Immunophenotyping of Kidney Renal Clear Cell Carcinoma Based on Tumor Immune Microenvironment for Cancer Immunotherapy

Abstract

Background: Breakthroughs have been made in cancer immunotherapy using antibodies against immune checkpoints. But successful immune checkpoint blockade (ICB) responses only occur in a fraction of people, and we have no idea which patients will be the lucky one before treatment. Picking out the effective population accurately can improve the cure rate significantly. We set out to design a novel immunophenotyping approaches for kidney renal clear cell carcinoma (KIRC) based on the tumor immune microenvironment(TIME), which target to distinguish immunotherapy responders. Methods: Five hundred and thirty KIRC samples from The Cancer Genome Atlas (TCGA) were analyzed as the training cohort. Non-negative matrix factorization (NMF) was used to extract immune-related features from complex tumor bulks. We associated the expression patterns with a series of immune-related gene signatures and clinicopathological features. GSE73731 and GSE40435 validation datasets were analyzed to further confirm our findings. Findings: We found that almost 40% of KIRC patients in the training cohort (209/530) were designated as the Immune Class with a high enrichment score for inflammatory response, cytolytic activity, and CD8 T cells (all P<0.05). We subdivided the Immune Class into two subgroups based on the tumor immune microenvironment: the Active Immune Class and the Exhausted Immune Class. The latter was distinguished by the enrichment of activated stroma and some immunosuppressive factors, such as fibroblast-TBRS (TGF-β response signature), M2 macrophages, and WNT/TGF signature (all P<0.05). So the patients in the Active Immune Class are ideal candidate for immunotherapy. The mutational burden and neoantigens among these immunophenotypes are significant differences(P=0.008 and P=0.009, respectively). In addition to, the results of validation datasets verified the robustness of the immunophenotypes. Interpretation: This study presented an novel immunophenotyping for KIRC samples based on TIME, and can pick out the ideal candidate to accept immunotherapy. Microenvironment-based immunophenotyping of KIRC paves the way for tailored immunotherapies. Funding Statement: This work was supported in part by National Natural Science Foundation of China (grant numbers 81773551). Natural Science Foundation of Heilongjiang province (H2018012); Research and Innovation Foundation of Harbin Medical University (grant numbers YJSKYCX2018-07HYD). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: Not required.