Evidence map›Paper›PMID 31806877›Full record

ArticleBritish journal of cancer2020

Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function.

Maud Fagny, John Platig, Marieke Lydia Kuijjer, Xihong Lin, John Quackenbush

Open access · hybridAbstract read
In one paragraph

Article in British journal of cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 13% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Association BetweenGenetics research · 2025
    Pooled it
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  12. A catalog of curated breast cancer genes.Breast cancer research and treatment · 2022
    Article
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  15. Article
  16. Article
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  19. Molecular Alterations in Gastric Intestinal Metaplasia.International journal of molecular sciences · 2021
    Review
  20. The Panorama of Cancer Genetics.Cancer research · 2021
    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 at 3 institutions in 3 countries.

Maud FagnyGenetique Quantitative et Evolution-Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, Paris, France.
John PlatigChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Marieke Lydia KuijjerDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
Xihong LinDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
John QuackenbushChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA. johnq@hsph.harvard.edu.ORCID http://orcid.org/0000-0002-2702-5879
Brigham and Women's Hospital · USHarvard University · USUniversité Paris-Sud · FR

Funding

VectorP30CA006516 · NCI · DANA-FARBER CANCER INSTITUTE · PI A. Heather Eliassen · 1985 to 2026
$330.6M
Tissue and Pathology ResourcesP50CA127003 · NCI · DANA-FARBER CANCER INST · PI EL-BARDEESY, NABEEL, SELLERS, WILLIAM R · 2007 to 2023
$33.2M
Respiratory Computational Discovery CoreP01HL114501 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI CHOI, MARY E · 2013 to 2025
$24.9M
Systems Biology, Bioinformatics, and BiostatisticsP01HL105339 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2011 to 2015
$12.2M
Statistical Methods for Analysis of Massive Genetic and Genomic Data in Cancer ResearchR35CA197449 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI XIHONG LIN · 2015 to 2026
$10.9M
Chemical Inhibitors to Define an Essential M. Tuberculosis Signaling NetworkR01AI099204 · NIAID · BOSTON CHILDREN'S HOSPITAL · PI HUSSON, ROBERT N · 2012 to 2016
$6.1M
Unraveling the Complexities of Risk and Mechanism in CancerR35CA220523 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI QUACKENBUSH, JOHN · 2018 to 2024
$6.0M
Using Networks to Assign Gene Function in Lung DiseaseR01HL111759 · NHLBI · DANA-FARBER CANCER INST · PI QUACKENBUSH, JOHN, SILVERMAN, EDWIN K · 2012 to 2015
$3.4M
Genotype and Imaging Phenotype Biomarkers in Lung CancerU01CA190234 · NCI · DANA-FARBER CANCER INST · PI AERTS, HUGO, QUACKENBUSH, JOHN · 2015 to 2019
$3.3M
Context matters: Network modeling of COPD regulatory variants across tissues and exposuresK25HL140186 · NHLBI · UNIVERSITY OF VIRGINIA · PI PLATIG, JOHN · 2018 to 2022
$926k
NCI NIH HHS P30 CA006516NCI NIH HHS P50 CA127003NCI NIH HHS R35 CA197449NCI NIH HHS R35 CA220523NCI NIH HHS U01 CA190234NHLBI NIH HHS P01 HL105339NHLBI NIH HHS P01 HL114501NHLBI NIH HHS R01 HL111759NIAID NIH HHS R01 AI099204U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) 1R35CA197449U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) 5P50CA127003U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID) 5R01AI099204
6 · The paper itself

Abstract

backgroundGenome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. However, how these SNPs affect cancer risk is still largely unknown.

methodsWe used a systems biology approach to analyse the regulatory role of cancer-risk SNPs in thirteen tissues. By using data from the Genotype-Tissue Expression (GTEx) project, we performed an expression quantitative trait locus (eQTL) analysis. We represented both significant cis- and trans-eQTLs as edges in tissue-specific eQTL bipartite networks.

resultsEach tissue-specific eQTL network is organised into communities that group sets of SNPs and functionally related genes. When mapping cancer-risk SNPs to these networks, we find that in each tissue, these SNPs are significantly overrepresented in communities enriched for immune response processes, as well as tissue-specific functions. Moreover, cancer-risk SNPs are more likely to be 'cores' of their communities, influencing the expression of many genes within the same biological processes. Finally, cancer-risk SNPs preferentially target oncogenes and tumour-suppressor genes, suggesting that they may alter the expression of these key cancer genes.

conclusionsThis approach provides a new way of understanding genetic effects on cancer risk and provides a biological context for interpreting the results of GWAS cancer studies.

Indexed as

Genes, Tumor SuppressorPolymorphism, Single NucleotideGenetic Predisposition to DiseaseHumansNeoplasmsOncogenesQuantitative Trait Loci

Identifiers

PMID31806877
PMCPMC7028992
OpenAlexW2992457023

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.