Evidence map›Paper›PMID 31138119›Full record

ArticleBMC bioinformatics2019

Conventionally used reference genes are not outstanding for normalization of gene expression in human cancer research.

Jihoon Jo, Sunkyung Choi, Jooseong Oh, Sung-Gwon Lee, Song Yi Choi, Kee K Kim, Chungoo Park

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

35 citing papers in PubMed, 61 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Jihoon JoSchool of Biological Sciences and Technology, Chonnam National University, 77 Yongbong-Ro, Buk-Ku, GwangJu, 61186, Republic of Korea.
Sunkyung ChoiDepartment of Biochemistry, Chungnam National University, 99 Daehak-Ro, Yuseong-Ku, Daejeon, 34134, Republic of Korea.
Jooseong OhSchool of Biological Sciences and Technology, Chonnam National University, 77 Yongbong-Ro, Buk-Ku, GwangJu, 61186, Republic of Korea.
Sung-Gwon LeeSchool of Biological Sciences and Technology, Chonnam National University, 77 Yongbong-Ro, Buk-Ku, GwangJu, 61186, Republic of Korea.
Song Yi ChoiDepartment of Pathology, Chungnam National University, 282 Munhwa-Ro, Jung-Ku, Daejeon, 35015, Republic of Korea. sychoi@cnu.ac.kr.
Kee K KimDepartment of Biochemistry, Chungnam National University, 99 Daehak-Ro, Yuseong-Ku, Daejeon, 34134, Republic of Korea. kimkk@cnu.ac.kr.
Chungoo ParkSchool of Biological Sciences and Technology, Chonnam National University, 77 Yongbong-Ro, Buk-Ku, GwangJu, 61186, Republic of Korea. chungoo@jnu.ac.kr.
Chonnam National University · KRChungnam National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe selection of reference genes is essential for quantifying gene expression. Theoretically they should be expressed stably and not regulated by experimental or pathological conditions. However, identification and validation of reference genes for human cancer research are still being regarded as a critical point, because cancerous tissues often represent genetic instability and heterogeneity. Recent pan-cancer studies have demonstrated the importance of the appropriate selection of reference genes for use as internal controls for the normalization of gene expression; however, no stably expressed, consensus reference genes valid for a range of different human cancers have yet been identified.

resultsIn the present study, we used large-scale cancer gene expression datasets from The Cancer Genome Atlas (TCGA) database, which contains 10,028 (9,364 cancerous and 664 normal) samples from 32 different cancer types, to confirm that the expression of the most commonly used reference genes is not consistent across a range of cancer types. Furthermore, we identified 38 novel candidate reference genes for the normalization of gene expression, independent of cancer type. These genes were found to be highly expressed and highly connected to relevant gene networks, and to be enriched in transcription-translation regulation processes. The expression stability of the newly identified reference genes across 29 cancerous and matched normal tissues were validated via quantitative reverse transcription PCR (RT-qPCR).

conclusionsWe reveal that most commonly used reference genes in current cancer studies cannot be appropriate to serve as representative control genes for quantifying cancer-related gene expression levels, and propose in this study three potential reference genes (HNRNPL, PCBP1, and RER1) to be the most stably expressed across various cancerous and normal human tissues.

Indexed as

Biomedical ResearchGene Expression Regulation, NeoplasticGenesAdaptor Proteins, Vesicular TransportDatabases, GeneticGene Expression ProfilingHumansMembrane GlycoproteinsNeoplasmsReal-Time Polymerase Chain ReactionReference StandardsReproducibility of ResultsAdaptor Proteins, Vesicular TransportMembrane GlycoproteinsRER1 protein, humanHuman cancerReference genesRT-qPCR

Identifiers

PMID31138119
PMCPMC6538551
OpenAlexW2946858259

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LicenceCC BY
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Registered trials

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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.