Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 65,445 bioRxiv papers from 289,895 authors.
Most downloaded bioRxiv papers, since beginning of last month
in category cancer biology
2,126 results found. For more information, click each entry to expand.
6,588 downloads cancer biology
Chenchen Pan, Oliver Schoppe, Arnaldo Parra-Damas, Ruiyao Cai, Mihail Ivilinov Todorov, Gabor Gondi, Bettina von Neubeck, Alireza Ghasemi, Madita Alice Reimer, Javier Coronel, Boyan K. Garvalov, Bjoern Menze, Reinhard Zeidler, Ali Erturk
Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long been needed to better understand and treat cancer metastasis. Here, we developed an integrated pipeline for automated quantification of cancer metastases and therapeutic antibody targeting, named DeepMACT. First, we enhanced the fluorescent signal of tumor cells more than 100-fold by applying the vDISCO method to image single cancer cells in intact transparent mice. Second, we developed deep learning algorithms for automated quantification of metastases with an accuracy matching human expert manual annotation. Deep learning-based quantifications in a model of spontaneous metastasis using human breast cancer cells allowed us to systematically analyze clinically relevant features such as size, shape, spatial distribution, and the degree to which metastases are targeted by a therapeutic monoclonal antibody in whole mice. DeepMACT can thus considerably improve the discovery of effective therapeutic strategies for metastatic cancer.
2,745 downloads cancer biology
The U.S. National Toxicology Program (NTP) has carried out extensive rodent toxicology and carcinogenesis studies of radiofrequency radiation (RFR) at frequencies and modulations used in the U.S. telecommunications industry. This report presents partial findings from these studies. The occurrences of two tumor types in male Harlan Sprague Dawley rats exposed to RFR, malignant gliomas in the brain and schwannomas of the heart, were considered of particular interest and are the subject of this report. The findings in this report were reviewed by expert peer reviewers selected by the NTP and National Institutes of Health (NIH). These reviews and responses to comments are included as appendices to this report, and revisions to the current document have incorporated and addressed these comments. When the studies are completed, they will undergo additional peer review before publication in full as part of the NTP's Toxicology and Carcinogenesis Technical Reports Series. No portion of this work has been submitted for publication in a scientific journal. Supplemental information in the form of four additional manuscripts has or will soon be submitted for publication. These manuscripts describe in detail the designs and performance of the RFR exposure system, the dosimetry of RFR exposures in rats and mice, the results to a series of pilot studies establishing the ability of the animals to thermoregulate during RFR exposures, and studies of DNA damage. (1) Capstick M, Kuster N, Kuhn S, Berdinas-Torres V, Wilson P, Ladbury J, Koepke G, McCormick D, Gauger J, and Melnick R. A radio frequency radiation reverberation chamber exposure system for rodents; (2) Yijian G, Capstick M, McCormick D, Gauger J, Horn T, Wilson P, Melnick RL, and Kuster N. Life time dosimetric assessment for mice and rats exposed to cell phone radiation; (3) Wyde ME, Horn TL, Capstick M, Ladbury J, Koepke G, Wilson P, Stout MD, Kuster N, Melnick R, Bucher JR, and McCormick D. Pilot studies of the National Toxicology Program's cell phone radiofrequency radiation reverberation chamber exposure system; (4) Smith-Roe SL, Wyde ME, Stout MD, Winters J, Hobbs CA, Shepard KG, Green A, Kissling GE, Tice RR, Bucher JR, and Witt KL. Evaluation of the genotoxicity of cell phone radiofrequency radiation in male and female rats and mice following subchronic exposure.
