IGF system genes as colorectal cancer biomarkers in Puerto Rico

Introduction: Colorectal cancer (CRC) disproportionately affects Hispanic/Latino (H/L) populations; however molecular biomarkers remain understudied in this population. While individual IGF-axis have been explored as CRC biomarkers, comprehensive transcriptomic evaluation of the complete IGF system, including IGFs, receptors, and binding proteins, for stage-specific detection remains limited, particularly for H/L living in Puerto Rico. This study aimed to characterize transcriptomic dysregulation of the IGF system in CRC and evaluate individual genes and multi-gene signatures as diagnostic biomarkers to discriminate tumor from normal tissue and differentiate early-stage from advanced-stage disease. Methods: RNA was extracted from 28 tissue samples (15 CRC cases, 13 controls) from the Puerto Rico Familial Colorectal Cancer Registry (PURIFICAR) using QIAGEN RNeasy Kit. RNA sequencing was performed on Illumina NextSeq 550. Differential gene expressions were analyzed using DESeq2 (adjusted p<0.05, log2FC>1). Pathway enrichment was analyzed using the Reactome database. Logistic regression models (crude and age and BMI-adjusted) estimated odds ratios for gene associations, overall and by CRC stage. ROC analysis determined diagnostic performance: AUC, sensitivity, and specificity. An IGF system multi-gene signature score was developed using the uncorrelated differentially expressed IGF genes (IGF1, IGF2, IGFL2, IGFL4). Significance was set at p<0.05. Results: Our results show dysregulation of the IGF system across CRC stages, with IGF2 and IGF1R consistently upregulated and stage-specific IGFBP expression patterns. The multi-gene signature demonstrated good CRC discrimination (AUC: 0.831, p=0.002), with superior performance in advanced disease (AUC: 0.894, p=0.002). Among individual genes, IGFBP5 showed highest crude accuracy (AUC: 0.856, p=0.020), which improved when adjusted for age and BMI (AUC: 0.964, 92.3% sensitivity/specificity, p<0.001). IGFL4 showed excellent discrimination in advanced-stage models (adjusted AUC: 1.00, OR: 6.03, p<0.001). Early-stage detection was particularly strong for IGFBP5 and IGFL2 (adjusted AUC>0.94). Enriched pathways included IGF1R-SHC signaling and platelet activation in advanced disease. Conclusion: This transcriptomic analysis identifies IGFBP5 and a multi-gene IGF signature as potential stage-specific biomarker candidates for CRC in H/L in Puerto Rico. Further validation in larger cohorts is warranted to determine whether IGF system genes can improve CRC detection.