Posts Tagged ‘mechanisms of disease’

Can IntraTumoral Heterogeneity Be Thought of as a Mechanism of Resistance?

Curator/Reporter: Stephen J. Williams, Ph.D.

Therapeutic resistance remains one of the most challenging problems for the oncologist, despite the increase of new therapeutics in the oncologist’s toolkit. As new targeted therapies are developed, and new novel targets are investigated as potential therapies, especially cytostatic therapies which it has become evident our understanding of chemoresistance is expanding beyond mechanisms to circumvent a drug’s pharmacologic mechanism of action (i.e. increased DNA repair and cisplatin) or pharmacokinetic changes (i.e. increased efflux by acquisition of a MDR phenotype).

In a talk at the 2015 AACR National Meeting, Dr. Charles Swanton discusses the development of tumor heterogeneity in the light of developing, or acquired, drug resistance. Chemoresistance is either categorized as acquired resistance (where resistance develops upon continued exposure to drug) or inherent resistance (related to a tumor being refractory or unresponsive to drug). Dr Swanton discusses findings where development of this heterogeneity (discussed here in a posting on Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing) and here (Notes On Tumor Heterogeneity: Targets and Mechanisms, from the 2015 AACR Meeting in Philadelphia PA) on recent findings on Branched Chain Heterogeneity) is resulting in clones resistant to the initial drug treatment.

To recount a bit of background I list the overall points of the one of previous posts on tumor heterogeneity (and an interview with Dr. Charles Swanton) are as follows:

Multiple biopsies of primary tumor and metastases are required to determine the full mutational landscape of a patient’s tumor

The intratumor heterogeneity will have an impact on the personalized therapy strategy for the clinician

Metastases arising from primary tumor clones will have a greater genomic instability and mutational spectrum than the tumor from which it originates

Tumors and their metastases do NOT evolve in a linear path but have a branched evolution and would complicate biomarker development and the prognostic and resistance outlook for the patient


The following is a curation of various talks and abstracts from the 2015 AACR National Meeting in Philadelphia on effects of clonal evolution and intratumoral heterogeneity of a tumor with respect to development of chemoresistance. As this theory of heterogeneity and clonal evolution is particularly new I attempted to present all works (although apologize for the length upfront) to forgo bias and so the reader may extract any information pertinent to their clinical efforts and research. However I will give a brief highlight summary below:


From the 2015 AACR National Meeting in Philadelphia






Presentation Title: Polyclonal and heterogeneous resistance to targeted therapy in leukemia
Presentation Time: Monday, Apr 20, 2015, 10:40 AM -10:55 AM
Location: Room 201, Pennsylvania Convention Center
Author Block: Catherine C. Smith, Amy Paguirigan, Chen-Shan Chin, Michael Brown, Wendy Parker, Mark J. Levis, Alexander E. Perl, Kevin Travers, Corynn Kasap, Jerald P. Radich, Susan Branford, Neil P. Shah. University of California, San Francisco, CA, Fred Hutchinson Cancer Research Center, Seattle, WA, Pacific Biosciences, Menlo Park, CA, Royal Adelaide Hospital, Adelaide, Australia, Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, University of California, San Francisco, CA
Abstract Body: Genomic studies in solid tumors have revealed significant branching intratumoral clonal genetic heterogeneity. Such complexity is not surprising in solid tumors, where sequencing studies have revealed thousands of mutations per tumor genome. However, in leukemia, the genetic landscape is considerably less complex. Chronic myeloid leukemia (CML) is the human malignancy most definitively linked to a single genetic lesion, the BCR-ABL gene fusion. Genome wide sequencing of acute myeloid leukemia (AML) has revealed that AML is the most genetically straightforward of all extensively sequenced adult cancers to date, with an average of 13 coding mutations and 3 or less clones identified per tumor.
In CML, tyrosine kinase inhibitors (TKIs) of BCR-ABL have resulted in high rates of remission. However, despite excellent initial response rates with TKI monotherapy, patients still relapse, including virtually all patients with Philadelphia-positive acute lymphoblastic leukemia and blast crisis CML. Studies of clinical resistance highlight BCR-ABL as the sole genetic driver in CML as secondary kinase domain (KD) mutations that prevent drug binding are the predominant mechanism of relapse on BCR-ABL TKIs.
In AML, a more diverse panel of disease-defining genetic mutations has been uncovered. However, in individual patients, a single oncogene can still drive disease. This is the case in FLT3 mutant AML, in which the investigational FLT3 TKI quizartinib achieved an initial response rate of ~50% in relapsed/refractory AML patients with activating FLT3 internal tandem duplication (ITD) mutations, though most patients eventually relapsed. Confirming the importance of FLT3 in disease maintenance, we showed that 8 of 8 patients who relapsed on quizartinib did so due to acquired drug-resistant FLT3 KD mutations.
Studies in CML have revealed that sequential TKI therapy is associated with additional complexity where multiple mutations can coexist separately in an individual patient (“polyclonality”) or in tandem on a single allele (“compound mutations”). In AML, we observed polyclonal FLT3-ITD KD mutations in 2 of 8 patients examined in our initial study of quizartinib resistance.
In light of the polyclonal KD mutations observed in CML and AML at the time of TKI relapse, we undertook next generation sequencing studies to determine the true genetic complexity in CML and AML patients at the time of relapse on targeted therapy. We used Pacific Biosciences RS Single Molecule Real Time (SMRT) third generation sequencing technology to sequence the entire ABL KD or the entire FLT3 juxtamembrane and KD on a single strand of DNA. Using this method, we assessed a total of 103 samples from 79 CML patients on ABL TKI therapy and 36 paired pre-treatment and relapse samples from 18 FLT3-ITD+ AML patients who responded to investigational FLT3 TKI therapy.
In CML, using SMRT sequencing, we detected all mutations previously detected by direct sequencing. Of samples in which multiple mutations were detectable by direct sequencing, 85% had compound mutant alleles detectable in a variety of combinations. Compound mutant alleles were comprised of both dominant and minor mutations, some which were not detectable by direct sequencing. In the most complex case, 12 individual mutant alleles comprised of 7 different mutations were identified in a single sample.
For 12 CML patients, we interrogated longitudinal samples (2-4 time points per patient) and observed complex clonal relationships with highly dynamic shifts in mutant allele populations over time. We detected compound mutations arising from ancestral single mutant clones as well as parallel evolution of de novo polyclonal and compound mutations largely in keeping with what would be expected to cause resistance to the second generation TKI therapy received by that patient.
We used a phospho-flow cytometric technique to assesses the phosphorylation status of the BCR-ABL substrate CRKL in as a method to test the ex vivo biochemical responsiveness of individual mutant cell populations to TKI therapy and assess functional cellular heterogeneity in a given patient at a given timepoint. Using this technique, we observed co-existing cell populations with differential ex vivo response to TKI in 2 cases with detectable polyclonal mutations. In a third case, we identified co-existence of an MLL-AF9 containing cell population that retained the ability to modulate p-CRKL in response to BCR-ABL TKIs along with a BCR-ABL containing only population that showed biochemical resistance to all TKIs, suggesting the co-existence of BCR-ABL independent and dependent resistance in a single patient.
In AML, using SMRT sequencing, we identified acquired quizartinib resistant KD mutations on the FLT3-ITD (ITD+) allele of 9 of 9 patients who relapsed after response to quizartinib and 4 of 9 patients who relapsed after response to the investigational FLT3 inhibitor, PLX3397. In 4 cases of quizartinib resistance and 3 cases of PLX3397 resistance, polyclonal mutations were observed, including 7 different KD mutations in one patient with PLX3397 resistance. In 7 quizartinib-resistant cases and 3 PLX3397-resistant cases, mutations occurred at the activation loop residue D835. When we examined non-ITD containing (ITD-) alleles, we surprisingly uncovered concurrent drug-resistant FLT3 KD mutations on ITD- alleles in 7 patients who developed quizartinib resistance and 4 patients with PLX3397 resistance. One additional PLX3397-resistant patient developed a D835Y mutation only in ITD- alleles at the time of resistance, suggesting selection for a non-ITD containing clone. All of the individual substitutions found on ITD- alleles were the same substitutions identified on ITD+ alleles for each individual patient.
Given that the same individual mutations found on ITD- alleles were also found on ITD+ alleles, we sought to determine whether these mutations were found in the same cell or were indicative of polyclonal blast populations in each patient. To answer this question, we performed single cell sorting of viably frozen blasts from 3 quizartinib-resistant patients with D835 mutations identified at the time of relapse and genotyped single cells for the presence or absence of ITD and D835 mutations. This analysis revealed striking genetic heterogeneity. In 2/3 cases, polyclonal D835 mutations were found in both ITD+ and ITD- cells. In all cases, FLT3-ITD and D835 mutations were found in both heterozygous and homozygous combinations. Most surprisingly, in all 3 patients, approximately 30-40% of FLT3-ITD+ cells had no identified quizartinib resistance-causing FLT3 KD mutation to account for resistance, suggesting the presence of non-FLT3 dependent resistance in all patients.
To determine that ITD+ cells lacking FLT3 KD mutations observed in patients relapsed on quizartinib are indeed consistent with leukemic blasts functionally resistant to quizartinib and do not instead represent a population of differentiated or non-proliferating cells, we utilized relapse blasts from another patient who initially achieved clearance of bone marrow blasts on quizartinib and developed a D835Y mutation at relapse. We performed a colony assay in the presence of 20nM quizartinib. As expected, this dose of quizartinib was unable to suppress the colony-forming ability of blasts from this relapsed patient when compared to DMSO treatment. Genotyping of individual colonies grown from this relapse sample in the presence of 20nM quizartinib again showed remarkable genetic heterogeneity, including ITD+ and ITD- colonies with D835Y mutations in homozygous and heterozygous combinations as well as ITD+ colonies without D835Y mutations, again suggesting the presence of blasts with non-FLT3 dependent resistance. Additionally, 4 colonies with no FLT3 mutations at all were identified in this sample, suggesting the presence of a quizartinib-resistant non-FLT3 mutant blast population. To see if we could identify specific mechanisms of off-target resistance, we performed targeted exome sequencing 33-AML relevant genes from relapse and pre-treatment DNA from all four patients and detected no new mutations in any genes other than FLT3 acquired at the time of disease relapse. Clonal genetic heterogeneity is not surprising in solid tumors, where multiple driver mutations frequently occur, but in CML and FLT3-ITD+ AML, where disease has been shown to be exquisitely dependent on oncogenic driver mutations, our studies suggest a surprising amount of clonal diversity. Our findings show that clinical TKI resistance in these diseases is amazingly intricate on the single allele level and frequently consists of both polyclonal and compound mutations that give rise to an complicated pool of TKI-resistant alleles that can change dynamically over time. In addition, we demonstrate that cell populations with off-target resistance can co-exist with other TKI-resistant populations, underscoring the emerging complexity of clinical TKI resistance. Such complexity argues strongly that monotherapy strategies in advanced CML and AML may be ultimately doomed to fail due to heterogeneous cell intrinsic resistance mechanisms. Ultimately, combination strategies that can address both on and off target resistance will be required to effect durable therapeutic responses.
Session Title: Tumor Heterogeneity and Evolution
Session Type: Educational Session
Session Start/End Time: Saturday, Apr 18, 2015, 1:00 PM – 3:00 PM
Location: Terrace Ballroom II-III (400 Level), Pennsylvania Convention Center
CME: CME-Designated
CME/CE Hours: 2
Session Description: One of the major challenges for both the measurement and management of cancer is its heterogeneity. Recent studies have revealed both extensive inter- and intra-tumor heterogeneity at the genotypic and phenotypic levels. Leaders in the field will discuss this challenge, its origins, dynamics and clinical importance. They will also review how we can best measure and deal with tumor heterogeneity, particularly intra-tumor heterogeneity.
Saturday, Apr 18, 2015, 1:00 PM – 3:00 PM
Carlo C. Maley. UCSF Helen Diller Family Comp. Cancer Center, San Francisco, CA
Universal biomarkers: How to handle tumor heterogeneity
Saturday, Apr 18, 2015, 1:00 PM – 1:25 PM
Carlo C. Maley. UCSF Helen Diller Family Comp. Cancer Center, San Francisco, CA
Saturday, Apr 18, 2015, 1:25 PM – 1:30 PM
Heterogeneity of resistance to cancer therapy
Saturday, Apr 18, 2015, 1:30 PM – 1:55 PM
Ivana Bozic. HARVARD UNIV., Cambridge, MA
Saturday, Apr 18, 2015, 1:55 PM – 2:00 PM
Determinants of phenotypic intra-tumor heterogeneity: integrative approach
Saturday, Apr 18, 2015, 2:00 PM – 2:25 PM
Andriy Marusyk, Michalina Janiszewska, Doris Tabassum. Dana-Farber Cancer Institute, Boston, MA, Dana-Farber Cancer Institute, Boston, MA
Saturday, Apr 18, 2015, 2:25 PM – 2:30 PM
Cancer clonal complexity and evolution at the macro- and microheterogeneity scale
Saturday, Apr 18, 2015, 2:30 PM – 2:55 PM
Marco Gerlinger. Institute of Cancer Research, London, United Kingdom
Saturday, Apr 18, 2015, 2:55 PM – 3:00 PM

From Ivana Bozic:

A spatial model predicts that dispersal and cell turnover limit intratumour heterogeneity.

Waclaw B, Bozic I, Pittman ME, Hruban RH, Vogelstein B, Nowak MA.

Nature. 2015 Sep 10;525(7568):261-4. doi: 10.1038/nature14971. Epub 2015 Aug 26.



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Timing and heterogeneity of mutations associated with drug resistance in metastatic cancers.

Bozic I, Nowak MA.

Proc Natl Acad Sci U S A. 2014 Nov 11;111(45):15964-8. doi: 10.1073/pnas.1412075111. Epub 2014 Oct 27.



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Session Title: Mechanisms of Cancer Therapy Resistance
Session Type: Educational Session
Session Start/End Time: Saturday, Apr 18, 2015, 1:00 PM – 3:00 PM
Location: Room 204, Pennsylvania Convention Center
CME: CME-Designated
CME/CE Hours: 2
Session Description: Despite dramatic advances in the treatment of cancer, therapy resistance remains the most significant hurdle in improving the outcome of cancer patients. In this session, we will discuss many different aspects of therapy resistance, including a summary of our current understanding of therapy resistant tumor cell populations as well as analyses of the challenges associated with intratumoral heterogeneity and adaptive responses to targeted therapies.
Saturday, Apr 18, 2015, 1:00 PM – 3:00 PM
Charles Swanton. Cancer Research UK London Research Institute, London, United Kingdom
Tumor heterogeneity and drug resistance
Saturday, Apr 18, 2015, 1:00 PM – 1:30 PM
Charles Swanton. Cancer Research UK London Research Institute, London, United Kingdom

Saturday, Apr 18, 2015, 1:30 PM – 1:40 PM
Discussion Discussion, Discussion

Principles of resistance to targeted therapy
Saturday, Apr 18, 2015, 1:40 PM – 2:10 PM
Levi A. Garraway. Dana-Farber Cancer Institute, Boston, MA

Saturday, Apr 18, 2015, 2:10 PM – 2:20 PM
Discussion Discussion, Discussion

Adaptive re-wiring of signaling pathways driving drug resistance to targeted therapies
Saturday, Apr 18, 2015, 2:20 PM – 2:50 PM
Taru E. Muranen. Harvard Medical School, Boston, MA

Saturday, Apr 18, 2015, 2:50 PM – 3:00 PM
Discussion Discussion, Discussion

Presentation Abstract  




Abstract Number: 737
Presentation Title: Clonal evolution of the HER2 L755S mutation as a mechanism of acquired HER-targeted therapy resistance
Presentation Time: Sunday, Apr 19, 2015, 1:00 PM – 5:00 PM
Location: Section 30
Poster Board Number: 29
Author Block: Xiaowei Xu1, Agostina Nardone1, Huizhong Hu1, Lanfang Qin1, Sarmistha Nanda1, Laura Heiser2, Nicholas Wang2, Kyle Covington1, Edward Chen1, Alexander Renwick1, Tamika Mitchell1, Marty Shea1, Tao Wang1, Carmine De Angelis1, Alejandro Contreras1, Carolina Gutierrez1, Suzanne Fuqua1, Gary Chamness1, Chad Shaw1, Marilyn Li1, David Wheeler1, Susan Hilsenbeck1, Mothaffar Fahed Rimawi1, Joe Gray2, C.Kent Osborne1, Rachel Schiff1. 1Baylor College of Medicine, Houston, TX; 2Oregon Health & Science University, Portland, OR
Abstract Body: Background: Targeting HER2 with lapatinib (L), trastuzumab (T), or the LT combination, is effective in HER2+ breast cancer (BC), but acquired resistance commonly occurs. In our 12-week neoadjuvant
trial (TBCRC006) of LT without chemotherapy in HER2+ BC, the overall pathologic complete response (pCR) rate was 27%. To investigate resistance mechanisms, we developed 10 HER2+ BC cell line
models resistant (R) to one or both drugs (LR/TR/LTR). To discover potential predictive markers/therapeutic targets to circumvent resistance, we completed genomic profiling of the cell lines and a
subset of pre-treatment specimens from TBCRC006.
Methods: Parental (P) and LR/TR/LTR lines of 10 cell line models were profiled with whole exome/RNA sequencing. Mutations detected in R lines but not in P lines of the same model were identified. Mutation-specific Q-PCR was designed for sensitive quantification. Resistant cell and xenograft tumor growth were measured in response to drugs. Whole exome sequencing (>100X) and Ampliseq of 17 baseline tumor/normal pairs from TBCRC006 were performed.
Results: We found and validated the HER2 L755S mutation in the BT474/ATCC-LTR line and BT474/AZ-LR line (in ~30% of DNA/RNA), in which the HER pathway was reactivated for resistance. Overexpression of this mutation was previously shown to induce LR in HER2-negative BC cell lines, and resistant growth of BT474/AZ-LR line is significantly inhibited by HER2-L755S-specific siRNA knock-down, suggesting its role as an acquired L/LT resistance driver in HER2+ BC. Sequencing of BT474/AZ-LR single cell clones found the mutation in ~30% of HER2 copies in every cell. Using mutation-specific Q-PCR, we found statistically higher HER2 L755S levels in two BT474 parentals compared to P lines of SKBR3, AU565, and UACC812. These data suggest that HER2 L755S resistant subclones preexist in the BT474 parentals and were selected by L treatment to become the major clone in the two R lines. The HER1/2 irreversible tyrosine kinase inhibitor (TKI) afatinib (Afa) robustly inhibited growth of BT474/AZ-LR and BT474/ATCC-LTR cells (IC50: Afa 0.02µM vs. L 3 µM) and BT474/AZ-LR xenografts. Whole exome sequencing/Ampliseq of TBCRC006 found the HER2 L755S mutation in 1/17 primaries. This patient did not achieve pCR. The variant was present in 2% of DNA on both platforms, indicating a subclonal event of the resistance mutation.
Conclusion: Acquired L/LT resistance in the two BT474 R lines is due to selection of HER2 L755S subclones present in parental cells. The higher HER2 L755S
levels in BT474 parentals compared with other parentals, and detection of its subclonal presence in a pre-treatment HER2+ BC patient, suggest that sensitive mutation detection methods will be needed to identify patients with potentially actionable HER family mutations in primary tumor. Treating this patient group
with an irreversible TKI like Afa may prevent resistance and improve clinical outcome of this subset of HER2+ BC.
Presentation Number: SY07-04
Presentation Title: The evolutionary landscape of CLL: Therapeutic implications
Presentation Time: Sunday, Apr 19, 2015, 2:25 PM – 2:45 PM
Location: Grand Ballroom (300 Level), Pennsylvania Convention Center
Author Block: Catherine J. Wu. Dana-Farber Cancer Institute, Boston, MA
Abstract Body: Clonal evolution is a key feature of cancer progression and relapse. Recent studies across cancers have demonstrated the extensive degree of intratumoral heterogeneity present within individual cancers. We hypothesized that evolutionary dynamics contribute to the variations in disease tempo and response to therapy that are highly characteristic of chronic lymphocytic leukemia (CLL). We have recently investigated this phenomenon by developing a pipeline that estimates the fraction of cancer cells harboring each somatic mutation within a tumor through integration of whole-exome sequence (WES) and local copy number data (Landau et al., Cell 2013). By applying this analysis approach to 149 CLL cases, we discovered earlier and later cancer drivers, uncovered patterns of clonal evolution in CLL and linked the presence of subclones harboring driver mutations with adverse clinical outcome. Thus, our study, generated from a heterogeneous sample cohort, strongly supports the concept that CLL clonal evolution arises from mass extinction and therapeutic bottlenecks which lead to the emergence of highly fit (and treatment resistant) subclones. We further hypothesized that epigenetic heterogeneity also shapes CLL clonal evolution through interrelation with genetic heterogeneity. Indeed, in recent work, we have uncovered stochastic methylation disorder as the primary cause of methylation changes in CLL and cancer in general, and that this phenomena impacts gene transcription, genetic evolution and clinical outcome. Thus, integrated studies of genetic and epigenetic heterogeneity in CLL have revealed the complex and diverse evolutionary trajectories of these cancer cells.
Immunotherapy is exquisitely suited for specifically and simultaneously targeting multiple lesions. We have developed an approach that leverages whole-exome sequencing to systematically identify personal tumor mutations with immunogenic potential, which can be incorporated as antigen targets in multi-epitope personalized therapeutic vaccines. We are pioneering this approach in an ongoing trial in melanoma and will now expand this concept to address diverse malignancies. Our expectation is that the choice of tumor neoantigens for a vaccine bypasses thymic tolerance and thus generates highly specific and potent high-affinity T cell responses to eliminate tumors in any cancer, including both ‘trunk’ and ‘branch’ lesions.