2,002 downloads cancer biology
Recent studies have reported that CRISPR-Cas9 gene editing induces a p53 -dependent DNA damage response in primary cells, which may select for cells with oncogenic p53 mutations,. It is unclear whether these CRISPR-induced changes are applicable to different cell types, and whether CRISPR gene editing may select for other oncogenic mutations. Addressing these questions, we analyzed genome-wide CRISPR and RNAi screens to systematically chart the mutation selection potential of CRISPR knockouts across the whole exome. Our analysis suggests that CRISPR gene editing can select for mutants of KRAS and VHL , at a level comparable to that reported for p53 . These predictions were further validated in a genome-wide manner by analyzing independent CRISPR screens and patients’ tumor data. Finally, we performed a new set of pooled and arrayed CRISPR screens to evaluate the competition between CRISPR-edited isogenic p53 WT and mutant cell lines, which further validated our predictions. In summary, our study systematically charts and points to the potential selection of specific cancer driver mutations during CRISPR-Cas9 gene editing. : #ref-11 : #ref-12
1,841 downloads cancer biology
Gabriela S Kinker, Alissa C Greenwald, Rotem Tal, Zhanna Orlova, Michael S Cuoco, James M McFarland, Allison Warren, Christopher Rodman, Jennifer A Roth, Samantha A Bender, Bhavna Kumar, James W. Rocco, Pedro ACM Fernandes, Christopher C Mader, Hadas Keren-Shaul, Alexander Plotnikov, Haim Barr, Aviad Tsherniak, Orit Rozenblatt-Rosen, Valery Krizhanovsky, Sidharth V Puram, Aviv Regev, Itay Tirosh
Cultured cell lines are the workhorse of cancer research, but it is unclear to what extent they recapitulate the cellular heterogeneity observed among malignant cells in tumors, given the absence of a native tumor microenvironment. Here, we used multiplexed single cell RNA-Seq to profile ~200 cancer cell lines. We uncovered expression programs that are recurrently heterogeneous within many cancer cell lines and are largely independent of observed genetic diversity. These programs of heterogeneity are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelial-to-mesenchymal transition (EMT), and protein maturation and degradation. Notably, some of these recurrent programs recapitulate those seen in human tumors, suggesting a prominent role of intrinsic plasticity in generating intra-tumoral heterogeneity. Moreover, the data allowed us to prioritize specific cell lines as model systems of cellular plasticity. We used two such models to demonstrate the dynamics, regulation and vulnerabilities associated with a cancer senescence program observed both in cell lines and in human tumors. Our work describes the landscape of cellular heterogeneity in diverse cancer cell lines, and identifies recurrent patterns of expression heterogeneity that are shared between tumors and specific cell lines and can thus be further explored in follow up studies.
923 downloads cancer biology
Ludmil Alexandrov, Jaegil Kim, Nicholas J Haradhvala, Mi Ni Huang, Alvin W T Ng, Yang Wu, Arnoud Boot, Kyle R Covington, Dmitry A. Gordenin, Erik N Bergstrom, S. M. Ashiqul Islam, Nuria Lopez-Bigas, Leszek J. Klimczak, John R McPherson, Sandro Morganella, Radhakrishnan Sabarinathan, David A Wheeler, Ville Mustonen, the PCAWG Mutational Signatures Working Group, Gad Getz, Steven G. Rozen, Michael R. Stratton
Somatic mutations in cancer genomes are caused by multiple mutational processes each of which generates a characteristic mutational signature. Using 84,729,690 somatic mutations from 4,645 whole cancer genome and 19,184 exome sequences encompassing most cancer types we characterised 49 single base substitution, 11 doublet base substitution, four clustered base substitution, and 17 small insertion and deletion mutational signatures. The substantial dataset size compared to previous analyses enabled discovery of new signatures, separation of overlapping signatures and decomposition of signatures into components that may represent associated, but distinct, DNA damage, repair and/or replication mechanisms. Estimation of the contribution of each signature to the mutational catalogues of individual cancer genomes revealed associations with exogenous and endogenous exposures and defective DNA maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes contributing to the development of human cancer including a comprehensive reference set of mutational signatures in human cancer.
