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Related Concept Videos

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Related Experiment Video

Updated: Dec 9, 2025

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
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Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns.

Lidia Mateo1, Miquel Duran-Frigola1, Albert Gris-Oliver2

  • 1Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain.

Genome Medicine
|September 10, 2020
PubMed
Summary

This study identifies genomic vulnerabilities for precision oncology by linking gene alterations to drug sensitivity using patient-derived xenografts. The findings improve the clinical impact of genomic profiling by revealing new oncogenic alteration connections.

Keywords:
Driver co-occurrence networksDrug-response biomarkersPrecision oncology

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Area of Science:

  • Oncology
  • Genomics
  • Pharmacology

Background:

  • Precision oncology relies on identifying actionable genomic vulnerabilities.
  • Patient-derived xenografts (PDXs) are valuable models for cancer research.

Purpose of the Study:

  • To uncover connections between driver gene alterations and drug sensitivity.
  • To develop predictive models for drug response in cancer patients.

Main Methods:

  • Large-scale drug screening in patient-derived xenografts.
  • Derivation of driver co-occurrence (DCO) networks.
  • Development and validation of drug-response predictors.

Main Results:

  • A collection of 53 drug-response predictors achieved 58% average balanced accuracy in cross-validation.
  • High-confidence predictions reached 66% accuracy.
  • 12 out of 14 predictions were experimentally validated in mice.

Conclusions:

  • The strategy links oncogenic alterations to drug sensitivity, enhancing precision oncology.
  • The approach can be adapted to utilize patient progression-free survival data for drug-response modeling.