Paula Maguire

Bio: Paula Maguire is an academic researcher from Karolinska Institutet. The author has contributed to research in topics: Breast cancer & Cancer. The author has an hindex of 7, co-authored 9 publications receiving 227 citations. Previous affiliations of Paula Maguire include Karolinska University Hospital.

Estrogen receptor beta (ESR2) polymorphisms in familial and sporadic breast cancer.

Abstract: Estrogen is involved in both normal mammary development and in breast carcinogenesis. A family history of disease and exposure to estrogen are major risk factors for developing breast cancer. Estrogen exerts its biological effects through binding to the estrogen receptors, estrogen receptor alpha (ESR1) and the more recently discovered estrogen receptor beta (ESR2). Genetic variation in genes involved in estrogen biosynthesis, metabolism and signal transduction have been suggested to play a role in breast cancer risk. We therefore tested the hypothesis that common genetic variants of the ESR2 gene may be associated with increased risk for breast cancer and this risk may vary between breast cancer groups. We investigated three common ESR2 polymorphisms, rs1256049 (G1082A), rs4986938 (G1730A) and rs928554 (Cx+56 A→G) for association to breast cancer risk. A total of 723 breast cancer cases and 480 controls were included in the study. Of the breast cancer cases, 323 were sporadic and 400 were familial, the familial cases were further divided into familial high-risk and familial low-risk breast cancer cases. We found no overall statistically significant association for any of the single polymorphisms studied. Haplotype analysis suggested one haplotype associated with increased risk in sporadic breast cancer patients (OR = 3.0, p = 0.03). Further analysis is needed to elucidate the role of estrogen receptor beta in breast cancer susceptibility.

High incidence of skewed X chromosome inactivation in young patients with familial non-BRCA1/BRCA2 breast cancer

Abstract: Background: A higher frequency of skewed X chromosome inactivation has been reported in a consecutive series of young patients with breast cancer compared with controls of a similar age. Objective: To investigate the X inactivation pattern in patients with familial non- BRCA1 / BRCA2 breast cancer (n = 272), BRCA1 / BRCA2 germline mutations (n = 35), and sporadic breast cancer (n = 292). Methods: X inactivation pattern was determined by polymerase chain reaction analysis of the highly polymorphic CAG repeat in the androgen receptor ( AR ) gene. The X inactivation pattern was classified as skewed when 90% or more of the cells preferentially expressed one X chromosome. Results: Young patients with familial breast cancer had a significantly higher frequency of skewed X inactivation (11.2%) than young controls (2.7%) (p = 0.001). There was also a strong tendency for middle aged patients with sporadic breast cancer to be more skewed than middle aged controls (13.6% v 4.4%) (p = 0.02). No association between skewed X inactivation and breast cancer was found for the BRCA1 / BRCA2 patients . Conclusions: Skewed X inactivation may be a risk factor for the development of breast cancer in both sporadic and familial breast cancer and may indicate an effect of X linked genes.

Comprehensive mutational analysis of a cohort of Swedish Cornelia de Lange syndrome patients

Abstract: Cornelia de Lange syndrome (CdLS; OMIM 122470) is a rare multiple congenital anomaly/mental retardation syndrome characterized by distinctive dysmorphic facial features, severe growth and developmental delay and abnormalities of the upper limbs. About 50% of CdLS patients have been found to have heterozygous mutations in the NIPBL gene and a few cases were recently found to be caused by mutations in the X-linked SMC1L1 gene. We performed a mutation screening of all NIPBL coding exons by direct sequencing in 11 patients (nine sporadic and two familial cases) diagnosed with CdLS in Sweden and detected mutations in seven of the cases. All were de novo, and six of the mutations have not been previously described. Four patients without identifiable NIPBL mutations were subsequently subjected to multiplex ligation-dependent probe amplification analysis to exclude whole exon deletions/duplications of NIPBL. In addition, mutation analysis of the 5' untranslated region (5' UTR) of NIPBL was performed. Tiling resolution array comparative genomic hybridization analysis was carried out on these four patients to detect cryptic chromosome imbalances and in addition the boys were screened for SMC1L1 mutations. We found a de novo 9p duplication with a size of 0.6 Mb in one of the patients with a CdLS-like phenotype but no mutations were detected in SMC1L1. So far, two genes (NIPBL and SMC1L1) have been identified causing CdLS or CdLS-like phenotypes. However, in a considerable proportion of individuals demonstrating the CdLS phenotype, mutations in any of these two genes are not found and other potential loci harboring additional CdLS-causing genes should be considered.

