Saleh Rawdhah M, Mansour Reham, Almaghrbi Heba A, Kumar S Udhaya, Surendranath Anju, Al Moustafa Ala-Eddin, Alsamman Alsamman M, Zayed Hatem
Department of Biomedical Sciences, College of Health and Sciences, Qatar University, QU Health, Doha, Qatar.
Department of Medicine, Division Endocrinology, Diabetes and Metabolism, Baylor College of Medicine, Houston 77030 TX, USA.
Gene. 2025 Sep 10;964:149594. doi: 10.1016/j.gene.2025.149594. Epub 2025 May 24.
Colorectal adenocarcinoma (COAD) is among the most common causes of cancer-related death globally. Early detection and targeted therapy depend on identifying key molecular biomarkers that drive tumor progression. The molecular heterogeneity of COAD demands robust computational strategies to improve the accuracy of biomarker discovery.
We developed and implemented a comprehensive, multi-step bioinformatics and statistical pipeline to systematically prioritize clinically relevant biomarkers in COAD. This pipeline integrated differential gene expression analysis, protein-protein interaction (PPI) network construction, and functional enrichment analysis to identify key hub genes associated with tumor progression. We subsequently applied principal component analysis (PCA) and overall survival modeling to evaluate the diagnostic and prognostic relevance of these candidates. Receiver operating characteristic (ROC) curve analysis was used to assess their sensitivity and specificity. Finally, experimental validation of the prioritized hub genes was conducted via qPCR across three CRC cell lines (LoVo, HCT-116, and HT-29), confirming their upregulation and supporting their clinical potential.
Our integrative pipeline prioritized five key hub genes (CDH3, CXCL1, MMP1, MMP3, and TGFBI) as significantly upregulated in COAD tissues compared to normal controls. Functional enrichment analysis linked these genes to extracellular matrix degradation, epithelial-mesenchymal transition (EMT), inflammatory signaling, and tumor invasion, underscoring their roles in key oncogenic processes. Survival analysis revealed varying degrees of association with patient prognosis, most notably for CXCL1. Diagnostic performance, assessed by ROC analysis, yielded moderate AUC values (0.669-0.692), supporting their potential as biomarkers. Finally, qPCR validation across three CRC cell lines confirmed robust upregulation of all five genes, reinforcing their biological relevance in COAD progression.
Our study establishes a reproducible, integrative bioinformatics and statistical framework for the systematic identification of clinically actionable biomarkers in CRC. The five hub genes prioritized (CDH3, CXCL1, MMP1, MMP3, and TGFBI) demonstrated consistent diagnostic and prognostic value, offering a solid basis for the development of non-invasive molecular diagnostics and contributing to precision oncology.
结直肠癌（COAD）是全球癌症相关死亡的最常见原因之一。早期检测和靶向治疗依赖于识别驱动肿瘤进展的关键分子生物标志物。COAD的分子异质性需要强大的计算策略来提高生物标志物发现的准确性。
我们开发并实施了一个全面的多步骤生物信息学和统计流程，以系统地对COAD中临床相关的生物标志物进行优先级排序。该流程整合了差异基因表达分析、蛋白质-蛋白质相互作用（PPI）网络构建和功能富集分析，以识别与肿瘤进展相关的关键枢纽基因。随后，我们应用主成分分析（PCA）和总生存建模来评估这些候选物的诊断和预后相关性。采用受试者工作特征（ROC）曲线分析来评估它们的敏感性和特异性。最后，通过qPCR在三种结直肠癌细胞系（LoVo、HCT-116和HT-29）中对优先排序的枢纽基因进行实验验证，证实了它们的上调并支持了它们的临床潜力。
我们的综合流程将五个关键枢纽基因（CDH3、CXCL1、MMP1、MMP3和TGFBI）列为与正常对照相比在COAD组织中显著上调的基因。功能富集分析将这些基因与细胞外基质降解、上皮-间质转化（EMT）、炎症信号传导和肿瘤侵袭联系起来，强调了它们在关键致癌过程中的作用。生存分析揭示了与患者预后的不同程度关联，最显著的是CXCL1。通过ROC分析评估的诊断性能产生了中等的AUC值（0.669 - 0.692），支持了它们作为生物标志物的潜力。最后，在三种结直肠癌细胞系中的qPCR验证证实了所有五个基因的强烈上调，加强了它们在COAD进展中的生物学相关性。
我们的研究建立了一个可重复的、综合的生物信息学和统计框架，用于系统识别结直肠癌中具有临床可操作性的生物标志物。优先排序的五个枢纽基因（CDH3、CXCL1、MMP1、MMP3和TGFBI）显示出一致的诊断和预后价值，为开发非侵入性分子诊断提供了坚实基础，并有助于精准肿瘤学的发展。
