Zihan Chen, Jiangnan Yu, Zhikun Guo, Shuxian Chen, Yina Li, Qian Zhou, Lei Wang
{"title":"Harnessing the power of tumor-draining lymph nodes: unveiling predictive biomarkers for immune checkpoint inhibitor.","authors":"Zihan Chen, Jiangnan Yu, Zhikun Guo, Shuxian Chen, Yina Li, Qian Zhou, Lei Wang","doi":"10.37349/etat.2025.1002315","DOIUrl":null,"url":null,"abstract":"<p><p>With the escalating application of immune checkpoint inhibitors (ICIs) in solid tumors, these therapies have demonstrated clinical benefits but remain hampered by relatively low response rates. Reliable biomarkers to predict ICIs responsiveness are essential for selecting appropriate patients and optimizing therapeutic outcomes. Given the pivotal role of tumor-draining lymph nodes (TDLNs) in orchestrating systemic antitumor immunity, their intrinsic features-such as dynamic organization in T cell subsets and functional status of antigen-presenting cells, hold considerable potential as predictive biomarkers for ICIs. Moreover, the complexity of ICIs-induced responses in TDLNs necessitates integrating multiple biomarkers for accurate prediction. Through continuous refinement of predictive strategies, TDLNs are poised to play an indispensable role in enhancing ICIs efficacy and guiding personalized immunotherapy. Here, we provide a review to discuss the possibility of using the intrinsic features of TDLNs as a predictive marker for ICI therapy.</p>","PeriodicalId":73002,"journal":{"name":"Exploration of targeted anti-tumor therapy","volume":"6 ","pages":"1002315"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082330/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Exploration of targeted anti-tumor therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37349/etat.2025.1002315","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
With the escalating application of immune checkpoint inhibitors (ICIs) in solid tumors, these therapies have demonstrated clinical benefits but remain hampered by relatively low response rates. Reliable biomarkers to predict ICIs responsiveness are essential for selecting appropriate patients and optimizing therapeutic outcomes. Given the pivotal role of tumor-draining lymph nodes (TDLNs) in orchestrating systemic antitumor immunity, their intrinsic features-such as dynamic organization in T cell subsets and functional status of antigen-presenting cells, hold considerable potential as predictive biomarkers for ICIs. Moreover, the complexity of ICIs-induced responses in TDLNs necessitates integrating multiple biomarkers for accurate prediction. Through continuous refinement of predictive strategies, TDLNs are poised to play an indispensable role in enhancing ICIs efficacy and guiding personalized immunotherapy. Here, we provide a review to discuss the possibility of using the intrinsic features of TDLNs as a predictive marker for ICI therapy.