Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, PR China.
Department of Nanfang Hospital Administration Office, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, PR China.
Int Immunopharmacol. 2024 Jul 30;136:112184. doi: 10.1016/j.intimp.2024.112184. Epub 2024 Jun 1.
Despite the availability of established surgical and chemotherapy options, the treatment of bladder cancer (BCa) patients remains challenging. While immunotherapy has emerged as a promising approach, its benefits are limited to a subset of patients. The exploration of additional targets to enhance the efficacy of immunotherapy is a valuable research direction.
High endothelial venules (HEV) ssGSEA analysis was conducted using BEST. Through the utilization of R packages Limma, Seurat, SingleR, and Harmony, analyses were performed on spatial transcriptomics, bulk RNA-sequencing (bulk RNA-seq), and single-cell RNA sequencing (scRNA-seq) data, yielding HEV-related genes (HEV.RGs). Molecular subtyping analysis based on HEV.RGs was conducted using R package MOVICS, and various machine learning-integrated algorithm was employed to construct prognostic model. LDLRAD3 was validated through subcutaneous tumor formation in mice, HEV induction, Western blot, and qPCR.
A correlation between higher HEV levels and improved immune response and prognosis was revealed by HEV ssGSEA analysis in BCa patients receiving immunotherapy. HEV.RGs were identified in subsequent transcriptomic analyses. Based on these genes, BCa patients were stratified into two molecular clusters with distinct survival and immune infiltration patterns using various clustering-integrated algorithm. Prognostic model was developed using multiple machine learning-integrated algorithm. Low LDLRAD3 expression may promote HEV generation, leading to enhanced immunotherapy efficacy, as suggested by bulk RNA-seq, scRNA-seq analyses, and experimental validation of LDLRAD3.
HEV served as a predictive factor for immune response and prognosis in BCa patients receiving immunotherapy. LDLRAD3 represented a potential target for HEV induction and enhancing the efficacy of immunotherapy.
尽管已经有了成熟的手术和化疗选择，膀胱癌（BCa）患者的治疗仍然具有挑战性。虽然免疫疗法已经成为一种很有前途的方法，但它的益处仅限于一部分患者。探索其他靶点来提高免疫疗法的疗效是一个有价值的研究方向。
使用 BEST 进行高内皮静脉（HEV）ssGSEA 分析。通过使用 R 包 Limma、Seurat、SingleR 和 Harmony，对空间转录组学、批量 RNA 测序（bulk RNA-seq）和单细胞 RNA 测序（scRNA-seq）数据进行分析，得出 HEV 相关基因（HEV.RGs）。使用 R 包 MOVICS 对基于 HEV.RGs 的分子亚型分析进行，并用各种机器学习整合算法构建预后模型。通过在小鼠中进行皮下肿瘤形成、HEV 诱导、Western blot 和 qPCR 验证 LDLRAD3。
通过 BCa 患者接受免疫治疗的 HEV ssGSEA 分析，发现 HEV 水平与免疫反应和预后改善之间存在相关性。随后的转录组分析中确定了 HEV.RGs。基于这些基因，使用各种聚类整合算法将 BCa 患者分为两个分子聚类，具有不同的生存和免疫浸润模式。使用多种机器学习整合算法开发了预后模型。LDLRAD3 表达降低可能会促进 HEV 的产生，从而增强免疫治疗的疗效，这一点在 bulk RNA-seq、scRNA-seq 分析和 LDLRAD3 的实验验证中得到了证实。
HEV 是 BCa 患者接受免疫治疗时免疫反应和预后的预测因子。LDLRAD3 是 HEV 诱导和增强免疫治疗效果的潜在靶点。
