Evidence map›Paper›PMID 26058462›Full record

ArticleLiver international : official journal of the International Association for the Study of the Liver2016

Clinicopathological indices to predict hepatocellular carcinoma molecular classification.

Poh Seng Tan, Shigeki Nakagawa, Nicolas Goossens, Anu Venkatesh, Tiangui Huang, Stephen C Ward, Xiaochen Sun, Won-Min Song, Anna Koh, Claudia Canasto-Chibuque and 8 more

Abstract read
In one paragraph

Article in Liver international : official journal of the International Association for the Study of the Liver, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
–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

52 citing papers in PubMed.

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  11. The Liver and Glycogen: In Sickness and in Health.International journal of molecular sciences · 2023
    Review
  12. Article
  13. Tumor metabolism derived fromQuantitative imaging in medicine and surgery · 2023
    Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Review
  20. Review
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

18 authors.

Poh Seng TanDivision of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Shigeki NakagawaDivision of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Nicolas GoossensDivision of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Anu VenkateshDivision of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Tiangui HuangDepartment of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Stephen C WardDepartment of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Xiaochen SunDivision of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Won-Min SongDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Anna KohDivision of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Claudia Canasto-ChibuqueDivision of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Manjeet DeshmukhDivision of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Venugopalan NairDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Milind MahajanDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Bin ZhangDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Maria Isabel FielDepartment of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Masahiro KobayashiDepartment of Hepatology, Toranomon Hospital, Tokyo, Japan.
Hiromitsu KumadaDepartment of Hepatology, Toranomon Hospital, Tokyo, Japan.
Yujin HoshidaDivision of Liver Diseases, Department of Medicine, Liver Cancer Program, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Funding

THE TISCH CANCER INSTITUTE - CANCER CENTER SUPPORT GRANTP30CA196521 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Deanna L Benson · 2015 to 2026
$35.4M
Molecular Prognostic Indicators in Liver Cirrhosis and CancerR01DK099558 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI HOSHIDA, YUJIN · 2013 to 2016
$2.6M
NCI NIH HHS P30 CA196521NIDDK NIH HHS DK099558NIDDK NIH HHS R01 DK099558
6 · The paper itself

Abstract

BACKGROUND &

aimsHepatocellular carcinoma (HCC) is the second most lethal cancer caused by lack of effective therapies. Although promising, HCC molecular classification, which enriches potential responders to specific therapies, has not yet been assessed in clinical trials of anti-HCC drugs. We aimed to overcome these challenges by developing clinicopathological surrogate indices of HCC molecular classification.

methodsHepatocellular carcinoma classification defined in our previous transcriptome meta-analysis (S1, S2 and S3 subclasses) was implemented in an FDA-approved diagnostic platform (Elements assay, NanoString). Ninety-six HCC tumours (training set) were assayed to develop molecular subclass-predictive indices based on clinicopathological features, which were independently validated in 99 HCC tumours (validation set). Molecular deregulations associated with the histopathological features were determined by pathway analysis. Sample sizes for HCC clinical trials enriched with specific molecular subclasses were determined.

resultsHepatocellular carcinoma subclass-predictive indices were steatohepatitic (SH)-HCC variant and immune cell infiltrate for S1 subclass, macrotrabecular/compact pattern, lack of pseudoglandular pattern, and high serum alpha-foetoprotein (>400 ng/ml) for S2 subclass, and microtrabecular pattern, lack of SH-HCC and clear cell variants, and lower histological grade for S3 subclass. Macrotrabecular/compact pattern, a predictor of S2 subclass, was associated with the activation of therapeutically targetable oncogene YAP and stemness markers EPCAM/KRT19. BMP4 was associated with pseudoglandular pattern. Subclass-predictive indices-based patient enrichment reduced clinical trial sample sizes from 121, 184 and 53 to 30, 43 and 22 for S1, S2 and S3 subclass-targeting therapies respectively.

conclusionsHepatocellular carcinoma molecular subclasses can be enriched by clinicopathological indices tightly associated with deregulation of therapeutically targetable molecular pathways.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsAgedalpha-FetoproteinsAmino Acid SequenceAntigens, NeoplasmBone Morphogenetic Protein 4Cell Adhesion MoleculesDrug DiscoveryEpithelial Cell Adhesion MoleculeFemaleGene Expression ProfilingGenome-Wide Association StudyHumansKeratin-19Malealpha-FetoproteinsAntigens, NeoplasmBMP4 protein, humanBone Morphogenetic Protein 4Cell Adhesion MoleculesEPCAM protein, humanEpithelial Cell Adhesion MoleculeKeratin-19clinical diagnosticgene expressionhistopathologymolecular subclasspredictive index

Identifiers

PMID26058462
PMCPMC4674393

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Registered trials

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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.