Abstract
INTRODUCTION: The relationship between the expression of opioid-associated receptors and cancer outcomes is complex and varies among studies. METHODS: This study focused on six opioid-related receptors (OPRM1, OPRD1, OPRK1, OPRL1, OGFR, and TLR4) and their impact on cancer patient survival. Bioinformatics analysis was conducted on 33 cancer types from The Cancer Genome Atlas database to examine their expression, clinical correlations, mechanisms in the tumor microenvironment, and potential for immunotherapy. Due to significantly lower expression of OPRM1, OPRD1, and OPRK1 compared to OGFR and TLR4, the analysis concentrated on the latter two genes. RESULTS: OGFR was highly expressed in 16 tumor types, while TLR4 showed low expression in 13. Validation from external samples, the Gene Expression Omnibus, and the Human Protein Atlas supported these findings. The diagnostic value of these two genes was demonstrated using the Genotype-Tissue Expression database. Univariate Cox regression models and Kaplan-Meier curves confirmed OGFR's impact on prognosis in a cancer type-specific manner, while high TLR4 expression was associated with a favorable prognosis. Analysis of the tumor microenvironment using a deconvolution algorithm linked OGFR to CD8+ T cells and TLR4 to macrophages. Single-cell datasets further validated this correlation. In 25 immune checkpoint blockade treatment cohorts, TLR4 expression showed promise as an immunotherapy efficacy predictor in non-small cell lung cancer, urothelial carcinoma, and melanoma. CONCLUSION: In a pan-cancer analysis of 33 tissues, OGFR was consistently highly expressed, while TLR4 had low expression. Both genes have diagnostic and prognostic significance and are linked to immune cells in the tumor microenvironment. TLR4 has potential as an immunotherapeutic response marker.