Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 92,466 bioRxiv papers from 394,911 authors.
Most downloaded bioRxiv papers, all time
in category cancer biology
3,207 results found. For more information, click each entry to expand.
2,416 downloads cancer biology
Yu Kong, Chris Rose, Ashley A Cass, Martine Darwish, Steve Lianoglou, Pete M Haverty, Ann-Jay Tong, Craig Blanchette, Ira Mellman, Richard Bourgon, John Greally, Suchit Jhunjhunwala, Matthew L. Albert, Haiyin Chen-Harris
Profound loss of DNA methylation is a well-recognized hallmark of cancer. Given its role in silencing transposable elements (TEs), we hypothesized that extensive TE expression occurs in tumors with highly demethylated DNA. We developed REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observed increased expression of over 400 TE subfamilies, of which 262 appeared to result from a proximal loss of DNA methylation. The most recurrent TEs were among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent resulted in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing both inflammation and the display of potentially immunogenic neoantigens.
2,415 downloads cancer biology
One of the main goals of the Cancer Dependency Map project is to systematically identify cancer vulnerabilities across cancer types to accelerate therapeutic discovery. Project Achilles serves this goal through the in vitro study of genetic dependencies in cancer cell lines using CRISPR/Cas9 (and, previously, RNAi) loss-of-function screens. The project is committed to the public release of its experimental results quarterly on the DepMap Portal (https://depmap.org), on a pre-publication basis. As the experiment has evolved, data processing procedures have changed. Here we present the current and projected Achilles processing pipeline, including recent improvements and the analyses that led us to adopt them, spanning data releases from early 2018 to the first quarter of 2020. Notable changes include quality control metrics, calculation of probabilities of dependency, and correction for screen quality and other biases. Developing and improving methods for extracting biologically-meaningful scores from Achilles experiments is an ongoing process, and we will continue to evaluate and revise data processing procedures to produce the best results.
2,376 downloads cancer biology
Michael K Dame, Durga Attili, Shannon D McClintock, Priya H Dedhia, Peter Ouilette, Olaf Hardt, Alana M Chin, Xiang Xue, Julie Laliberte, Erica L Katz, Gina M Newsome, David R. Hill, Alyssa J. Miller, Yu-Hwai Tsai, David Agorku, Christopher H Altheim, Andreas Bosio, Becky Simon, Linda C Samuelson, Jay A Stoerker, Henry D Appelman, James Varani, Max S Wicha, Dean E Brenner, Yatrik M. Shah, Jason R. Spence, Justin A. Colacino
The intestine is maintained by stem cells located at the base of crypts and distinguished by the expression of LGR5. Genetically engineered mouse models have provided a wealth of information about intestinal stem cells, while less is known about human intestinal stem cells due to difficulty detecting and isolating these cells. We established an organoid repository from patient-derived adenomas, adenocarcinomas, and normal colon, which we analyzed for variants in 71 colorectal cancer (CRC) associated genes. Normal and neoplastic colon tissue organoids were analyzed by immunohistochemistry and fluorescent-activated cell sorting for LGR5. LGR5-positive cells were isolated from 4 adenoma organoid lines and were subjected to RNA-sequencing. We found that LGR5 expression in the epithelium and stroma was associated with tumor stage, and by integrating functional experiments with LGR5-sorted cell RNA-seq data from adenoma and normal organoids, we found correlations between LGR5 and CRC-specific genes, including DKK4 (dickkopf WNT signaling pathway inhibitor 4) and SMOC2 (SPARC related modular calcium binding 2). Collectively, this work provides resources, methods and new markers to isolate and study stem cells in human tissue homeostasis and carcinogenesis.
