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Updated: Jan 21, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
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Genetic Interaction-Based Biomarkers Identification for Drug Resistance and Sensitivity in Cancer Cells

Yue Han1, Chengyu Wang1, Qi Dong1

  • 1Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China.

Molecular Therapy. Nucleic Acids
|August 11, 2019
PubMed

Insights

Researchers identified thousands of genetic interactions in cancer, including synthetic viability (SV) and synthetic lethality (SL) interactions. These interactions impact drug response, with SL interactions potentially enhancing drug sensitivity and SV interactions conferring resistance.

Area of Science:

  • Genomics
  • Cancer Biology
  • Pharmacogenomics

Background:

  • Cancer cells accumulate numerous genomic alterations driving tumor development and progression.
  • Genetic interactions within the cancer genome significantly influence patient response to therapeutic drugs.

Purpose of the Study:

  • To develop an algorithm for identifying cancer-specific genetic interactions using genomic and functional screen data.
  • To establish a comprehensive database of cancer genetic interactions.

Main Methods:

  • Mining copy number alteration and whole-exome mutation profiles from The Cancer Genome Atlas (TCGA).
  • Utilizing functional screen data to identify potential genetic interactions.
  • Integrating existing genetic interaction data to build the Cancer Genetic Interaction database (CGIdb).

Main Results:

  • Detected 4,529 synthetic viability (SV) and 10,637 synthetic lethality (SL) interactions.
  • SV interactions were associated with drug resistance, while SL interactions were linked to drug sensitivity.
  • Deletion of HDAC1 and DVL1 (Notch pathway genes) showed an SV effect, with DVL1 deletion inducing resistance to HDAC1 inhibitors. Low expression of both correlated with poor prognosis.

Conclusions:

  • Genetic interactions play a critical role in cancer drug response.
  • The developed algorithm and CGIdb provide valuable resources for cancer research and therapeutic development.
  • Specific genetic interactions, like those involving HDAC1 and DVL1, offer potential therapeutic targets and prognostic markers.
Keywords:
biomarkerdrug resistancedrug sensitivitysynthetic lethalitysynthetic viability

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