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Dive into the research topics where Manjeet K. Bolla is active.

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Featured researches published by Manjeet K. Bolla.


Journal of Clinical Oncology | 2012

CHEK2*1100delC Heterozygosity in Women With Breast Cancer Associated With Early Death, Breast Cancer–Specific Death, and Increased Risk of a Second Breast Cancer

Maren Weischer; Børge G. Nordestgaard; Paul Pharoah; Manjeet K. Bolla; Heli Nevanlinna; Laura J. van't Veer; Montserrat Garcia-Closas; John L. Hopper; Per Hall; Irene L. Andrulis; Peter Devilee; Peter A. Fasching; Hoda Anton-Culver; Diether Lambrechts; Maartje J. Hooning; Angela Cox; Graham G. Giles; Barbara Burwinkel; Annika Lindblom; Fergus J. Couch; Arto Mannermaa; Grethe Grenaker Alnæs; Esther M. John; Thilo Dörk; Henrik Flyger; Alison M. Dunning; Qin Wang; Taru A. Muranen; Richard van Hien; Jonine D. Figueroa

PURPOSE We tested the hypotheses that CHEK2*1100delC heterozygosity is associated with increased risk of early death, breast cancer-specific death, and risk of a second breast cancer in women with a first breast cancer. PATIENTS AND METHODS From 22 studies participating in the Breast Cancer Association Consortium, 25,571 white women with invasive breast cancer were genotyped for CHEK2*1100delC and observed for up to 20 years (median, 6.6 years). We examined risk of early death and breast cancer-specific death by estrogen receptor status and risk of a second breast cancer after a first breast cancer in prospective studies. RESULTS CHEK2*1100delC heterozygosity was found in 459 patients (1.8%). In women with estrogen receptor-positive breast cancer, multifactorially adjusted hazard ratios for heterozygotes versus noncarriers were 1.43 (95% CI, 1.12 to 1.82; log-rank P = .004) for early death and 1.63 (95% CI, 1.24 to 2.15; log-rank P < .001) for breast cancer-specific death. In all women, hazard ratio for a second breast cancer was 2.77 (95% CI, 2.00 to 3.83; log-rank P < .001) increasing to 3.52 (95% CI, 2.35 to 5.27; log-rank P < .001) in women with estrogen receptor-positive first breast cancer only. CONCLUSION Among women with estrogen receptor-positive breast cancer, CHEK2*1100delC heterozygosity was associated with a 1.4-fold risk of early death, a 1.6-fold risk of breast cancer-specific death, and a 3.5-fold risk of a second breast cancer. This is one of the few examples of a genetic factor that influences long-term prognosis being documented in an extensive series of women with breast cancer.


Human Molecular Genetics | 2013

A genome-wide association scan (GWAS) for mean telomere length within the COGS project: identified loci show little association with hormone-related cancer risk

Karen A. Pooley; Stig E. Bojesen; Maren Weischer; Sune F. Nielsen; Deborah Thompson; Ali Amin Al Olama; Kyriaki Michailidou; Jonathan Tyrer; Sara Benlloch; Judith E. Brown; Tina Audley; Robert Luben; Kay-Tee Khaw; David E. Neal; Freddie C. Hamdy; Jenny Donovan; Zsofia Kote-Jarai; Caroline Baynes; Mitul Shah; Manjeet K. Bolla; Qin Wang; Joe Dennis; Ed Dicks; Rongxi Yang; Anja Rudolph; Joellen M. Schildkraut; Jenny Chang-Claude; Barbara Burwinkel; Georgia Chenevix-Trench; Paul Pharoah

Mean telomere length (TL) in blood cells is heritable and has been reported to be associated with risks of several diseases, including cancer. We conducted a meta-analysis of three GWAS for TL (total n=2240) and selected 1629 variants for replication via the “iCOGS” custom genotyping array. All ∼200 000 iCOGS variants were analysed with TL, and those displaying associations in healthy controls (n = 15 065) were further tested in breast cancer cases (n = 11 024). We found a novel TL association (Ptrend < 4 × 10−10) at 3p14.4 close to PXK and evidence (Ptrend < 7 × 10−7) for TL loci at 6p22.1 (ZNF311) and 20q11.2 (BCL2L1). We additionally confirmed (Ptrend < 5 × 10−14) the previously reported loci at 3q26.2 (TERC), 5p15.3 (TERT) and 10q24.3 (OBFC1) and found supportive evidence (Ptrend < 5 × 10−4) for the published loci at 2p16.2 (ACYP2), 4q32.2 (NAF1) and 20q13.3 (RTEL1). SNPs tagging these loci explain TL differences of up to 731 bp (corresponding to 18% of total TL in healthy individuals), however, they display little direct evidence for association with breast, ovarian or prostate cancer risks.


