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<p>Peritoneal metastasis (PM) poses a significant clinical challenge, yet the patient characteristics and genomic drivers underlying PM remain poorly characterized. Leveraging the MSK-MetTropism cohort (<i>n</i> = 25,755), our pan-cancer analysis reveals PM occurs in 29% of metastatic patients with extreme incidence variation (1% in THPA to 92% in HGSOC), and digestive/gynecologic malignancies exhibit the highest PM propensity with significant sex disparities. PM confers worse survival in 11/39 subtypes. Genomic profiling of 5,942 PM patients identifies enriched mutations in <i>ESR1</i>, <i>TCF7L2</i>, and FBXW7, pathway-level of TGF-Beta mutation, and subtype-specific drivers, including <i>RET</i> mutations in gastric PM. Mutational signatures implicate ROS (SBS18), HR deficiency (SBS3), and SBS8 across ≥9 cancer types. These results establish foundational insights into PM biology, though future PM tissue profiling is warranted to overcome primary tumor bias in genomic data.</p>

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Pan-cancer clinicopathological and genomic characteristics of peritoneal metastasis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月13日

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  • Tianwei Chen,
  • Yebin Yang,
  • Xiaoli Liu,
  • Fanhe Dong,
  • Liang Wang,
  • Yuqiang Shan,
  • Xiang Wang

摘要

Peritoneal metastasis (PM) poses a significant clinical challenge, yet the patient characteristics and genomic drivers underlying PM remain poorly characterized. Leveraging the MSK-MetTropism cohort (n = 25,755), our pan-cancer analysis reveals PM occurs in 29% of metastatic patients with extreme incidence variation (1% in THPA to 92% in HGSOC), and digestive/gynecologic malignancies exhibit the highest PM propensity with significant sex disparities. PM confers worse survival in 11/39 subtypes. Genomic profiling of 5,942 PM patients identifies enriched mutations in ESR1, TCF7L2, and FBXW7, pathway-level of TGF-Beta mutation, and subtype-specific drivers, including RET mutations in gastric PM. Mutational signatures implicate ROS (SBS18), HR deficiency (SBS3), and SBS8 across ≥9 cancer types. These results establish foundational insights into PM biology, though future PM tissue profiling is warranted to overcome primary tumor bias in genomic data.