{"title":"贫化-MLH1表达可预测子宫内膜癌的预后和免疫治疗效果:硅学方法","authors":"Tesfaye Wolde, Jing Huang, Peng Huang, Vijay Pandey, Peiwu Qin","doi":"10.3390/biomedinformatics4010019","DOIUrl":null,"url":null,"abstract":"Uterine corpus endometrial carcinoma (UCEC) poses significant clinical challenges due to its high incidence and poor prognosis, exacerbated by the lack of effective screening methods. The standard treatment for UCEC typically involves surgical intervention, with radiation and chemotherapy as potential adjuvant therapies. In recent years, immunotherapy has emerged as a promising avenue for the advanced treatment of UCEC. This study employs a multi-omics approach, analyzing RNA-sequencing data and clinical information from The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis (GEPIA), and GeneMANIA databases to investigate the prognostic value of MutL Homolog 1 (MLH1) gene expression in UCEC. The dysregulation of MLH1 in UCEC is linked to adverse prognostic outcomes and suppressed immune cell infiltration. Gene Set Enrichment Analysis (GSEA) data reveal MLH1’s involvement in immune-related processes, while its expression correlates with tumor mutational burden (TMB) and microsatellite instability (MSI). Lower MLH1 expression is associated with poorer prognosis, reduced responsiveness to Programmed cell death protein 1 (PD-1)/Programmed death-ligand 1 (PD-L1) inhibitors, and heightened sensitivity to anti-cancer agents. This comprehensive analysis establishes MLH1 as a potential biomarker for predicting prognosis, immunotherapy response, and drug sensitivity in UCEC, offering crucial insights for the clinical management of patients.","PeriodicalId":72394,"journal":{"name":"BioMedInformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Depleted-MLH1 Expression Predicts Prognosis and Immunotherapeutic Efficacy in Uterine Corpus Endometrial Cancer: An In Silico Approach\",\"authors\":\"Tesfaye Wolde, Jing Huang, Peng Huang, Vijay Pandey, Peiwu Qin\",\"doi\":\"10.3390/biomedinformatics4010019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Uterine corpus endometrial carcinoma (UCEC) poses significant clinical challenges due to its high incidence and poor prognosis, exacerbated by the lack of effective screening methods. The standard treatment for UCEC typically involves surgical intervention, with radiation and chemotherapy as potential adjuvant therapies. In recent years, immunotherapy has emerged as a promising avenue for the advanced treatment of UCEC. This study employs a multi-omics approach, analyzing RNA-sequencing data and clinical information from The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis (GEPIA), and GeneMANIA databases to investigate the prognostic value of MutL Homolog 1 (MLH1) gene expression in UCEC. The dysregulation of MLH1 in UCEC is linked to adverse prognostic outcomes and suppressed immune cell infiltration. Gene Set Enrichment Analysis (GSEA) data reveal MLH1’s involvement in immune-related processes, while its expression correlates with tumor mutational burden (TMB) and microsatellite instability (MSI). Lower MLH1 expression is associated with poorer prognosis, reduced responsiveness to Programmed cell death protein 1 (PD-1)/Programmed death-ligand 1 (PD-L1) inhibitors, and heightened sensitivity to anti-cancer agents. This comprehensive analysis establishes MLH1 as a potential biomarker for predicting prognosis, immunotherapy response, and drug sensitivity in UCEC, offering crucial insights for the clinical management of patients.\",\"PeriodicalId\":72394,\"journal\":{\"name\":\"BioMedInformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BioMedInformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/biomedinformatics4010019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BioMedInformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/biomedinformatics4010019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
子宫体子宫内膜癌(UCEC)发病率高、预后差,而且缺乏有效的筛查方法,这给临床带来了巨大挑战。子宫内膜癌的标准治疗方法通常包括手术干预,放疗和化疗是潜在的辅助疗法。近年来,免疫疗法已成为UCEC晚期治疗的一个很有前景的途径。本研究采用多组学方法,分析了癌症基因组图谱(TCGA)、基因表达谱交互分析(GEPIA)和GeneMANIA数据库中的RNA测序数据和临床信息,研究了MutL Homolog 1(MLH1)基因表达在UCEC中的预后价值。MLH1 在 UCEC 中的失调与不良预后结果和免疫细胞浸润受抑制有关。基因组富集分析(Gene Set Enrichment Analysis,GSEA)数据显示,MLH1参与了免疫相关过程,其表达与肿瘤突变负荷(TMB)和微卫星不稳定性(MSI)相关。MLH1表达较低与预后较差、对程序性细胞死亡蛋白1(PD-1)/程序性死亡配体1(PD-L1)抑制剂的反应性降低以及对抗癌药物的敏感性增强有关。这项全面的分析确定了MLH1是预测UCEC预后、免疫疗法反应和药物敏感性的潜在生物标志物,为患者的临床管理提供了重要的见解。
Depleted-MLH1 Expression Predicts Prognosis and Immunotherapeutic Efficacy in Uterine Corpus Endometrial Cancer: An In Silico Approach
Uterine corpus endometrial carcinoma (UCEC) poses significant clinical challenges due to its high incidence and poor prognosis, exacerbated by the lack of effective screening methods. The standard treatment for UCEC typically involves surgical intervention, with radiation and chemotherapy as potential adjuvant therapies. In recent years, immunotherapy has emerged as a promising avenue for the advanced treatment of UCEC. This study employs a multi-omics approach, analyzing RNA-sequencing data and clinical information from The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis (GEPIA), and GeneMANIA databases to investigate the prognostic value of MutL Homolog 1 (MLH1) gene expression in UCEC. The dysregulation of MLH1 in UCEC is linked to adverse prognostic outcomes and suppressed immune cell infiltration. Gene Set Enrichment Analysis (GSEA) data reveal MLH1’s involvement in immune-related processes, while its expression correlates with tumor mutational burden (TMB) and microsatellite instability (MSI). Lower MLH1 expression is associated with poorer prognosis, reduced responsiveness to Programmed cell death protein 1 (PD-1)/Programmed death-ligand 1 (PD-L1) inhibitors, and heightened sensitivity to anti-cancer agents. This comprehensive analysis establishes MLH1 as a potential biomarker for predicting prognosis, immunotherapy response, and drug sensitivity in UCEC, offering crucial insights for the clinical management of patients.