Unveiling the prognostic role of FABP4 in early-onset colorectal cancer through big data analysis and preliminary clinical validation
Year: 2026
Type: article
Abstract: Background: Early-onset colorectal cancer (EOCRC), characterized by greater aggressiveness and advanced stage at diagnosis, is increasing globally. This study aimed to identify suitable prognostic biomarkers for EOCRC. Methods: Gene expression and clinical data from TCGA and GEO (GSE39582, GSE17536, and GSE17537) datasets were analyzed. Differential expression, univariate and multivariate Cox regression, and correlation analyses were performed. Immune status was evaluated using ESTIMATE and CONSENSUS TME algorithm. Immunotherapy and chemotherapy response was predicted via the TIDE and oncoPredict algorithm, respectively. Candidate signatures were validated in clinical samples from three EOCRC patients using qRT-PCR. Results: Fatty Acid Binding Protein 4 (FABP4) was identified as an independent prognostic factor for poor overall survival in EOCRC patients. A prognostic model based on FABP4 demonstrated good predictive accuracy for 1-, 3-, and 5-year survival in both training and validation sets. The high-FABP4 expression was negative correlated TIDE scores, suggesting EOCRC patients with high expression of FABP4 maybe benefit from immunotherapy. Furthermore, 66 chemotherapeutic agents showed significant negative correlations with FABP4 expression. Validation in patient samples confirmed the coordinated upregulation of FABP4 and its associated genes ADIPOQ and IGF1. Conclusion: FABP4 is a promising independent prognostic biomarker for EOCRC, associated with an immunosuppressive microenvironment and maybe a potential guidance for immunotherapy and chemotherapy selection. Further multi-center prospective studies are warranted to validate its clinical utility.
Source: Frontiers in Oncology
Authors: Yu Wu, Weiwei Zou, Shengjun Zhang, Lipeng Zhao, Shaohua He, Fan Yao, Peilin Qing, Yixin Li, Jie Li, Xiao-Liang Xing
Institution: Hunan University of Medicine
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,801
Awards: G147444029, G6370988745
OpenAlex ID: W7123399852
