Publications by authors named "Mikael Hartman"

154 Publications

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer.

HGG Adv 2021 Jul 16;2(3). Epub 2021 Jun 16.

Department of Virus, Lifestyle, and Genes, Danish Cancer Society Research Center, Copenhagen, Denmark.

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were >1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.
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http://dx.doi.org/10.1016/j.xhgg.2021.100042DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312632PMC
July 2021

Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element.

Am J Hum Genet 2021 Jul 18;108(7):1190-1203. Epub 2021 Jun 18.

Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10).
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http://dx.doi.org/10.1016/j.ajhg.2021.05.013DOI Listing
July 2021

Gene-Environment Interactions Relevant to Estrogen and Risk of Breast Cancer: Can Gene-Environment Interactions Be Detected Only among Candidate SNPs from Genome-Wide Association Studies?

Cancers (Basel) 2021 May 14;13(10). Epub 2021 May 14.

Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, 2730 Herlev, Denmark.

In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (-2df = 1.2 × 10). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (-2df = 1.1 × 10). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.
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http://dx.doi.org/10.3390/cancers13102370DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8156547PMC
May 2021

Admission discipline and timing of admission may influence outcomes for gastrointestinal bleeding patients.

ANZ J Surg 2021 May 13. Epub 2021 May 13.

Yong Loo Lin School of Medicine, National University of Singapore, Singapore.

Background: Bleeding of the gastrointestinal tract (BGIT) is a common gastrointestinal emergency. There is no consensus whether this condition should be admitted to medical or surgical discipline. Timing of presentation may also impact patient outcomes due to differences in healthcare resource availability. This study thus aims to investigate the impact of admitting discipline and timing of admission on patient outcomes in BGIT.

Methods: A 2-year tertiary institution database was retrospectively reviewed. Outcome measures included 30-day mortality, 30-day readmissions and rebleeding requiring repeat endoscopic, angiographic or surgical interventions. Secondary outcome measures included time to endoscopy, percutaneous angiographic interventions and surgery. The effect of admission discipline (medical versus surgical) and time of admission (office-hours versus after office-hours) were analysed using a propensity-score-adjusted estimate.

Results: A total of 1384 patients were included for analysis, medical (n = 853), surgical (n = 530); during office-hours (n = 785) and after office-hours (n = 595). After propensity-score-adjusted analysis, no significant differences in mortality or readmissions were noted between medical or surgical admissions. Patients admitted under surgery were less likely to sustain rebleeding (P = 0.004) for lower BGIT and had an earlier time to endoscopy for upper BGIT (P = 0.04). Patients admitted after office-hours had similar outcomes with those admitted during office hours apart from a delay in time to endoscopy (P = 0.02).

Conclusion: For BGIT patients, admission to a surgical discipline compared to a medical discipline appeared to have at least equivalent patient outcomes. Patients presenting with BGIT after office-hours were more likely to experience a delay to endoscopy, although it did not affect patient mortality.
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http://dx.doi.org/10.1111/ans.16873DOI Listing
May 2021

Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer.

Cancers (Basel) 2021 Apr 28;13(9). Epub 2021 Apr 28.

Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore, Singapore 169610, Singapore.

Mammography is extensively used for breast cancer screening but has high false-positive rates. Here, prospectively collected blood samples were used to identify circulating microRNA (miRNA) biomarkers to discriminate between malignant and benign breast lesions among women with abnormal mammograms. The Discovery cohort comprised 72 patients with breast cancer and 197 patients with benign breast lesions, while the Validation cohort had 73 and 196 cancer and benign cases, respectively. Absolute expression levels of 324 miRNAs were determined using RT-qPCR. miRNA biomarker panels were identified by: (1) determining differential expression between malignant and benign breast lesions, (2) focusing on top differentially expressed miRNAs, and (3) building panels from an unbiased search among all expressed miRNAs. Two-fold cross-validation incorporating a feature selection algorithm and logistic regression was performed. A six-miRNA biomarker panel identified by the third strategy, had an area under the curve (AUC) of 0.785 and 0.774 in the Discovery and Validation cohorts, respectively, and an AUC of 0.881 when differentiating between cases versus those with benign lesions or healthy individuals with normal mammograms. Biomarker panel scores increased with tumor size, stage and number of lymph nodes involved. Our work demonstrates that circulating miRNA signatures can potentially be used with mammography to differentiate between patients with malignant and benign breast lesions.
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http://dx.doi.org/10.3390/cancers13092130DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124944PMC
April 2021

