Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 84,583 bioRxiv papers from 364,014 authors.
Most downloaded bioRxiv papers, since beginning of last month
in category cancer biology
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9,262 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.
8,918 downloads cancer biology
Yiwu Yan, Bo Zhou, Chen Qian, Alex Vasquez, Avradip Chatterjee, Xiaopu Yuan, Edwin Posadas, Natasha Kyprianou, Beatrice S. Knudsen, Ramachandran Murali, Arkadiusz Gertych, Sungyong You, Michael R Freeman, Wei Yang
Despite advances in diagnosis and treatment, metastatic prostate cancer remains incurable and is associated with high mortality rates. Thus, novel actionable drug targets are urgently needed for therapeutic interventions in advanced prostate cancer. Here we report receptor-interacting protein kinase 2 (RIPK2) as an actionable drug target for suppressing prostate cancer metastasis. RIPK2 is frequently amplified in lethal prostate cancers and its overexpression is associated with disease progression and aggressiveness. Genetic and pharmacological inhibition of RIPK2 significantly suppressed prostate cancer progression in vitro and metastasis in vivo. Multi-level proteomic analysis revealed that RIPK2 strongly regulates c-Myc protein stability and activity, largely by activating the MKK7/JNK/c-Myc phosphorylation pathway - a novel, non-canonical RIPK2 signaling pathway. Targeting RIPK2 inhibits this phosphorylation pathway, and thus promotes the degradation of c-Myc - a potent oncoprotein for which no drugs have been approved for clinical use yet. These results support targeting RIPK2 for personalized therapy in prostate cancer patients towards improving survival. ### Competing Interest Statement The authors have declared no competing interest.
4,294 downloads cancer biology
Karen Levy, Suchitra Natarajan, Jinghui Wang, Stephanie Chow, Joshua T. Eggold, Phoebe Loo, Rakesh Manjappa, Frederick M. Lartey, Emil Schüler, Lawrie Skinner, Marjan Rafat, Ryan Ko, Anna Kim, Duaa Al Rawi, Rie von Eyben, Oliver Dorigo, Kerriann M. Casey, Edward E Graves, Karl Bush, Amy S. Yu, Albert C Koong, Peter G. Maxim, Billy W Loo, Erinn B Rankin
Peritoneal metastases are the leading cause of morbidity and mortality in ovarian cancer. Despite current surgery, chemotherapy and targeted therapies, the majority of patients diagnosed with advanced epithelial ovarian cancer develop recurrent disease and overall survival rates remain poor. It is known that ovarian cancer is a radiosensitive tumor. Historically, total abdominal irradiation (TAI) was used as an effective postsurgical adjuvant therapy in the management of chemotherapy sensitive and resistant ovarian cancer. However, TAI fell out of favor due to high toxicity, particularly of the gastrointestinal tract. We have developed a preclinical irradiation platform that allows for total abdominal ultrahigh dose rate FLASH irradiation. We demonstrate that TAI-FLASH reduces radiation-induced intestinal injury in both healthy and tumor-bearing mice compared to conventional dose rate (CONV) irradiation. Single high dose TAI-FLASH reduced mortality from gastrointestinal syndrome, spared gut function and epithelial integrity, and decreased cell death in crypt base columnar cells. Importantly, FLASH and CONV irradiation had similar efficacy in the reduction of ovarian cancer peritoneal metastases. These findings suggest that FLASH irradiation may be an effective strategy to enhance the therapeutic index of radiotherapy for the treatment of metastatic ovarian cancer in women.
1,460 downloads cancer biology
Consequential events in cancer progression are typically rare and occur in the unobserved past. Detailed cell phylogenies can capture the history and chronology of such transient events - including metastasis. Here, we applied our Cas9-based lineage tracer to study metastatic progression in a lung cancer xenograft mouse model, revealing the underlying rates, routes, and patterns of metastasis. We report deeply resolved phylogenies for tens of thousands of metastatically disseminated cancer cells. We observe surprisingly diverse metastatic phenotypes, ranging from metastasis-incompetent to highly aggressive populations, and these differences are associated with characteristic changes in transcriptional state, including differential expression of metastasis-related genes like IFI27 and ID3. We further show that metastases transit via tissue routes that are diverse, complex, and multidirectional, and identify examples of reseeding, seeding cascades, and parallel seeding topologies. More broadly, we demonstrate the power of next-generation lineage tracers to record cancer evolution at high resolution and vast scale. ### Competing Interest Statement J.S.W. is an advisor and/or has equity in KSQ Therapeutics, Maze Therapeutics, Amgen, Tenaya, and 5 AM Ventures. T.G.B. is an advisor to Novartis, Astrazeneca, Revolution Medicines, Array, Springworks, Strategia, Relay, Jazz, Rain and receives research funding from Novartis and Revolution Medicines.
