Search

Your search keyword '"Tsherniak A"' showing total 621 results
Start Over Author "Tsherniak A"
621 results on '"Tsherniak A"'

1. Sparse dictionary learning recovers pleiotropy from human cell fitness screens

Author

Pan, Joshua, Kwon, Jason J., Talamas, Jessica A., Borah, Ashir A., Vazquez, Francisca, Boehm, Jesse S., Tsherniak, Aviad, Zitnik, Marinka, McFarland, James M., and Hahn, William C.

Subjects
Quantitative Biology - Quantitative Methods, Quantitative Biology - Genomics, Quantitative Biology - Molecular Networks
Abstract

In high-throughput functional genomic screens, each gene product is commonly assumed to exhibit a singular biological function within a defined protein complex or pathway. In practice, a single gene perturbation may induce multiple cascading functional outcomes, a genetic principle known as pleiotropy. Here, we model pleiotropy in fitness screen collections by representing each gene perturbation as the sum of multiple perturbations of biological functions, each harboring independent fitness effects inferred empirically from the data. Our approach ('Webster') recovered pleiotropic functions for DNA damage proteins from genotoxic fitness screens, untangled distinct signaling pathways upstream of shared effector proteins from cancer cell fitness screens, and learned aspects of the cellular hierarchy in an unsupervised manner. Modeling compound sensitivity profiles in terms of genetically defined functions recovered compound mechanisms of action. Our approach establishes a sparse approximation mechanism for unraveling complex genetic architectures underlying high-dimensional gene perturbation readouts., Comment: Accepted to the 16th Machine Learning in Computational Biology (MLCB) meeting 2021, and the Learning Meaningful Representations of Life (LMRL) Workshop at NeurIPS 2021

Published
2021

3. Genome-scale functional genomics identify genes preferentially essential for multiple myeloma cells compared to other neoplasias

Author

de Matos Simoes, Ricardo, Shirasaki, Ryosuke, Downey-Kopyscinski, Sondra L., Matthews, Geoffrey M., Barwick, Benjamin G., Gupta, Vikas A., Dupéré-Richer, Daphné, Yamano, Shizuka, Hu, Yiguo, Sheffer, Michal, Dhimolea, Eugen, Dashevsky, Olga, Gandolfi, Sara, Ishiguro, Kazuya, Meyers, Robin M., Bryan, Jordan G., Dharia, Neekesh V., Hengeveld, Paul J., Brüggenthies, Johanna B., Tang, Huihui, Aguirre, Andrew J., Sievers, Quinlan L., Ebert, Benjamin L., Glassner, Brian J., Ott, Christopher J., Bradner, James E., Kwiatkowski, Nicholas P., Auclair, Daniel, Levy, Joan, Keats, Jonathan J., Groen, Richard W. J., Gray, Nathanael S., Culhane, Aedin C., McFarland, James M., Dempster, Joshua M., Licht, Jonathan D., Boise, Lawrence H., Hahn, William C., Vazquez, Francisca, Tsherniak, Aviad, and Mitsiades, Constantine S.

Published
2023
Full Text
View/download PDF

4. Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal

Author

J. Michael Krill-Burger, Joshua M. Dempster, Ashir A. Borah, Brenton R. Paolella, David E. Root, Todd R. Golub, Jesse S. Boehm, William C. Hahn, James M. McFarland, Francisca Vazquez, and Aviad Tsherniak

Subjects
Functional genomics, Cancer genomics, Target identification, RNAi, CRISPR-Cas systems, CRISPR-Cas9 genome editing, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract Background Hundreds of functional genomic screens have been performed across a diverse set of cancer contexts, as part of efforts such as the Cancer Dependency Map, to identify gene dependencies—genes whose loss of function reduces cell viability or fitness. Recently, large-scale screening efforts have shifted from RNAi to CRISPR-Cas9, due to superior efficacy and specificity. However, many effective oncology drugs only partially inhibit their protein targets, leading us to question whether partial suppression of genes using RNAi could reveal cancer vulnerabilities that are missed by complete knockout using CRISPR-Cas9. Here, we compare CRISPR-Cas9 and RNAi dependency profiles of genes across approximately 400 matched cancer cell lines. Results We find that CRISPR screens accurately identify more gene dependencies per cell line, but the majority of each cell line’s dependencies are part of a set of 1867 genes that are shared dependencies across the entire collection (pan-lethals). While RNAi knockdown of about 30% of these genes is also pan-lethal, approximately 50% have selective dependency patterns across cell lines, suggesting they could still be cancer vulnerabilities. The accuracy of the unique RNAi selectivity is supported by associations to multi-omics profiles, drug sensitivity, and other expected co-dependencies. Conclusions Incorporating RNAi data for genes that are pan-lethal knockouts facilitates the discovery of a wider range of gene targets than could be detected using the CRISPR dataset alone. This can aid in the interpretation of contrasting results obtained from CRISPR and RNAi screens and reinforce the importance of partial gene suppression methods in building a cancer dependency map.

Published
2023
Full Text
View/download PDF

5. Next-generation characterization of the Cancer Cell Line Encyclopedia

Author

Ghandi, Mahmoud, Huang, Franklin W, Jané-Valbuena, Judit, Kryukov, Gregory V, Lo, Christopher C, McDonald, E Robert, Barretina, Jordi, Gelfand, Ellen T, Bielski, Craig M, Li, Haoxin, Hu, Kevin, Andreev-Drakhlin, Alexander Y, Kim, Jaegil, Hess, Julian M, Haas, Brian J, Aguet, François, Weir, Barbara A, Rothberg, Michael V, Paolella, Brenton R, Lawrence, Michael S, Akbani, Rehan, Lu, Yiling, Tiv, Hong L, Gokhale, Prafulla C, de Weck, Antoine, Mansour, Ali Amin, Oh, Coyin, Shih, Juliann, Hadi, Kevin, Rosen, Yanay, Bistline, Jonathan, Venkatesan, Kavitha, Reddy, Anupama, Sonkin, Dmitriy, Liu, Manway, Lehar, Joseph, Korn, Joshua M, Porter, Dale A, Jones, Michael D, Golji, Javad, Caponigro, Giordano, Taylor, Jordan E, Dunning, Caitlin M, Creech, Amanda L, Warren, Allison C, McFarland, James M, Zamanighomi, Mahdi, Kauffmann, Audrey, Stransky, Nicolas, Imielinski, Marcin, Maruvka, Yosef E, Cherniack, Andrew D, Tsherniak, Aviad, Vazquez, Francisca, Jaffe, Jacob D, Lane, Andrew A, Weinstock, David M, Johannessen, Cory M, Morrissey, Michael P, Stegmeier, Frank, Schlegel, Robert, Hahn, William C, Getz, Gad, Mills, Gordon B, Boehm, Jesse S, Golub, Todd R, Garraway, Levi A, and Sellers, William R

Subjects
Genetics, Human Genome, Lung, Cancer, Biotechnology, Lung Cancer, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Antineoplastic Agents, Biomarkers, Tumor, Cell Line, Tumor, DNA Methylation, Drug Resistance, Neoplasm, Ethnicity, Gene Editing, Histones, Humans, MicroRNAs, Molecular Targeted Therapy, Neoplasms, Protein Array Analysis, RNA Splicing, General Science & Technology
Abstract

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.

