Comprehensive bioinformatics evaluation uncovers the possible oncogenic contribution of acrylamide to endometrial cancer.

IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM
Yiting Zou, Shan Lu, Shiqiang Han, Renfeng Zhao
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Abstract

Background: Endometrial cancer (EC) is a prevalent gynecological malignancy with increasing incidence worldwide. Despite advancements in treatment, challenges such as tumor recurrence and chemoresistance persist. Acrylamide, a probable carcinogen formed in high-temperature cooked foods, has been associated with EC risk, but its oncogenic mechanisms remain underexplored.

Methods: Transcriptomic data from GEO datasets (GSE17025, GSE63678, GSE106191, GSE115810) and single-cell RNA sequencing (scRNA-seq) data (PRJNA786266) were integrated to identify differentially expressed genes (DEGs) using the limma package. Acrylamide molecular targets were predicted via SwissTargetPrediction and ChEMBL databases. Machine learning approaches, including LASSO regression, Support Vector Machine (SVM), and Random Forest, were employed to identify key genes. SHAP analysis evaluated gene importance, while ssGSEA assessed immune cell infiltration. Molecular docking experiments investigated acrylamide's binding affinity with key proteins.

Results: Differential expression analysis identified 2274 downregulated and 2545 upregulated genes in EC. Nine consensus genes were identified across GEO DEGs, scRNA-seq, WGCNA modules, and acrylamide targets, enriched in Notch, Wnt, and microRNA pathways. Machine learning pinpointed four key genes: ROCK1, CLK1, SIRT1, and PSENEN. SHAP analysis highlighted ROCK1 as the top predictor (AUC = 1.00). ssGSEA revealed significant correlations between these genes and immune cell infiltration, particularly with NK and T cells. Molecular docking confirmed strong binding affinities of acrylamide with CLK1 (- 6.3 kcal/mol), PSENEN (- 6.1 kcal/mol), ROCK1 (- 6.0 kcal/mol), and SIRT1 (- 5.8 kcal/mol).

Conclusion: This study elucidates acrylamide's potential oncogenic role in EC, identifying ROCK1, CLK1, SIRT1, and PSENEN as key mediators. These findings underscore the interplay between dietary exposures and EC pathogenesis, suggesting novel therapeutic targets. Further validation is needed to translate these insights into preventive and therapeutic strategies.

综合生物信息学评价揭示了丙烯酰胺对子宫内膜癌可能的致癌作用。
背景:子宫内膜癌(EC)是一种常见的妇科恶性肿瘤,在世界范围内发病率不断上升。尽管治疗取得了进步,但肿瘤复发和化疗耐药等挑战仍然存在。丙烯酰胺是一种可能在高温熟食中形成的致癌物,与EC风险有关,但其致癌机制仍未得到充分研究。方法:整合GEO数据集(GSE17025、GSE63678、GSE106191、GSE115810)的转录组学数据和单细胞RNA测序(scRNA-seq)数据(PRJNA786266),使用limma软件包鉴定差异表达基因(deg)。通过SwissTargetPrediction和ChEMBL数据库预测丙烯酰胺分子靶点。采用LASSO回归、支持向量机(SVM)和随机森林等机器学习方法识别关键基因。SHAP分析评估基因重要性,而ssGSEA评估免疫细胞浸润。分子对接实验研究了丙烯酰胺与关键蛋白的结合亲和力。结果:差异表达分析鉴定出2274个下调基因和2545个上调基因。在GEO DEGs、scRNA-seq、WGCNA模块和丙烯酰胺靶点中鉴定出9个共识基因,它们在Notch、Wnt和microRNA途径中富集。机器学习确定了四个关键基因:ROCK1、CLK1、SIRT1和PSENEN。SHAP分析强调ROCK1是最重要的预测因子(AUC = 1.00)。ssGSEA显示这些基因与免疫细胞浸润,特别是NK细胞和T细胞浸润之间存在显著相关性。分子对接证实丙烯酰胺与CLK1 (- 6.3 kcal/mol)、PSENEN (- 6.1 kcal/mol)、ROCK1 (- 6.0 kcal/mol)和SIRT1 (- 5.8 kcal/mol)具有很强的结合亲和性。结论:本研究阐明了丙烯酰胺在EC中的潜在致癌作用,并确定了ROCK1、CLK1、SIRT1和PSENEN是关键的介导因子。这些发现强调了饮食暴露与EC发病机制之间的相互作用,提出了新的治疗靶点。将这些见解转化为预防和治疗策略需要进一步的验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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