949 downloads cancer biology
Linde A Miles, Robert L. Bowman, Tiffany R Merlinsky, Isabelle S Csete, Aik Ooi, Robert Durruthy-Durruthy, Michael Bowman, Christopher Famulare, Minal A Patel, Pedro Mendez, Chrysanthi Ainali, Mani Manivannan, Sombeet Sahu, Aaron D Goldberg, Kelly Bolton, Ahmet Zehir, Raajit Rampal, Martin P Carroll, Sara E Meyer, Aaron D. Viny, Ross L. Levine
Myeloid malignancies, including acute myeloid leukemia (AML), arise from the proliferation and expansion of hematopoietic stem and progenitor cells which acquire somatic mutations. Bulk molecular profiling studies on patient samples have suggested that somatic mutations are obtained in a step-wise fashion, where mutant genes with high variant allele frequencies (VAFs) are proposed to occur early in disease development and mutations with lower VAFs are thought to be acquired later in disease progression 1-3. Although bulk sequencing informs leukemia biology and prognostication, it cannot distinguish which mutations occur in the same clone(s), accurately measure clonal complexity and clone size, or offer definitive evidence of mutational order. To elucidate the clonal framework of myeloid malignancies, we performed single cell mutational profiling on 146 samples from 123 patients. We found AML is most commonly comprised of a small number of dominant clones, which in many cases harbor co-occurring mutations in epigenetic regulators. Conversely, mutations in signaling genes often occur more than once in distinct subclones consistent with increasing clonal diversity. We also used these data to map the clonal trajectory of each patient and found that specific mutation combinations (FLT3-ITD + NPM1c) synergize to promote clonal expansion and dominance. We combined cell surface protein expression with single cell mutational analysis to map somatic genotype and clonal architecture with immunophenotype. Our studies of clonal architecture at a single cell level provide novel insights into the pathogenesis of myeloid transformation and how clonal complexity contributes to disease progression.
783 downloads cancer biology
Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar, Diether Lambrechts
The stromal compartment of the tumour microenvironment consists of a heterogeneous set of tissue-resident and tumour-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n=36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumour-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumours treated with checkpoint immunotherapy and identifying a naive CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate a first panoramic view on the shared complexity of stromal cells in different cancers.
728 downloads cancer biology
Sohrab Salehi, Farhia Kabeer, Nicholas Ceglia, Mirela Andronescu, Marc J. Williams, Kieran R Campbell, Tehmina Masud, Beixi Wang, Justina Biele, Jazmine Brimhall, Jerome Ting, Allen W. Zhang, Ciara O’Flanagan, Fatemeh Dorri, Nicole Rusk, Hak Woo Lee, Teresa Ruiz de Algara, So Ra Lee, Brian Yu Chieh Cheng, Peter Eirew, Takako Kono, Jennifer Pham, Diljot Grewal, Daniel Lai, Richard Moore, Andrew J. Mungall, Marco A. Marra, IMAXT Consortium, Andrew McPherson, Alexandre Bouchard-Côté, Samuel Aparicio, Sohrab P. Shah
Tumour fitness landscapes underpin selection in cancer, impacting etiology, evolution and response to treatment. Progress in defining fitness landscapes has been impeded by a lack of timeseries perturbation experiments over realistic intervals at single cell resolution. We studied the nature of clonal dynamics induced by genetic and pharmacologic perturbation with a quantitative fitness model developed to ascribe quantitative selective coefficients to individual cancer clones, enable prediction of clone-specific growth potential, and forecast competitive clonal dynamics over time. We applied the model to serial single cell genome (>60,000 cells) and transcriptome (>58,000 cells) experiments ranging from 10 months to 2.5 years in duration. We found that genetic perturbation of TP53 in epithelial cell lines induces multiple forms of copy number alteration that confer increased fitness to clonal populations with measurable consequences on gene expression. In patient derived xenografts, predicted selective coefficients accurately forecasted clonal competition dynamics, that were validated with timeseries sampling of experimentally engineered mixtures of low and high fitness clones. In cisplatin-treated patient derived xenografts, the fitness landscape was inverted in a time-dependent manner, whereby a drug resistant clone emerged from a phylogenetic lineage of low fitness clones, and high fitness clones were eradicated. Moreover, clonal selection mediated reversible drug response early in the selection process, whereas late dynamics in genomically fixed clones were associated with transcriptional plasticity on a fixed clonal genotype. Together, our findings outline causal mechanisms with implication for interpreting how mutations and multi-faceted drug resistance mechanisms shape the etiology and cellular fitness of human cancers. ### Competing Interest Statement SPS and SA are shareholders and consultants of Contextual Genomics Inc.
