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HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology
Prioritizing molecular alterations that act as drivers of cancer remains a crucial bottleneck in therapeutic development. Here we introduce HIT'nDRIVE, a computational method that integrates genomic and transcriptomic data to identify a set of patient-specific, sequence-altered genes, with suff...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5580716/ https://www.ncbi.nlm.nih.gov/pubmed/28768687 http://dx.doi.org/10.1101/gr.221218.117 |
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author | Shrestha, Raunak Hodzic, Ermin Sauerwald, Thomas Dao, Phuong Wang, Kendric Yeung, Jake Anderson, Shawn Vandin, Fabio Haffari, Gholamreza Collins, Colin C. Sahinalp, S. Cenk |
author_facet | Shrestha, Raunak Hodzic, Ermin Sauerwald, Thomas Dao, Phuong Wang, Kendric Yeung, Jake Anderson, Shawn Vandin, Fabio Haffari, Gholamreza Collins, Colin C. Sahinalp, S. Cenk |
author_sort | Shrestha, Raunak |
collection | PubMed |
description | Prioritizing molecular alterations that act as drivers of cancer remains a crucial bottleneck in therapeutic development. Here we introduce HIT'nDRIVE, a computational method that integrates genomic and transcriptomic data to identify a set of patient-specific, sequence-altered genes, with sufficient collective influence over dysregulated transcripts. HIT'nDRIVE aims to solve the “random walk facility location” (RWFL) problem in a gene (or protein) interaction network, which differs from the standard facility location problem by its use of an alternative distance measure: “multihitting time,” the expected length of the shortest random walk from any one of the set of sequence-altered genes to an expression-altered target gene. When applied to 2200 tumors from four major cancer types, HIT'nDRIVE revealed many potentially clinically actionable driver genes. We also demonstrated that it is possible to perform accurate phenotype prediction for tumor samples by only using HIT'nDRIVE-seeded driver gene modules from gene interaction networks. In addition, we identified a number of breast cancer subtype-specific driver modules that are associated with patients’ survival outcome. Furthermore, HIT'nDRIVE, when applied to a large panel of pan-cancer cell lines, accurately predicted drug efficacy using the driver genes and their seeded gene modules. Overall, HIT'nDRIVE may help clinicians contextualize massive multiomics data in therapeutic decision making, enabling widespread implementation of precision oncology. |
format | Online Article Text |
id | pubmed-5580716 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-55807162018-03-01 HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology Shrestha, Raunak Hodzic, Ermin Sauerwald, Thomas Dao, Phuong Wang, Kendric Yeung, Jake Anderson, Shawn Vandin, Fabio Haffari, Gholamreza Collins, Colin C. Sahinalp, S. Cenk Genome Res Method Prioritizing molecular alterations that act as drivers of cancer remains a crucial bottleneck in therapeutic development. Here we introduce HIT'nDRIVE, a computational method that integrates genomic and transcriptomic data to identify a set of patient-specific, sequence-altered genes, with sufficient collective influence over dysregulated transcripts. HIT'nDRIVE aims to solve the “random walk facility location” (RWFL) problem in a gene (or protein) interaction network, which differs from the standard facility location problem by its use of an alternative distance measure: “multihitting time,” the expected length of the shortest random walk from any one of the set of sequence-altered genes to an expression-altered target gene. When applied to 2200 tumors from four major cancer types, HIT'nDRIVE revealed many potentially clinically actionable driver genes. We also demonstrated that it is possible to perform accurate phenotype prediction for tumor samples by only using HIT'nDRIVE-seeded driver gene modules from gene interaction networks. In addition, we identified a number of breast cancer subtype-specific driver modules that are associated with patients’ survival outcome. Furthermore, HIT'nDRIVE, when applied to a large panel of pan-cancer cell lines, accurately predicted drug efficacy using the driver genes and their seeded gene modules. Overall, HIT'nDRIVE may help clinicians contextualize massive multiomics data in therapeutic decision making, enabling widespread implementation of precision oncology. Cold Spring Harbor Laboratory Press 2017-09 /pmc/articles/PMC5580716/ /pubmed/28768687 http://dx.doi.org/10.1101/gr.221218.117 Text en © 2017 Shrestha et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Method Shrestha, Raunak Hodzic, Ermin Sauerwald, Thomas Dao, Phuong Wang, Kendric Yeung, Jake Anderson, Shawn Vandin, Fabio Haffari, Gholamreza Collins, Colin C. Sahinalp, S. Cenk HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology |
title | HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology |
title_full | HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology |
title_fullStr | HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology |
title_full_unstemmed | HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology |
title_short | HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology |
title_sort | hit'ndrive: patient-specific multidriver gene prioritization for precision oncology |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5580716/ https://www.ncbi.nlm.nih.gov/pubmed/28768687 http://dx.doi.org/10.1101/gr.221218.117 |
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