Evidence map›Paper›PMID 24141781›Full record

ArticleOncogene2014

Identification of latent biomarkers in hepatocellular carcinoma by ultra-deep whole-transcriptome sequencing.

K-T Lin, Y-J Shann, G-Y Chau, C-N Hsu, C-Y F Huang

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Oncogene, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Integrative module analysis of HCC gene expression landscapes.Experimental and therapeutic medicine · 2020
    Article
  12. Alternative Splicing in Hepatocellular Carcinoma.Cellular and molecular gastroenterology and hepatology · 2020
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

K-T LinInstitute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan.
Y-J ShannInstitute of Biopharmaceutical Sciences, National Yang-Ming University, Taipei, Taiwan.
G-Y ChauDivision of General Surgery, Department of Surgery, Taipei Veterans General Hospital, Taipei, Taiwan.
C-N Hsu1] Institute of Information Science, Academia Sinica, Taipei, Taiwan [2] USC/Information Sciences Institute, Marina del Rey, CA, USA [3] Division of Biomedical Informatics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
C-Y F Huang1] Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan [2] Institute of Biopharmaceutical Sciences, National Yang-Ming University, Taipei, Taiwan [3] Cancer Research Center and Genome Research Center, National Yang-Ming University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is an urgent need to identify biomarkers for hepatocellular carcinoma due to limited treatment options and the poor prognosis of this common lethal disease. Whole-transcriptome shotgun sequencing (RNA-Seq) provides new possibilities for biomarker identification. We sequenced ∼250 million pair-end reads from a pair of adjacent normal and tumor liver samples. With the aid of bioinformatics tools, we determined the transcriptome landscape and sought novel biomarkers by further empirical validations in 55 pairs of adjacent normal and tumor liver samples with various viral statuses such as HBV(+), HCV(+) and HBV(-)HCV(-). We identified a novel gene with coding regions, termed DUNQU1, which has a tissue-specific expression pattern in tumor liver samples of HCV(+) and HBV(-)HCV(-) hepatocellular carcinomas. Overexpression of DUNQU1 in Huh7 cell lines enhances the ability to form colonies in soft agar. Also, we identified three novel differentially-expressed protein-coding genes (ALG1L, SERPINA11 and TMEM82) that lack documented expression profiles in liver cancer and showed that the level of SREPINA11 is correlated with pathology stages. Moreover, we showed that the alternative splicing event of FGFR2 is associated with virus infection, tumor size, cirrhosis and tumor recurrence. The findings indicate that these new markers of hepatocellular carcinoma may be of value in improving prognosis and could have potential as new targets for developing new treatment options.

Indexed as

TranscriptomeAlternative SplicingBiomarkers, TumorCarcinoma, HepatocellularCell Line, TumorFemaleHigh-Throughput Nucleotide SequencingHumansLiverLiver NeoplasmsMaleOrgan SpecificityProtein IsoformsReceptor, Fibroblast Growth Factor, Type 2Sequence Analysis, DNABiomarkers, TumorFGFR2 protein, humanProtein IsoformsReceptor, Fibroblast Growth Factor, Type 2

Identifiers

PMID24141781

What OpenQuestion holds

Textmetadata
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.