| 1. |
- Ahearn, Thomas U., et al.
(författare)
-
Common variants in breast cancer risk loci predispose to distinct tumor subtypes
- 2022
-
Ingår i: Breast Cancer Research. - : Springer Nature. - 1465-5411 .- 1465-542X. ; 24:1
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 2. |
- Barnekow, Elin, et al.
(författare)
-
A Swedish Familial Genome-Wide Haplotype Analysis Identified Five Novel Breast Cancer Susceptibility Loci on 9p24.3, 11q22.3, 15q11.2, 16q24.1 and Xq21.31
- 2023
-
Ingår i: International Journal of Molecular Sciences. - : MDPI AG. - 1661-6596 .- 1422-0067. ; 24:5
-
Tidskriftsartikel (refereegranskat)abstract
- Most breast cancer heritability is unexplained. We hypothesized that analysis of unrelated familial cases in a GWAS context could enable the identification of novel susceptibility loci. In order to examine the association of a haplotype with breast cancer risk, we performed a genome-wide haplotype association study using a sliding window analysis of window sizes 1–25 SNPs in 650 familial invasive breast cancer cases and 5021 controls. We identified five novel risk loci on 9p24.3 (OR 3.4; p 4.9 × 10−11), 11q22.3 (OR 2.4; p 5.2 × 10−9), 15q11.2 (OR 3.6; p 2.3 × 10−8), 16q24.1 (OR 3; p 3 × 10−8) and Xq21.31 (OR 3.3; p 1.7 × 10−8) and confirmed three well-known loci on 10q25.13, 11q13.3, and 16q12.1. In total, 1593 significant risk haplotypes and 39 risk SNPs were distributed on the eight loci. In comparison with unselected breast cancer cases from a previous study, the OR was increased in the familial analysis in all eight loci. Analyzing familial cancer cases and controls enabled the identification of novel breast cancer susceptibility loci.
|
|
| 3. |
- Barnekow, Elin, et al.
(författare)
-
A Swedish Genome-Wide Haplotype Association Analysis Identifies a Novel Breast Cancer Susceptibility Locus in 8p21.2 and Characterizes Three Loci on Chromosomes 10, 11 and 16
- 2022
-
Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 14:5
-
Tidskriftsartikel (refereegranskat)abstract
- Background: The heritability of breast cancer is partly explained but much of the genetic contribution remains to be identified. Haplotypes are often used as markers of ethnicity as they are preserved through generations. We have previously demonstrated that haplotype analysis, in addition to standard SNP association studies, could give novel and more detailed information on genetic cancer susceptibility.Methods: In order to examine the association of a SNP or a haplotype to breast cancer risk, we performed a genome wide haplotype association study, using sliding window analysis of window sizes 1-25 and 50 SNPs, in 3200 Swedish breast cancer cases and 5021 controls.Results: We identified a novel breast cancer susceptibility locus in 8p21.1 (OR 2.08; p 3.92 x 10(-8)), confirmed three known loci in 10q26.13, 11q13.3, 16q12.1-2 and further identified novel subloci within these three loci. Altogether 76 risk SNPs, 3302 risk haplotypes of window size 2-25 and 113 risk haplotypes of window size 50 at p < 5 x 10(-8) on chromosomes 8, 10, 11 and 16 were identified. In the known loci haplotype analysis reached an OR of 1.48 in overall breast cancer and in familial cases OR 1.68.Conclusions: Analyzing haplotypes, rather than single variants, could detect novel susceptibility loci even in small study populations but the method requires a fairly homogenous study population.
|
|
| 4. |
- Couch, Fergus J., et al.
(författare)
-
Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer
- 2016
-
Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 7:11375, s. 1-13
-
Tidskriftsartikel (refereegranskat)abstract
- Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 x 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for similar to 11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.
|
|
| 5. |
- Dixon-Suen, Suzanne C, et al.
(författare)
-
Physical activity, sedentary time and breast cancer risk : a Mendelian randomisation study
- 2022
-
Ingår i: British Journal of Sports Medicine. - : BMJ Publishing Group Ltd. - 0306-3674 .- 1473-0480. ; 56:20, s. 1157-1170
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 6. |
- Eriksson, Louise, et al.
(författare)
-
Time from breast cancer diagnosis to therapeutic surgery and breast cancer prognosis : A population-based cohort study
- 2018
-
Ingår i: International Journal of Cancer. - Stockholm : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 143:5, s. 1093-1104
-
Tidskriftsartikel (refereegranskat)abstract
- Theoretically, time from breast cancer diagnosis to therapeutic surgery should affect survival. However, it is unclear whether this holds true in a modern healthcare setting in which breast cancer surgery is carried out within weeks to months of diagnosis. This is a population- and register-based study of all women diagnosed with invasive breast cancer in the Stockholm-Gotland healthcare region in Sweden, 2001-2008, and who were initially operated. Follow-up of vital status ended 2014. 7,017 women were included in analysis. Our main outcome was overall survival. Main analyses were carried out using Cox proportional hazards models. We adjusted for likely confounders and stratified on mode of detection, tumor size and lymph node metastasis. We found that a longer interval between date of morphological diagnosis and therapeutic surgery was associated with a poorer prognosis. Assuming a linear association, the hazard rate of death from all causes increased by 1.011 (95% CI 1.006-1.017) per day. Comparing, for example, surgery 6 weeks after diagnosis to surgery 3 weeks after diagnosis, thereby confers a 1.26-fold increased hazard rate. The increase in hazard rate associated with surgical delay was strongest in women with largest tumors. Whilst there was a clear association between delays and survival in women without lymph node metastasis, the association may be attenuated in subgroups with increasing number of lymph node metastases. We found no evidence of an interaction between time to surgery and mode of detection. In conclusion, unwarranted delays to primary treatment of breast cancer should be avoided. What's new? Theoretically, an increase in the interval between breast-cancer diagnosis and therapeutic surgery should affect survival, but it is uncertain whether that holds true in a modern healthcare setting. In this prospective study, the authors found that even fairly short delays (on the order of days or weeks) from diagnosis to surgery are associated with decreased survival. These results suggest that the time between diagnosis and therapeutic surgery should be kept as short as possible without hampering diagnostic work-up and preoperative patient optimization.
|
|
| 7. |
- Escala-Garcia, Maria, et al.
(författare)
-
A network analysis to identify mediators of germline-driven differences in breast cancer prognosis
- 2020
-
Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- 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 similar to 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.
|
|
| 8. |
- Gabrielson, Marike, et al.
(författare)
-
Hormonal determinants of mammographic density and density change
- 2020
-
Ingår i: Breast Cancer Research. - : BMC. - 1465-5411 .- 1465-542X. ; 22:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background Mammographic density (MD) is a strong risk factor for breast cancer. We examined how endogenous plasma hormones are associated with average MD area (cm(2)) and annual MD change (cm(2)/year). Methods This study within the prospective KARMA cohort included analyses of plasma hormones of 1040 women. Hormones from the progestogen (n = 3), androgen (n = 7), oestrogen (n = 2) and corticoid (n = 5) pathways were analysed by ultra-performance supercritical fluid chromatography-tandem mass spectrometry (UPSFC-MS/MS), as well as peptide hormones and proteins (n = 2). MD was measured as a dense area using the STRATUS method (mean over the left and right breasts) and mean annual MD change over time. Results Greater baseline mean MD was associated with overall higher concentrations of progesterone (average + 1.29 cm(2)per doubling of hormone concentration), 17OH-progesterone (+ 1.09 cm(2)), oesterone sulphate (+ 1.42 cm(2)), prolactin (+ 2.11 cm(2)) and SHBG (+ 4.18 cm(2)), and inversely associated with 11-deoxycortisol (- 1.33 cm(2)). The association between MD and progesterone was confined to the premenopausal women only. The overall annual MD change was - 0.8 cm(2). Hormones from the androgen pathway were statistically significantly associated with MD change. The annual MD change was - 0.96 cm(2)and - 1.16 cm(2)lesser, for women in the highest quartile concentrations of testosterone and free testosterone, respectively, compared to those with the lowest concentrations. Conclusions Our results suggest that, whereas hormones from the progestogen, oestrogen and corticoid pathways drive baseline MD, MD change over time is mainly driven by androgens. This study emphasises the complexity of risk factors for breast cancer and their mechanisms of action.
|
|
| 9. |
- Gabrielson, Marike, et al.
(författare)
-
Inclusion of Endogenous Plasma Dehydroepiandrosterone Sulfate and Mammographic Density in Risk Prediction Models for Breast Cancer
- 2020
-
Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association For Cancer Research (AACR). - 1055-9965 .- 1538-7755. ; 29:3, s. 574-581
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Endogenous hormones and mammographic density are risk factors for breast cancer. Joint analyses of the two may improve the ability to identify high-risk women.Methods: This study within the KARMA cohort included pre-diagnostic measures of plasma hormone levels of dehydroepiandrosterone (DHEA), its sulfate (DHEAS), and mammographic density in 629 cases and 1,223 controls, not using menopausal hormones. We evaluated the area under the receiver-operating curve (AUC) for risk of breast cancer by adding DHEA, DHEAS, and mammographic density to the Gail or Tyrer-Cuzick 5-year risk scores or the CAD2Y 2-year risk score.Results: DHEAS and percentage density were independently and positively associated with breast cancer risk (P = 0.007 and P < 0.001, respectively) for postmenopausal, but not premenopausal, women. No significant association was seen for DHEA. In postmenopausal women, those in the highest tertiles of both DHEAS and density were at greatest risk of breast cancer (OR, 3.5; 95% confidence interval, 1.9-6.3) compared with the lowest tertiles. Adding DHEAS significantly improved the AUC for the Gail (+2.1 units, P = 0.008) and Tyrer-Cuzick (+1.3 units, P = 0.007) risk models. Adding DHEAS to the Gail and Tyrer-Cuzick models already including mammographic density further increased the AUC by 1.2 units (P = 0.006) and 0.4 units (P = 0.007), respectively, compared with only including density.Conclusions: DHEAS and mammographic density are independent risk factors for breast cancer and improve risk discrimination for postmenopausal breast cancer.Impact: Combining DHEAS and mammographic density could help identify women at high risk who may benefit from individualized breast cancer screening and/or preventive measures among postmenopausal women.
|
|
| 10. |
- Gabrielson, Marike, et al.
(författare)
-
Inclusion of Plasma Prolactin Levels in Current Risk Prediction Models of Premenopausal and Postmenopausal Breast Cancer
- 2018
-
Ingår i: JNCI CANCER SPECTRUM. - : OXFORD UNIV PRESS. - 2515-5091. ; 2:4
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Circulating plasma prolactin is associated with breast cancer risk and may improve our ability to identify high-risk women. Mammographic density is a strong risk factor for breast cancer, but the association with prolactin is unclear. We studied the association between breast cancer, established breast cancer risk factors and plasma prolactin, and improvement of risk prediction by adding prolactin. Methods: We conducted a nested case-control study including 721 breast cancer patients and 1400 age-matched controls. Plasma prolactin levels were assayed using immunoassay and mammographic density measured by STRATUS. Odds ratios (ORs) were calculated by multivariable adjusted logistic regression, and improvement in the area under the curve for the risk of breast cancer by adding prolactin to established risk models. Statistical tests were two-sided. Results: In multivariable adjusted analyses, prolactin was associated with risk of premenopausal (OR, top vs bottom quintile = 1.9; 1.88 (95% confidence interval [CI] = 1.08 to 3.26) but not with postmenopausal breast cancer. In postmenopausal cases prolactin increased by 10.6% per cBIRADS category (P-trend = .03). In combined analyses of prolactin and mammographic density, ORs for women in the highest vs lowest tertile of both was 3.2 (95% CI = 1.3 to 7.7) for premenopausal women and 2.44 (95% CI = 1.44 to 4.14) for postmenopausal women. Adding prolactin to current risk models improved the area under the curve of the Gail model (+2.4 units, P = .02), Tyrer-Cuzick model (+3.8, P = .02), and the CAD2Y model (+1.7, P = .008) in premenopausal women. Conclusion: Circulating plasma prolactin and mammographic density appear independently associated with breast cancer risk among premenopausal women, and prolactin may improve risk prediction by current risk models.
|
|
