Identification and validation of molecular subtypes and prognostic models in patients with kidney cancer based on differential genes based on B cells: a multiomics analysis.
{"title":"Identification and validation of molecular subtypes and prognostic models in patients with kidney cancer based on differential genes based on B cells: a multiomics analysis.","authors":"Jiaao Sun, Shiyan Song, Qiancheng Ma, Feng Chen, Xiaochi Chen, Guangzhen Wu","doi":"10.1186/s12885-025-13923-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>B cells play a variety of complex roles in cancer, both promoting cancer progression and enhancing anti-tumor immune responses, but their mechanism of action in kidney cancer has not been elucidated.</p><p><strong>Results: </strong>We collected kidney cancer sample data from the GEO database and TCGA database, mapped the single-cell landscape inside kidney cancer tissue, identified 25 B-cell-related genes, and based on this, identified related molecular subtypes of kidney cancer patients, and explored their internal microenvironment characteristics. Finally, we constructed a 6-gene biological prognostic model that can be used to predict survival in patients with renal cancer, and we further validated the predictive performance of the model based on imaging omics. It is worth mentioning that the structural patterns and functional sites of 6 model gene transcription proteins were also mined.</p><p><strong>Conclusions: </strong>Overall, we explored for the first time the profound role of B cells in kidney cancer and developed a bio-predictive model based on B cell-related genes, providing scientific guidance for personalized treatment of kidney cancer patients.</p>","PeriodicalId":9131,"journal":{"name":"BMC Cancer","volume":"25 1","pages":"559"},"PeriodicalIF":3.4000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951520/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Cancer","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12885-025-13923-5","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: B cells play a variety of complex roles in cancer, both promoting cancer progression and enhancing anti-tumor immune responses, but their mechanism of action in kidney cancer has not been elucidated.
Results: We collected kidney cancer sample data from the GEO database and TCGA database, mapped the single-cell landscape inside kidney cancer tissue, identified 25 B-cell-related genes, and based on this, identified related molecular subtypes of kidney cancer patients, and explored their internal microenvironment characteristics. Finally, we constructed a 6-gene biological prognostic model that can be used to predict survival in patients with renal cancer, and we further validated the predictive performance of the model based on imaging omics. It is worth mentioning that the structural patterns and functional sites of 6 model gene transcription proteins were also mined.
Conclusions: Overall, we explored for the first time the profound role of B cells in kidney cancer and developed a bio-predictive model based on B cell-related genes, providing scientific guidance for personalized treatment of kidney cancer patients.
期刊介绍：
BMC Cancer is an open access, peer-reviewed journal that considers articles on all aspects of cancer research, including the pathophysiology, prevention, diagnosis and treatment of cancers. The journal welcomes submissions concerning molecular and cellular biology, genetics, epidemiology, and clinical trials.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