625 downloads cancer biology
Zainab Jagani, Gregg Chenail, Kay Xiang, Geoffrey Bushold, Hyo-Eun C Bhang, Ailing Li, GiNell Elliott, Jiang Zhu, Anthony Vattay, Tamara Gilbert, Anka Bric, Rie Kikkawa, Valerie Dubost, Remi Terranova, John Cantwell, Catherine Luu, Serena Silver, Matt Shirley, Francois Huet, Rob Maher, John Reece-Hoyes, David Ruddy, Daniel Rakiec, Joshua Korn, Carsten Russ, Vera Ruda, Julia Dooley, Emily Costa, Isabel Park, Henrik Moebitz, Katsumasa Nakajima, Christopher D Adair, Simon Mathieu, Rukundo Ntaganda, Troy Smith, David Farley, Daniel King, Xiaoling Xie, Raviraj Kulathila, Tiancen Hu, Xuewen Pan, Qicheng Ma, Katarina Vulic, Florencia Rago, Scott Clarkson, Robin Ge, Frederic Sigoillot, Gwynn Pardee, Linda Bagdasarian, Margaret McLaughlin, Kristy Haas, Jan Weiler, Steve Kovats, Mariela Jaskelioff, Marie Apolline-Gerard, Johanna Beil, Ulrike Naumann, Pascal Fortin, Frank P Stegmeier, Michael G Acker, Juliet Williams, Matthew Meyer, James E Bradner, Nicholas Keen, William R Sellers, Francesco Hofmann, Jeffrey Engelman, Darrin Stuart, Julien P.N Papillon
Members of the ATP-dependent SWI/SNF chromatin remodeling complexes are among the most frequently mutated genes in cancer, suggesting their dysregulation plays a critical role. The synthetic lethality between SWI/SNF catalytic subunits BRM/SMARCA2 and BRG1/SMARCA4 has instigated great interest in targeting BRM. Here we have performed a critical and in-depth investigation of novel dual inhibitors (BRM011 and BRM014) of BRM and BRG1 in order to validate their utility as chemical probes of SWI/SNF catalytic function, while obtaining insights into the therapeutic potential of SWI/SNF inhibition. In corroboration of on-target activity, we discovered compound resistant mutations through pooled screening of BRM variants in BRG1-mut cancer cells. Strikingly, genome-wide transcriptional and chromatin profiling (ATAC-Seq) provided further evidence of pharmacological perturbation of SWI/SNF chromatin remodeling as BRM011 treatment induced specific changes in chromatin accessibility and gene expression similar to genetic depletion of BRM. Finally, these compounds have the capacity to inhibit the growth of tumor-xenografts, yielding important insights into the feasibility of developing BRM/BRG1 ATPase inhibitors for the treatment of BRG1-mut lung cancers. Overall, our studies not only establish the feasibility of inhibiting SWI/SNF catalytic function, providing a framework for SWI/SNF therapeutic targeting, but have also yielded successful elucidation of small-molecule inhibitors that will be of importance in probing SWI/SNF function in various disease contexts.
529 downloads cancer biology
To understand the architecture of a tissue it is necessary to know both the cell populations and their physical relationships to one another. Single-cell RNA-Seq (scRNA-Seq) has made significant progress towards the unbiased and systematic characterization of the cell populations within a tissue, as well as their cellular states, by studying hundreds and thousands of cells in a single experiment. However, the characterization of the spatial organization of individual cells within a tissue has been more elusive. The recently introduced "spatial transcriptomics" method (ST) reveals the spatial pattern of gene expression within a tissue section at a resolution of one thousand 100 µm spots, each capturing the transcriptomes of ~10-20 cells. Here, we present an approach for the integration of scRNA-Seq and ST data generated from the same sample of pancreatic cancer tissue. Using markers for cell-types identified by scRNA-Seq, we robustly deconvolved the cell-type composition of each ST spot, to generate a spatial atlas of cell proportions across the tissue. Studying this atlas, we found that distinct spatial localizations accompany each of the three cancer cell populations that we identified. Strikingly, we find that subpopulations defined in the scRNA-Seq data also exhibit spatial segregation in the atlas, suggesting such an atlas may be used to study the functional attributes of subpopulations. Our results provide a framework for creating a tumor atlas by mapping single-cell populations to their spatial region, as well as the inference of cell architecture in any tissue.
