A Network of Conserved Synthetic Lethal Interactions for Exploration of Precision Cancer Therapy
Autor: | Robert W. Sobol, Justin K. Huang, Trey Ideker, Jianfeng Li, Jia L. Xu, Ana Bojorquez-Gomez, Andrew M. Gross, James Jensen, Leonie Kollenstart, Rohith Srivas, Daniel Pekin, John Paul Shen, Haico van Attikum, Kristin Klepper, Vignesh Sivaganesh, Chih Cheng Yang, Su Ming Sun, Pedro Aza-Blanc, Huwate Yeerna, Katherine Licon |
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Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
0301 basic medicine
Saccharomyces cerevisiae Proteins Time Factors Cell Survival Gene regulatory network Uterine Cervical Neoplasms Antineoplastic Agents Cell Cycle Proteins Kaplan-Meier Estimate Saccharomyces cerevisiae Biology medicine.disease_cause Transfection 03 medical and health sciences RNA interference Gene Expression Regulation Fungal medicine Biomarkers Tumor Humans Gene Regulatory Networks Genes Tumor Suppressor Genetic Predisposition to Disease Molecular Targeted Therapy Protein Interaction Maps Precision Medicine Molecular Biology Gene Cell Proliferation Genetics Mutation Dose-Response Relationship Drug RecQ Helicases Cancer Cell Biology medicine.disease Phenotype Gene Expression Regulation Neoplastic 030104 developmental biology Female RNA Interference Synthetic Lethal Mutations Function (biology) HeLa Cells Signal Transduction |
Zdroj: | Molecular Cell, 63(3), 514-525 |
Popis: | An emerging therapeutic strategy for cancer is to induce selective lethality in a tumor by exploiting interactions between its driving mutations and specific drug targets. Here we use a multi-species approach to develop a resource of synthetic lethal interactions relevant to cancer therapy. First, we screen in yeast ∼169,000 potential interactions among orthologs of human tumor suppressor genes (TSG) and genes encoding drug targets across multiple genotoxic environments. Guided by the strongest signal, we evaluate thousands of TSG-drug combinations in HeLa cells, resulting in networks of conserved synthetic lethal interactions. Analysis of these networks reveals that interaction stability across environments and shared gene function increase the likelihood of observing an interaction in human cancer cells. Using these rules, we prioritize ∼10(5) human TSG-drug combinations for future follow-up. We validate interactions based on cell and/or patient survival, including topoisomerases with RAD17 and checkpoint kinases with BLM. |
Databáze: | OpenAIRE |
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