Genetic variants of genes in the NER pathway associated with risk of breast cancer: A large‐scale analysis of 14 published GWAS datasets in the DRIVE study
A recent hypothesis‐free pathway‐level analysis of genome‐wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no d...
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| Published in | International journal of cancer Vol. 145; no. 5; pp. 1270 - 1279 |
|---|---|
| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Hoboken, USA
John Wiley & Sons, Inc
01.09.2019
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0020-7136 1097-0215 1097-0215 |
| DOI | 10.1002/ijc.32371 |
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| Abstract | A recent hypothesis‐free pathway‐level analysis of genome‐wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta‐analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis‐driven approach, we selected 138 candidate genes from the NER pathway using the “Molecular Signatures Database (MsigDB)” and “PathCards”. All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta‐analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM‐ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03–1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89–0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03–1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90–0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08–1.16, ptrend < 0.0001). The eQTL analysis revealed that BIVM‐ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10−22, respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression.
What's new?
Although breast carcinogenesis is still not fully understood, a variety of risk factors have been identified, some of them with mechanisms likely involved in DNA damage and repair. This study identified four novel independent SNPs in the nucleotide excision repair (NER) pathway genes (BIVM‐ERCC5 rs1323697_C, GTF2H4 rs1264308_T, COPS2 rs141308737_C deletion and ELL rs1469412_C) to be associated with breast cancer risk. BIVM‐ERCC5 rs1323697_C and ELL rs1469412_C alleles were correlated with increased mRNA expression. These findings suggest that variants in the NER pathway genes play an important role in the development of breast cancer, possibly by influencing gene expression. |
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| AbstractList | A recent hypothesis‐free pathway‐level analysis of genome‐wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta‐analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis‐driven approach, we selected 138 candidate genes from the NER pathway using the “Molecular Signatures Database (MsigDB)” and “PathCards”. All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta‐analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk,
BIVM‐ERCC5
rs1323697_C (OR = 1.06, 95% CI = 1.03–1.10),
GTF2H4
rs1264308_T (OR = 0.93, 95% CI = 0.89–0.97),
COPS2
rs141308737_C deletion (OR = 1.06, 95% CI = 1.03–1.09) and
ELL
rs1469412_C (OR = 0.93, 95% CI = 0.90–0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08–1.16,
p
trend
< 0.0001). The eQTL analysis revealed that
BIVM‐ERCC5
rs1323697 C and
ELL
rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (
p
= 0.022 and 2.67 × 10
−22
, respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression.
What's new?
Although breast carcinogenesis is still not fully understood, a variety of risk factors have been identified, some of them with mechanisms likely involved in DNA damage and repair. This study identified four novel independent SNPs in the nucleotide excision repair (NER) pathway genes (
BIVM‐ERCC5
rs1323697_C,
GTF2H4
rs1264308_T,
COPS2
rs141308737_C deletion and
ELL
rs1469412_C) to be associated with breast cancer risk.
BIVM‐ERCC5
rs1323697_C and
ELL
rs1469412_C alleles were correlated with increased mRNA expression. These findings suggest that variants in the NER pathway genes play an important role in the development of breast cancer, possibly by influencing gene expression. A recent hypothesis-free pathway-level analysis of genome-wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta-analysis of 14 previously published GWAS datasets in the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Study with 53107 European descent. Using a hypothesis-driven approach, we selected 138 candidate genes from the NER pathway using the “Molecular Signatures Database (MsigDB)” and “PathCards”. All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta-analysis using the false discovery rate (FDR) for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM-ERCC5 rs1323697_C (OR=1.06, 95% CI=1.03–1.10), GTF2H4 rs1264308_T (OR=0.93, 95% CI=0.89–0.97), COPS2 rs141308737_C deletion (OR=1.06, 95% CI=1.03–1.09) and ELL rs1469412_C (OR=0.93, 95% CI=0.90–0.96). Their combined genetic score was also associated with BC risk (OR=1.12, 95% CI=1.08–1.16, P trend <0.0001). The eQTL analysis revealed that BIVM-ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression of their genes in 373 lymphoblastoid cell lines ( P =0.022 and 2.67×10 −22 , respectively). These SNPs might have biological roles in the BC etiology, likely through modulating their corresponding gene expression. A recent hypothesis-free pathway-level analysis of genome-wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta-analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis-driven approach, we selected 138 candidate genes from the NER pathway using the "Molecular Signatures Database (MsigDB)" and "PathCards". All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta-analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM-ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03-1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89-0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03-1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90-0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08-1.16, p < 0.0001). The eQTL analysis revealed that BIVM-ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10 , respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression. A recent hypothesis‐free pathway‐level analysis of genome‐wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta‐analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis‐driven approach, we selected 138 candidate genes from the NER pathway using the “Molecular Signatures Database (MsigDB)” and “PathCards”. All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta‐analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM‐ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03–1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89–0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03–1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90–0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08–1.16, ptrend < 0.0001). The eQTL analysis revealed that BIVM‐ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10−22, respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression. What's new? Although breast carcinogenesis is still not fully understood, a variety of risk factors have been identified, some of them with mechanisms likely involved in DNA damage and repair. This study identified four novel independent