Abstract Number: LB-056
Presentation Title: TP53 and RB1 alterations promote reprogramming and antiandrogen resistance in advanced prostate cancer
Presentation Time: Sunday, Apr 19, 2015, 4:50 PM – 5:05 PM
Location: Room 122, Pennsylvania Convention Center
Author Block: Ping Mu, Zhen Cao, Elizabeth Hoover, John Wongvipat, Chun-Hao Huang, Wouter Karthaus, Wassim Abida, Elisa De Stanchina, Charles Sawyers. Memorial Sloan Kettering Cancer Center, New York, NY
Abstract Body: Castration-resistant prostate cancer (CRPC) is one of the most difficult cancers to treat with conventional methods and is responsible for nearly all prostate cancer deaths in the US. The Sawyers laboratory first showed that the primary mechanism of resistance to antiandrogen therapy is elevated androgen receptor (AR) expression. Research based on this finding has led to the development of next-generation antiandrogen: enzalutamide. Despite the exciting clinical success of enzalutamide, about 60% of patients exhibit various degrees of resistance to this agent. Highly variable responses to enzalutamide limit the clinical benefit of this novel antiandrogen, underscoring the importance of understanding the mechanisms of enzalutamide resistance. Most recently, an unbiased SU2C-Prostate Cancer Dream Team metastatic CRPC sequencing project led by Dr. Sawyers and Dr. Chinnaiyan revealed that mutations in the TP53 locus are the most significantly enriched alteration in CRPC tumors when compared to primary prostate cancers. Moreover, deletions and decreased expressions of the TP53 and RB1 loci (co-occurrence and individual occurrence) are more commonly associated with CRPC than with primary tumors. These results established that alteration of the TP53 and RB1 pathways are associated with the development of antiandrogen resistance.
By knockdowning TP53 or/and RB1 in the castration resistant LNCaP/AR model, we demonstrate that the disruption of either TP53 or RB1 alone confers significant resistance to enzalutamide both in vitro and in vivo. Strikingly, the co-inactivation of these pathways confers the most dramatic resistance. Since up-regulation of either AR or AR target genes is not observed in the resistant tumors, loss of TP53 and RB1 function confers enzalutamide resistance likely through an AR independent mechanism. In the clinic, resistance to enzalutamide is increasingly being associated with a transition to a poorly differentiated or neuroendocrine-like histology. Interestingly, we observed significant up-regulations of the basal cell marker Ck5 and the neuroendocrine-like cell marker Synaptophysin in the TP53 and RB1 inactivated cells, as well as down-regulation of the luminal cell marker Ck8. The differences between these markers became even greater after enzalutamide treatment. By using the p53-stabilizing drug Nutlin, level of p53 is rescued and consequently the the decrease of AR protein caused by RB1 and TP53 knockdown is reversed. These results strongly suggest that interference of TP53 and RB1 pathways confers antiandrogen resistance by “priming” prostate cancer cells to reprogramming or transdifferentiation, likely neuroendocrine-like differentiation, in response to treatment. Futher experiments will be performed to assess the molecular mechanism of TP53/RB1 alterations in mediating cell programming and conferring antiandrogen resistance.


Abstract Number: LB-146
Presentation Title: TGF-β-induced tumor heterogeneity and drug resistance of cancer stem cells
Presentation Time: Monday, Apr 20, 2015, 1:00 PM – 5:00 PM
Location: Section 41
Author Block: Naoki Oshimori1, Daniel Oristian1, Elaine Fuchs2. 1Rockefeller University, New York, NY; 2HHMI/Rockefeller University, New York, NY
Abstract Body: Among the most common and life-threatening cancers world-wide, squamous cell carcinoma (SCC) exhibit high rates of tumor recurrence following anti-cancer therapy. Subsets of cancer stem cells (CSCs) often escape anti-cancer therapeutics and promote recurrence. However, its sources and mechanisms that generate tumor heterogeneity and therapy-resistant cell population are largely unknown. Tumor microenvironment may drive intratumor heterogeneity by transmitting signaling factors, oxygen and metabolites to tumor cells depending on their proximity to the local sources. While the hypothesis is attractive, experimental evidence is lacking, and non-genetic mechanisms that drive functional heterogeneity remain largely unknown. As a potential non-genetic factor, we focused on TGF-β because of its multiple roles in tumor progression.
Here we devise a functional reporter system to monitor, track and modify TGF-β signaling in mouse skin SCC in vivo. Using this approach, we found that perivascular TGF-β in the tumor microenvironment generates heterogeneity in TGF-β signaling in neighboring CSCs. This heterogeneity is functionally important: small subsets of TGF-β-responding CSCs proliferate more slowly than their non-responding counterparts. They also exhibit invasive morphology and a malignant differentiation program compared to their non-responding neighbors. By lineage tracing, we show that although TGF-β-responding CSCs clonally expand more slowly they gain a growth advantage in a remarkable ability to escape cisplatin-induced apoptosis. We show that indeed it is their progenies that make a substantial contribution in tumor recurrence. Surprisingly, the slower proliferating state of this subset of CSCs within the cancer correlated with but did not confer the survival advantage to anti-cancer drugs. Using transcriptomic, biochemical and genetic analyses, we unravel a novel mechanism by which heterogeneity in the tumor microenvironment allows a subset of CSCs to respond to TGF-β, and evade anti-cancer drugs.
Our findings also show that TGF-β established ability to suppress proliferation and promote invasion and metastasis do not happen sequentially, but rather simultaneously. This new work build upon the roles of this factor in tumor progression, and sets an important paradigm for a non-genetic factor that produces tumor heterogeneity.
Abstract Number: LB-129
Presentation Title: Identifying tumor subpopulations and the functional consequences of intratumor heterogeneity using single-cell profiling of breast cancer patient-derived xenografts
Presentation Time: Monday, Apr 20, 2015, 1:00 PM – 5:00 PM
Location: Section 41
Author Block: Paul Savage1, Sadiq M. Saleh1, Ernesto Iacucci1, Timothe Revil1, Yu-Chang Wang1, Nicholas Bertos1, Anie Monast1, Hong Zhao1, Margarita Souleimanova1, Keith Szulwach2, Chandana Batchu2, Atilla Omeroglu1, Morag Park1, Ioannis Ragoussis1. 1McGill University, Montreal, QC, Canada; 2Fluidigm Corporation, South San Francisco, CA
Abstract Body: Human breast tumors have been shown to exhibit extensive inter- and intra-tumor heterogeneity. While recent advances in genomic technologies have allowed us to deconvolute this heterogeneity, few studies have addressed the functional consequences of diversity within tumor populations. Here, we identified an index case for which we have derived a patient-derived xenograft (PDX) as a renewable tissue source to identify subpopulations and perform functional assays. On pathology, the tumor was an invasive ductal carcinoma which was hormone receptor-negative, HER2-positive (IHC 2+, FISH average HER2/CEP17 2.4), though the FISH signal was noted to be heterogeneous. On gene expression profiling of bulk samples, the primary tumor and PDX were classified as basal-like. We performed single cell RNA and exome sequencing of the PDX to identify population structure. Using a single sample predictor of breast cancer subtype, we have identified single basal-like, HER2-enriched and normal-like cells co-existing within the PDX tumor. Genes differentially expressed between these subpopulations are involved in proliferation and differentiation. Functional studies distinguishing these subpopulations are ongoing. Microfluidic whole genome amplification followed by whole exome capture of 81 single cells showed high and homogeneous target enrichment with >75% of reads mapping uniquely on target. Variant calling using GATK and Samtools revealed founder mutations in key genes as BRCA1 and TP53, as well as subclonal mutations that are being investigated further. Loss of heterozygocity was observed in 16 TCGA cancer driver genes and novel mutations in 7 cancer driver genes. These findings may be important in understanding the functional consequences of intra-tumor heterogeneity with respect to clinically important phenotypes such as invasion, metastasis and drug-resistance.
Abstract Number: 2847
Presentation Title: High complexity barcoding to study clonal dynamics in response to cancer therapy
Presentation Time: Monday, Apr 20, 2015, 4:35 PM – 4:50 PM
Location: Room 118, Pennsylvania Convention Center
Author Block: Hyo-eun C. Bhang1, David A. Ruddy1, Viveksagar Krishnamurthy Radhakrishna1, Rui Zhao2, Iris Kao1, Daniel Rakiec1, Pamela Shaw1, Marissa Balak1, Justina X. Caushi1, Elizabeth Ackley1, Nicholas Keen1, Michael R. Schlabach1, Michael Palmer1, William R. Sellers1, Franziska Michor2, Vesselina G. Cooke1, Joshua M. Korn1, Frank Stegmeier1. 1Novartis Institutes for BioMedical Research, Cambridge, MA; 2Dana-Farber Cancer Institute, Boston, MA
Abstract Body: Targeted therapies, such as erlotinib and imatinib, lead to dramatic clinical responses, but the emergence of resistance presents a significant challenge. Recent studies have revealed intratumoral heterogeneity as a potential source for the emergence of therapeutic resistance. However, it is still unclear if relapse/resistance is driven predominantly by pre-existing or de novo acquired alterations. To address this question, we developed a high-complexity barcode library, ClonTracer, which contains over 27 million unique DNA barcodes and thus enables the high resolution tracking of cancer cells under drug treatment. Using this library in two clinically relevant resistance models, we demonstrate that the majority of resistant clones pre-exist as rare subpopulations that become selected in response to therapeutic challenge. Furthermore, our data provide direct evidence that both genetic and non-genetic resistance mechanisms pre-exist in cancer cell populations. The ClonTracer barcoding strategy, together with mathematical modeling, enabled us to quantitatively dissect the frequency of drug-resistant subpopulations and evaluate the impact of combination treatments on the clonal complexity of these cancer models. Hence, monitoring of clonal diversity in drug-resistant cell populations by the ClonTracer barcoding strategy described here may provide a valuable tool to optimize therapeutic regimens towards the goal of curative cancer therapies.
Abstract Number: 3590
Presentation Title: Resistance mechanisms to ALK inhibitors
Presentation Time: Tuesday, Apr 21, 2015, 8:00 AM -12:00 PM
Location: Section 31
Poster Board Number: 13
Author Block: Ryohei Katayama1, Noriko Yanagitani1, Sumie Koike1, Takuya Sakashita1, Satoru Kitazono1, Makoto Nishio1, Yasushi Okuno2, Jeffrey A. Engelman3, Alice T. Shaw3, Naoya Fujita1. 1Japanese Foundation for Cancer Research, Tokyo, Japan; 2Graduate School of Medicine, Kyoto University, Kyoto, Japan; 3Massachusetts General Hospital Cancer Center, Boston, MA
Abstract Body: Purpose: ALK-rearranged non-small cell lung cancer (NSCLC) was first reported in 2007. Approximately 3-5% of NSCLCs harbor an ALK gene rearrangement. The first-generation ALK tyrosine kinase inhibitor (TKI) crizotinib is a standard therapy for patients with advanced ALK-rearranged NSCLC. Several next-generation ALK-TKIs have entered the clinic and have shown promising antitumor activity in crizotinib-resistant patients. As patients still relapse even on these next-generation ALK-TKIs, we examined mechanisms of resistance to one next-generation ALK-TKI – alectinib – and potential strategies to overcome this resistance.
Experimental Procedure: We established a cell line model of alectinib resistance, and analyzed resistant tumor specimens from patients who had relapsed on alectinib. Cell lines were also established under an IRB-approved protocol when there was sufficient fresh tumor tissue. We established Ba/F3 cells expressing EML4-ALK and performed ENU mutagenesis to compare potential crizotinib or alectinib-resistance mutations. In addition, we developed Ba/F3 models harboring ALK resistance mutations and evaluated the potency of multiple next-generation ALK-TKIs including 3rd generation ALK inhibitor in these models and in vivo. To elucidate structure-activity-relationships of ALK resistance mutations, we performed computational thermodynamic simulation with MP-CAFEE.
Results: We identified multiple resistance mutations, including ALK I1171N, I1171S, and V1180L, from the ENU mutagenesis screen and the cell line model. In addition we found secondary mutations at the I1171 residue from the Japanese patients who developed resistance to alectinib or crizotinib. Both ALK mutations (V1180L and I1171 mutations) conferred resistance to alectinib as well as to crizotinib, but were sensitive to ceritinib and other next-generation ALK-TKIs. Based on thermodynamics simulation, each resistance mutation is predicted to lead to distinct structural alterations that decrease the binding affinity of ALK-TKIs for ALK.
Conclusions: We have identified multiple alectinib-resistance mutations from the cell line model, patient derived cell lines, and tumor tissues, and ENU mutagenesis. ALK secondary mutations arising after alectinib exposure are sensitive to other next generation ALK-TKIs. These findings suggest a potential role for sequential therapy with multiple next-generation ALK-TKIs in patients with advanced, ALK-rearranged cancers.
Session Title: Mechanisms of Resistance: From Signaling Pathways to Stem Cells
Session Type: Major Symposium
Session Start/End Time: Tuesday, Apr 21, 2015, 10:30 AM -12:30 PM
Location: Terrace Ballroom II-III (400 Level), Pennsylvania Convention Center
CME: CME-Designated
CME/CE Hours: 2
Session Description: Even the most effective cancer therapies are limited due to the development of one or more resistance mechanisms. Acquired resistance to targeted therapies can, in some cases, be attributed to the selective propagation of a small population of intrinsically resistant cells. However, there is also evidence that cancer drugs themselves can drive resistance by triggering the biochemical- or genetic-reprogramming of cells within the tumor or its microenvironment. Therefore, understanding drug resistance at the molecular and biological levels may enable the selection of specific drug combinations to counteract these adaptive responses. This symposium will explore some of the recent advances addressing the molecular basis of cancer cell drug resistance. We will address how tumor cell signaling pathways become rewired to facilitate tumor cell survival in the face of some of our most promising cancer drugs. Another topic to be discussed involves how drugs select for or induce the reprogramming of tumor cells toward a stem-like, drug resistant fate. By targeting the molecular driver(s) of rewired signaling pathways and/or cancer stemness it may be possible to select drug combinations that prevent the reprogramming of tumors and thereby delay or eliminate the onset of drug resistance.
Tuesday, Apr 21, 2015, 10:30 AM -12:30 PM
David A. Cheresh. UCSD Moores Cancer Center, La Jolla, CA
Tuesday, Apr 21, 2015, 10:30 AM -10:40 AM
Resistance to tyrosine kinase inhibitors: Heterogeneity and therapeutic strategies.
Tuesday, Apr 21, 2015, 10:40 AM -10:55 AM
Jeffrey A. Engelman. Massachusetts General Hospital, Boston, MA
Tuesday, Apr 21, 2015, 10:55 AM -11:00 AM
NG04: Clinical acquired resistance to RAF inhibitor combinations in BRAF mutant colorectal cancer through MAPK pathway alterations
Tuesday, Apr 21, 2015, 11:00 AM -11:15 AM
Ryan B. Corcoran, Leanne G. Ahronian, Eliezer Van Allen, Erin M. Coffee, Nikhil Wagle, Eunice L. Kwak, Jason E. Faris, A. John Iafrate, Levi A. Garraway, Jeffrey A. Engelman. Massachusetts General Hospital Cancer Center, Boston, MA, Dana-Farber Cancer Institute, Boston, MA
Tuesday, Apr 21, 2015, 11:15 AM -11:20 AM
SY27-02: Tumour heterogeneity and therapy resistance in melanoma
Tuesday, Apr 21, 2015, 11:20 AM -11:35 AM
Claudia Wellbrock. Univ. of Manchester, Manchester, United Kingdom

