Abstract
BACKGROUND: Since the pathophysiology of clear cell renal cell carcinoma (ccRCC) was still unknown, finding novel therapeutic targets to support current treatment approaches was crucial. METHODS: We conducted an RNA-Sequencing analysis using data from the TCGA-KIRC dataset, with our own clinical data serving as validation. Kaplan–Meier survival curves, univariate and multivariate studies of overall survival, and differential expression analysis were all used. Furthermore, we explored the correlation between LGALS1 (Galectin-1) and clinical characteristics in ccRCC patients by leveraging proteomics data from the CPTAC analysis. Additionally, the Single-cell RNA-Sequencing (scRNA-Seq) analysis elucidated the cellular landscape of LGALS1 using the GSE159115 database, complemented by pathway enrichment analysis via GO and KEGG datasets. Lastly, we performed an immunohistochemistry (IHC) analysis on ccRCC tissue microarrays and scored the staining intensity. While p < 0.05 was used for other analyses, p < 0.1 was deemed significant in multivariate analysis. RESULTS: As shown in TCGA and confirmed in our clinical data, higher LGALS1 expression in ccRCC was associated with a bad prognosis. Proteomics analysis in the CPTAC dataset revealed that LGALS1 levels were statistically significant across different grade and stage groups of patients. The high expression was confirmed on the IHC chip, with tumor tissue displaying a higher staining intensity score. Additionally, scRNA-Seq analysis identified that the differential expression of LGALS1 primarily occurred in endothelial and epithelial cells, along with associated signaling pathways. CONCLUSIONS: We performed a multi-omics analysis using transcriptomics, proteomics, single-cell omics, and our clinical data, confirming LGALS1 as a possible target for ccRCC.