Expression profile of epithelial-mesenchymal transition-related genes as a prognostic biomarker of endometrial cancer

Epithelial-mesenchymal transition (EMT) is regulated by inducible factors, transcription factors, and a series of genes involved in signaling pathways, which are correlated with tumor invasion and progression. The present study retrieved the expression profile data of endometrial cancer (EC) from the Cancer Genome Atlas (TCGA) database, screened 1169 EMT-related genes from the dbEMT database, and performed consistency clustering to divide EC samples into two subgroups based on overall survival. Then, the genes differentially expressed between the two subtypes were screened, including 44 related to EMT. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) were applied to construct a prognostic model based on these 44 genes. Five genes were finally included to establish a formula for prognostic risk score calculation as 0.08112529 x L1CAM levels + 0.01497074 x PRKCI levels - 0.05119486 x ESR1 levels + 0.06843238 x CDKN2A levels -0.01311061 x vimentin levels. The low-risk group showed significantly better prognosis compared with the high-risk group (TCGA data, p<0.0001; Gene Expression Omnibus [GEO] data, p=0.0089). In addition, the GEO dataset GSE102073 showed similar results based on the above model, with the high-risk group having poorer prognosis than the low-risk group. The relationship between ERa and vimentin levels was assessed by immunohistochemistry in 323 EC samples with known clinical pathological parameters to confirm the above results. In conclusion, these data indicated that the expression profile of EMT-related genes could predict prognosis in EC.