517 downloads cancer biology
Peter Priestley, Jonathan Baber, Martijn P. Lolkema, Neeltje Steeghs, Ewart de Bruijn, Charles Shale, Korneel Duyvesteyn, Susan Haidari, Arne van Hoeck, Wendy Onstenk, Paul Roepman, Mircea Voda, Haiko J. Bloemendal, Vivianne C.G. Tjan-Heijnen, Carla M.L. van Herpen, Mariette Labots, Petronella O. Witteveen, Egbert F. Smit, Stefan Sleijfer, Emile E. Voest, Edwin Cuppen
Metastatic cancer is one of the major causes of death and is associated with poor treatment efficiency. A better understanding of the characteristics of late stage cancer is required to help tailor personalised treatment, reduce overtreatment and improve outcomes. Here we describe the largest pan-cancer study of metastatic solid tumor genomes, including 2,520 whole genome-sequenced tumor-normal pairs, analyzed at a median depth of 106x and 38x respectively, and surveying over 70 million somatic variants. Metastatic lesions were found to be very diverse, with mutation characteristics reflecting those of the primary tumor types, although with high rates of whole genome duplication events (56%). Metastatic lesions are relatively homogeneous with the vast majority (96%) of driver mutations being clonal and up to 80% of tumor suppressor genes bi-allelically inactivated through different mutational mechanisms. For 62% of all patients, genetic variants that may be associated with outcome of approved or experimental therapies were detected. These actionable events were distributed across various mutation types underlining the importance of comprehensive genomic tumor profiling for cancer precision medicine.
504 downloads cancer biology
Steven M. Corsello, Rohith T Nagari, Ryan D Spangler, Jordan Rossen, Mustafa Kocak, Jordan G Bryan, Ranad Humeidi, David Peck, Xiaoyun Wu, Andrew A Tang, Vickie M Wang, Samantha A Bender, Evan Lemire, Rajiv Narayan, Philip Montgomery, Uri Ben-David, Yejia Chen, Matthew G Rees, Nicholas J. Lyons, James M McFarland, Bang T Wong, Li Wang, Nancy Dumont, Patrick J. O’Hearn, Eric Stefan, John G. Doench, Heidi Greulich, Matthew Meyerson, Francisca Vazquez, Aravind Subramanian, Jennifer A Roth, Joshua A. Bittker, Jesse S Boehm, Christopher C Mader, Aviad Tsherniak, Todd R. Golub
Anti-cancer uses of non-oncology drugs have been found on occasion, but such discoveries have been serendipitous and rare. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. To accomplish this, we used PRISM, which involves drug treatment of molecularly barcoded cell lines in pools. Relative barcode abundance following treatment thus reflects viability of each cell line. We found that an unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines. Moreover, the killing activity of the majority of these drugs was predictable based on the molecular features of the cell lines. Follow-up of several of these compounds revealed novel mechanisms. For example, compounds that kill by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing is dependent on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which kills cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, whose killing is dependent on high expression of the multi-drug resistance gene ABCB1. These results illustrate the potential of the PRISM drug repurposing resource as a starting point for new oncology therapeutic development. The resource is available at https://depmap.org.
