Healthcare analytics, AI solutions for biological big data, providing an AI platform for the biotech, life sciences, medical and pharmaceutical industries, as well as for related technological approaches, i.e., curation and text analysis with machine learning and other activities related to AI applications to these industries.
Progress in the Design, Testing, and Approval of Immuno-therapeutic Reagents: Target the Most Promising Cancer Antigens – NCI Pilot Project for the Acceleration of Translational Research
The purpose of the National Cancer Institute pilot project to prioritize cancer antigens was to develop a well-vetted, priority-ranked list of cancer vaccine target antigens based on predefined and preweighted objective criteria. An additional aim was for the National Cancer Institute to test a new approach for prioritizing translational research opportunities based on an analytic hierarchy process for dealing with complex decisions. Antigen prioritization involved developing a list of “ideal” cancer antigen criteria/characteristics, assigning relative weights to those criteria using pairwise comparisons, selecting 75 representative antigens for comparison and ranking, assembling information on the predefined criteria for the selected antigens, and ranking the antigens based on the predefined, preweighted criteria. Using the pairwise approach, the result of criteria weighting, in descending order, was as follows: (a) therapeutic function, (b) immunogenicity, (c) role of the antigen in oncogenicity, (d) specificity, (e) expression level and percent of antigen-positive cells, (f) stem cell expression, (g) number of patients with antigen-positive cancers, (h) number of antigenic epitopes, and (i) cellular location of antigen expression. None of the 75 antigens had all of the characteristics of the ideal cancer antigen. However, 46 were immunogenic in clinical trials and 20 of them had suggestive clinical efficacy in the “therapeutic function” category. These findings reflect the current status of the cancer vaccine field, highlight the possibility that additional organized efforts and funding would accelerate the development of therapeutically effective cancer vaccines, and accentuate the need for prioritization.
Gene Editing with CRISPR gets Crisper, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair
Gene Editing with CRISPR gets Crisper
Curators: Larry H. Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN
CRISPR Moves from Butchery to Surgery
More Genomes Are Going Under the CRISPR Knife, So Surgical Standards Are Rising
The Dharmacon subsidary of GE Healthcare provides the Edit-R Lentiviral Gene Engineering platform. It is based on the natural S. pyrogenes system, but unlike that system, which uses a single guide RNA (sgRNA), the platform uses two component RNAs, a gene-specific CRISPR RNA (crRNA) and a universal trans-activating crRNA (tracrRNA). Once hybridized to the universal tracrRNA (blue), the crRNA (green) directs the Cas9 nuclease to a specific genomic region to induce a double- strand break.
Scientists recently convened at the CRISPR Precision Gene Editing Congress, held in Boston, to discuss the new technology. As with any new technique, scientists have discovered that CRISPR comes with its own set of challenges, and the Congress focused its discussion around improving specificity, efficiency, and delivery.
In the naturally occurring system, CRISPR-Cas9 works like a self-vaccination in the bacterial immune system by targeting and cleaving viral DNA sequences stored from previous encounters with invading phages. The endogenous system uses two RNA elements, CRISPR RNA (crRNA) and trans-activating RNA (tracrRNA), which come together and guide the Cas9 nuclease to the target DNA.
Early publications that demonstrated CRISPR gene editing in mammalian cells combined the crRNA and tracrRNA sequences to form one long transcript called asingle-guide RNA (sgRNA). However, an alternative approach is being explored by scientists at the Dharmacon subsidiary of GE Healthcare. These scientists have a system that mimics the endogenous system through a synthetic two-component approach thatpreserves individual crRNA and tracrRNA. The tracrRNA is universal to any gene target or species; the crRNA contains the information needed to target the gene of interest.
Predesigned Guide RNAs
In contrast to sgRNAs, which are generated through either in vitro transcription of a DNA template or a plasmid-based expression system, synthetic crRNA and tracrRNA eliminate the need for additional cloning and purification steps. The efficacy of guide RNA (gRNA), whether delivered as a sgRNA or individual crRNA and tracrRNA, depends not only on DNA binding, but also on the generation of an indel that will deliver the coup de grâce to gene function.
“Almost all of the gRNAs were able to create a break in genomic DNA,” said Louise Baskin, senior product manager at Dharmacon. “But there was a very wide range in efficiency and in creating functional protein knock-outs.”
To remove the guesswork from gRNA design, Dharmacon developed an algorithm to predict gene knockout efficiency using wet-lab data. They also incorporated specificity as a component of their algorithm, using a much more comprehensive alignment tool to predict potential off-target effects caused by mismatches and bulges often missed by other alignment tools. Customers can enter their target gene to access predesigned gRNAs as either two-component RNAs or lentiviral sgRNA vectors for multiple applications.
“We put time and effort into our algorithm to ensure that our guide RNAs are not only functional but also highly specific,” asserts Baskin. “As a result, customers don’t have to do any design work.”
MilliporeSigma’s CRISPR Epigenetic Activator is based on fusion of a nuclease-deficient Cas9 (dCas9) to the catalytic histone acetyltransferase (HAT) core domain of the human E1A-associated protein p300. This technology allows researchers to target specific DNA regions or gene sequences. Researchers can localize epigenetic changes to their target of interest and see the effects of those changes in gene expression.
Knockout experiments are a powerful tool for analyzing gene function. However, for researchers who want to introduce DNA into the genome, guide design, donor DNA selection, and Cas9 activity are paramount to successful DNA integration.MilliporeSigma offers two formats for donor DNA: double-stranded DNA (dsDNA) plasmids and single-stranded DNA (ssDNA) oligonucleotides. The most appropriate format depends on cell type and length of the donor DNA. “There are some cell types that have immune responses to dsDNA,” said Gregory Davis, Ph.D., R&D manager, MilliporeSigma.
The ssDNA format can save researchers time and money, but it has a limited carrying capacity of approximately 120 base pairs.In addition to selecting an appropriate donor DNA format, controlling where, how, and when the Cas9 enzyme cuts can affect gene-editing efficiency. Scientists are playing tug-of-war, trying to pull cells toward the preferred homology-directed repair (HDR) and away from the less favored nonhomologous end joining (NHEJ) repair mechanism.One method to achieve this modifies the Cas9 enzyme to generate a nickase that cuts only one DNA strand instead of creating a double-strand break. Accordingly, MilliporeSigma has created a Cas9 paired-nickase system that promotes HDR, while also limiting off-target effects and increasing the number of sequences available for site-dependent gene modifications, such as disease-associated single nucleotide polymorphisms (SNPs).“The best thing you can do is to cut as close to the SNP as possible,” advised Dr. Davis. “As you move the double-stranded break away from the site of mutation you get an exponential drop in the frequency of recombination.”
Ribonucleo-protein Complexes
Another strategy to improve gene-editing efficiency, developed by Thermo Fisher, involves combining purified Cas9 protein with gRNA to generate a stable ribonucleoprotein (RNP) complex. In contrast to plasmid- or mRNA-based formats, which require transcription and/or translation, the Cas9 RNP complex cuts DNA immediately after entering the cell. Rapid clearance of the complex from the cell helps to minimize off-target effects, and, unlike a viral vector, the transient complex does not introduce foreign DNA sequences into the genome.
To deliver their Cas9 RNP complex to cells, Thermo Fisher has developed a lipofectamine transfection reagent called CRISPRMAX. “We went back to the drawing board with our delivery, screened a bunch of components, and got a brand-new, fully optimized lipid nanoparticle formulation,” explained Jon Chesnut, Ph.D., the company’s senior director of synthetic biology R&D. “The formulation is specifically designed for delivering the RNP to cells more efficiently.”
Besides the reagent and the formulation, Thermo Fisher has also developed a range of gene-editing tools. For example, it has introduced the Neon® transfection system for delivering DNA, RNA, or protein into cells via electroporation. Dr. Chesnut emphasized the company’s focus on simplifying complex workflows by optimizing protocols and pairing everything with the appropriate up- and downstream reagents.
From Mammalian Cells to Microbes
One of the first sources of CRISPR technology was the Feng Zhang laboratory at the Broad Institute, which counted among its first licensees a company called GenScript. This company offers a gene-editing service called GenCRISPR™ to establish mammalian cell lines with CRISPR-derived gene knockouts.
“There are a lot of challenges with mammalian cells, and each cell line has its own set of issues,” said Laura Geuss, a marketing specialist at GenScript. “We try to offer a variety of packages that can help customers who have difficult-to-work-with cells.” These packages include both viral-based and transient transfection techniques.
However, the most distinctive service offered by GenScript is its microbial genome-editing service for bacteria (Escherichia coli) and yeast (Saccharomyces cerevisiae). The company’s strategy for gene editing in bacteria can enable seamless knockins, knockouts, or gene replacements by combining CRISPR with lambda red recombineering. Traditionally one of the most effective methods for gene editing in microbes, recombineering allows editing without restriction enzymes through in vivo homologous recombination mediated by a phage-based recombination system such as lambda red.
On its own, lambda red technology cannot target multiple genes, but when paired with CRISPR, it allows the editing of multiple genes with greater efficiency than is possible with CRISPR alone, as the lambda red proteins help repair double-strand breaks in E. coli. The ability to knockout different gene combinations makes Genscript’s microbial editing service particularly well suited for the optimization of metabolic pathways.
Pooled and Arrayed Library Strategies
Scientists are using CRISPR technology for applications such as metabolic engineering and drug development. Yet another application area benefitting from CRISPR technology is cancer research. Here, the use of pooled CRISPR libraries is becoming commonplace. Pooled CRISPR libraries can help detect mutations that affect drug resistance, and they can aid in patient stratification and clinical trial design.
Pooled screening uses proliferation or viability as a phenotype to assess how genetic alterations, resulting from the application of a pooled CRISPR library, affect cell growth and death in the presence of a therapeutic compound. The enrichment or depletion of different gRNA populations is quantified using deep sequencing to identify the genomic edits that result in changes to cell viability.
MilliporeSigma provides pooled CRISPR libraries ranging from the whole human genome to smaller custom pools for these gene-function experiments. For pharmaceutical and biotech companies, Horizon Discovery offers a pooled screening service, ResponderSCREEN, which provides a whole-genome pooled screen to identify genes that confer sensitivity or resistance to a compound. This service is comprehensive, taking clients from experimental design all the way through to suggestions for follow-up studies.
Horizon Discovery maintains a Research Biotech business unit that is focused on target discovery and enabling translational medicine in oncology. “Our internal backbone gives us the ability to provide expert advice demonstrated by results,” said Jon Moore, Ph.D., the company’s CSO.
In contrast to a pooled screen, where thousands of gRNA are combined in one tube, an arrayed screen applies one gRNA per well, removing the need for deep sequencing and broadening the options for different endpoint assays. To establish and distribute a whole-genome arrayed lentiviral CRISPR library, MilliporeSigma partnered with the Wellcome Trust Sanger Institute. “This is the first and only arrayed CRISPR library in the world,” declared Shawn Shafer, Ph.D., functional genomics market segment manager, MilliporeSigma. “We were really proud to partner with Sanger on this.”
Pooled and arrayed screens are powerful tools for studying gene function. The appropriate platform for an experiment, however, will be determined by the desired endpoint assay.
The QX200 Droplet Digital PCR System from Bio-Rad Laboratories can provide researchers with an absolute measure of target DNA molecules for EvaGreen or probe-based digital PCR applications. The system, which can provide rapid, low-cost, ultra-sensitive quantification of both NHEJ- and HDR-editing events, consists of two instruments, the QX200 Droplet Generator and the QX200 Droplet Reader, and their associated consumables.
Finally, one last challenge for CRISPR lies in the detection and quantification of changes made to the genome post-editing. Conventional methods for detecting these alterations include gel methods and next-generation sequencing. While gel methods lack sensitivity and scalability, next-generation sequencing is costly and requires intensive bioinformatics.
To address this gap, Bio-Rad Laboratories developed a set of assay strategies to enable sensitive and precise edit detection with its Droplet Digital PCR (ddPCR) technology. The platform is designed to enable absolute quantification of nucleic acids with high sensitivity, high precision, and short turnaround time through massive droplet partitioning of samples.
Using a validated assay, a typical ddPCR experiment takes about five to six hours to complete. The ddPCR platform enables detection of rare mutations, and publications have reported detection of precise edits at a frequency of <0.05%, and of NHEJ-derived indels at a frequency as low as 0.1%. In addition to quantifying precise edits, indels, and computationally predicted off-target mutations, ddPCR can also be used to characterize the consequences of edits at the RNA level.
According to a recently published Science paper, the laboratory of Charles A. Gersbach, Ph.D., at Duke University used ddPCR in a study of muscle function in a mouse model of Duchenne muscular dystrophy. Specifically, ddPCR was used to assess the efficiency of CRISPR-Cas9 in removing the mutated exon 23 from the dystrophin gene. (Exon 23 deletion by CRISPR-Cas9 resulted in expression of the modified dystrophin gene and significant enhancement of muscle force.)
Quantitative ddPCR showed that exon 23 was deleted in ~2% of all alleles from the whole-muscle lysate. Further ddPCR studies found that 59% of mRNA transcripts reflected the deletion.
“There’s an overarching idea that the genome-editing field is moving extremely quickly, and for good reason,” asserted Jennifer Berman, Ph.D., staff scientist, Bio-Rad Laboratories. “There’s a lot of exciting work to be done, but detection and quantification of edits can be a bottleneck for researchers.”
The gene-editing field is moving quickly, and new innovations are finding their way into the laboratory as researchers lay the foundation for precise, well-controlled gene editing with CRISPR.
Researchers utilized a systems biology approach to develop new methods to assess drug sensitivity in cells. [The Institute for Systems Biology]
Understanding how cells respond and proliferate in the presence of anticancer compounds has been the foundation of drug discovery ideology for decades. Now, a new study from scientists at Vanderbilt University casts significant suspicion on the primary method used to test compounds for anticancer activity in cells—instilling doubt on methods employed by the entire scientific enterprise and pharmaceutical industry to discover new cancer drugs.
“More than 90% of candidate cancer drugs fail in late-stage clinical trials, costing hundreds of millions of dollars,” explained co-senior author Vito Quaranta, M.D., director of the Quantitative Systems Biology Center at Vanderbilt. “The flawed in vitro drug discovery metric may not be the only responsible factor, but it may be worth pursuing an estimate of its impact.”
The Vanderbilt investigators have developed what they believe to be a new metric for evaluating a compound’s effect on cell proliferation—called the DIP (drug-induced proliferation) rate—that overcomes the flawed bias in the traditional method.
The findings from this study were published recently in Nature Methods in an article entitled “An Unbiased Metric of Antiproliferative Drug Effect In Vitro.”
For more than three decades, researchers have evaluated the ability of a compound to kill cells by adding the compound in vitro and counting how many cells are alive after 72 hours. Yet, proliferation assays that measure cell number at a single time point don’t take into account the bias introduced by exponential cell proliferation, even in the presence of the drug.
“Cells are not uniform, they all proliferate exponentially, but at different rates,” Dr. Quaranta noted. “At 72 hours, some cells will have doubled three times and others will not have doubled at all.”
Dr. Quaranta added that drugs don’t all behave the same way on every cell line—for example, a drug might have an immediate effect on one cell line and a delayed effect on another.
The research team decided to take a systems biology approach, a mixture of experimentation and mathematical modeling, to demonstrate the time-dependent bias in static proliferation assays and to develop the time-independent DIP rate metric.
“Systems biology is what really makes the difference here,” Dr. Quaranta remarked. “It’s about understanding cells—and life—as dynamic systems.”This new study is of particular importance in light of recent international efforts to generate data sets that include the responses of thousands of cell lines to hundreds of compounds. Using the
Cancer Cell Line Encyclopedia (CCLE) and
Genomics of Drug Sensitivity in Cancer (GDSC) databases
will allow drug discovery scientists to include drug response data along with genomic and proteomic data that detail each cell line’s molecular makeup.
“The idea is to look for statistical correlations—these particular cell lines with this particular makeup are sensitive to these types of compounds—to use these large databases as discovery tools for new therapeutic targets in cancer,” Dr. Quaranta stated. “If the metric by which you’ve evaluated the drug sensitivity of the cells is wrong, your statistical correlations are basically no good.”
The Vanderbilt team evaluated the responses from four different melanoma cell lines to the drug vemurafenib, currently used to treat melanoma, with the standard metric—used for the CCLE and GDSC databases—and with the DIP rate. In one cell line, they found a glaring disagreement between the two metrics.
“The static metric says that the cell line is very sensitive to vemurafenib. However, our analysis shows this is not the case,” said co-lead study author Leonard Harris, Ph.D., a systems biology postdoctoral fellow at Vanderbilt. “A brief period of drug sensitivity, quickly followed by rebound, fools the static metric, but not the DIP rate.”
Dr. Quaranta added that the findings “suggest we should expect melanoma tumors treated with this drug to come back, and that’s what has happened, puzzling investigators. DIP rate analyses may help solve this conundrum, leading to better treatment strategies.”
The researchers noted that using the DIP rate is possible because of advances in automation, robotics, microscopy, and image processing. Moreover, the DIP rate metric offers another advantage—it can reveal which drugs are truly cytotoxic (cell killing), rather than merely cytostatic (cell growth inhibiting). Although cytostatic drugs may initially have promising therapeutic effects, they may leave tumor cells alive that then have the potential to cause the cancer to recur.
The Vanderbilt team is currently in the process of identifying commercial entities that can further refine the software and make it widely available to the research community to inform drug discovery.
An unbiased metric of antiproliferative drug effect in vitro
In vitro cell proliferation assays are widely used in pharmacology, molecular biology, and drug discovery. Using theoretical modeling and experimentation, we show that current metrics of antiproliferative small molecule effect suffer from time-dependent bias, leading to inaccurate assessments of parameters such as drug potency and efficacy. We propose the drug-induced proliferation (DIP) rate, the slope of the line on a plot of cell population doublings versus time, as an alternative, time-independent metric.
Researchers develop a technique to direct chromosome recombination with CRISPR/Cas9, allowing high-resolution genetic mapping of phenotypic traits in yeast.
Researchers used CRISPR/Cas9 to make a targeted double-strand break (DSB) in one arm of a yeast chromosome labeled with a green fluorescent protein (GFP) gene. A within-cell mechanism called homologous repair (HR) mends the broken arm using its homolog, resulting in a recombined region from the site of the break to the chromosome tip. When this cell divides by mitosis, each daughter cell will contain a homozygous section in an outcome known as “loss of heterozygosity” (LOH). One of the daughter cells is detectable because, due to complete loss of the GFP gene, it will no longer be fluorescent.REPRINTED WITH PERMISSION FROM M.J. SADHU ET AL., SCIENCE
When mapping phenotypic traits to specific loci, scientists typically rely on the natural recombination of chromosomes during meiotic cell division in order to infer the positions of responsible genes. But recombination events vary with species and chromosome region, giving researchers little control over which areas of the genome are shuffled. Now, a team at the University of California, Los Angeles (UCLA), has found a way around these problems by using CRISPR/Cas9 to direct targeted recombination events during mitotic cell division in yeast. The team described its technique today (May 5) in Science.
