Evidence map›Paper›PMID 39242496›Full record

ReviewMolecular cancer2024

Biomarkers for diagnosis and therapeutic options in hepatocellular carcinoma.

Yau-Tuen Chan, Cheng Zhang, Junyu Wu, Pengde Lu, Lin Xu, Hongchao Yuan, Yibin Feng, Zhe-Sheng Chen, Ning Wang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Molecular cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 194 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
194citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

194 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Review

134 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yau-Tuen ChanSchool of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Cheng ZhangSchool of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Junyu WuSchool of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Pengde LuSchool of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Lin XuSchool of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Hongchao YuanSchool of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Yibin FengSchool of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong.
Zhe-Sheng ChenSchool of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong. chenz@stjohns.edu.
Ning WangSchool of Chinese Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong. ckwang@hku.hk.

Funding

Health and Medical Research Fund 21222151Innovation and Technology Fund PRP/028/22FXResearch Grant Committee of Hong Kong 17119621University Research Committee, University of Hong Kong 109000349
6 · The paper itself

Abstract

Liver cancer is a global health challenge, causing a significant social-economic burden. Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer, which is highly heterogeneous in terms of molecular and cellular signatures. Early-stage or small tumors are typically treated with surgery or ablation. Currently, chemotherapies and immunotherapies are the best treatments for unresectable tumors or advanced HCC. However, drug response and acquired resistance are not predictable with the existing systematic guidelines regarding mutation patterns and molecular biomarkers, resulting in sub-optimal treatment outcomes for many patients with atypical molecular profiles. With advanced technological platforms, valuable information such as tumor genetic alterations, epigenetic data, and tumor microenvironments can be obtained from liquid biopsy. The inter- and intra-tumoral heterogeneity of HCC are illustrated, and these collective data provide solid evidence in the decision-making process of treatment regimens. This article reviews the current understanding of HCC detection methods and aims to update the development of HCC surveillance using liquid biopsy. Recent critical findings on the molecular basis, epigenetic profiles, circulating tumor cells, circulating DNAs, and omics studies are elaborated for HCC diagnosis. Besides, biomarkers related to the choice of therapeutic options are discussed. Some notable recent clinical trials working on targeted therapies are also highlighted. Insights are provided to translate the knowledge into potential biomarkers for detection and diagnosis, prognosis, treatment response, and drug resistance indicators in clinical practice.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularLiver NeoplasmsAnimalsDisease ManagementEpigenesis, GeneticHumansLiquid BiopsyPrognosisTumor MicroenvironmentBiomarkers, TumorArtificial intelligenceBiomarkersCancer diagnosisCancer surveillanceCancer treatmentCell-free DNACirculating tumor cellsCirculating tumor DNAClinical trialsHAICHepatocellular carcinomaImmunotherapiesLiquid biopsyLiver transplantationLocal ablationMetabolomicsMethylationNon-coding RNAsSerological biomarkersSurgical resectionTACETargeted therapiesTherapeutic optionTissue biopsyTumor-derived vesicles

Identifiers

PMID39242496
PMCPMC11378508

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.