Decoding breast cancer tissue-stroma interactions using species-specific sequencing

Decoding genome-wide effects of experimental tissue-tissue or cell-cell interactions is important, for example, to better understand tumor-stroma interactions after transplantation (xenografting). Transcriptome analysis of intermixed human and mouse cells has frequently relied on the need to separate the two cell populations prior to transcriptome analysis, which introduces confounding effects on gene expression. To circumvent this problem, we perform a bioinformatics-based genome-wide transcriptome analysis technique separating the mouse and human transcriptome part of a dataset, which allows a mixed mouse and human cell population to be sequenced without prior cell sorting. We use the new technology – which we call S3 (“S-cube” for Species-specific sequencing) technology – to provide new insights into the Notch downstream response following Notch ligand-stimulation and to explore transcriptional changes following transplantation of luminal (MCF7) and basal-type (MDA-MB-231) human breast cancer cells into mammary fat pad tissue in mice. Overall design: Analysis of Notch response to ligand in three settings: co-culture, immobilized ligand and xenografted tumors