2,375 downloads cancer biology
Eszter Lakatos, Marc J. Williams, Ryan O. Schenck, William C. H. Cross, Jacob Househam, Benjamin Werner, Chandler Gatenbee, Mark Robertson-Tessi, Chris P. Barnes, Alexander R. A. Anderson, Andrea Sottoriva, Trevor A. Graham
Cancer evolution is driven by the acquisition of somatic mutations that provide cells with a beneficial phenotype in a changing microenvironment. However, mutations that give rise to neoantigens, novel cancer-specific peptides that elicit an immune response, are likely to be disadvantageous. Here we show how the clonal structure and immunogenotype of growing tumours is shaped by negative selection in response to neoantigenic mutations. We construct a mathematical model of neoantigen evolution in a growing tumour, and verify the model using genomic sequencing data. The model predicts that, in the absence of active immune escape mechanisms, tumours either evolve clonal neoantigens (antigen-'hot'), or have no clonally-expanded neoantigens at all (antigen-'cold'), whereas antigen-'warm' tumours (with high frequency subclonal neoantigens) form only following the evolution of immune evasion. Counterintuitively, strong negative selection for neoantigens during tumour formation leads to an increased number of antigen-warm or -hot tumours, as a consequence of selective pressure for immune escape. Further, we show that the clone size distribution under negative selection is effectively-neutral, and moreover, that stronger negative selection paradoxically leads to more neutral-like dynamics. Analysis of antigen clone sizes and immune escape in colorectal cancer exome sequencing data confirms these results. Overall, we provide and verify a mathematical framework to understand the evolutionary dynamics and clonality of neoantigens in human cancers that may inform patient-specific immunotherapy decision-making.
2,371 downloads cancer biology
Kiyomi Morita, Feng Wang, Katharina Jahn, Jack Kuipers, Yuanqing Yan, Jairo Matthews, Latasha Little, Curtis Gumbs, Shujuan Chen, Jianhua Zhang, Xingzhi Song, Erika Thompson, Keyur Patel, Carlos Bueso-Ramos, Courtney D. DiNardo, Farhad Ravandi, Elias Jabbour, Michael Andreeff, Jorge Cortes, Marina Konopleva, Kapil Bhalla, Guillermo Garcia-Manero, Hagop Kantarjian, Niko Beerenwinkel, Nicholas Navin, P. Andrew Futreal, Koichi Takahashi
One of the pervasive features of cancer is the diversity of mutations found in malignant cells within the same tumor; a phenomenon called clonal diversity or intratumor heterogeneity. Clonal diversity allows tumors to adapt to the selective pressure of treatment and likely contributes to the development of treatment resistance and cancer recurrence. Thus, the ability to precisely delineate the clonal substructure of a tumor, including the evolutionary history of its development and the co-occurrence of its mutations, is necessary to understand and overcome treatment resistance. However, DNA sequencing of bulk tumor samples cannot accurately resolve complex clonal architectures. Here, we performed high-throughput single-cell DNA sequencing to quantitatively assess the clonal architecture of acute myeloid leukemia (AML). We sequenced a total of 556,951 cells from 77 patients with AML for 19 genes known to be recurrently mutated in AML. The data revealed clonal relationship among AML driver mutations and identified mutations that often co-occurred (e.g., NPM1/FLT3-ITD, DNMT3A/NPM1, SRSF2/IDH2, and WT1/FLT3-ITD ) and those that were mutually exclusive (e.g., NRAS/KRAS, FLT3 -D835/ITD, and IDH1/IDH2 ) at single-cell resolution. Reconstruction of the tumor phylogeny uncovered history of tumor development that is characterized by linear and branching clonal evolution patterns with latter involving functional convergence of separately evolved clones. Analysis of longitudinal samples revealed remodeling of clonal architecture in response to therapeutic pressure that is driven by clonal selection. Furthermore, in this AML cohort, higher clonal diversity (≥4 subclones) was associated with significantly worse overall survival. These data portray clonal relationship, architecture, and evolution of AML driver genes with unprecedented resolution, and illuminate the role of clonal diversity in therapeutic resistance, relapse and clinical outcome in AML.
