Construction of a Prognostic Model for Lysosome-dependent Cell Death in Gastric Cancer Based on Single-cell RNA-seq and Bulk RNA-seq Data.

Objective: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC).

Methods: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay.

Results: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including , , , and , were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. and exhibited predominant expression in macrophage species, whereas evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with inhibited proliferation and migration in GC cells.

Conclusion: , , , and are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.