Published
2019

7. Genome-scale analysis identifies paralog lethality as a vulnerability of chromosome 1p loss in cancer

Author

Viswanathan, Srinivas R, Nogueira, Marina F, Buss, Colin G, Krill-Burger, John M, Wawer, Mathias J, Malolepsza, Edyta, Berger, Ashton C, Choi, Peter S, Shih, Juliann, Taylor, Alison M, Tanenbaum, Benjamin, Pedamallu, Chandra Sekhar, Cherniack, Andrew D, Tamayo, Pablo, Strathdee, Craig A, Lage, Kasper, Carr, Steven A, Schenone, Monica, Bhatia, Sangeeta N, Vazquez, Francisca, Tsherniak, Aviad, Hahn, William C, and Meyerson, Matthew

Subjects
Cancer, Pediatric Research Initiative, Lung Cancer, Human Genome, Lung, Biotechnology, Genetics, Aetiology, 2.1 Biological and endogenous factors, Animals, Cell Line, Tumor, Cell Nucleus, Chromosomes, Human, Pair 1, Exons, Female, Gene Deletion, HEK293 Cells, Humans, Karyopherins, Mice, Mice, Nude, Neoplasms, Nuclear Proteins, RNA Splicing, RNA, Small Interfering, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Functional redundancy shared by paralog genes may afford protection against genetic perturbations, but it can also result in genetic vulnerabilities due to mutual interdependency1-5. Here, we surveyed genome-scale short hairpin RNA and CRISPR screening data on hundreds of cancer cell lines and identified MAGOH and MAGOHB, core members of the splicing-dependent exon junction complex, as top-ranked paralog dependencies6-8. MAGOHB is the top gene dependency in cells with hemizygous MAGOH deletion, a pervasive genetic event that frequently occurs due to chromosome 1p loss. Inhibition of MAGOHB in a MAGOH-deleted context compromises viability by globally perturbing alternative splicing and RNA surveillance. Dependency on IPO13, an importin-β receptor that mediates nuclear import of the MAGOH/B-Y14 heterodimer9, is highly correlated with dependency on both MAGOH and MAGOHB. Both MAGOHB and IPO13 represent dependencies in murine xenografts with hemizygous MAGOH deletion. Our results identify MAGOH and MAGOHB as reciprocal paralog dependencies across cancer types and suggest a rationale for targeting the MAGOHB-IPO13 axis in cancers with chromosome 1p deletion.

Published
2018

8. CRISPR-Cas9 screen reveals a MYCN-amplified neuroblastoma dependency on EZH2

Author

Chen, Liying, Alexe, Gabriela, Dharia, Neekesh V, Ross, Linda, Iniguez, Amanda Balboni, Conway, Amy Saur, Wang, Emily Jue, Veschi, Veronica, Lam, Norris, Qi, Jun, Gustafson, W Clay, Nasholm, Nicole, Vazquez, Francisca, Weir, Barbara A, Cowley, Glenn S, Ali, Levi D, Pantel, Sasha, Jiang, Guozhi, Harrington, William F, Lee, Yenarae, Goodale, Amy, Lubonja, Rakela, Krill-Burger, John M, Meyers, Robin M, Tsherniak, Aviad, Root, David E, Bradner, James E, Golub, Todd R, Roberts, Charles WM, Hahn, William C, Weiss, William A, Thiele, Carol J, and Stegmaier, Kimberly

Subjects
Neuroblastoma, Rare Diseases, Human Genome, Cancer, Pediatric Cancer, Pediatric Research Initiative, Neurosciences, Pediatric, Genetics, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, CRISPR-Cas Systems, Cell Differentiation, Cell Line, Tumor, Enhancer of Zeste Homolog 2 Protein, Gene Amplification, Gene Expression Regulation, Neoplastic, Humans, N-Myc Proto-Oncogene Protein, Neurons, Up-Regulation, Epigenetics, Oncology, Medical and Health Sciences, Immunology
Abstract

Pharmacologically difficult targets, such as MYC transcription factors, represent a major challenge in cancer therapy. For the childhood cancer neuroblastoma, amplification of the oncogene MYCN is associated with high-risk disease and poor prognosis. Here, we deployed genome-scale CRISPR-Cas9 screening of MYCN-amplified neuroblastoma and found a preferential dependency on genes encoding the polycomb repressive complex 2 (PRC2) components EZH2, EED, and SUZ12. Genetic and pharmacological suppression of EZH2 inhibited neuroblastoma growth in vitro and in vivo. Moreover, compared with neuroblastomas without MYCN amplification, MYCN-amplified neuroblastomas expressed higher levels of EZH2. ChIP analysis showed that MYCN binds at the EZH2 promoter, thereby directly driving expression. Transcriptomic and epigenetic analysis, as well as genetic rescue experiments, revealed that EZH2 represses neuronal differentiation in neuroblastoma in a PRC2-dependent manner. Moreover, MYCN-amplified and high-risk primary tumors from patients with neuroblastoma exhibited strong repression of EZH2-regulated genes. Additionally, overexpression of IGFBP3, a direct EZH2 target, suppressed neuroblastoma growth in vitro and in vivo. We further observed strong synergy between histone deacetylase inhibitors and EZH2 inhibitors. Together, these observations demonstrate that MYCN upregulates EZH2, leading to inactivation of a tumor suppressor program in neuroblastoma, and support testing EZH2 inhibitors in patients with MYCN-amplified neuroblastoma.

Published
2018

9. Chronos: a cell population dynamics model of CRISPR experiments that improves inference of gene fitness effects

Author

Joshua M. Dempster, Isabella Boyle, Francisca Vazquez, David E. Root, Jesse S. Boehm, William C. Hahn, Aviad Tsherniak, and James M. McFarland

Subjects
Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract CRISPR loss of function screens are powerful tools to interrogate biology but exhibit a number of biases and artifacts that can confound the results. Here, we introduce Chronos, an algorithm for inferring gene knockout fitness effects based on an explicit model of cell proliferation dynamics after CRISPR gene knockout. We test Chronos on two pan-cancer CRISPR datasets and one longitudinal CRISPR screen. Chronos generally outperforms competitors in separation of controls and strength of biomarker associations, particularly when longitudinal data is available. Additionally, Chronos exhibits the lowest copy number and screen quality bias of evaluated methods. Chronos is available at https://github.com/broadinstitute/chronos .

