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Published on: January 7, 2019
Molecular determinants of drug response in TNBC cell lines
Nathan M Merrill1, Eric J Lachacz1, Nathalie M Vandecan1
1Department of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA.
Purpose:
There is a need for biomarkers of drug efficacy for targeted therapies in triple-negative breast cancer (TNBC). As a step toward this, we identify multi-omic molecular determinants of anti-TNBC efficacy in cell lines for a panel of oncology drugs.
Methods:
Using 23 TNBC cell lines, drug sensitivity scores (DSS3) were determined using a panel of investigational drugs and drugs approved for other indications. Molecular readouts were generated for each cell line using RNA sequencing, RNA targeted panels, DNA sequencing, and functional proteomics. DSS3 values were correlated with molecular readouts using a FDR-corrected significance cutoff of p* < 0.05 and yielded molecular determinant panels that predict anti-TNBC efficacy.
Results:
Six molecular determinant panels were obtained from 12 drugs we prioritized based on their efficacy. Determinant panels were largely devoid of DNA mutations of the targeted pathway. Molecular determinants were obtained by correlating DSS3 with molecular readouts. We found that co-inhibiting molecular correlate pathways leads to robust synergy across many cell lines.
Conclusions:
These findings demonstrate an integrated method to identify biomarkers of drug efficacy in TNBC where DNA predictions correlate poorly with drug response. Our work outlines a framework for the identification of novel molecular determinants and optimal companion drugs for combination therapy based on these correlates.
Insights
Researchers identified molecular markers to predict triple-negative breast cancer (TNBC) drug effectiveness. This multi-omic approach reveals new biomarkers for targeted therapies and combination treatments, improving TNBC drug efficacy prediction.
Area of Science:
- Oncology
- Genomics
- Proteomics
Background:
- Triple-negative breast cancer (TNBC) lacks effective targeted therapies.
- Biomarkers for drug efficacy in TNBC are urgently needed.
Purpose of the Study:
- To identify multi-omic molecular determinants of anti-TNBC drug efficacy.
- To establish biomarkers for predicting treatment response in TNBC cell lines.
Main Methods:
- Assessed drug sensitivity scores (DSS3) for 23 TNBC cell lines against various oncology drugs.
- Generated molecular data via RNA sequencing, targeted panels, DNA sequencing, and functional proteomics.
- Correlated molecular readouts with DSS3 values to identify predictive determinant panels (p < 0.05, FDR-corrected).
Main Results:
- Identified six molecular determinant panels for 12 prioritized drugs.
- Found that DNA mutations in targeted pathways poorly predicted drug response.
- Observed robust synergy when co-inhibiting molecularly correlated pathways.
Conclusions:
- Developed an integrated method to discover drug efficacy biomarkers in TNBC.
- Demonstrated the utility of multi-omic data beyond DNA mutations for predicting response.
- Outlined a framework for identifying novel biomarkers and optimizing combination therapies for TNBC.
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