Analysis of prognostic features associated with extracellular matrix and lymph node metastasis in colorectal cancer.
- 1Department of Gastroenterology, Fujian Provincial Geriatric Hospital, Fuzhou, China.
- 2Department of Gastrointestinal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Abstract
Extracellular matrix (ECM) leads to worse outcomes in lymph node metastases (LNM) in colorectal cancer (CRC). However, the link between ECM-related genes (ECMRGs) and LNM in CRC is poorly understood. This study aims to create a prognostic model related to ECM and LNM for CRC patients, to optimize prognostic assessment for CRC patients. The Cancer Genome Atlas (TCGA)-CRC and GSE38832 datasets, together with 84 curated ECMRGs, served as the analytical basis. Candidate genes were screened by intersecting LNM-associated differentially expressed genes (DEGs) with key module genes identified through weighted gene co-expression network analysis (WGCNA). Prognostic genes were subsequently determined via Cox regression analyses to establish a risk model. An individualized nomogram was developed by incorporating the risk score with clinicopathological variables. Additional analyses included gene set enrichment analysis (GSEA), immune microenvironment profiling, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) validation in clinical specimens. Six genes-NKAIN4, VAX2, CILP2, MMP17, GRP, and RGCC-were identified as independent prognostic factors from 28 ECM- and LNM-related candidates. The risk model showed reliable performance in predicting CRC patient survival. A nomogram integrating risk score, age, pathological N stage, and pathological M stage achieved satisfactory prognostic accuracy. ECM-receptor interaction and nitrogen metabolism pathways were significantly enriched across risk strata. Among 12 differentially infiltrated immune cell populations, GRP was negatively correlated with neutrophil abundance, while RGCC showed the strongest positive correlation with plasmacytoid dendritic cells. RT-qPCR confirmed significant upregulation of NKAIN4, CILP2, GRP, and RGCC in CRC-LNM versus CRC-non-lymph node metastasis (NLNM) specimens. Six prognostic genes (NKAIN4, VAX2, CILP2, MMP17, GRP and RGCC) related to ECM and LNM in CRC were identified, based on which a prognostic model with outstanding predictive ability was constructed, offering a fresh reference for prognostic risk assessment of CRC patients.
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BibTeX
@article{chen2026analysis,
title = {{Analysis of prognostic features associated with extracellular matrix and lymph node metastasis in colorectal cancer.}},
author = {Xuefang Chen and Feng Qiu and Rujie Peng and Zhihua Chen and Chengchao Zheng and Yuling Shen and Qingxin Zeng},
journal = {Translational cancer research},
year = {2026},
month = sep,
doi = {10.21037/tcr-2026-0895},
url = {https://europepmc.org/article/MED/42997740},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Analysis of prognostic features associated with extracellular matrix and lymph node metastasis in colorectal cancer.
AU - Xuefang Chen
AU - Feng Qiu
AU - Rujie Peng
AU - Zhihua Chen
AU - Chengchao Zheng
AU - Yuling Shen
AU - Qingxin Zeng
PY - 2026
DA - 2026/09/29
JO - Translational cancer research
DO - 10.21037/tcr-2026-0895
UR - https://europepmc.org/article/MED/42997740
AB - Extracellular matrix (ECM) leads to worse outcomes in lymph node metastases (LNM) in colorectal cancer (CRC). However, the link between ECM-related genes (ECMRGs) and LNM in CRC is poorly understood. This study aims to create a prognostic model related to ECM and LNM for CRC patients, to optimize prognostic assessment for CRC patients. The Cancer Genome Atlas (TCGA)-CRC and GSE38832 datasets, together with 84 curated ECMRGs, served as the analytical basis. Candidate genes were screened by intersecting LNM-associated differentially expressed genes (DEGs) with key module genes identified through weighted gene co-expression network analysis (WGCNA). Prognostic genes were subsequently determined via Cox regression analyses to establish a risk model. An individualized nomogram was developed by incorporating the risk score with clinicopathological variables. Additional analyses included gene set enrichment analysis (GSEA), immune microenvironment profiling, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) validation in clinical specimens. Six genes-NKAIN4, VAX2, CILP2, MMP17, GRP, and RGCC-were identified as independent prognostic factors from 28 ECM- and LNM-related candidates. The risk model showed reliable performance in predicting CRC patient survival. A nomogram integrating risk score, age, pathological N stage, and pathological M stage achieved satisfactory prognostic accuracy. ECM-receptor interaction and nitrogen metabolism pathways were significantly enriched across risk strata. Among 12 differentially infiltrated immune cell populations, GRP was negatively correlated with neutrophil abundance, while RGCC showed the strongest positive correlation with plasmacytoid dendritic cells. RT-qPCR confirmed significant upregulation of NKAIN4, CILP2, GRP, and RGCC in CRC-LNM versus CRC-non-lymph node metastasis (NLNM) specimens. Six prognostic genes (NKAIN4, VAX2, CILP2, MMP17, GRP and RGCC) related to ECM and LNM in CRC were identified, based on which a prognostic model with outstanding predictive ability was constructed, offering a fresh reference for prognostic risk assessment of CRC patients.
SN - 2218-676X
SN - 2219-6803
ER -