483 downloads cancer biology
Moritz Gerstung, Clemency Jolly, Ignaty Leshchiner, Stefan C. Dentro, Santiago Gonzalez Rosado, Daniel Rosebrock, Thomas J. Mitchell, Yulia Rubanova, Pavana Anur, Kaixian Yu, Maxime Tarabichi, Amit Deshwar, Jeff Wintersinger, Kortine Kleinheinz, Ignacio Vázquez-García, Kerstin Haase, Lara Jerman, Subhajit Sengupta, Geoff Macintyre, Salem Malikic, Nilgun Donmez, Dimitri G. Livitz, Marek Cmero, Jonas Demeulemeester, Steven Schumacher, Yu Fan, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Paul C. Boutros, David D. Bowtell, Hongtu Zhu, Gad Getz, Marcin Imielinski, Rameen Beroukhim, S. Cenk Sahinalp, Yuan Ji, Martin Peifer, Florian Markowetz, Ville Mustonen, Ke Yuan, Wenyi Wang, Quaid D Morris, Paul T. Spellman, David C. Wedge, Peter Van Loo, on behalf of the PCAWG Evolution and Heterogeneity Working Group, the PCAWG network
Cancer develops through a process of somatic evolution. Here, we reconstruct the evolutionary history of 2,778 tumour samples from 2,658 donors spanning 39 cancer types. Characteristic copy number gains, such as trisomy 7 in glioblastoma or isochromosome 17q in medulloblastoma, are found amongst the earliest events in tumour evolution. The early phases of oncogenesis are driven by point mutations in a restricted set of cancer genes, often including biallelic inactivation of tumour suppressors. By contrast, increased genomic instability, a more than three-fold diversification of driver genes, and an acceleration of mutational processes are features of later stages. Clock-like mutations yield estimates for whole genome duplications and subclonal diversification in chronological time. Our results suggest that driver mutations often precede diagnosis by many years, and in some cases decades. Taken together, these data reveal common and divergent trajectories of cancer evolution, pivotal for understanding tumour biology and guiding early cancer detection.
390 downloads cancer biology
Hitomi Sakamoto, Marc Attiyeh, Jeff Gerold, Alvin P Makohon-Moore, Akimasa Hayashi, Jungeui Hong, Rajya Kappagantula, Lance Zhang, Jerry Melchor, Johannes Reiter, Alex Heyde, Craig Bielski, Alex Penson, Debyani Chakravarty, Eileen O'Reilly, Laura Wood, Ralph H. Hruban, Martin A Nowak, Nicholas Socci, Barry S Taylor, Christine A. Iacobuzio-Donahue
Surgery is the only curative option for Stage I/II pancreatic cancer, nonetheless most patients will recur after surgery and die of their disease. To identify novel opportunities for management of recurrent pancreatic cancer we performed whole exome or targeted sequencing of 10 resected primary cancers and matched intrapancreatic recurrences or distant metastases. We identified that adjuvant or first-line platinum therapy corresponds to an increased mutational burden of recurrent disease. Recurrent disease is enriched for mutations that activate Mapk/Erk and PI3K/AKT signaling and develops from a monophyletic or polyphyletic origin. Treatment induced genetic bottlenecks lead to a modified genetic landscape and subclonal heterogeneity for driver gene alterations in part due to intermetastatic seeding. In one patient what was believed to be recurrent disease was an independent (second) primary tumor. These findings advocate for combination therapies with immunotherapy and routine post-treatment sampling as a component of management of recurrent pancreatic cancer.
