNAs from almost 300 individuals with 96% accuracy for the presence of cancer.

    Additionally, the platelet mRNA profiles were able to identify the particular type of cancer within each patient participant, including distinguishing among three types of gastrointestinal adenocarcinoma: colorectal cancer, pancreatic cancer, and hepatobiliary cancer. Platelets from patients with tumors driven by mutations in KRAS or EGFR proteins—biomarkers that can guide the use of drugs targeting those mutations—proved to have unique RNA profiles as well.

    The researchers were excited by their findings and emphasize the uniqueness of their approach as currently utilized liquid biopsy approaches have been unable to diagnose cancer while simultaneously pinpointing the location of the primary tumor.

    “We observed that the mRNA profiles of tumor-educated platelets have the sensitivity and specificity to detect cancer, even in early, non-metastasized tumors,” noted Dr. Tannous. “We are further assessing the potential of TEP-based screening for therapeutic decision making and also investigating how non-cancerous diseases may further influence the RNA repertoire of TEPs.”

  • RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics

Myron G. Best Nik Sol, Jihane Tannous, Bart A. Westerman, François Rustenburg, Pepijn Schellen, Heleen Verschueren, Edward Post, Jan Koster, Bauke Ylstra, Irsan Kooi, et al.
Highlights

Tumors “educate” platelets (TEPs) by altering the platelet RNA profile

TEPs provide a RNA biosource for pan-cancer, multiclass, and companion diagnostics

TEP-based liquid biopsies may guide clinical diagnostics and therapy selection

A total of 100–500 pg of total platelet RNA is sufficient for TEP-based diagnostics

mRNA Profiles of Tumor-Educated Platelets Are Distinct from Platelets of Healthy Individuals

Summary

Tumor-educated blood platelets (TEPs) are implicated as central players in the systemic and local responses to tumor growth, thereby altering their RNA profile. We determined the diagnostic potential of TEPs by mRNA sequencing of 283 platelet samples. We distinguished 228 patients with localized and metastasized tumors from 55 healthy individuals with 96% accuracy. Across six different tumor types, the location of the primary tumor was correctly identified with 71% accuracy. Also, MET or HER2-positive, and mutant KRAS, EGFR, orPIK3CA tumors were accurately distinguished using surrogate TEP mRNA profiles. Our results indicate that blood platelets provide a valuable platform for pan-cancer, multiclass cancer, and companion diagnostics, possibly enabling clinical advances in blood-based “liquid biopsies”.

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http://www.cell.com/cms/attachment/2039645414/2053235278/fx1.jpg

Significance

Blood-based “liquid biopsies” provide a means for minimally invasive molecular diagnostics, overcoming limitations of tissue acquisition. Early detection of cancer, clinical cancer diagnostics, and companion diagnostics are regarded as important applications of liquid biopsies. Here, we report that mRNA profiles of tumor-educated blood platelets (TEPs) enable for pan-cancer, multiclass cancer, and companion diagnostics in both localized and metastasized cancer patients. The ability of TEPs to pinpoint the location of the primary tumor advances the use of liquid biopsies for cancer diagnostics. The results of this proof-of-principle study indicate that blood platelets are a potential all-in-one platform for blood-based cancer diagnostics, using the equivalent of one drop of blood.

Introduction

Cancer is primarily diagnosed by clinical presentation, radiology, biochemical tests, and pathological analysis of tumor tissue, increasingly supported by molecular diagnostic tests. Molecular profiling of tumor tissue samples has emerged as a potential cancer classifying method (Akbani et al., 2014, Golub et al., 1999, Han et al., 2014, Hoadley et al., 2014, Kandoth et al., 2013,Ramaswamy et al., 2001, Su et al., 2001). In order to overcome limitations of tissue acquisition, the use of blood-based liquid biopsies has been suggested (Alix-Panabières et al., 2012, Crowley et al., 2013, Haber and Velculescu, 2014). Several blood-based biosources are currently being evaluated as liquid biopsies, including plasma DNA (Bettegowda et al., 2014, Chan et al., 2013, Diehl et al., 2008, Murtaza et al., 2013, Newman et al., 2014, Thierry et al., 2014) and circulating tumor cells (Bidard et al., 2014, Dawson et al., 2013, Maheswaran et al., 2008, Rack et al., 2014). So far, implementation of liquid biopsies for early detection of cancer has been hampered by non-specificity of these biosources to pinpoint the nature of the primary tumor (Alix-Panabières and Pantel, 2014,Bettegowda et al., 2014).

It has been reported that tumor-educated platelets (TEPs) may enable blood-based cancer diagnostics (Calverley et al., 2010, McAllister and Weinberg, 2014,Nilsson et al., 2011). Blood platelets—the second most-abundant cell type in peripheral blood—are circulating anucleated cell fragments that originate from megakaryocytes in bone marrow and are traditionally known for their role in hemostasis and initiation of wound healing (George, 2000, Leslie, 2010). More recently, platelets have emerged as central players in the systemic and local responses to tumor growth. Confrontation of platelets with tumor cells via transfer of tumor-associated biomolecules (“education”) is an emerging concept and results in the sequestration of such biomolecules (Klement et al., 2009,Kuznetsov et al., 2012, McAllister and Weinberg, 2014, Nilsson et al., 2011,Quail and Joyce, 2013). Moreover, external stimuli, such as activation of platelet surface receptors and lipopolysaccharide-mediated platelet activation (Denis et al., 2005, Rondina et al., 2011), induce specific splicing of pre-mRNAs in circulating platelets (Power et al., 2009, Rowley et al., 2011, Schubert et al., 2014). Platelets may also undergo queue-specific splice events in response to signals released by cancer cells and the tumor microenvironment—such as stromal and immune cells. The combination of specific splice events in response to external signals and the capacity of platelets to directly ingest (spliced) circulating mRNA can provide TEPs with a highly dynamic mRNA repertoire, with potential applicability to cancer diagnostics (Calverley et al., 2010, Nilsson et al., 2011) (Figure 1A). In this study, we characterize the platelet mRNA profiles of various cancer patients and healthy donors and investigate their potential for TEP-based pan-cancer, multiclass cancer, and companion diagnostics.

  
Results

We prospectively collected and isolated blood platelets from healthy donors (n = 55) and both treated and untreated patients with early, localized (n = 39) or advanced, metastatic cancer (n = 189) diagnosed by clinical presentation and pathological analysis of tumor tissue supported by molecular diagnostics tests. The patient cohort included six tumor types, i.e., non-small cell lung carcinoma (NSCLC, n = 60), colorectal cancer (CRC, n = 41), glioblastoma (GBM, n = 39), pancreatic cancer (PAAD, n = 35), hepatobiliary cancer (HBC, n = 14), and breast cancer (BrCa, n = 39) (Figure 1B; Table 1; Table S1). The cohort of healthy donors covered a wide range of ages (21–64 years old, Table 1).

Table 1Summary of Patient Characteristics
PATIENT GROUP TOTAL (N) GENDER M (%)A AGE (SD)B METASTASIS (%) MUTATION PRESENCE (%)
TRAINING VALIDATION TRAINING VALIDATION TRAINING VALIDATION TRAINING VALIDATION TRAINING VALIDATION
HD 39 16 21 (54) 6 (38) 41 (13) 38 (16)
GBM 23 16 18 (78) 10 (63) 59 (16) 62 (14) 0 (0) 0 (0)
NSCLC 36 24 14 (39) 14 (58) 60 (11) 59 (12) 33 (92) 23 (96) KRAS 15 (42) 11 (46)
EGFR 14 (39) 7 (29)
MET-overexpression 5 (14) 3 (13)
CRC 25 16 13 (52) 9 (56) 59 (13) 63 (16) 20 (80) 15 (94) KRAS 7 (28) 8 (50)
PAAD 21 14 12 (57) 7 (50) 66 (9) 66 (10) 15 (71) 9 (64) KRAS 13 (62) 9 (64)
BrCa 23 16 0 (0) 0 (0) 59 (11) 59 (11) 16 (70) 9 (56) HER2+ 7 (30) 5 (31)
PIK3CA 6 (26) 2 (13)
triple negative 5 (22) 3 (19)
HBC 8 6 6 (75) 2 (33) 68 (13) 62 (16) 6 (75) 4 (67) KRAS 3 (38) 1 (17)

HD, healthy donors; GBM, glioblastoma; NSCLC, non-small cell lung cancer; CRC, colorectal cancer; PAAD, pancreatic cancer; BrCa, breast cancer; HBC, hepatobiliary cancer. See also Table S1.

aIndicated are number of male individuals.
bIndicated is mean age in years.

Platelet purity was confirmed by morphological analysis of randomly selected and freshly isolated platelet samples (contamination is 1 to 5 nucleated cells per 10 million platelets, see Supplemental Experimental Procedures), and platelet RNA was isolated and evaluated for quality and quantity (Figure S1A). A total of 100–500 pg of platelet total RNA (the equivalent of purified platelets in less than one drop of blood) was used for SMARTer mRNA amplification and sequencing (Ramsköld et al., 2012) (Figures 1C and S1A). Platelet RNA sequencing yielded a mean read count of ∼22 million reads per sample. After selection of intron-spanning (spliced) RNA reads and exclusion of genes with low coverage (seeSupplemental Experimental Procedures), we detected in platelets of healthy donors (n = 55) and localized and metastasized cancer patients (n = 228) 5,003 different protein coding and non-coding RNAs that were used for subsequent analyses. The obtained platelet RNA profiles correlated with previously reported mRNA profiles of platelets (Bray et al., 2013, Kissopoulou et al., 2013, Rowley et al., 2011, Simon et al., 2014) and megakaryocytes (Chen et al., 2014) and not with various non-related blood cell mRNA profiles (Hrdlickova et al., 2014) (Figure S1B). Furthermore, DAVID Gene Ontology (GO) analysis revealed that the detected RNAs are strongly enriched for transcripts associated with blood platelets (false discovery rate [FDR] < 10−126).

Among the 5,003 RNAs, we identified known platelet markers, such as B2M, PPBP, TMSB4X, PF4, and several long non-coding RNAs (e.g., MALAT1). A total of 1,453 out of 5,003 mRNAs were increased and 793 out of 5,003 mRNAs were decreased in TEPs as compared to platelet samples of healthy donors (FDR < 0.001), while presenting a strong correlation between these platelet mRNA profiles (r = 0.90, Pearson correlation) (Figure 1D). Unsupervised hierarchical clustering based on the differentially detected platelet mRNAs distinguished two sample groups with minor overlap (Figure 1E; Table S2). DAVID GO analysis revealed that the increased TEP mRNAs were enriched for biological processes such as vesicle-mediated transport and the cytoskeletal protein binding while decreased mRNAs were strongly involved in RNA processing and splicing (Table S3). A correlative analysis of gene set enrichment (CAGE) GO methodology, in which 3,875 curated gene sets of the GSEA database were correlated to TEP profiles (see Experimental Procedures), demonstrated significant correlation of TEP mRNA profiles with cancer tissue signatures, histone deacetylases regulation, and platelets (Table 2). The levels of 20 non-protein coding RNAs were altered in TEPs as compared to platelets from healthy individuals and these show a tumor type-associated RNA profile (Figure S1C).

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Tumor-Educated Platelet mRNA Profiling for Pan-Cancer Diagnostics

(A) Schematic overview of tumor-educated platelets (TEPs) as biosource for liquid biopsies.

(B) Number of platelet samples of healthy donors and patients with different types of cancer.

(C) TEP mRNA sequencing (mRNA-seq) workflow, as starting from 6 ml EDTA-coated tubes, to platelet isolation, mRNA amplification, and sequencing.

(D) Correlation plot of mRNAs detected in healthy donor (HD) platelets and cancer patients’ TEPs, including highlighted increased (red) and decreased (blue) TEP mRNAs.

(E) Heatmap of unsupervised clustering of platelet mRNA profiles of healthy donors (red) and patients with cancer (gray).

(F) Cross-table of pan-cancer SVM/LOOCV diagnostics of healthy donor subjects and patients with cancer in training cohort (n = 175). Indicated are sample numbers and detection rates in percentages.

(G) Performance of pan-cancer SVM algorithm in validation cohort (n = 108). Indicated are sample numbers and detection rates in percentages.

(H) ROC-curve of SVM diagnostics of training (red), validation (blue) cohort, and random classifiers, indicating the classification accuracies obtained by chance of the training and validation cohort (gray).

(I) Total accuracy ratios of SVM classification in five subgroups, including corresponding predictive strengths. Genes, number of mRNAs included in training of the SVM algorithm.

See also Figure S1 and Tables S1, S2, S3, and S4.

Table 2Pan-Cancer CAGE Gene Ontology
TOP 25 GO CORRELATIONS
# LOWESTA HIGHESTA
DOWN
Translation 10 −0.865 −0.890
Immune, T cell 5 −0.853 −0.883
Cancer-associated 2 −0.875 −0.887
Viral replication 2 −0.875 −0.878
IL-signaling 2 −0.869 −0.874
RNA processing 1 −0.886
Ago2-Dicer-silencing 1 −0.882
Protein metabolism 1 −0.879
Receptor processing 1 −0.869
UP
Cancer-associated 6 −0.783 −0.906
Infection 3 −0.798 −0.853
HDAC 3 −0.795 −0.852
Platelet 3 −0.837 −0.906
Cytoskeleton 2 −0.801 −0.886
Hypoxia 2 −0.763 −0.937
Protease 1 −0.854
Immunodeficiency 1 −0.812
Differentiation 1 −0.810
Immune differentiation 1 −0.801
Methylation 1 −0.778
Metabolism 1 −0.768

Top-ranking correlations of platelet-mRNA profiles with 3,875 Broad Institute curated gene sets. CAGE, Correlative Analysis of Gene Set Enrichment; GO, gene ontology; #, number of hits per annotation; IL, interleukin; HDAC, histone deacetylase.

aIndicated are lowest and highest correlations per annotation.

Next, we determined the diagnostic accuracy of TEP-based pan-cancer classification in the training cohort (n = 175), employing a leave-one-out cross-validation support vector machine algorithm (SVM/LOOCV, see Experimental Procedures; Figures S1D and S1E), previously used to classify primary and metastatic tumor tissues (Ramaswamy et al., 2001, Su et al., 2001, Vapnik, 1998, Yeang et al., 2001). Briefly, the SVM algorithm (blindly) classifies each individual sample as cancer or healthy by comparison to all other samples (175 − 1) and was performed 175 times to classify and cross validate all individuals samples. The algorithms we developed use a limited number of different spliced RNAs for sample classification. To determine the specific input gene lists for the classifying algorithms we performed ANOVA testing for differences (as implemented in the R-package edgeR), yielding classifier-specific gene lists (Table S4). For the specific algorithm of the pan-cancer TEP-based classifier test we selected 1,072 RNAs (Table S4) for the n = 175 training cohort, yielding a sensitivity of 96%, a specificity of 92%, and an accuracy of 95% (Figure 1F). Subsequent validation using a separate validation cohort (n = 108), not involved in input gene list selection and training of the algorithm, yielded a sensitivity of 97%, a specificity of 94%, and an accuracy of 96% (Figure 1G), with an area under the curve (AUC) of 0.986 to detect cancer (Figure 1H) and high predictive strength (Figure 1I). In contrast, random classifiers, as determined by multiple rounds of randomly shuffling class labels (permutation) during the SVM training process (see Experimental Procedures), had no predictive power (mean overall accuracy: 78%, SD ± 0.3%, p < 0.01), thereby showing, albeit an unbalanced representation of both groups in the study cohort, specificity of our procedure. A total of 100 times random class-proportional subsampling of the entire dataset in a training and validation set (ratio 60:40) yielded similar accuracy rates (mean overall accuracy: 96%, SD: ± 2%), confirming reproducible classification accuracy in this dataset. Of note, all 39 patients with localized tumors and 33 of the 39 patients with primary tumors in the CNS were correctly classified as cancer patients (Figure 1I). Visualization of 22 genes previously identified at differential RNA levels in platelets of patients with various non-cancerous diseases (Gnatenko et al., 2010, Healy et al., 2006, Lood et al., 2010,Raghavachari et al., 2007), revealed mixed levels in our TEP dataset (Figure S1F), suggesting that the platelet RNA repertoire in patients with non-cancerous disease is distinct from patients with cancer.

Tumor-Specific Educational Program of Blood Platelets Allows for Multiclass Cancer Diagnostics

In addition to the pan-cancer diagnosis, the TEP mRNA profiles also distinguished healthy donors and patients with specific types of cancer, as demonstrated by the unsupervised hierarchical clustering of differential platelet mRNA levels of healthy donors and all six individual tumor types, i.e., NSCLC, CRC, GBM, PAAD, BrCa, and HBC (Figures 2A, all p < 0.0001, Fisher’s exact test, and S2A; Table S5), and this resulted in tumor-specific gene lists that were used as input for training and validation of the tumor-specific algorithms (Table S4). For the unsupervised clustering of the all-female group of BrCa patients, male healthy donors were excluded to avoid sample bias due to gender-specific platelet mRNA profiles (Figure S2B). SVM-based classification of all individual tumor classes with healthy donors resulted in clear distinction of both groups in both the training and validation cohort, with high sensitivity and specificity, and 38/39 (97%) cancer patients with localized disease were classified correctly (Figures 2B and S2C). CAGE GO analysis showed that biological processes differed between TEPs of individual tumor types, suggestive of tumor-specific “educational” programs (Table S6). We did not detect sufficient differences in mRNA levels to discriminate patients with non-metastasized from patients with metastasized tumors, suggesting that the altered platelet profile is predominantly influenced by the molecular tumor type and, to a lesser extent, by tumor progression and metastases.

 We next determined whether we could discriminate three different types of adenocarcinomas in the gastro-intestinal tract by analysis of the TEP-profiles, i.e., CRC, PAAD, and HBC. We developed a CRC/PAAD/HBC algorithm that correctly classified the mixed TEP samples (n = 90) with an overall accuracy of 76% (mean overall accuracy random classifiers: 42%, SD: ± 5%, p < 0.01,Figure 2C). In order to determine whether the TEP mRNA profiles allowed for multiclass cancer diagnosis across all tumor types and healthy donors, we extended the SVM/LOOCV classification test using a combination of algorithms that classified each individual sample of the training cohort (n = 175) as healthy donor or one of six tumor types (Figures S2D and S2E). The results of the multiclass cancer diagnostics test resulted in an average accuracy of 71% (mean overall accuracy random classifiers: 19%, SD: ± 2%, p < 0.01,Figure 2D), demonstrating significant multiclass cancer discriminative power in the platelet mRNA profiles. The classification capacity of the multiclass SVM-based classifier was confirmed in the validation cohort of 108 samples, with an overall accuracy of 71% (Figure 2E). An overall accuracy of 71% might not be sufficient for introduction into cancer diagnostics. However, of the initially misclassified samples according to the SVM algorithms choice with strongest classification strength the second ranked classification was correct in 60% of the cases. This yields an overall accuracy using the combined first and second ranked classifications of 89%. The low validation score of HBC samples can be attributed to the relative low number of samples and possibly to the heterogenic nature of this group of cancers (hepatocellular cancers and cholangiocarcinomas).
large Image

Tumor-Educated Platelet mRNA Profiles for Multiclass Cancer Diagnostics

(A) Heatmaps of unsupervised clustering of platelet mRNA profiles of healthy donors (HD; n = 55) (red) and patients with non-small cell lung cancer (NSCLC; n = 60), colorectal cancer (CRC; n = 41), glioblastoma (GBM; n = 39), pancreatic cancer (PAAD, n = 35), breast cancer (BrCa; n = 39; female HD; n = 29), and hepatobiliary cancer (HBC; n = 14).

(B) ROC-curve of SVM diagnostics of healthy donors and individual tumor classes in both training (left) and validation (right) cohort. Random classifiers, indicating the classification accuracies obtained by chance, are shown in gray.

(C) Confusion matrix of multiclass SVM/LOOCV diagnostics of patients with CRC, PAAD, and HBC. Indicated are detection rates as compared to the actual classes in percentages.

(D) Confusion matrix of multiclass SVM/LOOCV diagnostics of the training cohort consisting of healthy donors (healthy) and patients with GBM, NSCLC, PAAD, CRC, BrCa, and HBC. Indicated are detection rates as compared to the actual classes in percentages.

(E) Confusion matrix of multiclass SVM algorithm in a validation cohort (n = 108). Indicated are sample numbers and detection rates in percentages. Genes, number of mRNAs included in training of the SVM algorithm.

See also Figure S2 and Tables S4, S5, and S6.

Companion Diagnostics Tumor Tissue Biomarkers Are Reflected by Surrogate TEP mRNA Onco-signatures

Blood provides a promising biosource for the detection of companion diagnostics biomarkers for therapy selection (Bettegowda et al., 2014, Crowley et al., 2013,Papadopoulos et al., 2006). We selected platelet samples of patients with distinct therapy-guiding markers confirmed in matching tumor tissue. Although the platelet mRNA profiles contained undetectable or low levels of these mutant biomarkers, the TEP mRNA profiles did allow to distinguish patients with KRASmutant tumors from KRAS wild-type tumors in PAAD, CRC, NSCLC, and HBC patients, and EGFR mutant tumors in NSCLC patients, using algorithms specifically trained on biomarker-specific input gene lists (all p < 0.01 versus random classifiers, Figures 3A–3E ; Table S4). Even though the number of samples analyzed is relatively low and the risk of algorithm overfitting needs to be taken into account, the TEP profiles distinguished patients with HER2-amplified, PIK3CA mutant or triple-negative BrCa, and NSCLC patients with MET overexpression (all p < 0.01 versus random classifiers, Figures 3F–3I).

 We subsequently compared the diagnostic accuracy of the TEP mRNA classification method with a targeted KRAS (exon 12 and 13) and EGFR (exon 20 and 21) amplicon deep sequencing strategy (∼5,000× coverage) on the Illumina Miseq platform using prospectively collected blood samples of patients with localized or metastasized cancer. This method did allow for the detection of individual mutant KRAS and EGFR sequences in both plasma DNA and platelet RNA (Table S7), indicating sequestration and potential education capacity of mutant, tumor-derived RNA biomarkers in TEPs. Mutant KRAS was detected in 62% and 39%, respectively, of plasma DNA (n = 103, kappa statistics = 0.370, p < 0.05) and platelet RNA (n = 144, kappa statistics = 0.213, p < 0.05) of patients with a KRAS mutation in primary tumor tissue. The sensitivity of the plasma DNA tests was relatively poor as reported by others (Bettegowda et al., 2014, Thierry et al., 2014), which may partly be attributed to the loss of plasma DNA quality due to relatively long blood sample storage (EDTA blood samples were stored up to 48 hr at room temperature before plasma isolation). To discriminate KRAS mutant from wild-type tumors in blood, the TEP mRNA profiles provided superior concordance with tissue molecular status (kappa statistics = 0.795–0.895, p < 0.05) compared to KRAS amplicon sequencing analysis of both plasma DNA and platelet RNA (Table S7). Thus, TEP mRNA profiles can harness potential blood-based surrogate onco-signatures for tumor tissue biomarkers that enable cancer patient stratification and therapy selection.
large Image

Tumor-Educated Platelet mRNA Profiles for Molecular Pathway Diagnostics

Cross tables of SVM/LOOCV diagnostics with the molecular markers KRAS in (A) CRC, (B) PAAD, and (C) NSCLC patients, (D) KRAS in the combined cohort of patients with either CRC, PAAD, NSCLC, or HBC, (E) EGFR and (F) MET in NSCLC patients, (G) PIK3CA mutations, (H) HER2-amplification, and (I) triple negative status in BrCa patients. Genes, number of mRNAs included in training of the SVM algorithm. See alsoTables S4 and S7.

