Interleukin-6 trans-signaling is a candidate mechanism to drive progression of human DCCs during clinical latency.

Although thousands of breast cancer cells disseminate and home to bone marrow until primary surgery, usually less than a handful will succeed in establishing manifest metastases months to years later. To identify signals that support survival or outgrowth in patients, we profile rare bone marrow-derived disseminated cancer cells (DCCs) long before manifestation of metastasis and identify IL6/PI3K-signaling as candidate pathway for DCC activation. Surprisingly, and similar to mammary epithelial cells, DCCs lack membranous IL6 receptor expression and mechanistic dissection reveals IL6 trans-signaling to regulate a stem-like state of mammary epithelial cells via gp130. Responsiveness to IL6 trans-signals is found to be niche-dependent as bone marrow stromal and endosteal cells down-regulate gp130 in premalignant mammary epithelial cells as opposed to vascular niche cells. PIK3CA activation renders cells independent from IL6 trans-signaling. Consistent with a bottleneck function of microenvironmental DCC control, we find PIK3CA mutations highly associated with late-stage metastatic cells while being extremely rare in early DCCs. Our data suggest that the initial steps of metastasis formation are often not cancer cell-autonomous, but also depend on microenvironmental signals.

Targeted transcript quantification in single disseminated cancer cells after whole transcriptome amplification.

Gene expression analysis of rare or heterogeneous cell populations such as disseminated cancer cells (DCCs) requires a sensitive method allowing reliable analysis of single cells. Therefore, we developed and explored the feasibility of a quantitative PCR (qPCR) assay to analyze single-cell cDNA pre-amplified using a previously established whole transcriptome amplification (WTA) protocol. We carefully selected and optimized multiple steps of the protocol, e.g. re-amplification of WTA products, quantification of amplified cDNA yields and final qPCR quantification, to identify the most reliable and accurate workflow for quantitation of gene expression of the ERBB2 gene in DCCs. We found that absolute quantification outperforms relative quantification. We then validated the performance of our method on single cells of established breast cancer cell lines displaying distinct levels of HER2 protein. The different protein levels were faithfully reflected by transcript expression across the tested cell lines thereby proving the accuracy of our approach. Finally, we applied our method to breast cancer DCCs of a patient undergoing anti-HER2-directed therapy. Here, we were able to measure ERBB2 expression levels in all HER2-protein-positive DCCs. In summary, we developed a reliable single-cell qPCR assay applicable to measure distinct levels of ERBB2 in DCCs.