Abstract
Background: Uterine corpus endometrial carcinoma (UCEC) is a frequent gynecological malignancy with a poor prognosis especially when at an advanced stage. In the present study, we explored the potential of an immune-related gene signature to predict overall survival in UCEC patients.Methods: We analyzed expression data of 616 UCEC patients from The Cancer Genome Atlas database and the International Cancer Genome Consortium as well as immune genes from the ImmPort database and identified the signature. We constructed a transcription factor regulatory network based on Cistrome databases and performed functional enrichment and pathway analyses for the differentially expressed immune genes. Moreover, the prognostic value of 410 immune genes was determined using Cox regression analysis then constructed a prognostic model. Finally, we performed immune infiltration analysis using TIMER-generating immune cell content.Results: Results indicated that the immune cell microenvironment as well as the PI3K-Akt, and MARK signaling pathways were involved in UCEC development. The established prognostic model revealed a ten-gene prognosis signature , comprising PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, and CBLC . This can be used as an independent tool to predict the prognosis of UCEC owing to the observed risk-score. In addition, levels of B cells and neutrophils were significantly correlated with the patient's risk score, and the expression of ten genes is associated with immune cell infiltrates.Conclusions: In summary, we present a 10-gene signature with the potential to predict the prognosis of UCEC. This is expected to guide future development of individualized treatment approaches.
Multiomics profile and prognostic gene signature of m6A regulators in uterine corpus endometrial carcinoma