Presentation Number: SY27-02
Presentation Title: Tumour heterogeneity and therapy resistance in melanoma
Presentation Time: Tuesday, Apr 21, 2015, 11:20 AM -11:35 AM
Location: Terrace Ballroom II-III (400 Level), Pennsylvania Convention Center
Author Block: Claudia Wellbrock. Univ. of Manchester, Manchester, United Kingdom
Abstract Body: Solid tumors are structurally very complex; they consist of heterogeneous cancer cell populations, other non-cancerous cell types and a distinct extracellular matrix. Interactions of cancer cells with non-cancerous cells is well investigated, and our recent work in melanoma has demonstrated that the cellular environment that surrounds cancer cells has a major impact on the way a patient responds to MAP-kinase pathway targeting therapy.
We have shown that intra-tumor signaling within a heterogeneous tumor can have a major impact on the efficacy of BRAF and MEK inhibitors. With the increasing evidence of genetic and phenotypic heterogeneity within tumors, intra-tumor signaling between individual cancer-cell subpopulations is therefore a crucial factor that needs to be considered in future therapy approaches. Our work has identified the ‘melanocyte-lineage survival oncogene’ MITF as an important player in phenotypic heterogeneity (MITFhigh and MITFlow cells) in melanoma, and MITF expression levels are crucial for the response to MAP-kinase pathway targeted therapy. We found that ‘MITF heterogeneity’ can be caused by cell-autonomous mechanisms or by the microenvironment, including the immune-microenvironment.
We have identified various mechanisms underlying MITF action in resistance to BRAF and MEK inhibitors in melanoma. In MITFhigh expressing cells, MITF confers cell-autonomous resistance to MAP-kinase pathway targeted therapy. Moreover, it appears that in melanomas heterogeneous for MITF expression (MITFhigh and MITFlow cells), individual subpopulations of resistant and sensitive cells communicate and MITF can contribute to overall tumor-resistance through intra-tumor signaling. Finally, we have identified a novel approach of interfering with MITF action, which profoundly sensitizes melanoma to MAP-kinase pathway targeted therapy.
Tuesday, Apr 21, 2015, 11:35 AM -11:40 AM
SY27-03: Breast cancer stem cell state transitions mediate therapeutic resistance
Tuesday, Apr 21, 2015, 11:40 AM -11:55 AM
Max S. Wicha. University of Michigan, Comprehensive Cancer Center, Ann Arbor, MI
Tuesday, Apr 21, 2015, 11:55 AM -12:00 PM
SY27-04: Induction of cancer stemness and drug resistance by EGFR blockade
Tuesday, Apr 21, 2015, 12:00 PM -12:15 PM
David A. Cheresh. UCSD Moores Cancer Center, La Jolla, CA


Cellular Reprogramming in Carcinogenesis: Implications for Tumor Heterogeneity, Prognosis, and Therapy
Session Type: Major Symposium
Session Start/End Time: Tuesday, Apr 21, 2015, 10:30 AM -12:30 PM
Location: Room 103, Pennsylvania Convention Center
CME: CME-Designated
CME/CE Hours: 2
Session Description: Cancers, both solid and liquid, consist of phenotypically heterogeneous cell types that make up the full cellular complement of disease. Deep sequencing of bulk cancers also frequently reveals a genetic intratumoral heterogeneity that reflects clonal evolution in space and in time and under the influence of treatment. How the distinct phenotypic and genotypic cells contribute to individual cancer growth and progression is incompletely understood. In this symposium, we will discuss issues of cancer heterogeneity and effects on growth and treatment resistance, with emphasis on cancer cell functional properties and influences of the microenvironment, interclonal genomic heterogeneity, and lineage relationships between cancer cells with stem cell and differentiated properties. Understanding these complex cellular relationships within cancers will have critical implications for devising more effective treatments.
Tuesday, Apr 21, 2015, 10:30 AM -12:30 PM
Peter B. Dirks. Univ. of Toronto Hospital for Sick Children, Toronto, ON, Canada

Tuesday, Apr 21, 2015, 10:30 AM -10:40 AM

Origins, evolution and selection in childhood leukaemia
Tuesday, Apr 21, 2015, 10:40 AM -11:00 AM
Tariq Enver. Cancer Research UK, London, United Kingdom

Tuesday, Apr 21, 2015, 11:00 AM -11:05 AM

Cytokine-controlled stem cell plasticity inintestinal tumorigenesis
Tuesday, Apr 21, 2015, 11:05 AM -11:25 AM
Florian Greten. Georg-Speyer-Haus, Frankfurt, Germany

Tuesday, Apr 21, 2015, 11:25 AM -11:30 AM

SY23-03: Intratumoural heterogeneity in human serous ovarian carcinoma
Tuesday, Apr 21, 2015, 11:30 AM -11:50 AM
John P. Stingl. Cancer Research UK Cambridge Research Inst., Cambridge, United Kingdom

Tuesday, Apr 21, 2015, 11:50 AM -11:55 AM

Functional and genomic heterogeneity in brain tumors
Tuesday, Apr 21, 2015, 11:55 AM -12:15 PM


Proc Natl Acad Sci U S A. 2015 Jan 20;112(3):851-6. doi: 10.1073/pnas.1320611111. Epub 2015 Jan 5.

Single cell-derived clonal analysis of human glioblastoma links functional and genomic heterogeneity.

Meyer M1, Reimand J2, Lan X3, Head R1, Zhu X1, Kushida M1, Bayani J4, Pressey JC5, Lionel AC6, Clarke ID7, Cusimano M8, Squire JA9, Scherer SW6, Bernstein M10, Woodin MA5, Bader GD11, Dirks PB12.

Author information


Glioblastoma (GBM) is a cancer comprised of morphologically, genetically, and phenotypically diverse cells. However, an understanding of the functional significance of intratumoral heterogeneity is lacking. We devised a method to isolate and functionally profile tumorigenic clones from patient glioblastoma samples. Individual clones demonstrated unique proliferation and differentiation abilities. Importantly, naïve patient tumors included clones that were temozolomide resistant, indicating that resistance to conventional GBM therapy can preexist in untreated tumors at a clonal level. Further, candidate therapies for resistant clones were detected with clone-specific drug screening. Genomic analyses revealed genes and pathways that associate with specific functional behavior of single clones. Our results suggest that functional clonal profiling used to identify tumorigenic and drug-resistant tumor clones will lead to the discovery of new GBM clone-specific treatment strategies.



739: Tumor cell plasticity with transition to a mesenchymal phenotype is a mechanism of chemoresistance that is reversed by Notch pathway inhibition in lung adenocarcinoma
Sunday, Apr 19, 2015, 1:00 PM – 5:00 PM
Khaled A. Hassan. University Of Michigan, Ann Arbor, MI

745: Oncostatin M receptor activation leads to molecular targeted therapy resistance in non-small cell lung cancer
Sunday, Apr 19, 2015, 1:00 PM – 5:00 PM
Kazuhiko Shien1, Vassiliki A. Papadimitrakopoulou1, Dennis Ruder1, Nana E. Hanson1, Neda Kalhor1, J. Jack Lee1, Waun Ki Hong1, Ximing Tang1, Roy S. Herbst2, Luc Girard3, John D. Minna3, Jonathan M. Kurie1, Ignacio I. Wistuba1, Julie G. Izzo1. 1University of Texas MD Anderson Cancer Center, Houston, TX; 2Yale Cancer Center, Yale School of Medicine, New Haven, CT; 3Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TX

746: Activation of EGFR bypass signaling through TGFα overexpression induces acquired resistance to alectinib in ALK-translocated lung cancer cells
Sunday, Apr 19, 2015, 1:00 PM – 5:00 PM
Tetsuo Tani, Hiroyuki Yasuda, Junko Hamamoto, Aoi Kuroda, Daisuke Arai, Kota Ishioka, Keiko Ohgino, Ichiro Kawada, Katsuhiko Naoki, Hayashi Yuichiro, Tomoko Betsuyaku, Kenzo Soejima. Keio University, Tokyo, Japan

752: Elucidating the mechanisms of acquired resistance in lung adenocarcinomas
Sunday, Apr 19, 2015, 1:00 PM – 5:00 PM
Sandra Ortiz-Cuarán1, Lynnette Fernandez-Cuesta1, Christine M. Lovly2, Marc Bos1, Matthias Scheffler3, Sebastian Michels3, Kerstin Albus4, Lydia Meyer4, Katharina König4, Ilona Dahmen1, Christian Mueller1, Luca Ozretić4, Lars Tharun4, Philipp Schaub1, Alexandra Florin4, Berit Pinther1, Nike Bahlmann1, Sascha Ansén3, Martin Peifer1, Lukas C. Heukamp4, Reinhard Buettner4, Martin L. Sos1, Jürgen Wolf3, William Pao2, Roman K. Thomas1. 1University of Cologne, Cologne, Germany; 2Department of Medicine, Vanderbilt University, Nashville, TN; 3Department of Internal Medicine, Center for Integrated Oncology Köln-Bonn, University Hospital Cologne, Cologne, Germany; 4Institute of Pathology, University Hospital Cologne, Cologne, Germany

760: On the evolution of erlotinib-resistant NSCLC subpopulations
Sunday, Apr 19, 2015, 1:00 PM – 5:00 PM
Michael E. Ramirez1, Robert J. Steininger, III1, Lani F. Wu2, Steven J. Altschuler2. 1UT Southwestern, Dallas, TX; 2UCSF, San Francisco, CA
763: Implications of resistance patterns with NSCLC targeted agents
Sunday, Apr 19, 2015, 1:00 PM – 5:00 PM
David J. Stewart, Paul Wheatley-Price, Rob MacRae, Jason Pantarotto. University of Ottawa, Ottawa, ON, Canada


768: A kinome-wide siRNA screen identifies modifiers of sensitivity to the EGFR T790M-targeted tyrosine kinase inhibitor (TKI), AZD9291, in EGFR mutant lung adenocarcinoma
Sunday, Apr 19, 2015, 1:00 PM – 5:00 PM
Eiki Ichihara1, Joshua A. Bauer2, Pengcheng Lu3, Fei Ye3, Darren Cross4, William Pao1, Christine M. Lovly1. 1Vanderbilt University School of Medicine, Nashville, TN; 2Vanderbilt Institute of Chemical Biology High-Throughput Screening Facility, Nashville, TN; 3Vanderbilt University Medical Center, Nashville, TN; 4AstraZeneca Oncology Innovative Medicines, United Kingdom

LB-055: Clinical acquired resistance to RAF inhibitor combinations in BRAF-mutant colorectal cancer through MAPK pathway alterations
Sunday, Apr 19, 2015, 4:35 PM – 4:50 PM
Leanne G. Ahronian1, Erin M. Sennott1, Eliezer M. Van Allen2, Nikhil Wagle2, Eunice L. Kwak1, Jason E. Faris1, Jason T. Godfrey1, Koki Nishimura1, Kerry D. Lynch3, Craig H. Mermel1, Elizabeth L. Lockerman1, Anuj Kalsy1, Joseph M. Gurski, Jr.1, Samira Bahl4, Kristin Anderka4, Lisa M. Green4, Niall J. Lennon4, Tiffany G. Huynh3, Mari Mino-Kenudson3, Gad Getz1, Dora Dias-Santagata3, A. John Iafrate3, Jeffrey A. Engelman1, Levi A. Garraway2, Ryan B. Corcoran1. 1Massachusetts General Hospital Cancer Center, Boston, MA; 2Dana Farber Cancer Institute, Boston, MA; 3Massachusetts General Hospital Department of Pathology, Boston, MA; 4Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA


Other Articles on this Site Related to Tumor Heterogeneity Include

Notes On Tumor Heterogeneity: Targets and Mechanisms, from the 2015 AACR Meeting in Philadelphia PA

Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn

Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

CANCER COMPLEXITY: Heterogeneity in Tumor Progression and Drug Response – 2015 Annual Symposium @Koch Institute for Integrative Cancer Research at MIT – W34, 6/12/2015 9:00 AM EDT – 4:30 PM EDT

In vitro Models of Tumor Microenvironment for New Cancer Target and Drug Discovery, 11/17 – 11/19/2014, Hyatt Boston Harbor

What can we expect of tumor therapeutic response?


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Genomics and Metabolomics Advances in Cancer

Writer and Curator: Larry H. Bernstein, MD, FCAP

UPDATED 6/01/2019 

UPDATED 9/26/2021


Unraveling the clonal hierarchy of somatic genomic aberrations

D Prandi, SC Baca, A Romanel, CE Barbieri, Juan-Miguel Mosquera, et al.
Genome Biology 2014, 15:439

Defining the chronology of molecular alterations may identify milestones in carcinogenesis. To unravel the temporal evolution of aberrations from clinical tumors, we developed CLONET, which upon estimation of tumor admixture and ploidy infers the clonal hierarchy of genomic aberrations. Comparative analysis across 100 sequenced genomes from prostate, melanoma, and lung cancers established diverse evolutionary hierarchies, demonstrating the early disruption of tumor-specific pathways. The analyses highlight the diversity of clonal evolution within and across tumor types that might be informative for risk stratification and patient selection for targeted therapies. CLONET addresses heterogeneous clinical samples seen in the setting of precision medicine.

The Transcription Factor Titration Effect Dictates Level of Gene Expression

RC Brewster, FM Weinert, HG Garcia, D Song, M Rydenfelt, and R Phillips
Cell,  Mar 13, 2014;156: 1312–1323

Models of transcription are often built around a picture of RNA polymerase and transcription factors (TFs) acting on a single copy of a promoter. However, most TFs are shared between multiple genes with varying binding affinities. Beyond that, genes often exist at high copy number—in multiple identical copies on the chromosome or on plasmids or viral vectors with copy numbers in the hundreds. Using a thermodynamic model, we characterize the interplay between TF copy number and the demand for that TF. We demonstrate the parameter-free predictive power of this model as a function of the copy number of the TF and the number and affinities of the available specific binding sites; such predictive control is important for the understanding of transcription and the desire to quantitatively design the output of genetic circuits. Finally, we use these experiments to dynamically measure plasmid copy number through the cell cycle.

Telomere dynamics in human mesenchymal stem cells after exposure to acute oxidative stress

M Harbo, S Koelvraa, N Serakinci, L Bendixa
DNA Repair 2012.  http://dx.doi.org/10.1016/j.dnarep.2012.06.003

A gradual shortening of telomeres due to replication can be measured using the standard telomere restriction fragments (TRF) assay and other methods by measuring the mean length of all the telomeres in a cell. In contrast, stress-induced telomere shortening, which is believed to be just as important for causing cellular senescence, cannot be measured properly using these methods. Stress-induced telomere shortening caused by, e.g. oxidative damage happens in a stochastic manner leaving just a few single telomeres critically short. It is now possible to visualize these few ultra-short telomeres due to the advantages of the newly developed Universal single telomere length assay (STELA), and we therefore believe that this method should be considered the method of choice when measuring the length of telomeres after exposure to oxidative stress. In order to test our hypothesis, cultured human mesenchymal stem cells, either primary or hTERT immortalized, were exposed to sub-lethal doses of hydrogen peroxide, and the short term effect on telomere dynamics was monitored by Universal STELA and TRF measurements. Both telomere measures were then correlated with the percentage of senescent cells estimated by senescence-associated β-galactosidase staining. The exposure to acute oxidative stress resulted in an increased number of ultra-short telomeres, which correlated strongly with the percentage of senescent cells, whereas a correlation between mean telomere length and the percentage of senescent cells was absent. Based on the findings in the present study, it seems reasonable to conclude that Universal STELA is superior to TRF in detecting telomere damage caused by exposure to oxidative stress. The choice of method should therefore be considered carefully in studies examining stress-related telomere shortening as well as in the emerging field of lifestyle studies involving telomere length measurements.

tDNA insulators and the emerging role of TFIIIC in genome organization

Kevin Van Bortle and Victor G. Corces
Transcription Dec 12, 2012; 3(6): 1-8. www.landesbioscience.com

Recent findings provide evidence that tDNAs function as chromatin insulators from yeast to humans. TFIIIC, a transcription factor that interacts with the B-box in tDNAs as well as thousands of ETC sites in the genome, is responsible for insulator function. Though tDNAs are capable of enhancer-blocking and barrier activities for which insulators are defined, new insights into the relationship between insulators and chromatin structure suggest that TFIIIC serves a complex role in genome organization. We review the role of tRNA genes and TFIIIC as chromatin insulators, and highlight recent findings that have broadened our understanding of insulators in genome biology.

Structure and organization of insulators in eukaryotes. (A) From yeast to mammals, in organisms in which it has been studied, the TFIIIC protein interacts with the B-box sequence in tRNA genes or sites in the genome named ETC sites.

Synthetic CpG islands reveal DNA sequence determinants of chromatin structure

E Wachter, T Quante, C Merusi, A Arczewska, F Stewart, S Webb, A Bird
eLife 2014;3:e03397. http://dx.doi.org:/10.7554/eLife.03397.001

The mammalian genome is punctuated by CpG islands (CGIs), which differ sharply from the bulk genome by being rich in G + C and the dinucleotide CpG. CGIs often include transcription initiation sites and display ‘active’ histone marks, notably histone H3 lysine 4 methylation. In embryonic stem cells (ESCs) some CGIs adopt a ‘bivalent’ chromatin state bearing simultaneous ‘active’ and ‘inactive’ chromatin marks. To determine whether CGI chromatin is developmentally programmed at specific genes or is imposed by shared features of CGI DNA, we integrated artificial CGI-like DNA sequences into the ESC genome. We found that bivalency is the default chromatin structure for CpG-rich, G + C-rich DNA. A high CpG density alone is not sufficient for this effect, as A + T-rich sequence settings invariably provoke de novo DNA methylation leading to loss of CGI signature chromatin. We conclude that both CpG-richness and G + C-richness are required for induction of signature chromatin structures at CGIs.

Locus-specific mutation databases: pitfalls and good practice based on the p53 experience

Thierry Soussi, Chikashi Ishioka, Mireille Claustres and Christophe Béroud

Between 50,000 and 60,000 mutations have been described in various genes that are associated with a wide variety of diseases. Reporting, storing and analysing these data is an important challenge as such data provide invaluable information for both clinical medicine and basic science.

The practical value of mutation analysis All studies performed to date show that mutations are, in general, not randomly distributed. Hot-spot regions have been demonstrated, corresponding to a region of DNA that is susceptible to mutations (such as CpG dinucleotides), a codon encoding a key residue in the biological function of the protein, or both (BOX 1). Identification of these hot-spot regions and natural mutants is essential to define crucial regions in an unknown protein.

Locus-specific databases have been developed to exploit this huge volume of data. The p53 mutation database is a paradigm, as it constitutes the largest collection of somatic mutations (22,000). However, there are several biases in this database that can lead to serious erroneous interpretations. We describe several rules for mutation database management that could benefit the entire scientific community.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

A Subramaniana, P Tamayo, VK  Mootha, S Mukherjee, BL Ebert, et al.
PNAS  Oct 25, 2005; 102(43): 15545–15550

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

Mutational landscape and significance across 12 major cancer types

C Kandoth, MD McLellan, F Vandin, Kai Ye, B Niu, C Lu, et al.
NATURE  OCT 2013; 502: 333-337. http://dx.doi.org:/10.1038/nature12634

The Cancer Genome Atlas (TCGA) has used the latest sequencing and analysis methods to identify somatic variants across thousands of tumours. Here we present data and analytical results for point mutations and small insertions/deletions from 3,281 tumours across 12 tumour types as part of the TCGA Pan-Cancer effort. We illustrate the distributions of mutation frequencies, types and contexts across tumour types, and establish their links to tissues of origin, environmental/ carcinogen influences, and DNA repair defects. Using the integrated data sets, we identified 127 significantly mutated genes from well-known(for example, mitogen-activated protein kinase, phosphatidylinositol-3-OH kinase,Wnt/b-catenin and receptor tyrosine kinase signalling pathways, and cell cycle control) and emerging (for example, histone, histone modification, splicing, metabolism and proteolysis) cellular processes in cancer. The average number of mutations in these significantly mutated genes varies across tumour types; most tumours have two to six, indicating that the numberof driver mutations required during oncogenesis is relatively small. Mutations in transcriptional factors/regulators show tissue specificity, whereas histone modifiers are often mutated across several cancer types. Clinical association analysis identifies genes having a significant effect on survival, and investigations of mutations with respect to clonal/subclonal architecture delineate their temporal orders during tumorigenesis. Taken together, these results lay the groundwork for developing new diagnostics and individualizing cancer treatment.

