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Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles
Motivation: Somatic homozygous deletions of chromosomal regions in cancer, while not necessarily oncogenic, may lead to therapeutic vulnerabilities specific to cancer cells compared with normal cells. A recently reported example is the loss of one of the two isoenzymes in glioblastoma cancer cells s...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4080742/ https://www.ncbi.nlm.nih.gov/pubmed/24665131 http://dx.doi.org/10.1093/bioinformatics/btu164 |
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author | Aksoy, Bülent Arman Demir, Emek Babur, Özgün Wang, Weiqing Jing, Xiaohong Schultz, Nikolaus Sander, Chris |
author_facet | Aksoy, Bülent Arman Demir, Emek Babur, Özgün Wang, Weiqing Jing, Xiaohong Schultz, Nikolaus Sander, Chris |
author_sort | Aksoy, Bülent Arman |
collection | PubMed |
description | Motivation: Somatic homozygous deletions of chromosomal regions in cancer, while not necessarily oncogenic, may lead to therapeutic vulnerabilities specific to cancer cells compared with normal cells. A recently reported example is the loss of one of the two isoenzymes in glioblastoma cancer cells such that the use of a specific inhibitor selectively inhibited growth of the cancer cells, which had become fully dependent on the second isoenzyme. We have now made use of the unprecedented conjunction of large-scale cancer genomics profiling of tumor samples in The Cancer Genome Atlas (TCGA) and of tumor-derived cell lines in the Cancer Cell Line Encyclopedia, as well as the availability of integrated pathway information systems, such as Pathway Commons, to systematically search for a comprehensive set of such epistatic vulnerabilities. Results: Based on homozygous deletions affecting metabolic enzymes in 16 TCGA cancer studies and 972 cancer cell lines, we identified 4104 candidate metabolic vulnerabilities present in 1019 tumor samples and 482 cell lines. Up to 44% of these vulnerabilities can be targeted with at least one Food and Drug Administration-approved drug. We suggest focused experiments to test these vulnerabilities and clinical trials based on personalized genomic profiles of those that pass preclinical filters. We conclude that genomic profiling will in the future provide a promising basis for network pharmacology of epistatic vulnerabilities as a promising therapeutic strategy. Availability and implementation: A web-based tool for exploring all vulnerabilities and their details is available at http://cbio.mskcc.org/cancergenomics/statius/ along with supplemental data files. Contact: statius@cbio.mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4080742 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-40807422014-07-03 Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles Aksoy, Bülent Arman Demir, Emek Babur, Özgün Wang, Weiqing Jing, Xiaohong Schultz, Nikolaus Sander, Chris Bioinformatics Original Papers Motivation: Somatic homozygous deletions of chromosomal regions in cancer, while not necessarily oncogenic, may lead to therapeutic vulnerabilities specific to cancer cells compared with normal cells. A recently reported example is the loss of one of the two isoenzymes in glioblastoma cancer cells such that the use of a specific inhibitor selectively inhibited growth of the cancer cells, which had become fully dependent on the second isoenzyme. We have now made use of the unprecedented conjunction of large-scale cancer genomics profiling of tumor samples in The Cancer Genome Atlas (TCGA) and of tumor-derived cell lines in the Cancer Cell Line Encyclopedia, as well as the availability of integrated pathway information systems, such as Pathway Commons, to systematically search for a comprehensive set of such epistatic vulnerabilities. Results: Based on homozygous deletions affecting metabolic enzymes in 16 TCGA cancer studies and 972 cancer cell lines, we identified 4104 candidate metabolic vulnerabilities present in 1019 tumor samples and 482 cell lines. Up to 44% of these vulnerabilities can be targeted with at least one Food and Drug Administration-approved drug. We suggest focused experiments to test these vulnerabilities and clinical trials based on personalized genomic profiles of those that pass preclinical filters. We conclude that genomic profiling will in the future provide a promising basis for network pharmacology of epistatic vulnerabilities as a promising therapeutic strategy. Availability and implementation: A web-based tool for exploring all vulnerabilities and their details is available at http://cbio.mskcc.org/cancergenomics/statius/ along with supplemental data files. Contact: statius@cbio.mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2014-07-15 2014-03-24 /pmc/articles/PMC4080742/ /pubmed/24665131 http://dx.doi.org/10.1093/bioinformatics/btu164 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Aksoy, Bülent Arman Demir, Emek Babur, Özgün Wang, Weiqing Jing, Xiaohong Schultz, Nikolaus Sander, Chris Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles |
title | Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles |
title_full | Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles |
title_fullStr | Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles |
title_full_unstemmed | Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles |
title_short | Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles |
title_sort | prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4080742/ https://www.ncbi.nlm.nih.gov/pubmed/24665131 http://dx.doi.org/10.1093/bioinformatics/btu164 |
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