Publications by authors named "Jonathan Beesley"

139 Publications

Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment.

Breast Cancer Res 2021 Aug 18;23(1):86. Epub 2021 Aug 18.

Department of Medicine, Huntsman Cancer Institute, Salt Lake City, UT, USA.

Background: Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients.

Methods: We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15).

Results: Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy.

Conclusions: We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited.
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http://dx.doi.org/10.1186/s13058-021-01450-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371820PMC
August 2021

Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals.

HGG Adv 2021 Jul 12;2(3). Epub 2021 Jun 12.

Department of Laboratory Medicine and Pathology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, MN, USA.

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the and genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.
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http://dx.doi.org/10.1016/j.xhgg.2021.100041DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336922PMC
July 2021

Identification of a Locus Near Associated With Progression-Free Survival in Ovarian Cancer.

Cancer Epidemiol Biomarkers Prev 2021 Sep 23;30(9):1669-1680. Epub 2021 Jun 23.

Gynecologic Oncology Center, Kiel, Germany.

Background: Many loci have been found to be associated with risk of epithelial ovarian cancer (EOC). However, although there is considerable variation in progression-free survival (PFS), no loci have been found to be associated with outcome at genome-wide levels of significance.

Methods: We carried out a genome-wide association study (GWAS) of PFS in 2,352 women with EOC who had undergone cytoreductive surgery and standard carboplatin/paclitaxel chemotherapy.

Results: We found seven SNPs at 12q24.33 associated with PFS ( < 5 × 10), the top SNP being rs10794418 (HR = 1.24; 95% CI, 1.15-1.34; = 1.47 × 10). High expression of a nearby gene, , is associated with shorter PFS in EOC, and with poor prognosis in other cancers. SNP rs10794418 is also associated with expression of in ovarian tumors, with the allele associated with shorter PFS being associated with higher expression, and chromatin interactions were detected between the promoter and associated SNPs in serous and endometrioid EOC cell lines. ULK1 knockout ovarian cancer cell lines showed significantly increased sensitivity to carboplatin .

Conclusions: The locus at 12q24.33 represents one of the first genome-wide significant loci for survival for any cancer. is a plausible candidate for the target of this association.

Impact: This finding provides insight into genetic markers associated with EOC outcome and potential treatment options..
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http://dx.doi.org/10.1158/1055-9965.EPI-20-1817DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419101PMC
September 2021

A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

Nat Commun 2021 02 17;12(1):1078. Epub 2021 Feb 17.

Copenhagen General Population Study, Herlev and Gentofte Hospital Copenhagen University Hospital, Herlev, Denmark.

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.
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http://dx.doi.org/10.1038/s41467-020-20496-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890067PMC
February 2021

RNF168 regulates R-loop resolution and genomic stability in BRCA1/2-deficient tumors.

J Clin Invest 2021 02;131(3)

Princess Margaret Cancer Centre, University Health Network and Department of Medical Biophysics, and.

Germline mutations in BRCA1 and BRCA2 (BRCA1/2) genes considerably increase breast and ovarian cancer risk. Given that tumors with these mutations have elevated genomic instability, they exhibit relative vulnerability to certain chemotherapies and targeted treatments based on poly (ADP-ribose) polymerase (PARP) inhibition. However, the molecular mechanisms that influence cancer risk and therapeutic benefit or resistance remain only partially understood. BRCA1 and BRCA2 have also been implicated in the suppression of R-loops, triple-stranded nucleic acid structures composed of a DNA:RNA hybrid and a displaced ssDNA strand. Here, we report that loss of RNF168, an E3 ubiquitin ligase and DNA double-strand break (DSB) responder, remarkably protected Brca1-mutant mice against mammary tumorigenesis. We demonstrate that RNF168 deficiency resulted in accumulation of R-loops in BRCA1/2-mutant breast and ovarian cancer cells, leading to DSBs, senescence, and subsequent cell death. Using interactome assays, we identified RNF168 interaction with DHX9, a helicase involved in the resolution and removal of R-loops. Mechanistically, RNF168 directly ubiquitylated DHX9 to facilitate its recruitment to R-loop-prone genomic loci. Consequently, loss of RNF168 impaired DHX9 recruitment to R-loops, thereby abrogating its ability to resolve R-loops. The data presented in this study highlight a dependence of BRCA1/2-defective tumors on factors that suppress R-loops and reveal a fundamental RNF168-mediated molecular mechanism that governs cancer development and vulnerability.
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http://dx.doi.org/10.1172/JCI140105DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843228PMC
February 2021

