Predictive "omic" biomarkers of drug response: Colorectal cancer as a model

The introduction of biomarkers for the rational choice of drug treatment options in several cancer types has significantly improved therapeutic outcomes. At present, optimal therapeutic planning considers however a few somatic tumor gene mutations to improve drug treatment response. Other omics-based molecular biomarkers may provide a deeper knowledge of the sources of interindividual variability in cancer patient drug response. Thus, a molecular biomarker signature predictive of response linked to standard clinical, pathological, biochemical, and molecular markers would be useful for patient stratification and drug treatment customization to select personalized therapies with greater efficacy and tolerability. Colorectal cancer represents a model of a tumor with a high impact on health, being one of the most incident and lethal cancers worldwide. Elevated death rates depend on neoplastic progression guided by several dysregulated biomolecular events, including the evolutionary metastatic process occurring in about 50% of the patients. Despite the availability of active cytotoxic and targeted drugs, including antiangiogenic agents, the efficacy of pharmacological treatment of metastatic, and even early, colorectal cancer is hampered by the occurrence of intrinsic and acquired drug resistance. This chapter describes the status of the art of known and potential biomarkers predictive of drug response and tolerability in colorectal cancer from various “omics” sciences. It also highlights promising perspectives in this field. Combined analysis by machine learning and artificial intelligence of these determinants may contribute to identifying molecular comprehensive signatures predictive of efficacy and toxicity to be validated by prospective clinical trials, for the use in precision medicine of colorectal cancer patients.