{
  "abstract": "Hepatocellular carcinoma (HCC) commonly develops in chronically diseased liver and remains challenging because of late detection, heterogeneity, recurrence and limited hepatic reserve. Immune checkpoint inhibitor (ICI)-based combinations improve outcomes in advanced HCC, but durable responses occur in only a subset of patients. This structured narrative review evaluates biomarkers by intended use: surveillance and early detection, pretreatment prognostic stratification, treatment selection, on-treatment monitoring, neoadjuvant response assessment and postoperative minimal residual disease (MRD) detection. Serum alpha-fetoprotein and clinical scores are accessible but largely reflect tumor burden, inflammation or liver function. Cell-free DNA methylation and fragmentomics provide early-detection and tissue-of-origin signals, while circulating tumor DNA tracks molecular burden and clonal evolution. Tissue and spatial profiling clarify immune responsiveness and resistance, whereas radiomics and deep learning noninvasively assess whole-tumor and peritumoral heterogeneity. These modalities are complementary but require distinct evidence standards. Most early-detection studies use case-control or enriched cohorts, and most immunotherapy associations are retrospective, prognostic or monitoring-related. No biomarker yet supports routine selection among ICI regimens. Unlike modality-specific summaries, this review aligns each biomarker with a defined clinical decision and evidentiary category and proposes a longitudinal framework integrating baseline blood, imaging and tissue features with on-treatment dynamics, preoperative reassessment and postoperative molecular surveillance. Clinical translation requires standardized assays, representative multicenter cohorts, locked external validation and biomarker-guided trials demonstrating value beyond established criteria.",
  "abstract_shown": true,
  "affiliations": [
    "School of Food & Pharmaceutical Science and Technology, Guangzhou College of Technology and Business, Guangzhou, China.",
    "Department of Medical Oncology, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, China."
  ],
  "article_type": "review article",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yuli Zhao"
    },
    {
      "affs": [
        0
      ],
      "name": "Xiaolei Chen"
    },
    {
      "affs": [
        1
      ],
      "name": "Hanyu Zhao"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5p7avd74swta7.bib",
  "cited_by": 0,
  "doi": "10.3389/fgene.2026.1951687",
  "fulltext_url": "https://europepmc.org/articles/PMC13678074",
  "id": "5p7avd74swta7",
  "issns": [
    "1664-8021"
  ],
  "landing_url": "https://europepmc.org/article/MED/42898703",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2721|Hepatocellular Carcinoma Treatment and Prognosis"
    ]
  ],
  "openalex": "W7220459600",
  "pdf_url": "https://europepmc.org/articles/PMC13678074?pdf=render",
  "pmcid": "PMC13678074",
  "pmid": "42898703",
  "published": "2026-10-05",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5p7avd74swta7.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:37Z",
      "native_id": "MED:42898703",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42898703"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2721|Hepatocellular Carcinoma Treatment and Prognosis",
      "subfield": "general"
    }
  ],
  "title": "Multimodal biomarkers for early detection and immunotherapy assessment in hepatocellular carcinoma: integrating liquid biopsy, AI-based imaging and tumor immune profiling.",
  "title_text": "Multimodal biomarkers for early detection and immunotherapy assessment in hepatocellular carcinoma: integrating liquid biopsy, AI-based imaging and tumor immune profiling.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:37Z",
  "url": "https://research.draconitic.com/paper/5p7avd74swta7",
  "venue": "Frontiers in genetics",
  "versions": []
}