Single-cell Omics Decipher Tumor Evolution

Abstract Intra-tumor heterogeneity, the major cause of therapeutic resistance, results from the genetic, epigenetic and microenvironmental selective pressure during tumor progression. However, our knowledge of how this diversity emerges over time remains limited. Single-cell omics approaches, which provide high-resolution data on cellular composition, evolutionary dynamics and clonal relationships in tumor progression, have greatly expanded our toolkit for delineating tumor evolution. Here we summarize recent progress in decoding tumor evolution through single-cell omics measurements and discuss the challenges and opportunities in this emerging field. Tumor evolution begins when a normal cell transforms and expands to form a tumor mass. During this complex process, tumor clonal lineages diverge and form distinct subpopulations under selective pressures in their microenvironment, including the nutrient deprivation, immune system and anti-tumor therapy[1]. Being a result of clonal diversity within the same tumor, intratumor heterogeneity can be manifested in variability of genetic and epigenetic status, gene and protein expression, morphological structure, and other features of the tumor[2,3], which could be used to deconvolution the process of tumor progression. Deep sequencing methods can measure thousands of DNA mutations and generate large-scale genomic datasets on tumors[4]. However standard deep sequencing methods require bulk tissue and therefore provide limited information on the subclonal architecture of a tumor[5,6].