Immune checkpoint therapy responders display early clonal expansion of tumor infiltrating lymphocytes.

Immune checkpoint therapy (ICT) causes durable tumour responses in a subgroup of patients, but it is not well known how T cell receptor beta (TCRß) repertoire dynamics contribute to the therapeutic response. Using murine models that exclude variation in host genetics, environmental factors and tumour mutation burden, limiting variation between animals to naturally diverse TCRß repertoires, we applied TCRseq, single cell RNAseq and flow cytometry to study TCRß repertoire dynamics in ICT responders and non-responders. Increased oligoclonal expansion of TCRß clonotypes was observed in responding tumours. Machine learning identified TCRß CDR3 signatures unique to each tumour model, and signatures associated with ICT response at various timepoints before or during ICT. Clonally expanded CD8+ T cells in responding tumours post ICT displayed effector T cell gene signatures and phenotype. An early burst of clonal expansion during ICT is associated with response, and we report unique dynamics in TCRß signatures associated with ICT response.

Sensitization to immune checkpoint blockade through activation of a STAT1/NK axis in the tumor microenvironment.

Cancer immunotherapy using antibodies that target immune checkpoints has delivered outstanding results. However, responses only occur in a subset of patients, and it is not fully understood what biological processes determine an effective outcome. This lack of understanding hinders the development of rational combination treatments. We set out to define the pretreatment microenvironment associated with an effective outcome by using the fact that inbred mouse strains bearing monoclonal cancer cell line-derived tumors respond in a dichotomous manner to immune checkpoint blockade (ICB). We compared the cellular composition and gene expression profiles of responsive and nonresponsive tumors from mice before ICB and validated the findings in cohorts of patients with cancer treated with ICB antibodies. We found that responsive tumors were characterized by an inflammatory gene expression signature consistent with up-regulation of signal transducer and activator of transcription 1 (STAT1) and Toll-like receptor 3 (TLR3) signaling and down-regulation of interleukin-10 (IL-10) signaling. In addition, responsive tumors had more infiltrating-activated natural killer (NK) cells, which were necessary for response. Pretreatment of mice with large established tumors using the STAT1-activating cytokine interferon-γ (IFNγ), the TLR3 ligand poly(I:C), and an anti-IL-10 antibody sensitized tumors to ICB by attracting IFNγ-producing NK cells into the tumor, resulting in increased cure rates. Our results identify a pretreatment tumor microenvironment that predicts response to ICB, which can be therapeutically attained. These data suggest a biomarker-driven approach to patient management to establish whether a patient would benefit from treatment with sensitizing therapeutics before ICB.