Evidence map›Paper›PMID 37969400›Full record

ArticleTranslational cancer research2023

DNA damage repair molecular subtype derived immune signature applicable for the prognosis and immunotherapy response prediction in colon cancer.

Zhen Shang, Ze Wang, Yongtao Zhang, Shanglong Liu

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Article in Translational cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
–field-weighted citation impact, top 52% of its field
1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Zhen ShangMedical Department of Qingdao University, Qingdao, China.
Ze WangDepartment of Emergency Medicine, Qingdao Haici Medical Treatment Group, Qingdao, China.
Yongtao ZhangDepartment of Orthopedics, The Affiliated Hospital of Qingdao University, Qingdao, China.
Shanglong LiuDepartment of Gastrointestinal Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
Affiliated Hospital of Qingdao University · CNHaier Group (China) · CNQingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The DNA damage repair (DDR) pathway is one of the pathways of tumor pathogenesis, but its relationship with the immunophenotype has not been clarified in colon cancer (CC). Methods: We identified the differentially expressed immune-related genes (DEIRGs) between two DDR molecular subtypes, namely, C1 and C2, and used univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct the risk score in the training cohort [n=1,009, a combination of The Cancer Genome Atlas (TCGA) and GSE39582]. Regarding the median risk score as the unified cutoff to classify the patients into high- and low-risk groups. Two independent cohorts (GSE17538, n=232; GSE38832, n=122) were used for external validation of the prognostic value of the risk score. The IMvigor210 cohort (n=348) was used to test the predictive value of the risk score for immunotherapy response. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were performed to discover the underlying mechanism. Immune cell infiltration was quantified by the single sample gene set enrichment analysis (ssGSEA) algorithm. Results: The high-risk group showed significantly reduced overall survival (OS), disease-specific survival (DSS), disease-free survival (DFS), progression-free survival (PFS), and relapse-free survival (RFS) compared to the low-risk group, and the two groups differed significantly in lymphatic invasion, American Joint Committee on Cancer (AJCC) TNM stage, preoperative carcinoembryonic antigen (CEA) level, etc. The enrichment levels of pathways related to colorectal cancer, epithelial-mesenchymal transition (EMT), angiogenesis, hypoxia, P53, TGF-β, KRAS signaling, etc., were upregulated in the high-risk group, but DDR-related pathways were defective in the high-risk group. The immunophenotypes of the high-risk group tended to be desert and excluded, and the risk score of patients who responded to immunotherapy was significantly lower than that of patients who did not respond to immunotherapy. The higher the infiltration levels of gamma delta T cells (γδ T cells), immature dendritic cells, and T follicular helper (Tfh) cells, the more significant adverse impact on the prognosis of CC patients was exhibited and an obviously positive correlation with the risk score was showed. Conclusions: An immune gene risk score associated with the DDR molecular subtype was built and verified herein; that is applicable to the prognosis and immunotherapy response prediction in CC.

Indexed as

Colon cancer (CC)DNA damage repair (DDR)immuneprognosissignature

Identifiers

PMID37969400
PMCPMC10643980
OpenAlexW4387952936

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.