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Dive into the research topics where Montserrat Garcia-Closas is active.

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Featured researches published by Montserrat Garcia-Closas.


Nature Genetics | 2009

A genome-wide association study identifies a new ovarian cancer susceptibility locus on 9p22.2

Honglin Song; Susan J. Ramus; Jonathan Tyrer; Kelly L. Bolton; Aleksandra Gentry-Maharaj; Eva Wozniak; Hoda Anton-Culver; Jenny Chang-Claude; Daniel W. Cramer; Richard A. DiCioccio; Thilo Dörk; Ellen L. Goode; Marc T. Goodman; Joellen M. Schildkraut; Thomas A. Sellers; Laura Baglietto; Matthias W. Beckmann; Jonathan Beesley; Jan Blaakær; Michael E. Carney; Stephen J. Chanock; Zhihua Chen; Julie M. Cunningham; Ed Dicks; Jennifer A. Doherty; Matthias Dürst; Arif B. Ekici; David Fenstermacher; Brooke L. Fridley; Graham G. Giles

Epithelial ovarian cancer has a major heritable component, but the known susceptibility genes explain less than half the excess familial risk. We performed a genome-wide association study (GWAS) to identify common ovarian cancer susceptibility alleles. We evaluated 507,094 SNPs genotyped in 1,817 cases and 2,353 controls from the UK and ∼2 million imputed SNPs. We genotyped the 22,790 top ranked SNPs in 4,274 cases and 4,809 controls of European ancestry from Europe, USA and Australia. We identified 12 SNPs at 9p22 associated with disease risk (P < 10−8). The most significant SNP (rs3814113; P = 2.5 × 10−17) was genotyped in a further 2,670 ovarian cancer cases and 4,668 controls, confirming its association (combined data odds ratio (OR) = 0.82, 95% confidence interval (CI) 0.79–0.86, Ptrend = 5.1 × 10−19). The association differs by histological subtype, being strongest for serous ovarian cancers (OR 0.77, 95% CI 0.73–0.81, Ptrend = 4.1 × 10−21).


Molecular Oncology | 2010

Genetic susceptibility to breast cancer

Nasim Mavaddat; Antonis C. Antoniou; Douglas F. Easton; Montserrat Garcia-Closas

Genetic and lifestyle/environmental factors are implicated in the aetiology of breast cancer. This review summarizes the current state of knowledge on rare high penetrance mutations, as well as moderate and low‐penetrance genetic variants implicated in breast cancer aetiology. We summarize recent discoveries from large collaborative efforts to combine data from candidate gene studies, and to conduct genome‐wide association studies (GWAS), primarily in breast cancers in the general population. These findings are compared with results from collaborative efforts aiming to identify genetic modifiers in BRCA1 and BRCA2 carriers. Breast cancer is a heterogeneous disease, and tumours from BRCA1 and BRCA2 carriers display distinct pathological characteristics when compared with tumours unselected for family history. The relationship between genetic variants and pathological subtypes of breast cancer, and the implication of discoveries of novel genetic variants to risk prediction in BRCA1/2 mutation carriers and in populations unselected for mutation carrier status, are discussed.


Human Genetics | 2014

Genome-wide association study of endometrial cancer in E2C2

Immaculata De Vivo; Jennifer Prescott; Veronica Wendy Setiawan; Sara H. Olson; Nicolas Wentzensen; John Attia; Amanda Black; Louise A. Brinton; Chu Chen; Constance Chen; Linda S. Cook; Marta Crous-Bou; Jennifer A. Doherty; Alison M. Dunning; Douglas F. Easton; Christine M. Friedenreich; Montserrat Garcia-Closas; Mia M. Gaudet; Christopher A. Haiman; Susan E. Hankinson; Patricia Hartge; Brian E. Henderson; Elizabeth G. Holliday; Pamela L. Horn-Ross; David J. Hunter; Loic Le Marchand; Xiaolin Liang; Jolanta Lissowska; Jirong Long; Lingeng Lu

Endometrial cancer (EC), a neoplasm of the uterine epithelial lining, is the most common gynecological malignancy in developed countries and the fourth most common cancer among US women. Women with a family history of EC have an increased risk for the disease, suggesting that inherited genetic factors play a role. We conducted a two-stage genome-wide association study of Type I EC. Stage 1 included 5,472 women (2,695 cases and 2,777 controls) of European ancestry from seven studies. We selected independent single-nucleotide polymorphisms (SNPs) that displayed the most significant associations with EC in Stage 1 for replication among 17,948 women (4,382 cases and 13,566 controls) in a multiethnic population (African America, Asian, Latina, Hawaiian and European ancestry), from nine studies. Although no novel variants reached genome-wide significance, we replicated previously identified associations with genetic markers near the HNF1B locus. Our findings suggest that larger studies with specific tumor classification are necessary to identify novel genetic polymorphisms associated with EC susceptibility.