Cohort profile: The Singapore Breast Cancer Cohort (SGBCC), a multi-center breast cancer cohort for evaluation of phenotypic risk factors and genetic markers.

PLoS One 2021 26;16(4):e0250102. Epub 2021 Apr 26.

Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore, Singapore.

This article aims to provide a detailed description of the Singapore Breast Cancer Cohort (SGBCC), an ongoing multi-ethnic cohort established with the overarching goal to identify genetic markers for breast cancer risk, prognosis and treatment response, as well as to understand the ethnic differences in disease risk and outcome in an Asian setting. The cohort comprises of breast cancer patients aged 21 years and above from six public hospitals which diagnose and treat nearly 76% breast cancer cases in Singapore. Self-reported data on sociodemographic and lifestyle, reproductive risk factors, medical history and family history of breast or ovarian cancer is collected using a structured questionnaire. Clinical data on tumour characteristics, and treatment modalities are obtained through medical record. Bio-specimens (blood or saliva) is collected at recruitment. Follow-up on survival information is done through routine linkage with the Registry of Births and Deaths. As of 31 December 2016, 7,768 subjects have been recruited to the study with 76% subjects contributed bio-specimens. The SGBCC provides a valuable platform which offers a unique, large and rich resource for new research ideas on breast cancer related phenotypic risk factors and genetic markers.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0250102PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075208PMC
April 2021

Cost effectiveness analysis of a polygenic risk tailored breast cancer screening programme in Singapore.

BMC Health Serv Res 2021 Apr 23;21(1):379. Epub 2021 Apr 23.

Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems Singapore, Singapore, Singapore.

Background: This study aimed to evaluate the cost-effectiveness of a breast cancer screening programme that incorporates genetic testing using breast cancer associated single nucleotide polymorphisms (SNPs), against the current biennial mammogram-only screening programme to aid in its implementation into the current programme in Singapore.

Methods: A Markov model was used to compare the costs and health outcomes of the current screening programme, against a polygenic risk-tailored screening programme, which can advise a long-term screening strategy depending on the individual's polygenic risk. The model took the perspective of the healthcare system, with a time horizon of 40 years, following women from the age of 35 to 74. Epidemiological and cost data were taken from Asian studies, and an annual discount rate of 3% was used. The model outcome was the incremental cost-effectiveness ratio (ICER), calculated from the difference in costs per quality-adjusted life year (QALY). Scenarios with varying risk thresholds for each polygenic risk group were examined. One-way and probabilistic sensitivity analyses were performed to assess parameter uncertainty.

Results: The ICER for a polygenic risk-tailored breast cancer screening programme, compared with the current biennial mammogram-only screening programme, was - 3713.80 SGD/QALY, with incremental costs < 0 and incremental effects > 0. The scenario analysis of different polygenic risk cutoffs showed that the ICERs remain negative, with all ICERs falling within the south-east quadrant of the cost-effectiveness plane, indicating that tailored screening is more cost effective than mammogram-only screening, with lower costs and higher QALYs to be gained. This suggests that a polygenic risk-tailored breast cancer screening programme is cost effective, entailing lower cost than the current mammogram-only programme, while causing no additional harm to women.

