Genome perspective: Several cancer types consist of multiple genetically distinct subpopulations. The underlying mechanism for this intra-tumor heterogeneity can be explained by the clonal evolution model, whereby growth advantageous mutations cause the expansion of cancer cell subclones. The recurrent phenotype of many cancers may be a consequence of these coexisting subpopulations responding unequally to therapies. To address cellular subpopulation dynamics within human tumors, we developed a bioinformatic method, EXPANDS. It leverages bulk DNA sequencing data to estimate the proportion of cells harboring specific mutations in a tumor. By modeling cellular frequencies as probability distributions, EXPANDS predicts mutations that accumulate in a cell before its clonal expansion.
Histopathology perspective: Recent advances in NGS technologies gave rise to a plethora of approaches that quantify and characterize the genotypic diversity within a given tumor. We recently presented evidence supporting a quantitative relation between genotypic intra-tumor heterogeneity and cellular diversity derived from H&E histopathology (Andor et al., 2015). However, so far qualitative details of how this cellular diversity is structured (i.e. how many subpopulations are present and what their geographical boundaries are on the H&E slide) are unknown. Our aim is to bring automated H&E image analysis to the next level of resolution, from distinction between tumor- and normal cell populations towards distinction amongst distinct tumor cell subpopulations.
Transcriptome perspective: Conventional RNA sequencing or microarray-based gene expression studies rely on processing of bulk tumor tissues where the single cell transcriptional information is lost. These approaches have limitations in characterizing gene expression heterogeneity amongst the various individual cells within a tumor and resolving the tumor cell subpopulations. Recently, single cell RNA-Seq technologies have matured such that one can sequence and analyze thousands of cells per a given tumor. At this scale, one can derive significant insights into a tumor’s cellular heterogeneity, characteristics of the cellular diversity in the local tumor microenviroment and the biological features that delineate different cell populations.
Identity: An “Identity” is a view on the phenotypic characteristics of a clone – a changing complex measure that ideally reflects a perfect agreement among clone perspectives. Perspectives may be obtained from different technologies applied on the same specimen (e.g. exome-sequencing and single cell RNA-sequencing) or from different specimens of the same biopsy. Consilience among the different perspectives on a clone indicates robust results; whereas lack of consilience gives feedback that the results cannot be trusted. Integration of multiple perspectives on the same clone provides a more complete picture, bringing us closer to the clone’s phenotypes (e.g. its genomic instability) and to the ability to predict how the clone will behave under different conditions, e.g. chemotherapy.