Published
2021
Full Text
View/download PDF

10. A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines

Author

Gönen, Mehmet, Weir, Barbara A, Cowley, Glenn S, Vazquez, Francisca, Guan, Yuanfang, Jaiswal, Alok, Karasuyama, Masayuki, Uzunangelov, Vladislav, Wang, Tao, Tsherniak, Aviad, Howell, Sara, Marbach, Daniel, Hoff, Bruce, Norman, Thea C, Airola, Antti, Bivol, Adrian, Bunte, Kerstin, Carlin, Daniel, Chopra, Sahil, Deran, Alden, Ellrott, Kyle, Gopalacharyulu, Peddinti, Graim, Kiley, Kaski, Samuel, Khan, Suleiman A, Newton, Yulia, Ng, Sam, Pahikkala, Tapio, Paull, Evan, Sokolov, Artem, Tang, Hao, Tang, Jing, Wennerberg, Krister, Xie, Yang, Zhan, Xiaowei, Zhu, Fan, Community, Broad-DREAM, Afsari, Bahman, Aittokallio, Tero, Boehm, Jesse S, Chang, Yu-Chuan, Chen, Tenghui, Chong, Zechen, Elmarakeby, Haitham, Fertig, Elana J, Gonçalves, Emanuel, Gong, Pinghua, Hafemeister, Christoph, Hahn, William C, Heath, Lenwood, Kędziorski, Łukasz, Khemka, Niraj, King, Erh-kan, Lauria, Mario, Liu, Mark, Machado, Daniel, Mamitsuka, Hiroshi, Margolin, Adam A, Mazurkiewicz, Mateusz, Menden, Michael P, Migacz, Szymon, Nie, Zhi, Praveen, Paurush, Priami, Corrado, Rizzetto, Simone, Rocha, Miguel, Root, David E, Rudd, Cameron, Rudnicki, Witold R, Saez-Rodriguez, Julio, Song, Lei, Stolovitzky, Gustavo, Stuart, Joshua M, Sun, Duanchen, and Szalai, Bence

Subjects
Biological Sciences, Genetics, Biotechnology, Prevention, Cancer, Human Genome, Algorithms, Cell Line, Tumor, Gene Expression, Genes, Essential, Genomics, Humans, RNA, Small Interfering, Broad-DREAM Community, cancer genomics, community challenge, crowdsourcing, functional screen, machine learning, oncogene, Biochemistry and Cell Biology, Biochemistry and cell biology
Abstract

We report the results of a DREAM challenge designed to predict relative genetic essentialities based on a novel dataset testing 98,000 shRNAs against 149 molecularly characterized cancer cell lines. We analyzed the results of over 3,000 submissions over a period of 4 months. We found that algorithms combining essentiality data across multiple genes demonstrated increased accuracy; gene expression was the most informative molecular data type; the identity of the gene being predicted was far more important than the modeling strategy; well-predicted genes and selected molecular features showed enrichment in functional categories; and frequently selected expression features correlated with survival in primary tumors. This study establishes benchmarks for gene essentiality prediction, presents a community resource for future comparison with this benchmark, and provides insights into factors influencing the ability to predict gene essentiality from functional genetic screens. This study also demonstrates the value of releasing pre-publication data publicly to engage the community in an open research collaboration.

Published
2017

11. Decomposing Oncogenic Transcriptional Signatures to Generate Maps of Divergent Cellular States

Author

Kim, Jong Wook, Abudayyeh, Omar O, Yeerna, Huwate, Yeang, Chen-Hsiang, Stewart, Michelle, Jenkins, Russell W, Kitajima, Shunsuke, Konieczkowski, David J, Medetgul-Ernar, Kate, Cavazos, Taylor, Mah, Clarence, Ting, Stephanie, Van Allen, Eliezer M, Cohen, Ofir, Mcdermott, John, Damato, Emily, Aguirre, Andrew J, Liang, Jonathan, Liberzon, Arthur, Alexe, Gabriella, Doench, John, Ghandi, Mahmoud, Vazquez, Francisca, Weir, Barbara A, Tsherniak, Aviad, Subramanian, Aravind, Meneses-Cime, Karina, Park, Jason, Clemons, Paul, Garraway, Levi A, Thomas, David, Boehm, Jesse S, Barbie, David A, Hahn, William C, Mesirov, Jill P, and Tamayo, Pablo

Subjects
Biological Sciences, Genetics, Biotechnology, Human Genome, Cancer, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Biomarkers, Tumor, Cell Line, Tumor, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Genes, ras, Genome, Humans, MAP Kinase Signaling System, Neoplasms, Precision Medicine, Bayesian nomogram, cellular states, drug sensitivity, genetic dependency, inferential model, matrix factorization, oncoGPS, oncogenic pathway, precision medicine, transcriptional signatures, Biochemistry and Cell Biology, Biochemistry and cell biology
Abstract

The systematic sequencing of the cancer genome has led to the identification of numerous genetic alterations in cancer. However, a deeper understanding of the functional consequences of these alterations is necessary to guide appropriate therapeutic strategies. Here, we describe Onco-GPS (OncoGenic Positioning System), a data-driven analysis framework to organize individual tumor samples with shared oncogenic alterations onto a reference map defined by their underlying cellular states. We applied the methodology to the RAS pathway and identified nine distinct components that reflect transcriptional activities downstream of RAS and defined several functional states associated with patterns of transcriptional component activation that associates with genomic hallmarks and response to genetic and pharmacological perturbations. These results show that the Onco-GPS is an effective approach to explore the complex landscape of oncogenic cellular states across cancers, and an analytic framework to summarize knowledge, establish relationships, and generate more effective disease models for research or as part of individualized precision medicine paradigms.

Published
2017

12. Genome-scale screens identify factors regulating tumor cell responses to natural killer cells

Author

Sheffer, Michal, Lowry, Emily, Beelen, Nicky, Borah, Minasri, Amara, Suha Naffar-Abu, Mader, Chris C., Roth, Jennifer A., Tsherniak, Aviad, Freeman, Samuel S., Dashevsky, Olga, Gandolfi, Sara, Bender, Samantha, Bryan, Jordan G., Zhu, Cong, Wang, Li, Tariq, Ifrah, Kamath, Govinda M., Simoes, Ricardo De Matos, Dhimolea, Eugen, Yu, Channing, Hu, Yiguo, Dufva, Olli, Giannakis, Marios, Syrgkanis, Vasilis, Fraenkel, Ernest, Golub, Todd, Romee, Rizwan, Mustjoki, Satu, Culhane, Aedin C., Wieten, Lotte, and Mitsiades, Constantine S.

Published
2021
Full Text
View/download PDF

13. Integrated cross-study datasets of genetic dependencies in cancer

Author

Clare Pacini, Joshua M. Dempster, Isabella Boyle, Emanuel Gonçalves, Hanna Najgebauer, Emre Karakoc, Dieudonne van der Meer, Andrew Barthorpe, Howard Lightfoot, Patricia Jaaks, James M. McFarland, Mathew J. Garnett, Aviad Tsherniak, and Francesco Iorio

Subjects
Science
Abstract

The integration of independent pan-cancer CRISPR-Cas9 datasets allows better representation of genomic heterogeneity across different cancer types. Here, the authors propose a strategy for the integration of two large CRISPR-Cas9 screens and report increased coverage of molecular diversity and genetic dependencies.

