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Identifying collateral and synthetic lethal vulnerabilities within the DNA-damage response.

Pietro Pinoli1, Sriganesh Srihari2, Limsoon Wong3

  • 1Department of Electronic, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan, Italy. pietro.pinoli@polimi.it.

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|May 16, 2021
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Summary

We developed a novel method to identify synthetic lethal (SL) gene pairs, crucial for targeted cancer therapies. This approach improves accuracy by analyzing copy number variations and gene essentiality, reducing false positives.

Keywords:
Copy number alterationDNA damage repair genesSynthetic lethality

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Area of Science:

  • Genomics
  • Computational Biology
  • Cancer Therapeutics

Background:

  • Synthetic lethality (SL) describes gene pairs where defects in both are lethal, but in only one is viable.
  • SL gene pairs offer potential for highly selective cancer therapies by targeting cancer-specific vulnerabilities.
  • Exploiting differences between normal and cancer cells is key for effective SL-based treatments.

Purpose of the Study:

  • To present a novel computational method for predicting synthetic lethal (SL) gene pairs.
  • To enhance the accuracy and reduce false positives in SL gene pair identification.
  • To establish explicit collateral lethality relationships within predicted gene pairs.

Main Methods:

  • Clustering proximal genes with similar copy number variation (CNA) profiles.
  • Utilizing a graph-based method for mutual-exclusion testing, considering mutation frequencies.
  • Identifying SL gene pairs using gene essentiality (GARP score) and biological pathway annotations.

Main Results:

  • A new method for predicting synthetic lethal (SL) gene pairs is introduced.
  • The method clusters genes based on CNA profiles and identifies mutually exclusive groups.
  • SL gene pairs are selected using gene essentiality and pathway data.

Conclusions:

  • The developed method is unique and reduces false-positive SL predictions.
  • It enables the establishment of explicit collateral lethality relationships.
  • This approach advances the discovery of targeted cancer therapies.