Evidence map›Paper›PMID 29486777›Full record

ArticleGenome medicine2018

Weak sharing of genetic association signals in three lung cancer subtypes: evidence at the SNP, gene, regulation, and pathway levels.

Timothy D O'Brien, Peilin Jia, Neil E Caporaso, Maria Teresa Landi, Zhongming Zhao

Abstract read
In one paragraph

Article in Genome medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
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

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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

29 citing papers in PubMed.

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  19. Association ofTranslational pediatrics · 2021
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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

5 authors.

Timothy D O'BrienVanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA.
Peilin JiaCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin St. Suite 820, Houston, TX, 77030, USA.
Neil E CaporasoDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Maria Teresa LandiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Zhongming ZhaoVanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA. zhongming.zhao@uth.tmc.edu.

Funding

Transforming dbGaP genetic and genomic data to FAIR-ready by artificial intelligence and machine learning algorithmsR01LM012806 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Zhongming Zhao · 2017 to 2026
$3.7M
Training Program on Genetic Variation and Human PhenotypesT32GM080178 · NIGMS · VANDERBILT UNIVERSITY · PI COX, NANCY J, SAMUELS, DAVID C · 2007 to 2021
$3.1M
Mapping the Genetic Architecture of Complex Disease via RNA-seq and GWAS DataR01LM011177 · NLM · VANDERBILT UNIVERSITY · PI ZHAO, ZHONGMING · 2012 to 2014
$1.0M
NIGMS NIH HHS T32 GM080178NIGMS NIH HHS T32GM080178NIH HHS R01LM011177NIH HHS R01LM012806NLM NIH HHS R01 LM011177NLM NIH HHS R01 LM012806
6 · The paper itself

Abstract

backgroundThere are two main types of lung cancer: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). NSCLC has many subtypes, but the two most common are lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). These subtypes are mainly classified by physiological and pathological characteristics, although there is increasing evidence of genetic and molecular differences as well. Although some work has been done at the somatic level to explore the genetic and biological differences among subtypes, little work has been done that interrogates these differences at the germline level to characterize the unique and shared susceptibility genes for each subtype.

methodsWe used single-nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) of European samples to interrogate the similarity of the subtypes at the SNP, gene, pathway, and regulatory levels. We expanded these genotyped SNPs to include all SNPs in linkage disequilibrium (LD) using data from the 1000 Genomes Project. We mapped these SNPs to several lung tissue expression quantitative trait loci (eQTL) and enhancer datasets to identify regulatory SNPs and their target genes. We used these genes to perform a biological pathway analysis for each subtype.

resultsWe identified 8295, 8734, and 8361 SNPs with moderate association signals for LUAD, LUSC, and SCLC, respectively. Those SNPs had p < 1 × 10

conclusionsOur results suggest that the three lung cancer subtypes do not share much genetic signal at the SNP, gene, pathway, or regulatory level, which differs from the common subtype classification based upon histology. However, three (CHRNA5, IDH3A, and PSMA4) of the five genes shared between the subtypes are well-known lung cancer genes that may act as general lung cancer genes regardless of subtype.

Indexed as

Gene Expression Regulation, NeoplasticGenome-Wide Association StudyEnhancer Elements, GeneticEpigenesis, GeneticGerm CellsHumansLinkage DisequilibriumLungLung NeoplasmsPolymorphism, Single NucleotidePrincipal Component AnalysisQuantitative Trait LociEnhancereQTLFunctional genomicsGWASLung cancer subtypePathway analysis

Identifiers

PMID29486777
PMCPMC5828003

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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.