Published
2021
Full Text
View/download PDF

14. A first-generation pediatric cancer dependency map

Author

Dharia, Neekesh V., Kugener, Guillaume, Guenther, Lillian M., Malone, Clare F., Durbin, Adam D., Hong, Andrew L., Howard, Thomas P., Bandopadhayay, Pratiti, Wechsler, Caroline S., Fung, Iris, Warren, Allison C., Dempster, Joshua M., Krill-Burger, John M., Paolella, Brenton R., Moh, Phoebe, Jha, Nishant, Tang, Andrew, Montgomery, Philip, Boehm, Jesse S., Hahn, William C., Roberts, Charles W. M., McFarland, James M., Tsherniak, Aviad, Golub, Todd R., Vazquez, Francisca, and Stegmaier, Kimberly

Published
2021
Full Text
View/download PDF

15. Global computational alignment of tumor and cell line transcriptional profiles

Author

Allison Warren, Yejia Chen, Andrew Jones, Tsukasa Shibue, William C. Hahn, Jesse S. Boehm, Francisca Vazquez, Aviad Tsherniak, and James M. McFarland

Subjects
Science
Abstract

The determination of whether cancer cell lines recapitulate the molecular features of corresponding patient tumours remains essential for the selection of appropriate cell line models for preclinical studies. The method developed here, Celligner, integrates cancer cell line and tumour RNA-seq datasets and reveals large differences in their concordance across cell lines and cancer types.

Published
2021
Full Text
View/download PDF

16. Characterizing genomic alterations in cancer by complementary functional associations

Author

Kim, Jong Wook, Botvinnik, Olga B, Abudayyeh, Omar, Birger, Chet, Rosenbluh, Joseph, Shrestha, Yashaswi, Abazeed, Mohamed E, Hammerman, Peter S, DiCara, Daniel, Konieczkowski, David J, Johannessen, Cory M, Liberzon, Arthur, Alizad-Rahvar, Amir Reza, Alexe, Gabriela, Aguirre, Andrew, Ghandi, Mahmoud, Greulich, Heidi, Vazquez, Francisca, Weir, Barbara A, Van Allen, Eliezer M, Tsherniak, Aviad, Shao, Diane D, Zack, Travis I, Noble, Michael, Getz, Gad, Beroukhim, Rameen, Garraway, Levi A, Ardakani, Masoud, Romualdi, Chiara, Sales, Gabriele, Barbie, David A, Boehm, Jesse S, Hahn, William C, Mesirov, Jill P, and Tamayo, Pablo

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Cancer, Good Health and Well Being, Biomarkers, Tumor, Chromosome Mapping, Drug Resistance, Neoplasm, Genes, Neoplasm, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Mutation, Neoplasm Proteins, Neoplasms, Polymorphism, Single Nucleotide, Signal Transduction
Abstract

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes.

Published
2016

17. High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines

Author

Yu, Channing, Mannan, Aristotle M, Yvone, Griselda Metta, Ross, Kenneth N, Zhang, Yan-Ling, Marton, Melissa A, Taylor, Bradley R, Crenshaw, Andrew, Gould, Joshua Z, Tamayo, Pablo, Weir, Barbara A, Tsherniak, Aviad, Wong, Bang, Garraway, Levi A, Shamji, Alykhan F, Palmer, Michelle A, Foley, Michael A, Winckler, Wendy, Schreiber, Stuart L, Kung, Andrew L, and Golub, Todd R

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer, Animals, Cell Line, Tumor, DNA Barcoding, Taxonomic, Drug Resistance, Neoplasm, Genotyping Techniques, High-Throughput Nucleotide Sequencing, Humans, Mice, Neoplasms
Abstract

Hundreds of genetically characterized cell lines are available for the discovery of genotype-specific cancer vulnerabilities. However, screening large numbers of compounds against large numbers of cell lines is currently impractical, and such experiments are often difficult to control. Here we report a method called PRISM that allows pooled screening of mixtures of cancer cell lines by labeling each cell line with 24-nucleotide barcodes. PRISM revealed the expected patterns of cell killing seen in conventional (unpooled) assays. In a screen of 102 cell lines across 8,400 compounds, PRISM led to the identification of BRD-7880 as a potent and highly specific inhibitor of aurora kinases B and C. Cell line pools also efficiently formed tumors as xenografts, and PRISM recapitulated the expected pattern of erlotinib sensitivity in vivo.

Published
2016

18. Multiplexed single-cell transcriptional response profiling to define cancer vulnerabilities and therapeutic mechanism of action

Author

James M. McFarland, Brenton R. Paolella, Allison Warren, Kathryn Geiger-Schuller, Tsukasa Shibue, Michael Rothberg, Olena Kuksenko, William N. Colgan, Andrew Jones, Emily Chambers, Danielle Dionne, Samantha Bender, Brian M. Wolpin, Mahmoud Ghandi, Itay Tirosh, Orit Rozenblatt-Rosen, Jennifer A. Roth, Todd R. Golub, Aviv Regev, Andrew J. Aguirre, Francisca Vazquez, and Aviad Tsherniak

Subjects
Science
Abstract

Large-scale screens of chemical and genetic vulnerabilities in cancer are typically limited to simple readouts of cell viability. Here, the authors develop a method for profiling post-perturbation transcriptional responses across large pools of cancer cell lines, enabling deep characterization of shared and context-specific responses.

Published
2020
Full Text
View/download PDF

22. Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets

Author

Joshua M. Dempster, Clare Pacini, Sasha Pantel, Fiona M. Behan, Thomas Green, John Krill-Burger, Charlotte M. Beaver, Scott T. Younger, Victor Zhivich, Hanna Najgebauer, Felicity Allen, Emanuel Gonçalves, Rebecca Shepherd, John G. Doench, Kosuke Yusa, Francisca Vazquez, Leopold Parts, Jesse S. Boehm, Todd R. Golub, William C. Hahn, David E. Root, Mathew J. Garnett, Aviad Tsherniak, and Francesco Iorio

Subjects
Science
Abstract

Integrating independent large-scale pharmacogenomic screens can enable unprecedented characterization of genetic vulnerabilities in cancers. Here, the authors show that the two largest independent CRISPR-Cas9 gene-dependency screens are concordant, paving the way for joint analysis of the data sets.

