Evidence map›Paper›PMID 20385424›Full record

ReviewJournal of hepatology2010

Cancer gene discovery in hepatocellular carcinoma.

Lars Zender, Augusto Villanueva, Victoria Tovar, Daniela Sia, Derek Y Chiang, Josep M Llovet

Open access · greenAbstract readReview
In one paragraph

Review in Journal of hepatology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing papers in PubMed
8.2field-weighted citation impact, top 2% 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

86 citing papers in PubMed, 183 citations in OpenAlex.

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

26 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

6 authors at 3 institutions in 3 countries.

Lars ZenderHelmholtz Centre for Infection Research, Braunschweig 38124, Germany.
Augusto Villanueva
Victoria Tovar
Daniela Sia
Derek Y Chiang
Josep M Llovet
Consorci Institut D'Investigacions Biomediques August Pi I Sunyer · ESHelmholtz Centre for Infection Research · DEUNC Lineberger Comprehensive Cancer Center

Funding

Integrative genomic analysis in hepatocellular carcinomaR01DK076986 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI LLOVET, JOSEP M · 2007 to 2011
$1.3M
NIDDK NIH HHS R01 DK076986
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a deadly cancer, whose incidence is increasing worldwide. Albeit the main risk factors for HCC development have been clearly identified, such as hepatitis B and C virus infection and alcohol abuse, there is still preliminary understanding of the key drivers of this malignancy. Recent data suggest that genomic analysis of cirrhotic tissue - the pre-neoplastic carcinogenic field - may provide a read-out to identify at risk populations for cancer development. Given this contextual complexity, it is of utmost importance to characterize the molecular pathogenesis of this disease, and pinpoint the dominant pathways/drivers by integrative oncogenomic approaches and/or sophisticated experimental models. Identification of the dominant proliferative signals and key aberrations will allow for a more personalized therapy. Pathway-based approaches and functional experimental studies have aided in identifying the activation of different signaling cascades in HCC (e.g. epidermal growth factor, insulin-like growth factor, RAS, MTOR, WNT-betacatenin, etc.). However, the introduction of new high-throughput genomic technologies (e.g. microarrays, deep sequencing, etc.), and increased sophistication of computational biology (e.g. bioinformatics, biomodeling, etc.), opens the field to new strategies in oncogene and tumor suppressor discovery. These oncogenomic approaches are framed within emerging new disciplines such as systems biology, which integrates multiple inputs to explain cancer onset and progression. In addition, the consolidation of sophisticated animal models, such as mosaic cancer mouse models or the use of transposons for mutagenesis screens, have been instrumental for the identification of novel tumor drivers. We herein review some classical as well as some recent fast track approaches for oncogene discovery in HCC, and provide a comprehensive landscape of the currently known spectrum of molecular aberrations involved in hepatocarcinogenesis.

Indexed as

Gene Expression Regulation, NeoplasticAnimalsCarcinoma, HepatocellularDisease Models, AnimalHumansLiver NeoplasmsMiceSignal Transduction

Identifiers

PMID20385424
PMCPMC2905725
OpenAlexW2077986225

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.