Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach
Varduhi Petrosyan, Lacey E. Dobrolecki, Lillian R Thistlethwaite, Alaina Lewis, Christina Sallas, Ramakrishnan Rajaram Srinivasan, Jonathan T. Lei, Vladimir Kovačević, Predrag Obradović, Matthew J. Ellis, C. Kent Osborne, Mothaffar F. Rimawi, Anne C. Pavlick, Maryam Nemati Shafaee, Heidi Dowst, Antrix Jain, Alexander B. Saltzman, Anna Malovannaya, Elisabetta Marangoni, Alana L. Welm, Bryan E. Welm, Shunqiang Li, Gerburg M. Wulf, Olmo Sonzogni, Chen Huang, Suhas Vasaikar, Susan G. Hilsenbeck, Bing Zhang, Aleksandar Milosavljevic, Michael T. Lewis
Abstract
Although systemic chemotherapy remains the standard of care for 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 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.