高级检索
当前位置: 首页 > 详情页

A model based on immunogenic cell death-related genes predicts prognosis and response to immunotherapy in kidney renal clear cell carcinoma

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE

机构: [1]Department of Clinical Laboratory, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China. [2]Information Security Center, Information and Communication Branch of State Grid Hebei Electric Power Co. Ltd., Shijiazhuang, China. [3]Research Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
出处:
ISSN:

关键词: Biomarkers prognosis renal cancer immunogenic cell death-related genes (ICD-related genes)

摘要:
The prognosis of patients with kidney renal clear cell carcinoma (KIRC), a life-threatening condition, is poor. Immunogenic cell death (ICD) induces regulated cell death via immunogenic signal secretion and exposure. ICD induces regulated cell death through immunogenic signal secretion and exposure. ICD plays an essential role in tumorigenesis, however, the role of ICD in KIRC remains unclear.This study examined the expression levels of 34 ICD-related genes in The Cancer Genome Atlas (TCGA) data set. Signature genes linked to KIRC survival were identified using Cox regression. Next, a prognostic risk model (RM) was built. Subsequently, the KIRC patients were divided into low- and high-risk groups. Kaplan-Meier curves and receiver operating characteristic (ROC) curves were plotted. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were carried out to investigate the possible role of differential gene expression between the two groups. The immune microenvironment (IME) was assessed using Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression, CIBERSORT, and single-sample gene-set enrichment analysis algorithms. An enrichment analysis was used to determine the biological significance of these regulatory networks we conducted. The relationship between immune checkpoint gene expression and risk score, and the relationship between treatment outcome and gene expression were assessed using correlation analyses.We developed a KIRC RM based on five ICD-related genes (i.e., FOXP3, IFNB1, IL6, LY96, and TLR4), which were identified as the prognostic signature genes. Using the TCGA data set, we conducted a survival analysis and found that the 3-year RM had an area under the curve (AUC) of 0.735, which validated the reliability of the signature. Similarly, using the International Cancer Genome Consortium (ICGC) data set, we found that the 3-year RM had an AUC of 0.732.A RM based on five ICD-related genes was built to predict the prognosis of KIRC patients. This RM predicted patient prognosis and reflected the tumor IME of KIRC patients. Thus, this RM could be used to promote individualized treatments and provide potential novel targets for immunotherapy.2024 Translational Cancer Research. All rights reserved.

基金:
语种:
被引次数:
WOS:
PubmedID:
中科院分区:
出版当年[2025]版:
大类 | 4 区 医学
小类 | 4 区 肿瘤学
最新[2025]版:
大类 | 4 区 医学
小类 | 4 区 肿瘤学
JCR分区:
出版当年[2024]版:
Q4 ONCOLOGY
最新[2024]版:
Q4 ONCOLOGY

影响因子: 最新[2024版] 最新五年平均 出版当年[2024版] 出版当年五年平均 出版前一年[2023版]

第一作者:
第一作者机构: [1]Department of Clinical Laboratory, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:42313 今日访问量:0 总访问量:1365 更新日期:2025-08-01 建议使用谷歌、火狐浏览器 常见问题

技术支持:重庆聚合科技有限公司 地址:河北省石家庄市健康路12号