Evidence map›Paper›PMID 30251028›Full record

ArticleFunctional & integrative genomics2019

Integrated analysis of transcription factors and targets co-expression profiles reveals reduced correlation between transcription factors and target genes in cancer.

Jinsheng Liang, Ying Cui, Yuhuan Meng, Xingsong Li, Xueping Wang, Wanli Liu, Lizhen Huang, Hongli Du

Abstract read
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In one paragraph

Article in Functional & integrative genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

5 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

8 authors at 2 institutions in 1 country.

Jinsheng LiangSchool of Biology and Biological Engineering, South China University of Technology, 382 Zhonghuan Road East, Panyu District, Guangzhou Higher Education Mega Centre, Guangzhou, 510006, Guangdong, China.
Ying CuiSchool of Biology and Biological Engineering, South China University of Technology, 382 Zhonghuan Road East, Panyu District, Guangzhou Higher Education Mega Centre, Guangzhou, 510006, Guangdong, China.
Yuhuan MengSchool of Biology and Biological Engineering, South China University of Technology, 382 Zhonghuan Road East, Panyu District, Guangzhou Higher Education Mega Centre, Guangzhou, 510006, Guangdong, China.
Xingsong LiSchool of Biology and Biological Engineering, South China University of Technology, 382 Zhonghuan Road East, Panyu District, Guangzhou Higher Education Mega Centre, Guangzhou, 510006, Guangdong, China.
Xueping WangDepartment of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Wanli LiuDepartment of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Lizhen HuangSchool of Biology and Biological Engineering, South China University of Technology, 382 Zhonghuan Road East, Panyu District, Guangzhou Higher Education Mega Centre, Guangzhou, 510006, Guangdong, China.
Hongli DuSchool of Biology and Biological Engineering, South China University of Technology, 382 Zhonghuan Road East, Panyu District, Guangzhou Higher Education Mega Centre, Guangzhou, 510006, Guangdong, China. hldu@scut.edu.cn.ORCID http://orcid.org/0000-0002-6419-0160
South China University of Technology · CNSun Yat-sen University · CN

Funding

National key research and development program SQ2018YFC090062Science and Technology Planning Project of Guangzhou 201704020176, 201508020040, 201510010044the Fundamental Research Funds for the Central Universities 2015ZZ125
6 · The paper itself

Abstract

Transcription factors are recognized as the key regulators of gene expression. However, the changes in the correlation of transcription factors and their target genes between normal and tumor tissues are usually ignored. In this research, we used mRNA expression profile data from The Cancer Genome Atlas which included 5726 samples across 11 major human cancers to perform co-expression analysis by the Pearson correlation coefficients. Then, integrating 81,357 pairs of transcription factors and target genes from transcription factors databases to find out the changes in the co-expression correlation of these gene pairs from normal to tumor tissues. Based on the changes in the number of co-expressed TF-TG pairs and changes in the level of co-expression, we found the generally reduced correlation between transcription factors and their target genes in cancer. Additionally, we screened out universal and specific transcription factors-target genes pairs which may significant influence particular cancer. Then, we obtained 423 cancer cell line expression profiles from Broad Institute Cancer Cell Line Encyclopedia to verify our results. Some of these pairs like XRCC5-XRCC6 have been reported to involve in multiple cancers, while pairs like IRF1-PSMB9 without any previous articles related to tumor but involve in the biological processes of cancer, which are of great potential to be therapeutic targets. Our research may provide insights to better understand the tumor development mechanisms and find potential therapeutic targets.

Indexed as

Gene Expression Regulation, NeoplasticAtlases as TopicCarcinogenesisCell Line, TumorCysteine EndopeptidasesDatabases, GeneticGene OntologyGene Regulatory NetworksGenome, HumanHumansInterferon Regulatory Factor-1Ku AutoantigenMicroRNAsMolecular Sequence AnnotationNeoplasm ProteinsNeoplasmsCysteine EndopeptidasesInterferon Regulatory Factor-1IRF1 protein, humanKu AutoantigenLMP-2 proteinMicroRNAsNeoplasm ProteinsRNA, MessengerTranscription FactorsXRCC5 protein, humanXrcc6 protein, humanCo-expressionIntegrative analysisTherapeutic targetTranscription factorTumorigenesis

Identifiers

PMID30251028
OpenAlexW2893144798

What OpenQuestion holds

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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.