Evidence map›Paper›PMID 30242023›Full record

SynthesisClinical cancer research : an official journal of the American Association for Cancer Research2019

Multimodal Meta-Analysis of 1,494 Hepatocellular Carcinoma Samples Reveals Significant Impact of Consensus Driver Genes on Phenotypes.

Kumardeep Chaudhary, Olivier B Poirion, Liangqun Lu, Sijia Huang, Travers Ching, Lana X Garmire

Open access · bronzeAbstract readMeta-Analysis
In one paragraph

Synthesis in Clinical cancer research : an official journal of the American Association for Cancer Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
5.7field-weighted citation impact, top 3% 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

29 citing papers in PubMed, 54 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Evolution of systemic treatment for advanced hepatocellular carcinoma.The Kaohsiung journal of medical sciences · 2021
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Assessment of risk factors, and racial and ethnic differences in hepatocellular carcinoma.JGH open : an open access journal of gastroenterology and hepatology · 2020
    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

6 authors at 2 institutions in 1 country.

Kumardeep ChaudharyEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.
Olivier B PoirionEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.
Liangqun LuEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.ORCID 0000-0002-4654-2126
Sijia HuangEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.
Travers ChingEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.
Lana X GarmireEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii. lgarmire@med.umich.edu.ORCID 0000-0002-4654-2126
University of Hawaiʻi at Mānoa · USCancer Center of Hawaii · US

Funding

Transgenic Mouse, ICSI and IVF CoreP20GM103457 · NIGMS · UNIVERSITY OF HAWAII AT MANOA · PI URSCHITZ, JOHANN · 2012 to 2018
$12.9M
An Integrative Omics Approach to Identify Biomarkers Related to Preeclampsia and Breast Cancer RisksR01HD084633 · NICHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2016 to 2020
$3.0M
Cancer precision medicine through spatially informative single cell image and transcriptomics data analysisR01LM012373 · NLM · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2016 to 2024
$2.4M
DR. EPS: Drug Repurposing for Extended Patient SurvivalR01LM012907 · NLM · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2019 to 2022
$1.0M
An Integrative Bioinformatics Approach to Study Single Cancer Cell HeterogeneityK01ES025434 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2014 to 2018
$905k
NICHD NIH HHS R01 HD084633NIEHS NIH HHS K01 ES025434NIGMS NIH HHS P20 GM103457NLM NIH HHS R01 LM012373NLM NIH HHS R01 LM012907
6 · The paper itself

Abstract

Although driver genes in hepatocellular carcinoma (HCC) have been investigated in various previous genetic studies, prevalence of key driver genes among heterogeneous populations is unknown. Moreover, the phenotypic associations of these driver genes are poorly understood. This report aims to reveal the phenotypic impacts of a group of consensus driver genes in HCC. We used MutSigCV and OncodriveFM modules implemented in the IntOGen pipeline to identify consensus driver genes across six HCC cohorts comprising 1,494 samples in total. To access their global impacts, we used The Cancer Genome Atlas (TCGA) mutations and copy-number variations to predict the transcriptomics data, under generalized linear models. We further investigated the associations of the consensus driver genes to patient survival, age, gender, race, and risk factors. We identify 10 consensus driver genes across six HCC cohorts in total. Integrative analysis of driver mutations, copy-number variations, and transcriptomic data reveals that these consensus driver mutations and their copy-number variations are associated with a majority (62.5%) of the mRNA transcriptome but only a small fraction (8.9%) of miRNAs. Genes associated with

Indexed as

Carcinoma, HepatocellularGenetic Predisposition to DiseaseLiver NeoplasmsOncogenesPhenotypeAlgorithmsComputational BiologyConsensus SequenceGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksGenetic Association StudiesHumansModels, BiologicalMutationTranscriptome

Identifiers

PMID30242023
PMCPMC6542354
OpenAlexW2892147204

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.