Evidence map›Paper›PMID 26483192›Full record

ArticleHuman molecular genetics2015

Identification of shared and unique susceptibility pathways among cancers of the lung, breast, and prostate from genome-wide association studies and tissue-specific protein interactions.

David C Qian, Jinyoung Byun, Younghun Han, Casey S Greene, John K Field, Rayjean J Hung, Yonathan Brhane, John R Mclaughlin, Gordon Fehringer, Maria Teresa Landi and 13 more

Open access · bronzeAbstract read
In one paragraph

Article in Human molecular genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 11% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. A review of post-GWAS studies in schizophrenia.Translational psychiatry · 2025
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
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  11. Article
  12. Review
  13. Article
  14. The statistical properties of gene-set analysis.Nature reviews. Genetics · 2016
    Review
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

23 authors at 16 institutions in 4 countries.

David C QianDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.
Jinyoung ByunDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.
Younghun HanDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.
Casey S GreeneDepartment of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA.
John K FieldDepartment of Molecular and Clinical Cancer Medicine, University of Liverpool Cancer Research Centre, Liverpool L69 3GA, UK.
Rayjean J HungLunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada.
Yonathan BrhaneLunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada.
John R MclaughlinDalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada.
Gordon FehringerLunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada.
Maria Teresa LandiNational Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Albert RosenbergerDepartment of Genetic Epidemiology, University Medical Centre Göttingen, 37099 Göttingen, Germany.
Heike BickeböllerDepartment of Genetic Epidemiology, University Medical Centre Göttingen, 37099 Göttingen, Germany.
Jyoti MalhotraDivision of Hematology and Oncology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Angela RischDivision of Epigenomics and Cancer Risk Factors, German Cancer Research Center, 69120 Heidelberg, Germany.
Joachim HeinrichInstitute of Epidemiology I, German Research Center for Environmental Health, 85764 Neuherberg, Germany.
David J HunterDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
Brian E HendersonDepartment of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
Christopher A HaimanDepartment of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
Fredrick R SchumacherDepartment of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
Rosalind A EelesDepartment of Cancer Genetics, Institute of Cancer Research, London SW7 3RP, UK and.
Douglas F EastonCentre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK.
Daniela SeminaraNational Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Christopher I AmosDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA, christopher.i.amos@dartmouth.edu.
Dartmouth College · USUniversity of Southern California · USMount Sinai Hospital · CAUniversity of Göttingen · DEHarvard University · USHeidelberg University · DEHelmholtz Zentrum München · DEIcahn School of Medicine at Mount Sinai · USInstitute of Cancer Research · GBLunenfeld-Tanenbaum Research Institute · CANational Cancer Institute · USNational Institutes of Health · USPublic Health Ontario · CATranslational Therapeutics (United States) · USUniversity of Cambridge · GBUniversity of Liverpool · GB

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Steven D Leach · 1985 to 2026
$91.3M
Transdisciplinary Research in Cancer of the Lung (TRICL)U19CA148127 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI AMOS, CHRISTOPHER I., LE MARCHAND, LOIC · 2010 to 2014
$10.9M
Epidemiologic StudiesU19CA148065 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI AHSAN, HABIBUL, BRUGGE, JOAN SIEFERT · 2010 to 2014
$10.6M
Epidemiological and Clinical Translational Studies Post Genome-Wide AssociationU19CA148537 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI EASTON, DOUGLAS FREDERICK, EELES, ROSALIND · 2010 to 2014
$10.4M
Training Program for Quantitative Population Sciences in CancerR25CA134286 · NCI · DARTMOUTH COLLEGE · PI KARAGAS, MARGARET RITA, TOSTESON, TOR D · 2009 to 2018
$3.0M
Cancer Research UK 15007Cancer Research UK 17528NCI NIH HHS P30 CA023108NCI NIH HHS R25 CA134286NCI NIH HHS U19 CA148065NCI NIH HHS U19CA148127NCI NIH HHS U19 CA148537
6 · The paper itself

Abstract

Results from genome-wide association studies (GWAS) have indicated that strong single-gene effects are the exception, not the rule, for most diseases. We assessed the joint effects of germline genetic variations through a pathway-based approach that considers the tissue-specific contexts of GWAS findings. From GWAS meta-analyses of lung cancer (12 160 cases/16 838 controls), breast cancer (15 748 cases/18 084 controls) and prostate cancer (14 160 cases/12 724 controls) in individuals of European ancestry, we determined the tissue-specific interaction networks of proteins expressed from genes that are likely to be affected by disease-associated variants. Reactome pathways exhibiting enrichment of proteins from each network were compared across the cancers. Our results show that pathways associated with all three cancers tend to be broad cellular processes required for growth and survival. Significant examples include the nerve growth factor (P = 7.86 × 10(-33)), epidermal growth factor (P = 1.18 × 10(-31)) and fibroblast growth factor (P = 2.47 × 10(-31)) signaling pathways. However, within these shared pathways, the genes that influence risk largely differ by cancer. Pathways found to be unique for a single cancer focus on more specific cellular functions, such as interleukin signaling in lung cancer (P = 1.69 × 10(-15)), apoptosis initiation by Bad in breast cancer (P = 3.14 × 10(-9)) and cellular responses to hypoxia in prostate cancer (P = 2.14 × 10(-9)). We present the largest comparative cross-cancer pathway analysis of GWAS to date. Our approach can also be applied to the study of inherited mechanisms underlying risk across multiple diseases in general.

Indexed as

Breast NeoplasmsFemaleGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyHumansLung NeoplasmsMalePolymorphism, Single NucleotideProstatic Neoplasms

Identifiers

PMID26483192
PMCPMC4664175
OpenAlexW2207695604

What OpenQuestion holds

Textmetadata
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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.