eQTL Colocalization Analyses Identify NTN4 as a Candidate Breast Cancer Risk Gene.

Am J Hum Genet 2020 10 31;107(4):778-787. Epub 2020 Aug 31.

Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia.

Breast cancer genome-wide association studies (GWASs) have identified 150 genomic risk regions containing more than 13,000 credible causal variants (CCVs). The CCVs are predominantly noncoding and enriched in regulatory elements. However, the genes underlying breast cancer risk associations are largely unknown. Here, we used genetic colocalization analysis to identify loci at which gene expression could potentially explain breast cancer risk phenotypes. Using data from the Breast Cancer Association Consortium (BCAC) and quantitative trait loci (QTL) from the Genotype-Tissue Expression (GTEx) project and The Cancer Genome Project (TCGA), we identify shared genetic relationships and reveal novel associations between cancer phenotypes and effector genes. Seventeen genes, including NTN4, were identified as potential mediators of breast cancer risk. For NTN4, we showed the rs61938093 CCV at this region was located within an enhancer element that physically interacts with the NTN4 promoter, and the risk allele reduced NTN4 promoter activity. Furthermore, knockdown of NTN4 in breast cells increased cell proliferation in vitro and tumor growth in vivo. These data provide evidence linking risk-associated variation to genes that may contribute to breast cancer predisposition.
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http://dx.doi.org/10.1016/j.ajhg.2020.08.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536644PMC
October 2020

SNPs in lncRNA Regions and Breast Cancer Risk.

Front Genet 2020 30;11:550. Epub 2020 Jun 30.

Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Long non-coding RNAs (lncRNAs) play crucial roles in human physiology, and have been found to be associated with various cancers. Transcribed ultraconserved regions (T-UCRs) are a subgroup of lncRNAs conserved in several species, and are often located in cancer-related regions. Breast cancer is the most common cancer in women worldwide and the leading cause of female cancer deaths. We investigated the association of genetic variants in lncRNA and T-UCR regions with breast cancer risk to uncover candidate loci for further analysis. Our focus was on low-penetrance variants that can be discovered in a large dataset. We selected 565 regions of lncRNAs and T-UCRs that are expressed in breast or breast cancer tissue, or show expression correlation to major breast cancer associated genes. We studied the association of single nucleotide polymorphisms (SNPs) in these regions with breast cancer risk in the 122970 case samples and 105974 controls of the Breast Cancer Association Consortium's genome-wide data, and also by functional analyses using Integrated Expression Quantitative trait and prediction of GWAS targets (INQUISIT) and expression quantitative trait loci (eQTL) analysis. The eQTL analysis was carried out using the METABRIC dataset and analyses from GTEx and ncRNA eQTL databases. We found putative breast cancer risk variants ( < 1 × 10) targeting the lncRNA in INQUISIT and eQTL analysis. In addition, putative breast cancer risk associated SNPs ( < 1 × 10) in the region of two T-UCRs, uc.184 and uc.313, located in protein coding genes and , respectively, targeted these genes in INQUISIT and in eQTL analysis. Other non-coding regions containing SNPs with the defined p-value and highly significant false discovery rate (FDR) for breast cancer risk association were discovered that may warrant further studies. These results suggest candidate lncRNA loci for further research on breast cancer risk and the molecular mechanisms.
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http://dx.doi.org/10.3389/fgene.2020.00550DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340126PMC
June 2020

Immune Cell Associations with Cancer Risk.

iScience 2020 Jul 20;23(7):101296. Epub 2020 Jun 20.