Journal of Clinical Oncology | 2016

Age- and Tumor Subtype–Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers

Marjanka K. Schmidt; Frans B. L. Hogervorst; Richard van Hien; Sten Cornelissen; Annegien Broeks; Muriel A. Adank; Hanne Meijers; Quinten Waisfisz; Antoinette Hollestelle; Mieke Schutte; Ans van den Ouweland; Maartje J. Hooning; Irene L. Andrulis; Hoda Anton-Culver; Natalia Antonenkova; Antonis C. Antoniou; Volker Arndt; Marina Bermisheva; Natalia Bogdanova; Manjeet K. Bolla; Hiltrud Brauch; Hermann Brenner; Thomas Brüning; Barbara Burwinkel; Jenny Chang-Claude; Georgia Chenevix-Trench; Fergus J. Couch; Angela Cox; Simon S. Cross; Kamila Czene

PURPOSE CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC. PATIENTS AND METHODS CHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies. RESULTS Proportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center-based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10(-20)). The OR was higher for estrogen receptor (ER)-positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10(-21)]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10(-4)). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom. CONCLUSION These CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into guidelines for intensified screening and follow-up.


Cancer Research | 2015

Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures

Jennifer Stone; Deborah Thompson; Isabel dos Santos Silva; Christopher G. Scott; Rulla M. Tamimi; Sara Lindström; Peter Kraft; Aditi Hazra; Jingmei Li; Louise Eriksson; Kamila Czene; Per Hall; Matt Jensen; Julie M. Cunningham; Janet E. Olson; Kristen Purrington; Fergus J. Couch; Judith E. Brown; Jean Leyland; Ruth Warren; Robert Luben; Kay-Tee Khaw; Paula Smith; Nicholas J. Wareham; Sebastian M. Jud; Katharina Heusinger; Matthias W. Beckmann; Julie A. Douglas; Kaanan P. Shah; Heang Ping Chan

Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.


Human Molecular Genetics | 2014

DNA mismatch repair gene MSH6 implicated in determining age at natural menopause

John Perry; Yi-Hsiang Hsu; Daniel I. Chasman; Andrew D. Johnson; Cathy E. Elks; Eva Albrecht; Irene L. Andrulis; Jonathan Beesley; Gerald S. Berenson; Sven Bergmann; Stig E. Bojesen; Manjeet K. Bolla; Judith E. Brown; Julie E. Buring; Harry Campbell; Jenny Chang-Claude; Georgia Chenevix-Trench; Tanguy Corre; Fergus J. Couch; Angela Cox; Kamila Czene; Adamo Pio D'Adamo; Gail Davies; Ian J. Deary; Joe Dennis; Douglas F. Easton; Ellen G. Engelhardt; Johan G. Eriksson; Tonu Esko; Peter A. Fasching

The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10−9), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.


Nature Genetics | 2016

Five endometrial cancer risk loci identified through genome-wide association analysis

Timothy Cheng; D Thompson; Tracy O'Mara; Jodie N. Painter; Dylan M. Glubb; Susanne Flach; Annabelle Lewis; Juliet D. French; Luke Freeman-Mills; David N. Church; Maggie Gorman; Lynn Martin; Shirley Hodgson; Penelope M. Webb; John Attia; Elizabeth G. Holliday; Mark McEvoy; Rodney J. Scott; Anjali K. Henders; Nicholas G. Martin; Grant W. Montgomery; Dale R. Nyholt; Shahana Ahmed; Catherine S. Healey; Mitul Shah; Joe Dennis; Peter A. Fasching; Matthias W. Beckmann; Alexander Hein; Arif B. Ekici

We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r2 = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer.