Human Molecular Genetics | 2009

Association between invasive ovarian cancer susceptibility and 11 best candidate SNPs from breast cancer genome-wide association study

Honglin Song; Susan J. Ramus; Susanne K. Kjaer; Richard A. DiCioccio; Georgia Chenevix-Trench; Celeste Leigh Pearce; Estrid Høgdall; Alice S. Whittemore; Valerie McGuire; Claus Høgdall; Jan Blaakær; Anna H. Wu; David Van Den Berg; Daniel O. Stram; Usha Menon; Aleksandra Gentry-Maharaj; Ian Jacobs; Penny Webb; Jonathan Beesley; Xiaoqing Chen; Mary Anne Rossing; Jennifer A. Doherty; Jenny Chang-Claude; Shan Wang-Gohrke; Marc T. Goodman; Galina Lurie; Pamela J. Thompson; Michael E. Carney; Roberta B. Ness; Kirsten B. Moysich

Because both ovarian and breast cancer are hormone-related and are known to have some predisposition genes in common, we evaluated 11 of the most significant hits (six with confirmed associations with breast cancer) from the breast cancer genome-wide association study for association with invasive ovarian cancer. Eleven SNPs were initially genotyped in 2927 invasive ovarian cancer cases and 4143 controls from six ovarian cancer case-control studies. Genotype frequencies in cases and controls were compared using a likelihood ratio test in a logistic regression model stratified by study. Initially, three SNPs (rs2107425 in MRPL23, rs7313833 in PTHLH, rs3803662 in TNRC9) were weakly associated with ovarian cancer risk and one SNP (rs4954956 in NXPH2) was associated with serous ovarian cancer in non-Hispanic white subjects (P-trend < 0.1). These four SNPs were then genotyped in an additional 4060 cases and 6308 controls from eight independent studies. Only rs4954956 was significantly associated with ovarian cancer risk both in the replication study and in combined analyses. This association was stronger for the serous histological subtype [per minor allele odds ratio (OR) 1.07 95% CI 1.01-1.13, P-trend = 0.02 for all types of ovarian cancer and OR 1.14 95% CI 1.07-1.22, P-trend = 0.00017 for serous ovarian cancer]. In conclusion, we found that rs4954956 was associated with increased ovarian cancer risk, particularly for serous ovarian cancer. However, none of the six confirmed breast cancer susceptibility variants we tested was associated with ovarian cancer risk. Further work will be needed to identify the causal variant associated with rs4954956 or elucidate its function.


International Journal of Cancer | 2017

Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium.

Myrto Barrdahl; Anja Rudolph; John L. Hopper; Melissa C. Southey; Annegien Broeks; Peter A. Fasching; Matthias W. Beckmann; Manuela Gago-Dominguez; J. Esteban Castelao; Pascal Guénel; Thérèse Truong; Stig E. Bojesen; Susan M. Gapstur; Mia M. Gaudet; Hermann Brenner; Volker Arndt; Hiltrud Brauch; Ute Hamann; Arto Mannermaa; Diether Lambrechts; Lynn Jongen; Dieter Flesch-Janys; Kathrin Thoene; Fergus J. Couch; Graham G. Giles; Jacques Simard; Mark S. Goldberg; Jonine D. Figueroa; Kyriaki Michailidou; Manjeet K. Bolla

Investigating the most likely causal variants identified by fine‐mapping analyses may improve the power to detect gene–environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine‐scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER–) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene–environment interactions were identified as noteworthy (BFDPu2009<u20090.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR‐rs7558475 and current smoking (ORintu2009=u20090.77, 95% CI: 0.67–0.88, pintu2009=u20091.8 × 10−4). The interaction with the strongest statistical evidence was found between 5q14‐rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16–1.59, pintu2009=u20091.9 × 10−5) in relation to ER– disease risk. The remaining two gene–environment interactions were also identified in relation to ER– breast cancer risk and were found between 3p21‐rs6796502 and age at menarche (ORintu2009=u20091.26, 95% CI: 1.12–1.43, pint =1.8 × 10−4) and between 8q23‐rs13267382 and age at first full‐term pregnancy (ORintu2009=u20090.89, 95% CI: 0.83–0.95, pintu2009=u20095.2 × 10−4). While these results do not suggest any strong gene–environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.


