Expression of EMT-Related Genes in Lymph Node Metastasis in Endometrial Cancer: A TCGA-based study

Background: Endometrial cancer (EC) identified in pelvic/para-aortic lymph nodes suggests a poorer prognosis. Literature focusing on the role of epithelial-mesenchymal transition (EMT) in lymph node metastasis (LNM) remains few. Methods Transcriptional data were acquired from TCGA database. Patients with stage IA-IIIC2 EC were included, constituting the LN positive and negative groups. To evaluate the extent of EMT, an EMT signature composed of 315 genes was adopted. EMT-related genes (ERGs) were obtained from dbEMT2 database, differentially expressed ERGs (DEERGs) of which between the two groups were screened out. On the basis of DEERGs, pathway analysis was carried out. We finally used the logistic regression model to build an ERG-based gene signature with diagnostic value for LNM in EC. Results A total of 498 patients were included, with 75 in the LN positive group. Median EMT score of tumor tissues from LN negative group was − 0.369, while that from LN positive group was − 0.296 (P < 0.001), suggesting a more mesenchymal phenotype for LNM cases on the EMT continuum. By comparing the expression profiles, 266 genes were identified as DEGs, in which 184 were upregulated and 82 were downregulated. In pathway analyses, various EMT-related pathways were enriched. DEERGs shared between molecular subtypes were relatively few. The ROC curve and logistic regression analysis screened 7 genes with the best performance to discriminate between the LN positive and negative group, i.e. CIRBP, DDR1, F2RL2, HOXA10, PPARGC1A, SEMA3E and TGFB1 . A logistic regression model including the 7-genes based risk score, age, grade, myometrial invasion and histological subtype was built, with an AUC of 0.850 and a good calibration (P = 0.074). In a validation dataset composed of 83 EC patients, the model exhibited a promising diagnostic value and was well calibrated (P = 0.42). Conclusion The EMT status and expression of ERGs varied in EC tissues from LN positive and negative cases, involving multiple EMT-related signalling pathways, and the distribution of DEGs differed among molecular subtypes. An ERG-based gene signature including 7 DEERGs exhibited a potential application value.