“Current methods rely on events that happen naturally during meiosis,” explained study coauthor Leonid Kruglyak of UCLA. “Whatever rate those events occur at, you’re kind of stuck with. Our idea was that using CRISPR, we can generate those events at will, exactly where we want them, in large numbers, and in a way that’s easy for us to pull out the cells in which they happened.”
Generally, researchers use coinheritance of a trait of interest with specific genetic markers—whose positions are known—to figure out what part of the genome is responsible for a given phenotype. But the procedure often requires impractically large numbers of progeny or generations to observe the few cases in which coinheritance happens to be disrupted informatively. What’s more, the resolution of mapping is limited by the length of the smallest sequence shuffled by recombination—and that sequence could include several genes or gene variants.
“Once you get down to that minimal region, you’re done,” said Kruglyak. “You need to switch to other methods to test every gene and every variant in that region, and that can be anywhere from challenging to impossible.”
But programmable, DNA-cutting champion CRISPR/Cas9 offered an alternative. During mitotic—rather than meiotic—cell division, rare, double-strand breaks in one arm of a chromosome preparing to split are sometimes repaired by a mechanism called homologous recombination. This mechanism uses the other chromosome in the homologous pair to replace the sequence from the break down to the end of the broken arm. Normally, such mitotic recombination happens so rarely as to be impractical for mapping purposes. With CRISPR/Cas9, however, the researchers found that they could direct double-strand breaks to any locus along a chromosome of interest (provided it was heterozygous—to ensure that only one of the chromosomes would be cut), thus controlling the sites of recombination.
Combining this technique with a signal of recombination success, such as a green fluorescent protein (GFP) gene at the tip of one chromosome in the pair, allowed the researchers to pick out cells in which recombination had occurred: if the technique failed, both daughter cells produced by mitotic division would be heterozygous, with one copy of the signal gene each. But if it succeeded, one cell would end up with two copies, and the other cell with none—an outcome called loss of heterozygosity.
“If we get loss of heterozygosity . . . half the cells derived after that loss of heterozygosity event won’t have GFP anymore,” study coauthor Meru Sadhu of UCLA explained. “We search for these cells that don’t have GFP out of the general population of cells.” If these non-fluorescent cells with loss of heterozygosity have the same phenotype as the parent for a trait of interest, then CRISPR/Cas9-targeted recombination missed the responsible gene. If the phenotype is affected, however, then the trait must be linked to a locus in the recombined, now-homozygous region, somewhere between the cut site and the GFP gene.
By systematically making cuts using CRISPR/Cas9 along chromosomes in a hybrid, diploid strain ofSaccharomyces cerevisiae yeast, picking out non-fluorescent cells, and then observing the phenotype, the UCLA team demonstrated that it could rapidly identify the phenotypic contribution of specific gene variants. “We can simply walk along the chromosome and at every [variant] position we can ask, does it matter for the trait we’re studying?” explained Kruglyak.
For example, the team showed that manganese sensitivity—a well-defined phenotypic trait in lab yeast—could be pinpointed using this method to a single nucleotide polymorphism (SNP) in a gene encoding the Pmr1 protein (a manganese transporter).
Jason Moffat, a molecular geneticist at the University of Toronto who was not involved in the work, toldThe Scientist that researchers had “dreamed about” exploiting these sorts of mechanisms for mapping purposes, but without CRISPR, such techniques were previously out of reach. Until now, “it hasn’t been so easy to actually make double-stranded breaks on one copy of a pair of chromosomes, and then follow loss of heterozygosity in mitosis,” he said, adding that he hopes to see the approach translated into human cell lines.
Applying the technique beyond yeast will be important, agreed cell and developmental biologist Ethan Bier of the University of California, San Diego, because chromosomal repair varies among organisms. “In yeast, they absolutely demonstrate the power of [this method],” he said. “We’ll just have to see how the technology develops in other systems that are going to be far less suited to the technology than yeast. . . . I would like to see it implemented in another system to show that they can get the same oomph out of it in, say, mammalian somatic cells.”
Kruglyak told The Scientist that work in higher organisms, though planned, is still in early stages; currently, his team is working to apply the technique to map loci responsible for trait differences between—rather than within—yeast species.
“We have a much poorer understanding of the differences across species,” Sadhu explained. “Except for a few specific examples, we’re pretty much in the dark there.”
Linkage and association studies have mapped thousands of genomic regions that contribute to phenotypic variation, but narrowing these regions to the underlying causal genes and variants has proven much more challenging. Resolution of genetic mapping is limited by the recombination rate. We developed a method that uses CRISPR to build mapping panels with targeted recombination events. We tested the method by generating a panel with recombination events spaced along a yeast chromosome arm, mapping trait variation, and then targeting a high density of recombination events to the region of interest. Using this approach, we fine-mapped manganese sensitivity to a single polymorphism in the transporter Pmr1. Targeting recombination events to regions of interest allows us to rapidly and systematically identify causal variants underlying trait differences.
Thank you, David, for the kind words and comments. We agree that the most immediate applications of the CRISPR-based recombination mapping will be in unicellular organisms and cell culture. We also think the method holds a lot of promise for research in multicellular organisms, although we did not mean to imply that it “will be an efficient mapping method for all multicellular organisms”. Every organism will have its own set of constraints as well as experimental tools that will be relevant when adapting a new technique. To best help experts working on these organisms, here are our thoughts on your questions.
You asked about mutagenesis during recombination. We Sanger sequenced 72 of our LOH lines at the recombination site and did not observe any mutations, as described in the supplementary materials. We expect the absence of mutagenesis is because we targeted heterozygous sites where the untargeted allele did not have a usable PAM site; thus, following LOH, the targeted site is no longer present and cutting stops. In your experiments you targeted sites that were homozygous; thus, following recombination, the CRISPR target site persisted, and continued cutting ultimately led to repair by NHEJ and mutagenesis.
As to the more general question of the optimal mapping strategies in different organisms, they will depend on the ease of generating and screening for editing events, the cost and logistics of maintaining and typing many lines, and generation time, among other factors. It sounds like in Drosophila today, your related approach of generating markers with CRISPR, and then enriching for natural recombination events that separate them, is preferable. In yeast, we’ve found the opposite to be the case. As you note, even in Drosophila, our approach may be preferable for regions with low or highly non-uniform recombination rates.
Finally, mapping in sterile interspecies hybrids should be straightforward for unicellular hybrids (of which there are many examples) and for cells cultured from hybrid animals or plants. For studies in hybrid multicellular organisms, we agree that driving mitotic recombination in the early embryo may be the most promising approach. Chimeric individuals with mitotic clones will be sufficient for many traits. Depending on the system, it may in fact be possible to generate diploid individuals with uniform LOH genotype, but this is certainly beyond the scope of our paper. The calculation of the number of lines assumes that the mapping is done in a single step; as you note in your earlier comment, mapping sequentially can reduce this number dramatically.
This is a lovely method and should find wide applicability in many settings, especially for microorganisms and cell lines. However, it is not clear that this approach will be, as implied by the discussion, an efficient mapping method for all multicellular organisms. I have performed similar experiments in Drosophila, focused on meiotic recombination, on a much smaller scale, and found that CRISPR-Cas9 can indeed generate targeted recombination at gRNA target sites. In every case I tested, I found that the recombination event was associated with a deletion at the gRNA site, which is probably unimportant for most mapping efforts, but may be a concern in some specific cases, for example for clinical applications. It would be interesting to know how often mutations occurred at the targeted gRNA site in this study.
The wider issue, however, is whether CRISPR-mediated recombination will be more efficient than other methods of mapping. After careful consideration of all the costs and the time involved in each of the steps for Drosophila, we have decided that targeted meiotic recombination using flanking visible markers will be, in most cases, considerably more efficient than CRISPR-mediated recombination. This is mainly due to the large expense of injecting embryos and the extensive effort and time required to screen injected animals for appropriate events. It is both cheaper and faster to generate markers (with CRISPR) and then perform a large meiotic recombination mapping experiment than it would be to generate the lines required for CRISPR-mediated recombination mapping. It is possible to dramatically reduce costs by, for example, mapping sequentially at finer resolution. But this approach would require much more time than marker-assisted mapping. If someone develops a rapid and cheap method of reliably introducing DNA into Drosophila embryos, then this calculus might change.
However, it is possible to imagine situations where CRISPR-mediated mapping would be preferable, even for Drosophila. For example, some genomic regions display extremely low or highly non-uniform recombination rates. It is possible that CRISPR-mediated mapping could provide a reasonable approach to fine mapping genes in these regions.
The authors also propose the exciting possibility that CRISPR-mediated loss of heterozygosity could be used to map traits in sterile species hybrids. It is not entirely obvious to me how this experiment would proceed and I hope the authors can illuminate me. If we imagine driving a recombination event in the early embryo (with maternal Cas9 from one parent and gRNA from a second parent), then at best we would end up with chimeric individuals carrying mitotic clones. I don’t think one could generate diploid animals where all cells carried the same loss of heterozygosity event. Even if we could, this experiment would require construction of a substantial number of stable transgenic lines expressing gRNAs. Mapping an ~20Mbp chromosome arm to ~10kb would require on the order of two-thousand transgenic lines. Not an undertaking to be taken lightly. It is already possible to perform similar tests (hemizygosity tests) using D. melanogaster deficiency lines in crosses with D. simulans, so perhaps CRISPR-mediated LOH could complement these deficiency screens for fine mapping efforts. But, at the moment, it is not clear to me how to do the experiment.
Somatic Mutation Theory – Why it’s Wrong for Most Cancers, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)
Somatic Mutation Theory – Why it’s Wrong for Most Cancers
Reporter: Aviva Lev-Ari, PhD, RN
Somatic Mutation Theory – Why it’s Wrong for Most Cancers.
Hysteron proteron reverses both temporal and logical order and this syllogism occurs in carcinogenesis and the somatic mutation theory (SMT): the first (somatic mutation) occurs only after the second (onset of cancer) and, therefore, observed somatic mutations in most cancers appear well after the early cues of carcinogenesis are in place. It is no accident that mutations are increasingly being questioned as the causal event in the origin of the vast majority of cancers as clinical data show little support for this theory when compared against the metrics of patient outcomes. Ever since the discovery of the double helical structure of DNA, virtually all chronic diseases came to be viewed as causally linked to one degree or another to mutations, even though we now know that genes are not simply blueprints, but rather an assemblage of alphabets that can, under non-genetic influences, be used to assemble a business letter or a work of Shakespearean literature. A minority of all cancers is indeed caused by mutations but the SMT has been applied to all cancers, and even to chemical carcinogenesis, in the absence of hard evidence of causality. Herein, we review the 100 year story of SMT and aspects that show why genes are not just blueprints, how radiation and mutation are associated in a more nuanced view, the proposed risk of cancer and bad luck, and the in vitro and in vivo evidence for a new cancer paradigm. This paradigm is scientifically applicable for the majority of non-heritable cancers and consists of a six-step sequence for the origin of cancer. This new cancer paradigm proclaims that somatic mutations are epiphenomena or later events occurring after carcinogenesis is already underway. This serves not just as a plausible alternative to SMT and explains the origin of the majority of cancers, but also provides opportunities for early interventions and prevention of the onset of cancer as a disease.
Conclusions
The incorrect interpretation of data can sometimes appear to be the more parsimonious explanation especially when it has acquired the mantle of a paradigm, as in the case of the SMT. Summa Cancerologica is not hypothetical or ontological. Its syllogism of carcinogenesis needs the consideration of all reasonable perspectives such as whether somatic mutations are later events or epiphenomena occurring at the end of the sequence of events in carcinogenesis. This mutatio praemissarum leads to a reflection of reasoned judgments of correct findings in cancer (mutations within tumors) together with clinical observations (relevance of such mutations to cancer therapy). An overemphasis of the SMT as the sole reason of the origin of carcinogenesis elevated it to the status of a dogma which downplays significant findings of mutations and genetics in different fields of nature, biology and science. However, there is hope that hereditary cancers can be treated in the near future as new technologies make it possible to manipulate proteins packaging DNA to turn on specific gene promoters and enhancers [164]. If this were applicable to the mass of non-hereditary cancers this approach would still be only symptomatic as the genesis of non-hereditary cancers is not caused by somatic mutations though somatic mutations occur within tumors. Focusing on the tumor cell without its origin including the microenvironment won’t be enough [165]. The reasoning on the origin of carcinogenesis, including different step-wise sequences, may help unmask mechanisms of the transition of a normal into a cancer cell (cancer genesis) as well as its different primary pathogenic stimulus, which can serve to prevent or retard cancers instead of concentrating on symptomatic strategies or for a cure for all cancers. It is scientifically valid based on in vitro and in vivo genetic findings that carcinogenesis consists of a six-step multi sequence process [17, 18]. This serves not just as a plausible alternative to the SMT to explain the origin of the majority of cancers, but could also suggest early interventions and thereby prevent the onset of cancer as a disease.
Generalized gene regulation mechanisms of miRNAs. [NIH]
Increasingly, cancer researchers are discovering novel biological pathways that regulate the expression of various genes that are often strongly associated with tumorigenesis. These new molecular mechanisms represent important potential therapeutic targets for aggressive and difficult-to-treat cancers. In particular, microRNAs (miRNAs)—small, noncoding genetic material that regulates gene expression—have steadily become implicated in the progression of some cancers.
Now, researchers at the University of Cincinnati (UC) have found a particular signaling route for a microRNA, miR-22, that they believe leads to targets for acute myeloid leukemia (AML), the most common type of fast-growing cancer of the blood and bone marrow.
The findings from this study were published recently in Nature Communications in an article entitled “miR-22 Has a Potent Anti-Tumour Role with Therapeutic Potential in Acute Myeloid Leukaemia.”
Structure of mi-22 miccroRNA. [Ppgardne at el., via Wikimedia Commons]
Increasingly, cancer researchers are discovering novel biological pathways that regulate the expression of various genes that are often strongly associated with tumorigenesis. These new molecular mechanisms represent important potential therapeutic targets for aggressive and difficult-to-treat cancers. In particular, microRNAs (miRNAs)—small, noncoding genetic material that regulates gene expression—have steadily become implicated in the progression of some cancers.
Now, researchers at the University of Cincinnati (UC) have found a particular signaling route for a microRNA, miR-22, that they believe leads to targets for acute myeloid leukemia (AML), the most common type of fast-growing cancer of the blood and bone marrow.
The findings from this study were published recently in Nature Communications in an article entitled “miR-22 Has a Potent Anti-Tumour Role with Therapeutic Potential in Acute Myeloid Leukaemia.”
“MicroRNAs make up a class of small, noncoding internal RNAs that control a gene’s job, or expression, by directing their target messaging RNAs, or mRNAs, to inhibit or stop. Cellular organisms use mRNA to convey genetic information,” explained senior study author Jianjun Chen, Ph.D., associate professor in the department of cancer biology at the UC College of Medicine. “Previous research has shown that microRNA miR-22 is linked to breast cancer and other blood disorders which sometimes turn into AML, but we found in this study that it could be an essential anti-tumor gatekeeper in AML when it is down-regulated, meaning its function is minimized.”
AML—most common type of acute leukemia—arises when the bone marrow begins to make blasts, cells that have not yet completely matured. These blast cells typically develop into white blood cells; however, in AML the cells do not develop and are unable to aid in warding off infections. In the current study, the UC team describes how altering the expression of miR-22 affected AML pathogenesis.
“When we forced miR-22 expression, we saw difficulty in leukemia cells developing, growing, and thriving. miR-22 targets multiple cancer-causing genes (CRTC1, FLT3, and MYCBP) and blocks certain pathways (CREB and MYC),” Dr. Chen noted. “The downregulation, or decreased output, of miR-22 in AML, is caused by the loss of the number of DNA being copied and/or stopping their expression through a pathway called TET1/GFI1/EZH2/SIN3A. Also, nanoparticles carrying miR-22 DNA oligonucleotides (short nucleic acid molecules) prevented leukemia advancement.”
The investigators conducted the study using bone marrow transplant samples and animal models. The researchers showed that the ten-eleven translocation proteins (TET1/2/3) in mammals helped to control genetic expression in normal developmental processes. This was in sharp contrast to mutations that cause function loss and tumor-slowing with TET2, which has been observed previously in blood and stem cell cancers.
“We recently reported that TET1 plays an essential cancer generating role in certain AML where it activates expression of homeobox genes, which are a large family of similar genes that direct the formation of many body structures during early embryonic development,” remarked Dr. Chen. “However, it is unknown whether TET1 can also function as a repressor for cellular function in cancer, and its role in microRNA expression has rarely been studied.”
Dr. Chen added that these findings are important in targeting a cancer that is both common and fatal, stating that “the majority of patients with ALM usually don’t survive longer than 5 years, even with chemotherapy, which is why the development of new effective therapies based on the underlying mechanisms of the disease is so important.”
“Our study uncovers a previously unappreciated signaling pathway (TET1/GFI1/EZH2/SIN3A/miR-22/CREB-MYC) and provides new insights into genetic mechanisms causing and progressing AML and also highlights the clinical potential of miR-22-based AML therapy. More research on this pathway and ways to target it are necessary,” Dr. Chen concluded.
miR-22 has a potent anti-tumour role with therapeutic potential in acute myeloid leukaemia
MicroRNAs are subject to precise regulation and have key roles in tumorigenesis. In contrast to the oncogenic role of miR-22 reported in myelodysplastic syndrome (MDS) and breast cancer, here we show that miR-22 is an essential anti-tumour gatekeeper in de novo acute myeloid leukaemia (AML) where it is significantly downregulated. Forced expression of miR-22 significantly suppresses leukaemic cell viability and growth in vitro, and substantially inhibits leukaemia development and maintenance in vivo. Mechanistically, miR-22 targets multiple oncogenes, including CRTC1, FLT3 and MYCBP, and thus represses the CREB and MYC pathways. The downregulation of miR-22 in AML is caused by TET1/GFI1/EZH2/SIN3A-mediated epigenetic repression and/or DNA copy-number loss. Furthermore, nanoparticles carrying miR-22 oligos significantly inhibit leukaemia progression in vivo. Together, our study uncovers a TET1/GFI1/EZH2/SIN3A/miR-22/CREB-MYC signalling circuit and thereby provides insights into epigenetic/genetic mechanisms underlying the pathogenesis of AML, and also highlights the clinical potential of miR-22-based AML therapy.
As one of the most common and fatal forms of hematopoietic malignancies, acute myeloid leukaemia (AML) is frequently associated with diverse chromosome translocations (for example t(11q23)/MLL-rearrangements, t(15;17)/PML-RARA and t(8;21)/AML1-ETO) and molecular abnormalities (for example, internal tandem duplications of FLT3 (FLT3-ITD) and mutations in nucleophosmin (NPM1c+))1. Despite intensive chemotherapies, the majority of patients with AML fail to survive longer than 5 years2, 3. Thus, development of effective therapeutic strategies based on a better understanding of the molecular mechanisms underlying the pathogenesis of AML is urgently needed.
