{"title":"Discovery of a T cell proliferation-associated regulator signature correlates with prognosis risk and immunotherapy response in bladder cancer.","authors":"Ting Yan, Wei Zhou, Chun Li","doi":"10.1007/s11255-024-04086-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The efficacy of immunotherapy is heavily influenced by T cell activity. This study aimed to examine how T cell proliferation regulators can predict the prognosis and response to immunotherapy in patients with bladder cancer (BCa).</p><p><strong>Methods: </strong>T cell proliferation-related subtypes were determined by employing the non-negative matrix factorization (NMF) algorithm that analyzed the expression patterns of T cell proliferation regulators. Subtypes were assessed for variations in prognosis, immune infiltration, and functional behaviors. Subsequently, a risk model related to T cell proliferation was created through Cox and Lasso regression analyses in the TCGA cohort and then confirmed in two GEO cohorts and an immunotherapy cohort.</p><p><strong>Results: </strong>BCa patients were categorized into two subtypes (C1 and C2) according to the expression profiles of 31 T cell proliferation-related genes (TRGs) with distinct prognoses and immune landscapes. The C2 subtype had a shorter overall survival (OS), with higher levels of M2 macrophage infiltration, and the activation of cancer-related pathways than the C1 subtype. Following this, thirteen prognosis-related genes that were involved in T cell proliferation were utilized to create the prognostic signature. The model's predictive accuracy was confirmed by analyzing both internal and external datasets. Individuals in the high-risk category experienced a poorer prognosis, increased immunosuppressive factors in the tumor microenvironment, and diminished responses to immunotherapy. Additionally, the immunotherapeutic prediction efficacy of the model was further confirmed by an immunotherapy cohort (anti-PD-L1 in the IMvigor210 cohort).</p><p><strong>Conclusions: </strong>Our study characterized two subtypes linked to T cell proliferation in BCa patients with distinct prognoses and tumor microenvironment (TME) patterns, providing new insights into the heterogeneity of T cell proliferation in BCa and its connection to the immune landscape. The signature has prospective clinical implications for predicting outcomes and may help physicians to select prospective responders who prioritize current immunotherapy.</p>","PeriodicalId":14454,"journal":{"name":"International Urology and Nephrology","volume":" ","pages":"3447-3462"},"PeriodicalIF":1.8000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Urology and Nephrology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11255-024-04086-6","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/24 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"UROLOGY & NEPHROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The efficacy of immunotherapy is heavily influenced by T cell activity. This study aimed to examine how T cell proliferation regulators can predict the prognosis and response to immunotherapy in patients with bladder cancer (BCa).
Methods: T cell proliferation-related subtypes were determined by employing the non-negative matrix factorization (NMF) algorithm that analyzed the expression patterns of T cell proliferation regulators. Subtypes were assessed for variations in prognosis, immune infiltration, and functional behaviors. Subsequently, a risk model related to T cell proliferation was created through Cox and Lasso regression analyses in the TCGA cohort and then confirmed in two GEO cohorts and an immunotherapy cohort.
Results: BCa patients were categorized into two subtypes (C1 and C2) according to the expression profiles of 31 T cell proliferation-related genes (TRGs) with distinct prognoses and immune landscapes. The C2 subtype had a shorter overall survival (OS), with higher levels of M2 macrophage infiltration, and the activation of cancer-related pathways than the C1 subtype. Following this, thirteen prognosis-related genes that were involved in T cell proliferation were utilized to create the prognostic signature. The model's predictive accuracy was confirmed by analyzing both internal and external datasets. Individuals in the high-risk category experienced a poorer prognosis, increased immunosuppressive factors in the tumor microenvironment, and diminished responses to immunotherapy. Additionally, the immunotherapeutic prediction efficacy of the model was further confirmed by an immunotherapy cohort (anti-PD-L1 in the IMvigor210 cohort).
Conclusions: Our study characterized two subtypes linked to T cell proliferation in BCa patients with distinct prognoses and tumor microenvironment (TME) patterns, providing new insights into the heterogeneity of T cell proliferation in BCa and its connection to the immune landscape. The signature has prospective clinical implications for predicting outcomes and may help physicians to select prospective responders who prioritize current immunotherapy.
背景:免疫疗法的疗效在很大程度上受T细胞活性的影响。本研究旨在探讨T细胞增殖调节因子如何预测膀胱癌(BCa)患者的预后和对免疫疗法的反应:方法:采用分析T细胞增殖调节因子表达模式的非负矩阵因式分解(NMF)算法确定T细胞增殖相关亚型。评估了亚型在预后、免疫浸润和功能行为方面的差异。随后,通过对TCGA队列进行Cox和Lasso回归分析,建立了与T细胞增殖相关的风险模型,并在两个GEO队列和一个免疫疗法队列中得到证实:结果:根据31个T细胞增殖相关基因(TRGs)的表达谱,BCa患者被分为两种亚型(C1和C2),其预后和免疫状况各不相同。与C1亚型相比,C2亚型的总生存期(OS)较短,M2巨噬细胞浸润水平较高,癌症相关通路被激活。随后,13 个与预后相关的基因被用于创建 T 细胞增殖预后特征。通过分析内部和外部数据集,证实了该模型的预测准确性。高危人群的预后较差,肿瘤微环境中的免疫抑制因素增加,对免疫疗法的反应减弱。此外,免疫疗法队列(IMvigor210队列中的抗PD-L1)进一步证实了该模型的免疫治疗预测功效:我们的研究揭示了两种与T细胞增殖相关的亚型,它们在BCa患者中具有不同的预后和肿瘤微环境(TME)模式,为了解BCa中T细胞增殖的异质性及其与免疫环境的联系提供了新的视角。该特征对预测预后具有前瞻性临床意义,可帮助医生选择优先接受当前免疫疗法的前瞻性应答者。
期刊介绍:
International Urology and Nephrology publishes original papers on a broad range of topics in urology, nephrology and andrology. The journal integrates papers originating from clinical practice.