Heterogeneity of Exhausted T Cell Subsets in Responders and Non-Responders Following Checkpoint Inhibition Therapy

The emerging recognition of multiple states of T cell exhaustion, of which only some are targetable by checkpoint inhibitors, has provided new insights into the variability in patient responses to immunotherapy. We hypothesized that non-responders to therapy have a higher proportion of non-targetable, terminally exhausted T cells compared to responders. To investigate this, we analyzed single-cell RNA sequencing data from 27 patients with head and neck squamous cell carcinoma (HNSCC) treated with neoadjuvant anti-PD-1 or anti-PD-1/CTLA-4 therapy. We identified gene signatures for T cells across different states, ranging from naïve to terminally exhausted, and evaluated their distribution post-treatment. Non-responders exhibited a more inflammatory profile, while responders showed a more balanced immune profile with higher proportions of both helper and regulatory T cells, suggesting that a balanced inflammatory environment may be crucial for therapeutic success. Our analysis further revealed differences between responders and non-responders in the composition of predicted T cell states, particularly in the exhausted T cell subsets, with non-responders showing a higher proportion of terminally exhausted T cells. We therefore propose existence of tumors that may be “too hot”, with resulting loss of efficacy and emergence of therapeutic resistance through a pathway that is different from that of “cold” tumors. Despite limitations, including the small sample size and the lack of well-established transcriptomic signatures of exhaustion subsets, our findings offer a starting point to encourage further investigation into the relationship between inflammation, T cell exhaustion, and therapy efficacy towards improving patient outcomes.