ProCURE, Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, Barcelona, Catalonia 08908, Spain. Electronic address:

Proper immune system function hinders cancer development, but little is known about whether genetic variants linked to cancer risk alter immune cells. Here, we report 57 cancer risk loci associated with differences in immune and/or stromal cell contents in the corresponding tissue. Predicted target genes show expression and regulatory associations with immune features. Polygenic risk scores also reveal associations with immune and/or stromal cell contents, and breast cancer scores show consistent results in normal and tumor tissue. SH2B3 links peripheral alterations of several immune cell types to the risk of this malignancy. Pleiotropic SH2B3 variants are associated with breast cancer risk in BRCA1/2 mutation carriers. A retrospective case-cohort study indicates a positive association between blood counts of basophils, leukocytes, and monocytes and age at breast cancer diagnosis. These findings broaden our knowledge of the role of the immune system in cancer and highlight promising prevention strategies for individuals at high risk.
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http://dx.doi.org/10.1016/j.isci.2020.101296DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334419PMC
July 2020

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Nat Genet 2020 06 18;52(6):572-581. Epub 2020 May 18.

Molecular Medicine Unit, Fundación Pública Galega de Medicina Xenómica, Santiago de Compostela, Spain.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.
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http://dx.doi.org/10.1038/s41588-020-0609-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808397PMC
June 2020

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.

Nat Commun 2020 01 16;11(1):312. Epub 2020 Jan 16.

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.
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http://dx.doi.org/10.1038/s41467-019-14100-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6965101PMC
January 2020

Candidate Causal Variants at the 8p12 Breast Cancer Risk Locus Regulate .

Cancers (Basel) 2020 Jan 10;12(1). Epub 2020 Jan 10.

Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD 4006, Australia.

Genome-wide association studies have revealed a locus at 8p12 that is associated with breast cancer risk. Fine-mapping of this locus identified 16 candidate causal variants (CCVs). However, as these variants are intergenic, their function is unclear. To map chromatin looping from this risk locus to a previously identified candidate target gene, , we performed chromatin conformation capture analyses in normal and tumoural breast cell lines. We identified putative regulatory elements, containing CCVs, which looped to the promoter region. Using reporter gene assays, we found that the risk allele of CCV rs7461885 reduced the activity of a enhancer element, consistent with the function of as a tumour suppressor gene. Furthermore, the risk allele of CCV rs12155535, located in another enhancer element, was negatively correlated with looping of this element to the promoter region, suggesting that this allele would be associated with reduced expression. These findings provide the first evidence that CCV risk alleles downregulate expression, suggesting that this gene is a regulatory target of the 8p12 breast cancer risk locus.
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http://dx.doi.org/10.3390/cancers12010170DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7016765PMC
January 2020

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Nat Genet 2020 01 7;52(1):56-73. Epub 2020 Jan 7.

Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
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http://dx.doi.org/10.1038/s41588-019-0537-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974400PMC
January 2020

Non-coding RNAs underlie genetic predisposition to breast cancer.

Genome Biol 2020 01 7;21(1). Epub 2020 Jan 7.

Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.

Background: Genetic variants identified through genome-wide association studies (GWAS) are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, the contribution of non-coding RNAs to complex traits is not clear.

Results: Using targeted RNA sequencing, we systematically annotated multi-exonic non-coding RNA (mencRNA) genes transcribed from 1.5-Mb intervals surrounding 139 breast cancer GWAS signals and assessed their contribution to breast cancer risk. We identify more than 4000 mencRNA genes and show their expression distinguishes normal breast tissue from tumors and different breast cancer subtypes. Importantly, breast cancer risk variants, identified through genetic fine-mapping, are significantly enriched in mencRNA exons, but not the promoters or introns. eQTL analyses identify mencRNAs whose expression is associated with risk variants. Furthermore, chromatin interaction data identify hundreds of mencRNA promoters that loop to regions that contain breast cancer risk variants.