663 downloads cancer biology
Michele Olivieri, Tiffany Cho, Alejandro Álvarez-Quilón, Kejiao Li, Matthew J. Schellenberg, Michal Zimmermann, Nicole Hustedt, Silvia Emma Rossi, Salomé Adam, Henrique Melo, Anne Margriet Heijink, Guillermo Sastre-Moreno, Nathalie Moatti, Rachel Szilard, Andrea McEwan, Alexanda K. Ling, Almudena Serrano-Benitez, Tajinder Ubhi, Irene Delgado-Sainz, Michael W. Ferguson, Grant W. Brown, Felipe Cortés-Ledesma, R. Scott Williams, Alberto Martin, Dongyi Xu, Daniel Durocher
The response to DNA damage is critical for cellular homeostasis, tumor suppression, immunity and gametogenesis. In order to provide an unbiased and global view of the DNA damage response in human cells, we undertook 28 CRISPR/Cas9 screens against 25 genotoxic agents in the retinal pigment epithelium-1 (RPE1) cell line. These screens identified 840 genes whose loss causes either sensitivity or resistance to DNA damaging agents. Mining this dataset, we uncovered that ERCC6L2, which is mutated in a bone-marrow failure syndrome, codes for a canonical non-homologous end-joining pathway factor; that the RNA polymerase II component ELOF1 modulates the response to transcription-blocking agents and that the cytotoxicity of the G-quadruplex ligand pyridostatin involves trapping topoisomerase II on DNA. This map of the DNA damage response provides a rich resource to study this fundamental cellular system and has implications for the development and use of genotoxic agents in cancer therapy.
635 downloads cancer biology
Erdem D. Tabdanov, Nelson J. Rodríguez-Merced, Alexander X. Cartagena-Rivera, Vikram V. Puram, Mackenzie K. Callaway, Ethan A. Ensminger, Emily J. Pomeroy, Kenta Yamamoto, Walker S. Lahr, Beau R. Webber, Branden S. Moriarity, Alexander S. Zhovmer, Paolo P. Provenzano
Defining the principles of T cell migration in structurally and mechanically complex tumor microenvironments is critical to understanding sanctuaries from antitumor immunity and optimizing T cell-related therapeutic strategies. To enhance T cell migration through complex microenvironments, we engineered nanotextured platforms that allowed us to define how the balance between T cell phenotypes influences migration in response to tumor-mimetic structural and mechanical cues and characterize a mechanical optimum for migration that can be perturbed by manipulating an axis between microtubule stability and force generation. In 3D environments and live tumors, we demonstrate that microtubules instability, leading to increased Rho pathway-dependent cell contractility, promotes migration while clinically used microtubule-targeting chemotherapies profoundly decrease effective migration. Indeed, we show that rational manipulation of the microtubule-contractility axis, either pharmacologically or through genome engineering, results in engineered T cells that more effectively move through and interrogate 3D matrix and tumor volumes. This suggests that engineering cells to better navigate through 3D microenvironments could be part of an effective strategy to enhance efficacy of immune therapeutics. ### Competing Interest Statement The authors have declared no competing interest.
