Scholarlink

<p>Bladder cancer exhibits marked cellular heterogeneity, which complicates the identification of molecular drivers with both functional and genetic relevance. The link between genetic susceptibility and transcriptional activity in tumorigenesis remains incompletely understood. Single-cell transcriptomes of bladder carcinoma and adjacent normal tissues were processed using Seurat and Harmony for data normalization, integration, and dimensionality reduction. Differentially expressed genes were further prioritized using causal inference based on genome-wide association and expression quantitative trait loci data. Functional analyses included pathway enrichment, immune profiling, and transcription factor network inference. Candidate genes were validated through immunohistochemistry, quantitative PCR, and Western blotting, and in vitro cell-based assays (including CCK-8, scratch wound healing, transwell invasion, and flow cytometry analysis). Among all cellular populations, B cells showed the highest fold-change score. Mendelian randomization highlighted six bladder-cancer-related genes—<i>ARHGEF18</i>, <i>HLA-DRB5</i>, <i>ISG20</i>, <i>NCF1</i>, <i>RPL13</i>, and <i>YPEL5</i>. <i>ARHGEF18</i> raised risk (OR 1.001; 95% CI 1.000–1.002; P 0.017), whereas <i>YPEL5</i> showed a protective association (OR 0.997; 95% CI 0.995–0.999; P 0.003). Immunohistochemistry confirmed elevated <i>ARHGEF18</i> and reduced <i>YPEL5</i> expression in tumor tissues. In vitro experiments demonstrated that <i>ARHGEF18</i> knockdown and <i>YPEL5</i> overexpression led to decreased cell proliferation, migration, invasion, and increased apoptosis in T24 and 5637 bladder cancer cells. Our findings identify <i>ARHGEF18</i> and <i>YPEL5</i> as genetically and transcriptionally supported regulators of bladder cancer, highlighting a scalable strategy for linking genetic risk to cell-type–specific mechanisms.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Single-cell transcriptomic profiling combined with Mendelian randomization illuminates molecular drivers of bladder cancer

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月4日

查看全文
  • Junrui He,
  • Zhuoying Jiang,
  • Shan Peng,
  • Lijuan Peng,
  • Zhongyou Xia,
  • Ting Ma,
  • Xiaojun Tan,
  • Qiongxian Long,
  • Ji Wu

摘要

Bladder cancer exhibits marked cellular heterogeneity, which complicates the identification of molecular drivers with both functional and genetic relevance. The link between genetic susceptibility and transcriptional activity in tumorigenesis remains incompletely understood. Single-cell transcriptomes of bladder carcinoma and adjacent normal tissues were processed using Seurat and Harmony for data normalization, integration, and dimensionality reduction. Differentially expressed genes were further prioritized using causal inference based on genome-wide association and expression quantitative trait loci data. Functional analyses included pathway enrichment, immune profiling, and transcription factor network inference. Candidate genes were validated through immunohistochemistry, quantitative PCR, and Western blotting, and in vitro cell-based assays (including CCK-8, scratch wound healing, transwell invasion, and flow cytometry analysis). Among all cellular populations, B cells showed the highest fold-change score. Mendelian randomization highlighted six bladder-cancer-related genes—ARHGEF18, HLA-DRB5, ISG20, NCF1, RPL13, and YPEL5. ARHGEF18 raised risk (OR 1.001; 95% CI 1.000–1.002; P 0.017), whereas YPEL5 showed a protective association (OR 0.997; 95% CI 0.995–0.999; P 0.003). Immunohistochemistry confirmed elevated ARHGEF18 and reduced YPEL5 expression in tumor tissues. In vitro experiments demonstrated that ARHGEF18 knockdown and YPEL5 overexpression led to decreased cell proliferation, migration, invasion, and increased apoptosis in T24 and 5637 bladder cancer cells. Our findings identify ARHGEF18 and YPEL5 as genetically and transcriptionally supported regulators of bladder cancer, highlighting a scalable strategy for linking genetic risk to cell-type–specific mechanisms.