MicroRNAs (miRNAs) are a class of small, non-coding RNAs that post-transcriptionally regulate gene expression4. Individual miRNAs may play distinct roles in cancers originating from different tissues or even from different lineages of hematopoietic cells4. It is unclear whether a single miRNA can play distinct roles between malignancies originating from the same hematopoietic lineage, such as de novo AML and myelodysplastic syndrome (MDS). Although around 30% of MDS cases transform to AML, the genetic and epigenetic landscapes of MDS or MDS-derived AML are largely different from those of de novo AML5, 6. MDS and MDS-derived AML are more responsive to hypomethylating agents than de novo AML7. The molecular mechanisms underlying the distinct pathogenesis and drug response between MDS (or MDS-derived AML) and de novo AML remain unclear.
The ten-eleven translocation (Tet1/2/3) proteins play critical transcriptional regulatory roles in normal developmental processes as activators or repressors8, 9, 10. In contrast to the frequent loss-of-function mutations and tumour-suppressor role of TET2 observed in hematopoietic malignancies11, 12, 13, we recently reported that TET1 plays an essential oncogenic role in MLL-rearranged AML where it activates expression of homeobox genes14. However, it is unknown whether TET1 can also function as a transcriptional repressor in cancer. Moreover, Tet1-mediated regulation of miRNA expression has rarely been studied10.
In the present study, we demonstrate that miR-22, an oncogenic miRNA reported in breast cancer and MDS15, 16, is significantly downregulated in most cases of de novo AML due to TET1/GFI1/EZH2/SIN3A-mediated epigenetic repression and/or DNA copy-number loss. miR-22 functions as an essential anti-tumour gatekeeper in various AML and holds great therapeutic potential to treat AML.
The downregulation of miR-22 in de novo AML
Through Exiqon miRNA array profiling, we previously identified a set of miRNAs, such as miR-150, miR-148a, miR-29a, miR-29b, miR-184, miR-342, miR-423 and miR-22, which are significantly downregulated in AML compared with normal controls17. Here we showed that among all the above miRNAs, miR-150 and especially miR-22 exhibited the most significant and consistent inhibitory effect on MLL-AF9-induced cell immortalization in colony-forming/replating assays (CFA) (Supplementary Fig. 1a). In contrast to the reported upregulation of miR-22 in MDS16, our original microarray data17 (Fig. 1a,b) and new quantitative PCR-independent validation data (Supplementary Fig. 1b) demonstrated a significant and global downregulation of miR-22 in de novo AML relative to normal controls. Notably, miR-22 is significantly downregulated in AML samples (P<0.05) compared with all three sub-populations of normal control cells, that is, normal CD34+ hematopoietic stem/progenitor cells (HSPCs), CD33+ myeloid progenitor cells, or mononuclear cells (MNCs) (Fig. 1a). Expression of miR-22 is significantly downregulated in all or the majority of individual subsets of AML samples than in the normal CD33+ or CD34+ cell samples (Fig. 1b).
Figure 1: miR-22 inhibits AML cell transformation and leukemogenesis.
(a,b) Exiqon microRNA profiling assay showed that miR-22 is significantly (P<0.05) downregulated in the entire set of AML set (n=85) (a) or each individual subset (b), relative to normal controls. The expression data were log(2) transformed and mean-centred. Mean±s.e.m. values were shown. (c) Comparison of effects of in-house miR-22, miR-22_Song16 and miR-22 mutant (miR-22mut; see the mutation sequence at the top) on MLL-AF9-induced colony forming. CFAs were performed using mouse BM progenitor (Lin–) cells transduced with MSCV-neo+MSCV-PIG (Ctrl), MSCV-neo-MLL-AF9+MSCV-PIG (MLL-AF9), or MSCV-neo-MLL-AF9+MSCV-PIG-miR-22/miR-22_Song/miR-22mut. (d) Effects of miR-22 on the colony forming induced by multiple fusion genes. CFA was performed using wild-type BM progenitor cells co-transduced with MSCV-neo-MLL-AF9 (MA9), -MLL-AF10 (MA10), -PML-RARA (PR) or –AML1-ETO9a(AE9a)19, together with MSCV-PIG (Ctrl) or MSCV-PIG-miR-22 (+miR-22), as well as miR-22−/− BM progenitors co-transduced with individual fusion genes and MSCV-PIG. Colony counts (mean±s.d.) of the second round of plating are shown. *P<0.05; **P<0.01. (e,f) Effect of miR-22 on MLL-AF9-induced primary leukemogenesis. Kaplan–Meier curves are shown for six cohorts of transplanted mice including MSCVneo+MSCV-PIG (Ctrl; n=5), MSCVneo+MSCV-PIG-miR-22 (miR-22; n=5), MSCVneo-MLL-AF9+MSCV-PIG (MA9; n=8), MSCVneo-MLL-AF9+MSCV-PIG-miR-150 (MA9+miR-150, n=6), MSCVneo-MLL-AF9+MSCV-PIG-miR-22 (MA9+miR-22; n=10) and MSCVneo-MLL-AF9+MSCV-PIG-miR-22mutant (MA9+miR-22mut; n=5) (e); Wright–Giemsa stained PB and bone marrow (BM), and hematoxylin and eosin (H&E) stained spleen and liver of the primary BMT recipient mice at the end point are shown (f). (g) Effect of miR-22 on MLL-AF10-induced primary leukemogenesis. Kaplan–Meier curves are shown for two cohorts of transplanted mice including MSCVneo-MLL-AF10+MSCV-PIG (MA10; n=5) and MSCVneo-MLL-AF10+MSCV-PIG-miR-22 (MA10+miR-22; n=5). (h) miR-22 knockout promotes AE9a-induced leukemogenesis. Kaplan–Meier curves are shown for mice transplanted with wild-type or miR-22−/− BM progenitor cells transduced MSCV-PIG-AE9a (n=5 for each group). The P values were generated by t-test (a–d) or log-rank test (e,g,h).
To rule out the possibility that the inhibitory effect of miR-22 shown in Supplementary Fig. 1a was due to a non-specific effect of our miR-22 construct, we included the MSCV-PIG-miR-22 construct from Song et al.16 in a repeated CFA. Both miR-22 constructs dramatically inhibited MLL-AF9-induced colony formation (Fig. 1c). As the ‘seed’ sequences at the 5′ end of individual miRNAs are essential for the miRNA-target binding18, we also mutated the 6-bases ‘seed’ sequence of miR-22 and found that the miR-22 mutant did not inhibit colony formation anymore (Fig. 1c). In human AML cells, forced expression of miR-22, but not miR-22 mutant, significantly inhibited cell viability and growth/proliferation, while promoting apoptosis (Supplementary Fig. 1c,d).
Furthermore, as miR-22 is globally downregulated in all major types of AML (Fig. 1b), we also investigated the role of miR-22 in colony formation induced by other oncogenic fusion genes, including MLL-AF10/t(10;11), PML-RARA/t(15;17) and AML1-ETO9a/t(8;21) (ref. 19). As expected, forced expression of miR-22 significantly inhibited colony formation induced by all individual oncogenic fusions; conversely, miR-22 knockout20 significantly enhanced colony forming (Fig. 1d). These results suggest that miR-22 likely plays a broad anti-tumour role in AML.
In accordance with the potential anti-tumour function of miR-22 in AML, miR-22 was expressed at a significantly higher level (P<0.05) in human normal CD33+ myeloid progenitor cells than in more immature CD34+ HSPCs or MNC cells (a mixed population containing both primitive progenitors and committed cells) (Fig. 1a,b), implying that miR-22 is upregulated during normal myelopoiesis. Similarly, we showed that miR-22 was also expressed at a significantly higher level in mouse normal bone marrow (BM) myeloid (Gr-1+/Mac-1+) cells, relative to lineage negative (Lin−) progenitor cells, long-term hematopoietic stem cells (LT-HSCs), short-term HSCs (ST-HSCs), and committed progenitors (CPs) (Supplementary Fig. 1e), further suggesting that miR-22 is upregulated in normal myelopoiesis.
The anti-tumour effect of miR-22 in the pathogenesis of AML
Through bone marrow transplantation (BMT) assays, we showed that forced expression of miR-22 (but not miR-22 mutant) dramatically blocked MLL-AF9 (MA9)-mediated leukemogenesis in primary BMT recipient mice, with a more potent inhibitory effect than miR-150 (Fig. 1e;Supplementary Fig. 2a). All MA9+miR-22 mice exhibited normal morphologies in peripheral blood (PB), BM, spleen and liver tissues (Fig. 1f), with a substantially reduced c-Kit+ blast cell population in BM (Supplementary Fig. 2b). Forced expression of miR-22 also almost completely inhibited leukemogenesis induced by MLL-AF10 (Fig. 1g; Supplementary Fig. 2a). Conversely, miR-22 knockout significantly promoted AML1-ETO9a (AE9a)-induced AML (Fig. 1h). Thus, the repression of miR-22 is critical for the development of primary AML. Notably, forced expression of miR-22 inMLL-AF9 and MLL-AF10 leukaemia mouse models caused only a 2–3-fold increase in miR-22 expression level (Supplementary Fig. 2a), in a degree comparable to the difference in miR-22 expression levels between human AML samples and normal controls (Fig. 1a), suggesting that a 2–3-fold change in miR-22 expression level appears to be able to exert significant physiological or pathological effects.
To examine whether the maintenance of AML is also dependent on the repression of miR-22, we performed secondary BMT assays. Forced expression of miR-22 remarkably inhibited progression of MLL-AF9-, AE9a– or FLT3-ITD/NPM1c+-induced AML in secondary recipient mice (Fig. 2a–d), resulting in largely normal morphologies in PB, BM, spleen and liver tissues (Fig. 2b;Supplementary Fig. 2c). Collectively, our findings demonstrate that miR-22 is a pivotal anti-tumour gatekeeper in both development and maintenance of various AML.
Figure 2: Effect of miR-22 on the maintenance of AMLin vivo.
(a,b) Effect of miR-22 on the maintenance of MLL-AF9-induced AML in secondary BMT recipient mice. The secondary BMT recipients were transplanted with BM blast cells from the primary MLL-AF9 AML mice retrovirally transduced with MSCV-PIG+MSCVneo (MA9-AML+Ctrl; n=7) or MSCV-PIG+MSCVneo-miR-22 (MA9-AML+miR-22; n=10). Kaplan–Meier curves (a) and Wright–Giemsa or H&E-stained PB, BM, spleen and liver (b) of the secondary leukaemic mice are shown. (c,d) Effect of miR-22 on the maintenance/progression of AML1-ETO9a (AE9a)-induced AML (c) or FLT3-ITD/NPM1c+-induced AML (d) in secondary BMT recipient mice (n=5 for each group). Kaplan–Meier curves and P values (log-rank test) are shown.
Identification of critical target genes of miR-22 in AML
To identify potential targets of miR-22 in AML, we performed a series of data analysis. Analysis of In-house_81S (ref. 21) and TCGA_177S (ref. 22) data sets revealed a total of 999 genes exhibiting significant inverse correlations with miR-22 in expression. Of them, 137 genes, including 21 potential targets of miR-22 as predicted by TargetScan18 (Supplementary Table 1), were significantly upregulated in both human and mouse AML compared with normal controls as detected in two additional in-house data sets14, 23. Among the 21 potential targets, CRTC1, ETV6and FLT3 are known oncogenes24, 25, 26, 27, 28, 29. We then focused on these three genes, along with MYCBP that encodes the MYC-binding protein and is an experimentally validated target of miR-22 (ref. 30) although due to a technical issue it was not shown in the 21-gene list (Supplementary Table 1), for further studies.
As expected, all four genes were significantly downregulated in expression by ectopic expression of miR-22 in human MONOMAC-6/t(9;11) cells (Fig. 3a). The coincidence of downregulation of those genes and upregulation of miR-22 was also observed in mouse MLL-ENL-ERtm cells, a leukaemic cell line with an inducible MLL-ENL derivative31, when MLL-ENL was depleted by 4-hydroxy-tamoxifen (4-OHT) withdrawal (Fig. 3b; Supplementary Fig. 3a). While MLL-AF9 remarkably promoted expression of those four genes in mouse BM progenitor cells, co-expressed miR-22 reversed the upregulation (Fig. 3c). In leukaemia BM blast cells of mice with MLL-AF9-induced AML, the expression of Crtc1, Flt3 and Mycbp, but not Etv6, was significantly downregulated by co-expressed miR-22 (but not by miR-22 mutant) (Fig. 3d). Because miR-22-mediated downregulation of Etv6 could be observed only in the in vitro models (Fig. 3a–c), but not in the in vivo model (Fig. 3d), which was probably due to the difference between in vitro and in vivo microenvironments, we decided to focus on the three target genes (that is, Crtc1, Flt3 and Mycbp) that showed consistent patterns between in vitro and in vivo for further studies. The repression of Crtc1, Flt3 and Mycbpwas also found in leukaemia BM cells of mice with AE9a or FLT3-ITD/NPM1c+-induced AML (Fig. 3e,f). As Mycbp is already a known target of miR-22 (ref. 30), here we further confirmed that FLT3and CRTC1 are also direct targets of miR-22 (Fig. 3g,h). The downregulation of CRTC1, FLT3 and MYCBP by miR-22 at the protein level was confirmed in both human and mouse leukaemic cells (Supplementary Fig. 3b,c). Overexpression of miR-22 had no significant influence on the level of leukaemia fusion genes (Supplementary Fig. 3d).
Figure 3: miR-22 targets multiple oncogenes.
(a) Downregulation of CRTC1, FLT3, MYCBP and ETV6 by forced expression of miR-22 in MONOMAC-6 cells. Expression of these genes was detected 48h post transfection of MSCV-PIG (Ctrl) or MSCV-PIG-miR-22 (miR-22). (b) Crtc1, Flt3, Mycbp and Etv6 levels in MLL-ENL-ERtm cells after withdrawal of 4-OHT for 0, 7 or 10 days. (c) Expression levels of Crtc1, Flt3, Mycbp and Etv6 in mouse BM progenitor cells retrovirally transduced with MSCV-PIG+MSCV-neo (Ctrl), MSCV-PIG-miR-22+MSCV-neo (miR-22), MSCV-PIG+MSCV-neo-MLL-AF9 (MLL-AF9) or MSCV-PIG-miR-22+MSCV-neo-MLL-AF9 (MLL-AF9+miR-22). (d) Expression levels of Crtc1, Flt3, Mycbp and Etv6 in BM blast cells of leukaemic mice transplanted with MLL-AF9, MLL-AF9+miR-22 or MLL-AF9+miR-22mut primary leukaemic cells. (e,f) Expression levels of Crtc1, Flt3 and Mycbp in BM blast cells of leukaemic mice transplanted with MSCV-PIG or MSCV-PIG-miR-22-retrovirally transduced AE9a (e) or FLT3-ITD/NPM1c+ (f) primary leukaemic cells. (g) Putative miR-22 target sites and mutants in the 3′UTRs of CRTC1 (upper panel) and FLT3(lower panel). (h) Effects of miR-22 on luciferase activity of the reporter gene bearing wild type or mutant 3′UTRs of CRTC1 or FLT3 in HEK293T cells. The mean±s.d. values from three replicates are shown.*P<0.05, t-test.
Co-expression of the coding region (CDS) of each of the three target genes (that is, CRTC1, FLT3and MYCBP) largely reversed the effects of miR-22 on cell viability, apoptosis and proliferation (Fig. 4a–e). More importantly, in vivo BMT assays showed that co-expressing CRTC1, FLT3 orMYCBP largely rescued the inhibitory effect of miR-22 on leukemogenesis (Fig. 4f,g;Supplementary Fig. 3e). Our data thus suggest that CRTC1, FLT3 and MYCBP are functionally important targets of miR-22 in AML.
Figure 4: Multiple onocgenes are functionally important targets of miR-22 in AML.
(a,b) Relative viability (a) and apoptosis (b) levels of MONOMAC-6 cells transfected with MSCV-PIG-CRTC1, -FLT3 or –MYCBP alone, or together with MSCVneo-miR-22. Values were detected 48h post transfection. (c–e) Rescue effects of CRTC1 (c), FLT3 (d) and MYCBP (e) on the inhibition of MONOMAC-6 growth mediated by miR-22. Cell counts at the indicated time points are shown. Mean±s.d. values are shown. *P<0.05, t-test. (f) In vivo rescue effects of CRTC1, FLT3 and MYCBP on the inhibition of MLL-AF9-induced leukemogenesis mediated by miR-22. The secondary recipients were transplanted with BM blast cells of the primary MLL-AF9 leukaemic mice retrovirally transduced with MSCVneo+MSCV-PIG (MA9-AML+Ctrl; n=7), MSCVneo-miR-22+MSCV-PIG (MA9-AML+miR-22; n=10), MSCVneo-miR-22+MSCV-PIG-CRTC1 (MA9-AML+miR-22+CRTC1; n=5), MSCVneo-miR-22+MSCV-PIG-FLT3 (MA9-AML+miR-22+FLT3; n=6) or MSCVneo-miR-22+MSCV-PIG-MYCBP (MA9-AML+miR-22+MYCBP; n=6). Kaplan–Meier curves for all the five groups of transplanted mice are shown. MA9-AML+Ctrl versus MA9-AML+miR-22, P<0.001 (log-rank test); MA9-AML+Ctrl versus any other groups,P>0.05 (log-rank test). (g) Wright–Giemsa stained PB and BM, and H&E stained spleen and liver of the secondary leukaemic mice.
(a) Correlation between the expression levels of miR-22 and TET1 in three independent AML patient databases. All expression data were log(2) transformed; the data in In-house_81S were also mean-centred. The correlation coefficient (r) and P values were detected by ‘Pearson Correlation’, and the correlation regression lines were drawn with the ‘linear regression’ algorithm. (b) Expression of pri-, pre- and mature miR-22, and Tet1/2/3 in colony-forming cells of wild-type mouse BM progenitors retrovirally transduced with MSCVneo (Ctrl), MSCVneo-MLL-AF9 (MLL-AF9), MSCVneo-MLL-AF10 (MLL-AF10) or MSCVneo-AE9a (AE9a), or of FLT3-ITD/NPM1c+ mouse BM progenitors transduced with MSCVneo (FLT3-ITD+/NPM1c+). (c) Expression of miR-22 and Tet1/2/3 in MLL-ENL-ERtm cells. Expression levels were detected at the indicated time points post 4-OHT withdrawal. (d) Effect of miR-22 overexpression onTet1 expression in colony-forming cells with MLL-AF9, AE9a or FLT3-ITD/NPM1c+. (e) Expression ofTet1 in BM progenitor cells of 6-weeks old miR-22−/− or wild-type mice. (f) Effect of miR-22 overexpression on TET1 expression in THP-1 and KOCL-48 AML cells 48h post transfection. (g) Expression of pri-, pre- and mature miR-22 in BM progenitor cells of 6-weeks old Tet1−/− or wild-type mice. Mean±s.d. values are shown. *P<0.05, t-test.
