Research innovations over the years have led to the discovery of various predictive biomarkers of cancer therapeutic outcome. However, there is now a general consensus that no single gene or protein could explain cancer behaviour or unify the differential responses to therapy. Also, large-scale studies on a multitude of genetic markers may be inadequate to explain the heterogeneous response to anticancer drugs given the clonal nature of cancer. To address this issue, the EU-funded SYSBIODREZ (Systems biology approach to predicting outcomes of lung cancer therapies and strategies to overcome drug resistance in vitro) project set out to couple high-content analyses with theoretical and computational methods to provide a global understanding of the origins of tumour cell heterogeneity in response to anticancer drugs. In this context, scientists utilised a systems pharmacology workflow that utilised single cells to perform high-throughput analyses of the responses to anticancer agents. They applied this approach to make predictions for responses in lung cancer. In particular, they quantified the relative importance of different TNF-related apoptosis-inducing ligand (TRAIL) resistance mechanisms in cancer cells with diverse genotypes. Unlike most studies, SYSBIODREZ used single cells to produce over 600 000 features of receptor dynamics following TRAIL activation and to quantify regulatory proteins. Various natural ligands and drugs were tested, and scientists successfully determined the relationships between protein levels and phenotypes at the single-cell level. Furthermore, the study provided compelling evidence to explain why multiple death receptor therapeutic antibodies have so far failed in clinical trials. They conclusively demonstrated an extraordinary lack of potency of apomab antibodies to induce cancer cell apoptosis compared to the recombinant endogenous ligands for the death receptors. Overall, the SYSBIODREZ study demonstrated the power of a systems biology platform to identify the mechanisms responsible for cancer heterogeneity. Furthermore, this tool could be exploited in various cancer types to determine the mechanism of resistance to various drugs.
Systems biology, drug resistance, biomarkers, anticancer drugs, SYSBIODREZ