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邻苯二甲酸二(2-乙基己基)酯在结直肠癌中致癌作用的计算分析

Computational analysis of DEHP's oncogenic role in colorectal cancer.

作者信息

Zhu Zhou, Qin Jian, He Chungang, Wang Shuangyou, Lu Yaolin, Wang Shuai, Zhong Xiaogang

机构信息

Department of Colorectal and Anal Surgery, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, Guangxi, China.

Department of Radiation Oncology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530021, Guangxi, China.

出版信息

Discov Oncol. 2025 May 21;16(1):848. doi: 10.1007/s12672-025-02616-x.

Abstract

BACKGROUND

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality globally, with many patients diagnosed at advanced stages. Current treatments, including surgery, chemotherapy, and targeted therapies, face limitations due to tumor metastasis and chemoresistance. Di-(2-ethylhexyl) phthalate (DEHP), a widely-used plasticizer, has been linked to various cancers, including CRC, through mechanisms such as metabolic reprogramming and inflammation. However, the direct relationship between DEHP and CRC requires further elucidation.

METHODS

We integrated transcriptomic data from TCGA-COADREAD (41 normal and 476 cancer tissues) and GEO datasets (GSE32323 and GSE21510) to identify differentially expressed genes (DEGs) using the limma package. We predicted DEHP molecular targets via SwissTargetPrediction and ChEMBL databases and constructed a protein-protein interaction (PPI) network using STRING. Machine learning methods, including LASSO regression, SVM, and Random Forest, identified key genes. SHAP analysis and ssGSEA were employed to evaluate gene importance and immune cell infiltration, respectively. Molecular docking experiments assessed the binding affinity of DEHP with key proteins.

RESULTS

Differential expression analysis identified 86 common genes involved in pathways such as PI3K-Akt and p53 signaling. The PPI network highlighted 14 candidate genes, with machine learning methods narrowing down to three key genes: CDK1, CDK4, and BCL2. SHAP analysis showed CDK1 and CDK4 as top contributors, while ssGSEA revealed significant correlations between these genes and immune cell infiltration. Molecular docking experiments demonstrated strong binding affinities of DEHP with BCL2 (- 8.7 kcal/mol), CDK1 (- 7.8 kcal/mol), and CDK4 (- 6.8 kcal/mol).

CONCLUSION

This study provides comprehensive insights into the oncogenic mechanisms of DEHP in CRC, identifying key genes and pathways that may serve as potential therapeutic targets. Our findings highlight the need for further investigation into DEHP's role in CRC and its potential as a target for prevention and treatment strategies.

摘要

背景

结直肠癌(CRC)仍是全球癌症相关死亡的主要原因之一,许多患者在晚期才被诊断出来。目前的治疗方法,包括手术、化疗和靶向治疗,由于肿瘤转移和化疗耐药性而面临局限性。邻苯二甲酸二(2-乙基己基)酯(DEHP)是一种广泛使用的增塑剂,已通过代谢重编程和炎症等机制与包括CRC在内的各种癌症相关联。然而,DEHP与CRC之间的直接关系仍需进一步阐明。

方法

我们整合了来自TCGA-COADREAD(41个正常组织和476个癌组织)和GEO数据集(GSE32323和GSE21510)的转录组数据,使用limma软件包来识别差异表达基因(DEG)。我们通过SwissTargetPrediction和ChEMBL数据库预测DEHP的分子靶点,并使用STRING构建蛋白质-蛋白质相互作用(PPI)网络。包括LASSO回归、支持向量机和随机森林在内的机器学习方法确定了关键基因。分别采用SHAP分析和单样本基因集富集分析(ssGSEA)来评估基因重要性和免疫细胞浸润情况。分子对接实验评估了DEHP与关键蛋白的结合亲和力。

结果

差异表达分析确定了86个参与PI3K-Akt和p53信号传导等通路的常见基因。PPI网络突出了14个候选基因,机器学习方法将其缩小到三个关键基因:细胞周期蛋白依赖性激酶1(CDK1)、细胞周期蛋白依赖性激酶4(CDK4)和B细胞淋巴瘤2(BCL2)。SHAP分析显示CDK1和CDK4是主要贡献者,而ssGSEA揭示了这些基因与免疫细胞浸润之间的显著相关性。分子对接实验表明DEHP与BCL2(-8.7千卡/摩尔)、CDK1(-7.8千卡/摩尔)和CDK4(-6.8千卡/摩尔)具有很强的结合亲和力。

结论

本研究全面深入地了解了DEHP在CRC中的致癌机制,确定了可能作为潜在治疗靶点的关键基因和通路。我们的研究结果凸显了进一步研究DEHP在CRC中的作用及其作为预防和治疗策略靶点的潜力的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1cf/12095122/73fd68de17dc/12672_2025_2616_Fig1_HTML.jpg

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