Systematic discovery of the functional impact of somatic genome alterations in individual tumors through tumor-specific causal inference.

Autor: Cai C; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Cooper GF; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Lu KN; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Ma X; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America., Xu S; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, United States of America., Zhao Z; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, United States of America., Chen X; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Xue Y; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Lee AV; Center for Causal Discovery, Pittsburgh, PA, United States of America.; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, United States of America.; Magee Women's Cancer Research Center, Pittsburgh, PA, United States of America.; UPMC Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, United States of America., Clark N; Center for Causal Discovery, Pittsburgh, PA, United States of America.; Department of Computational Biology and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America., Chen V; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Lu S; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Chen L; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Yu L; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Hochheiser HS; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Jiang X; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America., Wang QJ; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, United States of America., Lu X; Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.; Center for Causal Discovery, Pittsburgh, PA, United States of America.; UPMC Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, United States of America.
Jazyk: angličtina
Zdroj: PLoS computational biology [PLoS Comput Biol] 2019 Jul 05; Vol. 15 (7), pp. e1007088. Date of Electronic Publication: 2019 Jul 05 (Print Publication: 2019).
DOI: 10.1371/journal.pcbi.1007088
Abstrakt: Cancer is mainly caused by somatic genome alterations (SGAs). Precision oncology involves identifying and targeting tumor-specific aberrations resulting from causative SGAs. We developed a novel tumor-specific computational framework that finds the likely causative SGAs in an individual tumor and estimates their impact on oncogenic processes, which suggests the disease mechanisms that are acting in that tumor. This information can be used to guide precision oncology. We report a tumor-specific causal inference (TCI) framework, which estimates causative SGAs by modeling causal relationships between SGAs and molecular phenotypes (e.g., transcriptomic, proteomic, or metabolomic changes) within an individual tumor. We applied the TCI algorithm to tumors from The Cancer Genome Atlas (TCGA) and estimated for each tumor the SGAs that causally regulate the differentially expressed genes (DEGs) in that tumor. Overall, TCI identified 634 SGAs that are predicted to cause cancer-related DEGs in a significant number of tumors, including most of the previously known drivers and many novel candidate cancer drivers. The inferred causal relationships are statistically robust and biologically sensible, and multiple lines of experimental evidence support the predicted functional impact of both the well-known and the novel candidate drivers that are predicted by TCI. TCI provides a unified framework that integrates multiple types of SGAs and molecular phenotypes to estimate which genome perturbations are causally influencing one or more molecular/cellular phenotypes in an individual tumor. By identifying major candidate drivers and revealing their functional impact in an individual tumor, TCI sheds light on the disease mechanisms of that tumor, which can serve to advance our basic knowledge of cancer biology and to support precision oncology that provides tailored treatment of individual tumors.
Competing Interests: The authors have declared that no competing interests exist.
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje