| 1. |
- Ahearn, Thomas U., et al.
(author)
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Common variants in breast cancer risk loci predispose to distinct tumor subtypes
- 2022
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In: Breast Cancer Research. - : Springer Nature. - 1465-5411 .- 1465-542X. ; 24:1
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Journal article (peer-reviewed)abstract
- BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions.ConclusionThis report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.
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| 2. |
- Dixon-Suen, Suzanne C, et al.
(author)
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Physical activity, sedentary time and breast cancer risk : a Mendelian randomisation study
- 2022
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In: British Journal of Sports Medicine. - : BMJ Publishing Group Ltd. - 0306-3674 .- 1473-0480. ; 56:20, s. 1157-1170
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Journal article (peer-reviewed)abstract
- OBJECTIVES: Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics.METHODS: We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity.RESULTS: Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger).CONCLUSION: Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.
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| 3. |
- Fernandez-Rozadilla, Ceres, et al.
(author)
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Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries
- 2023
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In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 55, s. 89-99
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Journal article (peer-reviewed)abstract
- Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.
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| 4. |
- Mueller, Stefanie H., et al.
(author)
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Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry
- 2023
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In: Genome Medicine. - : BioMed Central (BMC). - 1756-994X .- 1756-994X. ; 15
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Journal article (peer-reviewed)abstract
- Background: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.Methods: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.Results: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 x 10(-6)) and AC058822.1 (P = 1.47 x 10(-4)), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C.Conclusions: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 x 10(-5)), demonstrating the importance of diversifying study cohorts.
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| 5. |
- Schmit, Stephanie L, et al.
(author)
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Novel Common Genetic Susceptibility Loci for Colorectal Cancer.
- 2019
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In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 111:2, s. 146-157
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Journal article (peer-reviewed)abstract
- Background: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk.Methods: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided.Results: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0.Conclusions: This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.
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