Molecular insights into RNA and DNA helicase evolution from the determinants of  specificity for a DEAD-box RNA helicase

Anna L. Mallam, David J. Sidote and Alan M. Lambowitz
eLife 2014; http://dx.doi.org:/10.7554/eLife.04630

How different helicase families with a conserved catalytic ‘helicase core’ evolved to function on varied RNA and DNA substrates by diverse mechanisms remains unclear. Here, we used Mss116, a yeast DEAD-box protein that utilizes ATP to locally unwind dsRNA, to investigate helicase specificity and mechanism. Our results define the molecular basis for the substrate specificity of a DEAD-box protein. Additionally, they show that Mss116 has ambiguous substrate-binding properties and interacts with all four NTPs and both RNA and DNA. The efficiency of unwinding correlates with the stability of the ‘closed-state’ helicase core, a complex with nucleotide and nucleic acid that forms as duplexes are unwound. Crystal structures reveal that core stability is modulated by family-specific interactions that favor certain substrates. This suggests how present-day  helicases diversified from an ancestral core with broad specificity by retaining core closure as a common catalytic mechanism while optimizing substrate-binding interactions for different cellular functions.

Identification of human TERT elements necessary for telomerase recruitment to telomeres

Jens C Schmidt, Andrew B Dalby, Thomas R Cech
eLife 2014; http://dx.doi.org/10.7554/eLife.03563

Human chromosomes terminate in telomeres, repetitive DNA sequences bound by the shelterin complex. Shelterin protects chromosome ends, prevents recognition by the DNA damage machinery, and recruits telomerase. A patch of  amino acids, termed the TEL-patch, on the OB-fold domain of the shelterin  component TPP1 is essential to recruit telomerase to telomeres. In contrast, the site on telomerase that interacts with the TPP1 OB-fold is not well defined. Here we identify separation-of-function mutations in the TEN-domain of human telomerase reverse transcriptase (hTERT) that disrupt the interaction of telomerase with TPP1 in vivo and in vitro but have very little effect on the catalytic activity of telomerase. Suppression of a TEN-domain mutation with a compensatory charge-swap mutation in the TEL-patch indicates that their association is direct. Our findings define the interaction interface required for telomerase recruitment to telomeres, an important step towards developing modulators of this interaction as therapeutics for human disease.


Single Cell Profiling of Circulating Tumor Cells: Transcriptional Heterogeneity and Diversity from Breast Cancer Cell Lines

MN Mindrinos, G Bhanot, SH Dairkee, RW Davis, SS Jeffrey
PLoS ONE 7(5): e33788. http://dx.doi.org:/doi:10.1371/journal.pone.0033788

Background: To improve cancer therapy, it is critical to target metastasizing cells. Circulating tumor cells (CTCs) are rare cells found in the blood of patients with solid tumors and may play a key role in cancer dissemination. Uncovering CTC phenotypes offers a potential avenue to inform treatment. However, CTC transcriptional profiling is limited by leukocyte contamination; an approach to surmount this problem is single cell analysis. Here we demonstrate feasibility of performing high dimensional single CTC profiling, providing early insight into CTC heterogeneity and allowing comparisons to breast cancer cell lines widely used for drug discovery.
Methodology/Principal Findings: We purified CTCs using the MagSweeper, an immunomagnetic enrichment device that isolates live tumor cells from unfractionated blood. CTCs that met stringent criteria for further analysis were obtained from 70% (14/20) of primary and 70% (21/30) of metastatic breast cancer patients; none were captured from patients with nonepithelial cancer (n = 20) or healthy subjects (n = 25). Microfluidic-based single cell transcriptional profiling of 87 cancer associated and reference genes showed heterogeneity among individual CTCs, separating them into two major subgroups, based on 31 highly expressed genes. In contrast, single cells from seven breast cancer cell lines were tightly clustered together by sample ID and ER status. CTC profiles were distinct from those of cancer cell lines, questioning the suitability of such lines for drug discovery efforts for late stage cancer therapy.
Conclusions/Significance: For the first time, we directly measured high dimensional gene expression in individual CTCs without the common practice of pooling such cells. Elevated transcript levels of genes associated with metastasis NPTN, S100A4, S100A9, and with epithelial mesenchymal transition: VIM, TGFß1, ZEB2, FOXC1, CXCR4, were striking compared to cell lines. Our findings demonstrate that profiling CTCs on a cell-by-cell basis is possible and may facilitate the application of ‘liquid biopsies’ to better model drug discovery

Simplifying Disease Complexity part 6 – Bringing Metabolomics into Practice
Dr. Kirk Beebe, Director of Application Science, Metabolon, Inc.

n the previous editions of this 6-part series, we’ve explored numerous example of how metabolomics is bringing success to areas such as cancer, metabolic disease, cardiovascular, and rare disease research. Although we did not devote attention to every area of biology or therapeutic area, the intent of this broad series was not only to convey how metabolomics can be used in a specific area of research (e.g. cancer), but actually, how metabolomics is a central science for interrogating any biological question. So, although it may seem like an oversimplification, to understand whether metabolomics could be used in a research setting one need only ask themselves, “Do I have a biological question that would benefit from a hypothesis-free approach?, am I interested in exploring my system for potential new discoveries? Or do I need a biomarker/better biomarker?

As described in our first part, metabolites have been and continue to be a staple for clinical and in vivo decision making (e.g. cholesterol, glucose, bilirubin, creatinine, thyroid hormone, newborn screening for inborn errors of metabolism (IEMs)). In short, this utility is fundamental to the foundations of biology since metabolism is central to all kingdoms of life and contemporary biology is driven to maintain metabolic homeostasis to maintain the phenotype. An unappreciated point that we leave this series with is that this fundamental nature (the connection of metabolism to the phenotype) confers an important advantage of metabolism for deriving biomarkers and understanding the underlying physiology.

Metabolites are a diagnostic data stream.

Whether a phenotype is driven by a single mutation or a combination of genetic differences, environmental influences or the microbiota, metabolism provides a systems-level diagnostic.

That is, no matter the source of the physiological or phenotypic change (i.e. genes, microbiota, environmental), the change will almost invariably register within metabolism. Thus, modern metabolomic approaches offer the opportunity to more deeply interrogate the “metabolome” to discover more sensitive and specific biomarkers and understand the basis of disease and drug response.

As such, metabolomics has the potential to be able to integrate systems on a number of levels. It is useful through its ability to enrich genomics, transcriptomics and proteomics, thus integrating a number of data streams that provide knowledge and contribute to informed decision-making and patient management1. Using metabolomics, individual tissues can be queried but less invasive sample types (e.g., blood, urine, feces, and/or saliva) can also yield biomarkers and mechanistic insight. The integration of the individual tissues at the level of these more accessible samples can offer an overview of the entire system and inform on important biological pathways. Finally, although the focus of this series was on what metabolomics can bring to biomarker and other related research areas, it should be noted that a combination of metabolomics with other scientific approaches will undoubtedly broaden insight and produce verifiable, validatable biomarkers that track with efficacy and therapy.

As we close this series, we hope that we have conveyed 4 critical points – 1) metabolism is central to biology and hence, key in research and biomarker discovery, 2) the reason for this is due to the fundamental nature of metabolism being central to the development of all life and being the focal point of contemporary biology’s drive to maintain homeostasis, 3) metabolomic is the most powerful way to survey metabolism by offering a simultaneous read-out if hundreds of reactions and pathways, and 4) metabolomics as a practical tool has only recently emerged.

And it is on this last point that we leave the reader with some final considerations. We imagine that, after careful review of the information outlined in this series, many readers will be motivated to explore the use of metabolomics in their research. However, as outlined throughout this series, mature technologies have only recently arisen. Nevertheless, there are many laboratories that perform some version of “metabolomics”. Although the experimental goal often dictates the precise approach, there are 5 critical features  that a metabolomic technology must harbor in order for it to achieve a similar purpose as mature omic technologies (e.g. DNA sequencers) in terms of depth of coverage and data quality. These minimally include:

  1. Must be based on an authenticated chemical library
    2. Must have procedures for eliminated noise from the data
    5. Must have a mechanism to identify novel metabolites
    6. Must have robust QC process from sample preparation through statistical analysis
    4. Must provide a mechanism to abstract information/interpret the data


  1. Eckhart, A.D., Beebe, K. & Milburn, M. Metabolomics as a key integrator for “omic” advancement of personalized medicine and future therapies. Clin Transl Sci 5, 285-288


  1. Evans, A., Mitchell, M., Dai, H. & DeHaven, C.D. Categorizing Ion –Features in Liquid Chromatography/Mass Spectrometry Metobolomics Data. Metabolomics 2 (2012).
  2. DeHaven, C.D., Evans, A., Dai, H. & Lawton, K.A. in Metabolomics. (ed. U. Roessner) (InTech, 2012).
  3. Dehaven, C.D., Evans, A.M., Dai, H. & Lawton, K.A. Organization of GC/MS and LC/MS metabolomics data into chemical libraries. J Cheminform 2, 9 (2010).
  4. Evans, A.M., DeHaven, C.D., Barrett, T., Mitchell, M. & Milgram, E. Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Anal Chem 81, 6656-6667 (2009).

Prediction of intracellular metabolic states from extracellular metabolomic data

MK Aurich, G Paglia, Ottar Rolfsson, S Hrafnsdottir, M  Magnusdottir, MM, et al.

Metabolomics Aug 14, 2014;  http://dx.doi.org:/10.1007/s11306-014-0721-3

intra- extracellular metabolites

intra- extracellular metabolites


Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used to investigate metabolic alternations in human diseases. An expression of the altered metabolic pathway utilization is the selection of metabolites consumed and released by cells. However, methods for the inference of intracellular metabolic states from extracellular measurements in the context of metabolic models remain underdeveloped compared to methods for other omics data. Herein, we describe a workflow for such an integrative analysis emphasizing on extracellular metabolomics data. We demonstrate, using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM, how our methods can reveal differences in cell metabolism. Our models explain metabolite uptake and secretion by predicting a more glycolytic phenotype for the CCRF-CEM model and a more oxidative phenotype for the Molt-4 model, which was supported by our experimental data. Gene expression analysis revealed altered expression of gene products at key regulatory steps in those central metabolic pathways, and literature query emphasized the role of these genes in cancer metabolism. Moreover, in silico gene knock-outs identified unique control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model. Thus, our workflow is well suited to the characterization of cellular metabolic traits based on extracellular metabolomic data, and it allows the integration of multiple omics data sets into a cohesive picture based on a defined model context.

Metabolome Informatics Research

Metabolome Informatics Research

Identification of Metabolites in the Normal Ovary and Their Transformation in Primary and Metastatic Ovarian Cancer MOC vs EOC

Identification of Metabolites in the Normal Ovary and Their Transformation in Primary and Metastatic Ovarian Cancer MOC vs EOC

Genomics and Cancer

Identification of Gene Networks Associated with Acute Myeloid Leukemia by Comparative Molecular Methylation and Expression Profiling

M Dellett, KA O’Hagan, HA Alexandra Colyer and KI Mills
Biomarkers in Cancer 2010:2 43–55  http://www.la-press.com.

Around 80% of acute myeloid leukemia (AML) patients achieve a complete remission, however many will relapse and ultimately die of their disease. The association between karyotype and prognosis has been studied extensively and identified patient cohorts as having favourable [e.g. t(8; 21), inv (16)/t(16; 16), t(15; 17)], intermediate [e.g. cytogenetically normal (NK-AML)] or adverse risk [e.g. complex karyotypes]. Previous studies have shown that gene expression profiling signatures can classify the sub-types of AML, although few reports have shown a similar feature by using methylation markers. The global methylation patterns in 19 diagnostic AML samples were investigated using the Methylated CpG Island Amplification Microarray (MCAM) method and CpG island microarrays containing 12,000 CpG sites. The first analysis, comparing favourable and intermediate cytogenetic risk groups, revealed significantly differentially methylated CpG sites (594 CpG islands) between the two subgroups. Mutations in the NPM1 gene occur at a high frequency (40%) within the NK-AML subgroup and are associated with a more favourable prognosis in these patients. A second analysis comparing the NPM1 mutant and wild-type research study subjects again identified distinct methylation profiles between these two subgroups. Network and pathway analysis revealed possible molecular mechanisms associated with the different risk and/or mutation sub-groups. This may result in a better classification of the risk groups, improved monitoring targets, or the identification of novel molecular therapies.

Molecular Imaging of Proteases in Cancer

Yunan Yang, Hao Hong, Yin Zhang and Weibo Cai
Cancer Growth and Metastasis 2009:2 13–27. http://www.la-press.com

Proteases play important roles during tumor angiogenesis, invasion, and metastasis. Various molecular imaging techniques have been employed for protease imaging: optical (both fluorescence and bioluminescence), magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). In this review, we will summarize the current status of imaging proteases in cancer with these techniques. Optical imaging of proteases, in particular with fluorescence, is the most intensively validated and many of the imaging probes are already commercially available. It is generally agreed that the use of activatable probes is the most accurate and appropriate means for measuring protease activity. Molecular imaging of proteases with other techniques (i.e. MRI, SPECT, and PET) has not been well-documented in the literature which certainly deserves much future effort. Optical imaging and molecular MRI of protease activity has very limited potential for clinical investigation. PET/SPECT imaging is suitable for clinical investigation; however the optimal probes for PET/SPECT imaging of proteases in cancer have yet to be developed. Successful development of protease imaging probes with optimal in vivo stability, tumor targeting efficacy, and desirable pharmacokinetics for clinical translation will eventually improve cancer patient management. Not limited to cancer, these protease-targeted imaging probes will also have broad applications in other diseases such as arthritis, atherosclerosis, and myocardial infarction.

Evolutionarily conserved genetic interactions with budding and fission yeast MutS identify orthologous relationships in mismatch repair-deficient cancer cells

E Tosti, JA Katakowski, S Schaetzlein, Hyun-Soo Kim, CJ Ryan, M Shales, et al.
Genome Medicine 2014, 6:68. http://genomemedicine.com/content/6/9/68

Background: The evolutionarily conserved DNA mismatch repair (MMR) system corrects base-substitution and insertion-deletion mutations generated during erroneous replication. The mutation or inactivation of many MMR factors strongly predisposes to cancer, where the resulting tumors often display resistance to standard chemotherapeutics. A new direction to develop targeted therapies is the harnessing of synthetic genetic interactions, where the simultaneous loss of two otherwise non-essential factors leads to reduced cell fitness or death. High-throughput screening in human cells to directly identify such interactors for disease-relevant genes is now widespread, but often requires extensive case-by-case optimization. Here we asked if conserved genetic interactors (CGIs) with MMR genes from two evolutionary distant yeast species (Saccharomyces cerevisiae and Schizosaccharomyzes pombe) can predict orthologous genetic relationships in higher eukaryotes.
Methods: High-throughput screening was used to identify genetic interaction profiles for the MutSα and MutSβ heterodimer subunits (msh2Δ, msh3Δ, msh6Δ) of fission yeast. Selected negative interactors with MutSβ (msh2Δ/msh3Δ) were directly analyzed in budding yeast, and the CGI with SUMO-protease Ulp2 further examined after RNA interference/drug treatment in MSH2-deficient and -proficient human cells.
Results: This study identified distinct genetic profiles for MutSα and MutSβ, and supports a role for the latter in recombinatorial DNA repair. Approximately 28% of orthologous genetic interactions with msh2Δ/msh3Δ are conserved in both yeasts, a degree consistent with global trends across these species. Further, the CGI between budding/fission yeast msh2 and SUMO-protease Ulp2 is maintained in human cells (MSH2/SENP6), and enhanced by Olaparib, a PARP inhibitor that induces the accumulation of single-strand DNA breaks. This identifies SENP6 as a promising new target for the treatment of MMR-deficient cancers.
Conclusion: Our findings demonstrate the utility of employing evolutionary distance in tractable lower eukaryotes to predict orthologous genetic relationships in higher eukaryotes. Moreover, we provide novel insights into the genome maintenance functions of a critical DNA repair complex and propose a promising targeted treatment for MMR deficient tumors.

Cancer Genome Landscapes

B Vogelstein, N Papadopoulos, VE Velculescu, S Zhou, LA Diaz Jr., KW Kinzler, et al.
Science 339, 1546 (2013); http://dx.doi.org:/10.1126/science.1235122

Over the past decade, comprehensive sequencing efforts have revealed the genomic landscapes of common forms of human cancer. For most cancer types, this landscape consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of “hills” (genes altered infrequently). To date, these studies have revealed ~140 genes that, when altered by intragenic mutations, can promote or “drive” tumorigenesis. A typical tumor contains two to eight of these “driver gene” mutations; the remaining mutations are passengers that confer no selective growth advantage. Driver genes can be classified into 12 signaling pathways that regulate three core cellular processes: cell fate, cell survival, and genome maintenance. A better understanding of these pathways is one of the most pressing needs in basic cancer research. Even now, however, our knowledge of cancer genomes is sufficient to guide the development of more effective approaches for reducing cancer morbidity and mortality.

Approaches for establishing the function of regulatory genetic variants involved in disease

Julian Charles Knight
Genome Medicine 2014, 6:92.  http://genomemedicine.com/content/6/10/92

The diversity of regulatory genetic variants and their mechanisms of action reflect the complexity and context-specificity of gene regulation. Regulatory variants are important in human disease and defining such variants and establishing mechanism is crucial to the interpretation of disease-association studies. This review describes approaches for identifying and functionally characterizing regulatory variants, illustrated using examples from common diseases. Insights from recent advances in resolving the functional epigenomic regulatory landscape in which variants act are highlighted, showing how this has enabled functional annotation of variants and the generation of hypotheses about mechanism of action. The utility of quantitative trait mapping at the transcript, protein and metabolite level to define association of specific genes with particular variants and further inform disease associations are reviewed. Establishing mechanism of action is an essential step in resolving functional regulatory variants, and this review describes how this is being facilitated by new methods for analyzing allele-specific expression, mapping chromatin interactions and advances in genome editing. Finally, integrative approaches are discussed together with examples highlighting how defining the mechanism of action of regulatory variants and identifying specific modulated genes can maximize the translational utility of genome-wide association studies to understand the pathogenesis of diseases and discover new drug targets or opportunities to repurpose existing drugs to treat them.


TRIM29 as a Novel Biomarker in Pancreatic Adenocarcinoma

Hongli Sun, Xianwei Dai, and Bing Han
Disease Markers 2014, Article ID 317817, 7 pages

Background and Aim. Tripartite motif-containing 29 (TRIM29) is structurally a member of the tripartite motif family of proteins and is involved in diverse human cancers. However, its role in pancreatic cancer remains unclear.
Methods. The expression pattern of TRIM29 in pancreatic ductal adenocarcinoma was assessed by immunocytochemistry. Multivariate logistic regression analysis was used to investigate the association between TRIM29 and clinical characteristics. In vitro analyses by scratch wound healing assay and invasion assays were performed using the pancreatic cancer cell lines.
Results. Immunohistochemical analysis showed TRIM29 expression in pancreatic cancer tissues was significantly higher (𝑛 = 186) than that in matched adjacent nontumor tissues. TRIM29 protein expression was significantly correlated with lymph node metastasis (𝑃 = 0.019). Patients with positive TRIM29 expression showed both shorter overall survival and shorter recurrence-free survival than those with negative TRIM29 expression. Multivariate analysis revealed that TRIM29 was an independent factor for pancreatic cancer over survival (HR = 2.180, 95% CI: 1.324–4.198, 𝑃 = 0.011). In vitro, TRIM29 knockdown resulted in inhibition of pancreatic cancer cell proliferation, migration, and invasion.
Conclusions. Our results indicate that TRIM29 promotes tumor progression and may be a novel prognostic marker for pancreatic ductal adenocarcinoma.

