Identification and validation of extracellular matrix-related genes in the progression of gastric cancer with intestinal metaplasia.

Abstract

Background: Gastric cancer (GC) is a highly lethal malignancy with a high incidence and mortality rate globally. Its development follows the Correa model, with intestinal metaplasia (IM) being a critical precursor to GC. However, the mechanisms underlying IM progression to GC remain unclear. This study explored extracellular matrix (ECM)-related gene changes during IM progression to GC, aiming to identify biomarkers that could improve early diagnosis and treatment strategies for GC, ultimately enhancing patient outcomes.

Aim: To analyze transcriptome sequencing data, molecular biomarkers that can predict GC risk and monitor IM progression can be identified, providing new insights and strategies for preventing IM-GC transformation.

Methods: Weighted gene co-expression network analysis served for confirming gene modules. Upregulated ECM-related genes were further tested using univariate Cox regression and least absolute shrinkage and selection operator analysis to select hub genes and construct a survival analysis model. The intestinal cell model was established by stimulating GES-1 cells with chenodeoxycholic acid.

Results: Weighted gene co-expression network analysis identified 1709 differentially expressed genes from the GSE191275 dataset, while The Cancer Genome Atlas stomach adenocarcinoma revealed 4633 differentially expressed genes. The intersection of these datasets identified 71 upregulated and 171 downregulated genes, which were enriched in ECM-related pathways. Univariate Cox regression analysis identified six genes with prognostic significance, and least absolute shrinkage and selection operator regression pinpointed secreted protein acidic and rich in cysteine (SPARC) and SERPINE1 as non-zero coefficient genes. A prognostic model integrating clinical tumor node metastasis staging, age, SERPINE1, and SPARC was constructed. Immunohistochemistry analysis confirmed an increasing expression of SPARC protein from normal gastric mucosa (-), to IM (+- to +), and to GC (+ to ++), with significant differences (P < 0.05). Western blot analysis demonstrated significantly higher SPARC expression in induced intestinal cells compared to GES-1. Furthermore, after SPARC knockdown in the human GC cell line HGC27, cell counting kit-8 and colony formation assays showed a reduction in cell proliferative ability, while the wound healing assay revealed impaired cell migration capacity.

Conclusion: Comprehensive analysis suggested that a model incorporating clinical tumor node metastasis staging, age, and SPARC/SERPINE1 expression served as a prognostic predictor for GC. Moreover, elevated SPARC expression in IM and GC suggests its potential as a proper biomarker to detect GC in early stage and as a novel therapeutic target, guiding clinical applications.