Construction of prediction model for prognosis of uterine corpus endometrial carcinoma based on pyroptosis gene

• Chunyan Zhang ^[2] ; Jie Bai ^[3] ; Yu Yang ^[4] ; Xiaojuan Wang ^[2] ; Wanqiu Liu ^[2] ; Shujuan Hou ^[2] ; Zhongwei Ai ^[1] ; Qingling Xia ^[5] ; Lei Shao ^[2]
  1. [1] Qiqihar Medical University

     Qiqihar Medical University

     China

     
  2. [2] Department of Gynecology, The Second Affiliated Hospital of Qiqihar Medical University, No. 37 Zhonghua West Road, Jianhua District, Qiqihar, 161000, Heilongjiang, China
  3. [3] Department of Scientific Research, The Second Affiliated Hospital of Qiqihar Medical University, Qiqihar, 161000, China
  4. [4] Reproductive Medicine Center, Qiqihar First Hospital, Qiqihar, 161000, China
  5. [5] Department of Physical Examination, The Second Affiliated Hospital of Qiqihar Medical University, Qiqihar, 161000, China

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• Localización: Clinical & translational oncology, ISSN 1699-048X, Vol. 25, Nº. 5 (May), 2023, págs. 1413-1424
• Idioma: inglés
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• Resumen

  • Purpose To assess the expression of genes that are relevant to pyroptosis and the relationship between these genes and prognosis in uterine corpus endometrial carcinoma (UCEC).

    Methods The research identifies 16 pyroptosis regulators with different expressions in normal endometrium and UCEC. In accordance with the differentially expressed genes (DEGs), the various kinds of UCEC are classified into two sub-types. With the help of the Cancer Genome Atlas (TCGA), the prognostic value of all pyroptosis-related genes for survival was assessed, and a multigene model has constructed accordingly. Ten genes were modeled by applying the minimum criteria for determining risk score selection (LASSO) Cox regression method. Meanwhile, by referring to the TCGA atlas, UCEC patients were divided into the high- and low-risk subgroups. The effects of the gene with significant differences on the proliferation of two cancer cells were also verified.

    Results The survival rate of UCEC cases with higher risk was higher than that with lower risk (P < 0.001). Through the median risk score of TCGA atlas, UCEC cases were ranked as patients with higher risk and patients with lower risk. The low risk has a significant relationship with the prolongation of overall survival (OS) (p = 0.001) in the low-risk subgroup. Moreover, the KEGG and gene ontology (GO) enrichment models indicated that among the patients in the high-risk subgroup, their immune-related genes were concentrated but with decreased immune status.

    Conclusion The apoptosis-related genes are crucial for the immunity of tumors and may forecast the prognosis of UCEC.