TEP-Profiles Provide an All-in-One Biosource for Blood-Based Liquid Biopsies in Patients with Cancer

Unequivocal discrimination of primary versus metastatic nature of a tumor may be difficult and hamper adequate therapy selection. Since the TEP profiles closely resemble the different tumor types as determined by their organ of origin—regardless of systemic dissemination—this potentially allows for organ-specific cancer diagnostics. Hence we selected all healthy donors and all patients with primary or metastatic tumor burden in the lung (n = 154), brain (n = 114), or liver (n = 127). We performed “organ exams” and instructed the SVM/LOOCV algorithm to determine for lung, brain, and liver the presence or absence of cancer (96%, 91%, and 96% accuracy, respectively), with cancer subclassified as primary or metastatic tumor (84%, 93%, and 90% accuracy, respectively) and in case of metastases to identify the potential organ of origin (64%, 70%, and 64% accuracy, respectively). The platelet mRNA profiles enabled assignment of the cancer to the different organs with high accuracy (Figure 4). In addition, using the same TEP mRNA profiles we were able to again indicate the biomarker status of the tumor tissues (90%, 82%, and 93% accuracy, respectively) (Figure 4).

large Image

Organ-Focused TEP-Based Cancer Diagnostics

SVM/LOOCV diagnostics of healthy donors (n = 55) and patients with primary or metastatic tumor burden in the lung (n = 99; totaling 154 tests), brain (n = 62; totaling 114 tests), or liver (n = 72; totaling 127 tests), to determine the presence or absence of cancer, with cancer subclassified as primary or metastatic tumor, in case of metastases the identified organ of origin, and the correctly identified molecular markers. Of note, at the exam level of mutational subtypes some samples were included in multiple classifiers (i.e., KRAS, EGFR, PIK3CA,HER2-amplification, MET-overexpression, or triple negative status), explaining the higher number in mutational tests than the total number of included samples. TP, true positive; FP, false positive; FN, false negative; TN, true negative. Indicated are sample numbers and detection rates in percentages.

Discussion

The use of blood-based liquid biopsies to detect, diagnose, and monitor cancer may enable earlier diagnosis of cancer, lower costs by tailoring molecular targeted treatments, improve convenience for cancer patients, and ultimately supplements clinical oncological decision-making. Current blood-based biosources under evaluation demonstrate suboptimal sensitivity for cancer diagnostics, in particular in patients with localized disease. So far, none of the current blood-based biosources, including plasma DNA, exosomes, and CTCs, have been employed for multiclass cancer diagnostics (Alix-Panabières and Pantel, 2014, Bettegowda et al., 2014, Skog et al., 2008), hampering its implementation for early cancer detection. Here, we report that molecular interrogation of blood platelet mRNA can offer valuable diagnostics information for all cancer patients analyzed—spanning six different tumor types. Our results suggest that platelets may be employable as an all-in-one biosource to broadly scan for molecular traces of cancer in general and provide a strong indication on tumor type and molecular subclass. This includes patients with localized disease possibly allowing for targeted diagnostic confirmation using routine clinical diagnostics for each particular tumor type.

Since the discovery of circulating tumor material in blood of patients with cancer (Leon et al., 1977) and the recognition of the clinical utility of blood-based liquid biopsies, a wealth of studies has assessed the use of blood for cancer diagnostics, prognostication and treatment monitoring (Alix-Panabières et al., 2012, Bidard et al., 2014, Crowley et al., 2013, Haber and Velculescu, 2014). By development of highly sensitive targeted detection methods, such as targeted deep sequencing (Newman et al., 2014), droplet digital PCR (Bettegowda et al., 2014), and allele-specific PCR (Maheswaran et al., 2008, Thierry et al., 2014), the utility and applicability of liquid biopsies for clinical implementation has accelerated. These advances previously allowed for a pan-cancer comparison of various biosources and revealed that in >75% of cancers, including advanced stage pancreas, colorectal, breast, and ovarian cancer, cell-free DNA is detectable although detection rates are dependent on the grade of the tumor and depth of analysis (Bettegowda et al., 2014). Here, we show that the platelet RNA profiles are affected in nearly all cancer patients, regardless of the type of tumor, although the abundance of tumor-associated RNAs seems variable among cancer patients. In addition, surrogate RNA onco-signatures of tissue biomarkers, also in 88% of localized KRAS mutant cancer patients as measured by the tumor-specific and pan-cancer SVM/LOOCV procedures, are readily available from a minute amount (100–500 pg) of platelet RNA. As whole blood can be stored up to 48 hr on room temperature prior to isolation of the platelet pellet, while maintaining high-quality RNA and the dominant cancer RNA signatures, TEPs can be more readily implemented in daily clinical laboratory practice and could potentially be shipped prior to further blood sample processing.

Blood platelets are widely involved in tumor growth and cancer progression (Gay and Felding-Habermann, 2011). Platelets sequester solubilized tumor-associated proteins (Klement et al., 2009) and spliced and unspliced mRNAs (Calverley et al., 2010, Nilsson et al., 2011), whereas platelets do also directly interact with tumor cells (Labelle et al., 2011), neutrophils (Sreeramkumar et al., 2014), circulating NK-cells (Palumbo et al., 2005, Placke et al., 2012), and circulating tumor cells (Ting et al., 2014, Yu et al., 2013). Interestingly, in vivo experiments have revealed breast cancer-mediated systemic instigation by supplying circulating platelets with pro-inflammatory and pro-angiogenic proteins, supporting outgrowth of dormant metastatic foci (Kuznetsov et al., 2012). Using a gene ontology methodology, CAGE, we correlated TEP-cancer signatures with publicly available curated datasets. Indeed, we identified widespread correlations with cancer tissues, hypoxia, platelet-signatures, and cytoskeleton, possibly reflecting the “alert” and pro-tumorigenic state of TEPs. We observed strong negative correlations with RNAs implicated in RNA translation, T cell immunity, and interleukin-signaling, implying diminished needs of TEPs for RNAs involved in these biological processes or orchestrated translation of these RNAs to proteins (Denis et al., 2005). We observed that the tumor-specific educational programs in TEPs are predominantly influenced by tumor type and, to a lesser extent, by tumor progression and metastases. Although we were not able to measure significant differences between non-metastasized and metastasized tumors, we do not exclude that the use of larger sample sets could allow for the generation of SVM algorithms that do have the power to discriminate between certain stages of cancer, including those with in situ carcinomas and even pre-malignant lesions. In addition, different molecular tumor subtypes (e.g., HER2-amplified versus wild-type BrCa) result in different effects on the platelet profiles, possibly caused by different “educational” stimuli generated by the different molecular tumor subtypes (Koboldt et al., 2012). Altogether, the RNA content of platelets in patients with cancer is dependent on the transcriptional state of the bone-marrow megakaryocyte (Calverley et al., 2010, McAllister and Weinberg, 2014), complemented by sequestration of spliced RNA (Nilsson et al., 2011), release of RNA (Clancy and Freedman, 2014, Kirschbaum et al., 2015, Rak and Guha, 2012, Risitano et al., 2012), and possibly queue-specific pre-mRNA splicing during platelet circulation. Partial or complete normalization of the platelet profiles following successful treatment of the tumor would enable TEP-based disease recurrence monitoring, requiring the analysis of follow-up platelet samples. Future studies will be required to address the tumor-specific “educated” profiles on both an (small non-coding) RNA (Laffont et al., 2013, Landry et al., 2009, Leidinger et al., 2014, Lu et al., 2005) and protein (Burkhart et al., 2014,Geiger et al., 2013, Klement et al., 2009) level and determine the ability of gene ontology, blood-based cancer classification.

In conclusion, we provide robust evidence for the clinical relevance of blood platelets for liquid biopsy-based molecular diagnostics in patients with several types of cancer. Further validation is warranted to determine the potential of surrogate TEP profiles for blood-based companion diagnostics, therapy selection, longitudinal monitoring, and disease recurrence monitoring. In addition, we expect the self-learning algorithms to further improve by including significantly more samples. For this approach, isolation of the platelet fraction from whole blood should be performed within 48 hr after blood withdrawal, the platelet fraction can subsequently be frozen for cancer diagnosis. Also, future studies should address causes and anticipated risks of outlier samples identified in this study, such as healthy donors classified as cancer patients. Systemic factors such as chronic or transient inflammatory diseases, or cardiovascular events and other non-cancerous diseases may also influence the platelet mRNA profile and require evaluation in follow-up studies, possibly also including individuals predisposed for cancer.

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Chi-Ping Day, Glenn Merlino, Terry Van Dyke
Cell, Vol. 163, Issue 1, p39–53
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Katherine A. Hoadley, Christina Yau, Denise M. Wolf, Andrew D. Cherniack, David Tamborero, Sam Ng, Max D.M. Leiserson, Beifang Niu, Michael D. McLellan, Vladislav Uzunangelov, Jiashan Zhang, Cyriac Kandoth, Rehan Akbani, Hui Shen, Larsson Omberg, Andy Chu, Adam A. Margolin, Laura J. van’t Veer, Nuria Lopez-Bigas, Peter W. Laird, Benjamin J. Raphael, Li Ding, A. Gordon Robertson, Lauren A. Byers, Gordon B. Mills, John N. Weinstein, Carter Van Waes, Zhong Chen, Eric A. Collisson, The Cancer Genome Atlas Research Network, Christopher C. Benz, Charles M. Perou, Joshua M. Stuart
Cell, Vol. 158, Issue 4, p929–944
Published online: August 7, 2014

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Liposomes, Lipidomics and Metabolism

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Building a Better Liposome

Computational models suggest new design for nanoparticles used in targeted drug delivery.

http://www.technologynetworks.com/Metabolomics/news.aspx?ID=184147

Using computational modeling, researchers at Carnegie Mellon University, the Colorado School of Mines and the University of California, Davis have come up with a design for a better liposome. Their findings, while theoretical, could provide the basis for efficiently constructing new vehicles for nanodrug delivery.

Liposomes are small containers with shells made of lipids, the same material that makes up the cell membrane. In recent years, liposomes have been used for targeted drug delivery. In this process, the membrane of a drug-containing liposome is engineered to contain proteins that will recognize and interact with complementary proteins on the membrane of a diseased or dysfunctional cell. After the drug-containing liposomes are administered, they travel through the body, ideally connecting with targeted cells where they release the drug.

liposome_853x480-min.jpg

This packaging technique is often used with highly toxic nanodrugs, like chemotherapy drugs, in an attempt to prevent the free drug from damaging non-cancerous cells. However, studies of this model of delivery have shown that in many cases less than 10 percent of the drugs transported by liposomes end up in tumor cells. Often, the liposome breaks open before it reaches a tumor cell and the drug is absorbed into the body’s organs, including the liver and spleen, resulting in toxic side effects.

“Even with current forms of targeted drug delivery, treatments like chemotherapy are still very brutal. We wanted to see how we could make targeted drug delivery better,” said Markus Deserno, professor of physics at Carnegie Mellon and a member of the university’s Center for Membrane Biology and Biophysics.

Deserno and colleagues propose that targeted drug delivery can be improved by making more stable liposomes. Using three different types of computer modeling, they have shown that liposomes can be made sturdier by incorporating a nanoparticle core made of a material like gold or iron and connecting that core to the liposome’s membrane using polymer tethers. The core and tethers act as a hub-and-spoke-like scaffold and shock-absorber system that help the liposome to weather the stresses and strains it encounters as it travels through the body to its target.

Francesca Stanzione and Amadeu K. Sum of the Colorado School of Mines conducted a fine-grained simulation that looked at how the polymer tethers anchor the liposome’s membrane at an atomistic level. Roland Faller of UC Davis did a meso-scale simulation that looked how a number of tethers held on to a small patch of membrane. Each of these simulations allowed researchers to look at smaller components of the liposome, nanoparticle core and tethers, but not the entire structure.

To see the entire structure, Carnegie Mellon’s Deserno and Mingyang Hu developed a coarse-grained model that represents groupings of components rather than individual atoms. For example, one lipid in the cell membrane might have 100 atoms. In a fine-grain simulation, each atom would be represented. In Deserno’s coarse grain simulation, those atoms might be represented by only three pieces instead of 100.

“Its unfeasible to look at the complete construct at an atomistic level. There are too many atoms to consider, and the timescale is too long. Even with the most advanced supercomputer, we wouldn’t have the power to run an atom-level simulation,” Deserno said. “But the physics that matters isn’t locally specific. It’s more like soft matter physics, which can be described at a much coarser resolution.”

Deserno’s simulation allowed the researchers to see how the entire reinforced liposome construct responded to stress and strain. They proposed that if a liposome was given the right-sized hub and tethers, its membrane would be much more resilient, bending to absorb impact and pressure.

Additionally, they were able to simulate how to best assemble the liposome, hub and tether system. They found that if the hub and tether are attached and placed in a solution of lipids, and solvent conditions are suitably chosen, a correctly sized liposome would self-assemble around the hub and tethers.

The researchers hope that chemists and drug developers will one day be able to use their simulations to determine what size core and polymer tethers they would need to effectively secure a liposome designed to deliver a specific drug or other nanoparticle. Using such simulations could narrow down the design parameters, speed up the development process and reduce costs.

 

Lipotype GmbH and NIHS Collaborate

http://www.technologynetworks.com/Metabolomics/news.aspx?ID=184363

NIHS to use the Lipotype Shotgun Lipidomics Technology for lipid analysis.

Lipotype GmbH and the Nestlé Institute of Health Sciences (NIHS) have collaborated to employ the innovative Lipotype Shotgun Lipidomics Technology to analyze lipids in blood for nutritional research. Recently, Lipotype and NIHS have jointly published results of the robustness of the Lipotype Technology. Lipotype envisions a future use of its technology in clinical diagnostics screens for establishing reliable lipid diagnostic biomarkers.

Innovative Lipotype Technology for lipid analysis
The purpose of this collaboration is to enable NIHS to use the Lipotype Shotgun Lipidomics Technology for lipid analysis. The mass spectrometry-based Lipotype technology covers a broad spectrum of lipid molecules and delivers quantitative results in high-throughput. The Nestlé Institute of Health Sciences uses this technology platform for nutritional research. NIHS is a specialized biomedical research institute and is part of Nestlé’s global Research & Development network.

Joint research project reveals robustness of Lipotype Technology
During the collaboration, Lipotype and NIHS conducted a joint research project and demonstrated that the Lipotype technology was robust enough to deliver data with high precision and negligible technical variation between different sites. In addition, important features are the high coverage and throughput, which were confirmed when applying the Lipotype technology.

Lipotype envisions these as important features, required for future use in clinical diagnostics screens, in order to establish and validate reliable lipid diagnostic biomarkers. The results have been published in October 2015, in the European Journal of Lipid Science and Technology (Surma et al. “An Automated Shotgun Lipidomics Platform for High Throughput, Comprehensive, and Quantitative Analysis of Blood Plasma Intact Lipids.”).

Lipids play an important role for health and disease
Lipotype is a spin-off company of the Max-Planck-Institute of Molecular Cell Biology and Genetics in Dresden, Germany. Prof. Kai Simons, CEO of Lipotype explains: “We developed a novel Shotgun-Lipidomics technology to analyze lipids in blood and other biological samples. Our analysis is quick and covers hundreds of lipid molecules at the same time. Our technology can be used to identify disease related lipid signatures.”

 

New Treatment for Obesity Developed

http://www.technologynetworks.com/Metabolomics/news.aspx?ID=183998

Researchers at the University of Liverpool, working with a global healthcare company, have helped develop a new treatment for obesity.
The treatment, which is a once-daily injectable derivative of a metabolic hormone called GLP-1 conventionally used in the treatment of type 2 diabetes, has proved successful in helping non-diabetic obese patients lose weight.

Professor John Wilding, who leads Obesity and Endocrinology research in the Institute of Ageing and Chronic Disease, investigates the pathophysiology and treatment of both obesity and type 2 diabetes and is applying his expertise in this area to work with, and often act as a consultant for, a number of large pharmaceutical companies looking to develop new treatments for obesity and diabetes.

Exciting development

Professor Wilding, said: “The biology of GLP-1 has been a focus of my research for 20 years; in particular when I was working at Hammersmith Hospital in London, I was part of the team that demonstrated that it was involved in appetite regulation; work on GLP-1 has continued during my time in Liverpool. Being involved in the development of a treatment, from the basic research right through to clinical trials in patients is very exciting”.

“It is likely that the treatment will be used initially in very specific situations, such as helping patients who are severely obese. It differs from current treatments used for diabetes, as it has stronger appetite regulating effects but no greater effect on glucose control.”

In 2014 more than 1.9 billion adults worldwide were classed as obese by the World Health Organisation; in the UK numbers have more than tripled since 1980. This Obesity can lead to other serious health-related illnesses including type 2 diabetes, hypertension and obstructive sleep apnoea as well as increasing the risk for many common cancers.

The drug has been approved in the European Union, but has not yet launched in the UK.

Professor Wilding added: “Consultancy like this can help relationship and reputation building and informs my research keeping it at the forefront of developments. It also brings many other benefits such as publications and income generation, which can help support other research, for example by such as funding for pilot projects that can lead to grant applications and investigator-initiated trials funded by the company”.

 

Evidence of How Incurable Cancer Develops

http://www.technologynetworks.com/Metabolomics/news.aspx?ID=184346

Researchers in the West Midlands have made a breakthrough in explaining how an incurable type of blood cancer develops from an often symptomless prior blood disorder.

The findings could lead to more effective treatments and ways to identify those most at risk of developing the cancer.

All patients diagnosed with myeloma, a cancer of the blood-producing bone marrow, first develop a relatively benign condition called ‘monoclonal gammopathy of undetermined significance’ or ‘MGUS’.

MGUS is fairly common in the older population and only progresses to cancer in approximately one in 100 cases. However, currently there is no way of accurately predicting which patients with MGUS are likely to go on to get myeloma.

Myeloma is diagnosed in around 4,000 people each year in the UK. It specifically affects antibody-producing white blood cells found in the bone marrow, called plasma cells. The researcher team from the University of Birmingham, New Cross and Heartlands Hospitals compared the cellular chemistry of bone marrow and blood samples taken from patients with myeloma, patients with MGUS and healthy volunteers.

Surprisingly, the researchers found that the metabolic activity of the bone marrow of patients with MGUS was significantly different to plasma from healthy volunteers, but there were very few differences at all between the MGUS and myeloma samples. The research was funded by the blood cancer charity Bloodwise, which changed its name from Leukaemia & Lymphoma in September.

The findings suggest that the biggest metabolic changes occur with the development of the symptomless condition MGUS and not with the later progression to myeloma.

Dr Daniel Tennant, who led the research at the University of Birmingham, said, “Our findings show that very few changes are required for a MGUS patient to progress to myeloma as we now know virtually all patients with myeloma evolve from MGUS. A drug that interferes with these specific initial metabolic changes could make a very effective treatment for myeloma, so this is a very exciting discovery.”

The research team found over 200 products of metabolism differed between the healthy volunteers and patients with MGUS or myeloma, compared to just 26 differences between MGUS patients and myeloma patients. The researchers believe that these small changes could drive the key shifts in the bone marrow required to support myeloma growth.