2,369 downloads cancer biology
Poly-(ADP-ribose) polymerase (PARP) inhibitors (PARPis) have shown remarkable therapeutic efficacy against BRCA1/2 mutant cancers through a synthetic lethal interaction. PARPis are believed to exert their therapeutic effects mainly through the blockade of single-strand DNA damage repair, which leads to the accumulation of toxic DNA double strand breaks, specifically in cancer cells with DNA repair deficiency (BCRAness), including those harboring BRCA1/2 mutations. Here, we show that PARPis modulate immune reposes, which contribute to their therapeutic effects independent of BRCA1/2 mutations. The mechanism underlying this PARPi-induced reprogramming of anti-tumor microenvironment involves a promoted accumulation of cytosolic DNA fragments due to unresolved DNA lesions. This in turn activates the DNA sensing cGAS-STING pathway and stimulates production of type I interferons. Ultimately, these events promote PARPi-induced antitumor immunity independent of BRCAness, which can be further enhanced by immune checkpoint blockade. Our results may provide a mechanistic rationale for using PARPis as immunomodulatory agents to harness therapeutic efficacy of immune checkpoint blockade.
2,335 downloads cancer biology
Background & Aims: Pancreatic ductal adenocarcinoma (PDA) is a major cause of cancer-related death with limited therapeutic options available. This highlights the need for improved understanding of the biology of PDA progression. The progression of PDA is a highly complex and dynamic process featuring changes in cancer cells and stromal cells; however, a comprehensive characterization of PDA cancer cell and stromal cell heterogeneity during disease progression is lacking. In this study, we aimed to profile cell populations and understand their phenotypic changes during PDA progression. Methods: We employed single-cell RNA sequencing technology to agnostically profile cell heterogeneity during different stages of PDA progression in genetically engineered mouse models. Results: Our data indicate that an epithelial-to-mesenchymal transition of cancer cells accompanies tumor progression. We also found distinct populations of macrophages with increasing inflammatory features during PDA progression. In addition, we noted the existence of three distinct molecular subtypes of fibroblasts in the normal mouse pancreas, which ultimately gave rise to two distinct populations of fibroblasts in advanced PDA, supporting recent reports on intratumoral fibroblast heterogeneity. Our data also suggest that cancer cells and fibroblasts are dynamically regulated by epigenetic mechanisms. Conclusion: This study systematically outlines the landscape of cellular heterogeneity during the progression of PDA. It strongly improves our understanding of the PDA biology and has the potential to aid in the development of therapeutic strategies against specific cell populations of the disease.
2,328 downloads cancer biology
Lina Wadi, Liis Uusküla-Reimand, Keren Isaev, Shimin Shuai, Vincent Huang, Minggao Liang, J. Drew Thompson, Yao Li, Luyao Ruan, Marta Paczkowska, Michal Krassowski, Irakli Dzneladze, Ken Kron, Alexander Murison, Parisa Mazrooei, Robert G Bristow, Jared T Simpson, Mathieu Lupien, Michael D. Wilson, Lincoln D Stein, Paul C. Boutros, Jüri Reimand
A comprehensive catalogue of the mutations that drive tumorigenesis and progression is essential to understanding tumor biology and developing therapies. Protein-coding driver mutations have been well-characterized by large exome-sequencing studies, however many tumors have no mutations in protein-coding driver genes. Non-coding mutations are thought to explain many of these cases, however few non-coding drivers besides TERT promoter are known. To fill this gap, we analyzed 150,000 cis-regulatory regions in 1,844 whole cancer genomes from the ICGC-TCGA PCAWG project. Using our new method, ActiveDriverWGS, we found 41 frequently mutated regulatory elements (FMREs) enriched in non-coding SNVs and indels (FDR<0.05) characterized by aging-associated mutation signatures and frequent structural variants. Most FMREs are distal from genes, reported here for the first time and also recovered by additional driver discovery methods. FMREs were enriched in super-enhancers, H3K27ac enhancer marks of primary tumors and long-range chromatin interactions, suggesting that the mutations drive cancer by distally controlling gene expression through three-dimensional genome organization. In support of this hypothesis, the chromatin interaction network of FMREs and target genes revealed associations of mutations and differential gene expression of known and novel cancer genes (e.g., CNNB1IP1, RCC1), activation of immune response pathways and altered enhancer marks. Thus distal genomic regions may include additional, infrequently mutated drivers that act on target genes via chromatin loops. Our study is an important step towards finding such regulatory regions and deciphering the somatic mutation landscape of the non-coding genome.
