Evidence map›Paper›PMID 32323426›Full record

ReviewHepatology research : the official journal of the Japan Society of Hepatology2020

Omics-derived hepatocellular carcinoma risk biomarkers for precision care of chronic liver diseases.

Naoto Fujiwara, Tongqi Qian, Bhuvaneswari Koneru, Yujin Hoshida

Open access · greenAbstract readReview
In one paragraph

Review in Hepatology research : the official journal of the Japan Society of Hepatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
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

13 citing papers in PubMed, 19 citations in OpenAlex.

  1. Hepatocellular Carcinoma: The Search for an Optimal Screening Test.Middle East journal of digestive diseases · 2025
    Review
  2. Sex differences in diabetes‑induced hepatic and renal damage.Experimental and therapeutic medicine · 2024
    Article
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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

4 authors at 2 institutions in 2 countries.

Naoto FujiwaraLiver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0002-4109-3421
Tongqi QianLiver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Bhuvaneswari KoneruLiver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Yujin HoshidaLiver Tumor Translational Research Program, Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0001-9430-1426
The University of Texas Southwestern Medical Center · USThe University of Tokyo · JP

Funding

Reverse-engineering precision liver cancer chemopreventionR01CA233794 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI HOSHIDA, YUJIN · 2019 to 2023
$3.5M
Glycopathology of HCC: identification of the source cells of serum fucosylationU01CA226052 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI DRAKE, RICHARD R., HOSHIDA, YUJIN · 2019 to 2023
$2.8M
Molecular Prognostic Indicators in Liver Cirrhosis and CancerR01DK099558 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI HOSHIDA, YUJIN · 2013 to 2016
$2.6M
(PQB6) Accurate Comparative Genome-wide Analysis of Primary Tumors and MetastasesR21CA180016 · NCI · UNIVERSITY OF VIRGINIA · PI PEMBERTON, LUCY F, WOTTON, DAVID · 2013 to 2014
$373k
Cancer Prevention and Research Institute of Texas RR180016European Commission ERC-2014-AdG-671231European Research Council 671231NCI NIH HHS R01 CA233794NCI NIH HHS U01 CA226052NIDDK NIH HHS R01 DK099558Uehara Memorial Foundation CA226052Uehara Memorial Foundation CA233794Uehara Memorial Foundation DK099558
6 · The paper itself

Abstract

Precise hepatocellular carcinoma (HCC) risk prediction will play increasingly important roles with the contemporary HCC etiologies, that is, non-alcoholic fatty liver disease and resolved hepatitis C virus infection. Because the HCC incidence rate in this emerging patient population is relatively low (~1% per year), identification of a subset of patients at the highest risk is critical to concentrate the effort and resources of regular HCC screening to those who most need it. Omics profiling has been derived using several candidate HCC risk biomarkers, which could refine HCC screening by enabling individual risk-based personalized or risk-stratified patient management. Various types of biomolecules have been explored as sources of information to predict HCC risk at various time horizons. Germline DNA polymorphisms likely reflect race/ethnicity- and/or etiology-specific susceptibility to HCC development or chronic liver disease progression toward carcinogenesis. Transcriptomic dysregulations in the diseased liver capture functional molecular status supporting oncogenesis such as inflammatory pathway and myofibroblast activation. Circulating nucleic acids, proteins, and metabolites could serve as less-invasive measures of molecular HCC risk. Characterization of gut microbiota could also inform HCC risk estimation. Each biomarker could have its niche of clinical application depending on logistics of use, performance, and costs with a goal to eventually improve patient prognosis as a part of the whole algorithm of chronic liver disease management.

Indexed as

biomarkerhepatocellular carcinomaomicsprecision medicine

Identifiers

PMID32323426
PMCPMC8318383
OpenAlexW3019306585

What OpenQuestion holds

Textmetadata
LicenceTDM
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.