(a) Tet1 targets miR-22 promoter region (−1,100/+55bp), as detected by luciferase reporter assay 48h post transfection in HEK293T cells. (b) Expression of TET1/2/3, EZH2, SIN3A, GFI1 and miR-22 in THP-1 cells 72h post treatment with 1μM ATRA or DMSO control. (c) Co-immunoprecipitation assay showing the binding of endogenous GFI1 and TET1 in THP1 cells. (d) ChIP-qPCR analyses of the promoter region of miR-22 in THP-1 cells 72h post treatment with 1μM ATRA or DMSO. Upper panel: PCR site on the CpG-enriched region of miR-22 gene locus. Note: miR-22 is coded within the second exon of a long non-coding RNA (MIR22HG), which represents the primary transcript of miR-22. Lower panels: enrichment of MLL-N terminal (for both wild-type MLL and MLL-fusion proteins), MLL-C terminal (for wild-type MLL), TET1, EZH2, SIN3A, GFI1, H3K27me3, H3K4me3 or RNA pol II at miR-22 promoter region. (e) Expression levels of TET1, EZH2, SIN3A and miR-22 in GFI1 knockdown cells. (f) ChIP-qPCR analyses of the promoter region of miR-22 in THP-1 cells transduced with GFI1 shRNA or control shRNA. Enrichment of GFI1, TET1, EZH2 and SIN3A are shown. (g) Effects of knockdown of TET1, EZH2 and/orSIN3A on miR-22 expression. The expression level of miR-22 was detected in THP-1 cells 72h post transfection with siRNAs targeting TET1, EZH2 and/or SIN3A. Mean±s.d. values are shown. *P<0.05;**P<0.01 (t-test). (h) Schematic model of the regulatory pathway involving miR-22 in AML and ATRA treatment.
The miR-22-associated regulatory circuit in AML
Restoration of miR-22 expression and function to treat AML
Figure 7: Therapeutic effect of miR-22-nanoparticles in treating AML.
(a,b) Primary leukaemia BM cells bearing MLL-AF9 (a) or AE9a (b) were transplanted into sublethally irradiated secondary recipient mice. After the onset of secondary AML (usually 10 days post transplantation), the recipient mice were treated with PBS control, or 0.5mgkg−1 miR-22 or miR-22 mutant RNA oligos formulated with G7 PAMAM dendrimer nanoparticles, i.v., every other day, until the PBS-treated control group all died of leukaemia. (c) NSGS mice49 were transplanted with MV4;11/t(4;11) AML cells. Five days post transplantation, these mice started to be treated with PBS control, miR-22 or miR-22 mutant nanoparticles at the same dose as described above. Kaplan–Meier curves are shown; the drug administration period and frequency were indicated with yellow arrows. The P values were detected by log-rank test. (d) Wright–Giemsa stained PB and BM, and H&E stained spleen and liver of the MLL-AF9-secondary leukaemic mice treated with PBS control, miR-22 or miR-22 mutant nanoparticles.
We then tested the miR-22 nanoparticles in a xeno-transplantation model49. Similarly, the nanoparticles carrying miR-22 oligos, but not miR-22 mutant, significantly delayed AML progression induced by human MV4;11/t(4;11) cells (Fig. 7c). The miR-22-nanoparticle administration also resulted in less aggressive leukaemic pathological phenotypes in the recipient mice (Supplementary Fig. 6e). Thus, our studies demonstrated the therapeutic potential of using miR-22-based nanoparticles to treat AML.
It remains poorly understood how TET proteins mediate gene regulation in cancer. Here we show that in de novo AML, it is TET1, but not TET2 (a reported direct target of miR-22 in MDS and breast cancer15, 16), that inversely correlates with miR-22 in expression and negatively regulates miR-22 at the transcriptional level. Likely together with GFI1, TET1 recruits polycomb cofactors (for example, EZH2/SIN3A) to the miR-22 promoter, leading to a significant increase in H3K27me3 occupancy and decrease in RNA pol II occupancy at that region, and thereby resulting in miR-22 repression in AML cells; such a repression can be abrogated by ATRA treatment. Thus, our study uncovers a novel epigenetic regulation mechanism in leukaemia involving the cooperation between TET1/GFI1 and polycomb factors.
Besides GFI1, it was reported that LSD1 is also a binding partner of TET1 (ref. 50). Interestingly, LSD1 is known as a common binding partner shared by TET1 and GFI1, and mediates the effect of GFI1 on hematopoietic differentiation51, 52. Thus, it is possible that LSD1 might also participate in the transcriptional repression of miR-22 as a component of the GFI1/TET1 repression complex.
We previously reported that TET1 cooperates with MLL fusions in positively regulating their oncogenic co-targets in MLL-rearranged AML14. Here we show that TET1 can also function as a transcriptional repressor (of a miRNA) in cancer. The requirement of TET1-mediated regulation on expression of its positive (for example, HOXA/MEIS1/PBX3)14 or negative (for example, miR-22) downstream effectors in leukemogenesis likely explains the rareness of TET1 mutations in AML53, and highlights its potent oncogenic role in leukaemia.
The aberrant activation of both CREB and MYC signalling pathways has been shown in AML24, 25,26, 54, 55, but the underlying molecular mechanisms remain elusive. Our data suggest that the activation of these two signalling pathways in AML can be attributed, at least in part, to the repression of miR-22, which in turn, results in the de-repression of CRTC1 (CREB pathway), FLT3and MYCBP (MYC pathway), and leads to the upregulation of oncogenic downstream targets (for example, CDK6, HOXA7, BMI1, FASN and HMGA1) and downregulation of tumour-suppressor downstream targets (for example, RGS2).
In summary, we uncover a TET1/GFI1/EZH2/SIN3A⊣miR-22⊣CREB-MYC signalling circuit in de novo AML, in which miR-22 functions as a pivotal anti-tumour gate-keeper, distinct from its oncogenic role reported in MDS or MDS-derived AML16. Thus, our study together with the study of Song et al.16 highlight the complexity and functional importance of miR-22-associated gene regulation and signalling pathways in hematopoietic malignancies, and may provide novel insights into the genetic/epigenetic differences between de novo AML and MDS.
Our findings also highlight the possibility of using miR-22-based therapy to treat AML patients. Our proof-of-concept studies demonstrate that the nanoparticles carrying miR-22 oligos significantly inhibit AML progression and prolong survival of leukaemic mice in both BMT and xeno-transplantation models. Notably, miRNA-based nanoparticles have already entered clinical trials56. It would be important, in the future, to further test the combination of miR-22-carrying nanoparticles (or small-molecule compounds that can induce endogenous expression of miR-22) with standard chemotherapy agents (cytosine arabinoside and anthracycline), or with the emerging small molecule inhibitors against MYC and/or CREB pathway effectors, to achieve optimal anti-leukaemia effect with minimal side effects. Overall, our results suggest that restoration of miR-22 expression/function (for example, using miR-22-carrying nanoparticles or small-molecule compounds) holds great therapeutic potential to treat AML, especially those resistant to current therapies.
MicroRNAs: A Gene Silencing Mechanism with Therapeutic Implications
MicroRNAs (miRNAs) are single-stranded RNAs about 22 nucleotides in length that repress the expression of specific proteins by annealing to complementary sequences in the 3′ untranslated regions (UTRs) of target mRNAs. Apart from their posttranscriptional expression, or silencing, miRNAs may also direct mRNA destabilization and cleavage. Moreover, rather than targeting a single disease-associated protein target as many small molecule drugs and antibodies do, each miRNA may serve to repress the expression of numerous proteins involved in the pathogenesis and progression of various diseases and could therefore potentially interfere with multiple disease-promoting signal transduction pathways. Because aberrant expression of miRNAs has been implicated in numerous disease states, miRNA-based therapies have sparked much interest for the treatment of a variety of diseases. The objective of this symposium is to bring together investigators who have led the field in describing what miRNAs do and their potential in treating diseases, as well as those who are translating these findings into promising drug candidates, some of which have already advanced into early stage clinical trials.
Call for Poster Abstracts
Abstract submissions are invited for a poster session. For complete submission instructions, please send an email to miRNA@nyas.org with the words “Abstract Information” in the subject line. The deadline for abstract submission is May 13, 2016.
LIVE – 8:00 am – 12:00 pm 4/25/2016 – First Look: The Next Wave of Cancer Breakthroughs @2016 World Medical Innovation Forum: CANCER, April 25-27, 2016, Westin Hotel, Boston
by Mark Cobbold, MD, PhD, MGH, Tumor Antigens in Cancer and How to Manipulate Antigens to Stimulate Immunity
which I found to be, as I wrote in Real Time, at the end of the Session:
[MOST IMPORTANT TALK]
challenges for immuno-oncology (IO)
Posttranslational NeoAntigens
tumor — Surfacre MHC
PTM post-translational modifications — MS
CRC Surface Phosphopeptides – antigenicity increasing in metastasis
Re-arming Existing Antibodies
Re-arming Existing Antibodies for Antigen Modulation
T cell activation
Redirecting CMV- specific T cells
Each presenter had 15 minutes, thus, what was captured was minimal. I am providing here few more details based on the material included in the handout distributed to attendees: First Look, The Next Wave of Cancer Breakthroughs, 4/25/2016, 8AM – 12PM
Tumor Antigens in Cancer and How to Manipulate Antigens to Stimulate Immunity
Mark Cobbold, MD, PhD, Center for Cancer Immunology, MGH
Associate Professor of Medicine, HMS
Associate Member of the Broad Institute of Harvard and MIT
QUOTE START
The role of anti-tumor immunity in the protection and control of arising tumors has been an intense focus of research for decades. While it is clear from strong correlative clinical data combined with definitive experimental evidence from mouse models that T-cells mediate this protection; the nature of the antigens targeted remains poorly characterized. Over the past decade, the role of altered-self antigens, termed neoantigens, has become clear. Tumor-specific neoantigens are known to act as targets of spontaneously arising adaptive immunity to cancer and thereby determine the ultimate fate of developing tumors. Nonsynonymous mutations in coding regions of expressed proteins are termed mutational neoantigents and, perhaps critically, are not subject to central tolerance. In cancers with high mutational loads such as non-small cell lung cancer and melanoma CD8+ T-cells can be identified within the tumor against MHC class-I restricted neoantigens in patients responding to immunotherapy. Despite these advance questions remain in the field, for example tumor-resident immunity against mutational neoantigens is typically at a very low frequencies and it is surprising that this magnitude of immunity can be responsible for dramatic reductions in tumor volume. Additionally, some of the tumors with the best clinical responses to immunotherapy have some of the lowest mutational loads for example renal cell carcinoma and leukemia. Hematological malignancies in particular are known to be amongst the most immunogenic cancers. Therefore, it is likely that the antigens in these malignancies derive from other classes of antigens.
Since dysregulation of cell signaling pathways plays a prominent role in cancer, leukemia-specific antigens may derive from the posttranslational modifications (PTMs) associated with aberrant signaling. Indeed, we have previously shown that a number of phosphorylated peptides as potent cancer antigens. Interestingly, immunity to these antigens was seen in healthy donors, but lost in a subset of leukemia patients with poor clinical outcomes and restored after SCT, suggesting a role for these neoantigens in the graft-vs-leukemia response. O-GlcNAcylation is another process involved in the dysregulation of cell signaling pathways in cancer. It functions as a nutrient sensor and regulates numerous cell signaling pathways by blocking and unblocking phosphorylation sites.
QUOTE END
SOURCE
Handout distributed to attendees: First Look, The Next Wave of Cancer Breakthroughs, 4/25/2016, 8AM – 12PM @2016 World Medical Innovation Forum: CANCER, April 25-27, 2016, Westin Hotel, Boston
Mechanism of new research targeting previously undruggable RAS gene. [Cell, Volume 165, 21 April 2016]
For greater than 30% of human cancers, RAS genes are mutated and have been implicated as key tumor drivers—making them some of the most sought after cancer drug targets. However, the absence of any drug-binding pockets in the mutant RAS proteins has made drug development extremely difficult. Yet now, a new study from researchers at the Icahn School of Medicine at Mount Sinai has identified a new mechanism for targeting this important cancer gene.
Mutations in RAS genes—such as HRAS, KRAS, and NRAS—are frequently observed in many of the most common and lethal tumors, including cancers of the pancreas, lung, and colon. While scientists have made significant headway in understanding these mutations and their impact on cellular signaling, little headway has been made toward developing drugs that systematically target the RAS oncogenes. This lack of progress has led many in the field to label RAS an “undruggable” cancer gene.
The Mt. Sinai team identified what they believe to be the first small molecule able to simultaneously inhibit the different signaling pathways activated by RAS oncogenes. This compound called rigosertib or ON01910.Na, acts as a protein-protein interaction inhibitor that prevents binding between RAS and signaling proteins (including RAF, PI3K, and others) that drive a cell into a cancer cell.
“Here, we present evidence that rigosertib, a styryl-benzyl sulfone, acts as a RAS-mimetic and interacts with the RBDs of RAF kinases, resulting in their inability to bind to RAS, disruption of RAF activation, and inhibition of the RAS-RAF-MEK pathway,” the authors wrote. “We also find that rigosertib binds to the RBDs of Ral-GDS and PI3Ks. These results suggest that targeting of RBDs across multiple signaling pathways by rigosertib may represent an effective strategy for inactivation of RAS signaling.”
The findings from this study were published recently in Cell through an article entitled “A Small Molecule RAS-Mimetic Disrupts RAS Association with Effector Proteins to Block Signaling.”
Additionally, the investigators performed structural experiments to confirm the mode of action for rigosertib and also demonstrated the potential for this targeted mechanism in the treatment of several RAS-driven cancers.
“This discovery is a significant breakthrough for the cancer field,” explained senior study author E. Premkumar Reddy, Ph.D., professor of oncological sciences at the Icahn School of Medicine at Mount Sinai. “Rigosertib’s mechanism of action represents a new paradigm for attacking the intractable RAS oncogenes. Our current focus is to use the information from our studies with rigosertib to design the next generation of small molecule RAS-targeting therapies, and we are excited to have recently identified several compounds which we think improve on the qualities of rigosertib.”
A Small Molecule RAS-Mimetic Disrupts RAS Association with Effector Proteins to Block Signaling
Sai Krishna Athuluri-Divakar, Rodrigo Vasquez-Del Carpio,….., Aneel K. Aggarwal, E. Premkumar Reddy
•Rigosertib binds to the RAS-binding domains (RBDs) of multiple RAS effectors
•Binding of rigosertib to RAF-RBD inhibits RAS-RAF interaction and impairs the kinase
•Rigosertib inhibits MEK-ERK pathway activated by growth factors and oncogenic RAS
Oncogenic activation of RAS genes via point mutations occurs in 20%–30% of human cancers. The development of effective RAS inhibitors has been challenging, necessitating new approaches to inhibit this oncogenic protein. Functional studies have shown that the switch region of RAS interacts with a large number of effector proteins containing a common RAS-binding domain (RBD). Because RBD-mediated interactions are essential for RAS signaling, blocking RBD association with small molecules constitutes an attractive therapeutic approach. Here, we present evidence that rigosertib, a styryl-benzyl sulfone, acts as a RAS-mimetic and interacts with the RBDs of RAF kinases, resulting in their inability to bind to RAS, disruption of RAF activation, and inhibition of the RAS-RAF-MEK pathway. We also find that ribosertib binds to the RBDs of Ral-GDS and PI3Ks. These results suggest that targeting of RBDs across multiple signaling pathways by rigosertib may represent an effective strategy for inactivation of RAS signaling.
Chemotherapy Benefit in Early Breast Cancer Patients
Larry H Bernstein, MD, FCAP, Curator
LPBI
Agendia’s MammaPrint® First and Only Genomic Assay to Receive Level 1A Clinical Utility Evidence for Chemotherapy Benefit in Early Breast Cancer Patients
Clinical high-risk patients with a low-risk MammaPrint® result, including 48 percent node-positive, had five-year distant metastasis-free survival rate in excess of 94 percent, whether randomized to receive adjuvant chemotherapy or not
MammaPrint could change clinical practice by substantially de-escalating the use of adjuvant chemotherapy and sparing many patients an aggressive treatment they will not benefit from
Forty-six percent overall reduction in chemotherapy prescription among clinically high-risk patients
April 19, 2016 / B3C newswire / —Agendia, Inc., together with the European Organisation for Research and Treatment of Cancer (EORTC) and Breast International Group (BIG), announced results from the initial analysis of the primary objective of the Microarray In Node-negative (and 1 to 3 positive lymph node) Disease may Avoid ChemoTherapy (MINDACT) study at the American Association for Cancer Research Annual Meeting 2016 in New Orleans, LA.
Using the company’s MammaPrint® assay, patients with early-stage breast cancer who were considered at high risk for disease recurrence based on clinical and biological criteria had a distant metastasis-free survival at five years in excess of 94 percent.The MammaPrint test—the first and only genomic assay with FDA 510(k) clearance for use in risk assessment for women of all ages with early stage breast cancer—identified a large group of patients for whom five-year distant metastasis–free survival was equally good whether or not they received adjuvant chemotherapy (chemotherapy given post-surgery).
“The MINDACT trial design is the optimal way to prove clinical utility of a genomic assay,” said Prof. Laura van ’t Veer, CRO at Agendia, Leader, Breast Oncology Program, and Director, Applied Genomics at UCSF Helen Diller Family Comprehensive Cancer Center. “It gives the level 1A clinical evidence (prospective, randomized and controlled) that empowers physicians to clearly and confidently know when chemotherapy is part of optimal early-stage breast cancer therapy. In this trial, MammaPrint (70-gene assay) was compared to the standard of care physicians use today, to decide what is the best treatment option for an early-stage breast cancer patient.”
The MINDACT trial is the first prospective randomized controlled clinical trial of a breast cancer recurrence genomic assay with level 1A clinical evidence and the first prospective translational research study of this magnitude in breast cancer to report the results of its primary objective.
Among the 3,356 patients enrolled in the MINDACT trial, who were categorized as having a high risk of breast cancer recurrence based on common clinical and pathological criteria (C-high), the MammaPrint assay reduced the chemotherapy treatment prescription by 46 percent.Using the 70-gene assay, MammaPrint, 48 percent of lymph-node positive breast cancer patients considered clinically high-risk (Clinical-high) and genomic low-risk (MammaPrint-low) had an excellent distant metastasis-free survival at five years in excess of 94 percent.
“Traditionally, physicians have relied on clinical-pathological factors such as age, tumor size, tumor grade, lymph node involvement, and hormone receptor status to make breast cancer treatment decisions,” said Massimo Cristofanilli, MD, Associate Director of Translational Research and Precision Medicine at the Robert H. Lurie Comprehensive Cancer Center, Northwestern University in Chicago. “These findings provide level 1A clinical utility evidence by demonstrating that the detection of low-risk of distant recurrence reported by the MammaPrint test can be safely used in the management of thousands of women by identifying those who can be spared from a toxic and unnecessary treatment.”
MINDACT is a randomized phase III trial that investigates the clinical utility of MammaPrint, when compared (or – “used in conjunction with”) to the standard clinical pathological criteria, for the selection of patients unlikely to benefit from adjuvant chemotherapy. From 2007 to 2011, 6,693 women who had undergone surgery for early-stage breast cancer enrolled in the trial (111 centers in nine countries). Participants were categorized as low or high risk for tumor recurrence in two ways: first, through analysis of tumor tissue using MammaPrint at a central location in Amsterdam; and second, using Adjuvant! Online, a tool that calculates risk of breast cancer recurrence based on common clinical and biological criteria.