2,242 downloads cancer biology
Personalized cancer vaccine strategies directed at tumor neoantigens derived from somatic mutations in the DNA are currently under prospective evaluation. Alterations in tumor RNA, rather than DNA, may also represent a previously-unexplored source of neoantigens. Here, we show that intron retention, a widespread feature of cancer transcriptomes, represents a novel source of tumor neoantigens. We developed an in silico approach to identify retained intron neoantigens from RNA sequencing data and applied this methodology to tumor samples from patients with melanoma treated with immune checkpoint blockade, discovering that the retained intron neoantigen burden in these samples augments the DNA-derived, somatic neoantigen burden. We validated the existence of retained intron derived neoantigens by implementing this technique on cancer cell lines with mass spectrometry-derived immunopeptidome data, revealing that retained intron neoantigens were complexed with MHC I experimentally. Unexpectedly, we observed a trend toward lack of clinical benefit from immune checkpoint blockade in high retained intron load-tumors, which harbored transcriptional signatures consistent with cell cycle dysregulation and DNA damage repair. Our results demonstrate the contribution of transcriptional dysregulation to the overall burden of tumor neoantigens, provide a foundation for augmenting personalized cancer vaccine development with a new class of tumor neoantigens, and demonstrate how global transcriptional dysregulation may impact selective response to immune checkpoint blockade.
2,207 downloads cancer biology
Jeremiah A Wala, Ofer Shapira, Marcin Imielinski, David Craft, Steven E Schumacher, James E Haber, Nicola D Roberts, Xiaotong Yao, Chip Stewart, Cheng-Zhong Zhang, Jose Tubio, Young Seok Ju, Peter J. Campbell, Joachim Weischenfeldt, Rameen Beroukhim, on behalf of the PCAWG-Structural Variation Working Group and the PCAWG Network.
Cancer cells can acquire profound alterations to the structure of their genomes, including rearrangements that fuse distant DNA breakpoints. We analyze the distribution of somatic rearrangements across the cancer genome, using whole-genome sequencing data from 2,693 tumor-normal pairs. We observe substantial variation in the density of rearrangement breakpoints, with enrichment in open chromatin and sites with high densities of repetitive elements. After accounting for these patterns, we identify significantly recurrent breakpoints (SRBs) at 52 loci, including novel SRBs near BRD4 and AKR1C3. Taking into account both loci fused by a rearrangement, we observe different signatures resembling either single breaks followed by strand invasion or two separate breaks that become joined. Accounting for these signatures, we identify 90 pairs of loci that are significantly recurrently juxtaposed (SRJs). SRJs are primarily tumor-type specific and tend to involve genes with tissue-specific expression. SRJs were frequently associated with disruption of topology-associated domains, juxtaposition of enhancer elements, and increased expression of neighboring genes. Lastly, we find that the power to detect SRJs decreases for short rearrangements, and that reliable detection of all driver SRJs will require whole-genome sequencing data from an order of magnitude more cancer samples than currently available.