Lack of HIN-1 methylation in BRCA1-linked and "BRCA1-like" breast tumors.

Abstract: We recently identified a candidate tumor suppressor gene, HIN-1, that is silenced due to methylation in the majority of sporadic breast carcinomas and is localized to 5q33-qter, an area frequently lost in BRCA1 tumors and thought to harbor a BRCA1 modifier gene. To establish whether germ-line mutations in HIN-1 may influence breast cancer risk, we sequenced the HIN-1 coding region in 10 familial breast cancer patients with positive logarithm of the odds scores of at least one of the markers flanking HIN-1. We also sequenced the HIN-1 coding region in 15 BRCA1 and 35 sporadic breast tumors to determine whether HIN-1 is the target of the frequent 5q loss in BRCA1 tumors. No sequence alterations were found in any of the cases analyzed. However, analysis of HIN-1 promoter methylation status revealed that in striking contrast to sporadic cases, there is a nearly complete lack of HIN-1 methylation in BRCA1 tumors (P < 0.0001). Sporadic breast tumors with a "BRCA1-like" histopathological phenotype also demonstrated significantly lower frequency of HIN-1 promoter methylation (P = 0.01) compared with other cancer types, and there was also a difference among tumors based on their estrogen receptor and HER2 status (P = 0.006), suggesting that HIN-1 methylation patterns are associated with specific breast cancer subtypes.

CGH analysis of familial non-BRCA1/BRCA2 breast tumors and mutation screening of a candidate locus on chromosome 17q11.2-12

Abstract: Mutations in the known predisposing breast cancer genes BRCA1 and BRCA2 account for only a small proportion (<10%) of breast cancer families in the Stockholm region of Sweden. This study aims to identify novel predisposing genes in non-BRCA1/BRCA2 breast cancer families. We have employed comparative genomic hybridization (CGH) and loss of heterozygosity (LOH) data in combination with data from a recently carried out genome wide linkage scan, in an effort to identify chromosomal regions harboring potential breast cancer genes. CGH revealed loss of chromosome 17 and chromosome 6q to be a frequent event in high-risk breast cancer families, while gain of 8q was most prevalent in low-risk families. The loss of chromosome 17 was consistent with previous LOH studies and so this region was investigated further. Disease was shown to be linked to chromosome 17 in those families exhibiting loss of the chromosome in both CGH and LOH analyses. An overlapping region of linkage was determined to lie between markers D17S1294 and D17S1293, fine mapping of the region delineated a region between markers D17S1880 and D17S1293. Ten genes were determined to lie within this 1.5 Mb region and families were screened for germline mutations in these genes. In conclusion, we have investigated one possible small region on chromosome 17 for its involvement in high-risk non-BRCA1/BRCA2 breast cancer families. No predisposing mutations were identified in the 10 genes investigated in this study, however further analysis of chromosome 17 is warranted.

Estrogen receptors and human disease

Abstract: Estrogens influence many physiological processes in mammals, including but not limited to reproduction, cardiovascular health, bone integrity, cognition, and behavior. Given this widespread role for estrogen in human physiology, it is not surprising that estrogen is also implicated in the development or progression of numerous diseases, which include but are not limited to various types of cancer (breast, ovarian, colorectal, prostate, endometrial), osteoporosis, neurodegenerative diseases, cardiovascular disease, insulin resistance, lupus erythematosus, endometriosis, and obesity. In many of these diseases, estrogen mediates its effects through the estrogen receptor (ER), which serves as the basis for many therapeutic interventions. This Review will describe diseases in which estrogen, through the ER, plays a role in the development or severity of disease.