620 downloads cancer biology
Giorgia Foggetti, Chuan Li, Hongchen Cai, Jessica A. Hellyer, Wen-Yang Lin, Deborah Ayeni, Katherine Hastings, Jungmin Choi, Anna Wurtz, Laura Andrejka, Dylan Maghini, Nicholas Rashleigh, Stellar Levy, Robert Homer, Scott Gettinger, Maximilian Diehn, Heather A. Wakelee, Dmitri A. Petrov, Monte M. Winslow, Katerina Politi
Cancer genome sequencing has uncovered substantial complexity in the mutational landscape of tumors. Given this complexity, experimental approaches are necessary to establish the impact of combinations of genetic alterations on tumor biology and to uncover genotype-dependent effects on drug sensitivity. In lung adenocarcinoma, EGFR mutations co-occur with many putative tumor suppressor gene alterations, however the extent to which these alterations contribute to tumor growth and their response to therapy in vivo has not been explored experimentally. By integrating a novel mouse model of oncogenic EGFR -driven Trp53 -deficient lung adenocarcinoma with multiplexed CRISPR– Cas9 -mediated genome editing and tumor barcode sequencing, we quantified the effects of inactivation of ten putative tumor suppressor genes. Inactivation of Apc , Rb1 , or Rbm10 most strongly promoted tumor growth. Unexpectedly, inactivation of Lkb1 or Setd2 – which were the strongest drivers of tumor growth in an oncogenic Kras -driven model – reduced EGFR -driven tumors growth. These results were consistent with the relative frequency of these tumor suppressor gene alterations in human EGFR - and KRAS -driven lung adenocarcinomas. Furthermore, Keap1 inactivation reduced the sensitivity of tumors to osimertinib in the EGFRL858R ; p53 flox/flox model. Importantly, in human EGFR / TP53 mutant lung adenocarcinomas, mutations in the KEAP1 pathway correlated with decreased time on tyrosine kinase inhibitor treatment. Our study highlights how genetic alterations can have dramatically different biological consequences depending on the oncogenic context and that the fitness landscape can shift upon drug treatment. ### Competing Interest Statement K.Politi is co-inventor on a patent licensed to Molecular MD for EGFR T790M mutation testing (through MSKCC). K.Politi has received Honoraria/Consulting fees from Takeda, NCCN, Novartis, Merck, AstraZeneca, Tocagen, Maverick Therapeutics and Dynamo Therapeutics and research support from AstraZeneca, Kolltan, Roche and Symphogen. M. M. Winslow has received honoraria from the speakers bureaus of Genentech, Merck, and Amgen. M. M. Winslow and D. Petrov have ownership interest (including stock, patents, etc.) in D2G Oncology and are a consultant/advisory board members for D2G Oncology. M. Diehn reports research funding from Varian Medical Systems and Illumina, ownership interest in CiberMed, patent filings related to cancer biomarkers, paid consultancy from Roche, AstraZeneca, and BioNTech, and travel/honoraria from RefleXion and Illumina.
554 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.
549 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.
543 downloads cancer biology
Ludmil B. Alexandrov, Jaegil Kim, Nicholas J. Haradhvala, Mi Ni Huang, Alvin WT 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.
538 downloads cancer biology
Merkel cell carcinoma (MCC) is a highly aggressive, neuroendocrine skin cancer that is either associated with the clonal integration of the Merkel cell polyomavirus or with chronic sun exposure. Immunotherapy is initially effective in many patients with metastatic MCC, but the response is rarely durable. MCC lacks actionable mutations that could be utilized for targeted therapies, but epigenetic regulators, which govern cell fate, provide unexplored therapeutic entry points. Here, we performed a pharmacological screen in MCC cells, targeting epigenetic regulators. We discovered that the lysine-specific histone demethylase 1A (LSD1/KDM1A) is required for MCC growth in vitro and in vivo. HMG20B (BRAF35), a poorly characterized subunit of the LSD1-CoREST complex, is also essential for MCC proliferation. LSD1 inhibition in MCC disrupts the LSD1-CoREST complex, directly induces the expression of key regulators of the neuronal lineage and of members of the TGFβ pathway, and activates a gene expression signature corresponding to normal Merkel cells. Our results provide a rationale for evaluating LSD1 inhibitors, which are currently being tested in patients with leukemia and solid tumors, in MCC. ### Competing Interest Statement The authors have declared no competing interest.
