高级检索
当前位置: 首页 > 详情页

Immune-related gene signature predicts overall survival of gastric cancer patients with varying microsatellite instability status

| 认领 | 导出 |

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE ◇ 预警期刊

单位: [1]Department of Oncology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China. [2]Department of Ultrasound, Aero Space Central Hospital, Beijing 100050, China. [3]Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing 100050, P. R. China.
出处:
ISSN:

关键词: gastric cancer microsatellite instability immune-related genes survival analysis The Cancer Genome Atlas

摘要:
Purpose: Gastric cancer (GC) is one of the most common and fatal malignancies globally. While microsatellite instability (MSI) index has earlier been correlated with survival outcome in gastric cancer patients, the present study aims to construct a risk-stratification model based on immune-related genes in GC patients with varying MSI status. Results: The univariate and multivariate Cox regression analyses identified SEMA7A, NUDT6, SCGB3A1, NPR3, PTH1R, and SHC4 as signature genes, which were used to build the prognostic model for GC patients with microsatellite instability-low (MSI-L) and microsatellite stable (MSS). Whereas, for GC patients with microsatellite instability-high (MSI-H), prognostic model was established with three genes (SEMA6A, LTBP1, and BACH2), based on the univariate and multivariate Cox regression, and Kaplan-Meier survival analyses. Conclusion: The prognostic immune-related gene signature identified in this study may offer new targets for personalized treatment and immunotherapy for GC patients with MSI-H or MSI-L/MSS status. Methods: The Cancer Genome Atlas (TCGA) and ImmPort databases were used to extract expression data and to explore prognostic genes from the immune-related genes (IRGs), respectively. Univariate and multivariate Cox regression analysis were applied to identify IRGs correlated with patient prognosis. The regulatory network between prognostic IRGs and TFs were performed using R software.

基金:
语种:
WOS:
中科院(CAS)分区:
出版当年[2020]版:
大类 | 2 区 医学
小类 | 1 区 老年医学 3 区 细胞生物学
最新[2025]版:
JCR分区:
出版当年[2019]版:
Q1 GERIATRICS & GERONTOLOGY Q2 CELL BIOLOGY
最新[2023]版:
Q2 CELL BIOLOGY Q2 GERIATRICS & GERONTOLOGY

影响因子: 最新[2023版] 最新五年平均[2021-2025] 出版当年[2019版] 出版当年五年平均[2015-2019] 出版前一年[2018版] 出版后一年[2020版]

第一作者:
第一作者单位: [1]Department of Oncology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China. [2]Department of Ultrasound, Aero Space Central Hospital, Beijing 100050, China.
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:1320 今日访问量:0 总访问量:817 更新日期:2025-05-01 建议使用谷歌、火狐浏览器 常见问题

版权所有:重庆聚合科技有限公司 渝ICP备12007440号-3 地址:重庆市两江新区泰山大道西段8号坤恩国际商务中心16层(401121)