Deciphering the multidimensional impact of expression on cancer prognosis, genetic alterations, and cellular functionality: A comprehensive Pan-cancer analysis.

OBJECTIVES

IGF-binding protein 1 () is a key regulator of insulin-like growth factors, impacting biological processes, including cancer progression and prognosis.

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 levels in LUAD and OV patients resulted in a 30 % and 20 % decrease in survival, respectively. Elevated levels are significantly linked to advanced tumor stage and grade in OV and LUAD, affecting prognostic outcomes. Nomogram models for OV, SKCM, LUAD, and STAD showed 's predictive strength with AUC values ranging from 0.70 to 0.85, indicating its diagnostic potential. Genetic analyses revealed mutations in IGFBP1 in 12 % of STAD cases and 10 % of UCEC cases, indicating significant genetic variation. Immune analysis showed that high expression significantly influenced immune cell infiltration, particularly macrophages and CD8 T cells, thereby affecting survival in LUAD and OV. Functional enrichment and gene set enrichment analysis identified involvement in crucial pathways, such as cell cycle regulation, immune response, and PD-1 signaling, highlighting its biological impact. Additionally, expression delineates distinct molecular and immune subtypes, correlating with specific cancer behaviors and immune patterns.

CONCLUSIONS

These findings highlight IGFBP1's potential as a biomarker and therapeutic target, particularly for immunoregulation and cancer subtype stratification.