结直肠腺癌（COAD）是一种常见的临床癌症，患病率和死亡率较高，其发病机制和治疗方法仍未成熟。许多研究已经证明了胆汁酸在肿瘤发展中的参与程度，然而其在肿瘤微环境（TME）中的代谢潜力仍未研究。本研究共获取了与胆汁酸代谢有关的481个基因，并使用最小绝对收缩和选择算子（LASSO）回归分析构建了基于癌症基因组图谱的COAD风险模型。并使用基因表达杂质库验证了结果。模型的预测性能通过列线图、主成分分析和受试者工作特征曲线得到验证。接下来，我们基于训练集分析了高风险组和低风险组之间的差异，包括临床特征、免疫细胞浸润、免疫相关功能、化疗药物敏感性和免疫治疗效果。另外，我们构建了一个蛋白质相互作用网络以筛选目标基因，并对它们在不同免疫细胞分布方面进行了进一步研究。在正常和肿瘤结肠组织之间获得了234个与胆汁酸相关的差异表达基因，其中111个基因在肿瘤样本中上调，123个基因在肿瘤样本中下调。借助LASSO逻辑回归算法，我们构建了一个胆汁酸风险评分模型，包括12个基因：CPT2、SLCO1A2、CD36、ACOX1、CDKN2A、HADH、GABRD、LEP、TIMP1、MAT1A、SLC6A15和PPARGC1A。这个模型在GEO-COAD数据集中得到了验证。年龄和风险评分被观察到是COAD患者的独立预后因素。与COAD中与胆汁酸代谢相关的基因密切相关的是胆汁分泌、肠道转运、类固醇和脂肪酸代谢。此外，高风险组对奥沙利铂的敏感性高于低风险组。最后，筛选得到的三个目标基因与免疫细胞密切相关。我们确定了一组与胆汁酸代谢相关的12个基因（CPT2、SLCO1A2、CD36、ACOX1、CDKN2A、HADH、GABRD、LEP、TIMP1、MAT1A、SLC6A15和PPARGC1A），并使用LASSO回归分析构建了一个胆汁酸风险评分模型。该模型表现出良好的预测性能，并在一个独立数据集中得到了验证。我们的研究结果显示，胆汁酸风险评分是COAD患者的独立预后因素。© 2023. Springer Nature Limited.

Colon adenocarcinoma (COAD), one of the common clinical cancers, exhibits high morbidity and mortality, and its pathogenesis and treatment are still underdeveloped. Numerous studies have demonstrated the involvement of bile acids in tumour development, while the potential role of their metabolism in the tumor microenvironment (TME) has not been explored. A collection of 481 genes related to bile acid metabolism were obtained, and The Cancer Genome Atlas-based COAD risk model was developed using the least absolute shrinkage selection operator (LASSO) regression analysis. The Gene Expression Omnibus dataset was used to validate the results. The predictive performance of the model was verified using column line plots, principal component analysis and receiver operating characteristic curves. Then, we analysed the differences between the high- and low-risk groups from training set based on clinical characteristics, immune cell infiltration, immune-related functions, chemotherapeutic drug sensitivity and immunotherapy efficacy. Additionally, we constructed a protein-protein interaction network to screen for target genes, which were further investigated in terms of differential immune cell distribution. A total of 234 bile acids-related differentially expressed genes were obtained between normal and tumour colon tissues. Among them, 111 genes were upregulated and 123 genes were down-regulated in the tumour samples. Relying on the LASSO logistic regression algorithm, we constructed a model of bile acid risk score, comprising 12 genes: CPT2, SLCO1A2, CD36, ACOX1, CDKN2A, HADH, GABRD, LEP, TIMP1, MAT1A, SLC6A15 and PPARGC1A. This model was validated in the GEO-COAD set. Age and risk score were observed to be independent prognostic factors in patients with COAD. Genes related to bile acid metabolism in COAD were closely related to bile secretion, intestinal transport, steroid and fatty acid metabolism. Furthermore, the high-risk group was more sensitive to Oxaliplatin than the low-risk group. Finally, the three target genes screened were closely associated with immune cells. We identified a set of 12 genes (CPT2, SLCO1A2, CD36, ACOX1, CDKN2A, HADH, GABRD, LEP, TIMP1, MAT1A, SLC6A15, and PPARGC1A) associated with bile acid metabolism and developed a bile acid risk score model using LASSO regression analysis. The model demonstrated good predictive performance and was validated using an independent dataset. Our findings revealed that the bile acid risk score were independent prognostic factors in COAD patients.© 2023. Springer Nature Limited.