Journal of Shandong University (Health Sciences) ›› 2019, Vol. 57 ›› Issue (10): 80-85.doi: 10.6040/j.issn.1671-7554.0.2019.104

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Establishment of survival related multigene prognostic model of epithelial ovarian cancer

ZHU Aiguo, MA Zhenchi, WANG Jian   

  1. Department of Comprehensive Surgery, Tianjin Medical University Cancer Institute and Hospital;
    National Clinical Research Center for Cancer;
    Key Laboratory of Cancer Prevention and Therapy, Tianjin;
    Tianjins Clinical Research Center for Cancer, Tianjin 300060, China
  • Published:2022-09-27

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Abstract: Objective To establish a multigene prognostic model associated with the prognosis of the epithelial ovarian cancer(EOC)patients and validate the prognostic power through Gene Expression Omnibus(GEO)database and The Cancer Genome Atlas(TCGA)database. Methods The Affymetrix expression profiles(GSE14407)were downloaded 山 东 大 学 学 报 (医 学 版)57卷10期 -朱爱国,等.利用上皮源性卵巢癌预后的多基因信息建立预测预后模型 \=-and analyzed from GEO dataset. Different expression genes(DEGs)between EOC tissue and normal epithelial tissue were selected to identify a multigene prognostic model. DEGs were selected by univariate and multivariate Cox regression model to establish a multigene prognostic model and prognostic index(PI)formula. mRNA expression data and clinical data of patients were obtained from TCGA dataset. According to PI, the patients were divided into high risk group and low risk group. Clinical and pathological feature(age, neoplasm subdivision, histologic grade, residual tumor, clinical stage)and PI were evaluated as influence factors affecting overall survival(OS)of EOC patients. The prognostic value of multigene model by Kaplan-Meier survival analysis was verified in overall and subgroup EOC patients according to age, neoplasm subdivision, residual tumor, and clinical stage. Results A total of 47 DEGs between EOC and normal tissues were screened, in which 37 DEGs were down-regulated and 17 DEGs were up-regulated. By univariate and multivariate Cox model, 4DEGs, i.e., PACSIN3,KCNT1,LAMP3 and KIR3DX1, were finally selected to establish a four-gene prognostic model. PI formula was as follows:(-0.169 × the expression of PACSIN3 + 0.078 × the expression of KCNT1 -0.246 × the expression of LAMP3 -0.147 × the expression of KIR3DX1). Age, residual tumor and multigene gene prognostic model were independent prognostic factors of EOC patients(P<0.01). OS of low risk group was longer than high risk group by K-M plots(P<0.05). In different subgroups(age,clinical stage, neoplasm subdivision, residual tumor)of EOC patients, low risk group had longer OS than high risk group(P<0.05). Conclusion Four-gene prognostic model is the independent prognostic factor in EOC patients, and is demonstrated remarkable prognostic value in overall EOC patients and each subgroup according to different clinical and pathological factors.

Key words: Ovary cancer, Prognosis, The Cancer Genome Atlas, Cox proportional regression model, Biological information

CLC Number: 

  • R711.75
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