Extracellular Matrix Organization Genes Predict the Prognosis and Immune Microenvironment in Stomach Adenocarcinoma

Abstract Background Extracellular matrix (ECM) dysregulation is crucial for malignant progression of human cancer. However, its effect on immune microenvironment of stomach adenocarcinoma (STAD) is unclarified. Method The Cancer Genome Atlas (TACG) database was utilized to retrieve STAD gene expression profiles and clinical information. Genes significantly associated with prognosis ( P < 0.05) were assessed by univariate Cox regression. The Gene Ontology (GO) enrichment and protein-protein interaction (PPI) network were performed to identify the critical bioprocesses. Multivariate Cox regression and the least absolute shrinkage and selection operator (LASSO) were utilized to identify independent prognostic signature. Differentiating between clusters according to ECM organization gene expression (ECMOGs) was achieved by unsupervised clustering analysis. The biological characteristics in the ECMOGs clusters were determined. The tumor microenvironment (TME) features, including immunization checkpoint block (ICB) response, immune checkpoint genes, and tumor-infiltrating lymphocytes, were predicted between the distinct clusters. Results A total of 948 genes were identified as STAD prognostic genes. ECM organization was found to be the most significant bioprocesses these prognostic genes enriched in. Twelve ECMOGs were considered to be linked to the development of STAD. Three ECMOGs ( ADAMTS1 , LOX , NFKB2 ) were determined as independent predictor signatures for risk scoring. Based on twelve ECMOGs expression, the 348 patients were divided into cluster 1 and 2. Patients in cluster 1 had the higher levels of the detected ECMOGs and the risk score, as well as the poor prognosis. Cluster 1 was distinguished by its higher ICB response as well as the infiltrated M2 macrophage. Conclusion This study demonstrated that ECMOGs were associated with a bad prognosis partly by affecting the immune microenvironment, which could be the potential biomarker for the diagnosis and prognosis, and therapeutic target in STAD.