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 Update on Chronic Myeloid Leukemia

Curator: Larry H Bernstein, MD, FCAP

 

Diagnosis and Treatment of Chronic Myeloid Leukemia in 2015
Philip A. Thompson, Hagop M. Kantarjian, Jorge E. Cortes,
Department of Leukemia, The University of Texas, MD Anderson Cancer Center, Houston
DOI: http://dx.doi.org/10.1016/j.mayocp.2015.08.010

Target Audience: The target audience for Mayo Clinic Proceedings is primarily internal medicine physicians and other clinicians who wish to advance their current knowledge of clinical medicine and who wish to stay abreast of advances in medical research.
Statement of Need: General internists and primary care physicians must maintain an extensive knowledge base on a wide variety of topics covering all body systems as well as common and uncommon disorders. Mayo Clinic Proceedings aims to leverage the expertise of its authors to help physicians understand best practices in diagnosis and management of conditions encountered in the clinical setting.
Learning Objectives: On completion of this article, you should be able to (1) identify clinical and laboratory features consistent with a diagnosis of chronic myeloid leukemia (CML) and diagnose the disease based on laboratory testing; (2) identify factors associated with poor treatment outcomes and how these are identified and managed; and (3) describe standard first and second line therapeutic options for CML and their adverse effects.
In their editorial and administrative roles, William L. Lanier, Jr, MD, Terry L. Jopke, Kimberly D. Sankey, and Nicki M. Smith, MPA, have control of the content of this program but have no relevant financial relationship(s) with industry.
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Questions? Contact dletcsupport@mayo.edu.
Article Outline
I. Clinical Features
A. Presenting Hematologic Parameters
II. Differential Diagnosis
A. Chronic Myelomonocytic Leukemia
B. Atypical CML
C. Chronic Neutrophilic Leukemia
D. Essential Thrombocythemia
E. Diagnostic Workup
III. Determining Prognosis in CP-CML at Baseline
IV. Response Definitions
V. Routine Monitoring Schedule
VI. Initial Treatment of CP-CML
A. Which TKI and Dose?
VII. Treatment Objectives
A. Achievement of CCyR and MMR/MR3.0
B. Definitions of Treatment Failure
VIII. Treatment of Patients With Primary or Secondary Treatment Failure Who Remain in CP
A. Switching to a Second TKI
IX. Stopping Treatment in Patients With Prolonged CMR
X. Treatment of AP-CML
XI. Treatment of BP-CML
A. Treatment of LBP
B. Treatment of MBP
C. Which TKI Should Be Used in BP-CML?
D. Treatment of Refractory and Relapsed BP
XII. Conclusion
XIII. References

Abstract
Few neoplastic diseases have undergone a transformation in a relatively short period like chronic myeloid leukemia (CML) has in the last few years. In 1960, CML was the first cancer in which a unique chromosomal abnormality was identified and a pathophysiologic correlation suggested. Landmark work followed, recognizing the underlying translocation between chromosomes 9 and 22 that gave rise to this abnormality and, shortly afterward, the specific genes involved and the pathophysiologic implications of this novel rearrangement. Fast forward a few years and this knowledge has given us the most remarkable example of a specific therapy that targets the dysregulated kinase activity represented by this molecular change. The broad use of tyrosine kinase inhibitors has resulted in an improvement in the overall survival to the point where the life expectancy of patients today is nearly equal to that of the general population. Still, there are challenges and unanswered questions that define the reasons why the progress still escapes many patients, and the details that separate patients from ultimate cure. In this article, we review our current understanding of CML in 2015, present recommendations for optimal management, and discuss the unanswered questions and what could be done to answer them in the near future.
Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm, characterized by the unrestrained expansion of pluripotent bone marrow stem cells.1 The hallmark of the disease is the presence of a reciprocal t(9;22)(q34;q11.2), resulting in a derivative 9q+ and a small 22q−. The latter, known as the Philadelphia (Ph) chromosome, results in a BCR-ABL fusion gene and production of a BCR-ABL fusion protein2; BCR-ABL has constitutive tyrosine kinase activity3 and is necessary and sufficient for production of the disease.4 In a few cases (5%-10%), the Ph chromosome is cytogenetically cryptic, often due to a complex translocation, and the diagnosis requires fluorescence in situ hybridization (FISH) to reveal the BCR-ABL fusion gene or polymerase chain reaction (PCR) to reveal the BCR-ABL messenger RNA transcript.5 A 210-kDa BCR-ABL transcript (p210) transcribed from the most common rearrangements between exons 13 or 14 of BCR and exon 2 of ABL (known as e13a2 [or b2a2] and e14a2 [or b3a2], respectively) is most common, but rare cases will have alternative BCR-ABL breakpoints, leading to a p190 transcript (from the e1a2 rearrangement, most typically seen in Ph-positive acute lymphoblastic leukemia [ALL]) or a p230 transcript.5 Indication of the typical hematopathologic features and the t(9;22)(q34;q11.2) by conventional cytogenetics or FISH and/or BCR-ABL by PCR is required for diagnosis.5

Clinical Features
Up to 50% of patients are asymptomatic and have their disease diagnosed incidentally after routine laboratory evaluation.6 Clinical features, when present, are generally nonspecific. Splenomegaly is present in 46% to 76%6, 7 and may cause left upper quadrant pain or early satiety, fatigue, night sweats, symptoms of anemia, and bleeding due to platelet dysfunction may occur, the last occurring most commonly in patients with marked thrombocytosis. Less than 5% of patients present with symptoms of hyperviscosity, including priapism, which are generally seen when the presenting white cell count exceeds 250,000/μL.7
The disease is classically staged into chronic phase (CP, most patients at presentation), accelerated phase (AP), and blast phase (BP).5 Many definitions have been used for these stages, but all the data generated from the tyrosine kinase inhibitor (TKI) studies have used the historically standard definition in which AP is defined by the presence of one or more of the following: 15% or more blasts in peripheral blood and bone marrow, 20% or more basophils in peripheral blood, and platelet counts less than 100,000/μL unrelated to treatment or the development of cytogenetic evolution. The blast phase is defined by the presence of 30% or more blasts in the peripheral blood or bone marrow, the presence of clusters of blasts in marrow, or the presence of extramedullary disease with immature cells (ie, a myeloid sarcoma).8 Progression to BP occurs at a median of 3 to 5 years from diagnosis in untreated patients, with or without an intervening identifiable AP.6

Presenting Hematologic Parameters
Characteristic complete blood cell count features are as follows: absolute leukocytosis (median leukocyte count of 100,000/μL) with a left shift and classic “myelocyte bulge” (more myelocytes than the more mature metamyelocytes seen on the blood smear); usual blast counts of less than 2%; nearly universal absolute basophilia, with absolute eosinophilia in 90% of cases5; monocytosis but generally not an increased monocyte percentage; absolute monocytosis in the unusual cases with a p190 BCR-ABL9; normal or elevated platelet count; and thrombocytopenia, which suggests an alternative diagnosis or the presence of AP, rather than CP, disease.

Differential Diagnosis
The differential diagnosis for chronic phase CML (CP-CML) includes the following Ph-negative conditions.

Chronic Myelomonocytic Leukemia
Chronic myelomonocytic leukemia is a myelodysplastic/myeloproliferative neoplasm that can be distinguished from CML by the presence of dysplastic features, more prominent cytopenias, more prominent monocytosis, and lack of basophilia. Chronic myelomonocytic leukemia is Ph negative and may have other cytogenetic abnormalities.5

Atypical CML
Atypical CML is a Ph-negative myelodysplastic/myeloproliferative neoplasm.

Chronic Neutrophilic Leukemia
Rare cases of CML with a p230 BCR-ABL transcript may be mistaken for chronic neutrophil leukemia (CNL) because of the predominant neutrophilia associated with this version of CML, but cytogenetics revealing the Ph chromosome will easily distinguish them. Importantly, this and other atypical rearrangements might not be detected by some standard PCR methods. The presence of these abnormalities should be suspected in instances where the Ph chromosome is detected by routine karyotype but with PCR “negative” for BCR-ABL, hence the importance of cytogenetic evaluation in all patients at baseline.

Essential Thrombocythemia
Rare cases of CML may present with isolated thrombocytosis, without leukocytosis. Basophilia is often present as a diagnostic clue. These cases will be distinguished by cytogenetics and molecular studies revealing Ph positivity and BCR-ABL positivity.10

Diagnostic Workup
The diagnosis will usually be suspected from the complete blood cell count and blood smear. FISH for t(9;22)(q34;q11.2) and quantitative reverse transcriptase PCR (qRT-PCR) for BCR-ABL can be performed on peripheral blood. However, bone marrow aspirate and unilateral biopsy with conventional cytogenetics and flow cytometry are essential at the time of diagnosis to exclude unrecognized advanced-stage disease and to detect rare cases with an alternative BCR-ABL transcript not detected by routine BCR-ABL PCR. Flow cytometry will identify cases with unrecognized progression to lymphoid blast crisis by their phenotypic features, whereas conventional karyotyping may identify additional cytogenetic abnormalities (cytogenetic clonal evolution).

Determining Prognosis in CP-CML at Baseline
The prognosis of CP-CML has markedly improved since the development of TKIs. The stage of disease is the most important prognostic feature. Most patients presenting with CP-CML achieve long-term control, and stem cell transplant is only needed in a few. Several prognostic scoring systems have been developed to assess the risk of poor outcome at presentation: the Sokal score11 and Hasford score were developed in the pre-imatinib era12 but retain prognostic significance in imatinib-treated patients. An online calculator is available to compute both these scores at http://www.leukemia-net.org/content/leukemias/cml/cml_score/index_eng.html. Approximately 25% of high-risk patients fail to achieve complete cytogenetic response (CCyR) with imatinib-based treatment by 18 months; this and other important therapeutic milestones are discussed in detail subsequently. A simpler system based on basophil percentage in peripheral blood and spleen size, the European Treatment and Outcome Study (EUTOS) system, found that 34% of high-risk patients fail to achieve CCyR by 18 months.13Notwithstanding the appeal of the simplicity of the EUTOS score, its predictive value has not been universally confirmed.14, 15 The prognostic relevance of these classifications is ameliorated but not completely eliminated among patients treated with second-generation TKIs. Currently, we do not make treatment decisions based solely on these risk scores.
Other proposed pretreatment predictors include the level of CML cell membrane expression of the organic cation transporter-1 (OCT-1). OCT-1 is required for entry of imatinib into the cell; this protein (and its corresponding RNA) can be measured, and higher levels of expression and/or activity are associated with superior survival in imatinib-treated patients.16 Importantly, patients with lesser OCT-1 activity may benefit more from higher starting doses of imatinib.16 OCT-1 activity is not important for nilotinib-17 or dasatinib-treated patients because these drugs are not OCT-1 substrates.18

Response Definitions
Dynamic response assessment is essential to identify patients at high risk of disease progression, who may benefit from a change of therapy. Response definitions are given in Table 1.19 A complete hematologic response (CHR) is defined by clinical and peripheral blood criteria. Cytogenetic response is classified according to the percentage of Ph-positive metaphases by routine karyotype on bone marrow aspiration. A CCyR has also been defined in some instances by interphase FISH on peripheral blood as the absence of detectable BCR-ABL fusion in at least 200 examined nuclei.20 Molecular testing for BCR-ABL transcripts using qRT-PCR is more sensitive for low-level residual disease than cytogenetics or FISH (sensitivity of 10−4 to 10−5). Levels of response in this qRT-PCR assay are clinically relevant and reported as a percentage of the transcript levels of a normal housekeeper gene, such as ABL1 or BCR. Given that assays used by different laboratories have significantly different sensitivities, attempts have been made to harmonize reporting by developing the international scale. By parallel testing of samples with a reference laboratory, laboratory-specific conversion factors are produced to correct for differing sensitivities and allow a laboratory to report BCR-ABL transcript levels in a more uniform way.21 A World Health Organization standard material has also been developed for assay calibration.22 Major molecular response (MMR or MR3.0) corresponds to less than 0.1% BCR-ABL on the international scale, which represents a 3-log reduction from the standardized baseline rather than a 3-log reduction from the individual patient’s baseline BCR-ABL transcript level (which can vary significantly).23 MR4.0is less than 0.01% bcr-abl on the international scale, and MR4.5 is 0.0032% or less on the international squale (equivalent to a ≥4.5-log reduction), which is the limit of sensitivity of many assays. There is also a fair correlation between transcript levels and depth of cytogenetic response such that transcript levels of 1% on the international scale are grossly equivalent to a CCyR.
Table 1Definitions of Response
Response Definition
CHR Leukocyte count <10 × 109/L, basophils <5%, platelets <450 × 109/L, the absence of immature granulocytes, impalpable spleen
Minor CyR 36%-95% Ph+ metaphases in bone marrow
Major CyR 1%-35% Ph+ metaphases in bone marrow
CCyR 0% Ph+ metaphases in bone marrow
MMR BCR-ABL International Scale ≤0.1%
CMR Undetectable BCR-ABL with assay sensitivity ≥4.5 or 5.0 logs
CHR = complete hematologic response; CMR = complete molecular response; CyR = cytogenetic response; MMR = major molecular response; Ph = Philadelphia chromosome.

Routine Monitoring Schedule
Different monitoring schedules have been proposed, with the aim of early identification of patients who are not achieving therapeutic milestones and are therefore at higher risk of disease progression. Our own practice is to monitor the complete blood cell count every 1 to 2 weeks for the first 2 to 3 months to identify treatment-related cytopenias and the achievement of complete hematologic response. Most instances of grade 3 to 4 myelosuppression occur in the first few months. Thus, once the peripheral blood cell counts become stable, monitoring with complete blood cell count can be reduced to every 4 to 6 weeks and eventually every 3 to 6 months. In addition, BCR-ABL qRT-PCR is performed from peripheral blood every 3 months until the achievement of MMR then every 6 months thereafter. We perform a bone marrow aspiration with cytogenetics every 6 months until achievement of stable CCyR. This allows not only for the confirmation of CCyR but also for the discovery of chromosomal abnormalities in the emerging Ph-negative metaphases, a phenomenon that occurs in 10% to 15% of patients and may be associated with eventual development of myelodysplastic syndrome or acute myeloid leukemia.24, 25, 26 Subsequently, bone marrow examination only need be performed in the following circumstances: failure to achieve therapeutic milestones; evaluation of a significant, unexplained increase in BCR-ABL after initial response, not attributable to lack of adherence (see later sections for evaluation of suboptimal response or loss of response); to monitor known chromosomal abnormalities in Ph-negative metaphases; and to investigate unexplained cytopenia(s).

Initial Treatment of CP-CML
The TKIs have transformed outcomes in CML. The pivotal International Randomized Study of Interferon and STI571 (IRIS) study found far superior rates of CHR, CCyR, and MMR in imatinib- compared with interferon-treated patients and a superior progression-free survival (PFS).27, 28 Before IRIS, other than interferon-based therapy, allogeneic stem cell transplant (alloSCT) was the treatment of choice for eligible patients and achieved long-term disease-free survival (DFS) in approximately 50% to 85% of patients29, 30, 31, 32, 33 due to a graft-vs-leukemia effect.34 AlloSCT is associated with a unique toxicity profile, particularly opportunistic infections and graft-vs-host disease, resulting in treatment-related mortality of 5% to 20% and significant morbidity in many long-term survivors. Combined with the marked success of TKIs, alloSCT is now reserved for patients with advanced-stage disease or treatment failure; this is discussed in more detail in later sections.

Which TKI and Dose?
Three TKIs are now approved by the Food and Drug Administration for initial treatment of CP-CML: imatinib, nilotinib and dasatinib. Debate continues regarding the optimal initial TKI and dose, with compelling arguments supporting each. A number of studies have attempted to improve on results achieved with 400 mg/d of imatinib.
Shortly after imatinib was introduced as frontline therapy for CML, studies focused on use of higher doses to improve outcome.35 The single-arm TIDEL (Therapeutic Intensification in De Novo Leukemia) study, in which patients were treated with 600 mg/d of imatinib, found superior rates of MMR at 12 and 24 months in those patients able to maintain a daily mean of 600 mg of imatinib for the first 6 months36; in our experience, 400 mg of imatinib twice daily was associated with superior cumulative rates of CCyR and MMR relative to a historical control cohort and was generally well tolerated, with 82% of patients continuing to take at least 600 mg/d.37, 38In a confirmatory randomized study, the German CML study group reported that an initial imatinib dose of 800 mg was associated with higher rates of MMR at 12 months than 400 mg of imatinib or 400 mg of imatinib plus interferon alfa (59% vs 44% vs 46%). The mean daily dose tolerated in the group assigned to 800 mg of imatinib was 628 mg because of the higher adverse event profile of higher doses.39 The higher initial dose was also associated with more rapid achievement of MR4.5. There was, however, no event-free survival (EFS) or survival benefit, relative to 400 mg/d of imatinib.
Combinations of imatinib and interferon have been reported in several randomized trials, with mixed results. The French SPIRIT (STI571 Prospective International Randomized Trial) study and a Nordic group found higher rates of MMR at 12 months for patients receiving imatinib plus pegylated interferon alfa 2a or pegylated interferon alfa 2b, respectively, but no difference in CCyR.40, 41 In contrast, the German CML study group found no difference in MMR at 12 months between 400 mg of imatinib with or without nonpegylated interferon alfa,39and there was no difference in the rates of CCyR or MMR when pegylated interferon alfa 2b was combined with 800 mg/d of imatinib compared with imatinib alone.42 All studies have found poor tolerability of interferons with high rates of discontinuation, and none have found PFS or survival benefit.
Ten years ago, the first studies using second-generation TKI as initial therapy for CML were initiated, which found very high rates of CCyR and MMR using first-line dasatinib, 100 mg/d or 50 mg twice daily,43 and nilotinib, 400 mg twice daily.44, 45 Two major company-sponsored randomized studies later confirmed these results, comparing second-generation TKIs to imatinib, 400 mg/d. The Evaluating Nilotinib Efficacy and Safety in Clinical Trials-Newly Diagnosed Patients study (ENEST-nd) compared imatinib, 400 mg, to nilotinib, 300 mg, twice daily and nilotinib, 400 mg, twice daily. Nilotinib at both doses was associated with more, faster, and deeper responses and higher freedom from progression. The 400-mg twice-daily dose was associated with a small, but statistically significant, improvement in overall survival (OS) compared with 400 mg of imatinib; however, the results were also notable for a significantly higher incidence of major arteriothrombotic events, including ischemic heart disease, cerebrovascular accidents, and peripheral arterial disease (especially at 400 mg twice daily).46 The Dasatinib versus Imatinib Study in Treatment-Naive CML Patients (DASASION) compared 400 mg/d of imatinib with 100 mg/d of dasatinib. More, faster, and deeper responses were seen, with fewer transformations to AP and BP, but at 5 years of follow-up (the end of the study), there was still no PFS or OS benefit.47 A frequent (although usually grade 1 or 2) adverse effect of dasatinib is the development of pleural effusions, which may require dose adjustments and occasionally thoracentesis. Of some concern, also, was the development of pulmonary hypertension, which was diagnosed in 8 patients by echocardiographic criteria; however, only one patient had right-heart catheterization, which did not confirm pulmonary hypertension.
Imatinib, 400 mg, has also been compared with bosutinib, 500 mg. Faster and deeper responses, with a higher rate of MMR (but not CCyR, the primary end point) at 12 months, were seen in the bosutinib group, leading to fewer transformations. There was a higher rate of treatment discontinuation in the bosutinib arm, particularly due to diarrhea and liver function test abnormalities.48 A second randomized trial, using a lower starting dose of bosutinib (400 mg/d), has been initiated, seeking regulatory approval for this indication.
Ponatinib is a highly potent TKI and is the only TKI with activity in patients with the T315I mutation in ABL1. Because of the high level of preclinical and clinical activity of ponatinib in the salvage setting,49 it was also investigated as frontline therapy. Both a single-arm, phase 2 study50 and a randomized phase 3 study were conducted, the latter comparing 400 mg of imatinib with 45 mg of ponatinib.51 Ponatinib treatment resulted in faster and deeper responses, including very high rates of early MR4.5. Both studies reported a 3-month rate of BCR-ABL/ABL less than 10% of 94%, the highest of any study with TKI. Unfortunately, the high rate of major arterial thrombotic events (7% in the ponatinib arm vs 1% in the imatinib arm) and pancreatitis led to the 2 studies being terminated early at a median follow-up of 23 and 5.1 months, respectively.51
We believe that imatinib, dasatinib, and nilotinib all constitute adequate treatment options for patients with CML at the time of diagnosis. Outside clinical trials, the decision regarding which TKI to use should be tailored to an individual patient and depends on an assessment of factors such as the relative risk of the disease, risk factors for specific adverse events (eg, arteriothrombotic events, pleural effusion, pulmonary hypertension, poorly controlled diabetes, and pancreatitis), possible effect of the dose administration schedule, and cost. In patients with a poorer likelihood of responding to 400 mg of imatinib (eg, those with high Sokal scores or those with e1a2 CML), a second-generation TKI might be preferred. Patients with low OCT-1 activity may also benefit from high-dose imatinib or a second-generation TKI, but this test is not clinically available in the United States. In contrast, in patients with lower-risk disease or those with a higher risk for arteriothrombotic events, imatinib might be preferred. Higher doses of imatinib might offer similar efficacy benefits as dasatinib or nilotinib (eg, similar rates of early responses and transformation to AP and BP).50 Although higher-dose imatinib is associated with increased incidence of some adverse events, these usually consist of peripheral edema, muscle cramps, and gastrointestinal toxicity, but not arteriothrombotic events. Specific agents may be avoided because of their particular toxicity profiles; for example, it may be preferable not to use nilotinib in a patient with a history of coronary artery disease or with several coronary risk factors, and dasatinib may be avoided in patients who have tenuous respiratory function because of the risk of pleural effusions. Increasingly, pharmacoeconomic concerns may drive therapeutic decision making; generic imatinib will soon be available, and there will be a substantial cost differential between imatinib and second-generation TKIs, which no doubt will be a factor in the decision-making process.

Treatment Objectives
Response definitions according to hematologic, cytogenetic, and molecular criteria are given in Table 1.19, 52 It is important to remember that different laboratories have different BCR-ABL qRT-PCR sensitivity, and quantitative results may differ markedly.53 If the laboratory does not report results on the international scale, BCR-ABL should be monitored in the same laboratory for consistency. In addition, MMR cannot be adequately identified if a laboratory does not report on the international scale, increasing the importance of cytogenetic analysis for response assessment.

Achievement of CCyR and MMR/MR3.0
The European LeukemiaNet (ELN) 2013 guidelines (Table 2) place a strong emphasis on the importance of achieving MMR, ideally by the 12-month time point. This is achieved by 1 year in 18% to 58% of patients taking 400 mg of imatinib and 43% to 77% taking 600 to 800 mg.19 This is based on data from long-term follow-up of IRIS,54 which found that, of patients in MMR at 18 months, only 3% lost CCyR, compared with 26% of patients with BCR-ABL levels of greater than 0.1% to less than 1.0%. The key transcript levels at the 6-, 12-, and 18-month landmarks found to be associated with favorable EFS were 10% or less, 1% or less, and 0.1% or less, respectively.54, 55 Despite the importance of achieving MMR with imatinib, however, there are no data to indicate that switching therapy in a patient in the ELN warning (formerly suboptimal response) category improves outcome.56 In addition, our own data suggest that achievement of MMR offers no EFS or survival advantage over the achievement of CCyR by 12 or 18 months during frontline treatment with second-generation TKIs; achievement of CCyR by 3 months should be considered optimal response in this setting, with PCyR considered suboptimal.57 In a combined analysis of patients receiving either imatinib or second-generation TKIs, patients achieving CCyR by 6 months have a 97% 3-year EFS on landmark analysis, which was the major point of difference, and this did not differ according to subsequent achievement of MMR or not.58
Table 2European LeukemiaNet (ELN) Response Criteriaa
Optimal Warning Failure
Baseline NA High risk or CCA/Ph+, major route NA
3 mo BCR-ABL1 ≤10% and/or Ph+ ≤35% BCR-ABL1 >10% and/or Ph+ 36%-95% Non-CHR and/or Ph+ >95%
6 mo BCR-ABL1 <1% and/or Ph+ 0 BCR-ABL1 1%-0% and/or Ph+ 1%-35% BCR-ABL1 >10% and/or Ph+ >35%
12 mo BCR-ABL1 ≤0.1% (ie, MMR) BCR-ABL1 >0.1%-1% (ie, lack of MMR) BCR-ABL1 >1% and/or Ph+ >0% (ie, lack of CCyR)
Then and at any time BCR-ABL1 ≤0.1% CCA/Ph− (−7, or 7q−) Loss of CHR

Loss of CCyR

Confirmed loss of MMRb

Mutations

CCA/Ph+
aCCA/Ph+ = clonal cytogenetic abnormalities in Ph-positive cells; CCA/Ph− = clonal cytogenetic abnormalities in Ph-negative cells; CCyR = complete cytogenetic response; MMR = major molecular response; NA = not applicable; Ph = Philadelphia chromosome.
bIn 2 consecutive tests, at least one of which has BCR-ABL transcripts of 1% or greater.
Several studies38, 47, 55, 56, 59 also support achievement of BCR-ABL of 10% or less at 3 months as an important goal. Patients with this level of response at 3 months have an improved long-term outcome (EFS and OS) compared with those who have more than 10% transcripts. Although this has triggered recommendations for change in therapy for patients without this depth of response, no data suggest that the change in therapy alters the long-term outcome. Furthermore, even when those with slower responses have a worse outcome, the EFS at 5 years is approximately 80% in all series. Changing therapy for all represents an overreaction for most patients who will still have a favorable outcome. In fact, with additional assessment at 6 months, 30% to 50% will catch up in their response, and these patients have a similarly favorable outcome as if they had achieved the less than 10% BCR-ABL/ABL at 3 months.60 Adding more than one time point thus improves the prognostication abilities of early response. The rate of change of BCR-ABL transcripts in the first 3 months of therapy may also be important; patients with BCR-ABL greater than 10% at 3 months had superior outcomes if they had a halving time of less than 76 days.61 Patients who receive less than 80% of the target dose of imatinib, either because of dose reductions or because of missed doses, have a significantly lower probability of achieving the optimal response. Thus, at the moment, it is most prudent to minimize unnecessary treatment interruptions and dose reductions and to monitor patients carefully at early time points. No change in therapy is indicated until there is clear evidence of failure as defined by the ELN.