Published
2019
Full Text
View/download PDF

23. Pan-cancer single-cell RNA-seq identifies recurring programs of cellular heterogeneity

Author

Kinker, Gabriela S., Greenwald, Alissa C., Tal, Rotem, Orlova, Zhanna, Cuoco, Michael S., McFarland, James M., Warren, Allison, Rodman, Christopher, Roth, Jennifer A., Bender, Samantha A., Kumar, Bhavna, Rocco, James W., Fernandes, Pedro A. C. M., Mader, Christopher C., Keren-Shaul, Hadas, Plotnikov, Alexander, Barr, Haim, Tsherniak, Aviad, Rozenblatt-Rosen, Orit, Krizhanovsky, Valery, Puram, Sidharth V., Regev, Aviv, and Tirosh, Itay

Published
2020
Full Text
View/download PDF

24. Discovering the anticancer potential of non-oncology drugs by systematic viability profiling

Author

Corsello, Steven M., Nagari, Rohith T., Spangler, Ryan D., Rossen, Jordan, Kocak, Mustafa, Bryan, Jordan G., Humeidi, Ranad, Peck, David, Wu, Xiaoyun, Tang, Andrew A., Wang, Vickie M., Bender, Samantha A., Lemire, Evan, Narayan, Rajiv, Montgomery, Philip, Ben-David, Uri, Garvie, Colin W., Chen, Yejia, Rees, Matthew G., Lyons, Nicholas J., McFarland, James M., Wong, Bang T., Wang, Li, Dumont, Nancy, O’Hearn, Patrick J., Stefan, Eric, Doench, John G., Harrington, Caitlin N., Greulich, Heidi, Meyerson, Matthew, Vazquez, Francisca, Subramanian, Aravind, Roth, Jennifer A., Bittker, Joshua A., Boehm, Jesse S., Mader, Christopher C., Tsherniak, Aviad, and Golub, Todd R.

Published
2020
Full Text
View/download PDF

25. Synthetic Lethal Interaction between the ESCRT Paralog Enzymes VPS4A and VPS4B in Cancers Harboring Loss of Chromosome 18q or 16q

Author

Jasper E. Neggers, Brenton R. Paolella, Adhana Asfaw, Michael V. Rothberg, Thomas A. Skipper, Annan Yang, Radha L. Kalekar, John M. Krill-Burger, Neekesh V. Dharia, Guillaume Kugener, Jérémie Kalfon, Chen Yuan, Nancy Dumont, Alfredo Gonzalez, Mai Abdusamad, Yvonne Y. Li, Liam F. Spurr, Westley W. Wu, Adam D. Durbin, Brian M. Wolpin, Federica Piccioni, David E. Root, Jesse S. Boehm, Andrew D. Cherniack, Aviad Tsherniak, Andrew L. Hong, William C. Hahn, Kimberly Stegmaier, Todd R. Golub, Francisca Vazquez, and Andrew J. Aguirre

Subjects
Biology (General), QH301-705.5
Published
2021
Full Text
View/download PDF

26. Erratum: Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies

Author

Cowley, Glenn S, Weir, Barbara A, Vazquez, Francisca, Tamayo, Pablo, Scott, Justine A, Rusin, Scott, East-Seletsky, Alexandra, Ali, Levi D, Gerath, William FJ, Pantel, Sarah E, Lizotte, Patrick H, Jiang, Guozhi, Hsiao, Jessica, Tsherniak, Aviad, Dwinell, Elizabeth, Aoyama, Simon, Okamoto, Michael, Harrington, William, Gelfand, Ellen, Green, Thomas M, Tomko, Mark J, Gopal, Shuba, Wong, Terence C, Li, Hubo, Howell, Sara, Stransky, Nicolas, Liefeld, Ted, Jang, Dongkeun, Bistline, Jonathan, Meyers, Barbara Hill, Armstrong, Scott A, Anderson, Ken C, Stegmaier, Kimberly, Reich, Michael, Pellman, David, Boehm, Jesse S, Mesirov, Jill P, Golub, Todd R, Root, David E, and Hahn, William C

Subjects
Biological Sciences, Genetics, Cancer, Bioinformatics and Computational Biology, Biotechnology, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Cell Line, Tumor, Cell Lineage, Cell Proliferation, DNA, Neoplasm, Gene Expression Regulation, Neoplastic, Genomics, Humans, Mutation, Neoplasms, RNA, Small Interfering
Abstract

Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,000 shRNAs after 16 population doublings using Next Generation Sequencing. All the cell lines were screened using standardized conditions to best assess differential genetic dependencies across cell lines. When combined with genomic characterization of these cell lines, this dataset facilitates the linkage of genetic dependencies with specific cellular contexts (e.g., gene mutations or cell lineage). To enable such comparisons, we developed and provided a bioinformatics tool to identify linear and nonlinear correlations between these features.

Published
2014

27. Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies.

Author

Cowley, Glenn S, Weir, Barbara A, Vazquez, Francisca, Tamayo, Pablo, Scott, Justine A, Rusin, Scott, East-Seletsky, Alexandra, Ali, Levi D, Gerath, William Fj, Pantel, Sarah E, Lizotte, Patrick H, Jiang, Guozhi, Hsiao, Jessica, Tsherniak, Aviad, Dwinell, Elizabeth, Aoyama, Simon, Okamoto, Michael, Harrington, William, Gelfand, Ellen, Green, Thomas M, Tomko, Mark J, Gopal, Shuba, Wong, Terence C, Li, Hubo, Howell, Sara, Stransky, Nicolas, Liefeld, Ted, Jang, Dongkeun, Bistline, Jonathan, Hill Meyers, Barbara, Armstrong, Scott A, Anderson, Ken C, Stegmaier, Kimberly, Reich, Michael, Pellman, David, Boehm, Jesse S, Mesirov, Jill P, Golub, Todd R, Root, David E, and Hahn, William C

Subjects
Cell Line, Tumor, Humans, Neoplasms, RNA, Small Interfering, DNA, Neoplasm, Genomics, Cell Proliferation, Gene Expression Regulation, Neoplastic, Cell Lineage, Mutation, Biotechnology, Genetics, Cancer, Human Genome, 2.1 Biological and endogenous factors
Abstract

Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,000 shRNAs after 16 population doublings using Next Generation Sequencing. All the cell lines were screened using standardized conditions to best assess differential genetic dependencies across cell lines. When combined with genomic characterization of these cell lines, this dataset facilitates the linkage of genetic dependencies with specific cellular contexts (e.g., gene mutations or cell lineage). To enable such comparisons, we developed and provided a bioinformatics tool to identify linear and nonlinear correlations between these features.

Published
2014

28. Neuronal differentiation and cell-cycle programs mediate response to BET-bromodomain inhibition in MYC-driven medulloblastoma

Author

Pratiti Bandopadhayay, Federica Piccioni, Ryan O’Rourke, Patricia Ho, Elizabeth M. Gonzalez, Graham Buchan, Kenin Qian, Gabrielle Gionet, Emily Girard, Margo Coxon, Matthew G. Rees, Lisa Brenan, Frank Dubois, Ofer Shapira, Noah F. Greenwald, Melanie Pages, Amanda Balboni Iniguez, Brenton R. Paolella, Alice Meng, Claire Sinai, Giovanni Roti, Neekesh V. Dharia, Amanda Creech, Benjamin Tanenbaum, Prasidda Khadka, Adam Tracy, Hong L. Tiv, Andrew L. Hong, Shannon Coy, Rumana Rashid, Jia-Ren Lin, Glenn S. Cowley, Fred C. Lam, Amy Goodale, Yenarae Lee, Kathleen Schoolcraft, Francisca Vazquez, William C. Hahn, Aviad Tsherniak, James E. Bradner, Michael B. Yaffe, Till Milde, Stefan M. Pfister, Jun Qi, Monica Schenone, Steven A. Carr, Keith L. Ligon, Mark W. Kieran, Sandro Santagata, James M. Olson, Prafulla C. Gokhale, Jacob D. Jaffe, David E. Root, Kimberly Stegmaier, Cory M. Johannessen, and Rameen Beroukhim

Subjects
Science
Abstract

BET-bromodomain inhibitors could be used to treat medulloblastoma tumors with Myc amplifications. Here, the authors show that both the response and resistance to BET inhibitors in mice is mediated by bHLH/homeobox transcription factors.