2,174 downloads cancer biology
Yilong Zou, Michael J Palte, Amy A Deik, Haoxin Li, John K. Eaton, Wenyu Wang, Yuen-Yi Tseng, Rebecca Deasy, Maria Alimova, Vlado Dančík, Elizaveta S Leshchiner, Vasanthi S. Viswanathan, Sabina Signoretti, Toni K. Choueiri, Jesse S. Boehm, Bridget K. Wagner, John Doench, Clary B. Clish, Paul A Clemons, Stuart L. Schreiber
Kidney cancers are characterized by extensive metabolic reprogramming and resistance to a broad range of anti-cancer therapies. By interrogating the Cancer Therapeutics Response Portal compound sensitivity dataset, we show that cells of clear-cell renal cell carcinoma (ccRCC) possess a lineage-specific vulnerability to ferroptosis that can be exploited by inhibiting glutathione peroxidase 4 (GPX4). Using genome-wide CRISPR screening and lipidomic profiling, we reveal that this vulnerability is driven by the HIF-2α - HILPDA pathway by inducing a polyunsaturated fatty acyl (PUFA)-lipid-enriched cell state that is dependent on GPX4 for survival and susceptible to ferroptosis. This cell state is developmentally primed by the HNF-1β - 1-acylglycerol-3-phosphate O-acyltransferase 3 (AGPAT3) axis in the renal lineage. In addition to PUFA metabolism, ferroptosis is facilitated by a phospholipid flippase TMEM30A involved in membrane topology. Our study uncovers an oncogenesis-associated vulnerability, delineates the underlying mechanisms and suggests targeting GPX4 to induce ferroptosis as a therapeutic opportunity in ccRCC.
2,171 downloads cancer biology
Tamara Ouspenskaia, Travis Law, Karl R. Clauser, Susan Klaeger, Siranush Sarkizova, François Aguet, Bo Li, Elena Christian, Binyamin A. Knisbacher, Phuong M. Le, Christina R. Hartigan, Hasmik Keshishian, Annie Apffel, Giacomo Oliveira, Wandi Zhang, Yuen Ting Chow, Zhe Ji, Irwin Jungreis, Sachet A. Shukla, Pavan Bachireddy, Manolis Kellis, Gad Getz, Nir Hacohen, Derin B. Keskin, Steven A. Carr, Catherine J. Wu, Aviv Regev
Tumor epitopes – peptides that are presented on surface-bound MHC I proteins - provide targets for cancer immunotherapy and have been identified extensively in the annotated protein-coding regions of the genome. Motivated by the recent discovery of translated novel unannotated open reading frames (nuORFs) using ribosome profiling (Ribo-seq), we hypothesized that cancer-associated processes could generate nuORFs that can serve as a new source of tumor antigens that harbor somatic mutations or show tumor-specific expression. To identify cancer-specific nuORFs, we generated Ribo-seq profiles for 29 malignant and healthy samples, developed a sensitive analytic approach for hierarchical ORF prediction, and constructed a high-confidence database of translated nuORFs across tissues. Peptides from 3,555 unique translated nuORFs were presented on MHC I, based on analysis of an extensive dataset of MHC I-bound peptides detected by mass spectrometry, with >20-fold more nuORF peptides detected in the MHC I immunopeptidomes compared to whole proteomes. We further detected somatic mutations in nuORFs of cancer samples and identified nuORFs with tumor-specific translation in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs thus expand the pool of MHC I-presented, tumor-specific peptides, targetable by immunotherapies.
2,121 downloads cancer biology
Anand Vasudevan, Prasamit S. Baruah, Joan C. Smith, Zihua Wang, Nicole M. Sayles, Peter Andrews, Jude Kendall, Justin E. Leu, Narendra Kumar Chunduri, Dan Levy, Michael Wigler, Zuzana Storchová, Jason M. Sheltzer
Most human tumors display chromosome-scale copy number alterations, and high levels of aneuploidy are frequently associated with advanced disease and poor patient prognosis. To examine the relationship between aneuploidy and cancer progression, we generated and analyzed a series of congenic human cell lines that harbor single extra chromosomes. We find that different aneuploidies can have distinct effects on invasive behavior: across 13 different cell lines, 12 trisomies suppressed invasiveness or were largely neutral, while a single trisomy increased metastatic behavior by triggering a partial epithelial-mesenchymal transition. In contrast, chromosomal instability, which can lead to the development of aneuploidy, uniformly suppressed cellular invasion. By analyzing genomic copy number and survival data from 10,133 cancer patients, we demonstrate that specific aneuploidies are associated with distinct clinical outcomes, and the acquisition of certain aneuploidies is in fact linked with a favorable prognosis. Thus, aneuploidy is not a uniform driver of malignancy, and different chromosome copy number changes can uniquely influence tumor progression. At the same time, the gain of a single chromosome is capable of inducing a profound cell state transition, underscoring how genomic plasticity can engender phenotypic plasticity and lead to the acquisition of enhanced metastatic properties.