Definitions of Treatment Failure
Primary treatment failure can be defined as failure to achieve CHR and less than 95% Ph positive at 3 months, less than 10% BCR-ABL and Ph less than 35% at 6 months, or less than 1% BCR-ABL and CCyR at 12 months. This occurs in approximately 25% of imatinib-treated patients.19 Progression to AP and BP defines treatment failure at any point. Secondary treatment failure is loss of response after initially meeting treatment targets. Loss of response is defined as loss of CCyR, loss of CHR, or progression to AP and BP. Loss of response should not be defined on the basis of a single qRT-PCR result due to potential fluctuations inherent in testing method. Increasing molecular markers on 2 occasions should prompt further investigation.62, 63However, only 11% of patients in CCyR who have increasing molecular markers develop clinical events (loss of CCyR, loss of CHR, development of AP and BC), and switching TKIs has not been found to benefit patients with only molecular relapse but without loss of CCyR.64 Similarly, although ELN recommends the appearance of mutations to be considered treatment failure, it is not advised to investigate the presence of mutations unless there is clinical evidence of treatment failure. Furthermore, if a mutation were to be identified in a patient with adequate response, there is no evidence suggesting that change of therapy at that time improves outcome compared with change when clinical failure becomes evident, further supporting the recommendation to only test for mutations in instances of clinical failure.
Causes of treatment failure are diverse.65 Poor adherence is the most frequent cause of treatment failure and must be carefully evaluated. BCR-ABL mutations, which alter drug binding by directly altering an amino acid at the drug-binding site (eg, T315I, F317L, F359C/V) or indirectly by altering protein conformation (eg, G250E, Q252H, E255K/V), are crucial to identify because they determine sensitivity to salvage therapy and the subsequent choice of TKI. Other potential causes include pharmacokinetic interactions, such as accelerated TKI metabolism due to use of CYP3A4 hepatic enzyme inducers, or the use of proton pump inhibitors, which inhibit drug absorption. Diverse mechanisms may result in lower drug concentration within the cell despite adequate plasma levels, such as p-glycoprotein or ABCG2 drug efflux protein overexpression (affecting imatinib, nilotinib, and dasatinb), or low OCT1 activity, which is required for imatinib transportation into the cell (see earlier). Finally, overexpression of the Src kinase Lyn66 has been reported in some instances of resistance, but the incidence of this phenomenon is unknown.
Changes in BCR-ABL transcript levels may be associated with disease progression or development of resistance. However, identification of a sustained increase and an increasing trend are more important than a single increase, given the fluctuation that can occur in the assay results. In addition, the kinetics of change in BCR-ABL may vary according to the type of loss of response: patients with a rapid increase in BCR-ABL generally have disease progression to AP and BP or are nonadherent with therapy; in contrast, patients who have developed BCR-ABL1 mutations generally have a more gradual increase in BCR-ABL transcripts.63 An increase in BCR-ABL on a single occasion, particularly if the increase is greater than 5-fold or if MMR is lost, should prompt questioning regarding adherence to therapy and an early additional BCR-ABL qRT-PCR. If the rise is confirmed and adherence is not thought responsible, bone marrow aspiration should be performed to assess for the presence of disease progression, cytogenetic evolution, and BCR-ABL1 mutations. As mentioned previously, routine testing for mutations in patients with adequate response is not warranted. Even in the instance of suboptimal response or warning, mutations are identified in less than 5% of instances.

Treatment of Patients With Primary or Secondary Treatment Failure Who Remain in CP
Treatment of patients with refractory disease still in CP depends on several factors, particularly the type of initial therapy, the presence of BCR-ABL1 mutations, adherence, comorbidities, and eligibility for alloSCT.67 Patients who meet the definition of failure per the ELN have a shortened survival, with a median of approximately 5 years, and thus need a change in therapy.68 No randomized comparisons of switching to a second TKI compared with performing alloSCT exist, but our practice is to treat with at least a second TKI; patients are closely monitored. Although eligible patients for alloSCT should be considered for this approach if meeting failure criteria after a second TKI, in practice, most patients prefer to try a third TKI; still, a discussion about alloSCT should be held after initial failure.

Switching to a Second TKI
Six-year results of switching to dasatinib after imatinib failure or intolerance have been reported and reveal PFS and OS of 49% and 71% at 6 years, respectively. The CCyR rates were less than 50%, and the MMR rate was approximately 40% in long-term follow-up69; importantly, early responses (BCR-ABL <10% at 3 months) predicted longer-term outcomes. Comparable results have been reported with nilotinib, 400 mg twice daily, with the option to escalate to 600 mg twice daily, with a 4-year OS of 78%, PFS of 57%, and CCyR rate of 45%.70 Finally, bosutinib is active in imatinib-resistant patients, including all those with ABL1 mutations except T315I, at a dose of 500 mg/d; CCyR was achieved in 41% of patients with a 2-year PFS of 73% in imatinib-refractory patients and 95% in imatinib-intolerant patients. Bosutinib has an adverse effect profile that does not overlap substantially with the other TKIs, with the most frequent adverse events being diarrhea, rash, and biochemical liver function abnormalities.48 The drug is approved by the Food and Drug Administration for patients in whom at least one TKI has previously failed. Higher response rates to second-line TKI after imatinib failure are seen in patients with a low baseline Sokal risk score, greater depth of initial cytogenetic response with imatinib (particularly if CCyR was achieved), lack of recurrent neutropenia during imatinib therapy, and a good performance status.71, 72
Identification of specific BCR-ABL1 mutations is critical to subsequent TKI choice. Patients with a T315I mutation are resistant to all TKIs except ponatinib. Patients with the F317L mutation are resistant to dasatinib but responsive to nilotinib. Y253H, E255K/V, and F359V/C mutations are resistant to nilotinib but sensitive to dasatinib. There are no randomized studies to guide choice of subsequent TKI; however, changing to dasatinib is superior to increasing imatinib dose.73 Although the three second-generation TKIs have never been compared head to head, it appears that they have somewhat equivalent efficacy and can be selected based on known mutations, risk factors for toxicity, and schedule preferences. Still, despite the overall good results, less than 50% of patients achieve a CCyR with either of these drugs. Thus, better second-line treatment options are needed. In addition, for patients treated with second-generation TKI as frontline therapy, the results with any of these agents as second-line therapy are not known but are expected to be inferior to what is achieved when used after imatinib failure. Ponatinib is a logical candidate to fill this void, but unfortunately there is limited experience in this setting. Still, in instances of resistance to a second-generation TKI used as initial therapy, we usually select ponatinib as second line provided the patient does not have excessive risk factors for arteriothrombotic events. It is clear then that, despite the many good treatment options available in CML, new drugs or new approaches would still be welcome for the relatively small percentage of patients facing this clinical scenario.
Patients in whom 2 TKIs failed have more limited options, and treatment should be individualized. In the absence of BCR-ABL1 mutations predicted to produce resistance, nilotinib or dasatinib could be used, although there is limited, mostly retrospective, data with these agents. Bosutinib was prospectively investigated and is active in patients with failure of 2 previous TKIs, with a CCyR rate of 22% to 40% and 2-year PFS of 73%.74, 75 The PACE (Ponatinib Ph ALL and CML Evaluation) study found that 45 mg/d of ponatinib is highly active, achieving a 63% CCyR rate in a heavily pretreated population (>90% of patients had previously received at least 2 TKIs, and nearly 60% had previously received at least 3 TKIs). A subgroup analysis of the PACE study found equivalent efficacy for patients with the T315I mutation, who are resistant to all other TKIs.76Ponatinib has therefore been approved for patients with the T315I mutation or for whom no other TKI is indicated, under a risk evaluation and mitigation strategy, due to the risk of arterial thrombotic events.77Omacetaxine is a non-TKI protein synthesis inhibitor, given by subcutaneous injection for 14 days in a 28-day cycle, that is approved by the Food and Drug Administration for patients in whom 2 or more TKIs have failed.78In a phase 2 study in patients in whom 2 TKIs had previously failed, the rates of CHR, minor cytogenic response, and CCyR were 67%, 22%, and 4%, respectively79; in addition, the drug is active in patients with T315I mutation. In a separate phase 2 study, the rates of CHR and CCyR were 77% and 16%, respectively. However, PFS was only 7.7 months.80 The drug is associated with substantial myelosuppression.79, 80Although these results are more modest than those seen with TKIs, we use omacetaxine in instances where TKIs have failed or may not be indicated because of unacceptably high risk of specific adverse events.
AlloSCT should be considered for patients with CP-CML in whom 2 TKIs have failed. There are no data to guide the choice between third-line TKI or alloSCT, and this decision must therefore be individualized. However, the relatively low rates of CCyR and 2-year PFS with bosutinib and the risk of cardiovascular toxicity of ponatinib suggest that alloSCT should be considered in eligible patients; conversely, there are limited data on transplant outcomes in these heavily pretreated patients. A recent German CML study group study found that, provided they remain in CP, patients who undergo transplant after imatinib failure have excellent results post-alloSCT, with an 89% achievement of CMR after transplant, a treatment-related mortality of 6%, and a 3-year survival of 94%.81 Whether these impressive results can be replicated in patients who have experienced resistance to 2 or more TKIs remains to be seen.

Stopping Treatment in Patients With Prolonged CMR
Overall, 41% to 47% of patients who have been in continuous CMR for at least 24 months may remain with stable undetectable transcripts after ceasing imatinib.82, 83, 84 If recurrence up to the level of MMR is tolerated, the success rate increases to approximately 60%. Predictors of increased relapse likelihood in this setting include a high baseline Sokal risk score and a duration of imatinib therapy of less than 5 years.82 Continuous CMR for more than 64 months and treatment with a second-generation TKI may be associated with lower incidence of relapse after TKI cessation.84 Relapses occur most frequently within approximately 6 months; notably, most patients remain imatinib sensitive and regain CMR when use of the drug is recommenced.85However, the follow-up is still relatively short. Therefore, one needs to consider that late relapses after interferon therapy or alloSCT occurring more than 10 years after cessation of therapy may occur, and these are often in the lymphoid BP. Thus, continued monitoring is required, perhaps indefinitely, through peripheral blood PCR. Most patients who stop taking imatinib and maintain undetectable transcripts by standard qRT-PCR still have evidence of low-level disease when more sensitive, patient-specific DNA-based PCR assays are used.83 In addition, some patients have low-level fluctuation of BCR-ABL levels detected by standard RNA-based qRT-PCR, without experiencing true molecular relapse.85 The reasons for the lack of relapses in these patients are unclear, but it has been suggested that these patients may have an increased number of natural killer cells that may contribute to keeping the disease at bay.86
Although reported to be safe in relatively small numbers of patients in the clinical trial setting, this approach should only be undertaken in a clinical study or where a protocol for prospective, very close monitoring of patients is implemented to allow detection of early relapses and intervene promptly.

Treatment of AP-CML
Criteria for the diagnosis of AP-CML have been outlined earlier. ABL1 mutations increase in frequency in advanced-stage disease; mutational evaluation should therefore be performed and TKI choice based on this.62, 67 The optimal therapeutic approach in AP-CML differs according to whether the patient is TKI naive or has progressed from CP while taking a TKI. Eighty to ninety percent of treatment-naive patients will achieve CCyR with TKI87, 88 and have a similar EFS and OS to patients presenting in CP, particularly when treated with second-generation TKI. Those patients with cytogenetic clonal evolution as the only criterion for AP also have superior outcomes to those with hematologic and clinical features of AP.89 In contrast, much lower response rates and inferior EFS, with continued relapses, have been seen in studies of second-generation TKIs in patients with imatinib failure and AP disease.90, 91
Treatment options include a TKI or alloSCT (either de novo or after initial TKI therapy). There are no randomized data to guide the choice or dose of TKI. However, there is a suggestion from nonrandomized studies that second-generation TKIs have superior response rates to imatinib,87 and ponatinib provides perhaps the best outcome.
There are also no randomized data to guide the decision to perform alloSCT for patients with AP-CML. In the pre-imatinib era, patients transplanted in AP had 30% to 40% DFS at 4 years compared with 70% to 80% for CP.92, 93 Nonrandomized data suggest superior outcomes in patients treated with imatinib followed by alloSCT compared with imatinib alone, but there is the standard selection bias in this study.94
In summary, patients with de novo AP-CML may have good outcomes, particularly if treated with a second-generation TKI. We treat these patients following the same guidelines we use for CP patients, and alloSCT is only considered on failure of 2 TKIs. However, patients with AP developing after imatinib failure have significantly poorer outcomes and may be best treated more aggressively with a second-generation TKI followed by alloSCT when eligible. Patients with excellent, rapid responses to the second TKI may be followed up closely and alloSCT considered only if showing recurrence. Another important question for which there are no data to guide decisions is the role of maintenance TKI after transplant. Our practice is to continue prescribing TKI after transplant after count recovery for patients who previously progressed to AP or BP.

Treatment of BP-CML
Criteria for BP progression were outlined above. Approximately 50% to 60% of patients have myeloid blast phase (MBP) and 20% to 30% lymphoid blast phase (LBP). The remaining 10% to 30% are mixed.5 The aim of treatment is to achieve reversion to CP, then perform alloSCT with or without posttransplant TKI maintenance.

Treatment of LBP
Induction chemotherapy is given as per de novo ALL, with the addition of a TKI. Chemotherapy with hyperfractionated cyclophosphamide, vincristine, doxorubicin (adriamycin), and dexamethasone (hyper-CVAD) with a TKI can achieve CHR in approximately 90% of patients.95 Most patients will have previously received a TKI. However, in patients presenting with de novo transformation, it is important (although sometimes difficult) to distinguish CML in LBP from Ph-positive ALL. Morphologic criteria to suggest preexisting CML, such as monolobated megakaryocytes and basophilia, may be useful, as is the BCR-ABL transcript type; p210 BCR-ABL is present in most CML-LBP, whereas most Ph-positive ALL has the p190 transcript. Mutations in BCR-ABL1 in patients in whom imatinib therapy has failed are more frequent in BP (73%) relative to C and/AP96; the use of ABL1 mutational analysis to guide treatment is therefore essential. T315I is very frequent and, in contrast to CP, may be identified even before exposure to a TKI. These patients require treatment with ponatinib, usually combined with chemotherapy (hyper-CVAD, in our hands). Additional chromosomal abnormalities are frequent (particularly monosomy 7),95 and outcomes are generally poor. AlloSCT after initial response appears to improve outcomes, but selection bias in such studies is inevitable.96

Treatment of MBP
CML-MBP has a poor response to standard acute myeloid leukemia induction regimens.97 Patients with de novo MBP may respond to TKI monotherapy, but responses are shallow and transient.98, 99 There are few studies of AML induction chemotherapy or low-dose cytarabine combined with TKI.100, 101 Our general approach is to give standard acute myeloid leukemia induction chemotherapy with the addition of a TKI and perform alloSCT in responding patients.102 Although outcome for patients with prior BP is better when there is only minimal residual disease or no detectable disease even by PCR, we recommend alloSCT as soon as a patient is back to CP or has CHR because continued chemotherapy is no guarantee of improved response and may cause complications that can disqualify the patient for a later transplant.

Which TKI Should Be Used in BP-CML?
There are no head-to-head data in this area, and much existing data concern use of single-agent TKIs, which are rarely used in practice. Imatinib, 600 mg, results in shallow and transient single-agent responses.98, 99Imatinib does not cross the blood brain barrier and so is inadequate when central nervous system involvement exists.103, 104 Dasatinib, 140 mg/d, achieves a significantly higher rate of CCyR (26% and 46% in MBP and LBP, respectively), but responses are again transient, with a median survival of less than 12 months for MBP and less than 6 months for LBP.105 Although dasatinib crosses the blood brain barrier, we do not rely on this for prophylaxis or management of central nervous system disease and give standard treatment with intrathecal chemotherapy, high-dose systemic chemotherapy, and occasionally radiotherapy to approach this issue. Nilotinib, 400 mg twice daily, is associated with no better results compared with dasatinib and is not approved for this indication.70 Bosutinib is also approved for BP and may induce hematologic response in 28% and minor cytogenic response in 37%.106 Ponatinib has resulted in favorable response in heavily pretreated patients and patients with T315I mutations. Approximately 50% patients had a hematologic response after failure of dasatinib or nilotinib in MBP or LBP,107 and 18% achieved CCyR. The 1-year survival was an impressive 55%. Whenever possible, we use ponatinib because this might be the most effective agent and covers all mutations. Dasatinib and bostunib are suitable alternatives.

Treatment of Refractory and Relapsed BP
Novel agents for ALL, such as the CD22-immunoconjugate inotuzumab ozogamicin and the CD3/19 bispecific antibody blinatumomab, are yet to be evaluated because major studies have excluded Ph-positive patients. However, these could potentially be effective, as could CAR T cells directed against CD19, although there would likely be potential for antigen-negative escape or development of frank myeloid reversion, and any response would require consolidation with alloSCT.

Conclusion
Although CML remains one of the great success stories in modern oncology treatment, a number of challenges remain. Pre-treatment identification of patients likely to have poor outcomes is crude at best, and predictive tools to guide the optimal choice of TKI at baseline are not widely available, making treatment decisions largely empiric. Patients with failure of more than 1 TKI have relatively poor outcomes, and no data exist for second-line therapy for patients treated initially with a second-generation TKI. The mechanisms underlying the risk of arteriothrombotic events seen with several of the TKIs need to be better understood so that prevention and management can be approached more rationally. Finally, most patients require indefinite suppressive therapy, with an associated cumulative risk of potential toxic effects, particularly cardiovascular disease, as well as chronic, low-grade toxic effects that affect quality of life. Strategies to produce eradication of MRD, with minimal toxic effects, are essential to address these issues and to reduce the long-term pharmacoeconomic burden of indefinite TKI therapy.

References
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6. Faderl, S., Talpaz, M., Estrov, Z., O’Brien, S., Kurzrock, R., and Kantarjian, H.M. The biology of chronic myeloid leukemia. N Engl J Med. 1999; 341: 164–172
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7. Savage, D.G., Szydlo, R.M., and Goldman, J.M. Clinical features at diagnosis in 430 patients with chronic myeloid leukaemia seen at a referral centre over a 16-year period. Br J Haematol. 1997; 96:111–116
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Leukemia’s Molecular Biography Uncovered in New Genomic Study

GEN 10/15/2015

  • Click Image To Enlarge +
    A new study offers a glimpse of the wealth of information that can be gleaned by combing the genome of a large collection of leukemia tissue samples. [hidesy/iStock]

    Researchers from the Dana-Farber Cancer Institute and the Broad Institute of MIT and Harvard have harnessed the power of next-generation sequencing to analyze a large collection of leukemia tissue samples. Using whole exome sequencing (WES), the investigators screened genetic material from more than 500 samples of chronic lymphocytic leukemia (CLL) and normal tissue—identifying dozens of genetic drivers for the disease, including two genes that had previously not been linked to human cancer.

    The investigators began to trace how some mutations affect the course of the disease and its susceptibility to treatment. Moreover, they started tracking the evolutionary path of CLL, as its dynamic genome spawns new groups and subgroups of tumor cells within a single patient.

    “Sequencing the DNA of CLL has taught us a great deal about the genetic basis of the disease,” explained senior author Catherine Wu, M.D., physician at Dana-Farber and associate professor of medicine at Harvard Medical School. “Previous studies, however, were limited by the relatively small number of tumor tissue samples analyzed, and by the fact that those samples were taken at different stages of the treatment process, from patients treated with different drug agents.

    Dr. Wu continued, stating “in our new study, we wanted to determine if analyzing tissue samples from a large, similarly-treated group of patients provides the statistical power necessary to study the disease in all its genetic diversity—to draw connections between certain mutations and the aggressiveness of the disease, and to chart the emergence of new mutations and their role in helping the disease advance.  Our results demonstrate the range of insights to be gained by this approach.”

    The findings from this study were published recently in Nature through an article entitled “Mutations driving CLL and their evolution in progression and relapse.”

    The researchers collected tumor and normal tissue samples from 538 patients with CLL, 278 of whom had participated in a German clinical trial that helped determine the standard treatment for the disease. After WES analysis, they uncovered dozens of genetic abnormalities that may play a role in CLL, including 44 mutated genes and 11 genes that were over- or under-copied in CLL cells. Interestingly, two of the mutated genes—RPS15 and IKZF3—have not previously been associated with human cancer.

    “This study also provides a vision of what the next phase of large-scale genomic sequencing efforts may look like,” noted lead author Dan Landau M.D., Ph.D., research fellow at Dana-Farber and the Broad Institute. “The growing sample size allows us to start engaging deeply with the complex interplay between different mutations found in any individual tumor, as well as reconstructs the evolutionary trajectories in which these mutations are acquired to allow the malignancy to thrive and overcome therapy.”

    Another fascinating discovery was that certain gene mutations were particularly common in tumor tissue from patients who had already undergone treatment, suggesting that these mutations help the disease rebound after initial therapy. In addition, the investigators found that therapy tends to produce shorter remissions in patients whose tumors carry mutations in the genes TP53 or SF3B1.

    “We found that genomic evolution after therapy is the rule rather than the exception,” Dr. Wu remarked. “Certain mutations were present in a greater number of leukemia cells within a sample after relapse, showing that these mutations, presumably, allow the tumor to persevere.”

    Dr. Wu and her colleagues hope that the findings from their studies will continue the push initiated by precision medicine to help personalize cancer treatments and develop new therapeutics.