Patients characterized in both clinical and genomic assessments as “low- risk” are spared chemotherapy, while patients characterized as “high- risk” are advised chemotherapy. Those with conflicting results are randomized to use either clinical or genomic risk (MammaPrint) evaluation to decide on chemotherapy treatment.
The MINDACT trial is managed and sponsored by the EORTC as part of an extensive and complex partnership in collaboration with Agendia and BIG, and many other academic and commercial partners, as well as patient advocates.
“These MINDACT trial results are a testament that the science of the MammaPrint test is the most robust in the genomic breast recurrence assay market. Agendia will continue to collaborate with pharmaceutical companies, leading cancer centers and academic groups on additional clinical research and in the pursuit of bringing more effective, individualized treatments within reach of cancer patients,” said Mark Straley, Chief Executive Officer at Agendia. “We value the partnership with the EORTC and BIG and it’s a great honor to share this critical milestone.”
Breast cancer is the most frequently diagnosed cancer in women worldwide(1). In 2012, there were nearly 1.7 million new breast cancer cases among women worldwide, accounting for 25 percent of all new cancer cases in women(2).
Imaging of Cancer Cells, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)
Imaging of Cancer Cells
Larry H. Bernstein, MD, FCAP, Curator
LPBI
Microscope uses nanosecond-speed laser and deep learning to detect cancer cells more efficiently
April 13, 2016
Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods.
In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological “labels” to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don’t use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.
Time-stretch quantitative phase imaging (TS-QPI) and analytics system
The new technique images cells without destroying them and can identify 16 physical characteristics — including size, granularity and biomass — instead of just one.
The new technique combines two components that were invented at UCLA:
A “photonic time stretch” microscope, which is capable of quickly imaging cells in blood samples. Invented by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering, it works by taking pictures of flowing blood cells using laser bursts (similar to how a camera uses a flash). Each flash only lasts nanoseconds (billionths of a second) to avoid damage to cells, but that normally means the images are both too weak to be detected and too fast to be digitized by normal instrumentation. The new microscope overcomes those challenges by using specially designed optics that amplify and boost the clarity of the images, and simultaneously slow them down enough to be detected and digitized at a rate of 36 million images per second.
A deep learning computer program, which identifies cancer cells with more than 95 percent accuracy. Deep learning is a form of artificial intelligence that uses complex algorithms to extract patterns and knowledge from rich multidimenstional datasets, with the goal of achieving accurate decision making.
The study was published in the open-access journal Nature Scientific Reports. The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease.
The research was supported by NantWorks, LLC.
Abstract of Deep Learning in Label-free Cell Classification
Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.
references:
Claire Lifan Chen, Ata Mahjoubfar, Li-Chia Tai, Ian K. Blaby, Allen Huang, Kayvan Reza Niazi & Bahram Jalali. Deep Learning in Label-free Cell Classification. Scientific Reports 6, Article number: 21471 (2016); doi:10.1038/srep21471 (open access)
Supplementary Information
Deep Learning in Label-free Cell Classification
Claire Lifan Chen, Ata Mahjoubfar, Li-Chia Tai, Ian K. Blaby, Allen Huang,Kayvan Reza Niazi & Bahram Jalali
Deep learning extracts patterns and knowledge from rich multidimenstional datasets. While it is extensively used for image recognition and speech processing, its application to label-free classification of cells has not been exploited. Flow cytometry is a powerful tool for large-scale cell analysis due to its ability to measure anisotropic elastic light scattering of millions of individual cells as well as emission of fluorescent labels conjugated to cells1,2. However, each cell is represented with single values per detection channels (forward scatter, side scatter, and emission bands) and often requires labeling with specific biomarkers for acceptable classification accuracy1,3. Imaging flow cytometry4,5 on the other hand captures images of cells, revealing significantly more information about the cells. For example, it can distinguish clusters and debris that would otherwise result in false positive identification in a conventional flow cytometer based on light scattering6.
In addition to classification accuracy, the throughput is another critical specification of a flow cytometer. Indeed high throughput, typically 100,000 cells per second, is needed to screen a large enough cell population to find rare abnormal cells that are indicative of early stage diseases. However there is a fundamental trade-off between throughput and accuracy in any measurement system7,8. For example, imaging flow cytometers face a throughput limit imposed by the speed of the CCD or the CMOS cameras, a number that is approximately 2000 cells/s for present systems9. Higher flow rates lead to blurred cell images due to the finite camera shutter speed. Many applications of flow analyzers such as cancer diagnostics, drug discovery, biofuel development, and emulsion characterization require classification of large sample sizes with a high-degree of statistical accuracy10. This has fueled research into alternative optical diagnostic techniques for characterization of cells and particles in flow.
Recently, our group has developed a label-free imaging flow-cytometry technique based on coherent optical implementation of the photonic time stretch concept11. This instrument overcomes the trade-off between sensitivity and speed by using Amplified Time-stretch Dispersive Fourier Transform12,13,14,15. In time stretched imaging16, the object’s spatial information is encoded in the spectrum of laser pulses within a pulse duration of sub-nanoseconds (Fig. 1). Each pulse representing one frame of the camera is then stretched in time so that it can be digitized in real-time by an electronic analog-to-digital converter (ADC). The ultra-fast pulse illumination freezes the motion of high-speed cells or particles in flow to achieve blur-free imaging. Detection sensitivity is challenged by the low number of photons collected during the ultra-short shutter time (optical pulse width) and the drop in the peak optical power resulting from the time stretch. These issues are solved in time stretch imaging by implementing a low noise-figure Raman amplifier within the dispersive device that performs time stretching8,11,16. Moreover, warped stretch transform17,18can be used in time stretch imaging to achieve optical image compression and nonuniform spatial resolution over the field-of-view19. In the coherent version of the instrument, the time stretch imaging is combined with spectral interferometry to measure quantitative phase and intensity images in real-time and at high throughput20. Integrated with a microfluidic channel, coherent time stretch imaging system in this work measures both quantitative optical phase shift and loss of individual cells as a high-speed imaging flow cytometer, capturing 36 million images per second in flow rates as high as 10 meters per second, reaching up to 100,000 cells per second throughput.
Box 1: The pulse train is spatially dispersed into a train of rainbow flashes illuminating the target as line scans. The spatial features of the target are encoded into the spectrum of the broadband optical pulses, each representing a one-dimensional frame. The ultra-short optical pulse illumination freezes the motion of cells during high speed flow to achieve blur-free imaging with a throughput of 100,000 cells/s. The phase shift and intensity loss at each location within the field of view are embedded into the spectral interference patterns using a Michelson interferometer. Box 2: The interferogram pulses were then stretched in time so that spatial information could be mapped into time through time-stretch dispersive Fourier transform (TS-DFT), and then captured by a single pixel photodetector and an analog-to-digital converter (ADC). The loss of sensitivity at high shutter speed is compensated by stimulated Raman amplification during time stretch. Box 3: (a) Pulse synchronization; the time-domain signal carrying serially captured rainbow pulses is transformed into a series of one-dimensional spatial maps, which are used for forming line images. (b) The biomass density of a cell leads to a spatially varying optical phase shift. When a rainbow flash passes through the cells, the changes in refractive index at different locations will cause phase walk-off at interrogation wavelengths. Hilbert transformation and phase unwrapping are used to extract the spatial phase shift. (c) Decoding the phase shift in each pulse at each wavelength and remapping it into a pixel reveals the protein concentration distribution within cells. The optical loss induced by the cells, embedded in the pulse intensity variations, is obtained from the amplitude of the slowly varying envelope of the spectral interferograms. Thus, quantitative optical phase shift and intensity loss images are captured simultaneously. Both images are calibrated based on the regions where the cells are absent. Cell features describing morphology, granularity, biomass, etc are extracted from the images. (d) These biophysical features are used in a machine learning algorithm for high-accuracy label-free classification of the cells.
On another note, surface markers used to label cells, such as EpCAM21, are unavailable in some applications; for example, melanoma or pancreatic circulating tumor cells (CTCs) as well as some cancer stem cells are EpCAM-negative and will escape EpCAM-based detection platforms22. Furthermore, large-population cell sorting opens the doors to downstream operations, where the negative impacts of labels on cellular behavior and viability are often unacceptable23. Cell labels may cause activating/inhibitory signal transduction, altering the behavior of the desired cellular subtypes, potentially leading to errors in downstream analysis, such as DNA sequencing and subpopulation regrowth. In this way, quantitative phase imaging (QPI) methods24,25,26,27 that categorize unlabeled living cells with high accuracy are needed. Coherent time stretch imaging is a method that enables quantitative phase imaging at ultrahigh throughput for non-invasive label-free screening of large number of cells.
In this work, the information of quantitative optical loss and phase images are fused into expert designed features, leading to a record label-free classification accuracy when combined with deep learning. Image mining techniques are applied, for the first time, to time stretch quantitative phase imaging to measure biophysical attributes including protein concentration, optical loss, and morphological features of single cells at an ultrahigh flow rate and in a label-free fashion. These attributes differ widely28,29,30,31 among cells and their variations reflect important information of genotypes and physiological stimuli32. The multiplexed biophysical features thus lead to information-rich hyper-dimensional representation of the cells for label-free classification with high statistical precision.
We further improved the accuracy, repeatability, and the balance between sensitivity and specificity of our label-free cell classification by a novel machine learning pipeline, which harnesses the advantages of multivariate supervised learning, as well as unique training by evolutionary global optimization of receiver operating characteristics (ROC). To demonstrate sensitivity, specificity, and accuracy of multi-feature label-free flow cytometry using our technique, we classified (1) OT-IIhybridoma T-lymphocytes and SW-480 colon cancer epithelial cells, and (2) Chlamydomonas reinhardtii algal cells (herein referred to as Chlamydomonas) based on their lipid content, which is related to the yield in biofuel production. Our preliminary results show that compared to classification by individual biophysical parameters, our label-free hyperdimensional technique improves the detection accuracy from 77.8% to 95.5%, or in other words, reduces the classification inaccuracy by about five times. ……..
Feature Extraction
The decomposed components of sequential line scans form pairs of spatial maps, namely, optical phase and loss images as shown in Fig. 2 (see Section Methods: Image Reconstruction). These images are used to obtain biophysical fingerprints of the cells8,36. With domain expertise, raw images are fused and transformed into a suitable set of biophysical features, listed in Table 1, which the deep learning model further converts into learned features for improved classification.
The new technique combines two components that were invented at UCLA:
A “photonic time stretch” microscope, which is capable of quickly imaging cells in blood samples. Invented by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering, it works by taking pictures of flowing blood cells using laser bursts (similar to how a camera uses a flash). Each flash only lasts nanoseconds (billionths of a second) to avoid damage to cells, but that normally means the images are both too weak to be detected and too fast to be digitized by normal instrumentation. The new microscope overcomes those challenges by using specially designed optics that amplify and boost the clarity of the images, and simultaneously slow them down enough to be detected and digitized at a rate of 36 million images per second.
A deep learning computer program, which identifies cancer cells with more than 95 percent accuracy. Deep learning is a form of artificial intelligence that uses complex algorithms to extract patterns and knowledge from rich multidimenstional datasets, with the goal of achieving accurate decision making.
The study was published in the open-access journal Nature Scientific Reports. The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease.
The optical loss images of the cells are affected by the attenuation of multiplexed wavelength components passing through the cells. The attenuation itself is governed by the absorption of the light in cells as well as the scattering from the surface of the cells and from the internal cell organelles. The optical loss image is derived from the low frequency component of the pulse interferograms. The optical phase image is extracted from the analytic form of the high frequency component of the pulse interferograms using Hilbert Transformation, followed by a phase unwrapping algorithm. Details of these derivations can be found in Section Methods. Also, supplementary Videos 1 and 2 show measurements of cell-induced optical path length difference by TS-QPI at four different points along the rainbow for OT-II and SW-480, respectively.
Table 1: List of extracted features.
Feature Name Description Category
Figure 3: Biophysical features formed by image fusion.
(a) Pairwise correlation matrix visualized as a heat map. The map depicts the correlation between all major 16 features extracted from the quantitative images. Diagonal elements of the matrix represent correlation of each parameter with itself, i.e. the autocorrelation. The subsets in box 1, box 2, and box 3 show high correlation because they are mainly related to morphological, optical phase, and optical loss feature categories, respectively. (b) Ranking of biophysical features based on their AUCs in single-feature classification. Blue bars show performance of the morphological parameters, which includes diameter along the interrogation rainbow, diameter along the flow direction, tight cell area, loose cell area, perimeter, circularity, major axis length, orientation, and median radius. As expected, morphology contains most information, but other biophysical features can contribute to improved performance of label-free cell classification. Orange bars show optical phase shift features i.e. optical path length differences and refractive index difference. Green bars show optical loss features representing scattering and absorption by the cell. The best performed feature in these three categories are marked in red.
Figure 4: Machine learning pipeline. Information of quantitative optical phase and loss images are fused to extract multivariate biophysical features of each cell, which are fed into a fully-connected neural network.
The neural network maps input features by a chain of weighted sum and nonlinear activation functions into learned feature space, convenient for classification. This deep neural network is globally trained via area under the curve (AUC) of the receiver operating characteristics (ROC). Each ROC curve corresponds to a set of weights for connections to an output node, generated by scanning the weight of the bias node. The training process maximizes AUC, pushing the ROC curve toward the upper left corner, which means improved sensitivity and specificity in classification.
…. How to cite this article: Chen, C. L. et al. Deep Learning in Label-free Cell Classification.
To better characterize the functional context of genomic variations in cancer, researchers developed a new computer algorithm called REVEALER. [UC San Diego Health]
Scientists at the University of California San Diego School of Medicine and the Broad Institute say they have developed a new computer algorithm—REVEALER—to better characterize the functional context of genomic variations in cancer. The tool, described in a paper (“Characterizing Genomic Alterations in Cancer by Complementary Functional Associations”) published in Nature Biotechnology, is designed to help researchers identify groups of genetic variations that together associate with a particular way cancer cells get activated, or how they respond to certain treatments.
REVEALER is available for free to the global scientific community via the bioinformatics software portal GenePattern.org.
“This computational analysis method effectively uncovers the functional context of genomic alterations, such as gene mutations, amplifications, or deletions, that drive tumor formation,” said senior author Pablo Tamayo, Ph.D., professor and co-director of the UC San Diego Moores Cancer Center Genomics and Computational Biology Shared Resource.
Dr. Tamayo and team tested REVEALER using The Cancer Genome Atlas (TCGA), the NIH’s database of genomic information from more than 500 human tumors representing many cancer types. REVEALER revealed gene alterations associated with the activation of several cellular processes known to play a role in tumor development and response to certain drugs. Some of these gene mutations were already known, but others were new.
For example, the researchers discovered new activating genomic abnormalities for beta-catenin, a cancer-promoting protein, and for the oxidative stress response that some cancers hijack to increase their viability.
REVEALER requires as input high-quality genomic data and a significant number of cancer samples, which can be a challenge, according to Dr. Tamayo. But REVEALER is more sensitive at detecting similarities between different types of genomic features and less dependent on simplifying statistical assumptions, compared to other methods, he adds.
“This study demonstrates the potential of combining functional profiling of cells with the characterizations of cancer genomes via next-generation sequencing,” said co-senior author Jill P. Mesirov, Ph.D., professor and associate vice chancellor for computational health sciences at UC San Diego School of Medicine.
Characterizing genomic alterations in cancer by complementary functional associations
Jong Wook Kim, Olga B Botvinnik, Omar Abudayyeh, Chet Birger, et al.
Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes
Figure 2: REVEALER results for transcriptional activation of β-catenin in cancer.close
(a) This heatmap illustrates the use of the REVEALER approach to find complementary genomic alterations that match the transcriptional activation of β-catenin in cancer. The target profile is a TCF4 reporter that provides an estimate of…
An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models
Jonathan P. Celli, Imran Rizvi, Adam R. Blanden, Iqbal Massodi, Michael D. Glidden, Brian W. Pogue & Tayyaba Hasan
While it is increasingly recognized that three-dimensional (3D) cell culture models recapitulate drug responses of human cancers with more fidelity than monolayer cultures, a lack of quantitative analysis methods limit their implementation for reliable and routine assessment of emerging therapies. Here, we introduce an approach based on computational analysis of fluorescence image data to provide high-content readouts of dose-dependent cytotoxicity, growth inhibition, treatment-induced architectural changes and size-dependent response in 3D tumour models. We demonstrate this approach in adherent 3D ovarian and pancreatic multiwell extracellular matrix tumour overlays subjected to a panel of clinically relevant cytotoxic modalities and appropriately designed controls for reliable quantification of fluorescence signal. This streamlined methodology reads out the high density of information embedded in 3D culture systems, while maintaining a level of speed and efficiency traditionally achieved with global colorimetric reporters in order to facilitate broader implementation of 3D tumour models in therapeutic screening.
The attrition rates for preclinical development of oncology therapeutics are particularly dismal due to a complex set of factors which includes 1) the failure of pre-clinical models to recapitulate determinants of in vivo treatment response, and 2) the limited ability of available assays to extract treatment-specific data integral to the complexities of therapeutic responses1,2,3. Three-dimensional (3D) tumour models have been shown to restore crucial stromal interactions which are missing in the more commonly used 2D cell culture and that influence tumour organization and architecture4,5,6,7,8, as well as therapeutic response9,10, multicellular resistance (MCR)11,12, drug penetration13,14, hypoxia15,16, and anti-apoptotic signaling17. However, such sophisticated models can only have an impact on therapeutic guidance if they are accompanied by robust quantitative assays, not only for cell viability but also for providing mechanistic insights related to the outcomes. While numerous assays for drug discovery exist18, they are generally not developed for use in 3D systems and are often inherently unsuitable. For example, colorimetric conversion products have been noted to bind to extracellular matrix (ECM)19 and traditional colorimetric cytotoxicity assays reduce treatment response to a single number reflecting a biochemical event that has been equated to cell viability (e.g. tetrazolium salt conversion20). Such approaches fail to provide insight into the spatial patterns of response within colonies, morphological or structural effects of drug response, or how overall culture viability may be obscuring the status of sub-populations that are resistant or partially responsive. Hence, the full benefit of implementing 3D tumour models in therapeutic development has yet to be realized for lack of analytical methods that describe the very aspects of treatment outcome that these systems restore.