Bioinformatic identification of proteins with tissue-specific expression for biomarker discovery

I Prassas, CC Chrystoja, S Makawita1, and EP Diamandis
BMC Medicine 2012, 10:39. http://www.biomedcentral.com/1741-7015/10/39

Background: There is an important need for the identification of novel serological biomarkers for the early detection of cancer. Current biomarkers suffer from a lack of tissue specificity, rendering them vulnerable to nondisease-specific increases. The present study details a strategy to rapidly identify tissue-specific proteins using bioinformatics.
Methods: Previous studies have focused on either gene or protein expression databases for the identification of candidates. We developed a strategy that mines six publicly available gene and protein databases for tissue-specific proteins, selects proteins likely to enter the circulation, and integrates proteomic datasets enriched for the cancer secretome to prioritize candidates for further verification and validation studies.
Results: Using colon, lung, pancreatic and prostate cancer as case examples, we identified 48 candidate tissuespecific biomarkers, of which 14 have been previously studied as biomarkers of cancer or benign disease. Twenty six candidate biomarkers for these four cancer types are proposed.
Conclusions: We present a novel strategy using bioinformatics to identify tissue-specific proteins that are potential cancer serum biomarkers. Investigation of the 26 candidates in disease states of the organs is warranted

The Serum Glycome to Discriminate between Early-Stage Epithelial Ovarian Cancer and Benign Ovarian Diseases

K Biskup, E Iona Braicu, J Sehouli, R Tauber, and V Blanchard
Disease Markers 2014, Article ID 238197, 10 pages

Epithelial ovarian cancer (EOC) is the sixth most common cause of cancer deaths in women because the diagnosis occurs mostly when the disease is in its late-stage. Current diagnostic methods of EOC show only a moderate sensitivity, especially at an early-stage of the disease; hence, novel biomarkers are needed to improve the diagnosis. We recently reported that serum glycome modifications observed in late-stage EOC patients by MALDI-TOF-MS could be combined as a glycan score named GLYCOV that was calculated from the relative areas of the 11 N-glycan structures that were significantly modulated. Here, we evaluated the ability of GLYCOV to recognize early-stage EOC in a cohort of 73 individuals comprised of 20 early-stage primary serous EOC, 20 benign ovarian diseases (BOD), and 33 age-matched healthy controls. GLYCOV was able to recognize stage I EOC whereas CA125 values were statistically significant only for stage II EOC patients. In addition, GLYCOV was more sensitive and specific compared to CA125 in distinguishing early-stage EOC from BOD patients, which is of high relevance to clinicians as it is difficult for them to diagnose malignancy prior to operation.

The Clinicopathological Significance of miR-133a in Colorectal Cancer

Timothy Ming-Hun Wan, Colin Siu-Chi Lam, Lui Ng, Ariel Ka-Man Chow, et al.
Disease Markers  2014, Article ID 919283, 8 pages http://dx.doi.org/10.1155/2014/919283

This study determined the expression of microRNA-133a (MiR-133a) in colorectal cancer (CRC) and adjacent normal mucosa samples and evaluated its clinicopathological role in CRC. The expression of miR-133a in 125 pairs of tissue samples was analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) and correlated with patient’s clinicopathological data by statistical analysis. Endogenous expression levels of several potential target genes were determined by qRT-PCR and correlated using Pearson’s method. MiR-133a was downregulated in 83.2% of tumors compared to normal mucosal tissue. Higher miR-133a expression in tumor tissues was associated with development of distant metastasis, advanced Dukes and TNM staging, and poor survival. The unfavorable prognosis of higher miR-133a expression was accompanied by dysregulation of potential miR-133a target genes, LIM and SH3 domain protein 1 (LASP1), Caveolin-1 (CAV1), and Fascin-1 (FSCN1). LASP1 was found to possess a negative correlation (𝛾 = −0.23), whereas CAV1 exhibited a significant positive correlation (𝛾 = 0.27), and a stronger correlation was found in patients who developed distant metastases (𝛾 = 0.42). In addition, a negative correlation of FSCN1 was only found in nonmetastatic patients. In conclusion, miR-133a was downregulated in CRC tissues, but its higher expression correlated with adverse clinical characteristics and poor prognosis.

The Clinical Significance of PR, ER, NF-𝜅B, and TNF-𝛼 in Breast Cancer

Xian-Long Zhou, Wei Fan, Gui Yang, and Ming-Xia Yu
Disease Markers 2014, Article ID 494581, 7 pages http://dx.doi.org/10.1155/2014/494581

Objectives. To investigate the expression of estrogen (ER), progesterone receptors (PR), nuclear factor-𝜅B (NF-𝜅B), and tumor necrosis factor-𝛼 (TNF-𝛼) in human breast cancer (BC), and the correlation of these four parameters with clinicopathological features of BC.
Methods and Results. We performed an immunohistochemical SABC method for the identification of ER, PR, NF-𝜅B, and TNF-𝛼 expression in 112 patients with primary BC.The total positive expression rate of ER, PR, NF-𝜅B, and TNF-𝛼 was 67%, 76%, 84%, and 94%, respectively. The expressions of ER and PR were correlated with tumor grade, TNM stage, and lymph node metastasis (𝑃 < 0.01, resp.), but not with age, tumor size, histological subtype, age at menarche, menopause status, number of pregnancies, number of deliveries, and family history of cancer. Expressions of ER and PR were both correlated with NF-𝜅B and TNF-𝛼 expression (𝑃 < 0.05, resp.). Moreover, there was significant correlation between ER and PR (𝑃 < 0.0001) as well as between NF-𝜅B and TNF-𝛼 expression (𝑃 < 0.05).
Conclusion. PR and ER are highly expressed, with significant correlation with NF-𝜅B and TNF-𝛼 expression in breast cancer. The important roles of ER and PR in invasion and metastasis of breast cancer are probably associated with NF-𝜅B and TNF-𝛼 expression.

Serum Protein Profile at Remission Can Accurately Assess Therapeutic Outcomes and Survival for Serous Ovarian Cancer

J Wang, A Sharma, SA Ghamande, S Bush, D Ferris, W Zhi, et la.
PLoS ONE 8(11): e78393. http://dx.doi.org:/10.1371/journal.pone.0078393

Background: Biomarkers play critical roles in early detection, diagnosis and monitoring of therapeutic outcome and recurrence of cancer. Previous biomarker research on ovarian cancer (OC) has mostly focused on the discovery and validation of diagnostic biomarkers. The primary purpose of this study is to identify serum biomarkers for prognosis and therapeutic outcomes of ovarian cancer. Experimental Design: Forty serum proteins were analyzed in 70 serum samples from healthy controls (HC) and 101 serum samples from serous OC patients at three different disease phases: post diagnosis (PD), remission (RM) and recurrence (RC). The utility of serum proteins as OC biomarkers was evaluated using a variety of statistical methods including survival analysis.
Results: Ten serum proteins (PDGF-AB/BB, PDGF-AA, CRP, sFas, CA125, SAA, sTNFRII, sIL-6R, IGFBP6 and MDC) have individually good area-under-the-curve (AUC) values (AUC = 0.69–0.86) and more than 10 three-marker combinations have excellent AUC values (0.91–0.93) in distinguishing active cancer samples (PD & RC) from HC. The mean serum protein levels for RM samples are usually intermediate between HC and OC patients with active cancer (PD & RC). Most importantly, five proteins (sICAM1, RANTES, sgp130, sTNFR-II and sVCAM1) measured at remission  can classify, individually and in combination, serous OC patients into two subsets with significantly different overall survival (best HR = 17, p,1023).
Conclusion: We identified five serum proteins which, when measured at remission, can accurately predict the overall survival of serous OC patients, suggesting that they may be useful for monitoring the therapeutic outcomes for ovarian cancer.

Serum Clusterin as a Tumor Marker and Prognostic Factor for Patients with Esophageal Cancer

Wei Guo, Xiao Ma, Christine Xue, Jianfeng Luo, Xiaoli Zhu, et al.
Disease Markers 2014, Article ID 168960, 7 pages http://dx.doi.org/10.1155/2014/168960

Background. Recent studies have revealed that clusterin is implicated in many physiological and pathological processes, including tumorigenesis. However, the relationship between serum clusterin expression and esophageal squamous cell carcinoma (ESCC) is unclear.
Methods. The serum clusterin concentrations of 87 ESCC patients and 136 healthy individuals were examined. An independent-samples Mann-Whitney 𝑈 test was used to compare serum clusterin concentrations of ESCC patients to those of healthy controls. Univariate analysis was conducted using the log-rank test and multivariate analyses were performed using the Cox proportional hazards model. Results. In healthy controls, the mean clusterin concentration was 288.8 ± 75.1 𝜇g/mL, while in the ESCC patients, the mean clusterin concentration was higher at 412.3±159.4 𝜇g/mL (𝑃 < 0.0001). The 1-, 2-, and 4-year survival rates for the 87 ESCC patients were 89.70%, 80.00%, and 54.50%. Serum clusterin had an optimal diagnostic cut-off point (serum clusterin concentration = 335.5 𝜇g/mL) for esophageal squamous cell carcinoma with sensitivity of 71.26% and specificity of 77.94%. And higher serum clusterin concentration (>500 𝜇g/mL) indicated better prognosis (𝑃 = 0.030).
Conclusions. Clusterin may play a key role during tumorigenesis and tumor progression of ESCC and it could be applied in clinical work as a tumor marker and prognostic factor.

Septin 9 methylated DNA is a sensitive and specific blood test for colorectal cancer

JD Warren, Wei Xiong, AM Bunker, CP Vaughn, LV Furtado, et al.
BMC Medicine 2011, 9:133. http://www.biomedcentral.com/1741-7015/9/133

Background: About half of Americans 50 to 75 years old do not follow recommended colorectal cancer (CRC) screening guidelines, leaving 40 million individuals unscreened. A simple blood test would increase screening compliance, promoting early detection and better patient outcomes. The objective of this study is to demonstrate the performance of an improved sensitivity blood-based Septin 9 (SEPT9) methylated DNA test for colorectal cancer. Study variables include clinical stage, tumor location and histologic grade.
Methods: Plasma samples were collected from 50 untreated CRC patients at 3 institutions; 94 control samples were collected at 4 US institutions; samples were collected from 300 colonoscopy patients at 1 US clinic prior to endoscopy. SEPT9 methylated DNA concentration was tested in analytical specimens, plasma of known CRC cases, healthy control subjects, and plasma collected from colonoscopy patients.
Results: The improved SEPT9 methylated DNA test was more sensitive than previously described methods; the test had an overall sensitivity for CRC of 90% (95% CI, 77.4% to 96.3%) and specificity of 88% (95% CI, 79.6% to 93.7%), detecting CRC in patients of all stages. For early stage cancer (I and II) the test was 87% (95% CI, 71.1% to 95.1%) sensitive. The test identified CRC from all regions, including proximal colon (for example, the cecum) and had a 12% false-positive rate. In a small prospective study, the SEPT9 test detected 12% of adenomas with a false-positive rate of 3%.
Conclusions: A sensitive blood-based CRC screening test using the SEPT9 biomarker specifically detects a majority of CRCs of all stages and colorectal locations. The test could be offered to individuals of average risk for CRC who are unwilling or unable to undergo colonoscopy.

Matrix Metalloproteinases in Cancer: Prognostic Markers and Therapeutic Targets

Pia Vihinen And Veli-Matti K¨Ah¨Ari
Int. J. Cancer 2002; 99: 157–166 http://dx.doi.org:/10.1002/ijc.10329

Degradation of extracellular matrix is crucial for malignant tumour growth, invasion, metastasis and angiogenesis. Matrix metalloproteinases (MMPs) are a family of zinc-dependent neutral endopeptidases collectively capable of degrading essentially all matrix components. Elevated levels of distinct MMPs can be detected in tumour tissue or serumof patients with advanced cancer and their role as prognostic indicators in cancer is studied. In addition, therapeutic intervention of tumour growth and invasion based on inhibition of MMP activity is under intensive investigation and several MMP inhibitors are in clinical trials in cancer. In this review, we discuss the current view on the feasibility of MMPs as prognostic markers and as targets for therapeutic intervention in cancer.

Mass Spectrometric Screening of Ovarian Cancer with Serum Glycans

Jae-Han Kim, Chang Won Park, Dalho Um, Ki Hwang Baek, Yohahn Jo, et al.
Disease Markers  2014, Article ID 634289, 9 pages

development of novel biomarkers based on the glycomic analysis. In this study, N-linked glycans from human serum were quantitatively profiled by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) and compared between healthy controls and ovarian cancer patients. A training set consisting of 40 healthy controls and 40 ovarian cancer cases demonstrated an inverse correlation between 𝑃 value of ANOVA and area under the curve (AUC) of each candidate biomarker peak from MALDI-TOF MS, providing standards for the classification. A multi-biomarker panel composed of 15 MALDI-TOF MS peaks resulted in AUC of 0.89, 80∼90% sensitivity, and 70∼83% specificity in the training set. The performance of the biomarker panel was validated in a separate blind test set composed of 23 healthy controls and 37 ovarian cancer patients, leading to 81∼84% sensitivity and 83% specificity with cut-off values determined by the training set. Sensitivity of CA-125, the most widely used ovarian cancer marker, was 74%in the training set and 78% in the test set, respectively. These results indicate that MALDI-TOF MS-mediated serum N-glycan analysis could provide critical information for the screening of ovarian cancer.

Large, Collaborative Lung Cancer Trial Goes for Precision Medicine Goal

News | June 30, 2014 | Lung Cancer Targets

By Anna Azvolinsky, PhD

In a new biomarker-focused clinical trial, five therapies will be tested to develop new, precision medicine approaches to treat squamous cell lung cancer. The Lung Cancer Master Protocol (Lung-MAP)/SWOG S1400 phase 2/3 clinical trial, brings together the National Cancer Institute (NCI), the Foundation for the National Institutes of Health (FNIH), SWOG Cancer Research, five pharmaceutical companies (Amgen, AstraZeneca, Genentech, MedImmune, and Pfizer), Foundation Medicine (a molecular informatics company), and Friends of Cancer Research, a non-profit foundation.

The trial aims to enroll about 10,000 patients total and will cost about $160 million, of which the NCI is contributing $25 million.

Lung-MAP is unique as this is the first public-private partnership in drug development that includes the NCI, the Food and Drug Administration (FDA), U.S. oncology cooperative groups, and a number of patient advocacy groups according to one of the study investigators, David Gandara, MD, chair of the SWOG lung committee, and thoracic oncologist at the UC Davis Cancer Center. “Funds are made available for every aspect of the trial,” said Gandara. “There is nothing in the history of oncology or drug development like it.”

The clinical trial seeks to identify molecular aberrations in patients with advanced squamous cell lung cancer that can be targeted either by existing therapies or through the development of new ones. The innovation of this trial is a master protocol that will rely on the strength of numbers—up to 1000 patients per year at more than 200 sites throughout the U.S. for more than 200 cancer-related genetic alterations. Testing results will then dictate which experimental trial arm is most appropriate for which patient. Unlike a trial that seeks to enroll patients harboring just one mutation, which limits the access for many patients, the Lung-MAP design better ensures that a patient who is screened will be eligible for a targeted therapy trial arm.

This type of umbrella trial design is particularly suitable for squamous cell lung cancer. Thus far, has not been defined by one or several driver mutations. Instead, these tumors are made of a spectrum of genetic aberrations that are each relatively rare within the squamous lung cancer patient population, making enrollment into targeted therapy clinical trials difficult. According to the NCI, Lung-MAP “aims to establish a model of clinical testing that more efficiently meets the needs of both patients and drug developers,” facilitating more efficient matching of a patient to an investigational targeted therapy trial.

Lung-MAP was specifically designed for squamous cell lung cancer because this lung cancer subtype represents the greatest unmet need for new treatment, Gandara told OncoTherapy Network:

“All of the dramatic advances that have been made in the treatment of lung cancer over the last ten years have occurred in adenocarcinoma, a lung cancer subtype with several recently recognized and ‘druggable oncogenes’ such as EGFR mutations or ALK translocations. However, there have been essentially no advances in squamous cell lung cancer.”

But, recent genome-wide studies have identified several gene alterations in squamous cell lung cancer that are also druggable, including PI3K, FGFR, and CDK mutations, said Gandara. The trial is initially testing four targeted therapies: Genentech’s GDC-0032 (a PI3 kinase inhibitor), Pfizer’s palbociclib (an oral cyclin-dependent-kinase 4/6 inhibitor, AZD4547), an oral fibroblast growth factor receptor inhibitor from AstraZeneca, and rilotumumab, Amgen’s antibody against the human hepatocyte growth factor.

The fifth agent is, MEDI4736, an immune checkpoint inhibitor antibody targeting PD-L1. Patients whose tumors do not harbor a mutation suitable for targeting with one of the four targeted therapies will be enrolled in the MED4736 sub-study.

Once a patient is matched to a specific trial sub-study, randomization will determine whether the patient receives the experimental therapy or standard of care chemotherapy. The planned trial endpoints for each sub-study are overall survival and progression-free survival.

“I cannot overemphasize the importance of the FDA’s participation in this project, since each of these sub-studies is designed to result in approval of a paired biomarker and new drug if that sub-study meets the requirements for improved effectiveness,” said Gandara.

– See more at: http://www.oncotherapynetwork.com/lung-cancer-targets/large-collaborative-lung-cancer-trial-goes-precision-medicine-goal

The BATTLE Trial: Personalizing Therapy for Lung Cancer

Kim, RS. Herbst, II. Wistuba, JJ Lee, GR. Blumenschein Jr., A Tsao, DJ. Stewart, et al.

Authors’ Affiliations: 1Departments of Thoracic/Head and Neck Medical Oncology, 2Pathology, 3Biostatistics, and 4Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas; 5Winship Cancer Center, Emory University, Atlanta, Georgia; 6Dana-Farber Cancer Institute, Boston, Massachusetts; and 7University of Maryland, Baltimore, Maryland.

Corresponding Author:

Waun K. Hong, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX 77030. Phone: 713-794-1441; Fax: 1-713-792-4654; E-mail:whong@mdanderson.org

The Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial represents the first completed prospective, biopsy-mandated, biomarker-based, adaptively randomized study in 255 pretreated lung cancer patients. Following an initial equal randomization period, chemorefractory non–small cell lung cancer (NSCLC) patients were adaptively randomized to erlotinib, vandetanib, erlotinib plus bexarotene, or sorafenib, based on relevant molecular biomarkers analyzed in fresh core needle biopsy specimens. Overall results include a 46% 8-week disease control rate (primary end point), confirm prespecified hypotheses, and show an impressive benefit from sorafenib among mutant-KRAS patients. BATTLE establishes the feasibility of a new paradigm for a personalized approach to lung cancer clinical trials.