Conclusion: Results from this cost-effectiveness analysis show that polygenic risk-tailored screening is cost effective with an ICER of - 3713.80 SGD/QALY. Tailored screening remains cost effective even across varying percentile cutoffs for each risk group. While the results look promising for incorporating polygenic risk into the current breast cancer screening programme, further studies should be conducted to address various limitations.
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http://dx.doi.org/10.1186/s12913-021-06396-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8066868PMC
April 2021

Positive impact of oral hydroxychloroquine and povidone-iodine throat spray for COVID-19 prophylaxis: An open-label randomized trial.

Int J Infect Dis 2021 May 20;106:314-322. Epub 2021 Apr 20.

Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.

Background: We examined whether existing licensed pharmacotherapies could reduce the spread of coronavirus disease 2019 (COVID-19).

Methods: An open-label parallel randomized controlled trial was performed among healthy migrant workers quarantined in a large multi-storey dormitory in Singapore. Forty clusters (each defined as individual floors of the dormitory) were randomly assigned to receive a 42-day prophylaxis regimen of either oral hydroxychloroquine (400 mg once, followed by 200 mg/day), oral ivermectin (12 mg once), povidone-iodine throat spray (3 times/day, 270 μg/day), oral zinc (80 mg/day)/vitamin C (500 mg/day) combination, or oral vitamin C, 500 mg/day. The primary outcome was laboratory evidence of SARS-CoV-2 infection as shown by either: (1) a positive serologic test for SARS-CoV-2 antibody on day 42, or (2) a positive PCR test for SARS-CoV-2 at any time between baseline and day 42.

Results: A total of 3037 asymptomatic participants (mean age, 33.0 years; all men) who were seronegative to SARS-CoV-2 at baseline were included in the primary analysis. Follow-up was nearly complete (99.6%). Compared with vitamin C, significant absolute risk reductions (%, 98.75% confidence interval) were observed for oral hydroxychloroquine (21%, 2-42%) and povidone-iodine throat spray (24%, 7-39%). No statistically significant differences were observed with oral zinc/vitamin C combination (23%, -5 to +41%) and ivermectin (5%, -10 to +22%). Interruptions due to side effects were highest among participants who received zinc/vitamin C combination (6.9%), followed by vitamin C (4.7%), povidone-iodine (2.0%), and hydroxychloroquine (0.7%).

Conclusions: Chemoprophylaxis with either oral hydroxychloroquine or povidone-iodine throat spray was superior to oral vitamin C in reducing SARS-CoV-2 infection in young and healthy men.
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http://dx.doi.org/10.1016/j.ijid.2021.04.035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056783PMC
May 2021

Characterisation of protein-truncating and missense variants in in 15 768 women from Malaysia and Singapore.

J Med Genet 2021 Apr 2. Epub 2021 Apr 2.

Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia

Background: Rare protein-truncating variants (PTVs) in partner and localiser of BRCA2 () confer increased risk to breast cancer, but relatively few studies have reported the prevalence in South-East Asian populations. Here, we describe the prevalence of rare variants in in a population-based study of 7840 breast cancer cases and 7928 healthy Chinese, Malay and Indian women from Malaysia and Singapore, and describe the functional impact of germline missense variants identified in this population.

Methods: Mutation testing was performed on germline DNA (n=15 768) using targeted sequencing panels. The functional impact of missense variants was tested in mouse embryonic stem cell based functional assays.

Results: PTVs in were found in 0.73% of breast cancer patients and 0.14% of healthy individuals (OR=5.44; 95% CI 2.85 to 10.39, p<0.0001). In contrast, rare missense variants in were not associated with increased risk of breast cancer. Whereas PTVs were associated with later stage of presentation and higher-grade tumours, no significant association was observed with missense variants in . However, two novel rare missense variants (p.L1027R and p.G1043V) produced unstable proteins and resulted in a decrease in homologous recombination-mediated repair of DNA double-strand breaks.

Conclusion: Despite genetic and lifestyle differences between Asian and other populations, the population prevalence of PTVs and associated relative risk of breast cancer, are similar to those reported in European populations.
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http://dx.doi.org/10.1136/jmedgenet-2020-107471DOI Listing
April 2021

DNA methylation and breast cancer-associated variants.

