BACKGROUND: GNL2, a nuclear protein, is involved in ribosome production and cell cycle regulation. However, its expression and function in different types of tumors are not well understood. Comprehensive studies across multiple cancer types are needed to assess the potential of GNL2 as a diagnostic, prognostic, and immunological marker. METHODS: mRNA expression data, copy number alteration threshold data, masked copy number segmentation data, and DNA methylation 450 K data from The Cancer Genome Atlas (TCGA) pan-cancer cohort were obtained from the Firehose database. Additional data, including miRNA, The Cancer Proteome Atlas (TCPA), mutation data, and clinical information, were sourced from the University of California Santa Cruz (UCSC) Xena database. The cBioPortal database facilitates the examination of GNL2 mutation frequency, location, and 3D structure in the TCGA database. Gene Expression Omnibus (GEO) data verified the transcriptome level expression in the TCGA cohort. Protein expression levels were analyzed via the Human Protein Atlas (HPA) database and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Gene set enrichment analysis (GSEA) was employed to investigate the biological role of GNL2 across cancers. Multiple immune infiltration algorithms from the TIMER2.0 database were utilized to examine the correlation between GNL2 expression and the tumor immune microenvironment. The transcriptome-wide immune infiltration results were validated using 72 single-cell datasets from the Tumor Immune Single-cell Hub (TISCH) database. Pan-cancer survival maps were constructed, and GNL2 expression in different molecular subtypes across cancers was examined. The relationship between GNL2 and drug resistance was investigated using data from CellMiner, GDSC, and CTRP. The Comparative Toxicogenomics Database (CTD) was used to identify chemicals affecting GNL2 expression. RESULTS: GNL2 is located primarily in the nucleus, and its expression is regulated mainly through somatic copy number alteration (SCNA) and aberrant DNA methylation, according to TCGA data. Database analysis and immunohistochemical results from clinical samples revealed high GNL2 expression in most tumors, which was correlated with diagnostic significance. High GNL2 expression often indicates a poor prognosis with pan-cancer prognostic value. Gene set enrichment analysis (GSEA) suggested that GNL2 is involved in tumor development through cell proliferation-related pathways. GNL2 expression is correlated with the expression of immune-related genes and the infiltration levels of multiple immune cells. The relationships between GNL2 and various drugs and chemicals were examined, revealing its influence on drug sensitivity and identifying five chemicals countering GNL2-mediated pro-cancer effects. CONCLUSION: Comprehensive bioinformatics analysis of GNL2 in pan-cancer tissues, combined with experimental validation, elucidated the pan-cancer expression pattern of GNL2, determined its diagnostic and prognostic value, and explored the biological functions of GNL2. GNL2 may be involved in the regulation of cell cycle progression and remodeling of the tumor microenvironment and is associated with poor prognosis as a risk factor in most tumors. The potential of GNL2-based cancer therapies is emphasized, assisting in predicting the response to chemotherapy.