BRCA1-associated breast and ovarian cancer risks in Poland: no association with commonly studied polymorphisms.
Anna Jakubowska,Anna Jakubowska,Jacek Gronwald,Janusz Menkiszak,Bohdan Górski,Tomasz Huzarski,Tomasz Byrski,Aleksandra Tołoczko-Grabarek,Michael Gilbert,Lutz Edler,Marc Zapatka,Roland Eils,Jan Lubinski,Rodney J. Scott,Ute Hamann +14 more
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TLDR
It appears that polymorphisms involved in DNA repair, steroid hormone biosynthesis/metabolism/signaling, folate metabolism as well as cell growth do not influence disease risk in Polish women carrying one of the three common BRCA1 founder mutations.Abstract:
Polymorphisms in genes involved in DNA repair, steroid hormone biosynthesis/metabolism/signaling, folate metabolism as well as cell growth are prime candidates for possible associations with breast and ovarian cancer risk in women with an inherited predisposition. We investigated 29 polymorphisms in 20 genes encoding key proteins of the above four biological pathways for their breast and ovarian cancer risk modifying effect in Polish women harboring BRCA1 founder mutations. Of the analyzed genes, ERCC2, XRCC1, XRCC2, XRCC3 and Lig4 participate in DNA repair, TP53 in cell cycle check point control, AIB1, AR, COMT, CYP11A1, CYP17A1, CYP19A1, HSD17 and PGR in steroid hormone biosynthesis/metabolism/signaling, TYMS in folate metabolism and HER2, IL6, LRP1, TGFB and TGFBR1 affect cell growth. Using validated methods, we genotyped 319 breast cancer cases, 146 ovarian cancer cases and 290 unaffected controls, all of whom harbored one of three causative mutations in BRCA1. Our results revealed no association of any of the investigated polymorphisms with BRCA1-associated breast or ovarian cancer risk. Thus, it appears that these polymorphisms do not influence disease risk in Polish women carrying one of the three common BRCA1 founder mutations.read more
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Meta-Analysis: A Constantly Evolving Research Integration Tool
TL;DR: The four articles in this special section onMeta-analysis illustrate some of the complexities entailed in meta-analysis methods and contributes both to advancing this methodology and to the increasing complexities that can befuddle researchers.
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Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case series unselected for family history: a combined analysis of 22 studies
Antonis C. Antoniou,Paul D.P. Pharoah,Steven A. Narod,Harvey A. Risch,Jorunn E. Eyfjord,John L. Hopper,Niklas Loman,Håkan Olsson,Oskar T. Johannsson,Åke Borg,Barbara Pasini,Paolo Radice,Siranoush Manoukian,Diana Eccles,Nelson L.S. Tang,E. Olah,Hoda Anton-Culver,Ellen Warner,Jan Lubinski,Jacek Gronwald,Bohdan Górski,Hrafn Tulinius,Steinunn Thorlacius,Hannaleena Eerola,Heli Nevanlinna,Kirsi Syrjäkoski,Olli Kallioniemi,Deborah J. Thompson,Christopher H. Evans,Julian Peto,Julian Peto,Fiona Lalloo,D G R Evans,Douglas F. Easton +33 more
TL;DR: Risks in carriers were higher when based on index breast cancer cases diagnosed at <35 years of age and for variation in risk by mutation position for both genes, and some evidence for a reduction in risk in women from earlier birth cohorts is found.
Journal ArticleDOI
Genetic Heterogeneity and Penetrance Analysis of the BRCA1 and BRCA2 Genes in Breast Cancer Families
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TL;DR: The lifetime risk of breast cancer appears similar to the risk in BRCA1 carriers, but there was some suggestion of a lower risk in bRCA2 carriers <50 years of age.
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Polymorphisms in DNA repair genes and associations with cancer risk.
TL;DR: It is concluded that large, well-designed studies of common polymorphisms in DNA repair genes are needed and such studies may benefit from analysis of multiple genes or polymorphisms and from the consideration of relevant exposures that may influence the likelihood of cancer in the presence of reduced DNA repair capacity.
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On the exact distribution of maximally selected rank statistics
Torsten Hothorn,Berthold Lausen +1 more
TL;DR: The computation of the exact distribution of a maximally selected rank statistic is discussed and a new lower bound of the distribution is derived based on an extension of an algorithm for the exactribution of a linear rank statistic.
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