ArticleFrontiers in oncology2019
Cross-Cancer Pleiotropic Analysis Reveals Novel Susceptibility Loci for Lung Cancer.
Article in Frontiers in oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- In Silico Pleiotropy Analysis in KEGG Signaling Networks Using a Boolean Network Model.Biomolecules · 2022Article
- Polymorphisms in DNA Repair and Xenobiotic Biotransformation Enzyme Genes and Lung Cancer Risk in Coal Mine Workers.Life (Basel, Switzerland) · 2022Article
- Genetic evaluation of the variants using MassARRAY in non-small cell lung cancer among North Indians.Scientific reports · 2021Article
- Detection of loci exhibiting pleiotropic effects on body weight and egg number in female broilers.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with cancer risk, several of which have shown pleiotropic effects across cancers. Therefore, we performed a systematic cross-cancer pleiotropic analysis to detect the effects of GWAS-identified variants from non-lung cancers on lung cancer risk in 12,843 cases and 12,639 controls from four lung cancer GWASs. The overall association between variants in each cancer and risk of lung cancer was explored using sequential kernel association test (SKAT) analysis. For single variant analysis, we combined the result of specific study using fixed-effect meta-analysis. We performed functional exploration of significant associations based on features from public databases. To further detect the biological mechanism underlying identified observations, pathway enrichment analysis were conducted with R package "clusterProfiler." SNP-set analysis revealed the overall associations between variants of 8 cancer types and lung cancer risk. Single variant analysis identified 6 novel SNPs related to lung cancer risk after multiple correction (
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