Breast Cancer Res Treat 2021 Aug 26;188(3):713-727. Epub 2021 Mar 26.

Genome Institute of Singapore, Human Genetics, Singapore, Singapore.

Background: A breast cancer polygenic risk score (PRS) comprising 313 common variants reliably predicts disease risk. We examined possible relationships between genetic variation, regulation, and expression to clarify the molecular alterations associated with these variants.

Methods: Genome-wide methylomic variation was quantified (MethylationEPIC) in Asian breast cancer patients (1152 buffy coats from peripheral whole blood). DNA methylation (DNAm) quantitative trait loci (mQTL) mapping was performed for 235 of the 313 variants with minor allele frequencies > 5%. Stability of identified mQTLs (p < 5e-8) across lifetime was examined using a public mQTL database. Identified mQTLs were also mapped to expression quantitative trait loci (eQTLs) in the Genotype-Tissue Expression Project and the eQTLGen Consortium.

Results: Breast cancer PRS was not associated with DNAm. A higher proportion of significant cis-mQTLs were observed. Of 822 significant cis-mQTLs (179 unique variants) identified in our dataset, 141 (59 unique variants) were significant (p < 5e-8) in a public mQTL database. Eighty-six percent (121/141) of the matched mQTLs were consistent at multiple time points (birth, childhood, adolescence, pregnancy, middle age, post-diagnosis, or treatment). Ninety-three variants associated with DNAm were also cis-eQTLs (35 variants not genome-wide significant). Multiple loci in the breast cancer PRS are associated with DNAm, contributing to the polygenic nature of the disease. These mQTLs are mostly stable over time.

Conclusions: Consistent results from DNAm and expression data may reveal new candidate genes not previously associated with breast cancer.
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http://dx.doi.org/10.1007/s10549-021-06185-9DOI Listing
August 2021

A New Procedure to Assess When Estimates from the Cumulative Link Model Can Be Interpreted as Differences for Ordinal Scales in Quality of Life Studies.

Clin Epidemiol 2021 4;13:53-65. Epub 2021 Feb 4.

Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.

Purpose: Assessing the clinical importance of an exposure effect on a quality of life (QoL) score often requires quantifying the effect in terms of a difference in scores. Using the linear regression model (LRM) for this purpose assumes the ordinal score is a proxy for an underlying continuous variable, but the analysis offers no assessment for the validity of the assumption. We propose an approach that assesses the proxy assumption and estimates the exposure effect by using the cumulative link model (CLM).

Patients And Methods: CLM is a well-established regression model that assumes an ordinal score is an ordered category generated from applying thresholds to a latent continuous variable. Our approach assesses the proxy assumption by testing whether these thresholds are equidistant. We compared the performance of CLM and LRM using simulated ordinal data and illustrated their application to the effect of time since diagnosis on five subscales of fatigue among breast cancer survivors measured using the Multidimensional Fatigue Inventory.

Results: CLM had good performance in estimating the difference in means with simulated ordinal data satisfying the proxy assumption, even when the outcome had only a few categories. When the proxy assumption was inadequate, both the CLM and LRM had biased estimates with poor coverage. The proxy assumption was appropriate for four of the five subscales in our real data application to fatigue scores, which highlighted the importance of assessing the proxy assumption to avoid reporting invalid estimates in terms of the difference in scores.

Conclusion: The proxy assumption is critical to the interpretation of the exposure effect on the difference in mean QoL scores. CLM offers a valid test for the presence of an association, a method for assessing the proxy assumption, and when the assumption is adequate, an assessment for clinical significance using the difference in means.
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http://dx.doi.org/10.2147/CLEP.S288801DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869833PMC
February 2021

Cost-effectiveness Analysis of Breast Cancer Screening Using Mammography in Singapore: A Modeling Study.