383 downloads cancer biology
Visual analysis of histopathology slides of lung cell tissues is one of the main methods used by pathologists to assess the stage, types and sub-types of lung cancers. Adenocarcinoma and squamous cell carcinoma are two most prevalent sub-types of lung cancer, but their distinction can be challenging and time-consuming even for the expert eye. In this study, we trained a deep learning convolutional neural network (CNN) model (inception v3) on histopathology images obtained from The Cancer Genome Atlas (TCGA) to accurately classify whole-slide pathology images into adenocarcinoma, squamous cell carcinoma or normal lung tissue. Our method slightly outperforms a human pathologist, achieving better sensitivity and specificity, with ~0.97 average Area Under the Curve (AUC) on a held-out population of whole-slide scans. Furthermore, we trained the neural network to predict the ten most commonly mutated genes in lung adenocarcinoma. We found that six of these genes - STK11, EGFR, FAT1, SETBP1, KRAS and TP53 - can be predicted from pathology images with an accuracy ranging from 0.733 to 0.856, as measured by the AUC on the held-out population. These findings suggest that deep learning models can offer both specialists and patients a fast, accurate and inexpensive detection
351 downloads cancer biology
Metastasis is the primary cause of cancer-related deaths, but the natural history, clonal evolution and patterns of systemic spread are poorly understood. We analyzed exome sequencing data from 458 paired primary tumors (P) or metastasis (M) samples from 136 breast, colorectal and lung cancer patients, including both untreated (n=98) and treated (n=101) metastases. We find that treated metastases often harbored private driver gene mutations whereas untreated metastases did not, suggesting that treatment promotes clonal evolution. Polyclonal seeding was common in lymph node metastases (n=19/35, 54%; mostly untreated) and untreated distant metastases (n=20/70, 29%), but less frequent in treated metastases (n=9/90, 10%). The low number of metastasis-private clonal mutations is consistent with early metastatic seeding, which commonly occurred several years prior to diagnosis in breast (2.4 years, range 0-3.3), lung (3.6 years, range 2.8-3.7) and colorectal (4.1 years, range 3.1-4.6) cancers. Thus, this pan-cancer analysis reveals early systemic spread in three common cancer types. Further, these data suggest that the natural course of metastasis is selectively relaxed relative to early tumor development and that metastasis-private mutations are not drivers of cancer spread but are instead associated with drug resistance.
345 downloads cancer biology
Kevin Litchfield, James Reading, Emilia Lim, Hang Xu, Po Liu, Maise AL-Bakir, Sophia Wong, Andrew Rowan, Sam Funt, Taha Merghoub, Martin Lauss, Inge Marie Svane, Göran Jönsson, Javier Herrero, James Larkin, Sergio A. Quezada, Matthew D. Hellmann, Samra Turajlic, Charles Swanton
Frameshift insertion/deletions (fs-indels) are an infrequent but potentially highly immunogenic mutation subtype. Although fs-indel transcripts are susceptible to degradation through the non-sense mediated decay (NMD) pathway, we hypothesise that some fs-indels escape degradation and lead to an increased abundance of tumor specific neoantigens, that are highly distinct from self. We analysed matched DNA and RNA sequencing data from TCGA, and five separate melanoma cohorts treated with immunotherapy. Using allele-specific expression analysis we show that expressed fs-indels were enriched in genomic positions predicted to escape NMD, and associated with higher protein expression, consistent with degradation escape (“NMD-escape”). Across four independent cohorts, fs-indel NMD-escape mutations were found to be significantly associated with clinical benefit to checkpoint inhibitor (CPI) therapy (Pmeta=0.0039), a stronger association than either nsSNV (Pmeta=0.073) or fs-indel (Pmeta=0.064) count. NMD-escape mutations were additionally shown to have independent predictive power in the “low-TMB” setting, and may serve as a biomarker to rescue patients judged ineligible for CPI based on overall TMB, but still with a high chance of response (low-TMB cohort: NMD-escape-positive % clinical benefit=53%, NMD-escape-negative % clinical benefit=16%, P=0.0098). Furthermore, in an adoptive cell therapy (ACT) treated cohort, NMD-escape mutation count was the most significant biomarker associated with clinical benefit (P=0.021). Analysis of functional T-cell reactivity screens from recent personalized vaccine and CPI studies shows direct evidence of fs-indel derived neoantigens eliciting patient anti-tumor immune response (n=15). We additionally observe a subset of fs-indel mutations, with highly elongated neo open reading frames, which are found to be significantly enriched for immunogenic reactivity in these patient studies (P=0.0032). Finally, consistent with the potency of NMD-escape derived neo-antigens and ongoing immune-editing, NMD-escape fs-indels appear to be under negative selective pressure in untreated TCGA cases. Given the strongly immunogenic potential, and relatively rare nature of NMD-escape fs-indels, these alterations may be attractive candidates in immunotherapy biomarker optimisation and neoantigen ACT or vaccine strategies.