Motivated by these factors, we introduce a new platform for quantitative in situ treatment assessment (qVISTA) in 3D tumour models based on computational analysis of information-dense biological image datasets (bioimage-informatics)21,22. This methodology provides software end-users with multiple levels of complexity in output content, from rapidly-interpreted dose response relationships to higher content quantitative insights into treatment-dependent architectural changes, spatial patterns of cytotoxicity within fields of multicellular structures, and statistical analysis of nodule-by-nodule size-dependent viability. The approach introduced here is cognizant of tradeoffs between optical resolution, data sampling (statistics), depth of field, and widespread usability (instrumentation requirement). Specifically, it is optimized for interpretation of fluorescent signals for disease-specific 3D tumour micronodules that are sufficiently small that thousands can be imaged simultaneously with little or no optical bias from widefield integration of signal along the optical axis of each object. At the core of our methodology is the premise that the copious numerical readouts gleaned from segmentation and interpretation of fluorescence signals in these image datasets can be converted into usable information to classify treatment effects comprehensively, without sacrificing the throughput of traditional screening approaches. It is hoped that this comprehensive treatment-assessment methodology will have significant impact in facilitating more sophisticated implementation of 3D cell culture models in preclinical screening by providing a level of content and biological relevance impossible with existing assays in monolayer cell culture in order to focus therapeutic targets and strategies before costly and tedious testing in animal models.
Using two different cell lines and as depicted in Figure 1, we adopt an ECM overlay method pioneered originally for 3D breast cancer models23, and developed in previous studies by us to model micrometastatic ovarian cancer19,24. This system leads to the formation of adherent multicellular 3D acini in approximately the same focal plane atop a laminin-rich ECM bed, implemented here in glass-bottom multiwell imaging plates for automated microscopy. The 3D nodules resultant from restoration of ECM signaling5,8, are heterogeneous in size24, in contrast to other 3D spheroid methods, such as rotary or hanging drop cultures10, in which cells are driven to aggregate into uniformly sized spheroids due to lack of an appropriate substrate to adhere to. Although the latter processes are also biologically relevant, it is the adherent tumour populations characteristic of advanced metastatic disease that are more likely to be managed with medical oncology, which are the focus of therapeutic evaluation herein. The heterogeneity in 3D structures formed via ECM overlay is validated here by endoscopic imaging ofin vivo tumours in orthotopic xenografts derived from the same cells (OVCAR-5).
Figure 1: A simplified schematic flow chart of imaging-based quantitative in situ treatment assessment (qVISTA) in 3D cell culture.
(This figure was prepared in Adobe Illustrator® software by MD Glidden, JP Celli and I Rizvi). A detailed breakdown of the image processing (Step 4) is provided in Supplemental Figure 1.
A critical component of the imaging-based strategy introduced here is the rational tradeoff of image-acquisition parameters for field of view, depth of field and optical resolution, and the development of image processing routines for appropriate removal of background, scaling of fluorescence signals from more than one channel and reliable segmentation of nodules. In order to obtain depth-resolved 3D structures for each nodule at sub-micron lateral resolution using a laser-scanning confocal system, it would require ~ 40 hours (at approximately 100 fields for each well with a 20× objective, times 1 minute/field for a coarse z-stack, times 24 wells) to image a single plate with the same coverage achieved in this study. Even if the resources were available to devote to such time-intensive image acquisition, not to mention the processing, the optical properties of the fluorophores would change during the required time frame for image acquisition, even with environmental controls to maintain culture viability during such extended imaging. The approach developed here, with a mind toward adaptation into high throughput screening, provides a rational balance of speed, requiring less than 30 minutes/plate, and statistical rigour, providing images of thousands of nodules in this time, as required for the high-content analysis developed in this study. These parameters can be further optimized for specific scenarios. For example, we obtain the same number of images in a 96 well plate as for a 24 well plate by acquiring only a single field from each well, rather than 4 stitched fields. This quadruples the number conditions assayed in a single run, at the expense of the number of nodules per condition, and therefore the ability to obtain statistical data sets for size-dependent response, Dfrac and other segmentation-dependent numerical readouts.
We envision that the system for high-content interrogation of therapeutic response in 3D cell culture could have widespread impact in multiple arenas from basic research to large scale drug development campaigns. As such, the treatment assessment methodology presented here does not require extraordinary optical instrumentation or computational resources, making it widely accessible to any research laboratory with an inverted fluorescence microscope and modestly equipped personal computer. And although we have focused here on cancer models, the methodology is broadly applicable to quantitative evaluation of other tissue models in regenerative medicine and tissue engineering. While this analysis toolbox could have impact in facilitating the implementation of in vitro 3D models in preclinical treatment evaluation in smaller academic laboratories, it could also be adopted as part of the screening pipeline in large pharma settings. With the implementation of appropriate temperature controls to handle basement membranes in current robotic liquid handling systems, our analyses could be used in ultra high-throughput screening. In addition to removing non-efficacious potential candidate drugs earlier in the pipeline, this approach could also yield the additional economic advantage of minimizing the use of costly time-intensive animal models through better estimates of dose range, sequence and schedule for combination regimens.
Microscope Uses AI to Find Cancer Cells More Efficiently
Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods.
In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological “labels” to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses.
There are other current techniques that don’t use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.
The new technique images cells without destroying them and can identify 16 physical characteristics — including size, granularity and biomass — instead of just one. It combines two components that were invented at UCLA: a photonic time stretch microscope, which is capable of quickly imaging cells in blood samples, and a deep learning computer program that identifies cancer cells with over 95 percent accuracy.
Deep learning is a form of artificial intelligence that uses complex algorithms to extract meaning from data with the goal of achieving accurate decision making.
The study, which was published in the journal Nature Scientific Reports, was led by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering; Claire Lifan Chen, a UCLA doctoral student; and Ata Mahjoubfar, a UCLA postdoctoral fellow.
Photonic time stretch was invented by Jalali, and he holds a patent for the technology. The new microscope is just one of many possible applications; it works by taking pictures of flowing blood cells using laser bursts in the way that a camera uses a flash. This process happens so quickly — in nanoseconds, or billionths of a second — that the images would be too weak to be detected and too fast to be digitized by normal instrumentation.
The new microscope overcomes those challenges using specially designed optics that boost the clarity of the images and simultaneously slow them enough to be detected and digitized at a rate of 36 million images per second. It then uses deep learning to distinguish cancer cells from healthy white blood cells.
“Each frame is slowed down in time and optically amplified so it can be digitized,” Mahjoubfar said. “This lets us perform fast cell imaging that the artificial intelligence component can distinguish.”
Normally, taking pictures in such minuscule periods of time would require intense illumination, which could destroy live cells. The UCLA approach also eliminates that problem.
“The photonic time stretch technique allows us to identify rogue cells in a short time with low-level illumination,” Chen said.
The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease. ….. see also http://www.nature.com/article-assets/npg/srep/2016/160315/srep21471/images_hires/m685/srep21471-f1.jpg
Prostate gland is surrounded by periprostatic adipose tissue (PPAT), which is increasingly believed to play a paracrine role in prostate cancer progression. Our previous work demonstrates that adipocytes promote homing of prostate cancer cells to PPAT and that this effect is upregulated by obesity. Here, we show that once tumor cells have invaded PPAT (mimicked by an in vitro model of coculture), they establish a bidirectional crosstalk with adipocytes, which promotes tumor cell invasion. Indeed, tumor cells induce adipocyte lipolysis and the free fatty acids (FFA) released are taken up and stored by tumor cells. Incubation with exogenous lipids also stimulates tumor cell invasion, underlining the importance of lipid transfer in prostate cancer aggressiveness. Transferred FFAs (after coculture or exogenous lipid treatment) stimulate the expression of one isoform of the pro-oxidant enzyme NADPH oxidase, NOX5. NOX5 increases intracellular reactive oxygen species (ROS) that, in turn, activate a HIF1/MMP14 pathway, which is responsible for the increased tumor cell invasion. In obesity, tumor-surrounding adipocytes are more prone to activate the depicted signaling pathway and to induce tumor invasion. Finally, the expression of NOX5 and MMP14 is upregulated at the invasive front of human tumors where cancer cells are in close proximity to adipocytes and this process is amplified in obese patients, underlining the clinical relevance of our results.
Implications: Our work emphasizes the key role of adjacent PPAT in prostate cancer dissemination and proposes new molecular targets for the treatment of obese patients exhibiting aggressive diseases.
Introduction
Malignant evolution of solid cancers relies on complex cell-to-cell interactions sustained by a broad network of physical and chemical mediators that constitute the tumor microenvironment (1). Adipose tissue, and its main cellular component, adipocytes, have recently emerged as key actors in solid tumor progression (2). Upon proximal adipose tissue infiltration, a bidirectional crosstalk takes place between invasive tumor cells and adipocytes. Initially described in breast cancer, tumor-surrounding adipocytes exhibit extensive phenotypical changes defined by a decrease in lipid content, a decreased expression of adipocyte markers, and an activated state demonstrated predominantly by the overexpression of proinflammatory cytokines and ECM (extracellular matrix)-related molecules (3). We named these cells cancer-associated adipocytes (CAA; ref. 3). Occurrence of CAAs is not restricted to breast cancer and has been described in a wide range of solid tumors including metastatic ovarian cancer, renal and colon cancers, as well as melanoma (2). In turn, CAAs promote tumor aggressiveness by secreting soluble factors, ECM proteins, and ECM-remodeling enzymes and by modulating tumor cell metabolism (2). The decrease in size and lipid content of tumor-surrounding adipocytes results from a “dedifferentiation” process depending on the reactivation of the Wnt/β-catenin pathway in response to Wnt3a secreted by tumor cells (4) and from induction of lipolysis, the latter process resulting in release of free fatty acids (FFA; refs. 5–7). These FFAs are then taken up, stored in lipid droplets, and used by tumor cells, where they have been described to contribute to tumor progression mainly through modulation of tumor cell metabolism toward fatty acid oxidation (FAO; refs. 5–7). This metabolic symbiosis instilled between cancer cells and tumor-surrounding adipocytes is only beginning to be explored but could provide new therapeutic targets as we recently reviewed in ref. 8. In addition to FAO, FFAs acquired from adipocytes could be used as membrane building blocks and/or signaling lipids and the fate of these lipids may depend on the tumor cell type.
Among the different types of tumors whose close interaction with adipose tissue could influence tumor progression is prostate cancer, the most common malignancy in men in Western countries. The prostate is surrounded by periprostatic adipose tissue (PPAT) and extraprostatic extension into PPAT is a widely acknowledged adverse prognostic factor in prostate cancer and an important determinant of prostate cancer recurrence after treatment (9). The positive association between obesity and aggressive prostate cancer, defined by an increase in local and distant dissemination, is also in favor of a role for adipose tissue in tumor progression (10). We have recently demonstrated that adipocytes from PPAT favor the initial step of PPAT infiltration by secreting the CCL7 chemokine that attracts CCR3-expressing cancer cells, and this process is amplified in obesity (11). Prostate-confined cancer cell migration and invasion may also be promoted at distance by inflammatory cytokines and metalloproteases secreted by PPAT, as well as by adipocyte-derived exosomes (12–14). In contrast to other cancer types such as breast or ovarian cancer (2), the effect of the invaded cancer cells on adipocytes within PPAT has been poorly described. Secretions from PPAT are modified by tumor-conditioned medium with upregulation of osteopontin, TNFα, and IL6, highlighting that, like other adipose depots, it is not inert to tumors (15). Coculture of prostate cancer cells with rat epididymal adipocytes increases growth and changes the morphology of prostate cancer cells (16, 17), but phenotypical changes of adipocytes have not been investigated in these studies. In addition, the mechanisms that govern increased prostate cancer cell aggressiveness in the presence of adipocytes are poorly described and have been mainly attributed to soluble factors (such as IL6; for review, see ref. 18). Finally, lipid transfer has not been demonstrated between periprostatic adipocytes and tumor cells, but only with bone marrow–derived adipocytes present at prostate cancer’s most frequent metastatic site (19, 20). Here, we demonstrate that prostate cancer cells are able to induce a CAA phenotype in vitro and in vivo, and that CAAs, in turn, promote tumor invasion. Lipid transfer between tumor-surrounding adipocytes and cancer cells promotes tumor aggressiveness by inducing oxidative stress in a NADPH oxidase–dependent manner, activating a proinvasive signaling pathway. The overall pathway is amplified in obesity and has been validated in human tumors. This study highlights the importance of lipid transfer in the tumor-promoting effect of adipocytes but also underlines that the consequence of this process is not univocal among all tumor types.
Revised 4/20/2016
AACR 2016: Novel Epigenetic Drug Therapeutics Revealed
As the 2016 American Association for Cancer Research meeting begins to downshift toward a close, the presentation sessions certainly did not suffer from a lack of enthusiasm from attendees or high-quality research from presenters. Of particular note was a major symposium that discussed next-generation epigenetic therapeutics.
In the past several years, there have been a variety of epigenetic targets exploited by newly developed drug compounds, many of which have already progressed into clinical trials. Often these compounds will target specific classes of epigenetic regulators like acetylases and histone demethylases, for instance, the small-molecule inhibitors of protein interacting bromodomains—implicated in a diverse range of cancers—and methyltransferase inhibitors, such as lysyl demethylases (KDM).
However, for all of their recently achieved success, researchers are continually searching for increasingly rapid methods to validate epigenetic drug targets. Session Chairperson Udo Oppermann, Ph.D., principal investigator at the University of Oxford, stressed that open access research and continued investigator cooperation were key factors for driving rapid development of novel therapeutics in the field. Anecdotally, Dr. Oppermann noted that if biologists were a bit more like the international cooperative teams of physicists that discovered the Higgs boson or gravitational waves, many biological endeavors would advance rather quickly.
After providing the audience with a brief introduction to the symposium’s topic, Dr. Oppermann described his current research on histone demethylase inhibitors in multiple myeloma and the connection to metabolic pathways. He surmised that tricarboxylic acid (TCA) cycle-derived metabolites can link cellular metabolism to cancer—impacting epigenetic landscapes. Specifically, the TCA intermediates are inhibitors of KDMs, ultimately controlling epigenetic and metabolic regulation.
Furthermore, Dr. Oppermann’s group was able to show that treatment of myeloma cell lines with the potent and specific histone demethylase inhibitor GSK-J4 was able to reverse the Myc-driven metabolic dependency, forcing a selected amino acid depletion. This deficiency led to the integrated stress response and the activation of proapoptotic genes. This work helps to solidify further the potent nature of GSK-J4 in cancer while simultaneously uncovering the metabolic mechanisms that cancer cells employ to keep their overproliferative phenotypes progressing forward.
Next, Tomasz Cierpicki, Ph.D., assistant professor at the University of Michigan, described his work on targeting leukemic stem cells with small-molecule inhibitors of the protein regulator of cytokinesis 1 (PRC1). Dr. Cierpicki took the audience through his research design, which was to target BMI1, an oncogene that determines the proliferative capacity and self-renewal potential of normal and leukemic stem cells. BMI1 has been implicated in a variety of tumors and is essential for the Polycomb Repressive Complex 1 (PRC1). Moreover, BMI1 interacts with the RING1B protein to form an active E3 ubiquitin ligase that targets histone H2A, modifying epigenetic regulation mechanisms.
Dr. Cierpicki’s laboratory looked at inhibitors of the RING1B–BMI1 E3 ligase complex as potential therapeutic agents targeting cancer stem cells. Using an array of techniques from fragment screening to medicinal chemistry, the researchers were able to identify potent compounds that bound to RING1B–BMI1 and inhibit its E3 ubiquitin ligase activity with low micromolar affinities. When testing in vitro, the inhibitors revealed robust downregulation of H2A ubiquitination. Dr. Cierpicki and his colleagues found that the RING1–BMI1 inhibitor blocked the self-renewal capacity of the stem cells and induced cellular differentiation—validating RING ligases as a novel epigenetic drug target.
Finishing up the session was William Sellers, M.D., vice president and global head of oncology for the Novartis Institutes for BioMedical Research. Dr. Sellers’ research is focused on what genes are necessary for epigenetic regulation of cancer and how they are linked to essential metabolic processes. He and his colleagues accomplished their studies through the use of large-scale shRNA screening across a diverse set of 390 cancer cell lines.
Utilizing deep small hairpin RNA (shRNA) screening libraries, at 20 shRNAs per genome, provided the investigators with highly robust gene-level data, which resulted in the emergence of several distinct classes of cancer-dependent genes. For example, Dr. Sellers’ group found that several known oncogenes fell into the genetic dependence class, whereas other genes were sorted into lineage, paralog, and collateral synthetic lethality dependent classes.
An interesting example from Dr. Sellers’ work was the link his laboratory discovered between polyamine metabolism and salvage and the protein arginine methyltransferase 5 (PRMT5). In particular, the loss of methylthioadenosine phosphorylase (MTAP)—which has been observed in many solid tumors and hematologic malignancies—resulted in the accumulation of S-methyl-5′-thioadenosine (MTA), which specifically inhibited the epigenetic mechanisms of PRMT5. The culmination Dr. Sellers’ analysis led to the finding that PRMT5 is a novel target for therapeutic development in MTAP deleted cancers.
These three presentations represented some of the excellent, cutting-edge research that is not only looking to develop novel drug therapeutics but also trying to uncover the underlying molecular mechanisms of epigenetic regulation and cancer.
A novel metabolic pathway that helps cancer cells thrive in conditions that are lethal to normal cells has been identified.
“It’s long been thought that if we could target tumor-specific metabolic pathways, it could lead to effective ways to treat cancer,” said senior author Dr. Ralph DeBerardinis, Associate Professor of CRI and Pediatrics, Director of CRI’s Genetic and Metabolic Disease Program, and Chief of the Division of Pediatric Genetics and Metabolism at UT Southwestern. “This study finds that two very different metabolic processes are linked in a way that is specifically required for cells to adapt to the stress associated with cancer progression.”
The study, available online today in the journal Nature, reveals that cancer cells use an alternate version of two well-known metabolic pathways called the pentose phosphate pathway (PPP) and the Krebs cycle to defend against toxins. The toxins are reactive oxygen species (ROS) that kill cells via oxidative stress.
This work builds on earlier studies by Dr. DeBerardinis’ laboratory that found the Krebs cycle, a series of chemical reactions that cells use to generate energy, could reverse itself under certain conditions to nourish cancer cells.
Dr. DeBerardinis said most normal cells and tumor cells grow by attaching to nutrient-rich tissue called a matrix. “They are dependent on matrix attachment to receive growth-promoting signals and to regulate their metabolism in a way that supports cell growth, proliferation, and survival,” he said.
Detachment from the matrix results in a sudden increase in ROS that is lethal to normal cells, he added. Cancer cells seem to have a workaround.
The destruction of healthy cells when detached from the matrix was reported in a landmark 2009 Nature study by Harvard Medical School cell biologist Dr. Joan Brugge. Intriguingly, that same study found that inserting an oncogene – a gene with the potential to cause cancer – into a normal cell caused it to behave like a cancer cell and survive detachment, said Dr. DeBerardinis, who also is affiliated with the Eugene McDermott Center for Human Growth & Development, holds the Joel B. Steinberg, M.D. Chair in Pediatrics, and is a Sowell Family Scholar in Medical Research at UT Southwestern.
“Another Nature study, this one from CRI Director Dr. Sean Morrison’s laboratory in November 2015, found that the rare skin cancer cells that were able to detach from the primary tumor and successfully metastasize to other parts of the body had the ability to keep ROS levels from getting dangerously high,” Dr. DeBerardinis said. Dr. Morrison, also a CPRIT Scholar in Cancer Research and a Howard Hughes Medical Institute Investigator, holds the Mary McDermott Cook Chair in Pediatrics Genetics at UT Southwestern.
