Evidence map›Paper›PMID 27398029›Full record

ReviewBiomarkers in cancer2016

Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma.

Ranjit Chauhan, Nivedita Lahiri

Abstract readReview
In one paragraph

Review in Biomarkers in cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 2 pooled it
–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

65 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Long noncoding RNAs as novel serum biomarkers for the diagnosis of hepatocellular carcinoma: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2017
    Pooled it
  2. Pooled it
  3. Spatial Glyco-Codes Define Human Liver Pathology and Progression.bioRxiv : the preprint server for biology · 2026
    Article
  4. Review
  5. Review
  6. HEPPAR1 and PIWIL2 as Panel Markers for Hepatocellular Carcinoma.Asian Pacific journal of cancer prevention : APJCP · 2024
    Article
  7. Bayesian Approach Integrating Prior Knowledge for Identifying miRNA-mRNA Interactions in Hepatocellular Carcinoma.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2023
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. A Bayesian two-step integrative procedure incorporating prior knowledge for the identification of miRNA-mRNAs involved in hepatocellular carcinoma.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2022
    Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

5 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

2 authors.

Ranjit ChauhanMolecular Virology and Hepatology Research Group, Division of BioMedical Sciences, Memorial University of Newfoundland, St. John's, Newfoundland, Canada.; Department of Biology, University of Winnipeg, Winnipeg, Manitoba, Canada.
Nivedita LahiriPfizer Clinical Research Unit, New Haven CT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC), one of the leading causes of cancer deaths in the world, is offering a challenge to human beings, with the current modes of treatment being a palliative approach. Lack of proper curative or preventive treatment methods encouraged extensive research around the world with an aim to detect a vaccine or therapeutic target biomolecule that could lead to development of a drug or vaccine against HCC. Biomarkers or biological disease markers have emerged as a potential tool as drug/vaccine targets, as they can accurately diagnose, predict, and even prevent the diseases. Biomarker expression in tissue, serum, plasma, or urine can detect tumor in very early stages of its development and monitor the cancer progression and also the effect of therapeutic interventions. Biomarker discoveries are driven by advanced techniques, such as proteomics, transcriptomics, whole genome sequencing, micro- and micro-RNA arrays, and translational clinics. In this review, an overview of the potential of tissue- and serum-associated HCC biomarkers as diagnostic, prognostic, and therapeutic targets for drug development is presented. In addition, we highlight recently developed micro-RNA, long noncoding RNA biomarkers, and single-nucleotide changes, which may be used independently or as complementary biomarkers. These active investigations going on around the world aimed at conquering HCC might show a bright light in the near future.

Indexed as

biomarkerHCCliverlncRNAmiRNApreventionprognosistherapeutic

Identifiers

PMID27398029
PMCPMC4933537

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.