Evidence map›Paper›PMID 30760197›Full record

ArticleBMC genomics2019

Identification and characterization of genes with absolute mRNA abundances changes in tumor cells with varied transcriptome sizes.

Hao Cai, Xiangyu Li, Jun He, Wenbin Zhou, Kai Song, You Guo, Huaping Liu, Qingzhou Guan, Haidan Yan, Xianlong Wang and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

3 citing papers in PubMed, 6 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

11 authors at 3 institutions in 1 country.

Hao CaiMedical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, 341000, Jiangxi, China.
Xiangyu LiDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, 350122, Fujian, China.
Jun HeDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, 350122, Fujian, China.
Wenbin ZhouDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, Fujian, China.
Kai SongDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, Fujian, China.
You GuoMedical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, 341000, Jiangxi, China.
Huaping LiuMedical Big Data and Bioinformatics Research Centre, First Affiliated Hospital of Gannan Medical University, Ganzhou, 341000, Jiangxi, China.
Qingzhou GuanDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, 350122, Fujian, China.
Haidan YanDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, 350122, Fujian, China.
Xianlong WangDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, 350122, Fujian, China. wang.xianlong@139.com.
Zheng GuoDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, 350122, Fujian, China. guoz@ems.hrbmu.edu.cn.
Fujian Medical University · CNFirst Affiliated Hospital of Gannan Medical University · CNHarbin Medical University · CN

Funding

Joint Scientific and Technology Innovation Fund of Fujian Province 2016Y9044National Natural Science Foundation of China 21534008National Natural Science Foundation of China 61602119National Natural Science Foundation of China 81572935National Natural Science Foundation of China 81602738
6 · The paper itself

Abstract

backgroundThe amount of RNA per cell, namely the transcriptome size, may vary under many biological conditions including tumor. If the transcriptome size of two cells is different, direct comparison of the expression measurements on the same amount of total RNA for two samples can only identify genes with changes in the relative mRNA abundances, i.e., cellular mRNA concentration, rather than genes with changes in the absolute mRNA abundances.

resultsOur recently proposed RankCompV2 algorithm identify differentially expressed genes (DEGs) through comparing the relative expression orderings (REOs) of disease samples with that of normal samples. We reasoned that both the mRNA concentration and the absolute abundances of these DEGs must have changes in disease samples. In simulation experiments, this method showed excellent performance for identifying DEGs between normal and disease samples with different transcriptome sizes. Through analyzing data for ten cancer types, we found that a significantly higher proportion of the DEGs with absolute mRNA abundance changes overlapped or directly interacted with known cancer driver genes and anti-cancer drug targets than that of the DEGs only with mRNA concentration changes alone identified by the traditional methods. The DEGs with increased absolute mRNA abundances were enriched in DNA damage-related pathways, while DEGs with decreased absolute mRNA abundances were enriched in immune and metabolism associated pathways.

conclusionsBoth the mRNA concentration and the absolute abundances of the DEGs identified through REOs comparison change in disease samples in comparison with normal samples. In cancers these genes might play more important upstream roles in carcinogenesis.

Indexed as

Genes, NeoplasmTranscriptomeAlgorithmsComputational BiologyDatabases, GeneticGene Expression Regulation, NeoplasticHumansNeoplasmsPhenotypeRNA, MessengerRNA, NeoplasmRNA, MessengerRNA, NeoplasmAbsolute mRNA abundancesCellular mRNA concentrationDifferentially expressed geneRelative expression ordering

Identifiers

PMID30760197
PMCPMC6374894
OpenAlexW2943601965

What OpenQuestion holds

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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.