Evidence map›Paper›PMID 31402092›Full record

ArticleAmerican journal of human genetics2019

Identifying Putative Susceptibility Genes and Evaluating Their Associations with Somatic Mutations in Human Cancers.

Zhishan Chen, Wanqing Wen, Alicia Beeghly-Fadiel, Xiao-Ou Shu, Virginia Díez-Obrero, Jirong Long, Jiandong Bao, Jing Wang, Qi Liu, Qiuyin Cai and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
5.4field-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

28 citing papers in PubMed, 53 citations in OpenAlex.

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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

13 authors at 4 institutions in 3 countries.

Zhishan ChenDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
Wanqing WenDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
Alicia Beeghly-FadielDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
Xiao-Ou ShuDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
Virginia Díez-ObreroUnit of Biomarkers and Susceptibility, Oncology Data Analytics Program, Catalan Institute of Oncology, Barcelona 08908, Spain; Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute, Barcelona 08908, Spain; Consortium for Biomedical Research in Epidemiology and Public Health, Barcelona 08908, Spain; Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona 08908, Spain.
Jirong LongDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
Jiandong BaoDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA; College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China.
Jing WangCenter for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Qi LiuCenter for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Qiuyin CaiDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
Victor MorenoUnit of Biomarkers and Susceptibility, Oncology Data Analytics Program, Catalan Institute of Oncology, Barcelona 08908, Spain; Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute, Barcelona 08908, Spain; Consortium for Biomedical Research in Epidemiology and Public Health, Barcelona 08908, Spain; Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona 08908, Spain.
Wei ZhengDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
Xingyi GuoDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA. Electronic address: xingyi.guo@vumc.org.
Vanderbilt University · USFujian Agriculture and Forestry University · CNInstitut Català d'Oncologia · ESUniversitat de Barcelona · ES

Funding

Translational Analysis CoreP30DK058404 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI RICHARD M. PEEK · 2002 to 2026
$29.9M
Transcriptome-wide association study to identify susceptibility genes for colorectal cancerR37CA227130 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GUO, XINGYI · 2018 to 2023
$3.7M
Uncovering colorectal cancer etiology and biology by integrating proteomics with other omics dataR01CA269589 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Xingyi Guo, Wei Zheng · 2023 to 2026
$2.9M
NCI NIH HHS R01 CA269589NCI NIH HHS R37 CA227130NIDDK NIH HHS P30 DK058404
6 · The paper itself

Abstract

Genome-wide association studies (GWASs) have identified hundreds of genetic risk variants for human cancers. However, target genes for the majority of risk loci remain largely unexplored. It is also unclear whether GWAS risk-loci-associated genes contribute to mutational signatures and tumor mutational burden (TMB) in cancer tissues. We systematically conducted cis-expression quantitative trait loci (cis-eQTL) analyses for 294 GWAS-identified variants for six major types of cancer-colorectal, lung, ovary, prostate, pancreas, and melanoma-by using transcriptome data from the Genotype-Tissue Expression (GTEx) Project, the Cancer Genome Atlas (TCGA), and other public data sources. By using integrative analysis strategies, we identified 270 candidate target genes, including 99 with previously unreported associations, for six cancer types. By analyzing functional genomic data, our results indicate that 180 genes (66.7% of 270) had evidence of cis-regulation by putative functional variants via proximal promoter or distal enhancer-promoter interactions. Together with our previously reported associations for breast cancer risk, our results show that 24 genes are shared by at least two cancer types, including four genes for both breast and ovarian cancer. By integrating mutation data from TCGA, we found that expression levels of 33 and 66 putative susceptibility genes were associated with specific mutational signatures and TMB of cancer-driver genes, respectively, at a Bonferroni-corrected p < 0.05. Together, these findings provide further insight into our understanding of how genetic risk variants might contribute to carcinogenesis through the regulation of susceptibility genes that are related to the biogenesis of somatic mutations.

Indexed as

Genetic Predisposition to DiseaseMutationGenome-Wide Association StudyHumansNeoplasmsPolymorphism, Single NucleotideQuantitative Trait Locicancer driver genescis-eQTLfunctional variantsgene expressionGWAS-identified variantshuman cancersmutational signaturesusceptibility genestumor mutational burden

Identifiers

PMID31402092
PMCPMC6731359
OpenAlexW2966592965

What OpenQuestion holds

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Registered trials

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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.