Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles

Bülent Arman Aksoy1, Emek Demir2, Özgün Babur2

  • 1Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USAComputational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10065 and Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USA.

Abstract

Insights

Researchers identified 4104 potential cancer vulnerabilities by analyzing genomic data from The Cancer Genome Atlas (TCGA) and cell lines. Many vulnerabilities are targetable with existing drugs, offering a new strategy for personalized cancer therapy.

Area of Science:

  • Genomics
  • Cancer Biology
  • Pharmacology

Background:

  • Somatic homozygous deletions in cancer can create unique vulnerabilities in cancer cells compared to normal cells.
  • Loss of one isoenzyme in glioblastoma necessitates dependence on the remaining isoenzyme, presenting a therapeutic target.
  • Large-scale cancer genomics data from TCGA and cell line data from CCLE enable systematic identification of such vulnerabilities.

Purpose of the Study:

  • To systematically identify epistatic vulnerabilities arising from homozygous deletions in cancer.
  • To leverage integrated pathway information systems for comprehensive vulnerability discovery.
  • To explore the potential for network pharmacology based on genomic profiling.

Main Methods:

  • Analysis of homozygous deletions affecting metabolic enzymes across 16 TCGA cancer studies.
  • Examination of 972 cancer cell lines for candidate metabolic vulnerabilities.
  • Integration of genomic data with pathway information systems.

Main Results:

  • Identified 4104 candidate metabolic vulnerabilities in 1019 tumor samples and 482 cell lines.
  • Up to 44% of identified vulnerabilities are targetable with FDA-approved drugs.
  • A web-based tool is available for exploring these vulnerabilities.

Conclusions:

  • Genomic profiling offers a promising basis for network pharmacology of epistatic vulnerabilities.
  • Personalized genomic profiles can guide the development of targeted cancer therapies.
  • Focused experiments and clinical trials are suggested to validate these findings.

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