Clinical Cancer Research | 2010

Abstract ED3-3: Etiological clues from breast cancer GWAS

Montserrat Garcia-Closas

Breast cancer is a heterogeneous disease and risk factors can be differentially associated with the development of distinct tumors subtypes that manifest different biological and clinical behavior. Tumor subtypes, such as those defined by hormone receptor expression, show different age-specific incidence rate patterns and risk factor profiles. In addition, tumors from BRCA1 and BRCA2 mutation carriers display distinct pathological characteristics. Large collaborative efforts to conduct genome-wide association studies (GWAS) have lead to recent discoveries of low penetrance, common susceptibility loci that also show distinct associations by tumor subtypes. Follow up studies are evaluating the biological mechanisms underlying the observed risk associations, as well as potential gene-gene and gene-environment interactions. The relationship between genetic variants associated with pathological subtypes of breast cancer, and the implication of discoveries of novel genetic variants to risk prediction in BRCA1/2 mutation carriers and the general population will be discussed. These discoveries might lead to improvements in our understanding of the etiology of specific tumor types, which may enable the development of targeted prevention, early detection, and treatment strategies. Citation Information: Clin Cancer Res 2010;16(7 Suppl):ED3-3


IARC scientific publications | 2011

Population-based study designs in molecular epidemiology.

Montserrat Garcia-Closas; Roel Vermeulen; David Cox; Qing Lan; Neil E. Caporaso; N. Rothman


Oxford University Press | 2010

Human Genome Epidemiology: Building the Evidence for Using Genetic Information to Improve Health and Prevent Disease: Second Edition

Muin J. Khoury; Lars Bertram; Paolo Boffetta; Adam S. Butterworth; Stephen J. Chanock; Siobhan M. Dolan; Isabel Fortier; Montserrat Garcia-Closas; Marta Gwinn; Julian P. T. Higgins; A. J W Cecile Janssens; James Ostell; Ryan P. Owen; Pagon Ra; Timothy Rebbeck; Nathaniel Rothman; Jonine L. Bernstein; Paul R. Burton; Harry Campbell; Anand P. Chokkalingam; Helena Furberg; Julian Little; Thomas R. O'Brien; Daniela Seminara; Paolo Vineis; Deborah M. Winn; Wei Yu; John P A Ioannidis


Archive | 2016

Additional file 3: of Prognostic value of automated KI67 scoring in breast cancer: a centralised evaluation of 8088 patients from 10 study groups

Mustapha Abubakar; Nick Orr; Frances Daley; Penny Coulson; H. Ali; Fiona Blows; Javier Benitez; Roger L. Milne; H Brenner; Christa Stegmaier; Arto Mannermaa; Jenny Chang-Claude; Anja Rudolph; Peter Sinn; Fergus J. Couch; P. Devilee; R.A.E.M. Tollenaar; Caroline M. Seynaeve; Jonine Figueroa; Mark E. Sherman; Jolanta Lissowska; Stephen Hewitt; Diana Eccles; Maartje J. Hooning; Antoinette Hollestelle; John W. M. Martens; Carolien Deurzen; kConFab Investigators; Manjeet K. Bolla; Qin Wang


Archive | 2015

Research data supporting "Crowdsourcing the General Public for Large Scale Molecular Pathology Studies in Cancer"

Francisco J. Candido do Reis; Stuart Lynn; H. Raza Ali; Diana Eccles; Andrew M. Hanby; Elena Provenzano; Carlos Caldas; William J. Howat; Leigh-Anne McDuffus; Bin Liu; Frances Daley; Penny Coulson; Rupesh J.Vyas; Leslie M. Harris; Joanna M. Owens; Janette P. McQuillan; Andy M. Paterson; Zohra Hirji; Sarah K. Christie; Amber R. Holmes; Marjanka K. Schmidt; Montserrat Garcia-Closas; Douglas F. Easton; Manjeet K. Bolla; Qin Wang; Javier Benitez; Roger L. Milne; Arto Mannermaa; Fergus J. Couch; P. Devilee

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Penny Coulson

Institute of Cancer Research

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Jolanta Lissowska

National Institutes of Health

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Fiona Blows

University of Cambridge

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Frances Daley

Institute of Cancer Research

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