SNPs in the nucleotide excision repair (NER) pathway genes (BIVM‐ERCC5 rs1323697_C, GTF2H4 rs1264308_T, COPS2 rs141308737_C deletion and ELL rs1469412_C) to be associated with breast cancer risk. BIVM‐ERCC5 rs1323697_C and ELL rs1469412_C alleles were correlated with increased mRNA expression. These findings suggest that variants in the NER pathway genes play an important role in the development of breast cancer, possibly by influencing gene expression. A recent hypothesis‐free pathway‐level analysis of genome‐wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta‐analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis‐driven approach, we selected 138 candidate genes from the NER pathway using the “Molecular Signatures Database (MsigDB)” and “PathCards”. All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta‐analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM‐ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03–1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89–0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03–1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90–0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08–1.16, ptrend < 0.0001). The eQTL analysis revealed that BIVM‐ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10−22, respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression. A recent hypothesis-free pathway-level analysis of genome-wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta-analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis-driven approach, we selected 138 candidate genes from the NER pathway using the "Molecular Signatures Database (MsigDB)" and "PathCards". All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta-analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM-ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03-1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89-0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03-1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90-0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08-1.16, ptrend < 0.0001). The eQTL analysis revealed that BIVM-ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10-22 , respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression.A recent hypothesis-free pathway-level analysis of genome-wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta-analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis-driven approach, we selected 138 candidate genes from the NER pathway using the "Molecular Signatures Database (MsigDB)" and "PathCards". All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta-analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM-ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03-1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89-0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03-1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90-0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08-1.16, ptrend < 0.0001). The eQTL analysis revealed that BIVM-ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10-22 , respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression. |
| Author | Wang, Xiaomeng Moorman, Patricia G. Wei, Qingyi Hwang, Shelley Qian, Danwen Liu, Hongliang Luo, Sheng Ge, Jie |
| AuthorAffiliation | 1 Department of Epidemiology and Statistics, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China 5 Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27710, USA 2 Duke Cancer Institute, Duke University Medical Center, Durham, NC 27710, USA 4 Department of Community and Family Medicine, Duke University Medical Center, Durham, NC 27710, USA 7 Department of Medicine, Duke University School of Medicine, Durham, NC 27710, USA 6 Department of Surgery, Duke University School of Medicine, Durham, NC 27710, USA 3 Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27710, USA |
| AuthorAffiliation_xml | – name: 7 Department of Medicine, Duke University School of Medicine, Durham, NC 27710, USA – name: 5 Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27710, USA – name: 6 Department of Surgery, Duke University School of Medicine, Durham, NC 27710, USA – name: 4 Department of Community and Family Medicine, Duke University Medical Center, Durham, NC 27710, USA – name: 1 Department of Epidemiology and Statistics, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China – name: 2 Duke Cancer Institute, Duke University Medical Center, Durham, NC 27710, USA – name: 3 Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27710, USA |
| Author_xml | – sequence: 1 givenname: Jie surname: Ge fullname: Ge, Jie organization: Duke University School of Medicine – sequence: 2 givenname: Hongliang surname: Liu fullname: Liu, Hongliang organization: Duke University School of Medicine – sequence: 3 givenname: Danwen surname: Qian fullname: Qian, Danwen organization: Duke University School of Medicine – sequence: 4 givenname: Xiaomeng surname: Wang fullname: Wang, Xiaomeng organization: Duke University School of Medicine – sequence: 5 givenname: Patricia G. surname: Moorman fullname: Moorman, Patricia G. organization: Duke University Medical Center – sequence: 6 givenname: Sheng orcidid: 0000-0003-4214-5809 surname: Luo fullname: Luo, Sheng organization: Duke University School of Medicine – sequence: 7 givenname: Shelley surname: Hwang fullname: Hwang, Shelley organization: Duke University School of Medicine – sequence: 8 givenname: Qingyi orcidid: 0000-0002-3845-9445 surname: Wei fullname: Wei, Qingyi email: qingyi.wei@duke.edu organization: Duke University School of Medicine |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31026346$$D View this record in MEDLINE/PubMed |
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| Keywords | expression quantitative trait loci analysis single nucleotide polymorphism DNA repair breast cancer susceptibility |
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| Snippet | A recent hypothesis‐free pathway‐level analysis of genome‐wide association study (GWAS) datasets suggested that the overall genetic variation measured by... A recent hypothesis-free pathway-level analysis of genome-wide association study (GWAS) datasets suggested that the overall genetic variation measured by... |
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| SubjectTerms | Breast cancer breast cancer susceptibility Breast Neoplasms - epidemiology Breast Neoplasms - genetics Cancer Case-Control Studies Clonal deletion Databases, Genetic Datasets Datasets as Topic DNA Repair Etiology European Continental Ancestry Group - genetics expression quantitative trait loci analysis Female Gene expression Genetic diversity Genetic Predisposition to Disease Genetic Variation Genome-wide association studies Genome-Wide Association Study Genomes Humans Hypotheses Logistic Models Lymphoblastoid cell lines Medical research Middle Aged Nucleotide excision repair Polymorphism, Single Nucleotide Quantitative trait loci Single-nucleotide polymorphism |
| Title | Genetic variants of genes in the NER pathway associated with risk of breast cancer: A large‐scale analysis of 14 published GWAS datasets in the DRIVE study |
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