Conclusions: We have compiled the largest catalog of breast cancer-associated mencRNAs to date and provide evidence that modulation of mencRNAs by GWAS variants may provide an alternative mechanism underlying complex traits.
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http://dx.doi.org/10.1186/s13059-019-1876-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6947989PMC
January 2020

Chromatin interactome mapping at 139 independent breast cancer risk signals.

Genome Biol 2020 01 7;21(1). Epub 2020 Jan 7.

Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.

Background: Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression.

Results: We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers, and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals and explore the functional mechanism underlying altered risk at the 12q24 risk region.

Conclusions: Our results demonstrate the power of combining genetics, computational genomics, and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.
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http://dx.doi.org/10.1186/s13059-019-1877-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6947858PMC
January 2020

Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer.

Nat Commun 2019 04 15;10(1):1741. Epub 2019 Apr 15.

Molecular Oncology Laboratory, CIBERONC, Hospital Clinico San Carlos, IdISSC (Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), 28040, Madrid, Spain.

Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.
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http://dx.doi.org/10.1038/s41467-018-08053-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6465407PMC
April 2019

Genome-wide association study of germline variants and breast cancer-specific mortality.

Br J Cancer 2019 03 21;120(6):647-657. Epub 2019 Feb 21.

Lund University, Department of Cancer Epidemiology, Clinical Sciences, Lund, Sweden.

Background: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.

Methods: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).

Results: We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.

Conclusions: We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.
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http://dx.doi.org/10.1038/s41416-019-0393-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461853PMC
March 2019

Publisher Correction: Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways.

Nat Commun 2019 01 14;10(1):299. Epub 2019 Jan 14.

Dermatology Research Centre, University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia.

The original version of this Article contained errors in the spelling of the authors Fan Liu and M. Arfan Ikram, which were incorrectly given as Fan Lui and Arfan M. Ikram. In addition, the original version of this Article also contained errors in the author affiliations which are detailed in the associated Publisher Correction.
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http://dx.doi.org/10.1038/s41467-018-08078-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6331636PMC
January 2019

Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways.

Nat Commun 2018 11 14;9(1):4774. Epub 2018 Nov 14.

Dermatology Research Centre, University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia.

The total number of acquired melanocytic nevi on the skin is strongly correlated with melanoma risk. Here we report a meta-analysis of 11 nevus GWAS from Australia, Netherlands, UK, and USA comprising 52,506 individuals. We confirm known loci including MTAP, PLA2G6, and IRF4, and detect novel SNPs in KITLG and a region of 9q32. In a bivariate analysis combining the nevus results with a recent melanoma GWAS meta-analysis (12,874 cases, 23,203 controls), SNPs near GPRC5A, CYP1B1, PPARGC1B, HDAC4, FAM208B, DOCK8, and SYNE2 reached global significance, and other loci, including MIR146A and OBFC1, reached a suggestive level. Overall, we conclude that most nevus genes affect melanoma risk (KITLG an exception), while many melanoma risk loci do not alter nevus count. For example, variants in TERC and OBFC1 affect both traits, but other telomere length maintenance genes seem to affect melanoma risk only. Our findings implicate multiple pathways in nevogenesis.
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http://dx.doi.org/10.1038/s41467-018-06649-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235897PMC
November 2018

Genome-wide association study of intraocular pressure uncovers new pathways to glaucoma.

Nat Genet 2018 08 27;50(8):1067-1071. Epub 2018 Jul 27.

QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

Intraocular pressure (IOP) is currently the sole modifiable risk factor for primary open-angle glaucoma (POAG), one of the leading causes of blindness worldwide. Both IOP and POAG are highly heritable. We report a combined analysis of participants from the UK Biobank (n = 103,914) and previously published data from the International Glaucoma Genetic Consortium (n = 29,578) that identified 101 statistically independent genome-wide-significant SNPs for IOP, 85 of which have not been previously reported. We examined these SNPs in 11,018 glaucoma cases and 126,069 controls, and 53 SNPs showed evidence of association. Gene-based tests implicated an additional 22 independent genes associated with IOP. We derived an allele score based on the IOP loci and loci influencing optic nerve head morphology. In 1,734 people with advanced glaucoma and 2,938 controls, participants in the top decile of the allele score were at increased risk (odds ratio (OR) = 5.6; 95% confidence interval (CI): 4.1-7.6) of glaucoma relative to the bottom decile.
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http://dx.doi.org/10.1038/s41588-018-0176-yDOI Listing
August 2018

The importance of using public data to validate reported associations.