Published
2019
Full Text
View/download PDF

29. Identification of ADAR1 adenosine deaminase dependency in a subset of cancer cells

Author

Hugh S. Gannon, Tao Zou, Michael K. Kiessling, Galen F. Gao, Diana Cai, Peter S. Choi, Alexandru P. Ivan, Ilana Buchumenski, Ashton C. Berger, Jonathan T. Goldstein, Andrew D. Cherniack, Francisca Vazquez, Aviad Tsherniak, Erez Y. Levanon, William C. Hahn, and Matthew Meyerson

Subjects
Science
Abstract

Specific cancer cell vulnerabilities can provide an opportunity for the development of novel cancer therapeutics. In this study the authors demonstrate that targeting ADAR1 represents a potential therapeutic vulnerability in cancers with activated interferon response signatures.

Published
2018
Full Text
View/download PDF

30. Genome-scale functional genomics identify genes preferentially essential for multiple myeloma cells compared to other neoplasias

Author

Ricardo de Matos Simoes, Ryosuke Shirasaki, Sondra L. Downey-Kopyscinski, Geoffrey M. Matthews, Benjamin G. Barwick, Vikas A. Gupta, Daphné Dupéré-Richer, Shizuka Yamano, Yiguo Hu, Michal Sheffer, Eugen Dhimolea, Olga Dashevsky, Sara Gandolfi, Kazuya Ishiguro, Robin M. Meyers, Jordan G. Bryan, Neekesh V. Dharia, Paul J. Hengeveld, Johanna B. Brüggenthies, Huihui Tang, Andrew J. Aguirre, Quinlan L. Sievers, Benjamin L. Ebert, Brian J. Glassner, Christopher J. Ott, James E. Bradner, Nicholas P. Kwiatkowski, Daniel Auclair, Joan Levy, Jonathan J. Keats, Richard W. J. Groen, Nathanael S. Gray, Aedin C. Culhane, James M. McFarland, Joshua M. Dempster, Jonathan D. Licht, Lawrence H. Boise, William C. Hahn, Francisca Vazquez, Aviad Tsherniak, Constantine S. Mitsiades, Hematology laboratory, AMS - Tissue Function & Regeneration, and CCA - Cancer biology and immunology

Subjects
Cancer Research, Oncology
Abstract

Clinical progress in multiple myeloma (MM), an incurable plasma cell (PC) neoplasia, has been driven by therapies that have limited applications beyond MM/PC neoplasias and do not target specific oncogenic mutations in MM. Instead, these agents target pathways critical for PC biology yet largely dispensable for malignant or normal cells of most other lineages. Here we systematically characterized the lineage-preferential molecular dependencies of MM through genome-scale clustered regularly interspaced short palindromic repeats (CRISPR) studies in 19 MM versus hundreds of non-MM lines and identified 116 genes whose disruption more significantly affects MM cell fitness compared with other malignancies. These genes, some known, others not previously linked to MM, encode transcription factors, chromatin modifiers, endoplasmic reticulum components, metabolic regulators or signaling molecules. Most of these genes are not among the top amplified, overexpressed or mutated in MM. Functional genomics approaches thus define new therapeutic targets in MM not readily identifiable by standard genomic, transcriptional or epigenetic profiling analyses.

Published
2023

31. Synthetic Lethal Interaction between the ESCRT Paralog Enzymes VPS4A and VPS4B in Cancers Harboring Loss of Chromosome 18q or 16q

Author

Jasper E. Neggers, Brenton R. Paolella, Adhana Asfaw, Michael V. Rothberg, Thomas A. Skipper, Annan Yang, Radha L. Kalekar, John M. Krill-Burger, Neekesh V. Dharia, Guillaume Kugener, Jérémie Kalfon, Chen Yuan, Nancy Dumont, Alfredo Gonzalez, Mai Abdusamad, Yvonne Y. Li, Liam F. Spurr, Westley W. Wu, Adam D. Durbin, Brian M. Wolpin, Federica Piccioni, David E. Root, Jesse S. Boehm, Andrew D. Cherniack, Aviad Tsherniak, Andrew L. Hong, William C. Hahn, Kimberly Stegmaier, Todd R. Golub, Francisca Vazquez, and Andrew J. Aguirre

Subjects
VPS4A, VPS4B, synthetic lethality, cancer, 18q loss, 16q loss, Biology (General), QH301-705.5
Abstract

Summary: Few therapies target the loss of tumor suppressor genes in cancer. We examine CRISPR-SpCas9 and RNA-interference loss-of-function screens to identify new therapeutic targets associated with genomic loss of tumor suppressor genes. The endosomal sorting complexes required for transport (ESCRT) ATPases VPS4A and VPS4B score as strong synthetic lethal dependencies. VPS4A is essential in cancers harboring loss of VPS4B adjacent to SMAD4 on chromosome 18q and VPS4B is required in tumors with co-deletion of VPS4A and CDH1 (E-cadherin) on chromosome 16q. We demonstrate that more than 30% of cancers selectively require VPS4A or VPS4B. VPS4A suppression in VPS4B-deficient cells selectively leads to ESCRT-III filament accumulation, cytokinesis defects, nuclear deformation, G2/M arrest, apoptosis, and potent tumor regression. CRISPR-SpCas9 screening and integrative genomic analysis reveal other ESCRT members, regulators of abscission, and interferon signaling as modifiers of VPS4A dependency. We describe a compendium of synthetic lethal vulnerabilities and nominate VPS4A and VPS4B as high-priority therapeutic targets for cancers with 18q or 16q loss.

Published
2020
Full Text
View/download PDF

33. Mitochondrial metabolism promotes adaptation to proteotoxic stress

Author

Tsvetkov, Peter, Detappe, Alexandre, Cai, Kai, Keys, Heather R., Brune, Zarina, Ying, Weiwen, Thiru, Prathapan, Reidy, Mairead, Kugener, Guillaume, Rossen, Jordan, Kocak, Mustafa, Kory, Nora, Tsherniak, Aviad, Santagata, Sandro, Whitesell, Luke, Ghobrial, Irene M., Markley, John L., Lindquist, Susan, and Golub, Todd R.

