Identified VCAM1 as prognostic gene in gastric cancer by co-expression network analysis

The diffuse gastric cancer (DGC) is a malignant tumor distinct from intestinal gastric cancer (IGC). This study aims to identify genetic variances and potential diagnostic and therapeutic approaches for diverse types of gastric cancer utilizing an extensive dataset. Data from RNA sequencing and clinical pathological details were acquired from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) dataset. Co-expression gene modules were constructed via Weighted Gene Co-Expression Network Analysis (WGCNA), followed by deciphering gene functions and protein-protein interaction networks within significantly associated modules. In total, analysis was conducted on 56,753 genes from 247 individuals with gastric cancer. Particularly, 621 genes from the green module exhibited strong associations with the Lauren type of gastric cancer. The prominent genes in the green module showed enrichment in processes such as signal transduction, immune response, and the positive regulation of GTPase activity. Noteworthy among these, VCAM1 was identified as the central gene linked to patients' prognosis. Moreover, 72 gastric cancer specimens were collected from The First Affiliated Hospital of University of Science and Technology of China. Immunohistochemical analysis demonstrated a significantly higher expression of VCAM1 in DGC compared to IGC (p = 0.019). Furthermore, it was confirmed that VCAM1 expression serves as a prognostic indicator for patients with DGC (p = 0.002), a correlation not observed in IGC (p = 0.760). In conclusion, this study identifies VCAM1 as a promising diagnostic and prognostic factor, suggesting novel avenues for diagnostic and therapeutic approaches in gastric cancer.

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Publication Details

Journal
Discover Oncology
Published
2024-12-18
DOI
https://doi.org/10.1007/s12672-024-01603-y
Citations
2
Primary Topic
Gastric Cancer Management and Outcomes
Type
article
Field-Weighted Citation Impact
0.84
Controls
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article

Identified VCAM1 as prognostic gene in gastric cancer by co-expression network analysis

Wenjun Li, Hong Gao, Jianjun Liu
2 citations
Discover Oncology
Gastric Cancer Management and Outcomes
0.84
article

Identified VCAM1 as prognostic gene in gastric cancer by co-expression network analysis

Wenjun Li, Hong Gao, Jianjun Liu
article en
2 citations

Abstract

The diffuse gastric cancer (DGC) is a malignant tumor distinct from intestinal gastric cancer (IGC). This study aims to identify genetic variances and potential diagnostic and therapeutic approaches for diverse types of gastric cancer utilizing an extensive dataset. Data from RNA sequencing and clinical pathological details were acquired from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) dataset. Co-expression gene modules were constructed via Weighted Gene Co-Expression Network Analysis (WGCNA), followed by deciphering gene functions and protein-protein interaction networks within significantly associated modules. In total, analysis was conducted on 56,753 genes from 247 individuals with gastric cancer. Particularly, 621 genes from the green module exhibited strong associations with the Lauren type of gastric cancer. The prominent genes in the green module showed enrichment in processes such as signal transduction, immune response, and the positive regulation of GTPase activity. Noteworthy among these, VCAM1 was identified as the central gene linked to patients' prognosis. Moreover, 72 gastric cancer specimens were collected from The First Affiliated Hospital of University of Science and Technology of China. Immunohistochemical analysis demonstrated a significantly higher expression of VCAM1 in DGC compared to IGC (p = 0.019). Furthermore, it was confirmed that VCAM1 expression serves as a prognostic indicator for patients with DGC (p = 0.002), a correlation not observed in IGC (p = 0.760). In conclusion, this study identifies VCAM1 as a promising diagnostic and prognostic factor, suggesting novel avenues for diagnostic and therapeutic approaches in gastric cancer.

Discover OncologyVol. 15(1)
University of Science and Technology of China (CN), Anhui Provincial Hospital (CN)
Openalex Percentile: Top 22%
Gastric Cancer Management and Outcomes
0.84
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