PLoS Genet 2018 06 29;14(6):e1007416. Epub 2018 Jun 29.

Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina, United States of America.

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http://dx.doi.org/10.1371/journal.pgen.1007416DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6025853PMC
June 2018

A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer.

Nat Genet 2018 07 18;50(7):968-978. Epub 2018 Jun 18.

Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.
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http://dx.doi.org/10.1038/s41588-018-0132-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314198PMC
July 2018

Genome-wide association study of paclitaxel and carboplatin disposition in women with epithelial ovarian cancer.

Sci Rep 2018 01 24;8(1):1508. Epub 2018 Jan 24.

Department of Gynaecological Oncology, Westmead Hospital, Sydney, Australia.

Identifying single nucleotide polymorphisms (SNPs) that influence chemotherapy disposition may help to personalize cancer treatment and limit toxicity. Genome-wide approaches are unbiased, compared with candidate gene studies, but usually require large cohorts. As most chemotherapy is given cyclically multiple blood sampling is required to adequately define drug disposition, limiting patient recruitment. We found that carboplatin and paclitaxel disposition are stable phenotypes in ovarian cancer patients and tested a genome-wide association study (GWAS) design to identify SNPs associated with chemotherapy disposition. We found highly significant SNPs in ABCC2, a known carboplatin transporter, associated with carboplatin clearance (asymptotic P = 5.2 × 10, empirical P = 1.4 × 10), indicating biological plausibility. We also identified novel SNPs associated with paclitaxel disposition, including rs17130142 with genome-wide significance (asymptotic P = 2.0 × 10, empirical P = 1.3 × 10). Although requiring further validation, our work demonstrated that GWAS of chemotherapeutic drug disposition can be effective, even in relatively small cohorts, and can be adopted in drug development and treatment programs.
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http://dx.doi.org/10.1038/s41598-018-19590-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5784122PMC
January 2018

Mixed ductal-lobular carcinomas: evidence for progression from ductal to lobular morphology.

J Pathol 2018 04 9;244(4):460-468. Epub 2018 Mar 9.

Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.

Mixed ductal-lobular carcinomas (MDLs) show both ductal and lobular morphology, and constitute an archetypal example of intratumoural morphological heterogeneity. The mechanisms underlying the coexistence of these different morphological entities are poorly understood, although theories include that these components either represent 'collision' of independent tumours or evolve from a common ancestor. We performed comprehensive clinicopathological analysis of a cohort of 82 MDLs, and found that: (1) MDLs more frequently coexist with ductal carcinoma in situ (DCIS) than with lobular carcinoma in situ (LCIS); (2) the E-cadherin-catenin complex was normal in the ductal component in 77.6% of tumours; and (3) in the lobular component, E-cadherin was almost always aberrantly located in the cytoplasm, in contrast to invasive lobular carcinoma (ILC), where E-cadherin is typically absent. Comparative genomic hybridization and multiregion whole exome sequencing of four representative cases revealed that all morphologically distinct components within an individual case were clonally related. The mutations identified varied between cases; those associated with a common clonal ancestry included BRCA2, TBX3, and TP53, whereas those associated with clonal divergence included CDH1 and ESR1. Together, these data support a model in which separate morphological components of MDLs arise from a common ancestor, and lobular morphology can arise via a ductal pathway of tumour progression. In MDLs that present with LCIS and DCIS, the clonal divergence probably occurs early, and is frequently associated with complete loss of E-cadherin expression, as in ILC, whereas, in the majority of MDLs, which present with DCIS but not LCIS, direct clonal divergence from the ductal to the lobular phenotype occurs late in tumour evolution, and is associated with aberrant expression of E-cadherin. The mechanisms driving the phenotypic change may involve E-cadherin-catenin complex deregulation, but are yet to be fully elucidated, as there is significant intertumoural heterogeneity, and each case may have a unique molecular mechanism. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
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http://dx.doi.org/10.1002/path.5040DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5873281PMC
April 2018

Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology.

