Evidence map›Paper›PMID 31311925›Full record

ArticleNature communications2019

Membrane protein-regulated networks across human cancers.

Chun-Yu Lin, Chia-Hwa Lee, Yi-Hsuan Chuang, Jung-Yu Lee, Yi-Yuan Chiu, Yan-Hwa Wu Lee, Yuh-Jyh Jong, Jenn-Kang Hwang, Sing-Han Huang, Li-Ching Chen and 4 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
4.5field-weighted citation impact, top 4% 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

67 citing papers in PubMed, 121 citations in OpenAlex.

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7 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

14 authors at 5 institutions in 3 countries.

Chun-Yu LinInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.ORCID http://orcid.org/0000-0003-2901-2681
Chia-Hwa LeeSchool of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, Taipei, 110, Taiwan.
Yi-Hsuan ChuangInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Jung-Yu LeeInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Yi-Yuan ChiuInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Yan-Hwa Wu LeeDepartment of Biological Science and Technology, College of Biological Science and Technology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Yuh-Jyh JongDepartment of Biological Science and Technology, College of Biological Science and Technology, National Chiao Tung University, Hsinchu, 300, Taiwan.ORCID http://orcid.org/0000-0002-1735-1101
Jenn-Kang HwangWarshel Institute for Computational Biology, The Chinese University of Hong Kong, 518172, Shenzhen, Guangdong, China.
Sing-Han HuangInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.ORCID http://orcid.org/0000-0003-0289-2260
Li-Ching ChenTMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei, 110, Taiwan.
Chih-Hsiung WuDepartment of Surgery, School of Medicine, College of Medicine, Taipei Medical University, Taipei, 110, Taiwan.
Shih-Hsin TuTMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei, 110, Taiwan.
Yuan-Soon HoSchool of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, Taipei, 110, Taiwan. hoyuansn@tmu.edu.tw.
Jinn-Moon YangInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan. moon@faculty.nctu.edu.tw.
National Yang Ming Chiao Tung University · TWTaipei Medical University Hospital · TWChinese University of Hong Kong, Shenzhen · CNEn Chu Kong Hospital · TWTaipei Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alterations in membrane proteins (MPs) and their regulated pathways have been established as cancer hallmarks and extensively targeted in clinical applications. However, the analysis of MP-interacting proteins and downstream pathways across human malignancies remains challenging. Here, we present a systematically integrated method to generate a resource of cancer membrane protein-regulated networks (CaMPNets), containing 63,746 high-confidence protein-protein interactions (PPIs) for 1962 MPs, using expression profiles from 5922 tumors with overall survival outcomes across 15 human cancers. Comprehensive analysis of CaMPNets links MP partner communities and regulated pathways to provide MP-based gene sets for identifying prognostic biomarkers and druggable targets. For example, we identify CHRNA9 with 12 PPIs (e.g., ERBB2) can be a therapeutic target and find its anti-metastasis agent, bupropion, for treatment in nicotine-induced breast cancer. This resource is a study to systematically integrate MP interactions, genomics, and clinical outcomes for helping illuminate cancer-wide atlas and prognostic landscapes in tumor homo/heterogeneity.

Indexed as

Gene Regulatory NetworksAnimalsAntineoplastic AgentsBiomarkers, TumorBupropionCell Line, TumorDatasets as TopicFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMiceNeoplasmsNicotinic AntagonistsPrognosisAntineoplastic AgentsBiomarkers, TumorBupropionCHRNA9 protein, humanNicotinic AntagonistsReceptors, Nicotinic

Identifiers

PMID31311925
PMCPMC6635409
OpenAlexW2956357290

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.