ArticlePLoS genetics2017
Trans-ethnic predicted expression genome-wide association analysis identifies a gene for estrogen receptor-negative breast cancer.
Article in PLoS genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.
- Expression- and splicing-based multi-tissue transcriptome-wide association studies identified multiple genes for breast cancer by estrogen-receptor status.Breast cancer research : BCR · 2024Pooled it
- A joint transcriptome-wide association study across multiple tissues identifies candidate breast cancer susceptibility genes.American journal of human genetics · 2023Pooled it
- The Paul Fearn Award for Excellence in Data Sharing in Cancer Control and Population Sciences.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Article
- Multi-tissue transcriptome-wide association studies identified 235 genes for intrinsic subtypes of breast cancer.Journal of the National Cancer Institute · 2024Article
- Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes.Nature communications · 2024Article
- Transforming Diagnosis and Therapeutics Using Cancer Genomics.Cancer treatment and research · 2023Article
- Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer.Cancer causes & control : CCC · 2022Article
- Functional annotation of breast cancer risk loci: current progress and future directions.British journal of cancer · 2022Review
- Aberrant epigenetic and transcriptional events associated with breast cancer risk.Clinical epigenetics · 2022Article
- 'Breast Cancer Resistance Likelihood and Personalized Treatment Through Integrated Multiomics'.Frontiers in molecular biosciences · 2022Review
- Multiple-ancestry genome-wide association study identifies 27 loci associated with measures of hemolysis following blood storage.The Journal of clinical investigation · 2021Article
- Transcriptome-wide association study of breast cancer risk by estrogen-receptor status.Genetic epidemiology · 2020Article
- Up For A Challenge (U4C): Stimulating innovation in breast cancer genetic epidemiology.PLoS genetics · 2017Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Genome-wide association studies (GWAS) have identified more than 90 susceptibility loci for breast cancer, but the underlying biology of those associations needs to be further elucidated. More genetic factors for breast cancer are yet to be identified but sample size constraints preclude the identification of individual genetic variants with weak effects using traditional GWAS methods. To address this challenge, we utilized a gene-level expression-based method, implemented in the MetaXcan software, to predict gene expression levels for 11,536 genes using expression quantitative trait loci and examine the genetically-predicted expression of specific genes for association with overall breast cancer risk and estrogen receptor (ER)-negative breast cancer risk. Using GWAS datasets from a Challenge launched by National Cancer Institute, we identified TP53INP2 (tumor protein p53-inducible nuclear protein 2) at 20q11.22 to be significantly associated with ER-negative breast cancer (Z = -5.013, p = 5.35×10-7, Bonferroni threshold = 4.33×10-6). The association was consistent across four GWAS datasets, representing European, African and Asian ancestry populations. There are 6 single nucleotide polymorphisms (SNPs) included in the prediction of TP53INP2 expression and five of them were associated with estrogen-receptor negative breast cancer, although none of the SNP-level associations reached genome-wide significance. We conducted a replication study using a dataset outside of the Challenge, and found the association between TP53INP2 and ER-negative breast cancer was significant (p = 5.07x10-3). Expression of HP (16q22.2) showed a suggestive association with ER-negative breast cancer in the discovery phase (Z = 4.30, p = 1.70x10-5) although the association was not significant after Bonferroni adjustment. Of the 249 genes that are 250 kb within known breast cancer susceptibility loci identified from previous GWAS, 20 genes (8.0%) were statistically significant associated with ER-negative breast cancer (p<0.05), compared to 582 (5.2%) of 11,287 genes that are not close to previous GWAS loci. This study demonstrated that expression-based gene mapping is a promising approach for identifying cancer susceptibility genes.
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