Department of Anorectal Surgery, Wuyi Hospital of Traditional Chinese Medicine, Jiangmen, China.
Department of Anorectal Surgery, Jiangxi Hospital of Integrated Traditional Chinese and Western Medicine, Nanchang, China.
Sci Rep. 2023 Aug 5;13(1):12728. doi: 10.1038/s41598-023-40020-z.
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.
结直肠癌（COAD）是一种常见的临床癌症，发病率和死亡率均较高，其发病机制和治疗仍在发展中。大量研究表明胆汁酸参与肿瘤的发生，但其在肿瘤微环境（TME）中的代谢作用尚未被探索。本研究收集了 481 个与胆汁酸代谢相关的基因，并利用最小绝对收缩和选择算子（LASSO）回归分析建立了基于癌症基因组图谱（TCGA）的 COAD 风险模型。采用列线图、主成分分析和受试者工作特征曲线验证模型的预测性能。然后，我们根据临床特征、免疫细胞浸润、免疫相关功能、化疗药物敏感性和免疫治疗疗效，对来自训练集的高低风险组之间的差异进行分析。此外，我们构建了一个蛋白质-蛋白质相互作用网络来筛选靶基因，并进一步研究其差异免疫细胞分布。共获得了 234 个正常和肿瘤结肠组织中差异表达的胆汁酸相关基因。其中，肿瘤样本中有 111 个基因上调，123 个基因下调。基于 LASSO 逻辑回归算法，构建了一个由 12 个基因组成的胆汁酸风险评分模型：CPT2、SLCO1A2、CD36、ACOX1、CDKN2A、HADH、GABRD、LEP、TIMP1、MAT1A、SLC6A15 和 PPARGC1A。该模型在 GEO-COAD 集进行了验证。在 COAD 患者中，年龄和风险评分是独立的预后因素。COAD 中与胆汁酸代谢相关的基因与胆汁分泌、肠道转运、类固醇和脂肪酸代谢密切相关。此外，高危组对奥沙利铂的敏感性高于低危组。最后，筛选出的三个靶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 回归分析建立了胆汁酸风险评分模型。该模型具有良好的预测性能，并通过独立数据集进行了验证。我们的研究结果表明，胆汁酸风险评分是 COAD 患者的独立预后因素。
