Abstract
Abstract
Background
Endometrial cancer (EC) is the most common cancer of the female reproductive system. Palmitoylation dysregulation is linked to various diseases. However, there is still insufficient research on its use as a prognostic marker for EC.
Methods
This research utilized transcriptomic data and clinical characteristics from EC patients sourced from the TCGA database. Key palmitoylation-related genes (PRGs) were identified through a series of bioinformatics analyses, followed by the construction of a prognostic model. The mRNA expression levels of characteristic genes in EC cells and clinical samples were investigated through reverse transcription quantitative polymerase chain reaction (RT-qPCR). Immune infiltration analysis was performed using ssGSEA and CIBERSORT. The molecular subtypes of EC were identified by consensus clustering.
Results
This study identified six PRGs, and the results of bioinformatic analysis of their mRNA expression patterns were consistent with experimental validation. A risk stratification model constructed based on these six PRGs was able to significantly distinguish between high-risk and low-risk patients in terms of survival prognosis, with patients in the low-risk group having a better prognosis than those in the high-risk group. Furthermore, immune characteristic heterogeneity was observed among different risk subgroups. Through consensus clustering analysis, EC samples were classified into two molecular subtypes with significant differences.
Conclusion
This study constructed and validated a prognostic risk model for EC based on PRGs, which demonstrated potential for stratifying patient survival rates and characterizing immune microenvironment features in a retrospective dataset.