Colorectal cancer (CRC) has one of the highest worldwide incidences (1.3 million new cases) and mortality rates (~610,000 deaths per year). Genotoxic chemotherapy in stage II and III confers minimal treatment benefit (improved survival in 3-4% stage II and 15-20% of stage III patients), and predictive markers to select responding/non-responding patients are lacking. The central hypothesis under investigation in this proposal is that modeling of apoptosis pathways at a cellular level and integration with tumor cellular and spatial heterogeneity measurements (tumor microenvironment (TME), stem cells, molecular/genetic subtype) and controlling for key clinical co-variates (e.g., location (proximal, distal, rectal), lymph node number) will better predict mechanisms and risk of poor prognosis and chemotherapy response in both stage II and III patients. While the immediate application would be for stage II patients, the results will provide important new mechanistic insights into stage III outcomes and diagnostic opportunities for new therapies.
We have shown with systems modeling of apoptosis pathways that tumor apoptosis competency is associated with improved chemotherapy response. We hypothesize that single-cell analysis of apoptosis signatures will significantly improve model prediction accuracies, delineating inter- and intra-tumor cell heterogeneity in apoptosis sensitivity as predictors of therapy resistance. Furthermore, we will combine the apoptotic signatures with TME measurements, including immune, endothelial and stromal cells. Stem cell markers and molecular/genetic subtype determination, will provide a comprehensive catalog of mechanisms of chemotherapy resistance. We will experimentally interrogate key mechanisms to identify alternative improved therapy options. This program of work will combine international expertise via a tri-partite collaboration in systems biology (Royal College of Surgeons Ireland (RCSI)), CRC diagnosis and treatment (Queen’s University Belfast (QUB) and Memorial Sloan Kettering Cancer Center (MSKCC)), and single cell imaging and analytics (GE Global Research).