Cancer Epidemiol Biomarkers Prev 2021 Apr 2;30(4):653-660. Epub 2021 Feb 2.

Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore.

Background: Limited research is available on the cost-effectiveness of breast cancer screening programs in Asian countries. We evaluated the cost-effectiveness of Singapore's national mammography screening program, implemented in 2002, recommending annual screening between ages 40 and 49 and biennial screening between ages 50 and 69, and alternative screening scenarios taking into account important country-specific factors.

Methods: We used national data from Singapore in the MIcrosimulation SCreening ANalysis-Fatal diameter (MISCAN-Fadia) model to simulate 302 screening scenarios for 10 million women born between 1910 and 1969. Screening scenarios varied by starting and ending age, screening interval, and attendance. Outcome measures included life-years gained (LYG), breast cancer deaths averted, false positives, overdiagnosis, quality-adjusted life years (QALY), costs (in 2002 Singapore dollars; S$), and incremental cost-effectiveness ratios (ICER). Costs and effects were calculated and discounted with 3% using a health care provider's perspective.

Results: Singapore's current screening program at observed attendance levels required 54,158 mammograms per 100,000 women, yielded 1,054 LYG, and averted 57 breast cancer deaths. At attendance rates ≥50%, the current program was near the efficiency frontier. Most scenarios on the efficiency frontier started screening at age 40. The ICERs of the scenarios on the efficiency frontiers ranged between S$10,186 and S$56,306/QALY, which is considered cost-effective at a willingness-to-pay threshold of S$70,000/QALY gained.

Conclusions: Singapore's current screening program lies near the efficiency frontier, and starting screening at age 40 or 45 is cost-effective. Furthermore, enhancing screening attendance rates would increase benefits while maintaining cost-effectiveness.

Impact: Screening all women at age 40 or 45 is cost-efficient in Singapore, and a policy change may be considered.
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http://dx.doi.org/10.1158/1055-9965.EPI-20-1230DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8026695PMC
April 2021

Breast Cancer Risk Factors and Survival by Tumor Subtype: Pooled Analyses from the Breast Cancer Association Consortium.

Cancer Epidemiol Biomarkers Prev 2021 Apr 26;30(4):623-642. Epub 2021 Jan 26.

Gynaecology Research Unit, Hannover Medical School, Hannover, Germany.

Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype.

Methods: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.

Results: There was no evidence of heterogeneous associations between risk factors and mortality by subtype ( > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking.

Conclusions: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype.

Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.
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http://dx.doi.org/10.1158/1055-9965.EPI-20-0924DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8026532PMC
April 2021

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

N Engl J Med 2021 02 20;384(5):428-439. Epub 2021 Jan 20.