2,105 downloads cancer biology
Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research.
2,073 downloads cancer biology
Heterogeneity across cancer makes it difficult to find driver genes with intermediate (2-20%) and low frequency (<2%) mutations, and we are potentially missing entire classes of networks (or pathways) of biological and therapeutic value. Here, we quantify the extent to which cancer genes across 21 tumor types have an increased burden of mutations in their immediate gene network derived from functional genomics data. We formalize a classifier that accurately calculates the significance level of a gene’s network mutation burden (NMB) and show it can accurately predict known cancer genes and recently proposed driver genes in the majority of tested tumours. Our approach predicts 62 putative cancer genes, including 35 with clear connection to cancer and 27 genes, which point to new cancer biology. NMB identifies proportionally more (4x) low-frequency mutated genes as putative cancer genes than gene-based tests, and provides molecular clues in patients without established driver mutations. Our quantitative and comparative analysis of pan-cancer networks across 21 tumour types gives new insights into the biological and genetic architecture of cancers and enables additional discovery from existing cancer genomes. The framework we present here should become increasingly useful with more sequencing data in the future.
2,064 downloads cancer biology
Elena Panzilius, Felix Holstein, Jonas Dehairs, Mélanie Planque, Christine von Toerne, Ann-Christine Koenig, Sebastian Doll, Marie Bannier-Hélaouët, Hilary M. Ganz, Stefanie M. Hauck, Ali Talebi, Johannes V. Swinnen, Sarah-Maria Fendt, José P. Friedmann Angeli, Marcus Conrad, Christina H. Scheel
Ferroptosis is a regulated form of necrotic cell death caused by iron-dependent phospholipid peroxidation. It can be induced by inhibiting glutathione peroxidase 4 (GPX4), the key enzyme for efficiently reducing peroxides within phospholipid bilayers. Recent data suggest that cancer cells undergoing EMT (dedifferentiation) and those resistant to standard therapy expose a high vulnerability toward ferroptosis. Although recent studies have begun to identify and characterize the metabolic and genetic determinants underlying ferroptosis, many mechanisms that dictate ferroptosis sensitivity remain unknown. Here, we show that low cell density sensitizes primary mammary epithelial and breast cancer cells to ferroptosis induced by GPX4 inhibition, whereas high cell density confers resistance. These effects occur irrespective of oncogenic signaling, cellular phenotype and expression of the fatty acid ligase acyl-CoA synthetase long chain family member 4 (ACSL4). By contrast, we show that a massive accumulation of neutral triacylglycerides (TAG) enriched with polyunsaturated fatty acids (PUFA) is induced at low cell density. In addition, de novo lipogenesis and desaturation pathways were found to be reduced at low cell density, indicative of increased fatty acid uptake. Our study suggests that PUFA-mediated toxicity is limited by the enrichment in TAGs that in turn might pose a vulnerability towards ferroptosis. Conclusively, cell density regulates lipid metabolism of breast epithelial and cancer cells, which results in a ferroptosis-sensitive cell state with the potential to be exploited therapeutically during metastatic dissemination.
2,043 downloads cancer biology
David Tamborero, Carlota Rubio-Perez, Jordi Deu-Pons, Michael P. Schroeder, Ana Vivancos, Ana Rovira, Ignasi Tusquets, Joan Albanell, Jordi Rodon, Josep Tabernero, Carmen de Torres, Rodrigo Dienstmann, Abel Gonzalez-Perez, Nuria Lopez-Bigas
While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Most of the alterations observed in tumors, including those in well-known cancer genes, are of uncertain significance. Moreover, the information on tumor genomic alterations shaping the response to existing therapies is fragmented across the literature and several specialized resources. Here we present the Cancer Genome Interpreter (http://www.cancergenomeinterpreter.org), an open access tool that we have implemented to annotate genomic alterations and interpret their possible role in tumorigenesis and in the response to anti-cancer therapies.
