Drug mechanism‐of‐action discovery through the integration of pharmacological and CRISPR screens
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Andrew R. Leach | Francesco Iorio | Clare Pacini | Ben Sidders | Stephen Fawell | Aldo Segura-Cabrera | Patricia Jaaks | Elizabeth A. Coker | Emanuel Gonçalves | Mathew J. Garnett | Andrew Barthorpe | Fiona M. Behan | Emanuel J. V. Gonçalves | Howard Lightfoot | A. Leach | F. Iorio | T. Mironenko | M. Garnett | Wanjuan Yang | H. Lightfoot | S. Fawell | J. Lynch | P. Jaaks | F. Behan | G. Picco | Andrew Barthorpe | C. Pacini | B. Sidders | Gabriele Picco | Claire Crafter | Donny van der Meer | James T. Lynch | A. Segura-Cabrera | C. Crafter | James Hall | L. Richardson | E. Coker | D. van der Meer | Alexandra Beck | Ermira Lleshi | Charlotte Tolley | Caitlin Hall | Iman Mali | Frances Thomas | J. Morris | E. Gonçalves | Andrew S. Barthorpe
[1] Lei Liu,et al. MARCH5 requires MTCH2 to coordinate proteasomal turnover of the MCL1:NOXA complex , 2020, Cell Death & Differentiation.
[2] B. Al-Lazikani,et al. The kinase polypharmacology landscape of clinical PARP inhibitors , 2020, Scientific Reports.
[3] A. Villunger,et al. MARCH5-dependent degradation of MCL1/NOXA complexes defines susceptibility to antimitotic drug treatment , 2020, Cell Death & Differentiation.
[4] A. Villunger,et al. MARCH5-dependent degradation of MCL1/NOXA complexes defines susceptibility to anti-mitotic drug treatment , 2020, Cell Death & Differentiation.
[5] Eiru Kim,et al. Biases and Blind-Spots in Genome-Wide CRISPR Knockout Screens , 2020, bioRxiv.
[6] A. Lin,et al. Off-target toxicity is a common mechanism of action of cancer drugs undergoing clinical trials , 2019, Science Translational Medicine.
[7] D. Durocher,et al. Control of homologous recombination by the HROB–MCM8–MCM9 pathway , 2019, Genes & Development.
[8] Johannes L. Schönberger,et al. SciPy 1.0: fundamental algorithms for scientific computing in Python , 2019, Nature Methods.
[9] Peter C. DeWeirdt,et al. Genetic screens in isogenic mammalian cell lines without single cell cloning , 2019, Nature Communications.
[10] Joshua M. Dempster,et al. Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets , 2019, Nature Communications.
[11] Emanuel J. V. Gonçalves,et al. Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens , 2019, Nature.
[12] Eiru Kim,et al. A network of human functional gene interactions from knockout fitness screens in cancer cells , 2019, Life Science Alliance.
[13] B. Kuster,et al. Chemoproteomic Selectivity Profiling of PIKK and PI3K Kinase Inhibitors. , 2019, ACS chemical biology.
[14] D. Durocher,et al. A consensus set of genetic vulnerabilities to ATR inhibition , 2019, bioRxiv.
[15] Emanuel J. V. Gonçalves,et al. Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR-Cas9 screening , 2019, Nature Communications.
[16] Emanuel J. V. Gonçalves,et al. Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects , 2019, Genome Biology.
[17] P. Pourquier,et al. [Genetic and transcriptional evolution alters cancer cell line drug response]. , 2019, Bulletin du cancer.
[18] Andrew R. Leach,et al. ChEMBL: towards direct deposition of bioassay data , 2018, Nucleic Acids Res..
[19] Howard Lightfoot,et al. Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models , 2018, Nucleic Acids Res..
[20] Kyoung-Mee Kim,et al. Pharmacogenomic landscape of patient-derived tumor cells informs precision oncology therapy , 2018, Nature Genetics.
[21] J. Pritchard,et al. High‐resolution mapping of cancer cell networks using co‐functional interactions , 2018, bioRxiv.
[22] Martin A. M. Reijns,et al. CRISPR screens identify genomic ribonucleotides as a source of PARP-trapping lesions , 2018, Nature.
