{"title":"Tumor immune microenvironment of colorectal cancer identifies novel prognostic signature and potential therapeutic drugs.","authors":"Weijie Fu, Yunhan Gao, Zhenhai Chen, Song Hu","doi":"10.3233/CBM-240110","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> The tumor microenvironment (TME) is increasingly recognized as a key player in colorectal cancer biology, however, its potential for improving diagnosis, prognosis, and treatment remains unclear. The major aim of this study is to explore the prognostic value of TME related gene in colorectal cancer. <b>Method:</b> Expression matrices and clinical data of colorectal cancer obtained from public databases were divided into TME relevant clusters according to immune characterization. A 11-gene molecular classifier was constructed based on differentially expressed genes between TME clusters and machine learning regression processes. <b>Results:</b> The efficacy and effectiveness of TME based prognostic signature (TPS) were examined in both the training and validation groups. The result indicated that TPS was able to serve as a superior prognosis indicator for colorectal cancer, alone or jointly with other clinical factors. Also, the study demonstrated that high risk colorectal cancer defined by TPS was considered to link with elevated immune infiltration, increased tumor mutation, and worse overall prognosis. Finally, potential therapeutic agents specialized for different risk subgroups of TPS was also identified to improve personalized treatment for colorectal cancer in the future. <b>Conclusions:</b> TPS might be a novel tool to improve the prognosis judgement and personalized treatment of the colorectal cancer in the future.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"41 3","pages":"CBM240110"},"PeriodicalIF":2.2000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Biomarkers","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3233/CBM-240110","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The tumor microenvironment (TME) is increasingly recognized as a key player in colorectal cancer biology, however, its potential for improving diagnosis, prognosis, and treatment remains unclear. The major aim of this study is to explore the prognostic value of TME related gene in colorectal cancer. Method: Expression matrices and clinical data of colorectal cancer obtained from public databases were divided into TME relevant clusters according to immune characterization. A 11-gene molecular classifier was constructed based on differentially expressed genes between TME clusters and machine learning regression processes. Results: The efficacy and effectiveness of TME based prognostic signature (TPS) were examined in both the training and validation groups. The result indicated that TPS was able to serve as a superior prognosis indicator for colorectal cancer, alone or jointly with other clinical factors. Also, the study demonstrated that high risk colorectal cancer defined by TPS was considered to link with elevated immune infiltration, increased tumor mutation, and worse overall prognosis. Finally, potential therapeutic agents specialized for different risk subgroups of TPS was also identified to improve personalized treatment for colorectal cancer in the future. Conclusions: TPS might be a novel tool to improve the prognosis judgement and personalized treatment of the colorectal cancer in the future.
期刊介绍:
Concentrating on molecular biomarkers in cancer research, Cancer Biomarkers publishes original research findings (and reviews solicited by the editor) on the subject of the identification of markers associated with the disease processes whether or not they are an integral part of the pathological lesion.
The disease markers may include, but are not limited to, genomic, epigenomic, proteomics, cellular and morphologic, and genetic factors predisposing to the disease or indicating the occurrence of the disease. Manuscripts on these factors or biomarkers, either in altered forms, abnormal concentrations or with abnormal tissue distribution leading to disease causation will be accepted.