(ClinicalTrials.gov numbers:NCT00409968, NCT00411671, NCT00411632, NCT00410059, and   NCT00410189.

Significance: The BATTLE study is the first completed prospective, adaptively randomized study in heavily pretreated NSCLC patients that mandated tumor profiling with “real-time” biopsies, taking a substantial step toward realizing personalized lung cancer therapy by integrating real-time molecular laboratory findings in delineating specific patient populations for individualized treatment. Cancer Discovery; 1(1); 44–53. © 2011 AACR.

Read the Commentary on this article by Sequist et al., p. 14
Read the Commentary on this article by Rubin et al., p. 17
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Pharmacometabolomics in Drug Discovery & Development: Applications and Challenges

Yang and F. Marotta
Metabolomics 2012, 2:5 http://dx.doi.org/10.4172/2153-0769.1000e122

Recently, the concept of pharmaco-metabolomics is mentioned more frequently as an emerging discipline to study the effect of drugs on the whole pattern of small endogenous molecules and in applying the profiles of metabolomics for drug development. For the latter part, metabolomics is majorly used to differentiate patients into responder or non-responder groups in an effort to decrease large inter-individual variation in clinical trials. It is a novel approach that combines metabolite profile and chemo-metrics to model and predict drug targets, efficacy, pharmacokinetics and toxicity on both individual and population basis. It attracts many scientists’ attention because of its intrinsic advantages and promising potentials in drug discovery and development. Considering personalized drug treatment is the desired goal for current drug development, pharmaco-metabolomics provide an effective and inexpensive strategy to evaluate drug efficacy and toxicology, which may make personalized medicine realistic both from scientific and financial perspectives. Furthermore, the FDA also realized that metabolomics coupling with other “Omics” approaches could be a valuable tool in evaluating general toxicology and could eventually replace the use of animals after addressing certain challenges.

Networking metabolites and diseases

Pascal Braun, Edward Rietman, and Marc Vidal
PNAS  July 22, 2008; 105(29): 9849–9850

Diseasome and Drug-Target Network

Recently, Goh et al. constructed a ‘‘diseasome’’ network in which two diseases are linked to each other if they share at least one gene, in which mutations are associated with both diseases. In the resulting network, related disease families cluster tightly together, thus phenotypically defining functional modules. Importantly, for the first time this study applied concepts from network biology to human diseases, thus opening the door for discovering causal relationships between  disregulated networks and resulting ailments.

Subsequently Yilderim et al. linked drugs to protein targets in a drug–target network, which could then be overlaid with the diseasome network. One notable finding was the recent trend toward the development of new compounds directly targeted at disease gene products, whereas previous drugs, often found by trial and error, appear to target proteins only indirectly related to the actual disease molecular mechanisms. An important question that remains in this emerging field of network analysis consists of investigating the extent to which directly targeting the product of mutated genes is an efficient approach or whether targeting network properties instead, and thereby accounting for indirect nonlinear effects of system perturbations by drugs, may prove more fruitful. However, to answer such questions it is important to have a good understanding of the various influences that can lead to diseases.

UPDATED 6/01/2019

Combined hereditary and somatic mutations of replication error repair genes result in rapid onset of ultra-hypermutated cancers

from  2015 Mar;47(3):257-62. doi: 10.1038/ng.3202. Epub 2015 Feb 2.

Shlien A1Campbell BB2de Borja R3Alexandrov LB4Merico D5Wedge D4Van Loo P6Tarpey PS4Coupland P7Behjati S4Pollett A8Lipman T9Heidari A9Deshmukh S9Avitzur N9Meier B10Gerstung M4Hong Y10Merino DM3Ramakrishna M4Remke M11Arnold R3Panigrahi GB3Thakkar NP12Hodel KP13Henninger EE13Göksenin AY13Bakry D14Charames GS15Druker H16Lerner-Ellis J17Mistry M2Dvir R18Grant R14Elhasid R18Farah R19Taylor GP20Nathan PC14Alexander S14Ben-Shachar S21Ling SC22Gallinger S23Constantini S24Dirks P25Huang A26Scherer SW27Grundy RG28Durno C29Aronson M30Gartner A10Meyn MS31Taylor MD25Pursell ZF13Pearson CE12Malkin D32Futreal PA4Stratton MR4Bouffet E26Hawkins C33Campbell PJ34Tabori U35Biallelic Mismatch Repair Deficiency Consortium.

Abstract: DNA replication-associated mutations are repaired by two components: polymerase proofreading and mismatch repair. The mutation/consequences of disruption to both repair components in humans are not well studied. We sequenced cancer genomes from children with inherited biallelic mismatch repair deficiency (bMMRD). High-grade bMMRD brain tumors exhibited massive numbers of substitution mutations (>250/Mb), which was greater than all childhood and most cancers (>7,000 analyzed). All ultra-hypermutated bMMRD cancers acquired early somatic driver mutations in DNA polymerase ɛ or δ. The ensuing mutation signatures and numbers are unique and diagnostic of childhood germ-line bMMRD (P < 10(-13)). Sequential tumor biopsy analysis revealed that bMMRD/polymerase-mutant cancers rapidly amass an excess of simultaneous mutations (∼600 mutations/cell division), reaching but not exceeding ∼20,000 exonic mutations in <6 months. This implies a threshold compatible with cancer-cell survival. We suggest a new mechanism of cancer progression in which mutations develop in a rapid burst after ablation of replication repair.

Genetic changes which occur in spontaneous arising somatic cancers include point mutations, copy number alterations and rearrangements and in general result from a defective DNA repair mechanisms during proliferation/replication over many years however as most somatic cancers are heterogeneous it is difficult to pinpoint the exact repair defects which may be ultimately responsible for such genetic aberrations.

However, early-onset cancers (e.g. pediatric cancers) in patients with hereditary DNA repair defects offer a good view of the mutation types and secondary pathways that drive oncogenesis. bMMRD is a childhood cancer syndrome characterized by early-onset cancers in various organs and caused by biallelic mutations.  In this study, genomes from 17 inherited cancers, by exomic sequencing and microarrays, were analyzed and compared to non-neoplastic tissue genomes from matched patients.  Brain cancers from these patients had an extremely high number of point mutations compared to other childhood cancers and adult cancers.

Mismatch repair was defective in all these cancers therefore it appeared that secondary mutations are required to cause the ultrahypermutated state.  The most frequently mutated gene was POLE (polymerase epsilon), affecting the proofreading ability of this DNA polymerase.  The genomes of tumors with mutant POLE had signature mutational spectrum and the signature occurred early but these signatures had been found in endometrial and colorectal cancers.  The authors concluded, based on serial analysis of other brain cancers with bMMRD and the observation that recurrent brain cancers accumulated mutations over a relatively short period, once the proofreading capability of pol epsilon is compromised in MMR deficient cells there is no defense against rapid and catastrophic accumulations of mutations.  This rapid accumulation of mutations apparently do not lead to apoptosis but rather rapid tumor initiation, and generating multiple subclones of tumor cells.

UPDATED 9/26/2021

Metabolic Profiling Reveals a Dependency of Human Metastatic Breast Cancer on Mitochondrial Serine and One-Carbon Unit Metabolism

Source: https://pubmed.ncbi.nlm.nih.gov/31941752/


Breast cancer is the most common cancer among American women and a major cause of mortality. To identify metabolic pathways as potential targets to treat metastatic breast cancer, we performed metabolomics profiling on the breast cancer cell line MDA-MB-231 and its tissue-tropic metastatic subclones. Here, we report that these subclones with increased metastatic potential display an altered metabolic profile compared with the parental population. In particular, the mitochondrial serine and one-carbon (1C) unit pathway is upregulated in metastatic subclones. Mechanistically, the mitochondrial serine and 1C unit pathway drives the faster proliferation of subclones through enhanced de novo purine biosynthesis. Inhibition of the first rate-limiting enzyme of the mitochondrial serine and 1C unit pathway, serine hydroxymethyltransferase (SHMT2), potently suppresses proliferation of metastatic subclones in culture and impairs growth of lung metastatic subclones at both primary and metastatic sites in mice. Some human breast cancers exhibit a significant association between the expression of genes in the mitochondrial serine and 1C unit pathway with disease outcome and higher expression of SHMT2 in metastatic tumor tissue compared with primary tumors. In addition to breast cancer, a few other cancer types, such as adrenocortical carcinoma and kidney chromophobe cell carcinoma, also display increased SHMT2 expression during disease progression. Together, these results suggest that mitochondrial serine and 1C unit metabolism plays an important role in promoting cancer progression, particularly in late-stage cancer. IMPLICATIONS: This study identifies mitochondrial serine and 1C unit metabolism as an important pathway during the progression of a subset of human breast cancers.


The majority of breast cancer patients die from metastatic disease. The process of cancer metastasis involves local invasion into surrounding tissue, dissemination into the bloodstream, extravasation, and eventual colonization of a new tissue. Following a period of dormancy, small numbers of micrometastases eventually proliferate into large macrometastases, or secondary tumors.

Previous studies have illuminated several themes of metabolic reprogramming that occur during metastasis (). However, the majority of these reported site-specific metabolic features of metastatic cancer cells. We reason that breast cancer cells that leave the primary tumor and successfully establish new lesions at distal sites would encounter similar metabolic stresses during metastasis. By performing comparative metabolomics on the MDA-MB-231 human breast cancer cell line and its tissue-tropic metastatic subclones, we uncovered that the catabolism of the non-essential amino acid serine through the mitochondrial one-carbon (1C) unit pathway is an important driver of proliferation in a subset of metastatic breast cancers that closely resembles the molecular features of MDA-MB-231 cells. Emerging evidence shows that the non-essential amino acid serine is essential for cancer cell survival and proliferation. The genomic regions containing PHGDH are amplified in breast cancer and melanoma, diverting 3PG to serine synthesis (,). We also reported that PHGDH is upregulated upon amino acid starvation by the transcription factor ATF4 (). On one hand, serine serves as a precursor for the synthesis of protein, lipids, nucleotides and other amino acids, which are necessary for cell division and growth. On the other hand, serine catabolism through the mitochondrial 1C unit pathway is critical for maintaining cellular redox control under stress conditions (,). In mitochondria, serine catabolism is initiated by serine hydroxymethyltransferase 2 (SHMT2). SHMT2 catalyzes a reversible reaction converting serine to glycine, with concurrent generation of the 1C unit donor methylene-THF, which is further oxidized by downstream enzymes MTHFD2 and MTHFD1L to produce NAD(P)H and formate. Subsequent export of formate from the mitochondria can then be re-assimilated into the cytosolic folate pool to support anabolic reactions. All three mitochondrial serine and 1C unit pathway enzymes (SHMT2, MTHFD2 and MTHFD1L) are upregulated in breast tumor samples compared to normal tissues (,). However, due to lack of functional investigations targeting this pathway in in vitro and in vivo breast cancer models, it remains unclear whether the mitochondrial 1C unit pathway represents a good target for treating metastatic breast cancer.

In this study, we report that enzymes in the mitochondrial serine and 1C unit pathway are even further upregulated specifically in subclones of the aggressive breast cancer cell line MDA-MB-231 that have been selected in vivo for the ability to preferentially metastasize to specific organs. We demonstrate that SHMT2 inhibition suppresses proliferation more strongly in these highly metastatic subclones compared to the parental population in vitro. Knockdown of SHMT2 also impairs breast cancer growth in vivo at both the primary and metastatic sites. In addition, we find that the expression of mitochondrial 1C unit pathway enzymes significantly associates with poor disease outcome in a subset of human breast cancer patients, potentiating its role as a therapeutic target or biomarker in advanced cancer. Finally, SHMT2 expression increases in breast invasive carcinoma, adrenocortical carcinoma, chromophobe renal cell carcinoma and papillary renal cell carcinoma during tumor progression, particularly in late stage tumors, suggesting that inhibitors targeting SHMT2 may hold promise for treating these late stage cancers when other therapeutic options become limited.

Materials and Methods

Cell lines

All of the paired parental and metastatic subclones were generated in Dr. Joan Massagué’s laboratory (Memorial Sloan-Kettering Cancer Center) (). Cells were cultured in DMEM/F12 with 10% fetal bovine serum (Sigma) with 1% penicillin/streptomycin. All cells lines were tested every three to six months and found negative for mycoplasma (MycoAlert Mycoplasma Detection Kit; Lonza). These cell lines were not authenticated by the authors. All cell lines used in experiments were passaged no more than ten times from time of thawing.


Stable 831-BrM,1833-BoM, and 4175-LM cell lines expressing shRNA against SHMT2, MTHFD2, and c-Myc were generated through infection with lentivirus and 1 μg/mL puromycin selection. shRNA-expressing virus was obtained using a previously published method (). Pooled populations were tested for on-target knockdown by immunoblot.


The following antibodies were used: SHMT1, SHMT2 (Sigma), MTHFD2, MTHFD1L, c-Myc, Actin (Cell Signaling Technologies).

RNA Isolation, Reverse Transcription, and Real-Time PCR

Total RNA was isolated from tissue culture plates according to the TRIzol Reagant (Invitrogen) protocol. 3 μg of total RNA was used in the reverse transcription reaction using the SuperScript III (Invitrogen) protocol. Quantitative PCR amplification was performed on the Prism 7900 Sequence Detection System (Applied Biosystems) using Taqman Gene Expression Assays (Applied Biosystems). Gene expression data were normalized to 18S rRNA.

In vivo Tumor Growth Assays

All procedures involving animals and their care were approved by the Institutional Animal Care and Use Committee of Stanford University in accordance with institutional and National Institutes of Health guidelines. For orthotopic growth studies, 4175-LM shNT and 4175-LM shSHMT2 cells (1 × 106 cells in 0.1 mL of PBS, n = 8 per group) were injected into the flanks of NU/J 10-week-old female mice (The Jackson Laboratory). Tumors were measured with calipers over a 50-day time course. Volumes were calculated using the formula width2 × length × 0.5.

For lung metastasis assays, 4175-LM shNT and 4175-LM shSHMT2 cells (0.2 × 105 cells, n = 8 per group) were injected via tail vein into 6–8 week-old female NOD SCID mice. Mice were imaged weekly using the Xenogen IVIS 200 (PerkinElmer, Waltham, MA). Briefly, mice were injected intraperitoneally with 100 μg/g of D-luciferin (potassium salt; PerkinElmer) on the day of imaging. 8 min later, mice were anesthetized in an anesthesia-induction chamber using a mixture of 3% isoflurane (Fluriso, VetOne) in O2. Anesthesia was maintained with a mixture of 2% isoflurane in O2 inside the imaging chamber. Using Living Image (PerkinElmer, Waltham, MA), images were acquired (Exposure time, auto; F stop. 1.2; Binning, medium) from both dorsal and ventral sides of mice and a total photon flux (p/sec/cm2/sr) per animal was calculated by averaging the signal acquired from the dorsal and ventral side. After 4 weeks, surviving mice were sacrificed and lungs snap frozen in liquid N2 prior to homogenization in TRIzol for RNA extraction.

Metabolite Profiling and Mass Spectrometry

For total metabolite analysis, parental and metastatic cell lines were seeded in 60mm culture dishes in DMEM/F12 supplemented with 10% dialyzed fetal bovine serum. Media was refreshed 2 hours prior to harvesting by washing 3x with PBS before quenching with 800mL of −80 C 80:20 methanol:water. Extracts were spun down, supernatants collected, dried and resuspended in water before LC-MS analysis. Samples were analyzed by reversed-phase ion-pairing chromatography coupled with negative-mode electrospray-ionization high-resolution MS on a stand-alone ThermoElectron Exactive orbitrap mass spectrometer (). Peak picking and quantification were conducted using MAVEN analysis software. Heatmap was generated in R. Multiple testing correction and q-value generation were performed in PRISM software (GraphPad).

For [2,3,3-2H]serine labeling experiments, parental and metastatic cells were cultured in RPMI medium lacking glucose, serine, and glycine (TEKnova) supplemented with 2 g/L glucose and 0.03 g/L [2,3,3-2H]serine (Cambridge Isotope Laboratories) for up to 24 hours before harvesting. Cells were washed twice with ice-cold PBS prior to extraction with 400 μL of 80:20 acetonitrile:water over ice for 15 min. Cells were scraped off plates to be collected with supernatants, sonicated for 30s, then spun down at 1.5 × 104 RPM for 10 min. 200 μL of supernatant was taken out for LC-MS/MS analysis immediately.

Quantitative LC-ESI-MS/MS analysis of [2,3,3-2H]serine-labeled cell extracts was performed using an Agilent 1290 UHPLC system equipped with an Agilent 6545 Q-TOF mass spectrometer (Santa Clara, CA, US). A hydrophilic interaction chromatography method (HILIC) with an BEH amide column (100 × 2.1 mm i.d., 1.7 μm; Waters) was used for compound separation at 35 °C with a flow rate of 0.3ml/min. The mobile phase A consisted of 25 mM ammonium acetate and 25mM ammonium hydroxide in water and mobile phase B was acetonitrile. The gradient elution was 0–1 min, 85 % B; 1–12 min, 85 % B → 65 % B; 12– 12.2 min, 65 % B-40%B; 12.2–15 min, 40%B. After the gradient, the column was re-equilibrated at 85%B for 5min. The overall runtime was 20 min and the injection volume was 5 μL. Agilent Q-TOF was operated in negative mode and the relevant parameters were as listed: ion spray voltage, 3500 V; nozzle voltage, 1000 V; fragmentor voltage, 125 V; drying gas flow, 11 L/min; capillary temperature, 325 °C, drying gas temperature, 350 °C; and nebulizer pressure, 40 psi. A full scan range was set at 50 to 1600 (m/z). The reference masses were 119.0363 and 980.0164. The acquisition rate was 2 spectra/s. Isotopologues extraction was performed in Agilent Profinder B.08.00 (Agilent Technologies). Retention time (RT) of each metabolite was determined by authentic standards (Supplementary Table S1). The mass tolerance was set to +/−15 ppm and RT tolerance was +/− 0.2 min. Natural isotope abundance was corrected using Agilent Profinder software (Agilent Technologies).

Cell Line Classification

Cell line expression and copy number data were downloaded from the COSMIC cell line dataset (https://cancer.sanger.ac.uk/cell_lines), and all cell lines were classified using different cell line classifiers, including PAM50 and scmod2 using the package genefu from Bioconductor; and iC10 using package iC10 (). The MDA-MB-231 parental and metastatic subclones were classified as Basal (posterior probability of 0.516), ER-Her2- (posterior probability of 0.997), IC4 (posterior probability of 0.999).

Outcome Analysis

METABRIC clinical and expression data was downloaded from EGA (EGAS00000000083) (). Outcome analysis was performed in IC4 samples only (N=342) in order to mimic the phenotype of the MDA-MB-231 breast cancer cell line. Survival analysis was performed over disease specific survival (DSS) censored to 20 years. Gene high/low categorization was performed using the maxstat algorithm, which determines the optimal threshold for separating high and low expression (from the surv cutpoint function of package survminer). Cox Proportional Hazard multivariate models use continuous expression adjusted by age, grade, size, number of lymph nodes, ER, PR and Her2 status. Kaplan-Meier plots were generated using the package survcomp, and Cox Proportional Hazards were generated using the package rms.

