免疫疗法的疗效很大程度上受 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治疗的反应。通过采用非负矩阵分解 (NMF) 算法来确定与 T 细胞增殖相关的亚型，该算法分析了膀胱癌 (BCa) 患者的预后和免疫治疗反应。 T 细胞增殖调节因子的表达模式。评估亚型的预后、免疫浸润和功能行为的差异。随后，在 TCGA 队列中通过 Cox 和 Lasso 回归分析创建了与 T 细胞增殖相关的风险模型，并在两个 GEO 队列和一个免疫治疗队列中得到证实。 BCa 患者根据表达分为两个亚型（C1 和 C2）具有不同预后和免疫景观的 31 个 T 细胞增殖相关基因 (TRG) 的概况。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，癌症相关通路的激活也较高。此后，利用参与 T 细胞增殖的 13 个预后相关基因来创建预后特征。通过分析内部和外部数据集证实了该模型的预测准确性。高风险类别的个体预后较差，肿瘤微环境中的免疫抑制因素增加，并且对免疫治疗的反应减弱。此外，该模型的免疫治疗预测功效得到了免疫治疗队列（IMvigor210队列中的抗PD-L1）的进一步证实。我们的研究描述了与具有不同预后和肿瘤微环境（TME）的BCa患者中T细胞增殖相关的两种亚型模式，为 BCa 中 T 细胞增殖的异质性及其与免疫景观的联系提供了新的见解。该签名对于预测结果具有前瞻性临床意义，并可能帮助医生选择优先考虑当前免疫治疗的潜在反应者。© 2024。作者获得 Springer Nature B.V. 的独家许可。

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).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.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).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.© 2024. The Author(s), under exclusive licence to Springer Nature B.V.