{"title":"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。","authors":"Yiting Zou, Shan Lu, Shiqiang Han, Renfeng Zhao","doi":"10.1007/s12672-025-03612-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1801"},"PeriodicalIF":2.9000,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive bioinformatics evaluation uncovers the possible oncogenic contribution of acrylamide to endometrial cancer.\",\"authors\":\"Yiting Zou, Shan Lu, Shiqiang Han, Renfeng Zhao\",\"doi\":\"10.1007/s12672-025-03612-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":11148,\"journal\":{\"name\":\"Discover. Oncology\",\"volume\":\"16 1\",\"pages\":\"1801\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Discover. Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s12672-025-03612-x\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discover. Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12672-025-03612-x","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Comprehensive bioinformatics evaluation uncovers the possible oncogenic contribution of acrylamide to endometrial cancer.
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.