Immunohistochemical Staining and Quantification for SHMT2

Human primary breast cancer tissue and paired lymph node metastases were obtained from Biomax.us. Tumors were graded by Biomax.us pathologists according to the Nottingham grading system with respect to degree of glandular duct formation, nuclear pleomorphism, and nuclear fission counting. Each feature was scored from 1–3, and the total score was used to determine the following grades: Grade 1 (total score 3–5; low grade or well differentiated), Grade 2 (total score 6–7; intermediate grade or moderately differentiated), Grade 3 (total score 8–9; high grade or poorly differentiated). Standard immunohistochemical methods were performed as previously described (). The primary anti-human SHMT2 antibody (Sigma) was used at a concentration of 1:3000. Images were acquired on a Leica DMi8 system (Leica Microsystems) and quantified for positive SHMT2 signal intensity by ImageJ software.

SHMT2 Expression Analysis by Individual Cancer Stage

SHMT2 expression data across every annotated TCGA cancer data set was queried and downloaded from the UALCAN database (http://ualcan.path.uab.edu/index.html) ().

Statistical Analyses

All statistical tests were performed using the paired or unpaired Student’s t test by PRISM software. Values with a p value of < 0.05 were considered significant.


Metastatic breast cancer cells exhibit altered metabolic profiles

To identify common metabolic pathways reprogrammed in metastatic breast cancer cells during cancer progression, we performed metabolomic profiling of the human triple negative breast cancer cell line MDA-MB-231 and its metastatic subpopulations (Fig. 1A and andB).B). This cell line was derived from the pleural effusion of a patient with widespread metastatic disease years after primary tumor removal (), and the subclones of this cell line with higher metastasis rate and preference to the bone, lung, or brain were previously isolated by in vivo selection () (831-BrM: brain metastasis. 1833-BoM: bone metastasis. 4175-LM: lung metastasis).

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Metastatic breast cancer subclones display an altered metabolic profile. (A) Schematic of targeted metabolomics workflow. Brain (831-BrM), bone (1833-BoM), and lung (4175-LM) metastatic subclones from tissue-tropic subpopulations were generated following IV injection of a parental population of MDA-MB-231 (231-Parental) cells into the tail vein or heart. Stable cell lines were passaged in culture prior to metabolite extraction for LC-MS/MS. (B) LC-MS profile of the 231-Parental, 831-BrM, and 1833-BoM cell lines. Cell lines were plated in biological triplicates prior to metabolite extraction. Signals were normalized to the mean signal of each metabolite across all samples, log2 transformed, and clustered.

At the time of initial metabolomics comparison, the lung metastatic subclone 4175-LM did not recover well in culture, so we profiled the 831-BrM and 1833-BoM metastatic subclones along with the parental population. We observed multiple metabolites involved in a plethora of metabolic pathways that were differentially enriched or depleted in the metastatic 831-BrM and 1833-BoM subclones compared to the parental population of MDA-MB-231 (231-Parental) cells (Fig. 1B). Following correction for false discovery rate, the levels of twenty-four metabolites were significantly altered in both 831-BrM and 1833-BoM cells compared to 231-Parental cells (Supplementary Table S2). Metabolites significantly enriched in metastatic subclones included the glycolytic intermediate dihydroxyacetone-phosphate (which is reversibly isomerized to glyceraldehyde-3-phosphate), the tricarboxylic acid (TCA) cycle intermediate succinate, amino acids such as proline and asparagine, and the pentose-phosphate pathway product 5-phosphoribosyl-1-pyrophosphate. These observations are consistent with prior observations of perturbations in lower glycolysis and the TCA cycle observed in other cell line models (notably murine 4T1 cells), suggesting common metabolic developments during metastasis of breast cancers in both mice and humans (,,). Additionally, enrichment of asparagine has been reported to promote metastatic cancer cell phenotypes by epithelial-to-mesenchymal transition (). Nonetheless, the most significantly depleted class of metabolites in 831-BrM and 1833-BoM cells compared to 231-Parental cells were free purine nucleotides, suggesting alterations in purine metabolism in metastatic cells (Fig. 1B).

c-Myc is important for breast cancer cell proliferation

We wondered whether reduced levels of purines reflected decreased synthesis or higher consumption in the metastatic subclones. Because it was previously reported that the oncogenic transcription factor c-Myc induces the expression of nucleotide biosynthesis genes and that c-Myc amplification and overexpression is a common event in triple-negative breast cancer (), we wondered if the relative differences in purine abundance could be explained by altered c-Myc protein levels in our cell line system. Indeed, 831-BrM, 1833-BoM, and 4175-LM cells overexpressed c-Myc compared to 231-Parental cells (Fig. 2A). Since sufficiency of free nucleotides can act as an important checkpoint for cell division (), we then compared the proliferation rates of parental and metastatic subclones. Accordingly, 831-BrM, 1833-BoM, and 4175-LM cells proliferated faster than 231-Parental cells in vitro (Fig. 2B), suggesting that the higher consumption rate is the cause of lower purine levels in the metastatic subclones.

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c-Myc drives proliferation in metastatic breast cancer cell subclones. (A) IB for c-Myc from whole-cell extracts of parental and metastatic subclones. (B) Proliferation of parental cells and metastatic subclones over 3 days (mean ± SD, n = 3). (C) 3 day proliferation of 231-Parental, 831-BrM, 1833-BoM, and 4175-LM cells expressing either a nontargeting (shNT) or c-Myc targeting (shMyc) vectors. (mean ± SD, n = 3).

Because the role of c-Myc in metastasis is still unclear, with evidence suggesting it plays both pro-metastatic and anti-metastatic functions in breast cancer depending on the genetic context (,), we tested the sensitivity of parental and metastatic subclones to c-Myc inhibition. Small hairpin RNA (shRNA)–mediated knockdown of c-Myc reduced cell proliferation in all four cell lines, although the degree of inhibition was stronger in 831-BrM and 1833-BoM cells (Fig. 2CSupplementary Fig. S1). Parental cells expressing a non-targeting shRNA showed elevated c-Myc expression, possibly due to puromycin selection. These data suggest that c-Myc is an important mediator of cell proliferation, and c-Myc overexpression provided a proliferative advantage at least in brain and bone-metastatic subclones.

Identification of serine and one-carbon unit pathway elevation in metastatic subclones

The products of several metabolic pathways feed into nucleotide synthesis, including ribulose-5-phosphate from the pentose phosphate pathway, and one-carbon (1C) units and glycine from the serine and 1C unit pathway. It is also known that c-Myc can promote the expression of serine and glycine metabolism genes in cancer cells (,). We performed expression analyses of the metastatic subclones and found elevated levels of the key mitochondrial enzymes serine hydroxymethyltransferase 2 (SHMT2), methylenetetrahydrofolate dehydrogenase 2 (MTHFD2), and methylenetetrahydrofolate dehydrogenase 1-like (MTHFD1L), in contrast to the downregulated expression of the cytosolic isoenzyme serine hydroxymethyltransferase 1 (SHMT1) (Fig. 3AC). Consistent with previous reports in other cell types, knockdown of c-Myc in parental and metastatic breast cancer subclones diminished MTHFD2 and MTHFD1L protein expression, suggesting these enzymes are c-Myc-regulated (Supplementary Fig. S1). SHMT2 expression did not reduce upon c-Myc knockdown, suggesting that SHMT2 expression was regulated by other transcription factors. To determine whether c-Myc and mitochondrial 1C unit pathway enzyme overexpression was a common co-occurrence in other cancer metastasis models, we checked protein expression levels in the parental and metastatic subpopulations of other human cell line systems derived from lung adenocarcinoma or ER+ breast carcinoma patients (,). There was a clear correlation of SHMT2, MTHFD2, and MTHFD1L expression with c-Myc expression among all the cell lines tested. The brain metastatic subclones of lung adnocacinoma cell lines PC9 and H2030 had increased MTHFD2 expression, though we could not find another system that also displayed overexpression of c-Myc and all the three mitochondrial 1C unit pathway enzymes in metastatic subclones relative to their corresponding parental cells (Supplementary Fig. S2). Taken together with the observations of higher serine and glycine levels in 831-BrM and 1833-BoM cells compared to 231-Parental cells (Fig. 1B), these data suggest that the role of c-Myc in regulating mitochondrial serine and 1C unit metabolism in metastatic cancer may be tissue-specific.

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The mitochondrial serine and one-carbon unit pathway is upregulated in metastatic breast cancer subclones. (A) Schematic of the cytosolic and mitochondrial serine and one-carbon unit pathway. (B) qPCR for serine and one-carbon unit pathway genes (mean ± SD, n = 3, *P < 0.05 **P < 0.01 ***P < 0.001 ****P < 0.0001 by two-tailed Student’s t test, compared to expression in parental cells). (C) IB for serine and one-carbon unit pathway enzymes from whole-cell extracts of parental cells and metastatic subclones. (D) Schematic diagram of incorporation of 2H (D) from [2,3,3-2H]serine onto glycine, one-carbon units, and purines. (E) SHMT flux estimated by relative abundance of labeled glycine from serine (mean ± SD, n = 3, **P < 0.01 by two-tailed Student’s t test). (F) Fractional labeling of [2,3,3-2H]serine onto GTP and ATP (mean ± SD, n = 3, *P < 0.05 **P < 0.01 ***P < 0.001 by two-tailed Student’s t test).

Metastatic subclones display increased mitochondrial serine and one-carbon unit pathway activity

We next asked if higher expression of mitochondrial serine and 1C unit pathway enzymes might indeed reflect higher pathway activity. Serine can be catabolized in both the mitochondrial and cytosolic branch of the 1C unit pathway. Since cancer cells predominately express the mitochondrial serine catabolic enzymes over the cytosolic enzymes, serine is generally catabolized in the mitochondria in cancer cells (,,). Serine hydroxyl-methyltransferase 2 (SHMT2) initiates this reaction by converting serine to glycine while donating a carbon group to tetrahydrafolate (THF) to generate methylene-THF. Subsequent oxidation of methylene-THF by MTHFD2 and MTHFD1L generates NAD(P)H and formate. Formate can cross the mitochondrial membrane to provide 1C units for anabolic reactions such as nucleotide synthesis ().

We hypothesized that the reason metastatic cells upregulate the serine and 1C unit pathway is to enhance nucleotide synthesis to fuel cell proliferation. Indeed, most cancer cells have been reported to utilize serine as the predominant source of 1C units for biosynthesis (). We performed [2,3,3-2H]serine tracing to examine 1C unit pathway flux to glycine and purine nucleotides. In cells grown in media containing [2,3,3-2H]serine, the cytosolic pathway generates methylene-THF (me-THF) mass heavy by 2 (M+2) and 10-formyl-THF mass heavy by 1 (M+1), while 10-formyl-THF derived from mitochondrial formate exchange to the cytosol is strictly M+1. [2,3,3-2H]serine labeling onto the metabolites glycine and purine nucleotide triphosphates produced from the mitochondrial pathway thereby produces glycine M+1 and purines either M+1 or M+2 (Fig. 3D). Time course experiments were performed in 4175-LM cells to determine the optimal steady state labeling conditions for glycine and ATP from serine: 2 hours and 24 hours respectively (Supplementary Fig. S3). We observed higher SHMT flux in metastatic subclones, as the relative abundance of M+1 glycine was approximately 1.5-fold higher in 4175-LM cells compared to 231-Parental cells, indicating that higher purine turnover in metastatic cells was fueled by higher SHMT flux (Fig. 3E). Importantly, while robust fractions of ATP and GTP were labeled in parental cells, the metastatic subclones displayed even higher labeling fractions from serine (Fig. 3F). These results demonstrate that upregulation of serine catabolism through the mitochondrial 1C unit pathway promotes de novo purine synthesis in metastatic breast cancer cells.

Serine catabolism is necessary for metastatic cancer cell proliferation in vitro

To address the extent to which mitochondrial serine catabolism is necessary for cell proliferation, 231-Parental, 831-BrM, 1833-BoM, and 4175-LM cells were infected with lentivirus expressing shRNAs against SHMT2 (shSHMT2) or a nontargeting control (shNT). Intriguingly, knockdown of SHMT2 protein expression with two different shRNAs drastically suppressed proliferation of the metastatic subclones significantly, with a reduced effect in 231-Parental cells (Fig. 4A and andB).B). In contrast, knockdown of the downstream enzyme of the mitochondrial serine and 1C unit pathway, MTHFD2, suppressed proliferation to a lesser extent (Supplementary Fig. S4A and B). To evaluate the therapeutic potential of targeting 1C unit metabolism to block metastatic growth, we treated cells with a small-molecule inhibitor of SHMT called SHIN1 (). In vitro, metastatic subclones were sensitive to SHIN1 with an EC50 in the 100–500 nM range (Supplementary Fig. S5). There was no obvious enhancement of SHIN1 sensitivity in 831-BrM, 1833-BoM, and 4175-LM cells compared to 231-Parental cells, possibly because SHIN1 inhibits both SHMT2 and SHMT1 (Fig. 4C). Importantly, inhibition of cell proliferation in the presence of SHIN1 could be rescued by the supplementation of formate (2 mM), a source of cellular 1C units (Fig. 4C). These results indicate that the major role of elevated mitochondrial serine catabolism is to generate 1C units for cytosolic purine biosynthesis in the metastatic subclones. Thus, targeting SHMT activity may be a promising way to restrict nucleotide availability to block metastatic breast cancer cell proliferation.

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Metastatic subclones are particularly sensitive to SHMT2 inhibition. (A) 3 day proliferation of 231-Parental, 831-BrM,1833-BoM, and 4175-LM cells expressing either a nontargeting (shNT) or SHMT2 targeting (shSHMT2) vectors. Relative proliferation was calculated relative to average proliferation of shNT cells (mean ± SD, n = 3). (B) IB for SHMT2 in parental and metastatic subclones. (C) 3 day proliferation of parental and metastatic cells with 2 μM SHIN1, in RPMI with or without 2 mM formate and dialyzed FBS (mean ± SD, n = 3, ***P < 0.001 ****P < 0.0001 by two-tailed Student’s t test). Counts were normalized to the proliferation of 231-Parental cells in media without SHIN1 and formate treatment. (D) Growth of 4175-LM shNT and shSHMT2 tumors in the mammary fat pad of nude mice (mean ± SEM, n = 8, **P < 0.01 by two-tailed Student’s t test). (E) Quantification of luminescence signal in the lungs of mice 3 weeks post injection of either 4175-LM shNT or shSHMT2 cells (mean ± SEM, **P < 0.01 by two-tailed Student’s t test, shNT;n = 8 shSHMT2;n = 7). (F) qPCR analysis of hGAPDH expression in the lungs of mice 4 weeks post injection of either 4175-LM shNT or shSHMT2 cells (mean ± SEM, *P < 0.05 by two-tailed Student’s t test, shNT;n = 6 shSHMT2;n = 7).

SHMT2 knockdown impairs primary and metastatic growth in vivo

We then interrogated the effect of reducing mitochondrial 1C unit pathway activity in two different models of cancer growth in vivo. 4175-LM cells were chosen due to the relative ease of monitoring, measuring, and collecting tissue from lung metastasis compared to brain and bone metastasis. For the first model, we monitored breast cancer growth at the primary tumor site. SHMT2 knockdown significantly impaired the growth of 4175-LM cells in the mammary fat pads of immunodeficient mice (Fig. 4DSupplementary Fig. S6). For the second model, we induced breast cancer metastasis to the lung by intravenous tail vein injection. Because 4175-LM cells express firefly luciferase (), we tracked tumor growth in the lung by bioluminescence imaging (BLI). Both BLI and quantification of human GAPDH (hGAPDH) expression from resected mouse lungs revealed a roughly two-fold reduction of lung tumor burden in mice injected with shSHMT2 cells compared to shNT cells (Fig. 4E and andF,FSupplementary Fig. S7A). While on average, shSHMT2 tumors had reduced human SHMT2 (hSHMT2) expression compared to shNT tumors, some shSHMT2 tumors appeared to have reacquired hSHMT2 expression (Supplementary Fig. S7B and C). These data suggest that SHMT2 is necessary for metastatic growth in vivo.

Mitochondrial serine and 1C unit pathway genes are associated with more aggressive metastatic disease in some human breast cancer patients

To further explore the relevancy of mitochondrial one-carbon unit metabolism in human breast cancer metastasis, we examined the expression of SHMT1, SHMT2, MTHFD2, and MTHFD1L in the METABRIC dataset of human breast cancer patients (). We retrospectively inferred metastatic recurrence in patients by examining the frequency of disease-specific survival (DSS) up to 20 years. Patients were separated into two groups based on the maxstat algorithm (see Materials and Methods). Patients with high SHMT2 expression were significantly more likely to succumb to metastatic recurrent disease, while patients with high expression of the cytosolic isozyme SHMT1 were significantly protected from metastatic relapse (Fig. 5ASupplementary Fig. S8). Using three different breast cancer subtype clustering analyses based on gene expression (PAM50, IC10, SCMOD2), we classified the MDA-MB-231 cell line as basal, IC4 (copy number flat), and ERHer2 (,). We have previously described IC4 as consisting of a mixture of ER tumors with lymphocytic infiltration and ER+ tumors with abundant stroma. Accordingly, further analysis of the IC4 patient subgroup following adjustment for covariates of age, grade, size, number of lymph nodes, ER, PR and Her2 status revealed a significant association of MTHFD1, MTHFD1L, MTHFD2, and SHMT2 expression with worse survival and SHMT1 expression with better survival (Fig. 5B). Finally, we stained a tissue microarray panel of human breast invasive ductal carcinoma and matched lymph node metastases and found significantly higher expression of SHMT2 in metastatic cancer cells comparing to the primary tumors (Fig. 5C and andD).D). Together, these data suggest that SHMT2 and other mitochondrial 1C unit pathway enzymes may be used as prognostic markers that indicate worse patient outcome, while cytosolic SHMT1 expression may indicate better survival rate in the IC4 patient subgroup.

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Mitochondrial serine and one-carbon unit pathway enzyme expression correlates with poor survival in human breast cancer. (A) Kaplan-Meier plot for SHMT1 (left) and SHMT2 (right) expression associated with disease-specific survival (DSS) in the human IC4 patient subgroup (METABRIC). (B) Forest plot for the hazard of individual 1C unit pathway genes adjusted for covariates (age, grade, size, number of lymph nodes, ER, PR and Her2 status) in the IC4 subgroup (n=343). (C) Representative SHMT2 staining (at 40x) of human breast invasive ductal carcinoma and matched metastatic carcinoma tissue samples (LN = lymph node). (D) Quantification of SHMT2 intensity by IHC in metastatic lesions compared to primary tumors (mean ± SD, n = 33 per group, *P < 0.05 by two-tailed Student’s t test).

