Deciphering the multidimensional impact of

Objectives: IGF-binding protein 1 ( Materials and methods: This study investigates genetic alterations affecting IGFBP1 expression in tumors using data from The Cancer Genome Atlas (TCGA) PanCancer Atlas via cBioPortal. We analyzed samples from 32 cancer types for mutation sites, including deep deletions, amplifications, and mutations. RNA-seq data were normalized using log2(value + 1). Statistical analyses, including survival outcomes, were conducted using R packages like ggplot2, stats, and car. Kaplan-Meier survival curves and log-rank tests assessed overall survival (OS) and progression-free survival (PFS). Univariate Cox regression was used to develop nomogram models for OS. Functional consequences of IGFBP1 mutations were explored through protein structure, stability, and IGF interaction analyses. Protein-protein interaction networks and functional enrichment were analyzed using GEPIA2, STRING, and Cytoscape. Gene Ontology (GO), KEGG, and Gene Set Enrichment Analysis (GSEA) provided insights into affected biological pathways. Results: Pan-cancer analysis revealed diverse expression patterns, including significant upregulation in cutaneous melanoma (SKCM) and downregulation in lung adenocarcinoma (LUAD) and stomach adenocarcinoma (STAD). Specifically, elevated IGFBP1 expression in SKCM patients led to a 25 % improvement in 5-year survival. In contrast, higher Conclusions: These findings highlight IGFBP1's potential as a biomarker and therapeutic target, particularly for immunoregulation and cancer subtype stratification.