Objective To explore the key genes in postmenopausal endometrial cancer(EC)patients by construc-ting and validating a clinical prediction model,and to discuss its role in predicting the survival prognosis of EC patients.Methods A total of 45 patients with EC in the Department of Obstetrics and Gynecology of Hospital from January 2022 to October 2023 were selected.Tumor tissues and adjacent normal tissues of EC patients were obtained by surgery.The tran-scriptome data of EC samples and normal tissue samples were downloaded from GEO data and the Cancer Genome Atlas(TCGA)database.The important gene modules and hub genes related to postmenopausal status of EC patients were deter-mined by weighted gene co-expression network analysis(WGCNA),and the signaling pathways involved in overlapping genes were enriched by GO and KEGG.The protein interaction was analyzed by the online tool(STRING)and visualized in Cytoscape software.The importance of each node was evaluated by the Degree algorithm in the CytoHubba plug in,and the top five nodes were selected.The Logistic regression model and ROC curve were constructed to analyze the role of key genes in predicting the survival of EC patients.Finally,Western blotting and real-time fluorescence quantitative PCR(RT qPCR)were used to verify the expression of key genes in postmenopausal EC tissues.Results WGCNA analysis of genes obtained by sequencing in GSE17025 dataset and TCGA_UCEC transcriptome samples identified 17 modules in GSE17025 dataset.The"red"module was highly positively correlated with EC(r=0.650,P＜0.001).1 019 genes were included.A total of 5 modules were identified in TCGA_UCEC,of which the"blue"module was highly positively correlated with EC(r=0.380,P＜0.001),including 336 genes.GO and KEGGenrichment analysis were performed on overlapping genes.Protein interaction analysis was performed on 126 genes in the top ten KEGG enriched pathways through STRING database.PKD1,ACTB,SRC,CDH1 and COL1A1 were selected as potential core genes based on Degree algorithm.By constructing logistic regres-sion,PKD1(OR=2.930,P=0.047),SRC(OR=0.656,P=0.041)and CDH1(OR=0.612,P=0.023)could effectively predict the survival of EC patients.The ROC curve showed that among PKD1,SRC and CDH1,PKD1 had a better diagnostic value for predicting the survival of EC(A UC=0.634,95％CI=0.540-0.727,P=0.006).The results of Western blot and RT qPCR showed that PKD1 protein and RNA levels in cancer tissues were significantly higher than those in adjacent tissues(pro-tein:3.17±1.09 vs.0.98±036,t=10.090,P＜0.001;RNA:2.15±0.84 vs.0.99±0.31,t=11.257,P＜0.001).Conclusion PKD1 may be a key gene affecting the prognosis and survival of postmenopausal EC patients by regulating the cell cycle or PI3K Akt signaling pathway.It provides a basis for further exploring the molecular mechanism of PKD1 in EC,which has impor-tant scientific value and significance.
维普
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