Population BRCA1 and BRCA2 Mutation Frequencies and Cancer Penetrances: A Kin–Cohort Study in Ontario, Canada

Abstract: Background: BRCA1 and BRCA2 mutations in general populations and in various types of cancers have not been well characterized. We investigated the presence of these mutations in unselected patients with newly diagnosed incident ovarian cancer in Ontario, Canada, with respect to cancers reported among their relatives. Methods: A population series of 1171 unselected patients with incident ovarian cancer diagnosed between January 1, 1995, and December 31, 1999, in Ontario, Canada, was screened for germline mutations throughout the BRCA1 and BRCA2 genes. Screening involved testing for common variants, then protein truncation testing of long exons, and then denaturing gradient gel electrophoresis or denaturing high-performance liquid chromatography for the remainder of BRCA1 and BRCA2, respectively. Cox regression analysis was used to examine cancer outcomes reported by the case probands for their 8680 fi rst-degree relatives. Population allele frequencies and relative risks (RRs) were de rived from the regression results by an extension of Saunders – Begg methods. Age-specifi c Ontario cancer incidence rates were used to estimate cumulative incidence of cancer to age 80 years by mutation status. Results: Among 977 patients with invasive ovarian cancer, 75 had BRCA1 mutations and 54 had BRCA2 mutations, for a total mutation frequency of 13.2% (95% confi dence interval [CI] = 11.2% to 15.5%). Higher risks for various cancer types in the general Ontario population were associated with BRCA1 mutation carriage than with noncarriage, including ovarian (RR = 21, 95% CI = 12 to 36), female breast (RR = 11, 95% CI = 7.5 to 15), and testis (RR = 17, 95% CI = 1.3 to 230) cancers. Higher risks were also associated with BRCA2 mutation carriage than with noncarriage, particularly for ovarian (RR = 7.0, 95% CI = 3.1 to 16), female and male breast (RR = 4.6, 95% CI = 2.7 to 7.8, and RR = 102, 95% CI = 9.9 to 1050, respectively), and pancreatic (RR = 6.6, 95% CI = 1.9 to 23) cancers. Cancer risks differed according to the mutation’s position in the gene. Estimated cumulative incidence to age 80 years among women carrying BRCA1 mutations was 24% for ovarian cancer and 90% for breast cancer and among women carrying BRCA2 mutations was 8.4% for ovarian cancer and 41% for breast cancer. For the general Ontario population, estimated carrier frequencies of BRCA1 and BRCA2 mutations, respectively, were 0.32% (95% CI = 0.23% to 0.45%) and 0.69% (95% CI = 0.43% to 1.10%). Conclusions: BRCA1 and BRCA2 mutations may be more frequent in general populations than previously thought and may be associated with various types of cancers. [J Natl Cancer Inst 2006;98: 1694 – 706 ]

Network-based global inference of human disease genes

Abstract: Deciphering the genetic basis of human diseases is an important goal of biomedical research. On the basis of the assumption that phenotypically similar diseases are caused by functionally related genes, we propose a computational framework that integrates human protein-protein interactions, disease phenotype similarities, and known gene-phenotype associations to capture the complex relationships between phenotypes and genotypes. We develop a tool named CIPHER to predict and prioritize disease genes, and we show that the global concordance between the human protein network and the phenotype network reliably predicts disease genes. Our method is applicable to genetically uncharacterized phenotypes, effective in the genome-wide scan of disease genes, and also extendable to explore gene cooperativity in complex diseases. The predicted genetic landscape of over 1000 human phenotypes, which reveals the global modular organization of phenotype-genotype relationships. The genome-wide prioritization of candidate genes for over 5000 human phenotypes, including those with under-characterized disease loci or even those lacking known association, is publicly released to facilitate future discovery of disease genes.