Nat Genet 2017 Dec 30;49(12):1752-1757. Epub 2017 Oct 30.

Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia.

Asthma, hay fever (or allergic rhinitis) and eczema (or atopic dermatitis) often coexist in the same individuals, partly because of a shared genetic origin. To identify shared risk variants, we performed a genome-wide association study (GWAS; n = 360,838) of a broad allergic disease phenotype that considers the presence of any one of these three diseases. We identified 136 independent risk variants (P < 3 × 10), including 73 not previously reported, which implicate 132 nearby genes in allergic disease pathophysiology. Disease-specific effects were detected for only six variants, confirming that most represent shared risk factors. Tissue-specific heritability and biological process enrichment analyses suggest that shared risk variants influence lymphocyte-mediated immunity. Six target genes provide an opportunity for drug repositioning, while for 36 genes CpG methylation was found to influence transcription independently of genetic effects. Asthma, hay fever and eczema partly coexist because they share many genetic risk variants that dysregulate the expression of immune-related genes.
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http://dx.doi.org/10.1038/ng.3985DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5989923PMC
December 2017

Association analysis identifies 65 new breast cancer risk loci.

Nature 2017 11 23;551(7678):92-94. Epub 2017 Oct 23.

Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.
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http://dx.doi.org/10.1038/nature24284DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798588PMC
November 2017

Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer.

Nat Genet 2017 Dec 23;49(12):1767-1778. Epub 2017 Oct 23.

Department of Epidemiology, University of California, Irvine, Irvine, California, USA.

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.
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http://dx.doi.org/10.1038/ng.3785DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5808456PMC
December 2017

Functional dissection of breast cancer risk-associated promoter variants.

Oncotarget 2017 Sep 26;8(40):67203-67217. Epub 2017 May 26.

Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia.

The multi-cancer susceptibility locus at 5p15.33 includes , encoding the telomerase catalytic subunit. Genome-wide association studies (GWAS) have identified six single nucleotide polymorphisms (SNPs) in the promoter associated with decreased breast cancer risk, although the precise causal variants and their mechanisms of action have remained elusive. Luciferase reporter assays indicated that the protective haplotype reduced promoter activity in human mammary epithelial and cancer cells in an estrogen-independent manner. Using single variant constructs, we identified rs3215401 and rs2853669 as likely functional variants. Silencing of MYC decreased promoter activity but neither MYC nor ETS2 silencing conferred allele-specificity. In chromatin immunoprecipitation experiments, the ETS protein GABPA, but not ETS2 or ELF1, bound rs2853669 in an allele-specific manner in mammary epithelial cells. Investigation of open chromatin in mammoplasty samples suggested involvement of three additional variants, though not rs3215401 or rs2853669. Chromosome conformation capture revealed no interaction of the promoter with regulatory elements in the locus, indicating limited local impact of candidate variants on the promoter. Collectively, our functional studies of the - breast cancer susceptibility locus describe rs2853669 as a functional variant of this association signal among three other potentially causal variants and demonstrate the versatile mechanisms by which promoter variants may affect breast cancer risk.
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http://dx.doi.org/10.18632/oncotarget.18226DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5620167PMC
September 2017

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

Nat Genet 2017 Jul 12;49(7):1126-1132. Epub 2017 Jun 12.

Department of Pharmaceutical Sciences, College of Pharmacy, Washington State University, Spokane, Washington, USA.

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.
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http://dx.doi.org/10.1038/ng.3892DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5510465PMC
July 2017
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