Published
2019
Full Text
View/download PDF

34. The landscape of cancer cell line metabolism

Author

Li, Haoxin, Ning, Shaoyang, Ghandi, Mahmoud, Kryukov, Gregory V., Gopal, Shuba, Deik, Amy, Souza, Amanda, Pierce, Kerry, Keskula, Paula, Hernandez, Desiree, Ann, Julie, Shkoza, Dojna, Apfel, Verena, Zou, Yilong, Vazquez, Francisca, Barretina, Jordi, Pagliarini, Raymond A., Galli, Giorgio G., Root, David E., Hahn, William C., Tsherniak, Aviad, Giannakis, Marios, Schreiber, Stuart L., Clish, Clary B., Garraway, Levi A., and Sellers, William R.

Published
2019
Full Text
View/download PDF

35. WRN helicase is a synthetic lethal target in microsatellite unstable cancers

Author

Chan, Edmond M., Shibue, Tsukasa, McFarland, James M., Gaeta, Benjamin, Ghandi, Mahmoud, Dumont, Nancy, Gonzalez, Alfredo, McPartlan, Justine S., Li, Tianxia, Zhang, Yanxi, Bin Liu, Jie, Lazaro, Jean-Bernard, Gu, Peili, Piett, Cortt G., Apffel, Annie, Ali, Syed O., Deasy, Rebecca, Keskula, Paula, Ng, Raymond W. S., Roberts, Emma A., Reznichenko, Elizaveta, Leung, Lisa, Alimova, Maria, Schenone, Monica, Islam, Mirazul, Maruvka, Yosef E., Liu, Yang, Roper, Jatin, Raghavan, Srivatsan, Giannakis, Marios, Tseng, Yuen-Yi, Nagel, Zachary D., D’Andrea, Alan, Root, David E., Boehm, Jesse S., Getz, Gad, Chang, Sandy, Golub, Todd R., Tsherniak, Aviad, Vazquez, Francisca, and Bass, Adam J.

Published
2019
Full Text
View/download PDF

36. Multiplexed single-cell transcriptional response profiling to define cancer vulnerabilities and therapeutic mechanism of action

Author

McFarland, James M., Paolella, Brenton R., Warren, Allison, Geiger-Schuller, Kathryn, Shibue, Tsukasa, Rothberg, Michael, Kuksenko, Olena, Colgan, William N., Jones, Andrew, Chambers, Emily, Dionne, Danielle, Bender, Samantha, Wolpin, Brian M., Ghandi, Mahmoud, Tirosh, Itay, Rozenblatt-Rosen, Orit, Roth, Jennifer A., Golub, Todd R., Regev, Aviv, Aguirre, Andrew J., Vazquez, Francisca, and Tsherniak, Aviad

Published
2020
Full Text
View/download PDF

37. Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration

Author

James M. McFarland, Zandra V. Ho, Guillaume Kugener, Joshua M. Dempster, Phillip G. Montgomery, Jordan G. Bryan, John M. Krill-Burger, Thomas M. Green, Francisca Vazquez, Jesse S. Boehm, Todd R. Golub, William C. Hahn, David E. Root, and Aviad Tsherniak

Subjects
Science
Abstract

Integrated analyses of multiple large-scale screenings can be complicated by batch effects and technical artefacts. McFarland et al. introduce DEMETER2, a hierarchical model coupled with model-based normalization, which allows the assessment of differential dependencies across genes and cell lines.

Published
2018
Full Text
View/download PDF

38. Targetable vulnerabilities in T- and NK-cell lymphomas identified through preclinical models

Author

Samuel Y. Ng, Noriaki Yoshida, Amanda L. Christie, Mahmoud Ghandi, Neekesh V. Dharia, Joshua Dempster, Mark Murakami, Kay Shigemori, Sara N. Morrow, Alexandria Van Scoyk, Nicolas A. Cordero, Kristen E. Stevenson, Maneka Puligandla, Brian Haas, Christopher Lo, Robin Meyers, Galen Gao, Andrew Cherniack, Abner Louissaint, Valentina Nardi, Aaron R. Thorner, Henry Long, Xintao Qiu, Elizabeth A. Morgan, David M. Dorfman, Danilo Fiore, Julie Jang, Alan L. Epstein, Ahmet Dogan, Yanming Zhang, Steven M. Horwitz, Eric D. Jacobsen, Solimar Santiago, Jian-Guo Ren, Vincent Guerlavais, D. Allen Annis, Manuel Aivado, Mansoor N. Saleh, Amitkumar Mehta, Aviad Tsherniak, David Root, Francisca Vazquez, William C. Hahn, Giorgio Inghirami, Jon C. Aster, David M. Weinstock, and Raphael Koch

Subjects
Science
Abstract

T- and NK-cell lymphomas (TCL) are a group of lymphoid malignancies characterized by poor prognosis, but the absence of appropriate pre-clinical models has hampered the development of effective therapies. Here the authors establish several pre-clinical models and identify vulnerabilities that could be further exploited to treat patients afflicted by these diseases.

Published
2018
Full Text
View/download PDF

39. PIK3CA mutant tumors depend on oxoglutarate dehydrogenase

Author

Ilic, Nina, Birsoy, Kıvanç, Aguirre, Andrew J., Kory, Nora, Pacold, Michael E., Singh, Shambhavi, Moody, Susan E., DeAngelo, Joseph D., Spardy, Nicole A., Freinkman, Elizaveta, Weir, Barbara A., Tsherniak, Aviad, Cowley, Glenn S., Root, David E., Asara, John M., Vazquez, Francisca, Widlund, Hans R., Sabatini, David M., and Hahn, William C.

Published
2017

40. Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets

Author

Dempster, Joshua M., Pacini, Clare, Pantel, Sasha, Behan, Fiona M., Green, Thomas, Krill-Burger, John, Beaver, Charlotte M., Younger, Scott T., Zhivich, Victor, Najgebauer, Hanna, Allen, Felicity, Gonçalves, Emanuel, Shepherd, Rebecca, Doench, John G., Yusa, Kosuke, Vazquez, Francisca, Parts, Leopold, Boehm, Jesse S., Golub, Todd R., Hahn, William C., Root, David E., Garnett, Mathew J., Tsherniak, Aviad, and Iorio, Francesco

Published
2019
Full Text
View/download PDF

41. Mutational processes shape the landscape of TP53 mutations in human cancer

Author

Giacomelli, Andrew O., Yang, Xiaoping, Lintner, Robert E., McFarland, James M., Duby, Marc, Kim, Jaegil, Howard, Thomas P., Takeda, David Y., Ly, Seav Huong, Kim, Eejung, Gannon, Hugh S., Hurhula, Brian, Sharpe, Ted, Goodale, Amy, Fritchman, Briana, Steelman, Scott, Vazquez, Francisca, Tsherniak, Aviad, Aguirre, Andrew J., Doench, John G., Piccioni, Federica, Roberts, Charles W. M., Meyerson, Matthew, Getz, Gad, Johannessen, Cory M., Root, David E., and Hahn, William C.