Endocrine-related Cancer | 2016

CYP19A1 fine-mapping and Mendelian randomization: estradiol is causal for endometrial cancer

Deborah Thompson; Tracy O'Mara; Dylan M. Glubb; Jodie N. Painter; Timothy Cheng; Elizabeth Folkerd; Deborah Doody; Joe Dennis; Penelope M. Webb; Maggie Gorman; Lynn Martin; Shirley Hodgson; Kyriaki Michailidou; Jonathan Tyrer; Mel Maranian; Per Hall; Kamila Czene; Hatef Darabi; Jingmei Li; Peter A. Fasching; Alexander Hein; Matthias W. Beckmann; Arif B. Ekici; Thilo Dörk; Peter Hillemanns; Matthias Dürst; Ingo B. Runnebaum; Hui Zhao; Jeroen Depreeuw; Stefanie Schrauwen

Candidate gene studies have reported CYP19A1 variants to be associated with endometrial cancer and with estradiol (E2) concentrations. We analyzed 2937 single nucleotide polymorphisms (SNPs) in 6608 endometrial cancer cases and 37 925 controls and report the first genome wide-significant association between endometrial cancer and a CYP19A1 SNP (rs727479 in intron 2, P=4.8×10−11). SNP rs727479 was also among those most strongly associated with circulating E2 concentrations in 2767 post-menopausal controls (P=7.4×10−8). The observed endometrial cancer odds ratio per rs727479 A-allele (1.15, CI=1.11–1.21) is compatible with that predicted by the observed effect on E2 concentrations (1.09, CI=1.03–1.21), consistent with the hypothesis that endometrial cancer risk is driven by E2. From 28 candidate-causal SNPs, 12 co-located with three putative gene-regulatory elements and their risk alleles associated with higher CYP19A1 expression in bioinformatical analyses. For both phenotypes, the associations with rs727479 were stronger among women with a higher BMI (Pinteraction=0.034 and 0.066 respectively), suggesting a biologically plausible gene-environment interaction.


EBioMedicine | 2015

Crowdsourcing the General Public for Large Scale Molecular Pathology Studies in Cancer

Francisco José Candido dos 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; Amy F.M. Carton; 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

Background Citizen science, scientific research conducted by non-specialists, has the potential to facilitate biomedical research using available large-scale data, however validating the results is challenging. The Cell Slider is a citizen science project that intends to share images from tumors with the general public, enabling them to score tumor markers independently through an internet-based interface. Methods From October 2012 to June 2014, 98,293 Citizen Scientists accessed the Cell Slider web page and scored 180,172 sub-images derived from images of 12,326 tissue microarray cores labeled for estrogen receptor (ER). We evaluated the accuracy of Citizen Scientists ER classification, and the association between ER status and prognosis by comparing their test performance against trained pathologists. Findings The area under ROC curve was 0.95 (95% CI 0.94 to 0.96) for cancer cell identification and 0.97 (95% CI 0.96 to 0.97) for ER status. ER positive tumors scored by Citizen Scientists were associated with survival in a similar way to that scored by trained pathologists. Survival probability at 15 years were 0.78 (95% CI 0.76 to 0.80) for ER-positive and 0.72 (95% CI 0.68 to 0.77) for ER-negative tumors based on Citizen Scientists classification. Based on pathologist classification, survival probability was 0.79 (95% CI 0.77 to 0.81) for ER-positive and 0.71 (95% CI 0.67 to 0.74) for ER-negative tumors. The hazard ratio for death was 0.26 (95% CI 0.18 to 0.37) at diagnosis and became greater than one after 6.5 years of follow-up for ER scored by Citizen Scientists, and 0.24 (95% CI 0.18 to 0.33) at diagnosis increasing thereafter to one after 6.7 (95% CI 4.1 to 10.9) years of follow-up for ER scored by pathologists. Interpretation Crowdsourcing of the general public to classify cancer pathology data for research is viable, engages the public and provides accurate ER data. Crowdsourced classification of research data may offer a valid solution to problems of throughput requiring human input.


