Multi-omics Profiling and Experimental Validation Identify APLNR as a Prognostic Biomarker Involved in Epithelial-Mesenchymal Transition and Immune Modulation in Gastric Cancer

Background : Gastric cancer (GC) is a leading cause of global cancer mortality, with limited treatment options for advanced disease, underscoring the urgent need for novel biomarkers and therapeutic targets. The Apelin Receptor (APLNR), a G protein-coupled receptor, has been implicated in tumor progression, yet its comprehensive role in GC remains poorly characterized. Methods : We conducted an integrated multi-omics analysis using TCGA, GTEx, and GEO datasets to characterize APLNR expression in GC. Its diagnostic and prognostic values were assessed via receiver operating characteristic (ROC) and Kaplan-Meier (KM) analyses. Functional enrichment (GO, KEGG, GSEA) was performed to identify APLNR-associated pathways. Single-sample gene set enrichment analysis (ssGSEA) and Spearman correlations were used to investigate the relationship between APLNR and the immune microenvironment as well as epithelial-mesenchymal transition (EMT). Key bioinformatic findings were experimentally validated in clinical GC samples and cell lines using qPCR, Western blot, and immunohistochemistry (IHC). Results: APLNR was significantly upregulated in GC tissues compared to normal tissues, demonstrating high diagnostic potential (AUC = 0.921). Elevated APLNR expression was associated with poorer overall survival (OS) and progression-free survival (PFS), particularly in female patients and those with stage II disease. Functional analyses linked APLNR to extracellular matrix remodeling, PI3K-Akt signaling, and EMT pathways. High APLNR expression correlated positively with the infiltration of multiple immune cell types, the expression of various immune checkpoints (e.g., PD-L1, CTLA4), and EMT markers. KM analysis suggested that GC patients with high APLNR expression may derive greater survival benefit from anti-PD-L1/CTLA-4 immunotherapy. Experimental validation confirmed APLNR overexpression at both mRNA and protein levels in GC. IHC further revealed significant positive correlations between APLNR protein levels and those of PD-L1 and N-cadherin. Conclusions: Our findings establish APLNR as a promising diagnostic and prognostic biomarker in GC. Its association with an immunosuppressive tumor microenvironment and EMT activation suggests its potential as a predictor of immune checkpoint inhibitor response and a node in aggressive tumor biology. Future functional studies are warranted to elucidate APLNR’s mechanistic role in GC pathogenesis and validate its therapeutic potential.