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<p>Clear cell renal cell carcinoma (ccRCC) is an aggressive malignancy associated with single-nucleotide variants in <i>VHL</i>, <i>PBRM1</i>, and <i>SETD2</i>. However, the role of structural variation (SV)—which have broader genomic impacts—and 3D genome architecture in ccRCC remains inadequately understood. Here, we reported a comprehensive molecular characterization. Through multi-omics analysis, we identify novel SV-associated oncogenic targets and reveal multidimensional 3D genome reorganization during ccRCC progression. We elucidate the dynamic interplay between SV and 3D chromatin architecture, demonstrating how structural rearrangements drive oncogenic dysregulation through 3D genome reorganization. Notably, an unrecognized pathogenic enhancer hijacking event is discovered and experimentally validated, leading to constitutive activation of the proto-oncogene <i>SEMA5B</i>. Furthermore, we developed a machine learning-based prognostic framework using enhancer hijacking signatures. Collectively, this work establishes a valuable resource for ccRCC research by elucidating how SVs and 3D genome reorganization collectively drive oncogenesis, and translates these findings into a clinically applicable prognostic tool.</p>

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Structural variation drives enhancer hijacking via 3D genome disruption in ccRCC

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月6日

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  • Yu Dong,
  • Wenjiao Xia,
  • Zitong Yang,
  • Liangliang Ren,
  • Hongru Wang,
  • Yiyang Zhou,
  • Qinchen Li,
  • Zhi Chen,
  • Zhinan Xia,
  • Yichun Zheng,
  • Feifan Wang,
  • Ning He,
  • Bing Cheng,
  • Dongmei Ma,
  • Wei Shao,
  • Wei Guo,
  • Shuwen Wang,
  • Ziqiao Liu,
  • Junxiao Shen,
  • Yiming Qi,
  • Xuke Gong,
  • Juan Jin,
  • Bo Xie,
  • Guixin Zhu,
  • Cheng Zhang

摘要

Clear cell renal cell carcinoma (ccRCC) is an aggressive malignancy associated with single-nucleotide variants in VHL, PBRM1, and SETD2. However, the role of structural variation (SV)—which have broader genomic impacts—and 3D genome architecture in ccRCC remains inadequately understood. Here, we reported a comprehensive molecular characterization. Through multi-omics analysis, we identify novel SV-associated oncogenic targets and reveal multidimensional 3D genome reorganization during ccRCC progression. We elucidate the dynamic interplay between SV and 3D chromatin architecture, demonstrating how structural rearrangements drive oncogenic dysregulation through 3D genome reorganization. Notably, an unrecognized pathogenic enhancer hijacking event is discovered and experimentally validated, leading to constitutive activation of the proto-oncogene SEMA5B. Furthermore, we developed a machine learning-based prognostic framework using enhancer hijacking signatures. Collectively, this work establishes a valuable resource for ccRCC research by elucidating how SVs and 3D genome reorganization collectively drive oncogenesis, and translates these findings into a clinically applicable prognostic tool.