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Hepatology communications

October 14, 2026 · via Europe PMC

Molecular biomarkers for diagnosis, prognosis, precision therapy, and immunotherapy in cholangiocarcinoma, cHCC-CCA, and HCC.

Sun J, Lu Y, Chang L, Gao R, Guan M, Ruan H, Deng X.

ReviewOpen access

AI summary — for doctors, generated from the abstract only

This review organizes liver cancer biomarkers by the treatment decision they support, separating decision-ready markers from trial-enrichment, monitoring and mechanistic signatures.

What was studied

A narrative review of molecular biomarkers in hepatocellular carcinoma, intrahepatic cholangiocarcinoma, combined hepatocellular-cholangiocarcinoma and rarer primary liver cancers, spanning curative-intent risk stratification, molecularly guided systemic therapy, immune-state assessment, dynamic monitoring and resistance reassessment.

Key findings

  • HCC has many approved systemic therapies but most are chosen by clinical context, liver function, tumor burden and treatment line rather than biomarkers
  • iCCA and biliary tract cancers have several treatment-directing alterations, including FGFR2 fusions or rearrangements, IDH1 mutations, HER2 positivity, BRAF V600E, NTRK or RET fusions and MSI-H/dMMR status
  • For combined HCC-CCA, lineage classification and sampling adequacy determine whether HCC-based or biliary-based evidence is more relevant

Clinical relevance

Oncology teams can use the framework to decide when molecular testing will change management, particularly in biliary tract cancers. It also cautions against treating investigational markers as actionable.

Who should care

HepatologyPediatric Hepatology

Limitations

As a narrative review the abstract reports no pooled data or study counts, and biomarker value is described as depending on evidence maturity, assay feasibility and timing.

Biomarker testing is most actionable in biliary tract cancer, whereas in HCC treatment selection still rests mainly on clinical factors.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

Abstract

Primary liver cancers include hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), combined hepatocellular-cholangiocarcinoma (cHCC-CCA), and rarer hepatic malignancies. Their biomarker landscapes differ substantially. HCC has many approved systemic therapies, yet most are still selected through clinical context, liver function, tumor burden, and treatment line. By contrast, iCCA and broader biliary tract cancers (BTCs) have fewer patients but multiple treatment-directing genomic alterations, including FGFR2 fusions or rearrangements, IDH1 mutations, HER2 positivity, BRAF V600E, NTRK or RET fusions, and microsatellite instability-high (MSI-H) or deficient mismatch repair (dMMR) status. cHCC-CCA adds a diagnostic layer because lineage classification and sampling adequacy influence whether HCC-based or BTC-based evidence is more relevant. This review organizes biomarkers by the treatment decision they are expected to support. It covers curative intent and locoregional risk stratification, molecularly guided systemic therapy, immune-state assessment, dynamic monitoring, resistance reassessment, and translational readiness. Across these settings, biomarker value depends on clinical action, evidence maturity, assay feasibility, and timing. The review separates decision-ready markers, trial-enrichment tools, monitoring assays, and mechanistic signatures.

DOI

10.1097/hc9.0000000000001069

PMID

42878587

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

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