Identification of novel key genes associated with uterine corpus endometrial carcinoma progression and prognosis

被引:5
作者
Li, Haixia [1 ,2 ,3 ]
Zhou, Quan [4 ]
Wu, Zhangying [5 ,7 ]
Lu, Xiaoling [1 ,2 ,6 ]
机构
[1] Guangxi Med Univ, Sch Basic Med Sci, Nanning, Peoples R China
[2] Guangxi Med Univ, Hosp Stomatol, Coll Stomatol, Guangxi Nanobody Engn Res Ctr,Guangxi Key Lab Nano, Nanning, Peoples R China
[3] Hubei Univ Med, Taihe Hosp, Dept Oncol, Shiyan, Peoples R China
[4] Hubei Univ Med, Renmin Hosp, Dept Tradit Chinese Med, Shiyan, Peoples R China
[5] Guizhou Med Univ, Dept Obstet & Gynecol, Affiliated Hosp, Guiyang, Peoples R China
[6] Guangxi Med Univ, 22 Shuangyong Rd, Nanning 530021, Peoples R China
[7] Guizhou Med Univ, Affiliated Hosp, 28 Guiyijie St, Guiyang 550001, Peoples R China
基金
国家重点研发计划;
关键词
Uterine corpus endometrial carcinoma (UCEC); weighted gene co-expression network analysis (WGCNA); differentially expressed gene analysis; survival analysis; bioinformatics; ESTROGEN-RECEPTOR-ALPHA; GINS COMPLEX; CANCER; AMPLIFICATION; SURVIVAL; RISK; EXPRESSION; BIOMARKER; PATTERNS; PREDICTS;
D O I
10.21037/atm-22-6461
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Uterine corpus endometrial carcinoma (UCEC) is a common malignant cancer type which affects the health of women worldwide. However, its molecular mechanism has not been elucidated.Methods: To identify the hub modules and genes in UCEC associated with clinical phenotypes, the RNA sequencing data and clinical data of 543 UCEC samples were obtained from The Cancer Genome Atlas (TCGA) database and then subjected to weighted gene co-expression network analysis (WGCNA). To explore the potential biological function of the hub modules, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Genes differentially expressed in UCEC were screened according to TCGA data using the "gdcDEAnalysis" package in R (The R Foundation for Statistical Computing). After intersecting with hub genes, the shared genes were used for further survival analyses. The relationship between gene expression level and clinical phenotype was analyzed in the TCGA-UCEC cohort in The University of ALabama at Birmingham CANcer data analysis Portal and the Human Protein Atlas. The microarray data set GSE17025 was also analyzed to validate the gene expression profiles.Results: There were 19 coexpression modules generated by WGCNA. Among them, 2 modules with 198 hub genes were highly correlated with clinical features (especially histologic grade and clinical stage). Meanwhile, 4,003 differentially expressed genes (DEGs) were screened out, and 164 DEGs overlapped with hub genes. Survival analyses revealed that high expression of GINS4 and low expression of ESR1 showed a trend of poor prognosis. Further analyses demonstrated that both messenger RNA (mRNA) and protein expression profiles of GINS4 and ESR1 were significantly associated with UCEC development and progression in TCGA and GSE17025 cohorts.Conclusions: Based on the integrated bioinformatic analyses, our data indicated that GINS4 and ESR1 might serve as potential prognostic markers and targets for UCEC therapy.
引用
收藏
页数:22
相关论文
共 50 条
  • [21] Identification and validation of key genes associated with pathogenesis and prognosis of gastric cancer
    Li, Ai
    Li, Yan
    Li, Yueyue
    Zhang, Mingming
    Zhang, Hong
    Chen, Feixue
    PEERJ, 2023, 11
  • [22] In Silico Identification of Genes Associated with Breast Cancer Progression and Prognosis and Novel Therapeutic Targets
    Uchida, Shiro
    Sugino, Takashi
    BIOMEDICINES, 2022, 10 (11)
  • [23] COVID-19-associated lncRNAs as predictors of survival in uterine corpus endometrial carcinoma: A prognostic model
    Ding, Yang
    Li, Xia
    Li, Jiena
    Zhu, Liqun
    FRONTIERS IN GENETICS, 2022, 13
  • [24] Data mining of key genes expression in hepatocellular carcinoma: novel potential biomarkers of diagnosis prognosis or progression
    Cabiati, Manuela
    Gaggini, Melania
    De Simone, Paolo
    Del Ry, Silvia
    CLINICAL & EXPERIMENTAL METASTASIS, 2022, 39 (04) : 589 - 602
  • [25] Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma
    Bian, Jia
    Xu, Yuzi
    Wu, Fei
    Pan, Qiangwei
    Liu, Yunlong
    ONCOLOGY LETTERS, 2020, 20 (03) : 2396 - 2410
  • [26] Key genes associated with prognosis and metastasis of clear cell renal cell carcinoma
    Zhong, Tingting
    Jiang, Zeying
    Wang, Xiangdong
    Wang, Honglei
    Song, Meiyi
    Chen, Wenfang
    Yang, Shicong
    PEERJ, 2022, 9
  • [27] Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA
    Xia, Wang-Xiao
    Yu, Qin
    Li, Gong-Hua
    Liu, Yao-Wen
    Xiao, Fu-Hui
    Yang, Li-Qin
    Rahman, Zia Ur
    Wang, Hao-Tian
    Kong, Qing-Peng
    PEERJ, 2019, 7
  • [28] Inflammation-Related LncRNAs Signature for Prognosis and Immune Response Evaluation in Uterine Corpus Endometrial Carcinoma
    Gu, Hongmei
    Song, Jiahang
    Chen, Yizhang
    Wang, Yichun
    Tan, Xiaofang
    Zhao, Hongyu
    FRONTIERS IN ONCOLOGY, 2022, 12
  • [29] Deciphering comprehensive features of tumor microenvironment controlled by chromatin regulators to predict prognosis and guide therapies in uterine corpus endometrial carcinoma
    Wu, Qihui
    Tian, Ruotong
    Liu, Jiaxin
    Ou, Chunlin
    Li, Yimin
    Fu, Xiaodan
    FRONTIERS IN IMMUNOLOGY, 2023, 14
  • [30] Identification and Analysis of Potential Key Genes Associated With Hepatocellular Carcinoma Based on Integrated Bioinformatics Methods
    Li, Zhuolin
    Lin, Yao
    Cheng, Bizhen
    Zhang, Qiaoxin
    Cai, Yingmu
    FRONTIERS IN GENETICS, 2021, 12