Cancer consists of (epi)genetically and phenotypically different populations of single cells. This intra-tumor cellular heterogeneity underlies therapeutic resistance to cancer treatments. Understanding the heterogeneity of tumors (at the level of the cancer cells and the surrounding immune cells) down to the single-cell level is therefore essential and enabled by the rapid emergence of single-cell technologies. The goal of this work package is to exploit these novel technologies and apply them to biopsies collected from BC patients. In the clinical trials where sample collection is ongoing and viable cells can be acquired, single-cell RNA analysis will be performed.
Pilot sc-RNA-seq analysis before and during treatment with checkpoint immune therapy (left above). Transcriptome data is generatied for 80 000 cells. Clustering reveals cell type identify for each cell (9 cell types in total) based on marker gene expression (right above). Re-clustering of T-cells reveals 9 T-cell states, as indicated. Among these, two exhausted T cell states express PD2, indicating that these re representing the exhausted CD4+ and CD8+ T cells (below left). Patients can be classified as potential responders based on high amounts of T cells, exhausted CD4+ and CD8+ T cells and are characterised by new TCR clonotypes in the on-treatment biopsies (i.e. T cell expansion) (below middle and right). Other patients are characterised by low numbers of T cells, including exhausted CD4+ and CD8+ T cells and no T cell expansion. This will be validated in RESCUER, where treatment response data are available.
