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基于GEO 和TCGA 数据库胰腺癌生存 相关基因的生物信息学分析

  • The First Affiliated Hospital of Xi’an Jiaotong University
  • Xi'an Jiaotong University

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

Objective Based on Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database, survival analysis was used to screen the key prognostic genes involved of pancreatic cancer patients. Methods Two pancreatic cancer gene chips (Microarray) from the GEO database and transcriptome sequencing (RNA-seq) from the TCGA database were used to filter the survival-related genes using Kaplan-Meier (KM) analysis and Cox risk model, and the target genes were intersected. Prognosis-associated genes were screened first and then pathway enrichment analysis or immune-enrichment analysis was performed based on these genes to find out their potential molecular mechanisms in regulating pancreatic cancer. Results In this study, five survival-related genes (i.e., CDOl, DCBLD2, FAM83A, ITGA3 and 5LC16A3) were screened out. Multifactorial Cox regression analysis and clinical correlation analysis showed that high CDOl expression was a protective factor for pancreatic cancer prognosis, and its antitumor effect was associated with its role in inhibiting the malignant biological behavior of pancreatic cancer cells and promoting the infiltration of immune killer cells in pancreatic cancer. Conclusion This study suggests that CDOl is a potential tumor suppress gene of pancreatic cancer, and the tumor inhibition effect of CDOl may be related to its role in remodeling the immune microenvironment of pancreatic cancer.

投稿的翻译标题Bioinformatics analysis of survival-related genes in pancreatic cancer based on GEO and TCGA database
源语言繁体中文
页(从-至)717-724
页数8
期刊Journal of Xi'an Jiaotong University (Medical Sciences)
44
5
出版状态已出版 - 9月 2023

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 3 - 良好健康与福祉
    可持续发展目标 3 良好健康与福祉

关键词

  • CDOl
  • immune microenvironment
  • pancreatic cancer
  • survival-related gene

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