Identifying Biomarkers of Differential Chemotherapy Response in TNBC Patient-Derived Xenografts With a CTD/WGCNA Approach

Are you working with patient-derived xenograft (PDX) models or looking for new ways to streamline preclinical medications development for breast cancer? In this upcoming Cancer Genomics Cloud (CGC) webinar, Dr. Varduhi Petrosyan of Baylor College of Medicine will describe how her team conducted research, using the CGC, to develop an approach that essentially turns a PDX model into a “patient cohort” to aid in preclinical-trial research. 

This network-based approach blends the algorithm, CTD (or “Connect the Dots”), with advanced analysis (i.e., weighted gene co-expression network analysis) to construct gene networks for identifying biomarkers linked to human disease. 

Using DNA whole exome sequencing, mRNA, transcriptomics, and proteomics, Dr. Petrosyan and her team compared data from the PDX models to cohorts from two widely used data sets (i.e., The Cancer Genome Atlas and the Clinical Proteomic Tumor Analysis Consortium) as well as results from human clinical trials. 

The team identified a specific set of genes that were particularly responsive (and those that were resistant) to two common chemotherapies (i.e., docetaxel and carboplatin) used in the treatment of breast cancer. 

As one of the three Cloud Resources within the NCI Cancer Research Data Commons, the Seven Bridges’ CGC provides researchers access to a wide variety of data sets, a catalog of tools to analyze and visualize the data directly from the browser, and scalable computational resources to perform large scale analysis on the cloud.