Systematic Prioritization of Druggable Mutations in ∼5000 Genomes Across 16 Cancer Types Using a Structural Genomics-based Approach*
暂无分享,去创建一个
Zhongming Zhao | Feixiong Cheng | Junfei Zhao | Carlos L. Arteaga | Yuanyuan Wang | Zhongming Zhao | F. Cheng | Junfei Zhao | C. Arteaga | Yuanyuan Wang | Zhongming Zhao
[1] Donald P. McDonnell,et al. International Union of Pharmacology. LXV. The Pharmacology and Classification of the Nuclear Receptor Superfamily: Glucocorticoid, Mineralocorticoid, Progesterone, and Androgen Receptors , 2006, Pharmacological Reviews.
[2] Zhongming Zhao,et al. ccmGDB: a database for cancer cell metabolism genes , 2015, Nucleic Acids Res..
[3] Steven Henikoff,et al. SIFT: predicting amino acid changes that affect protein function , 2003, Nucleic Acids Res..
[4] P. Bork,et al. A method and server for predicting damaging missense mutations , 2010, Nature Methods.
[5] C. Stephan,et al. Fatty acid binding proteins (FABPs) in prostate, bladder and kidney cancer cell lines and the use of IL-FABP as survival predictor in patients with renal cell carcinoma , 2011, BMC Cancer.
[6] Steven J. M. Jones,et al. Integrated Genomic Characterization of Papillary Thyroid Carcinoma , 2014, Cell.
[7] A. Sivachenko,et al. A Landscape of Driver Mutations in Melanoma , 2012, Cell.
[8] P. Shannon,et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.
[9] Yadi Zhou,et al. Prediction of Chemical-Protein Interactions Network with Weighted Network-Based Inference Method , 2012, PloS one.
[10] I. Raška,et al. Antitumor Activity of the Retinoid-Related Molecules (E)-3-(4′-Hydroxy-3′-adamantylbiphenyl-4-yl)acrylic Acid (ST1926) and 6-[3-(1-Adamantyl)-4-hydroxyphenyl]-2-naphthalene Carboxylic Acid (CD437) in F9 Teratocarcinoma: Role of Retinoic Acid Receptor γ and Retinoid-Independent Pathways , 2006, Molecular Pharmacology.
[11] Peilin Jia,et al. VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data , 2014, PLoS Comput. Biol..
[12] Patricia L. Harris,et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. , 2004, The New England journal of medicine.
[13] Chuang Liu,et al. Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference , 2012, PLoS Comput. Biol..
[14] Matthew J. Davis,et al. Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma , 2012, Nature Genetics.
[15] Arthur J. Olson,et al. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading , 2009, J. Comput. Chem..
[16] S. Gabriel,et al. EGFR Mutations in Lung Cancer: Correlation with Clinical Response to Gefitinib Therapy , 2004, Science.
[17] Hyojin Cho,et al. New pathway links from cancer‐progression determinants to gene expression of matrix metalloproteinases in breast cancer cells , 2008, Journal of cellular physiology.
[18] Gregory D. Schuler,et al. Database resources of the National Center for Biotechnology Information: update , 2004, Nucleic acids research.
[19] Jannik N. Andersen,et al. Cancer genomics: from discovery science to personalized medicine , 2011, Nature Medicine.
[20] Adam Godzik,et al. e-Driver: a novel method to identify protein regions driving cancer , 2014, Bioinform..
[21] David Chen,et al. ESR1 ligand binding domain mutations in hormone-resistant breast cancer , 2013, Nature Genetics.
[22] Y. Benjamini,et al. More powerful procedures for multiple significance testing. , 1990, Statistics in medicine.
[23] J. Engelman,et al. ERBB receptors: from oncogene discovery to basic science to mechanism-based cancer therapeutics. , 2014, Cancer cell.
[24] T. Tammela,et al. The cytostatic effect of 9-cis-retinoic acid, tretinoin, and isotretinoin on three different human bladder cancer cell lines in vitro , 1999, Urological Research.
[25] Javed Siddiqui,et al. Activating ESR1 mutations in hormone-resistant metastatic breast cancer , 2013, Nature Genetics.
[26] U. Reichert,et al. The role of specific retinoid receptors in sebocyte growth and differentiation in culture. , 2000, The Journal of investigative dermatology.
[27] T. Hubbard,et al. A census of human cancer genes , 2004, Nature Reviews Cancer.
[28] John P. Overington,et al. ChEMBL: a large-scale bioactivity database for drug discovery , 2011, Nucleic Acids Res..
[29] Chuang Liu,et al. A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types , 2015, PLoS Comput. Biol..
[30] John C Hunter,et al. In situ selectivity profiling and crystal structure of SML-8-73-1, an active site inhibitor of oncogenic K-Ras G12C , 2014, Proceedings of the National Academy of Sciences.
[31] X. Hua,et al. DrGaP: a powerful tool for identifying driver genes and pathways in cancer sequencing studies. , 2013, American journal of human genetics.
[32] Steven E Brenner,et al. The Impact of Structural Genomics: Expectations and Outcomes , 2005, Science.
[33] V. Krasnykh,et al. Molecular imaging of active mutant L858R EGF receptor (EGFR) kinase-expressing nonsmall cell lung carcinomas using PET/CT , 2011, Proceedings of the National Academy of Sciences.
[34] T. N. Bhat,et al. The Protein Data Bank , 2000, Nucleic Acids Res..
[35] H. Hakonarson,et al. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.
[36] B. Katzenellenbogen,et al. NFkappaB selectivity of estrogen receptor ligands revealed by comparative crystallographic analyses. , 2008, Nature chemical biology.