Working under the premise that the two findings were pieces of the same puzzle, a crucial part of the picture seemed to be missing, he said.
It was known for decades that the PPP was a major source of NADPH, which provides a source of reducing equivalents (that is, electrons) to scavenge ROS; however, the PPP produces NADPH in a part of the cell called the cytosol, whereas the reactive oxygen species are generated primarily in another subcellular structure called the mitochondria.
“If you think of ROS as fire, then NADPH is like the water used by cancer cells to douse the flames,” Dr. DeBerardinis said. But how could NADPH from the PPP help deal with the stress of ROS produced in a completely different part of the cell? “What we did was to discover how this happens,” Dr. DeBerardinis said.
The current study in Nature demonstrates that cancer cells use a “piggybacking” system to carry reducing equivalents from the PPP into the mitochondria. This movement involves an unusual reaction in the cytosol that transfers reducing equivalents from NADPH to a molecule called citrate, similar to a reversed reaction of the Krebs cycle, he said. The citrate then enters the mitochondria and stimulates another pathway that results in the release of reducing equivalents to produce NADPH right at the location of ROS creation, allowing the cancer cells to survive and grow without the benefit of matrix attachment.
“We knew that both the PPP and Krebs cycle provide metabolic benefits to cancer cells. But we had no idea that they were linked in this unusual fashion,” he said. “Strikingly, normal cells were unable to transport NADPH by this mechanism, and died as a result of the high ROS levels.”
Dr. DeBerardinis stressed that the findings were based on cultured cell models, and more research will be necessary to test the role of the pathway in living organisms. “We are particularly excited to test whether this pathway is required for metastasis, because cancer cells need to survive in a matrix-detached state in the circulation in order to metastasize,” he said.
A paper appearing in this week’s edition of the journal Nature by a team of researchers that includes University of Notre Dame biologist Zachary T. Schafer has important new implications for understanding the metabolism of tumors.
Schafer, an assistant professor of biological sciences and Coleman Junior Chair of Cancer Biology, points out that in the early stages of tumor formation some cells become detached from their normal cellular matrix. These “homeless” cells tend to develop certain defects that stop them from becoming cancerous. In a process known as apoptosis, these precancerous cells essentially kill themselves, allowing them to be destroyed by immune system cells.
The prevailing wisdom among researchers has been that apoptosis was the only way that cells could die.
In studies conducted prior to the research described in the Nature paper, it was found that even when apoptosis was inhibited in detached, precancerous cells, they still eventually died. Intrigued by these results, a team of researchers led by Joan S. Brugge, Louise Foote Pfieffer Professor of Cell Biology at Harvard Medical School, and Schafer decided to take a closer look.
They report in this week’s Nature paper that they found that even when apoptosis was inhibited in detached cells endowed with a cancer-causing gene, they still were incapable of absorbing glucose, their primary energy source. Additionally, the cells displayed signs of oxidative stress, which is a harmful accumulation of oxygen-derived molecules called reactive oxygen species (ROS). The research also revealed decreased ATP production, a key factor in energy transport in the cells.
Schafer notes that this combination of loss of glucose transport, decreased ATP production and heightened oxidative stress reveal a manner of cell death that hadn’t been previously demonstrated to play a role in this context.
In the next phase of the study, Schafer engineered the cells to express a high level of HER2, a gene known to be hyperactive in many breast cancer tumors. He also treated the cells with antioxidants to relieve oxidative stress.
Both approaches helped the cells survive. The HER2-treated cells regained glucose transport, avoided oxidative stress and recovered ATP levels.
Most surprisingly, the antioxidants restored metabolic activity in the cells by allowing fatty acids to be effectively used instead of glucose as an energy source, providing them with a chance to survive.
“Our results raise the possibility that antioxidant activity might allow early stage tumor cells to survive where they would otherwise die from these metabolic defects,” Schafer said.
He also cautions that while the antioxidant findings were surprising, their research was done solely in cell cultures and more research needs to be done before there are clear implications for individuals and their diets.
The paper does, however, offer important new clues about the metabolism of tumor cells and important information that may lead to drugs that can developed to target them.
http://www.nature.com/cdd/journal/v10/n8/full/4401251a.html Proteasome inhibitors have been shown to be effective in cancer treatment, an ability … a specific inhibitor of 26S proteasome, also reduced cell viability ( 80% with 10 mu …
be a consequence of the increased generation of ROS caused by MG132. …. vectors endowed with the wild type forms of RB or p53 genes (Figure 1f).
The Metastasis-Promoting Roles of Tumor-Associated Immune Cells
Tumor metastasis is driven not only by the accumulation of intrinsic alterations in malignant cells, but also by the interactions of cancer cells with various stromal cell components of the tumor microenvironment. In particular, inflammation and infiltration of the tumor tissue by host immune cells, such as tumor-associated macrophages, myeloid-derived suppressor cells, and regulatory T cells have been shown to support tumor growth in addition to invasion and metastasis. Each step of tumor development, from initiation through metastatic spread, is promoted by communication between tumor and immune cells via the secretion of cytokines, growth factors and proteases that remodel the tumor microenvironment. Invasion and metastasis requires neovascularization, breakdown of the basement membrane, and remodeling of the extracellular matrix for tumor cell invasion and extravasation into the blood and lymphatic vessels. The subsequent dissemination of tumor cells to distant organ sites necessitates a treacherous journey through the vasculature, which is fostered by close association with platelets and macrophages. Additionally, the establishment of the pre-metastatic niche and specific metastasis organ tropism is fostered by neutrophils and bone marrow-derived hematopoietic immune progenitor cells and other inflammatory cytokines derived from tumor and immune cells, which alter the local environment of the tissue to promote adhesion of circulating tumor cells. This review focuses on the interactions between tumor cells and immune cells recruited to the tumor microenvironment, and examines the factors allowing these cells to promote each stage of metastasis.
Once established, tumors are quite adept at preventing anti-tumor immune responses, and several defense mechanisms to circumvent immune detection have been described including antigen loss, down-regulation of major histocompatibility molecules (MHC), deregulation or loss of components of the endogenous antigen presentation pathway, and tumor-induced immune suppression mediated through cytokine secretion or direct interactions between tumor ligands and immune cell receptors [2]. These mechanisms contribute to the process of immunoediting in which tumor cell subpopulations susceptible to immune recognition are lysed and eliminated, while resistant tumor cells proliferate and increase their frequency in the developing neoplasia [3]. However, tumors not only effectively escape immune recognition, they also actively subvert the normal anti-tumor activity of immune cells to promote further tumor growth and metastasis.
During early stages of cancer development, infiltrating immune cell populations are primarily tumor suppressive, but depending on the presence of accessory stromal cells, the local cytokine milieu, and tumor-specific interactions, these immune cells can undergo phenotypic changes to enhance tumor cell dissemination and metastasis. For instance, CD4+ T cells, macrophages, and neutrophils have all been shown to possess opposing properties depending on the inflammatory state of the tumor environment, the tissue context, and other cellular stimuli intrinsic to the altered tumor cells [4, 5]. These features are dependent upon the inherent plasticity of immune cells in response to stimulatory or suppressive cytokines [6]. Notably, the switch from a Th1 tumor-suppressive phenotype such as CD4+ “helper” T cells, which aid cytotoxic CD8+ T cells in tumor rejection, to a Th2 tumor-promoting “regulatory” phenotype, which blocks CD8+ T-cell activity, is a characteristic outcome in the inflammatory, immune-suppressive tumor microenvironment [5, 7]. Likewise, M1 macrophages and N1 neutrophils are known to have pronounced anti-tumor activity; however, these immune cells are often subverted to a tumor-promoting M2 and N2 phenotype, respectively, in response to immune-suppressive cytokines secreted by tumor tissue [8].
The crosstalk that occurs between tumor and immune cells within the tumor microenvironment, the circulation, or at distant metastatic sites has been clearly shown to foster metastatic dissemination. Immune cells as well as the suppressive factors that they secrete represent potential targets for therapeutic intervention. Regardless of their source, cytokines, chemokines, proteases, and growth factors are some of the main factors contributing to immunosuppression and immune-mediated tumor progression. These molecules can be produced by immune, stromal, or malignant cells and can act in paracrine and autocrine fashion to promote each stage of tumor cell invasion and metastasis by enhancing inflammation, angiogenesis, tumor proliferation, and recruitment of additional immunosuppressive and tumor-promoting immune cells. These secreted factors provide the malignant cells with an abundant source of growth and survival signals that perpetuate a supportive microenvironment for tumor metastasis and represent some of the most attractive targets for directed anti-tumor therapy. Immune pathways provide numerous soluble targets for cancer treatment, and indeed, many drugs to target immune-suppressive molecules are moving forward in clinical trials. For instance, the anti-RANKL (Denosumab) antibody has been shown to effectively inhibit bone metastasis in prostate cancer patients [201], while a variety of neutralizing antibodies to IL-1β and IL-1 receptor have been shown to have efficacy in treating metastasis in pre-clinical animal models [202]. Several agents that target IL-1 or other immune-suppressive cytokines are already approved for the treatment of some inflammatory diseases and are prime candidates for human trails [202]. Additionally, other proteins involved in tumor progression that are induced directly or indirectly by immune cell populations, such as EMT-associated transcription factors, adhesion molecules, and tumor receptors and ligands which mediate immune suppression, could also be targeted with small molecules or blocking antibodies. Antibodies against two surface molecules expressed by suppressive lymphoid cells, anti-CTLA-4 (ipiliumimab) [203, 204] and anti-PD-1 have been recently gaining increasing support from clinical trials for their effective treatment for many forms of cancer including advanced melanoma and prostate cancer [205, 206]. Specifically, anti-CTLA-4 has been shown to be particularly efficacious in metastatic melanoma, while anti-PD-1 has only just begun a comprehensive evaluation in clinical trials [204, 207]. Likewise, non-steroidal anti-inflammatory drugs (NSAIDS) to prevent or treat chronic inflammation and lymphangiogenesis [208–210], and anti-coagulants to prevent platelet aggregation on circulating tumor cells [211] are just two examples of a multitude of therapeutic agents that could be utilized to prevent immune-mediated tumor progression at unique stages of metastasis. Of course, new methods or biomarkers for the detection of patients at risk of tumor progression or metastasis are also desperately needed to tailor personalized therapy for patients to obtain the best possible clinical outcome.
https://pharmaceuticalintelligence.com/category/cancer-and-therapeutics/Mar 26, 2016 … This turns your immune systems ability to attack and kill cancer cells back on” …. the rare skin cancer cells that were able to detach from theprimary tumor and successfully metastasize to other parts of the body had the ability to keep ROSlevels from getting dangerously high,” Dr. DeBerardinis remarked.
https://pharmaceuticalintelligence.com/tag/histone-deacetylase-inhibitors-hdac/The HDAC-inhibiting agent romidepsin significantly increased T-cell tumor … skin cancer cells that were able to detach from the primary tumor and successfully … of the body had the ability to keep ROS levels from getting dangerously high,” Dr. …. Sensitivity for EGFR or KRAS was higher in patients with multiplemetastatic …
Proteome Sciences plc has strongly encouraged by two recent reports that emphasise the importance of protein profiling to improve outcomes in cancer treatment. These highlight the growing need for more detailed, personal assessment of protein profiles to improve the management of cancer treatment.
In the first study two groups from University College London and Cancer Research UK demonstrated that genetic mutations in cancer can lead to changes in the proteins on the cell surface1. These are new sequences which are seen as foreign by the body’s immune system and, with appropriate immunotherapy, the level of response in lung cancer was greatly enhanced.
However many of the patients with these types of mutations unfortunately still did not respond which highlighted the need for deeper analysis of the protein expression in tumours in order to better appreciate the mechanisms that contribute to treatment failure.
The second study, led by Professor Nigel Bundred of Manchester University, reported that use of two drugs that act on the same breast cancer target, an over-expressing protein called Her-2, were able to eradicate detectable tumours in around 10% of those treated in just 11 days, with 87% of those treated having a proteomic change indicating cells had stopped growing and/or cell death had increased2.
Whilst these results appear very promising it is worth noting that the over-expressing Her-2 target is only present in about 20% of breast tumours meaning this combination therapy was successful in clearing tumours in just 2% of the total breast cancer population.
Dr. Ian Pike, Chief Operating Officer of Proteome Sciences commented, “Both these recent studies should rightly be recognised as important steps forward towards better cancer treatment. However, in order to overcome the limitations of current drug therapy programs, a much deeper and more comprehensive analysis of the complex protein networks that regulate tumour growth and survival is required and will be essential to achieve a major advance in the battle to treat cancer.
“Our SysQuant® workflows provide that solution. As an example, in pancreatic cancer3 we have successfully mapped the complex network of regulatory processes and demonstrate the ability to devise personalised treatment combinations on an individual basis for each patient. A retrospective study with SysQuant® to predict response to the targeted drug Sorafenib in liver cancer is in process and we are planning further prospective trials to guide personalised treatment selection in liver cancer.
“We are already delivering systems-wide biology solutions through SysQuant® and TMTcalibrator™ programs to our clients that are generating novel biological data and results using more sensitive profiling that are helping them to better understand their drug development programs and to provide new biomarkers for tracking patient response in clinical trials.
“We are strongly positioned to deliver more comprehensive analysis of proteins and cellular pathways across other areas of disease and in particular to extend the use of SysQuant® with other leading cancer research groups in liver and other cancers.”
Proteome Sciences has also expanded its offering in personalised medicine through the use of its TMTcalibrator™ technology to uniquely identify protein biomarkers that reveal active cancer and other disease processes in body fluid samples. The importance of these ‘mechanistic’ biomarkers is that they are essential to monitor that drugs are being effective and that they can be used as early biomarkers of disease recurrence.
Using SysQuant® and TMTcalibrator™, Proteome Sciences can deliver more comprehensive analysis and provide unparalleled levels of sensitivity and breadth of coverage of the proteome, enabling faster, more efficient drug development and more accurate disease diagnosis.
Discovering ‘Outlier’ Enzymes
Researchers at TSRI and Salk Institute have discovered ‘Outlier’ enzymes that could offer new targets to treat type 2 diabetes and inflammatory disorders.
A team led by scientists at The Scripps Research Institute (TSRI) and the Salk Institute for Biological Studies have discovered two enzymes that appear to play a role in metabolism and inflammation—and might someday be targeted with drugs to treat type 2 diabetes and inflammatory disorders. The discovery is unusual because the enzymes do not bear a resemblance—in their structures or amino-acid sequences—to any known class of enzymes.
The team of scientists nevertheless identified them as “outlier” members of the serine/threonine hydrolase class, using newer techniques that detect biochemical activity. “A huge fraction of the human ‘proteome’ remains uncharacterized, and this paper shows how chemical approaches can be used to uncover proteins of a given functionality that have eluded classification based on sequence or predicted structure,” said co-senior author Benjamin F. Cravatt, chair of TSRI’s Department of Chemical Physiology.
“In this study, we found two genes that control levels of lipids with anti-diabetic and anti-inflammatory activity, suggesting exciting targets for diabetes and inflammatory diseases,” said co-senior author Alan Saghatelian, who holds the Dr. Frederik Paulsen Chair at the Salk Institute. The study, which appeared as a Nature Chemical Biology Advance Online Publication on March 28, 2016, began as an effort in the Cravatt laboratory to discover and characterize new serine/threonine hydrolases using fluorophosphonate (FP) probes—molecules that selectively bind and, in effect, label the active sites of these enzymes.
Pulling FP-binding proteins out of the entire proteome of test cells and identifying them using mass spectrometry techniques, the team matched nearly all to known hydrolases. The major outlier was a protein called androgen-induced gene 1 protein (AIG1). The only other one was a distant cousin in terms of sequence, a protein called ADTRP. “Neither of these proteins had been characterized as an enzyme; in fact, there had been little functional characterization of them at all,” said William H. Parsons, a research associate in the Cravatt laboratory who was co-first author of the study.
Experiments on AIG1 and ADTRP revealed that they do their enzymatic work in a unique way. “It looks like they have an active site that is novel—it had never been described in the literature,” said Parsons. Initial tests with panels of different enzyme inhibitors showed that AIG1 and ADTRP are moderately inhibited by inhibitors of lipases—enzymes that break down fats and other lipids. But on what specific lipids do these newly discovered outlier enzymes normally work?
At the Salk Institute, the Saghatelian laboratory was investigating a class of lipids it had discovered in 2014. Known as fatty acid esters of hydroxy fatty acids (FAHFAs), these molecules showed strong therapeutic potential. Saghatelian and his colleagues had found that boosting the levels of one key FAHFA lipid normalizes glucose levels in diabetic mice and also reduces inflammation.
“[Ben Cravatt’s] lab was screening panels of lipids to find the ones that their new enzymes work on,” said Saghatelian, who is a former research associate in the Cravatt laboratory. “We suggested they throw FAHFAs in there—and these turned out to be very good substrates.” The Cravatt laboratory soon developed powerful inhibitors of the newly discovered enzymes, and the two labs began working together, using the inhibitors and genetic techniques to explore the enzymes’ functions in vitro and in cultured cells.
Co-first author Matthew J. Kolar, an MD-PhD student, performed most of the experiments in the Saghatelian lab. The team concluded that AIG1 and ADTRP, at least in the cell types tested, appear to work mainly to break down FAHFAs and not any other major class of lipid. In principle, inhibitors of AIG1 and ADTRP could be developed into FAHFA-boosting therapies.
“Our prediction,” said Saghatelian, “is that if FAHFAs do what we think they’re doing, then using an enzyme inhibitor to block their degradation would make FAHFA levels go up and should thus reduce inflammation as well as improve glucose levels and insulin sensitivity.” The two labs are now collaborating on further studies of the new enzymes—and the potential benefits of inhibiting them—in mouse models of diabetes, inflammation and autoimmune disease.
“One of the neat things this study shows,” said Cravatt, “is that even for enzyme classes as well studied as the hydrolases, there may still be hidden members that, presumably by convergent evolution, arrived at that basic enzyme mechanism despite sharing no sequence or structural homology.”
Other co-authors of the study, “AIG1 and ADTRP are atypical integral membrane hydrolases that degrade bioactive FAHFAs,” were Siddhesh S. Kamat, Armand B. Cognetta III, Jonathan J. Hulce and Enrique Saez, of TSRI; and co-senior author Barbara B. Kahn of Beth Israel Deaconess Medical Center and Harvard Medical School
New Weapon Against Breast Cancer
Molecular marker in healthy tissue can predict a woman’s risk of getting the disease, research says.
Harvard Stem Cell Institute (HSCI) researchers at Dana-Farber Cancer Institute (DFCI) and collaborators at Brigham and Women’s Hospital (BWH) have identified a molecular marker in normal breast tissue that can predict a woman’s risk for developing breast cancer, the leading cause of death in women with cancer worldwide.
The work, led by HSCI principal faculty member Kornelia Polyak and Rulla Tamimi of BWH, was published in an early online release and in the April 1 issue of Cancer Research.