Relevance of SHMT2 expression in the progression and aggressiveness of other cancer types

To evaluate the contribution of mitochondrial 1C unit metabolism to the progression of other cancer types, we queried SHMT2 expression in TCGA datasets through the UALCAN portal (). In addition to breast invasive carcinoma (BRCA), we identified adrenocortical carcinoma (ACC), head and neck squamous cell carcinoma (HNSC), kidney chromophobe cell carcinoma (KICH), and kidney renal papillary cell carcinoma (KIRP) as cancer types in which SHMT2 expression progressively increased as a function of stage (Fig. 6). Notably, gain of SHMT2 expression in BRCA and HNSC tended to occur early on in cancer progression, whereas in KICH, SHMT2 upregulation may occur only during the very late stage. A few cancer types such as mesothelioma (MESO) and ovarian serous cystadenocarcinoma (OV) showed the opposite trend: a progressive loss of SHMT2 expression with increasing cancer stage (Supplementary Fig. 9). Collectively, these data present the possibility that there exist additional cancer types in which mitochondrial 1C unit metabolism promotes progression and aggressiveness.

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SHMT2 expression increases with stage in various cancers.

Box plots depicting the average expression level (transcripts per million) of SHMT2 in normal tissue (N) and as a function of cancer stage (stage 1 = S1; stage 2 = S2; stage 3 = S4; stage 4 = S4). Statistically significant differences between pairwise comparisons are highlighted in red. Abbreviations for cancer types are explained as follows: ACC (adrenocortical carcinoma), BRCA (breast invasive carcinoma), HNSCC (head and neck squamous cell carcinoma), KICH (kidney chromophobe carcinoma), KIRP (kidney renal papillary cell carcinoma).


For breast cancer, common metastatic sites include the brain, bone, liver, and lung. At the cellular level, the original heterogeneous population of cancer cells from the primary tumor undergo a selection process whereby those clones with alterations (carrying both genetic lesions and epigenetic modifications) favoring fitness and plasticity are enriched. These adaptations, in turn, equip cells with the ability to withstand standard treatments such as chemotherapy and radiation therapy, ultimately leading to cancer progression and metastatic recurrence (). While many previous studies have elucidated a role for molecular processes such as epithelial to mesenchymal transition and invasion and migration of cancer cells, our understanding of how metabolic pathway alterations shape metastatic growth is still limited. It is important to note that the MDA-MB-231 cells we studied were isolated from a pleural population that already metastasizes well in vivo. Our metabolomics profiling of the even more highly metastatic triple-negative breast cancer subclones suggested alterations in both glycolysis and the TCA cycle during the late stages of cancer progression, consistent with findings from other groups of heightened mitochondrial metabolism in metastatic cells (,,,). We further discovered elevated catabolism of serine in the mitochondria of our metastatic subclones. A previous study in isogenic murine 4T1 breast cancer cell lines found that transformed cells showed higher levels of nucleotides than nontransformed cells, and that “more metastatic” lines had even more nucleotides than “less metastatic” ones (). In contrast, we found lower levels of free purines in metastatic variants of human MDA-MB-231 cell lines compared to the parental population (Fig. 1B). This discrepancy may be attributed to different oncogenic contexts in 4T1 cells versus MDA-MB-231 cells or inherent differences in purine metabolism between murine and human cells. Due to the difficulty of obtaining pure metastatic tumor tissue from in vivo studies, the metabolomic analysis were performed using established cell lines in vitro. Microenvironmental factors from metastatic niche, such as hypoxia and nutrient starvation, also regulate cancer cell metabolism. Since mitochondrial 1C unit metabolism can utilize both NAD+ and NADP+, cancer cells with upregulation of mitochondrial 1C unit metabolism may gain metabolic flexibility to sustain proliferation under stress conditions. When cells engage active respiration, the mitochondrial 1C unit pathway can utilize NAD+ to generate 1C units; under hypoxia or starvation conditions, when the NAD+/NADH ratio decreases, elevated mitochondrial ROS leads to an increased NADP+/NADPH ratio, which can also drive the 1C unit pathway and purine synthesis. Further investigations comparing the metabolic profile changes under these stress conditions may provide more insight into potential links between metabolic stresses and the evolution of metastatic cancer cells.

The role of serine in cancer growth has drawn increasing interest over the years ever since the identification of PHGDH amplifications in melanoma and breast cancer (,). A variety of mechanisms have been proposed to explain why increased serine synthesis and serine catabolism could promote tumorigenesis, including rerouting glucose carbon flux, maintenance of compartment-specific NAD(P)+/NAD(P)H ratios, and the control of metabolites such as acetyl-coA, α-ketoglutarate, or 2-hydroxyglutarate (,,). Moreover, a previous study had implicated SHMT2 and a neutral amino acid importer of serine and glycine (ASCT2) as prognostic biomarkers for breast cancer (). Our study is the first to directly evaluate the therapeutic potential of targeting SHMT2 in metastatic breast cancer using both genetic and pharmaceutical approaches. Intriguingly, genetic knockdown of SHMT2 strongly inhibited the proliferation of metastatic cells, while treatment with a dual SHMT1/SHMT2 inhibitor suppressed proliferation of both parental and metastatic subclones. This discrepancy may be explained by prior observations that while MDA-MB-231 cells preferentially utilize the mitochondrial pathway for 1C unit production, inhibition of individual mitochondrial enzymes can lead to a switch to the cytosolic pathway (). We thus speculate that 231-Parental cells may be more adept at switching to cytosolic serine catabolism, and for reasons still unclear, the metastatic subclones are less flexible. Consistent with observations in colon cancer xenografts (), SHMT2 knockdown in the lung metastatic subclone slowed, but not completely suppressed, tumor growth in the mammary fat pad and lung. In addition, we found that in the IC4 subset of human breast cancer patients, the expression of mitochondrial one-carbon unit enzymes is positively associated with more aggressive disease. Thus, interrogating the expression status of mitochondrial one-carbon unit enzymes through transcriptional or proteomic methods holds prognostic value in the metastatic setting, and warrants the need for further development of drugs that selectively inhibit serine catabolism for treating the metastasis of triple-negative breast cancer.

What causes the upregulation of mitochondrial serine catabolic flux in highly metastatic cancer cells? We provide evidence that a crucial oncogenic event promotes the ability of metastatic breast cancer subclones to catabolize serine faster than parental cells: c-Myc activation. c-Myc overexpression is known to be associated with up to 40% of breast cancers, with hyperactive c-Myc enriched particularly in the basal-like subtype (,). These observations are consistent with our findings of the MDA-MB-231 cell line as basal-like and its metastatic subclones expressing even higher levels of c-Myc than the parental population (Fig. 2A). We found that c-Myc was required for the maintenance of the mitochondrial serine and 1C unit pathway genes MTHFD2 and MTHFD1L, consistent with previous reports that c-Myc supports serine/glycine metabolism at the transcriptional level in other cell types (,). These results suggest a model for breast cancer metastasis in which a small fraction of c-Mychigh expressing cells from the primary tumor acquire the ability to upregulate serine catabolism to fuel growth in metastatic tissue sites. Alternatively, high c-Myc expression and the linked ability to upregulate serine catabolism may be intrinsic properties of stem-like metastasis-initiating cells that are enriched in breast cancer cell populations selected for high metastatic activity in mice. As one of the key oncogenic transcription factors, there is increasing evidence that c-Myc plays multiple roles during the metastatic process. c-Myc knockdown reduces invasion and migration of MDA-MB-231 cells (). Moreover, a recent study corroborated our findings of elevated c-Myc levels in brain-metastatic derivatives of human breast cancer cells and demonstrated its necessity for the invasive growth of brain metastases (). Our study highlights the role of c-Myc in enhancing 1C unit pathway activity and proliferation, which is also important for metastatic growth. Since SHMT2 expression was not reduced by c-Myc shRNA, it is likely that other tumor-promoting factors, such as ATF4 and NRF2, also play important roles in late stage cancer progression by modulating 1C unit metabolism. Intriguingly, a recent report showed that TGF-β signaling induces the expression of SHMT2 (). Given the critical role of TGF-β in promoting metastasis (,), it may be interesting to further investigate whether serine and 1C unit pathway metabolic reprogramming is controlled by TGF-ß signaling in metastatic subpopulations of human breast cancer cells.

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Selected References to Signaling and Metabolic Pathways in PharmaceuticalIntelligence.com

Curator: Larry H. Bernstein, MD, FCAP


This is an added selection of articles in Leaders in Pharmaceutical Intelligence after the third portion of the discussion in a series of articles that began with signaling and signaling pathways. There are fine features on the functioning of enzymes and proteins, on sequential changes in a chain reaction, and on conformational changes that we shall return to.  These are critical to developing a more complete understanding of life processes.  I have indicated that many of the protein-protein interactions or protein-membrane interactions and associated regulatory features have been referred to previously, but the focus of the discussion or points made were different.

  1. Signaling and signaling pathways
  2. Signaling transduction tutorial.
  3. Carbohydrate metabolism3.1  Selected References to Signaling and Metabolic Pathways in Leaders in Pharmaceutical Intelligence
  4. Lipid metabolism
  5. Protein synthesis and degradation
  6. Subcellular structure
  7. Impairments in pathological states: endocrine disorders; stress hypermetabolism; cancer.

Selected References to Signaling and Metabolic Pathwayspublished in this Open Access Online Scientific Journal, include the following:

Update on mitochondrial function, respiration, and associated disorders

Curator and writer: Larry H. Benstein, MD, FCAP


A Synthesis of the Beauty and Complexity of How We View Cancer

Cancer Volume One – Summary

A Synthesis of the Beauty and Complexity of How We View Cancer

Author: Larry H. Bernstein, MD, FCAP


Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?

Author and Curator: Larry H Bernstein, MD, FCAP


 The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia, Similarities and Differences, and Pharmaceutical Targets

Author and Curator: Larry H Bernstein, MD, FCAP, 
Author, and Content Consultant to e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC
And Curator: Aviva Lev-Ari, PhD, RN


Renal Distal Tubular Ca2+ Exchange Mechanism in Health and Disease

Author and Curator: Larry H. Bernstein, MD, FCAP
Curator:  Stephen J. Williams, PhD
and Curator: Aviva Lev-Ari, PhD, RN


Mitochondrial Metabolism and Cardiac Function

Curator: Larry H Bernstein, MD, FACP


Mitochondrial Dysfunction and Cardiac Disorders

Curator: Larry H Bernstein, MD, FACP


Reversal of Cardiac mitochondrial dysfunction

Curator: Larry H Bernstein, MD, FACP


Advanced Topics in Sepsis and the Cardiovascular System  at its End Stage

Author: Larry H Bernstein, MD, FCAP


Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis

Curator: Larry H Bernstein, MD, FACP


Ubiquitin-Proteosome pathway, Autophagy, the Mitochondrion, Proteolysis and Cell Apoptosis: Part III

Curator: Larry H Bernstein, MD, FCAP



Nitric Oxide, Platelets, Endothelium and Hemostasis (Coagulation Part II)

Curator: Larry H. Bernstein, MD, FCAP 


Mitochondrial Damage and Repair under Oxidative Stress

Curator: Larry H Bernstein, MD, FCAP


Mitochondria: Origin from oxygen free environment, role in aerobic glycolysis, metabolic adaptation

Reporter and Curator: Larry H Bernstein, MD, FACP



Nitric Oxide has a Ubiquitous Role in the Regulation of Glycolysis – with a Concomitant Influence on Mitochondrial Function

Reporter, Editor, and Topic Co-Leader: Larry H. Bernstein, MD, FCAP


Mitochondria and Cancer: An overview of mechanisms

Author and Curator: Ritu Saxena, Ph.D.


Mitochondria: More than just the “powerhouse of the cell”

Author and Curator: Ritu Saxena, Ph.D.


Overview of Posttranslational Modification (PTM)

Curator: Larry H. Bernstein, MD, FCAP


Ubiquitin Pathway Involved in Neurodegenerative Diseases

Author and curator: Larry H Bernstein, MD,  FCAP


Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?

Author: Larry H. Bernstein, MD, FCAP 


New Insights on Nitric Oxide donors – Part IV

Curator and Author: Larry H. Bernstein, MD, FCAP


Perspectives on Nitric Oxide in Disease Mechanisms [Kindle Edition]

Margaret Baker PhD (Author), Tilda Barliya PhD (Author), Anamika Sarkar PhD (Author), Ritu Saxena PhD (Author), Stephen J. Williams PhD (Author), Larry Bernstein MD FCAP (Editor), Aviva Lev-Ari PhD RN (Editor), Aviral Vatsa PhD (Editor)




Nitric oxide and its role in vascular biology

Signal transmission by a gas that is produced by one cell, penetrates through membranes and regulates the function of another cell represents an entirely new principle for signaling in biological systems.   All compounds that inhibit endothelium-derived relaxation-factor (EDRF) have one property in common, redox activity, which accounts for their inhibitory action on EDRF. One exception is hemoglobin, which inactivates EDRF by binding to it. Furchgott, Ignarro and Murad received the Nobel Prize in Physiology and Medicine for discovery of EDRF in 1998 and demonstrating that it might be nitric oxide (NO) based on a study of the transient relaxations of endothelium-denuded rings of rabbit aorta.  These investigators working independently demonstrated that NO is indeed produced by mammalian cells and that NO has specific biological roles in the human body. These studies highlighted the role of NO in cardiovascular, nervous and immune systems. In cardiovascular system NO was shown to cause relaxation of vascular smooth muscle cells causing vasodilatation, in nervous system NO acts as a signaling molecule and in immune system it is used against pathogens by the phagocytosis cells. These pioneering studies opened the path of investigation of role of NO in biology.

NO modulates vascular tone, fibrinolysis, blood pressure and proliferation of vascular smooth muscles. In cardiovascular system disruption of NO pathways or alterations in NO production can result in preponderance to hypertension, hypercholesterolemia, diabetes mellitus, atherosclerosis and thrombosis. The three enzyme isoforms of NO synthase family are responsible for generating NO in different tissues under various circumstances.

Reduction in NO production is implicated as one of the initial factors in initiating endothelial dysfunction. This reduction could be due to

  • reduction in eNOS production
  • reduction in eNOS enzymatic activity
  • reduced bioavailability of NO

Nitric oxide is one of the smallest molecules involved in physiological functions in the body. It is seeks formation of chemical bonds with its targets.  Nitric oxide can exert its effects principally by two ways:

  • Direct
  • Indirect

Direct actions, as the name suggests, result from direct chemical interaction of NO with its targets e.g. with metal complexes, radical species. These actions occur at relatively low NO concentrations (<200 nM)

Indirect actions result from the effects of reactive nitrogen species (RNS) such as NO2 and N2O3. These reactive species are formed by the interaction of NO with superoxide or molecular oxygen. RNS are generally formed at relatively high NO concentrations (>400 nM)

Although it can be tempting for scientists to believe that RNS will always have deleterious effects and NO will have anabolic effects, this is not entirely true as certain RNS mediated actions mediate important signalling steps e.g. thiol oxidation and nitrosation of proteins mediate cell proliferation and survival, and apoptosis respectively.

  • Cells subjected to NO concentration between 10-30 nM were associated with cGMP dependent phosphorylation of ERK
  • Cells subjected to NO concentration between 30-60 nM were associated with Akt phosphorylation
  • Concentration nearing 100 nM resulted in stabilisation of hypoxia inducible factor-1
  • At nearly 400 nM NO, p53 can be modulated
  • >1μM NO, it nhibits mitochondrial respiration


Nitric oxide signaling, oxidative stress,  mitochondria, cell damage

Recent data suggests that other NO containing compounds such as S- or N-nitrosoproteins and iron-nitrosyl complexes can be reduced back to produce NO. These NO containing compounds can serve as storage and can reach distant tissues via blood circulation, remote from their place of origin. Hence NO can have both paracrine and ‘endocrine’ effects.

Intracellularly the oxidants present in the cytosol determine the amount of bioacitivity that NO performs. NO can travel roughly 100 microns from NOS enzymes where it is produced.

NO itself in low concentrations have protective action on mitochondrial signaling of cell death.

The aerobic cell was an advance in evolutionary development, but despite the energetic advantage of using oxygen, the associated toxicity of oxygen abundance required adaptive changes.

Oxidation-reduction reactions that are necessary for catabolic and synthetic reactions, can cumulatively damage the organism associated with cancer, cardiovascular disease, neurodegerative disease, and inflammatory overload.  The normal balance between production of pro-oxidant species and destruction by the antioxidant defenses is upset in favor of overproduction of the toxic species, which leads to oxidative stress and disease.

We reviewed the complex interactions and underlying regulatory balances/imbalances between the mechanism of vasorelaxation and vasoconstriction of vascular endothelium by way of nitric oxide (NO), prostacyclin, in response to oxidative stress and intimal injury.

Nitric oxide has a ubiquitous role in the regulation of glycolysis with a concomitant influence on mitochondrial function. The influence on mitochondrial function that is active in endothelium, platelets, vascular smooth muscle and neural cells and the resulting balance has a role in chronic inflammation, asthma, hypertension, sepsis and cancer.

Potential cytotoxic mediators of endothelial cell (EC) apoptosis include increased formation of reactive oxygen and nitrogen species (ROSRNS) during the atherosclerotic process. Nitric oxide (NO) has a biphasic action on oxidative cell killing with low concentrations protecting against cell death, whereas higher concentrations are cytotoxic.

ROS induces mitochondrial DNA damage in ECs, and this damage is accompanied by a decrease in mitochondrial RNA (mtRNA) transcripts, mitochondrial protein synthesis, and cellular ATP levels.

NO and circulatory diseases

Blood vessels arise from endothelial precursors that are thin, flat cells lining the inside of blood vessels forming a monolayer throughout the circulatory system. ECs are defined by specific cell surface markers that characterize their phenotype.

Scientists at the University of Helsinki, Finland, wanted to find out if there exists a rare vascular endothelial stem cell (VESC) population that is capable of producing very high numbers of endothelial daughter cells, and can lead to neovascular growth in adults.

VESCs discovered that reside at the blood vessel wall endothelium are a small population of CD117+ ECs capable of self-renewal.  These cells are capable of undergoing clonal expansion unlike the surrounding ECs that bear limited proliferating potential. A single VESC cell isolated from the endothelial population was able to generate functional blood vessels.

Among many important roles of Nitric oxide (NO), one of the key actions is to act as a vasodilator and maintain cardiovascular health. Induction of NO is regulated by signals in tissue as well as endothelium.

Chen et. al. (Med. Biol. Eng. Comp., 2011) developed a 3-D model consisting of two branched arterioles and nine capillaries surrounding the vessels. Their model not only takes into account of the 3-D volume, but also branching effects on blood flow.

The model indicates that wall shear stress changes depending upon the distribution of RBC in the microcirculations of blood vessels, lead to differential production of NO along the vascular network.

Endothelial dysfunction, the hallmark of which is reduced activity of endothelial cell derived nitric oxide (NO), is a key factor in developing atherosclerosis and cardiovascular disease. Vascular endothelial cells play a pivotal role in modulation of leukocyte and platelet adherence, thrombogenicity, anticoagulation, and vessel wall contraction and relaxation, so that endothelial dysfunction has become almost a synonym for vascular disease. A single layer of endothelial cells is the only constituent of capillaries, which differ from other vessels, which contain smooth muscle cells and adventitia. Capillaries directly mediate nutritional supply as well as gas exchange within all organs. The failure of the microcirculation leads to tissue apoptosis/necrosis.

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