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  • Result 61-63 of 63
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61.
  • Shu, Xiang, et al. (author)
  • Evaluation of associations between genetically predicted circulating protein biomarkers and breast cancer risk
  • 2020
  • In: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 146:8, s. 2130-2138
  • Journal article (peer-reviewed)abstract
    • A small number of circulating proteins have been reported to be associated with breast cancer risk, with inconsistent results. Herein, we attempted to identify novel protein biomarkers for breast cancer via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82–1.18, p values: 6.96 × 10−4–3.28 × 10−8), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.
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62.
  • Stevens, Kristen N, et al. (author)
  • 19p13.1 is a triple negative-specific breast cancer susceptibility locus
  • 2012
  • In: Cancer Research. - 0008-5472 .- 1538-7445. ; 72, s. 1795-
  • Journal article (peer-reviewed)abstract
    • The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with risk of ovarian cancer. Here we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 Odds Ratio (OR)=1.10, 95% Confidence Interval (CI) 1.05 - 1.15, p=3.49 x 10-5] and triple negative (TN) (ER, PR and HER2 negative) breast cancer [rs8170 OR=1.22, 95% CI 1.13 - 1.31, p=2.22 x 10-7]. However, rs8170 was no longer associated with ER-negative breast cancer risk when TN cases were excluded [OR=0.98, 95% CI 0.89 - 1.07, p=0.62]. In addition, a combined analysis of TN cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC) (n=3,566) identified a genome-wide significant association between rs8170 and TN breast cancer risk [OR=1.25, 95% CI 1.18 - 1.33, p=3.31 x 10-13]. Thus, 19p13.1 is the first triple negative-specific breast cancer risk locus and the first locus specific to a histological subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple negative tumors and other subtypes likely arise through distinct etiologic pathways.
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63.
  • Yang, Xin, et al. (author)
  • Cancer risks associated with germline PALB2 pathogenic variants : An international study of 524 families
  • 2020
  • In: Journal of Clinical Oncology. - 0732-183X. ; 38:7, s. 674-685
  • Journal article (peer-reviewed)abstract
    • PURPOSE To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized. METHODS We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes. RESULTS We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 × 10-76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 × 10-3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 × 10-3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 3 1022). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (P for trend = 2.0 × 10-3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer. CONCLUSION These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer risk management of PALB2 PV carriers.
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  • Result 61-63 of 63
Type of publication
journal article (63)
Type of content
peer-reviewed (62)
other academic/artistic (1)
Author/Editor
Southey, Melissa C. (47)
Giles, Graham G (46)
Easton, Douglas F. (38)
Milne, Roger L. (33)
Offit, Kenneth (33)
Chang-Claude, Jenny (31)
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Hamann, Ute (31)
Couch, Fergus J. (31)
Nevanlinna, Heli (29)
Andrulis, Irene L. (29)
Kraft, Peter (29)
John, Esther M (28)
Benitez, Javier (28)
Chenevix-Trench, Geo ... (28)
Hopper, John L. (28)
Haiman, Christopher ... (27)
Chanock, Stephen J (27)
Brenner, Hermann (26)
Zheng, Wei (25)
Neuhausen, Susan L (23)
Radice, Paolo (23)
Simard, Jacques (23)
Pharoah, Paul D. P. (23)
Rennert, Gad (22)
Dunning, Alison M. (22)
Jakubowska, Anna (21)
Garcia-Closas, Monts ... (21)
Bojesen, Stig E. (20)
Cox, Angela (20)
Daly, Mary B. (20)
Devilee, Peter (20)
Meindl, Alfons (20)
Wolk, Alicja (19)
Arndt, Volker (19)
Hall, Per (19)
Mannermaa, Arto (19)
Schmidt, Marjanka K. (19)
Brauch, Hiltrud (18)
Czene, Kamila (18)
Evans, D. Gareth (18)
Fasching, Peter A. (18)
Lambrechts, Diether (18)
Schmutzler, Rita K. (18)
Wang, Qin (17)
Gago Dominguez, Manu ... (17)
Bolla, Manjeet K. (17)
Cross, Simon S. (17)
Guenel, Pascal (17)
Lindblom, Annika (17)
Terry, Mary Beth (17)
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University
Karolinska Institutet (48)
Uppsala University (40)
Lund University (30)
Umeå University (15)
Linköping University (5)
Stockholm University (2)
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University of Gothenburg (1)
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Language
English (63)
Research subject (UKÄ/SCB)
Medical and Health Sciences (56)
Natural sciences (4)

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