Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach
This February, our webinar series features a talk by Dr. Varduhi Petrosyan at Baylor College of Medicine. Dr. Petrosyan will present work she and colleagues conducted on the Cancer Genomics Cloud using their novel network-based approach, CTD/WGCNA.
Although systemic chemotherapy remains the standard of care for triple-negative breast cancer (TNBC), even combination chemotherapy is often ineffective. The identification of biomarkers for differential chemotherapy response would allow for the selection of responsive patients, thus maximizing efficacy and minimizing toxicities. Here, we leverage TNBC patient-derived xenografts (PDXs) to identify biomarkers of response. To demonstrate their ability to function as a preclinical cohort, PDXs were characterized using DNA sequencing, transcriptomics, and proteomics to show consistency with clinical samples. We then developed a network-based approach (CTD/WGCNA) to identify biomarkers of response to carboplatin (MSI1, TMSB15A, ARHGDIB, GGT1, SV2A, SEC14L2, SERPINI1, ADAMTS20, DGKQ) and docetaxel (c, MAGED4, CERS1, ST8SIA2, KIF24, PARPBP). CTD/WGCNA multigene biomarkers are predictive in PDX datasets (RNAseq and Affymetrix) for both taxane- (docetaxel or paclitaxel) and platinum-based (carboplatin or cisplatin) response, thereby demonstrating cross-expression platform and cross-drug class robustness. These biomarkers were also predictive in clinical datasets, thus demonstrating translational potential.
More about the speaker
Varduhi Petrosyan is a senior bioinformatics analyst at Baylor College of Medicine (Texas Medical Center). She employs big data approaches to identify biological signal in complex and heterogenous disease. Her research interests include network analysis, deconvolution, and liquid biomarkers.
LinkedIn: https://www.linkedin.com/in/varduhi-petrosyan/