    “The breadth of our findings shows what we will be able to achieve as we systematically sequence and analyze large cohorts of tumor tissue samples with defined clinical status,” stated co-senior author Gad Getz, Ph.D., director of the Cancer Genome Computational Analysis group at the Broad Institute. “Our work has enabled us to discover novel cancer genes, begin to chart the evolutionary path of CLL, and demonstrate specific mutations affect patients’ response to therapy. These discoveries will form the basis for precision medicine of CLL and other tumor types.”

Aurelian Udristioiu commented on Update on Chronic Myeloid Leukemia

 Update on Chronic Myeloid Leukemia  Larry H Bernstein, MD, FCAP, Curator LPBI Diagnosis and Treatment of Chronic …

In previous work the diagnosis of LAM-3 I made based on blood smears, the examination of bone marrow (BM) aspirates, the evaluation of promyeloblasts (greater than 30% in BM), and the presence of a specific immune phenotype. Immunocytochemical detection was performed to confirm the diagnosis of LAM-3 using FAR Leukemia kits (Italy), and there were positive results for the peroxidase reaction for promyelocytes, myelocytes, granulocytes, and peripheral blood cells (POX+) and negative results for the peroxidase reaction for the blast cells. We performed the leukocyte alkaline phosphatase reaction using a SIGMA kit (www.sigmaaldrich.com) to determine the neutrophil alkaline phosphatase (NAP) levels in granulocytes (negative or low values in LAM-3) and to evaluate the alpha-naphthyl-esterase reaction in monocytes cells (positive results indicate CMoL).
Lactate dehydrogenase (LDH) is an enzyme that is localized to the cytosol of human cells and catalyzes the reversible reduction of pyruvate to lactate via using hydrogenated nicotinamide deaminase (NADH) as co-enzyme. The causes of high LDH and high Mg levels in the serum include neoplastic states that promote the high production of intracellular LDH and the increased use of Mg²+ during molecular synthesis: Pyruvate acid>> LDH/NADH >>Lactate acid + NAD).
LDH is released from tissues in patients with physiological or pathological conditions and is present in the serum as a tetramer that is composed of the two monomers LDH-A and LDH-B, which can be combined into 5 isoenzymes: LDH-1 (B4), LDH-2 (B3-A1), LDH-3 (B2-A2), LDH-4 (B1-A3) and LDH-5 (A4). The LDH-A gene is located on chromosome 11, whereas the LDH-B gene is located on chromosome 12. The monomers differ based on their sensitivity to allosteric modulators. They facilitate adaptive metabolism in various tissues. The LDH-4 isoform predominates in the myocardium, is inhibited by pyruvate and is guided by the anaerobic conversion to lactate. Total LDH, which is derived from hemolytic processes, is used as a marker for monitoring the response to chemotherapy in patients with advanced neoplasm with or without metastasis.
The number of chromosome copies in malignant tumors can be correlated with the total serum LDH values. LDH levels in patients with malignant disease are increased as the result of high levels of the isoenzyme LDH-3 in patients with hematological malignant diseases and of the high level of the isoenzymes LDH-4 and LDH-5, which are increased in patients with other malignant diseases of tissues such as the liver, muscle, lungs, and conjunctive tissues. High concentrations of serum LDH damage the cell membrane.
In aerobic glucose metabolism, the oxidation of citric acid requires ADP and Mg²+, which will increase the speed of the reaction: Iso-citric acid + NADP (NAD) — isocitrate dehydrogenase (IDH) = alpha-ketoglutaric acid.
In the Krebs cycle (the citric cycle), IDH1 and IDH2 are NADP+-dependent enzymes that normally catalyze the inter-conversion of D-isocitrate and alpha-ketoglutarate (α-KG). The IDH1 and IDH2 genes are mutated in > 75% of different malignant diseases. Two distinct alterations are caused by tumor-derived mutations in IDH1 or IDH2: the loss of normal catalytic activity in the production of α-ketoglutarate (α-KG) and the gain of catalytic activity to produce 2-hydroxyglutarate (2-HG).
This product is a competitive inhibitor of multiple α-KG-dependent dioxygenases, including demethylases, prolyl-4-hydroxylase and the TET enzymes family (Ten-Eleven Translocation-2), resulting in genome-wide alternations in histones and DNA methylation.
IDH1 and IDH2 mutations have been observed in myeloid malignancies, including de novo and secondary AML (15%–30%), and in pre-leukemic clone malignancies, including myelodysplastic syndrome and myeloproliferative neoplasm (85% of the chronic phase and 20% of transformed cases in acute leukemia).
Today, the oncologists try a new drug, anti-IDH mutant, to treat AML..

Dr. Aurelian Udristioiu, MD,
Emergency County Hospital TARGU-JIU &USB University,
Primary Physician of Laboratory Medicine,
General Chemical Pathology, EuSpLM,
City Targu Jiu, Romania
National Academy of Biochemical Chemistry (NACB) Member,
Washington D.C, USA.

Aurelian Udristioiu commented on your update
” The IDH1 and IDH2 genes are mutated in > 75% of different malignant diseases. Two distinct alterations are caused by tumor-derived mutations in IDH1 or IDH2: the loss of normal catalytic activity. IDH1 and IDH2 mutations have been observed in myeloid malignancies, including de novo and secondary AML (15%–30%), and in pre-leukemic clone malignancies, including myelodysplastic syndrome and myeloproliferative neoplasm (85% of the chronic phase and 20% of transformed cases in acute leukemia). Today, the oncologists try a new drug, anti-IDH mutant, to treat AML.”

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 Rituximab for a Variety of B-cell Malignancies

Curator: Larry H Bernstein, MD, FCAP

 

 

Impact of Rituximab (Rituxan) on the Treatment of B-Cell Non-Hodgkin’s Lymphoma

Non-Hodgkin’s lymphoma (NHL) is the most common hematological malignancy in adults, with B-cell lymphomas accounting for 85% of all NHLs. The most substantial advancement in the treatment of B-cell malignancies, since the advent of combination chemotherapy, has been the addition of the monoclonal anti-CD20 antibody rituximab (Rituxan). Since its initially reported single-agent activity in indolent lymphomas in 1997, the role of rituximab has expanded to cover both indolent and aggressive lymphomas.

This article focuses on the impact of rituximab on the treatment, survival, and long-term outcomes of patients with indolent and aggressive lymphomas over the past two decades.

Keywords: rituximab, non-Hodgkin’s lymphoma
Non-Hodgkin’s lymphoma (NHL) is the most common adult hematological cancer. In 2009, almost 66,000 cases were anticipated in the U.S. alone.1The incidence of NHL in the U.S. over the previous 15 years has increased by approximately 4% annually, despite the decline in age-adjusted incidence rates for all cancers combined.

NHL encompasses a heterogeneous group of lymphomas that have been classified in various ways. In 1995, the World Health Organization developed a classification that included a combination of morphology, immunotyping, genetic features, and clinical syndromes. The goal was to define disease entities of B cells, T cells, and natural killer (NK) cells that pathologists could recognize and that had clinical relevance. The lymphomas were further subdivided into categories based on their clinical behavior (indolent, aggressive, or highly aggressive).2 More recent updates of this classification have clarified some less common entities but have left the overall schema intact.3

B-cell lymphomas account for about 85% of all NHL diagnoses.4 Although many subtypes of NHL exist clinically, most are grouped as either indolent (characterized by a prolonged median survival but generally considered incurable) or aggressive (characterized by rapid growth but with the potential for cure). Because patients with indolent lymphoma eventually die with this disease if they do not die of intercurrent illness, new treatments are needed to prolong survival, with the ultimate goal to provide cure. For patients with aggressive lymphoma, unmet needs include higher initial cure rates, improved salvage chemotherapy options, and less toxic therapies for old and frail patients.

Conventional methods of treatment, including chemotherapy and radiation, are associated with toxicity and lack specific antitumor-targeted activity. Cell–surface proteins, such as CD19, CD20, and CD22, are highly expressed on B-cell lymphomas and represent key potential targets for treatment.

Antibody therapy directed against CD20 has had the most important clinical impact to date. CD20 is thought to be involved in the regulation of intracellular calcium, cell cycle, and apoptosis. CD20 is not shed, modulated, or internalized significantly upon antibody binding, thus making it an ideal target for passive immunotherapy.5

Over the past two decades, significant progress has been made in the development of new therapies for B-cell lymphoma. Perhaps the most important advance is the addition of rituximab (Rituxan, Genentech/Biogen Idec), which the FDA approved for use in the U.S. in 1997. Rituximab is a chimeric (mouse and human) monoclonal antibody directed against the B-cell antigen CD20. It depletes B cells by several mechanisms, including direct antibody-dependent cellular cytotoxicity (ADCC), complement-mediated cell death, and signaling apoptosis.611

Phase 1 trials of two doses of rituximab (500 mg/m2 and 375 mg/m2 for four weeks) showed clinical responses with no dose-limiting toxicity.12 The weekly 375-mg/m2 dose, given for four weeks, was selected for further phase 2 evaluation and is currently the standard single-agent dose and schedule. Since this first reported activity, the role of rituximab has expanded to include both indolent and aggressive lymphomas.

This article addresses the effect of rituximab on survival and long-term outcomes in patients with NHL.

Indolent, Low-Grade Lymphomas

Unlike aggressive lymphomas, indolent B-cell lymphomas are not considered curable with conventional therapies. Many patients are observed for prolonged periods without requiring treatment.13 In one study, more than 50% of the patients remained untreated for a median period of almost six years after diagnosis.14 Treatment goals focus on maintaining good quality of life with minimal symptoms. The indications for treatment include the presence of B symptoms (fevers, night sweats, and weight loss), compromise of normal organ function, bulky disease, or the presence of cytopenias resulting from marrow involvement. Transformation to an aggressive histological pattern warrants treatment for the aggressive component.

Although many active therapies are available for indolent NHL, patients ultimately die of this disease, which is incurable. Additional therapeutic options with improved efficacy and reduced toxicity are still needed for patients with indolent NHL. In light of this unmet need, the FDA’s approval of rituximab for the treatment of relapsed or refractory CD20-positive (CD20+) NHL in 1997 was an important clinical advance. The approval was based on the pivotal trial reported by McLaughlin et al., in which single-agent rituximab brought about significant response rates in heavily pretreated patients with indolent lymphoma.15

Initial Therapy for Indolent (Follicular) Lymphoma

Rituximab as first-line therapy has been widely studied in patients with indolent lymphomas, both as a single agent and in combination with conventional chemotherapy (Table 1). Witzig et al. evaluated the use of single-agent rituximab, 375 mg/m2 weekly for four doses, as an initial therapy for patients with stage III or IV grade 1 follicular lymphoma (FL). In this small phase 2 trial of only 37 patients, the reported objective response rate (ORR) was 72% and the complete remission rate (CRR) was 36%.16 Similarly, a phase 2 study by Hainsworth et al., which evaluated initial therapy in patients with indolent lymphomas, showed response rates in the range of 50%.17

Table 1

Randomized Trials Using Rituximab in First-Line and Relapsed Settings in Indolent Lymphomas

Using rituximab as a first-line therapy in patients with low-tumor-burden, indolent NHL, Colombat et al. reported an ORR of 73%.18 Long-term follow-up results of the completed randomized phase 3 Rituximab ExtendedSchedule Or Re-treatment Trial (RESORT, ECOG 4402 [Eastern Cooperative Oncology Group]) are still pending. In this randomized study, patients received four weekly rituximab treatments. Retreatment is then given as a single dose of rituximab every three months or upon disease progression with four weekly doses. The aim of the study is to define the benefit of maintenance therapy or re-treatment with rituximab (in terms of time to requiring a therapy other than rituximab) when progressive disease is documented.

The benefit of adding rituximab to combination chemotherapy during the initial treatment of FL has been documented in multiple clinical trials over the past decade. The phase 3 trial by Marcus et al. compared cyclophosphamide, vincristine, and prednisone (CVP), with and without rituximab, in 318 previously untreated patients with stage III and IV CD20+ FL.19 The addition of rituximab to CVP (R-CVP) significantly improved time to disease progression (34 months with R-CVP vs. 15 months with CVP, respectively; P < 0.0001) and duration of response (38 months vs. 14 months, respectively; P < 0.0001). Disease-free survival was 21 months with CVP but has not yet been determined in the group receiving R-CVP.

The East German Study Group evaluated the combination of rituximab with mitoxantrone, chlorambucil, and prednisone (MCP), followed by maintenance interferon in treatment-naive patients with stage III/IV CD20+ FL.20 The ORR was 92% with rituximab and 75% with chemotherapy alone (P = 0.0009).

Rituximab was also tested in combination with cyclophosphamide, hydroxydaunorubicin (doxorubicin), Oncovin (vincristine), and prednisone (R-CHOP) as first-line therapy in 428 patients with FL in a randomized phase 3 study with three years of follow-up.21 This combination showed a significant prolongation of time to treatment failure (P < 0.001) and prolonged duration of remission (P = 0.001) with the addition of rituximab. A higher ORR was observed in the group receiving R-CHOP (96%), compared with CHOP alone (90%) (P = 0.011). Even with a short follow-up, overall survival rates improved in the group receiving chemotherapy and rituximab (P = 0.016).

Similar results were seen in the GELA–GOELAMS FL 2000 trial (Groupe d’Etude des Lymphomes de l’Adulte/Groupe Ouest Est des Leucémies etAutres Maladies du Sang). This study was designed to examine the combination of rituximab with cyclophosphamide, hydroxydaunorubicin (doxorubicin), etoposide (VP-16), and prednisolone (CHVP) plus interferon-2 .22 A significant improvement in event-free survival at five years was noted for the rituximab patients (37% vs. 53%, respectively; P = 0.0004).

A meta-analysis of seven randomized controlled trials assessed the value of adding rituximab to conventional chemotherapy for 1,943 patients with FL, mantle-cell lymphoma, and other indolent lymphomas.23 This analysis demonstrated improved overall survival with the combination, as follows:

  • hazard ratio (HR) for mortality, 0.65
  • 95% confidence interval (CI), 0.51–0.79
  • disease control (HR for the disease event, 0.62; 95% CI, 0.55–0.71)
  • response rates (relative risk for response 1.21; 91% CI, 1.16–1.27)

Specifically in FL, overall survival was better with rituximab plus chemotherapy (HR for mortality, 0.60; 95% CI, 0.37–0.98).23 The study authors concluded that the combination of rituximab and chemotherapy for patients with indolent lymphomas was superior to chemotherapy alone with respect to overall survival, disease-free survival, and response rates.23

Relapsed/Refractory Indolent Non-Hodgkin’s Lymphoma

The pivotal trial upon which the initial approval of rituximab was based showed the drug’s efficacy as a single agent in relapsed/refractory indolent NHL.15 Re-treatment with rituximab alone in 57 patients with low-grade FL who had previously responded to single-agent rituximab yielded a response rate of 40% and a similar duration of response, indicating sensitivity to re-treatment with the same agent.24

Davis et al. studied the use of single-agent rituximab in patients with bulky lesions (larger than 10 cm) and relapsed NHL.25 Patients receiving rituximab 375 mg/m2 weekly for four doses had an ORR of 43%. Among patients with a partial response, lesion size decreased by 76%.

The addition of rituximab to standard chemotherapy was found to be beneficial in the treatment of FL patients with relapsed/refractory NHL (see Table 1). An international trial by van Oers et al. evaluated the combination of six cycles of CHOP with rituximab 375 mg/m2 given intravenously on day 1 of each cycle, compared with chemotherapy alone in 465 patients with advanced disease.26 The ORR was higher with the addition of rituximab (85% with R-CHOP vs. 72% with CHOP alone; P < 0.001), and the median progression-free survival rate was also significantly improved in the rituximab group (33.1 vs. 20 months; P < 0.001). The addition of rituximab to the combination of fludarabine, cyclophosphamide, and mitoxantrone (FCM) in a similar group of patients also showed superior responses.27

Rituximab with bendamustine (Treanda, Cephalon) was studied in a phase 2 trial in patients with relapsed disease. This combination was found to be very effective, with an ORR of 92%.28

Maintenance Therapy for Follicular Lymphoma

Some authors consider rituximab to be an ideal medication to use as maintenance therapy for an incurable disease such as FL because of its minimal toxicity and long half-life, which obviates the need for frequent administration.29 The use of rituximab as maintenance therapy after induction treatment has been the subject of several studies (Table 2) and is being evaluated by two large phase 3 trials: Primary Rituximab and Maintenance (PRIMA) and RESORT.30,31

Table 2

Trials Showing Benefit for Maintenance Rituximab after Induction Therapy for Indolent Lymphomas

In the PRIMA trial, patients with previously untreated FL requiring therapy received a rituximab–chemotherapy regimen designated by the participating center as R-CHOP, R-CVP, or R-FCM. Responding patients were then randomly assigned to receive observation or scheduled re-treatment with rituximab as a single dose every eight weeks for two years. The RESORT trial was designed for asymptomatic patients with low-tumor-burden, indolent NHL (as discussed in detail on page 149).

The Swiss Group for Clinical Cancer Research (SAKK) evaluated maintenance rituximab following induction with rituximab monotherapy in a phase 3 trial in patients with newly diagnosed NHL and in previously treated patients with FL.32 In this study, the maintenance schedule consisted of four infusions at two-month intervals. Event-free survival was significantly longer among patients who received this maintenance schedule.

A phase 2 trial by the Minnie Pearl Cancer Research Network compared maintenance rituximab (four weekly doses repeated every six months for two years) with re-treatment using rituximab upon disease progression.33The study showed significant prolongation of progression-free survival in the maintenance therapy group (31.3 vs. 7.4 months, respectively; P = 0.007), although no difference in overall survival or duration benefit from rituximab was observed between the two cohorts.

ECOG 1496 was a study that compared the use of maintenance rituximab with observation after induction with a non-rituximab chemotherapy regimen (CVP) in 282 patients with newly diagnosed FL.34 Improvement in progression-free survival at three years (68% with rituximab vs. 33% with CVP; P < 0.001) and overall survival at three years (91% vs. 86%, respectively; P = 0.08) were noted in the maintenance arm. In the relapsed setting, the prolonged use of rituximab was found to be beneficial with improved progression-free survival when it was used after CHOP or R-CHOP and after treatment with R-FCM.26,35

Although significant evidence exists for the improved progression-free survival with the use of maintenance therapy for FL, the benefit in terms of overall survival is still controversial. Moreover, because different dosing schedules were used in these studies, no data are available for the optimal dosing schedule of maintenance therapy and the recommended duration of this treatment.

Rituximab plus Chemotherapy: Effect on Survival In Follicular Lymphoma

There is no doubt that the clinical development of rituximab has been a significant breakthrough in the field of indolent lymphomas. However, its effect on overall survival in this group of patients is still open to debate.

An analysis of survival in patients 15 years of age and older with NHL diagnosed between 1990 and 2004, using data from the Surveillance, Epidemiology and End Results (SEER) program, revealed a markedly improved outcome for patients with NHL in recent years. This finding may be related, in part, to the addition of rituximab.36

A large retrospective analysis by Swenson et al. was conducted to examine survival rates of 14,564 patients with FL diagnosed between 1978 and 1999 in the U.S.37 Improvement in survival was noted over the past 25 years, and a reduction in the relative risk of death by 1.8% per year was observed from 1983 to1999.

In a second analysis, the Southwest Oncology Group (SWOG) looked at the survival of patients with FL on three large randomized clinical trials between 1974 and 2000.38 Overall survival rates improved over this period of time. The greatest improvement was observed with the most recent treatment approach consisting of CHOP with an anti-CD20 monoclonal antibody.

The study by Marcus et al., published in 2008, showed improved survival rates among untreated patients receiving CVP plus rituximab when compared with CVP alone (four-year survival, 83% vs. 77%, respectively; P= 0.029).19 Other studies, including a Cochrane meta-analysis, have shown similar trends toward improved survival.23,26,34

These observations can be attributed to multiple factors, including improved supportive care measures, enhancements in education of physicians and patients, and better treatments of relapsed and transformed cases.39 Despite these uncertainties regarding its effect on overall survival, it is clear that rituximab has substantially advanced the treatment of indolent lymphomas in the last decade.

Diffuse Large B-Cell Lymphoma

As the most common high-grade form of NHL, diffuse large B-cell lymphoma (DLBCL) accounts for more than 30% of new diagnoses. The median age of presentation is 60 years. Unlike indolent lymphomas, DLBCL is an aggressive lymphoma; if it is untreated, survival can be measured in months. More than 70% of patients with DLBCL present at an advanced stage, and systemic chemotherapy is the foundation of treatment. Since its development in the 1970s, CHOP has been the mainstay of treatment for this group of patients.

A milestone phase 3 trial found that complex regimens that included the addition of other chemotherapy agents to CHOP did not demonstrate any significant difference in overall survival, disease-free survival, or remission rates over CHOP.4043 Moreover, CHOP was associated with significantly less toxicity and cost.

Based on these results, CHOP remained the gold standard of therapy for DLBCL. Nonetheless, long-term remission occurred in only about 45% of patients, so that more than half of patients relapsed with the best therapy possible in the early 1990s. A relatively small percentage of relapsed DLBCL patients (25%–50%) might have been “salvaged” with high-dose chemotherapy and stem-cell support, yet many patients were not even eligible for such therapy.

Thus, in the early 1990s, the addition of more chemotherapy drugs into complex regimens had not improved results with CHOP, and there was a sense that future improvements in therapy would not come from additional “standard” drugs. While rituximab was approved for treatment of low-grade lymphoma in 1997, several trials combining rituximab with CHOP (R-CHOP) for aggressive lymphomas began prior to that time. Because rituximab-related toxicities were not overlapping with those of CHOP, both CHOP and rituximab could be administered at full doses. Results from large international, randomized trials have demonstrated the significant benefits of the addition of rituximab to standard chemotherapy for DLBCL. These trials are summarized next.

Previously Untreated Diffuse Large B-Cell Lymphoma

Based on the efficacy of rituximab in low-grade lymphomas, Vose et al. conducted a phase 2 study of rituximab with CHOP chemotherapy in 33 previously untreated patients with advanced-stage, aggressive B-cell lymphoma.44 Rituximab at a dose of 375 mg/m2 was administered on day 1 of each of six cycles of CHOP. The ORR was 94%; 61% of patients had complete responses (CRs), and 33% had partial responses (PRs). This was the first report that demonstrated an improved efficacy of the combination without worsening toxicity.