513 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
495 downloads cancer biology
Tamara Ouspenskaia, Travis Law, Karl R. Clauser, Susan Klaeger, Siranush Sarkizova, Francois 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.
492 downloads cancer biology
Wenting Zhao, Athanassios Dovas, Eleonora Francesca Spinazzi, Hanna Mendes Levitin, Pavan Upadhyayula, Tejaswi Sudhakar, Tamara Marie, Marc L Otten, Michael Sisti, Jeffrey N. Bruce, Peter Canoll, Peter A. Sims
Precision oncology requires the timely selection of effective drugs for individual patients. An ideal platform would enable rapid screening of cell type-specific drug sensitivities directly in patient tumor tissue and reveal strategies to overcome intratumoral heterogeneity. Here we combine multiplexed drug perturbation in acute slice culture from freshly resected tumors with single-cell RNA sequencing (scRNA-seq) to profile transcriptome-wide drug responses. We applied this approach to glioblastoma (GBM) and demonstrated that acute slice cultures from individual patients recapitulate the cellular and molecular features of the originating tumor tissue. Detailed investigation of etoposide, a topoisomerase poison, and the histone deacetylase (HDAC) inhibitor panobinostat in acute slice cultures revealed cell type-specific responses across multiple patients, including unexpected effects on the immune microenvironment. We anticipate that this approach will facilitate rapid, personalized drug screening to identify effective therapies for solid tumors. ### Competing Interest Statement P.A.S. is listed as an inventor on patent applications filed by Columbia University related to the microwell technology described here.
489 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.
470 downloads cancer biology
Microbial taxa that are differentially abundant between cell types are likely to be intracellular. Here we describe a new computational pipeline called CSI-Microbes (computational identification of C ell type S pecific I ntracellular Microbes ) that aims to identify such putative intracellular species from single cell RNA-seq data in a given tumor sample. CSI-microbes also includes additional steps that can be applied to filter out microbial contaminants from the bona fide microbial residents of cells in the patients. We first test and validate CSI-microbes on a dataset of immune cells deliberately infected with Salmonella . We then apply CSI-microbes to identify intracellular microbes in breast cancer and melanoma. We identify Streptomyces as differentially abundant in the tumor cells of one breast cancer sample. We further identify three bacterial genera and four fungal genera that are differentially abundant and hence likely to be intracellular in the tumor cells in melanoma samples. No cell type specific bacteria were identified in our analysis of brain tumor samples. In sum, CSI-Microbes offers a new way to identify likely intracellular microbes living within specific cell populations in malignant tumors, markedly extending upon previous studies aimed at inferring microbial abundance from bulk tumor expression data. ### Competing Interest Statement The authors have declared no competing interest.
454 downloads cancer biology
Hamad Alshetaiwi, Nicholas Pervolarakis, Laura Lynn McIntyre, Dennis Ma, Quy Nguyen, Jan Akara Rath, Kevin Nee, Grace Hernandez, Katrina Evans, Leona Torosian, Anushka Silva, Craig Walsh, Kai Kessenbrock
Myeloid-derived suppressor cells (MDSCs) are innate immune cells that acquire the capacity to suppress adaptive immune responses during cancer. It remains elusive how MDSCs differ from their normal myeloid counterparts, which limits our ability to specifically detect and therapeutically target MDSCs during cancer. Here, we used single-cell RNAseq to compare MDSC-containing splenic myeloid cells from breast tumor-bearing mice to wildtype controls. Our computational analysis of 14,646 single-cell transcriptomes reveals that MDSCs emerge through a previously unrealized aberrant neutrophil maturation trajectory in the spleen giving rise to a unique chemokine-responsive, immunosuppressive cell state that strongly differs from normal myeloid cells. We establish the first MDSC-specific gene signature and identify novel surface markers for improved detection and enrichment of MDSCs in murine and human samples. Our study provides the first single-cell transcriptional map defining the development of MDSCs, which will ultimately enable us to specifically target these cells in cancer patients.
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