International Journal of Cancer | 2015

Investigation of gene‐environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

Anja Rudolph; Roger L. Milne; Thérèse Truong; Julia A. Knight; Petra Seibold; Dieter Flesch-Janys; Sabine Behrens; Ursula Eilber; Manjeet K. Bolla; Qin Wang; Joe Dennis; Alison M. Dunning; Mitul Shah; Hannah Munday; Hatef Darabi; Mikael Eriksson; Judith S. Brand; Janet E. Olson; Celine M. Vachon; Emily Hallberg; J. Esteban Castelao; Angel Carracedo; M.D. Torres; Jingmei Li; Keith Humphreys; Emilie Cordina-Duverger; Florence Menegaux; Henrik Flyger; Børge G. Nordestgaard; Sune F. Nielsen

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes‐type shrinkage estimator. Six SNPs showed interactions with associated p‐values (pint) <1.1 × 10−3. None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER‐negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER‐negative BC risk in women <160 cm (OR = 0.83, p = 0.039, pint = 1.9 × 10−4). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10−4), and absent in women who had had just one (OR = 0.96, p = 0.19, pint = 6.1 × 10−4). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10−5), but no association was observed in current smokers (OR = 1.07, p = 0.14, pint = 3.4 × 10−4). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.


Cancer Epidemiology, Biomarkers & Prevention | 2014

Alcohol Consumption and Survival after a Breast Cancer Diagnosis: A Literature-based Meta-analysis and Collaborative Analysis of Data for 29,239 Cases

Alaa M.G. Ali; Marjanka K. Schmidt; Manjeet K. Bolla; Qin Wang; Manuela Gago-Dominguez; J. Esteban Castelao; Angel Carracedo; Víctor Muñoz Garzón; Stig E. Bojesen; Børge G. Nordestgaard; Henrik Flyger; Jenny Chang-Claude; Alina Vrieling; Anja Rudolph; Petra Seibold; Heli Nevanlinna; Taru A. Muranen; Kirsimari Aaltonen; Carl Blomqvist; Keitaro Matsuo; Hidemi Ito; Hiroji Iwata; Akiyo Horio; Esther M. John; Mark Sherman; Jolanta Lissowska; Jonine D. Figueroa; Montserrat Garcia-Closas; Hoda Anton-Culver; Mitul Shah

Background: Evidence for an association of alcohol consumption with prognosis after a diagnosis of breast cancer has been inconsistent. We have reviewed and summarized the published evidence and evaluated the association using individual patient data from multiple case cohorts. Methods: A MEDLINE search to identify studies published up to January 2013 was performed. We combined published estimates of survival time for “moderate drinkers” versus nondrinkers. An analysis of individual participant data using Cox regression was carried out using data from 11 case cohorts. Results: We identified 11 published studies suitable for inclusion in the meta-analysis. Moderate postdiagnosis alcohol consumption was not associated with overall survival [HR, 0.95; 95% confidence interval (CI), 0.85–1.05], but there was some evidence of better survival associated with prediagnosis consumption (HR, 0.80; 95% CI, 0.73–0.88). Individual data on alcohol consumption for 29,239 cases with 4,839 deaths were available from the 11 case cohorts, all of which had data on estrogen receptor (ER) status. For women with ER-positive disease, there was little evidence that pre- or postdiagnosis alcohol consumption is associated with breast cancer–specific mortality, with some evidence of a negative association with all-cause mortality. On the basis of a single study, moderate postdiagnosis alcohol intake was associated with a small reduction in breast cancer–specific mortality for women with ER-negative disease. There was no association with prediagnosis intake for women with ER-negative disease. Conclusion: There was little evidence that pre- or post-diagnosis alcohol consumption is associated with breast cancer–specific mortality for women with ER-positive disease. There was weak evidence that moderate post-diagnosis alcohol intake is associated with a small reduction in breast cancer–specific mortality in ER-negative disease. Impact: Considering the totality of the evidence, moderate postdiagnosis alcohol consumption is unlikely to have a major adverse effect on the survival of women with breast cancer. Cancer Epidemiol Biomarkers Prev; 23(6); 934–45. ©2014 AACR.

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Qin Wang

University of Cambridge

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Joe Dennis

University of Cambridge

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Fergus J. Couch

University of Pennsylvania

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Peter A. Fasching

University of Erlangen-Nuremberg

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Matthias W. Beckmann

University of Erlangen-Nuremberg

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Anja Rudolph

University of Southern California

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Jenny Chang-Claude

German Cancer Research Center

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