By creating new mammary tumor models, we find that tumor mutation burden and specific immune cells are associated with response.
The core generated both single cell and bulk RNA-seq gene expression data to help this team of Lineberger researchers identify mechanisms mediating responses to immune checkpoint inhibitors using mouse models of triple-negative breast cancer.
Hollern et al. Cell. Volume 179, Issue 5, 14 November 2019, Pages 1191-1206.e21
Immune checkpoint inhibitors (ICIs) have improved patient outcomes in human cancers. In many solid tumors, tumor mutation burden (TMB) and, as a result of high TMB, neoantigen load are biomarkers for therapeutic benefit. In triple-negative breast cancer (TNBC), immune cells identified by pathology or by genomic signatures indicate a favorable prognosis and chemotherapy efficacy is more likely in tumors with immune infiltrates. In this project, the core helped developed a rich resource of single-cell RNA-seq and bulk mRNA-seq data of immunotherapy-treated and non-treated tumors from sensitive and resistant murine models. Using this, the research team uncover that immune checkpoint therapy induces T follicular helper cell activation of B cells to facilitate the anti-tumor response in these models. They also showed that B cell activation of T cells and the generation of antibody are key to immunotherapy response and propose a new biomarker for immune checkpoint therapy. This work presents resources of new preclinical models of breast cancer with large mRNA-seq and single-cell RNA-seq datasets annotated for sensitivity to therapy and uncovers new components of response to immune checkpoint inhibitors.