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Updated: Aug 25, 2025
Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Identification of phenocopies improves prediction of targeted therapy response over DNA mutations alone
Hamza Bakhtiar1, Kyle T Helzer1, Yeonhee Park2
1Department of Human Oncology, Madison, WI, 53792, USA.
Abstract:
DNA mutations in specific genes can confer preferential benefit from drugs targeting those genes. However, other molecular perturbations can "phenocopy" pathogenic mutations, but would not be identified using standard clinical sequencing, leading to missed opportunities for other patients to benefit from targeted treatments. We hypothesized that RNA phenocopy signatures of key cancer driver gene mutations could improve our ability to predict response to targeted therapies, despite not being directly trained on drug response. To test this, we built gene expression signatures in tissue samples for specific mutations and found that phenocopy signatures broadly increased accuracy of drug response predictions in-vitro compared to DNA mutation alone, and identified additional cancer cell lines that respond well with a positive/negative predictive value on par or better than DNA mutations. We further validated our results across four clinical cohorts. Our results suggest that routine RNA sequencing of tumors to identify phenocopies in addition to standard targeted DNA sequencing would improve our ability to accurately select patients for targeted therapies in the clinic.
Insights
RNA sequencing can identify cancer gene expression patterns that mimic DNA mutations, improving targeted drug response prediction. This approach enhances patient selection for precision cancer therapies beyond standard DNA sequencing.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Specific DNA mutations predict targeted drug efficacy in cancer.
- Non-mutational molecular changes (phenocopies) can mimic pathogenic mutations, leading to missed treatment opportunities.
- Standard DNA sequencing may not detect these phenocopies.
Purpose of the Study:
- To investigate if RNA expression signatures can identify cancer gene phenocopies.
- To determine if RNA phenocopy signatures improve prediction of targeted therapy response.
- To assess the clinical utility of RNA sequencing for patient stratification.
Main Methods:
- Developed gene expression signatures for specific cancer driver gene mutations using tissue samples.
- Evaluated the accuracy of DNA mutations versus RNA phenocopy signatures in predicting drug response in vitro.
- Validated findings across four independent clinical cancer cohorts.
Main Results:
- RNA phenocopy signatures significantly improved the accuracy of in vitro drug response predictions compared to DNA mutation status alone.
- Phenocopy signatures identified additional responsive cancer cell lines with predictive values comparable to or exceeding DNA mutations.
- Clinical validation confirmed the utility of RNA phenocopies in predicting treatment response.
Conclusions:
- RNA expression profiling can identify functionally relevant gene alterations beyond direct DNA mutations.
- Integrating RNA sequencing with DNA sequencing can enhance patient selection for targeted cancer therapies.
- Routine RNA sequencing may optimize precision medicine by uncovering broader patient eligibility for existing treatments.
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