Translational implications of tumor heterogeneity

Abstract

Advances in next-generation sequencing and bioinformatics have led to an unprecedented view of the cancer genome and its evolution. Genomic studies have demonstrated the complex and heterogeneous clonal landscape of tumors of different origins and the potential impact of intratumor heterogeneity on treatment response and resistance, cancer progression, and the risk of disease relapse. However, the significance of subclonal mutations, in particular mutations in driver genes, and their evolution through time and their dynamics in response to cancer therapies, is yet to be determined. The necessary tools are now available to prospectively determine whether clonal heterogeneity can be used as a biomarker of clinical outcome and to what extent subclonal somatic alterations might influence clinical outcome. Studies that use longitudinal tissue sampling, integrating both genomic and clinical data, have the potential to reveal the subclonal composition and track the evolution of tumors to address these questions and to begin to define the breadth of genetic diversity in different tumor types and its relevance to patient outcome. Such studies may provide further evidence for drug-resistance mechanisms informing combinatorial, adaptive, and tumor immune therapies placed within the context of tumor evolution.