[37] M. Goswami,et al. Expression of putative targets of immunotherapy in acute myeloid leukemia and healthy tissues , 2014, Leukemia.
[38] S. Elledge,et al. Cumulative Haploinsufficiency and Triplosensitivity Drive Aneuploidy Patterns and Shape the Cancer Genome , 2013, Cell.
[39] Steven J. M. Jones,et al. Comprehensive molecular portraits of human breast tumors , 2012, Nature.
[40] David Tamborero,et al. OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes , 2013, Bioinform..
[41] Xin Wen,et al. BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities , 2006, Nucleic Acids Res..
[42] Zhongming Zhao,et al. Functional consequences of somatic mutations in cancer using protein pocket-based prioritization approach , 2014, Genome Medicine.
[43] Zhongming Zhao,et al. Quantitative network mapping of the human kinome interactome reveals new clues for rational kinase inhibitor discovery and individualized cancer therapy , 2014, Oncotarget.
[44] Steven J. M. Jones,et al. Comprehensive molecular portraits of human breast tumours , 2013 .
[45] Theresa Zhang,et al. Personalized genomic analyses for cancer mutation discovery and interpretation , 2015, Science Translational Medicine.
[46] Zhongming Zhao,et al. Advances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomes , 2016, Briefings Bioinform..
[47] Steven A. Roberts,et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes , 2013 .
[48] D. Lane,et al. Drugging the p53 pathway: understanding the route to clinical efficacy , 2014, Nature Reviews Drug Discovery.
[49] Yang Zhang,et al. BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions , 2012, Nucleic Acids Res..
[50] David S. Wishart,et al. DrugBank 3.0: a comprehensive resource for ‘Omics’ research on drugs , 2010, Nucleic Acids Res..
[51] Gary D Bader,et al. International network of cancer genome projects , 2010, Nature.
[52] F. Demichelis,et al. Tumor clone dynamics in lethal prostate cancer , 2014, Science Translational Medicine.
[53] Peng Qiu,et al. TCGA-Assembler: open-source software for retrieving and processing TCGA data , 2014, Nature Methods.
[54] K. Kinzler,et al. Cancer Genome Landscapes , 2013, Science.
[55] Eytan Domany,et al. Diurnal suppression of EGFR signalling by glucocorticoids and implications for tumour progression and treatment , 2014, Nature Communications.
[56] M. Merino,et al. Phase I clinical trial of alitretinoin and tamoxifen in breast cancer patients: toxicity, pharmacokinetic, and biomarker evaluations. , 2001, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[57] Benjamin J. Raphael,et al. Pan-Cancer Network Analysis Identifies Combinations of Rare Somatic Mutations across Pathways and Protein Complexes , 2014, Nature Genetics.
[58] Jie Li,et al. Prediction of Polypharmacological Profiles of Drugs by the Integration of Chemical, Side Effect, and Therapeutic Space , 2013, J. Chem. Inf. Model..
[59] Mingming Jia,et al. COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer , 2010, Nucleic Acids Res..
[60] E. Lander,et al. Comprehensive assessment of cancer missense mutation clustering in protein structures , 2015, Proceedings of the National Academy of Sciences.
[61] Li Ding,et al. Endocrine-therapy-resistant ESR1 variants revealed by genomic characterization of breast-cancer-derived xenografts. , 2013, Cell reports.
[62] K. Pienta,et al. Activating ESR 1 mutations in hormone-resistant metastatic breast cancer , 2013 .
[63] Steven J. M. Jones,et al. Comprehensive molecular profiling of lung adenocarcinoma , 2014, Nature.
[64] Kevan M. Shokat,et al. K-Ras(G12C) inhibitors allosterically control GTP affinity and effector interactions , 2013, Nature.
[65] M F Sanner,et al. Python: a programming language for software integration and development. , 1999, Journal of molecular graphics & modelling.
[66] Lisa McShane,et al. Biomarkers: Exceptional responders—discovering predictive biomarkers , 2015, Nature Reviews Clinical Oncology.
[67] S. Carr,et al. Ubiquitylome analysis identifies dysregulation of effector substrates in SPOP-mutant prostate cancer , 2014, Science.
[68] C. Sander,et al. Predicting the functional impact of protein mutations: application to cancer genomics , 2011, Nucleic acids research.
[69] Benjamin J. Raphael,et al. Identifying driver mutations in sequenced cancer genomes: computational approaches to enable precision medicine , 2014, Genome Medicine.
[70] Zhongming Zhao,et al. Studying tumorigenesis through network evolution and somatic mutational perturbations in the cancer interactome. , 2014, Molecular biology and evolution.
[71] Qingxia Chen,et al. MSEA: detection and quantification of mutation hotspots through mutation set enrichment analysis , 2014, Genome Biology.
[72] S. Conzen,et al. Glucocorticoid Receptor Antagonism as a Novel Therapy for Triple-Negative Breast Cancer , 2013, Clinical Cancer Research.
[73] M. Nowak,et al. Only three driver gene mutations are required for the development of lung and colorectal cancers , 2014, Proceedings of the National Academy of Sciences.
[74] M. Roden,et al. A Thr94Ala mutation in human liver fatty acid-binding protein contributes to reduced hepatic glycogenolysis and blunted elevation of plasma glucose levels in lipid-exposed subjects. , 2007, American journal of physiology. Endocrinology and metabolism.
[75] Michael P. Schroeder,et al. In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals targeting opportunities. , 2015, Cancer cell.
[76] Conrad C. Huang,et al. UCSF Chimera—A visualization system for exploratory research and analysis , 2004, J. Comput. Chem..