[23] Evert Bosdriesz,et al. An Acquired Vulnerability of Drug-Resistant Melanoma with Therapeutic Potential , 2018, Cell.
[24] Aviad Tsherniak,et al. Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens. , 2018, Cell systems.
[25] J. Weissman,et al. CRISPR Approaches to Small Molecule Target Identification. , 2017, ACS chemical biology.
[26] Emanuel J. V. Gonçalves,et al. Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting , 2017, BMC Genomics.
[27] B. Kuster,et al. The target landscape of clinical kinase drugs , 2017, Science.
[28] C. Myers,et al. Pathway-based discovery of genetic interactions in breast cancer , 2017, PLoS genetics.
[29] Phillip G. Montgomery,et al. Defining a Cancer Dependency Map , 2017, Cell.
[30] Ann E. Sizemore,et al. Computational correction of copy-number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells , 2017, Nature Genetics.
[31] S. Kazmirski,et al. Abstract DDT01-02: AZD5991: A potent and selective macrocyclic inhibitor of Mcl-1 for treatment of hematologic cancers , 2017 .
[32] Angela N. Brooks,et al. A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles , 2017, Cell.
[33] Thomas Hielscher,et al. Toward an integrated map of genetic interactions in cancer cells , 2017, bioRxiv.
[34] Yiling Lu,et al. Characterization of Human Cancer Cell Lines by Reverse-phase Protein Arrays. , 2017, Cancer cell.
[35] Eric S. Lander,et al. Gene Essentiality Profiling Reveals Gene Networks and Synthetic Lethal Interactions with Oncogenic Ras , 2017, Cell.
[36] O. Stegle,et al. Joint genetic analysis using variant sets reveals polygenic gene-context interactions , 2016, bioRxiv.
[37] Tudor I. Oprea,et al. A comprehensive map of molecular drug targets , 2016, Nature Reviews Drug Discovery.
[38] Damian Szklarczyk,et al. The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible , 2016, Nucleic Acids Res..
[39] Julio Saez-Rodriguez,et al. A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia , 2016, Cell reports.
[40] Joshua M. Korn,et al. CRISPR Screens Provide a Comprehensive Assessment of Cancer Vulnerabilities but Generate False-Positive Hits for Highly Amplified Genomic Regions. , 2016, Cancer discovery.
[41] T. Golub,et al. Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting. , 2016, Cancer discovery.
[42] Emanuel J. V. Gonçalves,et al. A Landscape of Pharmacogenomic Interactions in Cancer , 2016, Cell.
[43] Francesco Iorio,et al. Multilevel models improve precision and speed of IC50 estimates. , 2016, Pharmacogenomics.
[44] U. McDermott,et al. Identification of differential PI3K pathway target dependencies in T-cell acute lymphoblastic leukemia through a large cancer cell panel screen , 2016, Oncotarget.
[45] Max A. Horlbeck,et al. Parallel shRNA and CRISPR-Cas9 screens enable antiviral drug target identification , 2016, Nature chemical biology.
[46] Gary D Bader,et al. Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance , 2016, Cell.
[47] P. Pinton,et al. Mcl-1 involvement in mitochondrial dynamics is associated with apoptotic cell death , 2016, Molecular biology of the cell.
[48] D. Durocher,et al. High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities , 2015, Cell.
[49] Meagan E. Sullender,et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9 , 2015, Nature Biotechnology.
[50] M. Stratton,et al. Combinations of PARP Inhibitors with Temozolomide Drive PARP1 Trapping and Apoptosis in Ewing’s Sarcoma , 2015, PloS one.
[51] B. Kuster,et al. Optimized chemical proteomics assay for kinase inhibitor profiling. , 2015, Journal of proteome research.
[52] Jean J. Zhao,et al. PI3K in cancer: divergent roles of isoforms, modes of activation and therapeutic targeting , 2014, Nature Reviews Cancer.
[53] G. Drewes,et al. Tracking cancer drugs in living cells by thermal profiling of the proteome , 2014, Science.
[54] M. Pangalos,et al. Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework , 2014, Nature Reviews Drug Discovery.
[55] S. Desagher,et al. Mcl-1 Ubiquitination: Unique Regulation of an Essential Survival Protein , 2014, Cells.
