Pan-cancer drivers are recurrent transcriptional regulatory heterogeneities in early-stage luminal breast cancer

The heterogeneous composition of solid tumors is known to impact disease progression and response to therapy. Malignant cells coexist in different regulatory states that can be accessed transcriptomically by RNA sequencing, but single-cell methods have many caveats related to sensitivity, noise, and sample handling. We revised a statistical fluctuation analysis called stochastic profiling to combine with 10-cell RNA sequencing, which was designed for laser-capture microdissection (LCM) and extended here for immuno-LCM. When applied to a cohort of late-onset, early-stage luminal breast cancers, the integrated approach identified thousands of candidate regulatory heterogeneities. Intersecting the candidates from different tumors yielded a relatively stable set of 710 recurrent heterogeneously expressed genes (RHEGs) that were significantly variable in >50% of patients. RHEGs were not confounded by dissociation artifacts, cell cycle oscillations, or driving mutations for breast cancer. Rather, we detected RHEG enrichments for epithelial-to-mesenchymal transition genes and, unexpectedly, the latest pan-cancer assembly of driver genes across all cancer types. Heterogeneous transcriptional regulation conceivably provides a faster, reversible mechanism for malignant cells to sample the effects of potential oncogenes or tumor suppressors on cancer hallmarks. 10-cell samples from human breast cancer biopsies were captured by laser capture microdissection. mRNA was extracted and PCR amplified for RNA-sequencing