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Molecular insights into early malignant transition of hepatocellular carcinoma

  • Zhengtao Zhang
  • , Hong Li
  • , Lingli Chen
  • , Tao Lu
  • , Xinyi Shentu
  • , Yuanhua Liu
  • , Zhixuan Tang
  • , Shuyi Ji
  • , Zhixin Qiu
  • , Yining Zou
  • , Hong Wen
  • , Jing Han
  • , Zhengzeng Jiang
  • , Jie Fan
  • , Xinbo Gao
  • , Dianfan Li
  • , Agavni Mesropian
  • , Roser Pinyol
  • , Josep M. Llovet
  • , Hui Dong
  • Yuan Ji, Lijian Hui

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Understanding the molecular drivers of the premalignant-to-malignant transition is essential for early cancer detection and intervention, yet this process remains poorly characterized due to limited access to evolutionarily related lesions. Here, we comprehensively profiled the genomic and immunological landscapes of 21 very early hepatocellular carcinomas (veHCCs) arising within 17 cancer-prone dysplastic nodules (DNs). Notably, 82% of cancer-prone DNs harbored TERT alterations, suggesting a predisposing rather than causative role of TERT alteration in malignant transition. Notably, the accumulation of copy number alterations (CNAs), rather than single-nucleotide variants, is strongly associated with malignant transition. Intriguingly, different from the paradigm that HCC arises in chronic inflammation, cancer-prone DNs displayed immune inactivity. Strikingly, 43% of veHCCs showed an inflamed yet immune-evasive phenotype. These findings propose two evolutionary scenarios of early hepatocarcinogenesis, CNA-dominant progression and inflamed progression with early immune evasion, underscoring the potential of immunotherapy for early intervention.

Original languageEnglish
Pages (from-to)1012-1028.e9
JournalCancer Cell
Volume44
Issue number5
DOIs
StatePublished - 11 May 2026

Keywords

  • Immune evasion
  • cancer
  • copy number alteration
  • early carcinogenesis
  • evolutionary trajectories
  • hepatocellular carcinoma
  • malignant transition
  • response to immune therapies
  • spatial transcriptomics
  • tumor heterogeneity

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