GELA investigators randomized previously untreated elderly patients (60–80 years of age) to eight cycles of CHOP alone (197 patients) or eight cycles of R-CHOP given on day 1 of each cycle (202 patients).45 The rate of CRs was significantly higher in the rituximab group (76% vs. 63% receiving CHOP alone, P = 0.005). Sixty percent of patients exhibited features of poor risk, with age-adjusted International Prognostic Index (aaIPI) scores of 2 to 3. With a median follow-up of two years, event-free survival rates (57% vs. 38%; P < 0.001) and overall survival rates (70% vs. 57%; P = 0.007) were significantly higher with rituximab (Table 3). Furthermore, toxicity was not greater with the addition of rituximab.

Table 3

Trials Using Rituximab for Diffuse Large B-Cell Lymphomas in the First-Line Setting

A long-term analysis at seven years has confirmed the benefit of the addition of rituximab.46 Event-free survival (42% with R-CHOP vs. 25%; P < 0.0001), progression-free survival (52% vs. 29%, respectively; P < 0.0001) and disease-free survival (66% vs. 42% respectively, P = 0.0001) were all statistically better for patients treated with combination therapy.

A retrospective analysis of the GELA trial suggested that R-CHOP increased overall survival preferentially in bcl-2–positive patients compared with CHOP alone.47 These data suggested that rituximab may overcome chemotherapy resistance associated with bcl-2 in patients with DLBCL. However, other retrospective analyses have led to conflicting results on whether the benefit of R-CHOP is primarily or only observed in bcl-2expressing DLBCL.

Habermann et al. randomly assigned patients older than 60 years of age to receive CHOP or R-CHOP, with a second random assignment to maintenance rituximab therapy or observation in responders (see Table 3).48This study demonstrated the benefit of the addition of rituximab to CHOP using a modified schedule of rituximab administration. Three-year failure-free survival rates were 53% and 46% (P = 0.04). Failure-free survival was higher for patients who received maintenance therapy with rituximab after CHOP but not for patients who received R-CHOP initially.

The trials described above established R-CHOP as standard first-line therapy for elderly patients with DLBCL. With respect to younger patients, the MabThera (rituximab) International Trial (MInT) confirmed the benefit of adding rituximab to standard chemotherapy in 824 patients (18 to 60 years of age) with only zero (0) to one risk factor, as assessed by the IPI (seeTable 3).49 Patients with stage II to IV or stage I disease with bulky lymphadenopathy were randomly assigned to six cycles of CHOP-like chemotherapy with or without the addition of rituximab. Radiation therapy was subsequently administered to initial sites of bulky disease. Three-year event-free survival rates (79% vs. 59%; P < 0.0001) and overall survival rates (93% vs. 84%; P = 0.00001) were both significantly higher for patients treated with the addition of rituximab. There were no additional major adverse effects.

Sehn et al. compared outcomes during a three-year period; 18 months pre- and post-inclusion of rituximab in standard treatment protocols guided care for patients with newly diagnosed advanced-stage DLBCL in British Columbia.50 All age and risk factor groups were included. Adding rituximab resulted in dramatic improvement in both progression-free survival and overall survival (Figure 1). These studies have indicated significant benefit for the addition of rituximab to chemotherapy for the treatment of DLBCL in a wide range of patient ages and risk categories. Although adding other cytotoxic chemotherapy agents to CHOP failed to improve outcomes, R-CHOP is now the gold standard for treating DLBCL in all subgroups.43

Figure 1

Overall survival according to treatment regimen in diffuse large B-cell lymphoma. Results of a randomized trial of non-rituximab containing regimens as historical controls for British Columbia outcome data with R-CHOP. MACOP-B = methotrexate, Adriamycin,

Relapsed/Refractory Diffuse Large B-Cell Lymphoma

Coiffier et al. conducted a randomized phase 2 trial to evaluate the efficacy and tolerability of rituximab in patients with relapsed/refractory DLBCL, mantle-cell lymphoma, or other intermediate-grade or high-grade B-cell lymphomas and previously untreated patients older than 60 years of age.51 Fifty-four patients received eight weekly infusions of rituximab 375 mg/m2 in arm A or one infusion of 375 mg/m2, followed by seven weekly infusions of 500 mg/m2in arm B. A total of five complete responses and 12 partial responses were observed among the 54 enrolled patients, with no difference between the two doses. The ORR was 31%. An analysis of prognostic factors showed that response rates were lower in patients with refractory disease, in patients with lymphoma not classified as DLBCL, and patients with a tumor larger than 5 cm in diameter. Single-agent rituximab is active in aggressive NHL but not as active as in indolent NHL. This finding led to the use of combinations of rituximab plus chemotherapy in such patients.

The combination of rituximab, ifosfamide, carboplatin, and etoposide (R-ICE) was evaluated in relapsed DLBCL for cytoreduction prior to autologous hematopoietic stem cell transplantation (HSCT).52 Thirty-six eligible patients received rituximab plus ICE (RICE), and 34 patients received all three planned cycles. The CR rate was 53%, significantly better than the 27% CR rate (P = 0.01) achieved among 147 similar consecutive historical control patients with DLBCL treated with ICE; the PR rate was 25%. Progression-free survival in patients who underwent transplantation after RICE was marginally better than for 95 consecutive historical controls who underwent transplantation after ICE alone, but the results did not reach statistical significance (54% with RICE vs. 43% with ICE alone at two years, respectively; P = 0.25). Preliminary results of the CORAL study (Collaborative Trial in Relapsed Aggressive Lymphoma) demonstrated a decreased response to rituximab in the salvage setting of patients previously treated with rituximab-containing regimens.53

In a phase 2 study, rituximab was evaluated in addition to etoposide, prednisone, Oncovin (vincristine), doxorubicin, and cyclophosphamide (EPOCH) in patients with relapsed or refractory aggressive NHL.54 The ORR of 68% included 28% of patients in complete remission. At three years, event-free survival and overall survival rates were 28% and 38%, respectively.

Few studies have explored the use of rituximab as an adjunct to autologous HSCT after high-dose chemotherapy in patients with relapsed DLBCL.5557 These studies have reported positive results with rituximab in this setting. Larger, randomized trials are needed to establish a definitive role for rituximab in these patients. While overall the data on rituximab efficacy in aggressive NHL is not as strong in relapsed patients as for initial R-CHOP, rituximab is active and additional confirmatory studies are needed in various relapsed settings.

Maintenance Therapy for Diffuse Large B-Cell Lymphoma

Unlike the situation with indolent lymphomas, there is no apparent benefit to maintenance rituximab in DLBCL. In an ECOG trial, responding patients were randomly assigned to receive maintenance rituximab or to observation alone.48 Two-year failure-free survival was 76% for maintenance therapy and 61% for observation alone, but these figures were confounded depending on whether rituximab was used initially. No significant differences in survival were seen when rituximab was included either as maintenance or as induction therapy. Failure-free survival was prolonged with maintenance therapy after CHOP but not after R-CHOP. This study confirmed the role of R-CHOP as standard first-line therapy in older DLBCL patients, with maintenance therapy to be used only for patients not previously treated with rituximab.

ADVERSE EFFECTS

Rituximab is usually well tolerated, and toxicities are generally mild.12,24,58Common side effects include pruritus, nausea, vomiting, dizziness, headaches, fevers, and rigors. A major concern is the potential for an infusion-related reaction, such as rigors, chills, anaphylactic reactions potentially leading to myocardial infarction and cardiogenic shock. These reactions occur most commonly during the first administration of rituximab. Although infusion reactions are rarely fatal, predisposing cardiac conditions can increase the risk of death. Pre medication with acetaminophen and antihistamines is recommended prior to infusion. Reactions usually abate if the infusion is discontinued and can then be restarted at a slower rate. The benefit of premedication with glucocorticoids is not entirely clear, but they are useful if a reaction occurs. Mucocutaneous reactions, including Stevens–Johnson syndrome, have also been reported within one to 13 weeks following rituximab exposure.

Tumor lysis syndrome has also occurred in patients with bulky lymphoma. Hepatitis B reactivation with fulminant hepatitis, hepatic failure, and death have been reported in patients with previous hepatitis B infection who have been treated with rituximab. Consultation with a hepatologist and administration of antiviral therapy should be considered if hepatitis B antigen is detectable. The risk of reactivation of hepatitis C is not well defined. The use of live vaccines, including those against herpes zoster, is not recommended during rituximab therapy secondary to the risk of causing an active infection. Rituximab-treated patients are also at risk for other viral infections, including cytomegalovirus, herpes simplex, parvovirus B19, and West Nile virus.

Late-onset neutropenia has been described as a possible complication of adding rituximab to chemotherapy.59 In a retrospective review, patients who received chemotherapy plus rituximab for CD20+, B-cell NHL had a higher rate of late-onset neutropenia compared with historical controls receiving chemotherapy alone.

A study published in 2009 reported 57 cases of progressive multifocal leukoencephalopathy (PML) following the administration of rituximab, usually with additional therapy, in HIV-negative patients.60 PML, a viral infection that affects the white matter of the brain, is usually fatal. This cohort of patients was treated with a median of six doses of rituximab. The median time from last rituximab dose to PML diagnosis was 5.5 months, and median survival after the diagnosis of PML was two months. In accordance with these data, the FDA issued a boxed (black-box) warning.

Reversible posterior leukoencephalopathy (RPLE), a subacute neurological syndrome manifested as headaches, cortical blindness, and seizures with a characteristic appearance on magnetic resonance imaging (MRI), has also been described in rare cases.61,62 It is not clear whether these events are directly related to rituximab, because most of these patients have received multiple therapies, but RPLE has also been reported after other antibody and small-molecule therapeutics. Cardiac arrhythmias, renal toxicity, and bowel obstruction with perforation have also been reported.57

Rituximab induces B-cell depletion, which may compromise the immune system; however, recovery of the normal B-cell population usually occurs six to nine months after discontinuation of therapy.15 Despite this depletion, rituximab has not been definitively shown to cause a significant decrease in circulating immunoglobulin levels, although this may occur with more prolonged maintenance strategies. Stable immunoglobulin levels are likely to reflect that plasma cells are long-lived and do not express CD20.

In a prospective study, van der Kolk et al. investigated the effect of rituximab on the humoral immune response to two primary antigens and two recall antigens.63 After rituximab treatment, the humoral immune response to the recall antigens was significantly decreased when compared with the response before treatment.

FUTURE DIRECTIONS

Attempts to improve upon rituximab have focused on antibody engineering, including humanized instead of chimeric antibodies, stronger binding affinity for CD20, or enhancing effector functions such as antibody-dependent, cell-mediated cytotoxicity (ADCC) or complement activation. Ofatumumab (Arzerra, GlaxoSmithKline) is a humanized monoclonal anti-CD20 antibody that targets a small loop epitope of CD20. Compared with rituximab, in the laboratory it delivers stronger complement-dependent cytotoxicity, even in lymphoma cells with low expression of CD20. Approved by the FDA in October 2009 for the treatment of fludarabine and alemtuzumab–refractory chronic lymphocytic leukemia (CLL), the drug also showed activity in relapsed/refractory FL.64,65

Additional humanized antibodies under development include some with enhanced ADCC, stronger binding to low-affinity polymorphisms of FcgRIII, or targeting other epitopes on the CD20 molecule. Whether these agents are more effective, less immunogenic, or faster to infuse with fewer infusion reactions resulting may be difficult to determine.

Other proteins on the surface of B cells are also potential antibody targets. CD22 has a pattern of expression similar to that of CD20 on normal and malignant B lymphocytes, and it is targeted by epratuzumab (UCB/Immunomedics).66,67 Because CD22 is internalized upon antibody binding, it might be better suited for delivering toxins inside CD22+ cells. Examples of this approach include inotuzumab ozogamicin (CMC-544, Wyeth), an anti-CD22 immunoconjugate with the antitumor antibiotic calicheamicin, and CAT-3888 (Cambridge Antibody Technology), formerly called BL22, which uses a Pseudomonas exotoxin fragment.68,69

CONCLUSION

Rituximab (Rituxan) has changed the treatment paradigms and outcomes for all CD20+ NHL and represents arguably the most noteworthy advance in lymphoma treatment over the past decade. In patients with NHL, the addition of rituximab to standard treatment significantly enhanced response to therapy and overall outcomes. Rituximab is currently approved for treatment of relapsed and refractory indolent lymphomas as single-agent therapy and as initial therapy in combination with standard chemotherapy regimens. In patients with DLBCL, it is approved for use as initial therapy with CHOP or other anthracycline-based chemotherapy. The drug was also recently approved for use with chemotherapy in previously treated and untreated patients with CLL.

Benefits have been sustained among all age groups, and the drug has been safe and well tolerated in elderly patients as well. Overall survival of patients with NHL has improved over the last two decades. While some of this improvement may stem from earlier or more precise diagnosis and better supportive care, the results of many trials reviewed in this article indicate significant improvement in outcomes with the addition of rituximab to the therapeutic armamentarium.

Despite these advances, questions remain, mainly in the field of indolent lymphomas. More research is under way to establish the optimal schedule, timing, and duration for maintenance rituximab. Reports of clinical trials demonstrating longer follow-up of indolent lymphoma are eagerly awaited in an attempt to clarify the effect of rituximab on overall survival.

Rituximab represents a paradigm shift in treatment of B-cell NHL; it marks the beginning of a new age of targeted therapies in oncology, being the first approved therapeutic monoclonal antibody for cancer. In the years to come, we anticipate more clinical trials combining rituximab with targeted treatments that might further improve outcomes while minimizing toxicity.

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Platelet Transfusions

Larry H. Bernstein, MD, FCAP, Curator

LPBI

Platelet Transfusion: A Clinical Practice Guideline From the AABB

Richard M. Kaufman, MD; Benjamin Djulbegovic, MD, PhD; Terry Gernsheimer, MD; Steven Kleinman, MD,
Alan T. Tinmouth, MD; Kelley E. Capocelli, MD; Mark D. Cipolle, MD, PhD; Claudia S. Cohn, MD, PhD; et al.

Ann Intern Med. 2015;162(3):205-213. http://dx.doi.org:/10.7326/M14-1589

Annals of Internal Medicine 3 February 2015, Vol 162, No. 3>

Approximately 2.2 million platelet doses are transfused annually in the United States (1). A high proportion of these platelet units are transfused prophylactically to reduce the risk for spontaneous bleeding in patients who are thrombocytopenic after chemotherapy or hematopoietic progenitor cell transplantation (HPCT) (13). Unlike other blood components, platelets must be stored at room temperature, limiting the shelf life of platelet units to only 5 days because of the risk for bacterial growth during storage. Therefore, maintaining hospital platelet inventories is logistically difficult and highly resource-intensive (45). Platelet transfusion is associated with several risks to the recipient (Table 1), including allergic reactions and febrile nonhemolytic reactions. Sepsis from a bacterially contaminated platelet unit represents the most frequent infectious complication from any blood product today (8). In any situation where platelet transfusion is being considered, these risks must be balanced against the potential clinical benefits.

Background: The AABB (formerly, the American Association of Blood Banks) developed this guideline on appropriate use of platelet transfusion in adult patients.

Methods: These guidelines are based on a systematic review of randomized, clinical trials and observational studies (1900 to September 2014) that reported clinical outcomes on patients receiving prophylactic or therapeutic platelet transfusions. An expert panel reviewed the data and developed recommendations using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework.

Recommendation 1: The AABB recommends that platelets should be transfused prophylactically to reduce the risk for spontaneous bleeding in hospitalized adult patients with therapy-induced hypoproliferative thrombocytopenia. The AABB recommends transfusing hospitalized adult patients with a platelet count of 10 × 109 cells/L or less to reduce the risk for spontaneous bleeding. The AABB recommends transfusing up to a single apheresis unit or equivalent. Greater doses are not more effective, and lower doses equal to one half of a standard apheresis unit are equally effective. (Grade: strong recommendation; moderate-quality evidence)

Recommendation 2: The AABB suggests prophylactic platelet transfusion for patients having elective central venous catheter placement with a platelet count less than 20 × 109 cells/L. (Grade: weak recommendation; low-quality evidence)

Recommendation 3: The AABB suggests prophylactic platelet transfusion for patients having elective diagnostic lumbar puncture with a platelet count less than 50 × 109 cells/L. (Grade: weak recommendation; very-low-quality evidence)

Recommendation 4: The AABB suggests prophylactic platelet transfusion for patients having major elective nonneuraxial surgery with a platelet count less than 50 × 109 cells/L. (Grade: weak recommendation; very-low-quality evidence)

Recommendation 5: The AABB recommends against routine prophylactic platelet transfusion for patients who are nonthrombocytopenic and have cardiac surgery with cardiopulmonary bypass. The AABB suggests platelet transfusion for patients having bypass who exhibit perioperative bleeding with thrombocytopenia and/or evidence of platelet dysfunction. (Grade: weak recommendation; very-low-quality evidence)

Recommendation 6: The AABB cannot recommend for or against platelet transfusion for patients receiving antiplatelet therapy who have intracranial hemorrhage (traumatic or spontaneous). (Grade: uncertain recommendation; very-low-quality evidence)

Table 1. Approximate Per-Unit Risks for Platelet Transfusion in the United States

Approximate_Per-Unit_Risks_for_Platelet_Transfusion_in_the_United_States

Approximate_Per-Unit_Risks_for_Platelet_Transfusion_in_the_United_States

Clinical and laboratory aspects of platelet transfusion therapy
Literature review current through: Sep 2015. | This topic last updated: Jun 12, 2015.

INTRODUCTION — Hemostasis depends on an adequate number of functional platelets, together with an intact coagulation (clotting factor) system. This topic covers the logistics of platelet use and the indications for platelet transfusion in adults. The approach to the bleeding patient, refractoriness to platelet transfusion, and platelet transfusion in neonates are discussed elsewhere.

(See “Approach to the adult patient with a bleeding diathesis”.)

(See “Refractoriness to platelet transfusion therapy”.)

(See “Clinical manifestations, evaluation, and management of neonatal thrombocytopenia”, section on ‘Platelet transfusion’.)

PLATELET COLLECTION — There are two ways that platelets can be collected: by isolation from a unit of donated blood, or by apheresis from a donor in the blood bank.

Pooled platelets – A single unit of platelets can be isolated from every unit of donated blood, by centrifuging the blood within the closed collection system to separate the platelets from the red blood cells (RBC). The number of platelets per unit varies according to the platelet count of the donor; a yield of 7 x 1010platelets is typical [1]. Since this number is inadequate to raise the platelet count in an adult recipient, four to six units are pooled to allow transfusion of 3 to 4 x 1011 platelets per transfusion [2]. These are called whole blood-derived or random donor pooled platelets.

Advantages of pooled platelets include lower cost and ease of collection and processing (a separate donation procedure and pheresis equipment are not required). The major disadvantage is recipient exposure to multiple donors in a single transfusion and logistic issues related to bacterial testing.

Apheresis (single donor) platelets – Platelets can also be collected from volunteer donors in the blood bank, in a one- to two-hour pheresis procedure. Platelets and some white blood cells are removed, and red blood cells and plasma are returned to the donor. A typical apheresis platelet unit provides the equivalent of six or more units of platelets from whole blood (ie, 3 to 6 x 1011platelets) [2]. In larger donors with high platelet counts, up to three units can be collected in one session. These are called apheresis or single donor platelets.

Advantages of single donor platelets are exposure of the recipient to a single donor rather than multiple donors, and the ability to match donor and recipient characteristics such as HLA type, cytomegalovirus (CMV) status, and blood type for certain recipients. (See ‘Ordering platelets’ below.)

Issues related to the effects of platelet pheresis on the donor are covered elsewhere. (See “Blood donor screening: Procedures and processes to enhance safety for the blood recipient and the blood donor”, section on ‘Apheresis platelet donors’.)

Both pooled and apheresis platelets contain some white blood cells (WBC) that were collected along with the platelets. These WBC can cause febrile non-hemolytic transfusion reactions (FNHTR), alloimmunization, and transfusion-associated graft-versus-host disease (ta-GVHD) in some patients.

Platelet products also contain plasma, which can be implicated in adverse reactions including transfusion-related acute lung injury (TRALI) and anaphylaxis. (See‘Complications of platelet transfusion’ below.)

Several strategies are used to prevent the complications associated with WBC and plasma contamination of platelets. (See ‘Ordering platelets’ below.)

Platelets concentrates also contain a small number of red blood cells (RBCs) that express Rh antigens on their surface (platelets do not express Rh antigens). The small numbers of RBCs in apheresis platelets negates the issue of Rh alloimmunization in most patients. However, blood banks avoid giving platelets from Rh+ donors to Rh female patients because of the potential risk of Rh alloimmunization and subsequent hemolytic disease of the newborn. (See “Overview of Rhesus D alloimmunization in pregnancy”.)

PLATELET STORAGE AND PATHOGEN REDUCTION — Platelets are stored at room temperature, because cold induces clustering of von Willebrand factor receptors on the platelet surface and morphological changes of the platelets, leading to enhanced clearance by hepatic macrophages and reduced platelet survival in the recipient [3-6].

All cells are more metabolically active at room temperature, so platelets are stored in bags that allow oxygen and carbon dioxide gas exchange. Citrate is included to prevent clotting and maintain proper pH, and dextrose is added as an energy source [2].

A disadvantage of room temperature storage is the increased growth of bacteria compared with blood products stored in the refrigerator or freezer. (See‘Complications of platelet transfusion’ below.)

Strategies for reducing exposure to contaminating pathogens include:

Donor screening for bloodborne pathogens (see “Blood donor screening: Laboratory testing”, section on ‘Infectious disease screening’ and “Blood donor screening: Procedures and processes to enhance safety for the blood recipient and the blood donor”, section on ‘Protection of the recipient’)

Proper skin sterilization techniques during collection, and discarding the first 15 to 30 mL of blood collected, which is most likely to be contaminated by skin bacteria

Performing tests to screen for bacterial contamination, such as automated culture-based assays, and rapid point-of-issue tests (see “Transfusion-transmitted bacterial infection”, section on ‘Detection of contamination’)

Using blood products that have been subjected to pathogen inactivation or reduction treatment (not available in the United States) (see “Pathogen inactivation of blood products”, section on ‘Pathogen inactivation of platelets’and “Preparation of blood components”, section on ‘Pathogen reduction’)

The shelf life of platelets stored at room temperature is five days because of the bacterial infection risk that increases in relationship to the storage duration. This short shelf life contributes to the greater sensitivity of platelet inventory to shortages.

INDICATIONS FOR PLATELET TRANSFUSION — Platelets can be transfused therapeutically (ie, to treat active bleeding or in preparation for an invasive procedure that would cause bleeding), or prophylactically (ie, to prevent spontaneous bleeding).

Actively bleeding patient — Actively bleeding patients with thrombocytopenia should be transfused with platelets immediately to keep platelet counts above50,000/microL in most bleeding situations, and above 100,000/microL if there is disseminated intravascular coagulation or central nervous system bleeding. (See“Clinical features, diagnosis, and treatment of disseminated intravascular coagulation in adults”, section on ‘Treatment’ and “Spontaneous intracerebral hemorrhage: Treatment and prognosis”, section on ‘Initial treatment’.).