Published
2018
Full Text
View/download PDF

43. Genetic and transcriptional evolution alters cancer cell line drug response

Author

Ben-David, Uri, Siranosian, Benjamin, Ha, Gavin, Tang, Helen, Oren, Yaara, Hinohara, Kunihiko, Strathdee, Craig A., Dempster, Joshua, Lyons, Nicholas J., Burns, Robert, Nag, Anwesha, Kugener, Guillaume, Cimini, Beth, Tsvetkov, Peter, Maruvka, Yosef E., O’Rourke, Ryan, Garrity, Anthony, Tubelli, Andrew A., Bandopadhayay, Pratiti, Tsherniak, Aviad, Vazquez, Francisca, Wong, Bang, Birger, Chet, Ghandi, Mahmoud, Thorner, Aaron R., Bittker, Joshua A., Meyerson, Matthew, Getz, Gad, Beroukhim, Rameen, and Golub, Todd R.

Published
2018
Full Text
View/download PDF

44. GeNets: a unified web platform for network-based genomic analyses

Author

Li, Taibo, Kim, April, Rosenbluh, Joseph, Horn, Heiko, Greenfeld, Liraz, An, David, Zimmer, Andrew, Liberzon, Arthur, Bistline, Jon, Natoli, Ted, Li, Yang, Tsherniak, Aviad, Narayan, Rajiv, Subramanian, Aravind, Liefeld, Ted, Wong, Bang, Thompson, Dawn, Calvo, Sarah, Carr, Steve, Boehm, Jesse, Jaffe, Jake, Mesirov, Jill, Hacohen, Nir, Regev, Aviv, and Lage, Kasper

Published
2018
Full Text
View/download PDF

45. Complementary information derived from CRISPR Cas9 mediated gene deletion and suppression

Author

Joseph Rosenbluh, Han Xu, William Harrington, Stanley Gill, Xiaoxing Wang, Francisca Vazquez, David E. Root, Aviad Tsherniak, and William C. Hahn

Subjects
Science
Abstract

CRISPR-Cas9 has been utilized to screen the genome in loss-of-function studies to identify genetic interactions. Here the authors compare catalytically active and dead Cas9 and observe different off-target effects in a screen for essential genes.

Published
2017
Full Text
View/download PDF

46. Supplementary Figures S6 - S10 from Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting

Author

Aguirre, Andrew J., primary, Meyers, Robin M., primary, Weir, Barbara A., primary, Vazquez, Francisca, primary, Zhang, Cheng-Zhong, primary, Ben-David, Uri, primary, Cook, April, primary, Ha, Gavin, primary, Harrington, William F., primary, Doshi, Mihir B., primary, Kost-Alimova, Maria, primary, Gill, Stanley, primary, Xu, Han, primary, Ali, Levi D., primary, Jiang, Guozhi, primary, Pantel, Sasha, primary, Lee, Yenarae, primary, Goodale, Amy, primary, Cherniack, Andrew D., primary, Oh, Coyin, primary, Kryukov, Gregory, primary, Cowley, Glenn S., primary, Garraway, Levi A., primary, Stegmaier, Kimberly, primary, Roberts, Charles W., primary, Golub, Todd R., primary, Meyerson, Matthew, primary, Root, David E., primary, Tsherniak, Aviad, primary, and Hahn, William C., primary

Published
2023
Full Text
View/download PDF

47. Data from Somatic Superenhancer Duplications and Hotspot Mutations Lead to Oncogenic Activation of the KLF5 Transcription Factor

Author

Zhang, Xiaoyang, primary, Choi, Peter S., primary, Francis, Joshua M., primary, Gao, Galen F., primary, Campbell, Joshua D., primary, Ramachandran, Aruna, primary, Mitsuishi, Yoichiro, primary, Ha, Gavin, primary, Shih, Juliann, primary, Vazquez, Francisca, primary, Tsherniak, Aviad, primary, Taylor, Alison M., primary, Zhou, Jin, primary, Wu, Zhong, primary, Berger, Ashton C., primary, Giannakis, Marios, primary, Hahn, William C., primary, Cherniack, Andrew D., primary, and Meyerson, Matthew, primary

Published
2023
Full Text
View/download PDF

48. Supplementary Table 2 from Somatic Superenhancer Duplications and Hotspot Mutations Lead to Oncogenic Activation of the KLF5 Transcription Factor

Author

Zhang, Xiaoyang, primary, Choi, Peter S., primary, Francis, Joshua M., primary, Gao, Galen F., primary, Campbell, Joshua D., primary, Ramachandran, Aruna, primary, Mitsuishi, Yoichiro, primary, Ha, Gavin, primary, Shih, Juliann, primary, Vazquez, Francisca, primary, Tsherniak, Aviad, primary, Taylor, Alison M., primary, Zhou, Jin, primary, Wu, Zhong, primary, Berger, Ashton C., primary, Giannakis, Marios, primary, Hahn, William C., primary, Cherniack, Andrew D., primary, and Meyerson, Matthew, primary

Published
2023
Full Text
View/download PDF

49. Supplementary Table S1 from Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting

Author

Aguirre, Andrew J., primary, Meyers, Robin M., primary, Weir, Barbara A., primary, Vazquez, Francisca, primary, Zhang, Cheng-Zhong, primary, Ben-David, Uri, primary, Cook, April, primary, Ha, Gavin, primary, Harrington, William F., primary, Doshi, Mihir B., primary, Kost-Alimova, Maria, primary, Gill, Stanley, primary, Xu, Han, primary, Ali, Levi D., primary, Jiang, Guozhi, primary, Pantel, Sasha, primary, Lee, Yenarae, primary, Goodale, Amy, primary, Cherniack, Andrew D., primary, Oh, Coyin, primary, Kryukov, Gregory, primary, Cowley, Glenn S., primary, Garraway, Levi A., primary, Stegmaier, Kimberly, primary, Roberts, Charles W., primary, Golub, Todd R., primary, Meyerson, Matthew, primary, Root, David E., primary, Tsherniak, Aviad, primary, and Hahn, William C., primary

Published
2023
Full Text
View/download PDF

50. Supplementary Figure Legends from Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting

Author

Aguirre, Andrew J., primary, Meyers, Robin M., primary, Weir, Barbara A., primary, Vazquez, Francisca, primary, Zhang, Cheng-Zhong, primary, Ben-David, Uri, primary, Cook, April, primary, Ha, Gavin, primary, Harrington, William F., primary, Doshi, Mihir B., primary, Kost-Alimova, Maria, primary, Gill, Stanley, primary, Xu, Han, primary, Ali, Levi D., primary, Jiang, Guozhi, primary, Pantel, Sasha, primary, Lee, Yenarae, primary, Goodale, Amy, primary, Cherniack, Andrew D., primary, Oh, Coyin, primary, Kryukov, Gregory, primary, Cowley, Glenn S., primary, Garraway, Levi A., primary, Stegmaier, Kimberly, primary, Roberts, Charles W., primary, Golub, Todd R., primary, Meyerson, Matthew, primary, Root, David E., primary, Tsherniak, Aviad, primary, and Hahn, William C., primary

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results