Development of an immune gene prognostic classifier for survival prediction and respond to immunocheckpoint inhibitor therapy/chemotherapy in endometrial cancer

Immunotherapy has provided a promising therapeutic strategy for endometrial cancer (EC). The present study aims to develop a prognostic classifier based on immune-related genes (IRGs) to stratify EC patients. A total of 15 prognosis-related IRGs were further filtrated by multivariate Cox regression: LTA, TMSB15A, S100A14, PLA2G2A, PDGFRA, CLDN4, CTF1, PRLH, PTN, SST, HTR3E, NRP1, RORA, THRA and CBLC. A prognostic signature was constructed to split EC patients into the high-risk and low-risk group with statistically different survival outcomes, indicating good potential for the prognostic signature in survival surveillance. Furthermore, five compounds with potential anti-tumor effects were selected, including ciclopirox, ikarugamycin, vincamine, mevalolactone, and thiamazole. The abundance of follicular helper T cells, regulatory T cells and M0 macrophages were significantly enhanced in the high-risk group while resting memory CD4+ T cells, gamma delta T cells, M2 macrophages and resting mast cells were markedly elevated in the low-risk group. Memory activated CD4+ T cells, CD8+ T cells and activated mast cells were three most correlative with riskscore. An immunophenoscore (IPS) analysis revealed that patients of the low-risk group had a higher IPS and more inclined to respond to immune checkpoint inhibitors. Mutation analysis showed that patients of the low-risk group represented more tumor mutation burden but low riskscore, thus getting better prognosis. Patients of the low-risk group were more sensitive for gemcitabine, bleomycin, vinblastine, vinorelbine and methotrexate by prediction. We constructed a potential prognostic model and might offer new insight on the identification of new immune-related biomarkers and target therapy in EC.