Objective: To identify lipid metabolism associated biomarkers in colorectal cancer (CRC).

Methods: To refine our list of candidate genes, we utilized the Molecular Complex Detection (MCODE) plug-in within Cytoscape software and performed protein-protein interaction (PPI) network analysis to extract hub genes centrally located within the networks, which potentially possess important regulatory functions. Hub gene-associated miRNAs and transcription factors (TFs) were analyzed using miRNet. Immunohistochemical staining was employed to verify the expression levels of hub genes in clinical CRC tissues. Concurrently, cellular experiments were designed to explore the functional roles of the hub gene DHCR7 at the cellular level, providing scientific evidence for the precision treatment of CRC.

Results: A total of 9008 differentially expressed genes (DEGs) were identified between CRC and control samples. Gene Set Enrichment Analysis (GSEA) revealed that these DEGs were mainly enriched in biological processes such as myogenesis, adipogenesis, oxidative phosphorylation, and fatty acid metabolism. Using Weighted Gene Co-expression Network Analysis (WGCNA), we found that the pink and yellow modules were most significantly associated with CRC. Cytoscape analysis identified six hub genes (DHCR7, FABP4, FASN, FAXDC2, PTGIS, SLC27A6). Their diagnostic performance was verified in the external GSE23878 dataset. Clinical studies showed a downregulation trend in the expression of FAXDC2 and PTGIS in CRC tissue samples, while FASN and DHCR7 were up-regulated in colon cancer tissues. However, the expression trend of FABP4 was inconsistent with previous bioinformatics predictions. Further cellular experimental results demonstrated that DHCR7 knockdown significantly inhibited CRC cell proliferation and induced apoptosis, which strongly supported the previous bioinformatics analysis.

Conclusion: Our research successfully identified six hub genes in CRC through a series of rigorous analyses and experimental validations. These findings provide important molecular basis for further investigation into the pathogenesis and progression of CRC.

Keywords: CRC; hub gene; lipid metabolism-related genes.

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目标： 识别与结直肠癌（CRC）相关的脂质代谢生物标志物。

方法： 为了精炼候选基因列表，我们使用了Cytoscape软件中的Molecular Complex Detection (MCODE) 插件，并进行了蛋白质-蛋白质相互作用（PPI）网络分析以提取位于网络中心的枢纽基因，这些基因可能具有重要的调节功能。利用miRNet分析与枢纽基因相关的miRNA和转录因子(TFs)。使用免疫组化染色验证了临床CRC组织中枢纽基因的表达水平。同时设计了细胞实验来探索DHCR7基因在细胞层面的功能作用，为CRC的精准治疗提供科学依据。

结果： 共鉴定了9008个差异表达基因（DEGs）存在于CRC样本和对照样本之间。Gene Set Enrichment Analysis (GSEA) 显示这些DEGs主要富集在肌生成、脂肪细胞分化、氧化磷酸化和脂肪酸代谢等生物学过程中。通过加权基因共表达网络分析（WGCNA），我们发现粉色和黄色模块与CRC关联最为显著。Cytoscape 分析鉴定了六个枢纽基因 (DHCR7, FABP4, FASN, FAXDC2, PTGIS, SLC27A6)。它们的诊断性能在外部分析集GSE23878中得到了验证。临床研究表明，CRC组织样本中的FAXDC2和PTGIS表达下调，而结肠癌组织中的FASN 和 DHCR7 表达上调。然而，FABP4 的表达趋势与之前的生物信息学预测不一致。进一步的细胞实验结果表明，DHCR7 敲低显著抑制了CRC 细胞增殖并诱导了凋亡，这强烈支持了先前的生物信息学分析。

结论： 通过一系列严格的分析和实验验证，我们的研究成功地在CRC中鉴定了六个枢纽基因。这些发现为进一步探讨 CRC 的发病机制和进展提供了重要的分子基础。

关键词： CRC；枢纽基因；脂质代谢相关基因。

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