The study builds on Polyak’s earlier research finding that women already identified as having a high risk of developing cancer — namely those with a mutation called BRCA1 or BRCA2 — or women who did not give birth before their 30s had a higher number of mammary gland progenitor cells.
In the latest study, Polyak, Tamimi, and their colleagues examined biopsies, some taken as many as four decades ago, from 302 participants in the Nurses’ Health Study and the Nurses’ Health Study II who had been diagnosed with benign breast disease. The researchers compared tissue from the 69 women who later developed cancer to the tissue from the 233 women who did not. They found that women were five times as likely to develop cancer if they had a higher percentage of Ki67, a molecular marker that identifies proliferating cells, in the cells that line the mammary ducts and milk-producing lobules. These cells, called the mammary epithelium, undergo drastic changes throughout a woman’s life, and the majority of breast cancers originate in these tissues.
Doctors already test breast tumors for Ki67 levels, which can inform decisions about treatment, but this is the first time scientists have been able to link Ki67 to precancerous tissue and use it as a predictive tool.
“Instead of only telling women that they don’t have cancer, we could test the biopsies and tell women if they were at high risk or low risk for developing breast cancer in the future,” said Polyak, a breast cancer researcher at Dana-Farber and co-senior author of the paper.
“Currently, we are not able to do a very good job at distinguishing women at high and low risk of breast cancer,” added co-senior author Tamimi, an associate professor at the Harvard T.H. Chan School of Public Health and Harvard Medical School. “By identifying women at high risk of breast cancer, we can better develop individualized screening and also target risk reducing strategies.”
To date, mammograms are the best tool for the early detection, but there are risks associated with screening. False positive and negative results and over-diagnosis could cause psychological distress, delay treatment, or lead to overtreatment, according to the National Cancer Institute (NCI).
Mammography machines also use low doses of radiation. While a single mammogram is unlikely to cause harm, repeated screening can potentially cause cancer, though the NCI writes that the benefits “nearly always outweigh the risks.”
“If we can minimize unnecessary radiation for women at low risk, that would be good,” said Tamimi.
Screening for Ki67 levels would “be easy to apply in the current setting,” said Polyak, though the researchers first want to reproduce the results in an independent cohort of women.
AIG1 and ADTRP are atypical integral membrane hydrolases that degrade bioactive FAHFAs
Enzyme classes may contain outlier members that share mechanistic, but not sequence or structural, relatedness with more common representatives. The functional annotation of such exceptional proteins can be challenging. Here, we use activity-based profiling to discover that the poorly characterized multipass transmembrane proteins AIG1 and ADTRP are atypical hydrolytic enzymes that depend on conserved threonine and histidine residues for catalysis. Both AIG1 and ADTRP hydrolyze bioactive fatty acid esters of hydroxy fatty acids (FAHFAs) but not other major classes of lipids. We identify multiple cell-active, covalent inhibitors of AIG1 and show that these agents block FAHFA hydrolysis in mammalian cells. These results indicate that AIG1 and ADTRP are founding members of an evolutionarily conserved class of transmembrane threonine hydrolases involved in bioactive lipid metabolism. More generally, our findings demonstrate how chemical proteomics can excavate potential cases of convergent or parallel protein evolution that defy conventional sequence- and structure-based predictions.
Figure 1: Discovery and characterization of AIG1 and ADTRP as FP-reactive proteins in the human proteome.
(a) Competitive ABPP-SILAC analysis to identify FP-alkyne-inhibited proteins, in which protein enrichment and inhibition were measured in proteomic lysates from SKOV3 cells treated with FP-alkyne (20 μM, 1 h) or DMSO using the FP-biotin…
Willems, L.I., Overkleeft, H.S. & van Kasteren, S.I.Current developments in activity-based protein profiling. Bioconjug. Chem.25, 1181–1191 (2014).
Berger, A.B., Vitorino, P.M. & Bogyo, M.Activity-based protein profiling: applications to biomarker discovery, in vivo imaging and drug discovery. Am. J. Pharmacogenomics4,371–381 (2004).
Simon, G.M. & Cravatt, B.F.Activity-based proteomics of enzyme superfamilies: serine hydrolases as a case study. J. Biol. Chem.285, 11051–11055 (2010).
National Institutes of Health (NIH)-sponsored screening centers provide academic researchers with a special opportunity to pursue small-molecule probes for protein targets that are outside the current interest of, or beyond the standard technologies employed by, the pharmaceutical industry. Here, we describe the outcome of an inhibitor screen for one such target, the enzyme protein phosphatase methylesterase-1 (PME-1), which regulates the methylesterification state of protein phosphatase 2A (PP2A) and is implicated in cancer and neurodegeneration. Inhibitors of PME-1 have not yet been described, which we attribute, at least in part, to a dearth of substrate assays compatible with high-throughput screening. We show that PME-1 is assayable by fluorescence polarization-activity-based protein profiling (fluopol-ABPP) and use this platform to screen the 300,000+ member NIH small-molecule library. This screen identified an unusual class of compounds, the aza-β-lactams (ABLs), as potent (IC50 values of approximately 10 nM), covalent PME-1 inhibitors. Interestingly, ABLs did not derive from a commercial vendor but rather an academic contribution to the public library. We show using competitive-ABPP that ABLs are exquisitely selective for PME-1 in living cells and mice, where enzyme inactivation leads to substantial reductions in demethylated PP2A. In summary, we have combined advanced synthetic and chemoproteomic methods to discover a class of ABL inhibitors that can be used to selectively perturb PME-1 activity in diverse biological systems. More generally, these results illustrate how public screening centers can serve as hubs to create spontaneous collaborative opportunities between synthetic chemistry and chemical biology labs interested in creating first-in-class pharmacological probes for challenging protein targets.
Protein phosphorylation is a pervasive and dynamic posttranslational protein modification in eukaryotic cells. In mammals, more than 500 protein kinases catalyze the phosphorylation of serine, threonine, and tyrosine residues on proteins (1). A much more limited number of phosphatases are responsible for reversing these phosphorylation events (2). For instance, protein phosphatase 2A (PP2A) and PP1 are thought to be responsible together for > 90% of the total serine/threonine phosphatase activity in mammalian cells (3). Specificity is imparted on PP2A activity by multiple mechanisms, including dynamic interactions between the catalytic subunit (C) and different protein-binding partners (B subunits), as well as a variety of posttranslational chemical modifications (2, 4). Within the latter category is an unusual methylesterification event found at the C terminus of the catalytic subunit of PP2A that is introduced and removed by a specific methyltransferase (leucine carbxoylmethyltransferase-1 or LCMT1) (5, 6) and methylesterase (protein phosphatase methylesterase-1 or PME-1) (7), respectively (Fig. 1A). PP2A carboxymethylation (hereafter referred to as “methylation”) has been proposed to regulate PP2A activity, at least in part, by modulating the binding interaction of the C subunit with various regulatory B subunits (8–10). A predicted outcome of these shifts in subunit association is the targeting of PP2A to different protein substrates in cells. PME-1 has also been hypothesized to stabilize inactive forms of nuclear PP2A (11), and recent structural studies have shed light on the physical interactions between PME-1 and the PP2A holoenzyme (12).
There were several keys to the success of our probe development effort. First, screening for inhibitors of PME-1 benefited from the fluopol-ABPP technology, which circumvented the limited throughput of previously described substrate assays for this enzyme. Second, we were fortunate that the NIH compound library contained several members of the ABL class of small molecules. These chiral compounds, which represent an academic contribution to the NIH library, occupy an unusual portion of structural space that is poorly accessed by commercial compound collections. Although at the time of their original synthesis (23) it may not have been possible to predict whether these ABLs would show specific biological activity, their incorporation into the NIH library provided a forum for screening against many proteins and cellular targets, culminating in their identification as PME-1 inhibitors. We then used advanced chemoproteomic assays to confirm the remarkable selectivity displayed by ABLs for PME-1 across (and beyond) the serine hydrolase superfamily. That the mechanism for PME-1 inhibition involves acylation of the enzyme’s conserved serine nucleophile (Fig. 3) suggests that exploration of a more structurally diverse set of ABLs might uncover inhibitors for other serine hydrolases. In this way, the chemical information gained from a single high-throughput screen may be leveraged to initiate probe development programs for additional enzyme targets.
Projecting forward, this research provides an example of how public small-molecule screening centers can serve as a portal for spawning academic collaborations between chemical biology and synthetic chemistry labs. By continuing to develop versatile high-throughput screens and combining them with a small-molecule library of expanding structural diversity conferred by advanced synthetic methodologies, academic biologists and chemists are well-positioned to collaboratively deliver pharmacological probes for a wide range of proteins and pathways in cell biology.
The frequency and proliferative activity of tissue-specific stem and progenitor cells are suggested to correlate with cancer risk. In this study, we investigated the association between breast cancer risk and the frequency of mammary epithelial cells expressing p27, estrogen receptor (ER), and Ki67 in normal breast tissue. We performed a nested case-control study of 302 women (69 breast cancer cases, 233 controls) who had been initially diagnosed with benign breast disease according to the Nurses’ Health Studies. Immunofluorescence for p27, ER, and Ki67 was performed on tissue microarrays constructed from benign biopsies containing normal mammary epithelium and scored by computational image analysis. We found that the frequency of Ki67+ cells was positively associated with breast cancer risk among premenopausal women (odds ratio [OR]=10.1, 95% confidence interval [CI]=2.12-48.0). Conversely, the frequency of ER+ or p27+ cells was inversely, but not significantly, associated with subsequent breast cancer risk (ER+: OR=0.70, 95% CI=0.33-1.50; p27+: OR=0.89, 95% CI=0.45-1.75). Notably, high Ki67+/low p27+ and high Ki67+/low ER+ cell frequencies were significantly associated with a 5-fold higher risk of breast cancer compared to low Ki67+/low p27+ and low Ki67+/low ER+ cell frequencies, respectively, among premenopausal women (Ki67hi/p27lo: OR=5.08, 95% CI=1.43-18.1; Ki67hi/ERlo: OR=4.68, 95% CI=1.63-13.5). Taken together, our data suggest that the fraction of actively cycling cells in normal breast tissue may represent a marker for breast cancer risk assessment, which may therefore impact the frequency of screening procedures in at-risk women.
Scientists have discovered a group of six proteins that may help to divulge secrets of how we age, potentially unlocking new insights into diabetes, Alzheimer’s, cancer, and other aging-related diseases.
The proteins appear to play several roles in our bodies’ cells, from decreasing the amount of damaging free radicals and controlling the rate at which cells die to boosting metabolism and helping tissues throughout the body respond better to insulin. The naturally occurring amounts of each protein decrease with age, leading investigators to believe that they play an important role in the aging process and the onset of diseases linked to older age.
The research team led by Pinchas Cohen, M.D., dean and professor of the University of Southern California Leonard Davis School of Gerontology, identified the proteins and observed their origin from mitochondria and their game-changing roles in metabolism and cell survival. This latest finding builds upon prior research by Dr. Cohen and his team that uncovered two significant proteins, humanin and MOTS-c, hormones that appear to have significant roles in metabolism and diseases of aging.
Unlike most other proteins, humanin and MOTS-c are encoded in mitochondria. Dr. Cohen’s team used computer analysis to see if the part of the mitochondrial genome that provides the code for humanin was coding for other proteins as well. The analysis uncovered the genes for six new proteins, which were dubbed small humanin-like peptides, or SHLPs, 1 through 6 (pronounced “schlep”).
After identifying the six SHLPs and successfully developing antibodies to test for several of them, the team examined both mouse tissues and human cells to determine their abundance in different organs as well as their functions. The proteins were distributed quite differently among organs, which suggests that the proteins have varying functions based on where they are in the body. Of particular interest is SHLP 2, according to Dr. Cohen. The protein appears to have insulin-sensitizing, antidiabetic effects as well as neuroprotective activity that may emerge as a strategy to combat Alzheimer’s disease. He added that SHLP 6 is also intriguing, with a unique ability to promote cancer cell death and thus potentially target malignant diseases.
Proteins That May Protect Against Age Related Illnesses Discovered
Tested in both mice and human cells, the proteins may lead to greater understanding of aging-related diseases, from diabetes to Alzheimer’s to cancer, according to researchers at USC Davis School of Gerontology who led the study.
Researchers have identified a group of six proteins that they believe may divulge secrets of how we age and unlock new insights into diabetes, Alzheimer’s, cancer, and other aging-related diseases.
Nicknamed “Schlep” or “SHLP” for “small humanin-like peptides,” these proteins appear to play several big roles in our bodies’ cells, from decreasing the amount of damaging free radicals and controlling the rate at which cells die, to boosting metabolism and helping tissues throughout the body respond better to insulin. The naturally occurring amounts of each protein decrease with age, leading researchers to believe that they play an important role in the aging process and the onset of age-related diseases.
The research team led by Pinchas Cohen, dean and professor of the USC Leonard Davis School of Gerontology, identified the tiny proteins for the first time and observed their surprising origin: organelles in the cell called mitochondria and their game-changing roles in metabolism and cell survival.
This latest finding builds upon prior research by Cohen and his team that uncovered two significant proteins, humanin and MOTS-c, hormones that appear to have significant roles in metabolism and diseases of aging.
The cell proliferation antigen Ki-67 organises heterochromatin
MichalSobecki,
KarimMrouj
Montpellier Institute of Molecular Genetics (IGMM) CNRS UMR 5535, Centre National de la Recherche Scientifique (CNRS), Montpellier, France; Faculty of Sciences, University of Montpellier, Montpellier, France
Contribution: Acquisition of data, Analysis and interpretation of data, Drafting or revising the article
No competing interests declared
</div>”>KarimMrouj,
AlainCamasses
Montpellier Institute of Molecular Genetics (IGMM) CNRS UMR 5535, Centre National de la Recherche Scientifique (CNRS), Montpellier, France; Faculty of Sciences, University of Montpellier, Montpellier, France
Contribution: Conception and design, Acquisition of data, Analysis and interpretation of data
No competing interests declared
</div>”>AlainCamasses,
NikolaosParisis
Montpellier Institute of Molecular Genetics (IGMM) CNRS UMR 5535, Centre National de la Recherche Scientifique (CNRS), Montpellier, France; Faculty of Sciences, University of Montpellier, Montpellier, France
Contribution: Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article
RNA Molecular Biology, Center for Microscopy and Molecular Imaging, Fonds de la Recherche Nationale, Université Libre de Bruxelles, Charleroi-Gosselies, Belgium
Contribution: Conception and design, Acquisition of data, Analysis and interpretation of data
Antigen Ki-67 is a nuclear protein expressed in proliferating mammalian cells. It is widely used in cancer histopathology but its functions remain unclear. Here, we show that Ki-67 controls heterochromatin organisation. Altering Ki-67 expression levels did not significantly affect cell proliferation in vivo. Ki-67 mutant mice developed normally and cells lacking Ki-67 proliferated efficiently. Conversely, upregulation of Ki-67 expression in differentiated tissues did not prevent cell cycle arrest. Ki-67 interactors included proteins involved in nucleolar processes and chromatin regulators. Ki-67 depletion disrupted nucleologenesis but did not inhibit pre-rRNA processing. In contrast, it altered gene expression. Ki-67 silencing also had wide-ranging effects on chromatin organisation, disrupting heterochromatin compaction and long-range genomic interactions. Trimethylation of histone H3K9 and H4K20 was relocalised within the nucleus. Finally, overexpression of human or Xenopus Ki-67 induced ectopic heterochromatin formation. Altogether, our results suggest that Ki-67 expression in proliferating cells spatially organises heterochromatin, thereby controlling gene expression.
A protein called Ki-67 is only produced in actively dividing cells, where it is located in the nucleus – the structure that contains most of the cell’s DNA. Researchers often use Ki-67 as a marker to identify which cells are actively dividing in tissue samples from cancer patients, and previous studies indicated that Ki-67 is needed for cells to divide. However, the exact role of this protein was not clear. Before cells can divide they need to make large amounts of new proteins using molecular machines called ribosomes and it has been suggested that Ki-67 helps to produce ribosomes.
Now, Sobecki et al. used genetic techniques to study the role of Ki-67 in mice. The experiments show that Ki-67 is not required for cells to divide in the laboratory or to make ribosomes. Instead, Ki-67 alters the way that DNA is packaged in the nucleus. Loss of Ki-67 from mice cells resulted in DNA becoming less compact, which in turn altered the activity of genes in those cells.
Article Info
2012pharmaceutical
sjwilliamspa
This is a lovely method and should find wide applicability in many settings, especially for microorganisms and cell lines. However, it is not clear that this approach will be, as implied by the discussion, an efficient mapping method for all multicellular organisms. I have performed similar experiments in Drosophila, focused on meiotic recombination, on a much smaller scale, and found that CRISPR-Cas9 can indeed generate targeted recombination at gRNA target sites. In every case I tested, I found that the recombination event was associated with a deletion at the gRNA site, which is probably unimportant for most mapping efforts, but may be a concern in some specific cases, for example for clinical applications. It would be interesting to know how often mutations occurred at the targeted gRNA site in this study.
The wider issue, however, is whether CRISPR-mediated recombination will be more efficient than other methods of mapping. After careful consideration of all the costs and the time involved in each of the steps for Drosophila, we have decided that targeted meiotic recombination using flanking visible markers will be, in most cases, considerably more efficient than CRISPR-mediated recombination. This is mainly due to the large expense of injecting embryos and the extensive effort and time required to screen injected animals for appropriate events. It is both cheaper and faster to generate markers (with CRISPR) and then perform a large meiotic recombination mapping experiment than it would be to generate the lines required for CRISPR-mediated recombination mapping. It is possible to dramatically reduce costs by, for example, mapping sequentially at finer resolution. But this approach would require much more time than marker-assisted mapping. If someone develops a rapid and cheap method of reliably introducing DNA into Drosophila embryos, then this calculus might change.
However, it is possible to imagine situations where CRISPR-mediated mapping would be preferable, even for Drosophila. For example, some genomic regions display extremely low or highly non-uniform recombination rates. It is possible that CRISPR-mediated mapping could provide a reasonable approach to fine mapping genes in these regions.
The authors also propose the exciting possibility that CRISPR-mediated loss of heterozygosity could be used to map traits in sterile species hybrids. It is not entirely obvious to me how this experiment would proceed and I hope the authors can illuminate me. If we imagine driving a recombination event in the early embryo (with maternal Cas9 from one parent and gRNA from a second parent), then at best we would end up with chimeric individuals carrying mitotic clones. I don’t think one could generate diploid animals where all cells carried the same loss of heterozygosity event. Even if we could, this experiment would require construction of a substantial number of stable transgenic lines expressing gRNAs. Mapping an ~20Mbp chromosome arm to ~10kb would require on the order of two-thousand transgenic lines. Not an undertaking to be taken lightly. It is already possible to perform similar tests (hemizygosity tests) using D. melanogaster deficiency lines in crosses with D. simulans, so perhaps CRISPR-mediated LOH could complement these deficiency screens for fine mapping efforts. But, at the moment, it is not clear to me how to do the experiment.