317 downloads cancer biology
Joao Manuel Fernandes Neto, Ernest Nadal, Salo N Ooft, Evert Bosdriesz, Lourdes Farre, Chelsea McLean, Sjoerd Klarenbeek, Anouk Jurgens, Hannes Hagen, Liqin Wang, Enriqueta Felip, Alex Martinez-Marti, Emile Voest, Lodewyk Wessels, Olaf van Tellingen, Alberto Villanueva, Rene Bernards
Targeted cancer drugs often elicit powerful initial responses, but generally fail to deliver long-term benefit due to the emergence of resistant cells. This is thought to be the consequence of strong selective pressure exerted on the cancer drug target by a Maximum Tolerated Dose (MTD) of a drug. We hypothesized that partial inhibition of multiple components in the same oncogenic signalling pathway might add up to complete pathway inhibition, while at the same time decreasing the selective pressure on each individual component to acquire a resistance mutation. We report here testing of this Multiple Low Dose (MLD) model of drug administration in Epidermal Growth Factor Receptor (EGFR) mutant non-small cell lung cancer (NSCLC). We show that as little as 20% of the individual drug doses required for full inhibition of cell viability is sufficient to completely block MAPK signalling and proliferation when used in 3D (RAF+MEK+ERK inhibitors) or 4D (EGFR+RAF+MEK+ERK inhibitors) combinations. Importantly, EGFR mutant NSCLC cells treated with EGFR inhibitors at a high dose rapidly developed resistance in vitro, but the cells treated with 3D or 4D MLD therapy did not. Moreover, NSCLC cells that had gained resistance to high dose anti-EGFR therapies were still sensitive to MLD therapy. Using several animal models, including patient derived xenografts of NSCLC tumours that are resistant to EGFR inhibitors erlotinib and osimertinib, we found durable responses to MLD therapy without associated toxicity. These data support the notion that partial inhibition of multiple components of cancer-activated signalling pathways is difficult to circumvent and suggest that MLD therapy could deliver clinical benefit. We propose that MLD strategy could be an effective treatment option for EGFR mutant NSCLC patients, especially those having acquired resistance to even third generation EGFR inhibitor therapy.
316 downloads cancer biology
We report the integrative analysis of more than 2,600 whole cancer genomes and their matching normal tissues across 39 distinct tumour types. By studying whole genomes we have been able to catalogue non-coding cancer driver events, study patterns of structural variation, infer tumour evolution, probe the interactions among variants in the germline genome, the tumour genome and the transcriptome, and derive an understanding of how coding and non-coding variations together contribute to driving individual patient's tumours. This work represents the most comprehensive look at cancer whole genomes to date. NOTE TO READERS: This is an incomplete draft of the marker paper for the Pan-Cancer Analysis of Whole Genomes Project, and is intended to provide the background information for a series of in-depth papers that will be posted to BioRixv during the summer of 2017.
302 downloads cancer biology
UCSC Xena is a visual exploration resource for both public and private omics data, supported through the web-based Xena Browser and multiple turn-key Xena Hubs. This unique archecture allows researchers to view their own data securely, using private Xena Hubs, simultaneously visualizing large public cancer genomics datasets, including TCGA and the GDC. Data integration occurs only within the Xena Browser, keeping private data private. Xena supports virtually any functional genomics data, including SNVs, INDELs, large structural variants, CNV, expression, DNA methylation, ATAC-seq signals, and phenotypic annotations. Browser features include the Visual Spreadsheet, survival analyses, powerful filtering and subgrouping, statistical analyses, genomic signatures, and bookmarks. Xena differentiates itself from other genomics tools, including its predecessor, the UCSC Cancer Genomics Browser, by its ability to easily and securely view public and private data, its high performance, its broad data type support, and many unique features.
