Differential In Vivo Tumorigenicity of Distinct Subpopulations from a Luminal-Like Breast Cancer Xenograft

Intratumor heterogeneity caused by genetic, phenotypic or functional differences between cancer cell subpopulations is a considerable clinical challenge. Understanding subpopulation dynamics is therefore central for both optimization of existing therapy and for development of new treatment. The aim of this study was to isolate subpopulations from a primary tumor and by comparing molecular characteristics of these subpopulations, find explanations to their differing tumorigenicity. Cell subpopulations from two patient derived in vivo models of primary breast cancer, ER+ and ER-, were identified. EpCAM+ cells from the ER+ model gave rise to tumors independently of stroma cell support. The tumorigenic fraction was further divided based on SSEA-4 and CD24 expression. Both markers were expressed in ER+ breast cancer biopsies. FAC-sorted cells based on EpCAM, SSEA-4 and CD24 expression were subsequently tested for differences in functionality by in vivo tumorigenicity assay. Three out of four subpopulations of cells were tumorigenic and showed variable ability to recapitulate the marker expression of the original tumor. Whole genome expression analysis of the sorted populations disclosed high similarity in the transcriptional profiles between the tumorigenic populations. Comparing the non-tumorigenic vs the tumorigenic populations, 44 transcripts were, however, significantly differentially expressed. A subset of these, 26 identified and named genes, highly expressed in the non-tumorigenic population, predicted longer overall survival (N = 737, p<0.0001) and distant metastasis free survival (DMFS) (N = 1379, p<0.0001) when performing Kaplan-Meier survival analysis using the GOBO online database. The 26 gene set correlated with longer DMFS in multiple breast cancer subgroups. Copy number profiling revealed no aberrations that could explain the observed differences in tumorigenicity. This study emphasizes the functional variability among cell populations that are otherwise genomically similar, and that the risk of breast cancer recurrence can only be eliminated if the tumorigenic abilities in multiple cancer cell subpopulations are inhibited.