Typing the tumor immune signatures in patients of Lynch syndrome facilitates predicting the responsiveness of immune checkpoint inhibition

Abstract Background: Although many efforts of predicting the responsiveness to immune checkpoint inhibition including expression of PD-L1 and MHC I, microsatellite instability (MSI), mismatch repair (MMR) defect, tumor mutation burden (TMB), tertiary lymphoid structures (TLSs) and several transcriptional signatures have been performed, the sensitivity remains to be further improved. Methods and Results: Here, we integrated T cell spatial distribution and intratumor transcriptional signals in predicting the response to immune checkpoint therapy in Lynch Syndrome (LS) which is featured with MMR deficiency. In all three cohorts, LS patients displayed the personalized tumor immune signatures of inflamed, immune excluded, and immune desert, which were not only individual-specific but also organ-specific. Furthermore, the immune desert exhibited more malignant indicated by low differentiation adenocarcinoma, larger tumor sizes, and higher metastasis rate. Moreover, the tumor immune signatures associated with distinct populations of infiltrating immune cells were comparable to TLSs and more sensitive than transcriptional signature gene expression profiles (GEPs) in immunotherapy prediction. Surprisingly, the tumor immune signatures might arise from the somatic mutations. Notably, LS patients had benefited from the typing of immune signatures and later immune checkpoint inhibition. Conclusions: Our findings suggest that compared to PD-L1 expression, MSI, MMR, TMB, and GEPs, characterization of the tumor immune signatures in Lynch syndrome improve the efficiency of predicting the responsiveness of immune checkpoint inhibition.