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Impact of Extracellular Matrix-Related Genes on the Tumor Microenvironment and Prognostic Indicators in Esophageal Cancer: A Comprehensive Analytical Study.
- Source :
-
Genetics research [Genet Res (Camb)] 2024 Jul 25; Vol. 2024, pp. 3577395. Date of Electronic Publication: 2024 Jul 25 (Print Publication: 2024). - Publication Year :
- 2024
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Abstract
- Esophageal cancer is a major global health challenge with a poor prognosis. Recent studies underscore the extracellular matrix (ECM) role in cancer progression, but the full impact of ECM-related genes on patient outcomes remains unclear. Our study utilized next-generation sequencing and clinical data from esophageal cancer patients provided by The Cancer Genome Atlas, employing the R package in RStudio for computational analysis. This analysis identified significant associations between patient survival and various ECM-related genes, including IBSP, LINGO4, COL26A1, MMP12, KLK4, RTBDN, TENM1, GDF15, and RUNX1. Consequently, we developed a prognostic model to predict patient outcomes, which demonstrated clear survival differences between high-risk and low-risk patient groups. Our comprehensive review encompassed clinical correlations, biological pathways, and variations in immune response among these risk categories. We also constructed a nomogram integrating clinical information with risk assessment. Focusing on the TENM1 gene, we found it significantly impacts immune response, showing a positive correlation with T helper cells, NK cells, and CD8+ T cells, but a negative correlation with neutrophils and Th17 cells. Gene Set Enrichment Analysis revealed enhanced pathways related to pancreatic beta cells, spermatogenesis, apical junctions, and muscle formation in patients with high TENM1 expression. This research provides new insights into the role of ECM genes in esophageal cancer and informs future research directions.<br />Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this article.<br /> (Copyright © 2024 Yinghong Wu et al.)
Details
- Language :
- English
- ISSN :
- 1469-5073
- Volume :
- 2024
- Database :
- MEDLINE
- Journal :
- Genetics research
- Publication Type :
- Academic Journal
- Accession number :
- 39139739
- Full Text :
- https://doi.org/10.1155/2024/3577395