Immune desert in MMR-deficient tumors predicts poor responsiveness of immune checkpoint inhibition - Zheng, Guoxing; Lu, Yingsi; Yang, Zheng; Chen, Hong; Liang, Qian; Zhu, Qingqing; Li, Yan; Xiao, Xing; He, Zhuzhen; Zhu, Yifan; Li, Bo; Huang, Leilei; et al. (Frontiers in Immunology, 2023)
Background: Although many efforts have been devoted to identify biomarkers to predict the responsiveness of immune checkpoint inhibitors, 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, the sensitivity of these indicators remains to be further improved. Materials and Methods: Here, we integrated T cell spatial distribution and intratumor transcriptional signals in predicting the response to immune checkpoint therapy in MMR deficient tumors including Lynch Syndrome (LS). Results: In both two cohorts, MMR deficient tumors displayed personalized tumor immune signatures, including inflammation, immune exclusion, and immune desert, which were not only individual-specific but also organ-specific. Furthermore, the immune desert tumor exhibited more malignant phenotype characterized 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, patients with MMR deficiency had benefited from the typing of immune signatures and later immune checkpoint inhibition. Conclusion: Our findings suggest that compared to PD-L1 expression, MMR, TMB, and GEPs, characterization of the tumor immune signatures in MMR deficient tumors improves the efficiency of predicting the responsiveness of immune checkpoint inhibition.