Evidence map›Paper›PMID 26384826›Full record

ReviewCellular oncology (Dordrecht, Netherlands)2015

Consensus reference gene(s) for gene expression studies in human cancers: end of the tunnel visible?

R N Sharan, S Thangminlal Vaiphei, Saibadaiahun Nongrum, Joshua Keppen, Mandahakani Ksoo

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cellular oncology (Dordrecht, Netherlands), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Inhibition monitoring in veterinary molecular testing.Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2020
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

5 authors.

R N SharanRadiation and Molecular Biology Unit, Department of Biochemistry, North-Eastern Hill University (NEHU), Shillong, 793022, India. rnsharan@nehu.ac.in.ORCID http://orcid.org/0000-0002-7120-8023
S Thangminlal VaipheiRadiation and Molecular Biology Unit, Department of Biochemistry, North-Eastern Hill University (NEHU), Shillong, 793022, India.
Saibadaiahun NongrumRadiation and Molecular Biology Unit, Department of Biochemistry, North-Eastern Hill University (NEHU), Shillong, 793022, India.
Joshua KeppenRadiation and Molecular Biology Unit, Department of Biochemistry, North-Eastern Hill University (NEHU), Shillong, 793022, India.
Mandahakani KsooRadiation and Molecular Biology Unit, Department of Biochemistry, North-Eastern Hill University (NEHU), Shillong, 793022, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGene expression studies are increasingly used to provide valuable information on the diagnosis and prognosis of human cancers. Also, for in vitro and in vivo experimental cancer models gene expression studies are widely used. The complex algorithms of differential gene expression analyses require normalization of data against a reference or normalizer gene, or a set of such genes. For this purpose, mostly invariant housekeeping genes are used. Unfortunately, however, there are no consensus (housekeeping) genes that serve as reference or normalizer for different human cancers. In fact, scientists have employed a wide range of reference genes across different types of cancer for normalization of gene expression data. As a consequence, comparisons of these data and/or data harmonizations are difficult to perform and challenging. In addition, an inadequate choice for a reference gene may obscure genuine changes and/or result in erroneous gene expression data comparisons.

methodsIn our effort to highlight the importance of selecting the most appropriate reference gene(s), we have screened the literature for gene expression studies published since the turn of the century on thirteen of the most prevalent human cancers worldwide.

conclusionsBased on the analysis of the data at hand, we firstly recommend that in each study the suitability of candidate reference gene(s) should carefully be evaluated in order to yield reliable differential gene expression data. Secondly, we recommend that a combination of PPIA and either GAPDH, ACTB, HPRT and TBP, or appropriate combinations of two or three of these genes, should be employed in future studies, to ensure that results from different studies on different human cancers can be harmonized. This approach will ultimately increase the depth of our understanding of gene expression signatures across human cancers.

Indexed as

Genes, EssentialReference StandardsAlgorithmsGene Expression ProfilingHumansNeoplasmsEndogenous controlsGene expressionHuman cancersNormalizer genesqPCRReference genes

Identifiers

PMID26384826
PMCPMC13004251

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.