Other factors contributing to bleeding should also be addressed. These include:

Surgical or anatomic defect

Fever

Infection or inflammation

Coagulopathy

Acquired or inherited platelet function defect

The dose and frequency of platelet transfusions will depend on the platelet count and the severity of bleeding. (See ‘Dose’ below.)

Preparation for an invasive procedure — Platelets are transfused in preparation for an invasive procedure if the thrombocytopenia is severe and the risks of bleeding are deemed high. Most of the data used to determine bleeding risk come from retrospective studies of patients who are afebrile and have thrombocytopenia but not coagulopathy [7]. Typical platelet count thresholds that are used for some common procedures are as follows:

Neurosurgery or ocular surgery – 100,000/microL

Most other major surgery – 50,000/microL

Endoscopic procedures – 50,000/microL for therapeutic procedures;20,000/microL for low risk diagnostic procedures (see “Endoscopic procedures in patients with disorders of hemostasis”, section on ‘Procedure-related bleeding risk’)

Central line placement – 20,000/microL [8]

Lumbar puncture – 10,000 to 20,000/microL in patients with hematologic malignancies and greater than 40,000 to 50,000 in patients without hematologic malignancies, but lower in patients with immune thrombocytopenia (ITP) [9-11]

Epidural anesthesia – 80,000/microL [11]

Bone marrow aspiration/biopsy20,000/microL

Prevention of spontaneous bleeding — Prophylactic transfusion is used to prevent spontaneous bleeding in patients at high risk of bleeding. The threshold for prophylactic transfusion varies depending on the patient and on the clinical scenario. (See ‘Specific clinical scenarios’ below.)

Predicting spontaneous bleeding — There are no ideal tests for predicting who will bleed spontaneously [12]. Studies of patients with thrombocytopenia suggest that patients can bleed even with platelet counts greater than 50,000/microL [13]. However, bleeding is much more likely at platelet counts less than 5000/microL. Among individuals with platelet counts between 5000/microL and 50,000/microL,clinical findings can be helpful in decision-making regarding platelet transfusion.

The platelet count at which a patient bled previously can be a good predictor of future bleeding.

Petechial bleeding and ecchymoses are generally not thought to be predictive of serious bleeding, whereas mucosal bleeding and epistaxis (so-called “wet” bleeding) are thought to be predictive.

Coexisting inflammation, infection, and fever also increase bleeding risk.

The underlying condition responsible for a patient’s thrombocytopenia also may help in estimating the bleeding risk. As an example, some patients with ITP often tolerate very low platelet counts without bleeding, while patients with some acute leukemias that are associated with coagulopathy (eg, acute promyelocytic leukemia) can have bleeding at higher platelet counts (eg, 30,000 to 50,000/microL). (See ‘Specific clinical scenarios’ below.)

Compared with adults, children with bone marrow suppression may be more likely to experience bleeding at the same degree of thrombocytopenia. In a secondary subgroup analysis of the PLADO trial, in which patients were randomly assigned to different platelet doses, children had more days of bleeding, more severe bleeding, and required more platelet transfusions than adults with similar platelet counts [14]. However, these findings do not suggest a different threshold for platelet transfusion in children, as the increased risk of bleeding was distributed across a wide range of platelet counts.

Tests for platelet-dependent hemostasis (ie, bleeding time, thromboelastography, and other point of care tests) are generally not used to predict bleeding in thrombocytopenic patients. (See “Platelet function testing”, section on ‘The in vivo bleeding time’ and “Platelet function testing”, section on ‘Instruments that simulate platelet function in vitro’.)

Therapeutic versus prophylactic transfusion — By convention, most authors use the term “therapeutic transfusion” to refer both to transfusion of platelets to treat active bleeding and transfusion of platelets in preparation for an invasive procedure that could cause bleeding. The term “prophylactic transfusion” is used to refer to platelet transfusion given to prevent spontaneous bleeding.

We use prophylactic platelet transfusion to prevent spontaneous bleeding in most afebrile patients with platelet counts below 10,000/microL due to bone marrow suppression. We use higher thresholds (ie, 30,000/microL) in patients who are febrile or septic. Patients with acute promyelocytic leukemia (APL) have a coexisting coagulopathy, and we use a platelet transfusion threshold of 30,000 to 50,000/microLfor them. (See ‘Leukemia and chemotherapy’ below.)

Patients with platelet consumption disorders (eg, immune thrombocytopenia [ITP], disseminated intravascular coagulation) and platelet function disorders are typically transfused only for bleeding or, in some cases, invasive procedures. Platelets should not be withheld in bleeding patients with these conditions due to fear of “fueling the fire” of thrombus formation. (See ‘Immune thrombocytopenia (ITP)’ below and ‘TTP or HIT’ below and ‘Platelet function defects’ below.)

Given the need to balance the risk of spontaneous bleeding with the potential complications of unnecessary platelet transfusion, the decision of whether to transfuse platelets based upon a clinical event (ie, for active bleeding or invasive procedures) or at a particular threshold (ie, to prevent spontaneous bleeding) is challenging. Standard practice has evolved to transfusion of platelets at a threshold platelet count of 10,000 to 20,000/microL for most patients with severe hypoproliferative thrombocytopenia due to hematologic malignancies, cytotoxic chemotherapy, and hematopoietic cell transplant (HCT) [15]. However, the risks and benefits of reserving platelet transfusion for active bleeding episodes in these patients continue to be evaluated [7,16-19].

In a randomized trial, 400 patients with acute myeloid leukemia (AML; patients with APL were excluded) and patients undergoing autologous HCT for hematologic malignancies were assigned to receive platelet transfusions when morning platelet counts were ≤10,000/microL or only for active bleeding [20]. Patients transfused only for active bleeding received fewer platelet transfusions during the 14-day period after induction or consolidation chemotherapy (1.63 versus 2.44 per patient, a 33.5 percent reduction). However, among patients with AML who were transfused only for active bleeding, there were more episodes of major bleeding (six cerebral, four retinal, and one vaginal) and there were two fatal intracranial hemorrhages compared with four retinal hemorrhages among patients transfused for a platelet count ≤10,000/microL. Patients undergoing HCT also experienced more bleeding episodes when transfused only for active bleeding, but most of these were minor.

In another randomized trial, 600 patients with hematologic malignancies receiving chemotherapy, autologous, or allogeneic HCT were assigned to receive platelet transfusion for a platelet count ≤10,000/microL or only for active bleeding (the Trial of Prophylactic Platelets [TOPPS]) [21-23]. Compared with those who received prophylactic transfusions, patients transfused only for active bleeding received fewer platelet transfusions during the 30-day period after randomization, but had a higher incidence of major bleeding (50 versus 43 percent) and a shorter time to first bleed (1.2 versus 1.7 days) [24]. There were no differences in the duration of hospitalization, and no deaths due to bleeding. In a predefined subgroup analysis, patients undergoing autologous HCT had similar rates of major bleeding whether they were transfused for a platelet count≤10,000/microL or only for active bleeding (45 and 47 percent).

The findings from these trials support continued use of prophylactic transfusion for patients with hematologic malignancies and HCT until further data become available. Although the findings suggest that reserving platelet transfusion for active bleeding may be safe for some adults undergoing autologous HCT, such a strategy requires intensive monitoring and the ability to perform immediate imaging for suspected CNS or ocular bleeding. We do not recommend reserving platelet transfusion for active bleeding in patients with HCT outside of highly specialized centers with the ability to support this level of vigilance.

SPECIFIC CLINICAL SCENARIOS — There are several common clinical scenarios that raise the questions of whether to transfuse patients prophylactically to prevent bleeding, and, if prophylactic transfusion is used, of what platelet count is the best threshold for transfusion.

Leukemia and chemotherapy — Patients with leukemia, hematopoietic cell transplant (HCT), or those being treated with cytotoxic chemotherapy have a suppressed bone marrow that cannot produce adequate platelets. We use prophylactic transfusion in these settings. The thresholds suggested below apply to patients with thrombocytopenia who are afebrile and without active infection. If fever or sepsis is present, higher thresholds may be needed.

Acute myeloid leukemia (AML) – Patients with AML can have suppressed bone marrow from AML, chemotherapy, or HCT. We use standard dose prophylactic transfusion of these patients at a threshold platelet count of10,000/microL, and transfusion for any bleeding greater than petechial bleeding. (See ‘Dose’ below.)

This approach is in line with the 2001 American Society for Clinical Oncology (ASCO) guidelines (table 1) and a practice guideline from the AABB [25]. It is supported by randomized trials comparing prophylactic (ie, threshold-based) and therapeutic platelet transfusion, in which patients who did not receive prophylactic transfusion had more severe bleeding [20,24,26]. (See ‘Therapeutic versus prophylactic transfusion’ above and “Overview of the complications of acute myeloid leukemia”, section on ‘Bleeding’.)

Acute promyelocytic leukemia (APL) – Patients with APL differ from other patients with AML because they often have an associated coagulopathy that puts them at high risk for disseminated intravascular coagulation and bleeding. We prophylactically transfuse these patients at a platelet count of 30,000 to50,000/microL, and treat any sign of bleeding, especially central nervous system bleeding, with immediate platelet transfusion. (See “Clinical manifestations, pathologic features, and diagnosis of acute promyelocytic leukemia in adults”, section on ‘Disseminated intravascular coagulation’ and“Initial treatment of acute promyelocytic leukemia in adults”, section on ‘Control of coagulopathy’.)

Acute lymphoblastic leukemia (ALL) – Patients with ALL have thrombocytopenia from bone marrow suppression. In addition, these patients are often treated with L-asparaginase, which causes severe hypofibrinogenemia. However, the risk of life-threatening bleeding is low. As an example, in over 2500 children with ALL, only two intracranial hemorrhages occurred, and they were associated with hyperleukocytosis in one case and intracerebral fungal infection in the other [9]. We transfuse adults with ALL at a threshold platelet count of 10,000/microL. The use of platelet transfusion in children with ALL is discussed separately. (See “Overview of the treatment of acute lymphoblastic leukemia in children and adolescents”, section on ‘Bleeding’.)

Chemotherapy for solid tumors – Cancer chemotherapy often makes patients thrombocytopenic from bone marrow suppression. Randomized trials of platelet transfusion threshold in this population have not been performed. Observational studies support a prophylactic platelet transfusion threshold of 10,000/microL[26]. A threshold of 20,000/microL may be appropriate for patients with necrotic tumors. These recommendations are generally consistent with the ASCO 2001 Guidelines (table 1) [26].

Hematopoietic cell transplant (HCT) – Chemotherapy and radiation therapy administered as part of the conditioning regimen for HCT can be highly bone marrow suppressive, depending on the doses used. We use standard dose prophylactic transfusion of these patients at a threshold platelet count of10,000/microL, and therapeutic transfusion for any bleeding greater than petechial bleeding. (See “Hematopoietic support after hematopoietic cell transplantation”, section on ‘Platelet transfusion’.)

Aplastic anemia – Patients with aplastic anemia do not have a malignancy, but they may have severe thrombocytopenia, and they may be candidates for HCT. Issues related to platelet transfusion in these patients are discussed separately. (See “Treatment of aplastic anemia in adults”.)

Prophylactic platelet transfusion for a platelet count ≤10,000/microL in hospitalized patients with thrombocytopenia from therapy-induced bone marrow suppression is consistent with a practice guideline from the AABB [25].

Immune thrombocytopenia (ITP) — Individuals with immune thrombocytopenia produce anti-platelet antibodies that destroy circulating platelets and megakaryocytes in the bone marrow. Circulating platelets in patients with ITP tend to be highly functional, and platelet counts tend to be well above 30,000/microL. Bleeding is rare even in patients with severe thrombocytopenia (ie, platelet count <30,000/microL). (See “Immune thrombocytopenia (ITP) in adults: Clinical manifestations and diagnosis”, section on ‘Pathogenesis’.)

Our general approach to platelet transfusion in patients with ITP is to transfuse for bleeding rather than at a specific platelet count. (See “Immune thrombocytopenia (ITP) in adults: Initial treatment and prognosis”, section on ‘Indications for treatment’.)

TTP or HIT — Thrombotic thrombocytopenic purpura (TTP) and heparin-induced thrombocytopenia (HIT) are disorders in which platelet consumption causes thrombocytopenia and an increased risk of bleeding; but the underlying platelet activation in these conditions also increases the risk of thrombosis.

Platelet transfusions can be helpful or even life-saving in patients with these conditions who are bleeding and/or have anticipated bleeding due to a required invasive procedure (eg, placement of a central venous catheter), and platelet transfusion should not be withheld from a bleeding patient due to concerns that platelet transfusion will exacerbate thrombotic risk. However, platelet transfusions may cause a slightly increased risk of thrombosis in patients with these conditions; thus, we do not use prophylactic platelet transfusions routinely in patients with TTP or HIT in the absence of bleeding or a required invasive procedure.

Support for this approach comes from a large retrospective review of hospitalized patients with TTP and HIT, in which platelet transfusion was associated with a very slight increased risk of arterial thrombosis but not venous thromboembolism [27]. In contrast, the review found that patients with immune thrombocytopenia (ITP) had no increased risk of arterial or venous thrombosis with platelet transfusion. Of note, this was a retrospective study in which sicker patients were more likely to have received platelets, and the temporal relationships between platelet transfusions and thromboses were not assessed.

TTP – Of 10,624 patients with TTP in the large review mentioned above, approximately 10 percent received a platelet transfusion [27]. Arterial thrombosis occurred in 1.8 percent of patients who received platelets, versus 0.4 percent of patients who did not (absolute increase, 1.4 percent; adjusted odds ratio [OR], 5.8; 95% CI, 1.3-26.6). The rate of venous thrombosis was not different in those who received platelets and those who did not (adjusted OR 1.1; 95% CI 0.5-2.2).

In contrast, a systematic review of patients with TTP who received platelet transfusions, which included retrospective data for 358 patients and prospective data for 54 patients, did not find clear evidence that platelet transfusions were associated with adverse outcomes [28].

HIT – Of 6332 patients with HIT in the large review mentioned above, approximately 7 percent received a platelet transfusion [27]. Arterial thrombosis occurred in 6.9 percent of patients who received platelets, versus 3.1 percent of patients who did not (absolute increase, 3.8 percent; adjusted OR, 3.4; 95% CI, 1.2-9.5). The rate of venous thrombosis was not different in those who received platelets and those who did not (adjusted OR 0.8; 95% CI 0.4-1.7).

In a series of four patients with HIT who received platelet transfusions, two of three with active bleeding had cessation of bleeding following platelet transfusion, and no thromboses occurred; a literature review was not able to identify any complications clearly attributable to platelet transfusion [29].

Management of TTP and HIT is discussed in detail separately. (See “Acquired TTP: Initial treatment” and “Management of heparin-induced thrombocytopenia”.)

Liver disease and DIC — Patients with liver disease and DIC have a complex mixture of procoagulant and anticoagulant defects along with thrombocytopenia, and therefore they are at risk for thrombosis and bleeding. There is no evidence to support the administration of platelets in these patients if they are not bleeding. However, platelet transfusion is justified in patients who have serious bleeding, are at high risk for bleeding (eg, after surgery), or require invasive procedures. (See “Clinical features, diagnosis, and treatment of disseminated intravascular coagulation in adults”, section on ‘Prevention/treatment of bleeding’ and “Hemostatic abnormalities in patients with liver disease”, section on ‘Bleeding’.)

Platelet function defects — Platelet function defects can be inherited or acquired, and may be associated with thrombocytopenia or a normal platelet count. Platelet transfusion in these settings is typically reserved for bleeding.

Inherited diseases Platelet function is impaired in Wiskott-Aldrich syndrome, Glanzmann thrombasthenia, and Bernard-Soulier syndrome. Bleeding in patients with these conditions is treated with platelet transfusion, along with other hemostatic agents discussed below. (See “Congenital and acquired disorders of platelet function”, section on ‘Inherited disorders of platelet function’ and‘Alternatives to platelet transfusion’ below.)

Acquired conditions – Uremia, diabetes mellitus, myeloproliferative disorders, and other medical conditions can impair platelet function. Bleeding risk can be reduced by treating the underlying condition. Platelet transfusion is typically reserved for major bleeding in these conditions. (See “Congenital and acquired disorders of platelet function”, section on ‘Acquired platelet functional disorders’.)

Patients who are febrile or septic can have impaired platelet function. We transfuse these patients for bleeding. We also use a higher threshold for when fever or sepsis coexist with thrombocytopenia (eg, in patients with leukemia). (See ‘Leukemia and chemotherapy’ above.)

Antiplatelet agentsAspirin, nonsteroidal antiinflammatory drugs (NSAIDs),dipyridamole, ADP receptor (P2Y12) inhibitors (eg, clopidogrel, ticlopidine), andGPIIb/IIIa antagonists (eg, abciximab, eptifibatide) are used to prevent thrombosis by interfering with normal platelet function. The antiplatelet effects of these agents are weakest with aspirin and more potent with the P2Y12inhibitors. (See “Platelet biology”, section on ‘Drugs with antiplatelet actions’.)

Typically, the approach to treating mild bleeding in a patient taking an antiplatelet agent is to discontinue the drug, assuming a favorable risk-benefit ratio. Although data are limited, platelet transfusion appears to be the best option in patients taking antiplatelet agents who experience severe bleeding [30].

Patients taking these agents may also require urgent surgical procedures (eg, coronary artery bypass grafting, neurosurgical interventions, and others). The role of platelet transfusion in this setting is not well defined. Some clinicians give prophylactic platelet transfusions to patients taking antiplatelet drugs who require major surgery, while other clinicians use platelet transfusion only to treat excessive surgical bleeding [30,31]. These cases can be complex, and we favor an individualized approach based on the complete clinical picture.

Other medications – Other medications may impair platelet function. As an example, the Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib inhibits platelet aggregation by interfering with activation signals. The role of platelet transfusion in patients with ibrutinab-associated bleeding despite a sufficient platelet count is unknown, and decisions are individualized according to the platelet count and the severity and site of bleeding.

Massive blood loss — Patients with massive blood loss from surgery or trauma are transfused with red blood cells (RBC), resulting in partial replacement of the blood volume with a product lacking platelets and clotting factors. In this setting, we transfuse RBC, fresh frozen plasma (FFP), and random donor platelet units in a 1:1:1 ratio. As an example, a patient transfused with six units of RBC would also receive six units of pooled platelets or one apheresis unit (both of which provide approximately 5 x 1011 platelets) and six units of FFP. (See “Initial evaluation and management of shock in adult trauma”, section on ‘Transfusion of blood products’.).

Cardiopulmonary bypass — Patients who undergo prolonged cardiopulmonary bypass can have thrombocytopenia and impaired platelet function. The use of platelet transfusion in the cardiopulmonary bypass setting is discussed separately. (See“Congenital and acquired disorders of platelet function”, section on ‘Cardiopulmonary bypass’ and “Early noncardiac complications of coronary artery bypass graft surgery”, section on ‘Bleeding’.)

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Plasmapheresis

Larry H. Bernstein, MD, FCAP, Curator

LPBI

Plasmapheresis

Author: Elliot Stieglitz, MD; Chief Editor: Emmanuel C Besa, MD

Plasmapheresis is a term used to refer to a broad range of procedures in which extracorporeal separation of blood components results in a filtered plasma product.[1, 2] The filtering of plasma from whole blood can be accomplished via centrifugation or semipermeable membranes.[3] Centrifugation takes advantage of the different specific gravities inherent to various blood products such as red cells, white cells, platelets, and plasma.[4] Membrane plasma separation uses differences in particle size to filter plasma from the cellular components of blood.[3]

Traditionally, in the United States, most plasmapheresis takes place using automated centrifuge-based technology.[5] In certain instances, in particular in patients already undergoing hemodialysis, plasmapheresis can be carried out using semipermeable membranes to filter plasma.[4]

In therapeutic plasma exchange, using an automated centrifuge, filtered plasma is discarded and red blood cells along with replacement colloid such as donor plasma or albumin is returned to the patient. In membrane plasma filtration, secondary membrane plasma fractionation can selectively remove undesired macromolecules, which then allows for return of the processed plasma to the patient instead of donor plasma or albumin. Examples of secondary membrane plasma fractionation include cascade filtration,[6] thermofiltration, cryofiltration,[7] and low-density lipoprotein pheresis.

Plasmapheresis is currently used as a therapeutic modality in a wide array of conditions.[2] Generally, plasmapheresis is used when a substance in the plasma, such as immunoglobulin, is acutely toxic and can be efficiently removed. Myriad conditions fall under this category, including neurologic, hematologic, metabolic, dermatologic, rheumatologic, and renal diseases, as well as intoxications, that can be treated with plasmapheresis.

The Apheresis Applications Committee of the American Society for Apheresis periodically evaluates potential indications for apheresis and categorizes them from I to IV based on the available medical literature. The following are some of the indications, and their categorization, from the society’s 2010 guidelines.[2]

Category I (disorders for which apheresis is accepted as first-line therapy, either as a primary standalone treatment or in conjunction with other modes of treatment) are as follows:

  • Chronic inflammatory demyelinating polyneuropathy
  • Hyperviscosity in monoclonal gammopathies
  • Thrombotic thrombocytopenic purpura
  • Goodpasture syndrome (unless dialysis dependent and no diffuse alveolar hemorrhage)
  • Hemolytic uremic syndrome (atypical, due to autoantibody to factor H)
  • Wilson disease, fulminant

Category II (disorders for which apheresis is accepted as second-line therapy, either as a standalone treatment or in conjunction with other modes of treatment) are as follows:

  • Lambert-Eaton myasthenic syndrome
  • Multiple sclerosis (acute central nervous system demyelination disease unresponsive to steroids)
  • Red cell alloimmunization in pregnancy
  • Mushroom poisoning
  • Acute disseminated encephalomyelitis
  • Hemolytic uremic syndrome (atypical, due to complement factor mutations)
  • Autoimmune hemolytic anemia (life-threatening cold agglutinin disease)
  • Systemic lupus erythematosus (severe)
  • Myeloma cast nephropathy

Category III (optimum role of apheresis therapy is not established; decision-making should be individualized) are as follows:

  • Post-transfusion purpura
  • Autoimmune hemolytic anemia (warm autoimmune hemolytic anemia)
  • Hypertriglyceridemic pancreatitis
  • Thyroid storm

Category IV (disorders in which published evidence demonstrates or suggests apheresis to be ineffective or harmful; IRB approval is desirable if apheresis treatment is undertaken in these circumstances) are as follows:

  • Stiff person syndrome
  • Hemolytic uremic syndrome (typical diarrhea-associated)
  • Systemic lupus erythematosus (nephritis)
  • Immune thrombocytopenia

Contraindications  

See the list below:

  • Patients who cannot tolerate central line placement.
  • Patients who are actively septic or are hemodynamically unstable.
  • Patients who have allergies to fresh frozen plasma or albumin depending on the type of plasma exchange.
  • Patients with heparin allergies should not receive heparin as an anticoagulant during plasmapheresis.
  • Patients with hypocalcemia are at risk for worsening of their condition because citrate is commonly used to prevent clotting and can potentiate hypocalcemia.

http://emedicine.medscape.com/article/1895577-overview#a4

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Granulocyte colony stimulating factor (G-CSF)

Larry H. Bernstein, MD, FCAP, Curator

LPBI

G-CSF (granulocyte colony stimulating factor)

http://www.cancerresearchuk.org/about-cancer/cancers-in-general/treatment/cancer-drugs/gcsf

G-CSF is a type of growth factor. Growth factors are proteins made in the body and some of them make the bone marrow produce blood cells. G-CSF makes the body produce white blood cells to reduce the risk of infection after some types of cancer treatment. It also makes some stem cells move from the bone marrow into the blood. Stem cells are the cells in the bone marrow from which red blood cells, white cells and platelets develop.