[56] C. Lippert,et al. LIMIX: genetic analysis of multiple traits , 2014, bioRxiv.
[57] G. Smyth,et al. voom: precision weights unlock linear model analysis tools for RNA-seq read counts , 2014, Genome Biology.
[58] Neville E. Sanjana,et al. Genome-Scale CRISPR-Cas9 Knockout Screening in Human Cells , 2014, Science.
[59] Yilong Li,et al. Genome-wide recessive genetic screening in mammalian cells with a lentiviral CRISPR-guide RNA library , 2013, Nature Biotechnology.
[60] Peter E. Czabotar,et al. Control of apoptosis by the BCL-2 protein family: implications for physiology and therapy , 2013, Nature Reviews Molecular Cell Biology.
[61] Tony Pawson,et al. Temporal regulation of EGF signaling networks by the scaffold protein Shc1 , 2013, Nature.
[62] P. Clemons,et al. Target identification and mechanism of action in chemical biology and drug discovery. , 2013, Nature chemical biology.
[63] Sridhar Ramaswamy,et al. Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells , 2012, Nucleic Acids Res..
[64] R. Korneluk,et al. Modulation of immune signalling by inhibitors of apoptosis. , 2012, Trends in immunology.
[65] J. Doudna,et al. A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity , 2012, Science.
[66] S. Ramaswamy,et al. Systematic identification of genomic markers of drug sensitivity in cancer cells , 2012, Nature.
[67] Adam A. Margolin,et al. The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity , 2012, Nature.
[68] Gaël Varoquaux,et al. The NumPy Array: A Structure for Efficient Numerical Computation , 2011, Computing in Science & Engineering.
[69] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[70] Tjerk P. Straatsma,et al. NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations , 2010, Comput. Phys. Commun..
[71] Derek Y. Chiang,et al. The landscape of somatic copy-number alteration across human cancers , 2010, Nature.
[72] Bernhard Kuster,et al. Quantitative chemical proteomics reveals mechanisms of action of clinical ABL kinase inhibitors , 2007, Nature Biotechnology.
[73] R. Youle,et al. The mitochondrial E3 ubiquitin ligase MARCH5 is required for Drp1 dependent mitochondrial division , 2007, The Journal of cell biology.
[74] John D. Hunter,et al. Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.
[75] T. Golub,et al. Gene expression-based chemical genomics identifies rapamycin as a modulator of MCL1 and glucocorticoid resistance. , 2006, Cancer cell.
[76] J. Baselga,et al. The Epidermal Growth Factor Receptor Pathway: A Model for Targeted Therapy , 2006, Clinical Cancer Research.
[77] R. Youle,et al. Mitochondrial fission in apoptosis , 2005, Nature Reviews Molecular Cell Biology.
[78] R. Bataille,et al. Mcl-1 is overexpressed in multiple myeloma and associated with relapse and shorter survival , 2005, Leukemia.
[79] G. Thomas,et al. Furin at the cutting edge: From protein traffic to embryogenesis and disease , 2002, Nature Reviews Molecular Cell Biology.
[80] Nuno A. Fonseca,et al. Transcription Factor Activities Enhance Markers of Drug Sensitivity in Cancer. , 2018, Cancer research.
[81] Y. Pommier,et al. Classification of PARP Inhibitors Based on PARP Trapping and Catalytic Inhibition, and Rationale for Combinations with Topoisomerase I Inhibitors and Alkylating Agents , 2015 .
[82] Y. Miki,et al. [PARP inhibitors for cancer therapy]. , 2011, Gan to kagaku ryoho. Cancer & chemotherapy.
[83] Wes McKinney,et al. Data Structures for Statistical Computing in Python , 2010, SciPy.
[84] Gábor Csárdi,et al. The igraph software package for complex network research , 2006 .
[85] T. A. Connors. Alkylating agents. , 1990, Cancer chemotherapy and biological response modifiers.
[86] Mulin Jun Li,et al. Nature Genetics Advance Online Publication a N a Ly S I S the Support of Human Genetic Evidence for Approved Drug Indications , 2022 .
[87] the original work is properly cited. , 2022 .