2,029 downloads cancer biology
Outcomes for cancer patients vary greatly even within the same tumor type, and characterization of molecular subtypes of cancer holds important promise for improving prognosis and personalized treatment. This promise has motivated recent efforts to produce large amounts of multidimensional genomic ('multi-omic') data, but current algorithms still face challenges in the integrated analysis of such data. Here we present Cancer Integration via Multikernel Learning (CIMLR), a new cancer subtyping method that integrates multi-omic data to reveal molecular subtypes of cancer. We apply CIMLR to multi-omic data from 36 cancer types and show significant improvements in both computational efficiency and ability to extract biologically meaningful cancer subtypes. The discovered subtypes exhibit significant differences in patient survival for 27 of 36 cancer types. Our analysis reveals integrated patterns of gene expression, methylation, point mutations and copy number changes in multiple cancers and highlights patterns specifically associated with poor patient outcomes.
2,025 downloads cancer biology
Paul Guilhamon, M.M. Kushida, A. Nikolic, D. Singhal, G. MacLeod, S.A. Madani Tonekaboni, F.M.G. Cavalli, C. Arlidge, N. Rajakulendran, N. Rastegar, X. Hao, R. Hassam, L.J. Smith, H. Whetstone, F.J. Coutinho, B. Nadorp, K.I. Ellestad, H.A. Luchman, J.A. Chan, M.S. Shoichet, M.D. Taylor, Benjamin Haibe-Kains, S. Weiss, Stéphane Angers, Marco Gallo, P.B. Dirks, Mathieu Lupien
Chromatin accessibility discriminates stem from mature cell populations, enabling the identification of primitive stem-like cells in primary tumors, such as Glioblastoma (GBM) where self-renewing cells driving cancer progression and recurrence are prime targets for therapeutic intervention. We show, using single-cell chromatin accessibility, that primary GBMs harbor a heterogeneous self-renewing population whose diversity is captured in patient-derived glioblastoma stem cells (GSCs). In depth characterization of chromatin accessibility in GSCs identifies three GSC states: Reactive, Constructive, and Invasive, each governed by uniquely essential transcription factors and present within GBMs in varying proportions. Orthotopic xenografts reveal that GSC states associate with survival, and identify an invasive GSC signature predictive of low patient survival. Our chromatin-driven characterization of GSC states improves prognostic precision and identifies dependencies to guide combination therapies.
2,010 downloads cancer biology
Tumor-propagating glioblastoma (GBM) stem-like cells (GSCs) of the proneural and mesenchymal molecular subtypes have been described. However, it is unknown if these two GSC populations are sufficient to generate the spectrum of cellular heterogeneity observed in GBM. The lineage relationships and niche interactions of GSCs have not been fully elucidated. We perform single-cell RNA-sequencing (scRNA-seq) and matched exome sequencing of human GBMs (12 patients; >37,000 cells) to identify recurrent hierarchies of GSCs and their progeny. We map sequenced cells to tumor-anatomical structures and identify microenvironment interactions using reference atlases and quantitative immunohistochemistry. We find that all GSCs can be described by a single axis of variation, ranging from proneural to mesenchymal. Increasing mesenchymal GSC (mGSC) content, but not proneural GSC (pGSC) content, correlates with significantly inferior survival. All clonal expressed mutations are found in the GSC populations, with a greater representation of mutations found in mGSCs. While pGSCs upregulate markers of cell-cycle progression, mGSCs are largely quiescent and overexpress cytokines mediating the chemotaxis of myeloid-derived suppressor cells. We find mGSCs enriched in hypoxic regions while pGSCs are enriched in the tumor's invasive edge. We show that varying proportions of mGSCs, pGSCs, their progeny and stromal/immune cells are sufficient to explain the genetic and phenotypic heterogeneity observed in GBM. This study sheds light on a long-standing debate regarding the lineage relationships between GSCs and other glioma cell types.
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