The full name for G-CSF is granulocyte colony stimulating factor.

There are different types, including

  • Lenograstim (Granocyte)
  • Filgrastim (Neupogen, Zarzio, Nivestim, Ratiograstim)
  • Long acting (pegylated) filgrastim (pegfilgrastim, Neulasta) and lipegfilgrastim (Longquex)

Pegylated G-CSF stays in the body for longer so you have treatment less often than with the other types of G-CSF.

G-CSF after chemotherapy

A common side effect of chemotherapy is a drop in the number of white blood cells, which leads to an increased risk of getting an infection. Most people’s white blood cells recover quickly after chemotherapy and they don’t need treatment with G-CSF. But with some types of chemotherapy, such as high dose treatment, it can take a long time for the number of white blood cells to rise again.

Having G-CSF treatment can make white blood cell levels go up faster. So if your white blood cell count doesn’t go up as it should you may have G-CSF treatment. With some types of chemotherapy you have G-CSF as a standard part of your treatment plan.

G-CSF before and after a stem cell transplant

You may have G-CSF as part of a stem cell transplant. Before the treatment you have G-CSF to stimulate the bone marrow to produce stem cells and release them into the blood. The stem cells are collected and then you have high dose chemotherapy.

The chemotherapy stops your bone marrow producing blood cells. So you have the stem cells back into your bloodstream. They go into the bone marrow and start making the different types of blood cells again.

You can have G-CSF either

You may have G-CSF as a drip into your bloodstream (intravenously). You can have it through a thin, short tube (a cannula) put into a vein in your arm each time you have treatment. Or you may have it through a central line, a portacath or aPICC line. These are long, plastic tubes that give the drugs directly into a large vein in your chest. You have the tube put in just before your course of treatment starts and it stays in place as long as you need it.

If you have G-CSF as an injection under the skin you have it daily for up to 14 days. You have regular blood tests to check your white blood cell count. If you are having it as part of a planned treatment you start at least a day after your chemotherapy and continue until the number of white blood cells called neutrophils is within the normal range.

If you are having pegylated G-CSF you only need to have one injection at least 24 hours after the end of the chemotherapy.

Common side effects

More than 10 in every 100 people have one or more of the side effects listed below.

  • Headaches
  • Loss of appetite
  • Redness and irritation at the injection site
  • Feeling or being sick, but this is usually well controlled with anti sickness medicines
  • Bone pain happens in up to 4 out of 10 people (40%). It is caused by the bone marrow making blood cells. Paracetamol can help to control any pain
  • Diarrhoea – drink plenty of fluids. Tell your doctor or nurse if diarrhoea becomes severe, or continues for more than 3 days
  • Constipation – your doctor or nurse may give you laxatives to help prevent this but do tell them if you are constipated for more than 3 days
  • Liver changes that are very mild and unlikely to cause symptoms – the liver will almost certainly go back to normal when the treatment ends. You will have regular blood tests to check how well your liver is working

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Blood Transfusions

Larry H Bernstein, MD, FCAP, Curator

LPBI

What Is a Blood Transfusion?  

A blood transfusion is a safe, common procedure in which blood is given to you through an intravenous (IV) line in one of your blood vessels.

Blood transfusions are done to replace blood lost during surgery or due to a serious injury. A transfusion also may be done if your body can’t make blood properly because of an illness.

During a blood transfusion, a small needle is used to insert an IV line into one of your blood vessels. Through this line, you receive healthy blood. The procedure usually takes 1 to 4 hours, depending on how much blood you need.

Blood transfusions are very common. Each year, almost 5 million Americans need a blood transfusion. Most blood transfusions go well. Mild complications can occur. Very rarely, serious problems develop.

Blood is made up of various parts, including red blood cells, white blood cells, platelets (PLATE-lets), and plasma. Blood is transfused either as whole blood (with all its parts) or, more often, as individual parts.

Blood Types

Every person has one of the following blood types: A, B, AB, or O. Also, every person’s blood is either Rh-positive or Rh-negative. So, if you have type A blood, it’s either A positive or A negative.

The blood used in a transfusion must work with your blood type. If it doesn’t, antibodies (proteins) in your blood attack the new blood and make you sick.

Type O blood is safe for almost everyone. About 40 percent of the population has type O blood. People who have this blood type are called universal donors. Type O blood is used for emergencies when there’s no time to test a person’s blood type.

People who have type AB blood are called universal recipients. This means they can get any type of blood.

If you have Rh-positive blood, you can get Rh-positive or Rh-negative blood. But if you have Rh-negative blood, you should only get Rh-negative blood. Rh-negative blood is used for emergencies when there’s no time to test a person’s Rh type.

Blood Banks

Blood banks collect, test, and store blood. They carefully screen all donated blood for possible infectious agents, such as viruses, that could make you sick. (For more information, see“What Are the Risks of a Blood Transfusion?”)

Blood bank staff also screen each blood donation to find out whether it’s type A, B, AB, or O and whether it’s Rh-positive or Rh-negative. Getting a blood type that doesn’t work with your own blood type will make you very sick. That’s why blood banks are very careful when they test the blood.

To prepare blood for a transfusion, some blood banks remove white blood cells. This process is called white cell or leukocyte (LU-ko-site) reduction. Although rare, some people are allergic to white blood cells in donated blood. Removing these cells makes allergic reactions less likely.

Not all transfusions use blood donated from a stranger. If you’re going to have surgery, you may need a blood transfusion because of blood loss during the operation. If it’s surgery that you’re able to schedule months in advance, your doctor may ask whether you would like to use your own blood, rather than donated blood.

Alternatives to Blood Transfusions 

Researchers are trying to find ways to make blood. There’s currently no man-made alternative to human blood. However, researchers have developed medicines that may help do the job of some blood parts.

For example, some people who have kidney problems can now take a medicine called erythropoietin that helps their bodies make more red blood cells. This means they may need fewer blood transfusions.

Surgeons try to reduce the amount of blood lost during surgery so that fewer patients need blood transfusions. Sometimes they can collect and reuse the blood for the patient.

https://www.nhlbi.nih.gov/health/health-topics/topics/bt

Your options may be limited by time and health factors, so it is important to begin carrying out your decision as soon as possible. For example, if friends or family members are donating blood for a patient (directed donors), their blood should be drawn several days prior to the anticipated need to allow adequate time for testing and labeling. The exact protocols are hospital and donor site specific.

The safest blood product is your own, so if a transfusion is likely, this is your lowest risk choice. Unfortunately this option is usually only practical when preparing for elective surgery. In most other instances the patient cannot donate their own blood due to the acute nature of the need for blood. Although you have the right to refuse a blood transfusion, this decision may have life-threatening consequences. If you are a parent deciding for your child, you as the parent or guardian must understand that in a life-threatening situation your doctors will act in your child’s best interest to insure your child’s health and wellbeing in accordance with standards of medical care regardless of religious beliefs. Please carefully review this material and decide with your doctor which option(s) you prefer, understanding that your doctor will always act in the best interest of his or her patient.

To assure a safe transfusion make sure your healthcare provider who starts the transfusion verifies your name and matches it to the blood that is going to be transfused. Besides your name, a second personal identifier usually used is your birthday. This assures the blood is given to the correct patient.

If during the transfusion you have symptoms of shortness of breath, itching,fever or chills or just not feeling well, alert the person transfusing the blood immediately.

Blood can be provided from two sources: autologous blood (using your own blood) or donor blood (using someone else’s blood).

Autologous blood (using your own blood)

Pre-operative donation: donating your own blood before surgery. The blood bank draws your blood and stores it until you need it during or after surgery. This option is only for non-emergency (elective) surgery. It has the advantage of eliminating or minimizing the need for someone else’s blood during and after surgery. The disadvantage is that it requires advanced planning which may delay surgery. Some medical conditions may prevent the pre-operative donation of blood products.

Intra-operative autologous transfusion: recycling your blood during surgery. Blood lost during surgery is filtered, and put back into your body during surgery. This can be done in emergency and elective surgeries. It has the advantage of eliminating or minimizing the need for someone else’s blood during surgery. Large amounts of blood can be recycled. This process cannot be used if cancer or infection is present.

Post-operative autologous transfusion: recycling your blood after surgery. Blood lost after surgery is collected, filtered and returned to your body. This can be done in emergency and elective surgeries. It has the advantage of eliminating or minimizing the need for someone else’s blood during surgery. This process can’t be used in patients where cancer or infection is present.

Hemodilution: donating your own blood during surgery. Immediately before surgery, some of your blood is taken and replaced with IV fluids. After surgery, your blood is filtered and returned to you. This is done only for elective surgeries. This process dilutes your own blood so you lose less concentrated blood during surgery. It has the advantage of eliminating or minimizing the need for someone else’s blood during surgery. The disadvantage of this process is that only a limited amount of blood can be removed, and certain medical conditions may prevent the use of this technique.

Apheresis: donating your own platelets and plasma. Before surgery, your platelets and plasma, which help stop bleeding, are withdrawn, filtered and returned to you when you need it later. This can be done only for elective surgeries. This process may eliminate the need for donor platelets and plasma, especially in high blood-loss procedures. The disadvantage of this process is that some medical conditions may prevent apheresis, and in actual practice it has limited applications. 

http://www.medicinenet.com/blood_transfusion/article.htm

Diseases Requiring Blood Transfusion

Cancer

Some illnesses cause your body to make too few platelets or clotting factors. You may need transfusions of just those blood components to make up for low levels.

Cancer may decrease your body’s production of red blood cells, white blood cells and platelets by impacting the organs that influence blood count, such as the kidneys, bone marrow and the spleen. Radiation and chemotherapy drugs also can decrease components of the blood. Blood transfusions may be used to counter such effects.

Other illness

Some illnesses cause your body to make too few platelets or clotting factors. You may need transfusions of just those blood components to make up for low levels.

Infection, liver failure or severe burns

If you experience an infection, liver failure or severe burns, you may need a transfusion of plasma. Plasma is the liquid part of blood.

Blood disorders

People with blood diseases may receive transfusions of red blood cells, platelets or clotting factors.

Severe liver malfunction

If you have severe liver problems, you may receive a transfusion of albumin, a blood protein.

Risks

By Mayo Clinic Staff

Blood transfusions are generally considered to be safe. But they do carry some risk of complications. Complications may happen during the transfusion or not for weeks, months or even years afterward. They include the following:

Allergic reaction and hives

If you have an allergic reaction to the transfusion, you may experience hives and itching during the procedure or very soon after. This type of reaction is usually treated with antihistamines. Rarely, a more serious allergic reaction causes difficulty breathing, low blood pressure and nausea.

Fever

If you quickly develop a fever during the transfusion, you may be having a febrile transfusion reaction. Your doctor will stop the transfusion to do further tests before deciding whether to continue. A febrile reaction can also occur shortly after the transfusion. Fever may be accompanied by chills and shaking.

Acute immune hemolytic reaction

This is a very rare but serious transfusion reaction in which your body attacks the transfused red blood cells because the donor blood type is not a good match. In response, your immune system attacks the transfused red blood cells, which are viewed as foreign. These destroyed cells release a substance into your blood that harms your kidneys. This usually occurs during or right after a transfusion. Signs and symptoms include fever, nausea, chills, lower back or chest pain, and dark urine.

Lung injury

Transfusion-related acute lung injury (TRALI) is thought to occur due to antibodies or other biologic substances in the blood components. With TRALI, the lungs become damaged, making it difficult to breathe. Usually, TRALI occurs within one to six hours of the transfusion. People usually recover, especially when treated quickly. Most people who die after TRALI were very sick before the transfusion.

Bloodborne infections

Blood banks screen donors for risk factors and test donated blood to reduce the risk of transfusion-related infections. Infections related to blood transfusion still rarely may occur. It can take weeks or months after a blood transfusion to determine that you’ve been infected with a virus, bacterium or parasite.

The National Institutes of Health offers the following estimates for the risk of a blood donation carrying an infectious disease:

  • HIV — 1 in 2 million donations, which is lower than the risk of being killed by lightning
  • Hepatitis B — 1 in 205,000 donations
  • Hepatitis C — 1 in 2 million donations

Delayed hemolytic reaction

This type of reaction is similar to an acute immune hemolytic reaction, but it occurs much more slowly. Your body gradually attacks the donor red blood cells. It could take one to four weeks to notice a decrease in red blood cell levels.

Iron overload  

If you receive multiple blood transfusions, you may end up with too much iron in your blood. Iron overload (hemochromatosis) can damage parts of your body, including the liver and the heart. You may receive iron chelation therapy, which uses medication to remove excess iron.

Graft-versus-host disease

Transfusion-associated graft-versus-host disease is a very rare condition in which transfused white blood cells attack the recipient’s bone marrow. This disease is usually fatal. It is more likely to affect people with severely weakened immune systems, such as those being treated for leukemia or lymphoma. Signs and symptoms include fever, rash, diarrhea and abnormal liver function test results. Irradiating the blood before transfusing it reduces the risk.

Most of the donated blood collected by the American Red Cross is used for direct blood transfusions. Common types of blood transfusions including platelet, plasma and red blood cell transfusions.

A patient suffering from an iron deficiency or anemia, a condition where the body does not have enough red blood cells, may receive a Red Blood Cell Transfusion. This type of transfusion increases a patient’s hemoglobin and iron levels, while improving the amount of oxygen in the body.

Platelets are a component of blood that stops the body from bleeding. Often patients suffering from leukemia, or other types of cancer, have lower platelet counts as a side effect of their chemotherapy treatments. Patients who have illnesses that prevent the body from making enough platelets have to get regular transfusions to stay healthy.

Plasma is the liquid part of the body’s blood. It contains important proteins and other substances crucial to one’s overall health. Plasma transfusions are used for patients with liver failure, severe infections, and serious burns.

If you experience an infection, liver failure or severe burns, you may need a transfusion of plasma. Plasma is the liquid part of blood.

Blood disorders

People with blood diseases may receive transfusions of red blood cells, platelets or clotting factors.

Severe liver malfunction

If you have severe liver problems, you may receive a transfusion of albumin, a blood protein.

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Erythropoietin

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 Erythropoietin test

The erythropoietin test measures the amount of a hormone called erythropoietin (EPO) in blood.

The hormone tells stem cells in the bone marrow to make more red blood cells. EPO is made by cells in the kidney. These cells release more EPO when blood oxygen levels are low.

https://www.nlm.nih.gov/medlineplus/ency/article/003683.htm

The Story of Erythropoietin

Millions of patients worldwide have benefited from research on erythropoietin spanning many decades. In the last 15 years, epoetin alfa (Epo) has become one of the most widely used drugs created through recombinant DNA technology, in which a nearly identical form of a substance that naturally occurs in the body – in this case, erythropoietin – is created by replicating human DNA in a laboratory. Epo is used to treat anemia, a shortage of red blood cells. Since red blood cells carry oxygen to the tissues and organs, anemia causes symptoms such as weakness, fatigue, and shortness of breath. Epo treats this condition by imitating the action of the hormone erythropoietin, stimulating the body to produce more red blood cells. Patients who may benefit from Epo therapy include those with chronic kidney disease, those who are anemic from AIDS or from a wide variety of hematologic disorders (including multiple myeloma and myelodysplastic syndromes), and some cancer patients who are anemic from receiving chemotherapy. In selected patients, Epo may be used to reduce the need for blood transfusions in surgery.

A century ago, two French investigators reported that small amounts of plasma from anemic rabbits injected into normal animals caused an increase in red blood cell production (erythropoiesis) within a few hours. They referred to this activity as hemopoietine. Over time, as investigators became more convinced that this red-blood-cell stimulating activity was caused by a single protein in the blood plasma, they gave it a variety of names – erythropoietic-stimulating activity, erythropoietic-stimulating factor, and, ultimately, “erythropoietin.”

It wasn’t until the 1950s and ’60s that several American investigators again took up the concept that a hormone regulated red cell production. Refining the work of the French scientists, the American investigators conclusively showed that a hormone stimulated red cell production, that the kidneys were the primary source of erythropoietin, and that low oxygen was the main driver of erythropoietin production. Soon, researchers found that patients with anemia responded by increasing their levels of erythropoietin to stimulate increased red blood cell production. Patients who required an increase in red blood cells in order to make up for low oxygen levels in the blood (such as patients with lung disease or patients living at high altitudes) also had elevated erythropoietin levels.

At the same time, other technologies were being developed that set the stage for a remarkable breakthrough involving a combination of medical and molecular engineering. In the early 1960s came the development of hemodialysis, a method of removing waste products from the blood when the kidneys are unable to perform this function, to sustain the lives of patients with end-stage kidney disease. As a result of this treatment advance, these patients were able to survive the underlying disease, but their damaged kidneys could no longer make erythropoietin, leaving them severely anemic and in desperate need of Epo therapy.

In 1983, scientists discovered a method for mass producing a synthetic version of the hormone. Experiments were conducted to test the safety and effectiveness of the new drug, Epo, for treating anemia in patients with kidney failure. The results of these early clinical trials were dramatic. Patients who had been dependent on frequent blood transfusions were able to increase their red blood cell levels to near-normal within just a few weeks of starting therapy. Patients’ appetites returned, and they resumed their active lives. It was the convergence of two technologies – long-term dialysis and molecular biology – that set the stage for anemia management in this group of patients. Since then, millions of patients worldwide have benefited from Epo therapy.

This article was published in December 2008 as part of the special ASH anniversary brochure,50 Years in Hematology: Research That Revolutionized Patient Care.

http://www.hematology.org/About/History/50-Years/1532.aspx

Erythropoietin Stimulating Agents

https://my.clevelandclinic.org/health/diseases_conditions/hic_Anemia/hic_erythropoietin-stimulating_agents

What is erythropoietin?

Red blood cells are produced in the bone marrow (the spongy tissue inside the bone). In order to make red blood cells, the body maintains an adequate supply of erythropoietin (EPO), a hormone that is produced by the kidney.

EPO helps make red blood cells. Having more red blood cells raises your hemoglobin levels. Hemoglobin is the protein in red blood cells that helps blood carry oxygen throughout the body.

Anemia is a disorder that occurs when there is not enough hemoglobin in a person’s blood. There are several different causes of anemia. For instance, anemia can be caused by the body’s inability to produce enough EPO to make red blood cells. If this is the case, the person may have to have a blood transfusion to treat this type of anemia. If you have anemia, your physician can determine the cause.

What is recombinant erythropoietin?

In cases where transfusions are not an option—for example, when the patient cannot have, or refuses, a transfusion—it may be necessary to give the patient recombinant erythropoietin. Recombinant erythropoietin is a man-made version of natural erythropoietin. It is produced by cloning the gene for erythropoietin.

Recombinant erythropoietin drugs are known as erythropoietin-stimulating agents (ESAs). These drugs are given by injection (shot) and work by stimulating the production of more red blood cells. These cells are then released from the bone marrow into the bloodstream.

There are two ESAs on the U.S. market: epoetin alfa (Procrit,® Epogen®), and darbepoietin alfa (Aranesp®).

Who receives ESAs?

ESAs are usually given to patients who have chronic (long-lasting) kidney disease or end-stage renal (kidney) disease. These patients usually have lower hemoglobin levels because they can’t produce enough erythropoietin.

ESAs are also prescribed for patients who have cancer. These patients often have anemia, which can be caused by chemotherapy.

What are the side effects of ESAs?

The side effects that occur most often with ESA use include:

  • High blood pressure
  • Swelling
  • Fever
  • Dizziness
  • Nausea
  • Pain at the site of the injection.

What should the patient consider before using ESAs?

There are several safety issues with ESAs:

  • ESAs increase the risk of venous thromboembolism (blood clots in the veins). A blood clot can break away from one location and travel to the lung (pulmonary embolism), where it can block circulation. Symptoms of blood clots include chest pain, shortness of breath, pain in the legs, and sudden numbness or weakness in the face, arm, or leg.
  • ESAs can cause hemoglobin to rise too high, which puts the patient at higher risk for heart attack, stroke, heart failure, and death.
  • In patients who have cancer, ESAs may cause the tumor to grow. If ESAs are used for these patients, they are usually stopped after the patient’s chemotherapy is finished.
  • The health care provider will keep an eye on the patient’s blood cell counts to make sure they do not put him or her at a higher risk. The dosing may change, depending on the patient’s needs.

Patients who have the following conditions need to consult with their health care provider if an ESA is being considered as part of the treatment plan:

  • Heart disease
  • High blood pressure
  • Porphyria (a group of diseases that are caused by enzyme deficiencies)
  • Seizures
  • An allergy to epoetin alfa or any other part of this medicine
  • Uncontrolled high blood pressure

In addition, women who are pregnant, planning to become pregnant, or breastfeeding should consult with their health care provider before taking an ESA.

Other issues to consider:

  • Transfusions may improve symptoms of anemia right away. ESAs may take from weeks to months to provide noticeable relief of the symptoms of anemia.
  • If a patient has several transfusions, he or she can develop an “iron overload,” or high iron levels. This is a serious medical problem.
  • Iron supplements are often needed for patients who are on ESAs.
  • Keep your health care provider informed about any change in your condition.
  • Check your blood pressure and heart rate as recommended by your health care provider.
  • Remain informed about the results from any blood work that is done.
  • The body may develop antibodies to an ESA. If this happens, the antibodies will block or lessen the body’s ability to make red blood cells. This could result in an anemia. It is important that the patient keep the health care provider informed of any unusual tiredness, lack of energy, dizziness, or fainting.

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