297 downloads cancer biology
Lisanne F. van Dessel, Job van Riet, Minke Smits, Yanyun Zhu, Paul Hamberg, Michiel S. van der Heijden, Andries M. Bergman, Inge M. van Oort, Ronald de Wit, Emile E. Voest, Neeltje Steeghs, Takafumi N. Yamaguchi, Julie Livingstone, Paul C. Boutros, John W.M. Martens, Stefan Sleijfer, Edwin Cuppen, Wilbert Zwart, Harmen JG van de Werken, Niven Mehra, Martijn P. Lolkema
Metastatic castration-resistant prostate cancer (mCRPC) has a highly complex genomic landscape. With the recent development of novel treatments, accurate stratification strategies are needed. Here we present the whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 mCRPC patients. Using unsupervised clustering based on genomic features, we define eight distinct genomic clusters. We observe potentially clinically relevant genotypes, including microsatellite instability (MSI), homologous recombination deficiency (HRD) enriched with genomic deletions and BRCA2 aberrations, a tandem duplication genotype associated with CDK12-/- and a chromothripsis-enriched subgroup. Our data suggests that stratification on WGS characteristics may improve identification of MSI, CDK12-/- and HRD patients. From WGS and ChIP-seq data, we show the potential relevance of recurrent alterations in non-coding regions identified with WGS and highlight the central role of AR signaling in tumor progression. These data underline the potential value of using WGS to accurately stratify mCRPC patients into clinically actionable subgroups.
296 downloads cancer biology
Shankha Satpathy, Eric J Jaehnig, Karsten Krug, Beom-Jun Kim, Alexander B. Saltzman, Doug Chan, Kimberly R Holloway, Meenakshi Anurag, Chen Huang, Purba Singh, Ari Gao, Noel Namai, Yongchao Dou, Bo Wen, Suhas Vasaikar, David Mutch, Mark Watson, Cynthia Ma, Foluso O. Ademuyiwa, Mothaffar Rimawi, Jeremy Hoog, Samuel Jacobs, Anna Malovannaya, Terry Hyslop, Karl C Clauser, D. R. Mani, Charles Perou, George Miles, Bing Zhang, Michael A. Gillette, Steven A. Carr, Matthew J Ellis
Cancer proteogenomics integrates genomics, transcriptomics and mass spectrometry (MS)-based proteomics to gain insights into cancer biology and treatment efficacy. A proteogenomics approach was therefore developed for frozen core biopsies using tissue-sparing specimen processing with a “microscaled” proteomics workflow. For technical proof-of-principle, biopsies from ERBB2 positive breast cancers before and 48-72 hours after the first dose of neoadjuvant trastuzumab-based chemotherapy were analyzed. ERBB2 protein and phosphosite levels, as well as mTOR target phosphosites, were significantly more suppressed upon treatment in cases associated with pathological complete response, suggesting MS-based pharmacodynamics is achievable. Furthermore, integrated analyses indicated potential causes of treatment resistance including the absence of ERBB2 amplification (false-ERBB2 positive) and insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification (pseudo-ERBB2 positive). Candidate resistance features in true-ERBB2+ cases, including androgen receptor signaling, mucin expression and an inactive immune microenvironment were observed. Thus, proteogenomic analysis of needle core biopsies is feasible and clinical utility should be investigated.
284 downloads cancer biology
Peter Ulz, Samantha Perakis, Qing Zhou, Tina Moser, Jelena Belic, Isaac Lazzeri, Albert Wölfler, Armin Zebisch, Armin Gerger, Gunda Pristauz, Edgar Petru, Brandon White, Charles E.S. Roberts, John St. John, Michael G Schimek, Jochen B Geigl, Thomas Bauernhofer, Heinz Sill, Christoph Bock, Ellen Heitzer, Michael R Speicher
Deregulation of transcription factors (TFs) is an important driver of tumorigenesis. We developed and validated a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyzed whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a newly developed bioinformatics pipeline that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observed patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of early detection of colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.
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