The authors' affiliations are as follows: the Centre for Cancer Genetic Epidemiology, Departments of Public Health and Primary Care (L.D., S. Carvalho, J.A., K.A.P., Q.W., M.K.B., J.D., B.D., N. Mavaddat, K. Michailidou, A.C.A., P.D.P.P., D.F.E.) and Oncology (C.L., P.A.H., C. Baynes, D.M.C., L.F., V.R., M. Shah, P.D.P.P., A.M.D., D.F.E.), University of Cambridge, Cambridge, the Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine (A. Campbell, D.J.P.), and the Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology (D.J.P.), University of Edinburgh, the Cancer Research UK Edinburgh Centre (D.A.C., J.F.), and the Usher Institute of Population Health Sciences and Informatics, University of Edinburgh Medical School (A. Campbell, J.F.), Edinburgh, the Divisions of Informatics, Imaging, and Data Sciences (E.F.H.), Cancer Sciences (A. Howell), Population Health, Health Services Research, and Primary Care (A. Lophatananon, K. Muir), and Evolution and Genomic Sciences, School of Biological Sciences (W.G.N., E.M.V., D.G.E.), University of Manchester, the NIHR Manchester Biomedical Research Unit (E.F.H.) and the Nightingale Breast Screening Centre, Wythenshawe Hospital (E.F.H., H.I.), Academic Health Science Centre and North West Genomics Laboratory Hub, and the Manchester Centre for Genomic Medicine, St. Mary's Hospital, Manchester University NHS Foundation Trust (W.G.N., E.M.V., D.G.E.), Manchester, the School of Cancer and Pharmaceutical Sciences, Comprehensive Cancer Centre, Guy's Campus, King's College London, London (E.J.S.), the Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham (I.T.), and the Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford (I.T.) - all in the United Kingdom; the Human Genotyping-CEGEN Unit, Human Cancer Genetic Program (A.G.-N., M.R.A., N.Á., B.H., R.N.-T.), and the Human Genetics Group (V.F., A.O., J.B.), Spanish National Cancer Research Center, Centro de Investigación en Red de Enfermedades Raras (A.O., J.B.), Servicio de Oncología Médica, Hospital Universitario La Paz (M.P.Z.), and Molecular Oncology Laboratory, Hospital Clinico San Carlos, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (M. de la Hoya), Madrid, the Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago de Compostela, Complejo Hospitalario Universitario de Santiago (A. Carracedo, M.G.-D.), and Centro de Investigación en Red de Enfermedades Raras y Centro Nacional de Genotipado, Universidad de Santiago de Compostela (A. Carracedo), Santiago de Compostela, the Oncology and Genetics Unit, Instituto de Investigacion Sanitaria Galicia Sur, Xerencia de Xestion Integrada de Vigo-Servizo Galeo de Saúde, Vigo (J.E.C.), and Servicio de Cirugía General y Especialidades, Hospital Monte Naranco, Oviedo (J.I.A.P.) - all in Spain; the Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund (C. Wahlström, J.V., M.L., T. Törngren, Å.B., A.K.), the Department of Oncology, Örebro University Hospital, Örebro (C. Blomqvist), and the Departments of Medical Epidemiology and Biostatistics (K.C., M.E., M.G., P. Hall, W.H., K.H.), Oncology, Södersjukhuset (P. Hall, S. Margolin), Molecular Medicine and Surgery (A. Lindblom), and Clinical Science and Education, Södersjukhuset (S. Margolin, C. Wendt), Karolinska Institutet, and the Department of Clinical Genetics, Karolinska University Hospital (A. Lindblom), Stockholm - all in Sweden; the Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD (M.T.P., C.F., G.C.-T., A.B.S.), the Cancer Epidemiology Division, Cancer Council Victoria (G.G.G., R.J.M., R.L.M.), the Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health (G.G.G., R.J.M., R.L.M.), and the Department of Clinical Pathology (M.C.S.), University of Melbourne, Anatomical Pathology, Alfred Hospital (C.M.), and the Cancer Epidemiology Division, Cancer Council Victoria (M.C.S.), Melbourne, VIC, and Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC (G.G.G., M.C.S., R.L.M.) - all in Australia; the Division of Molecular Pathology (R.K., S. Cornelissen, M.K.S.), Family Cancer Clinic (F.B.L.H., L.E.K.), Department of Epidemiology (M.A.R.), and Division of Psychosocial Research and Epidemiology (M.K.S.), the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, Division Laboratories, Pharmacy and Biomedical Genetics, Department of Genetics, University Medical Center, Utrecht (M.G.E.M.A.), the Department of Clinical Genetics, Erasmus University Medical Center (J.M.C., A.M.W.O.), and the Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute (B.A.M.H.-G., A. Hollestelle, M.J.H.), Rotterdam, the Department of Clinical Genetics, Maastricht University Medical Center, Maastricht (E.B.G.G.), the Departments of Human Genetics (I.M.M.L., M.P.G.V., P.D.), Clinical Genetics (C.J.A.), and Pathology (P.D.), Leiden University Medical Center, Leiden, the Department of Human Genetics, Radboud University Medical Center, Nijmegen (A.R.M.), and the Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen (J.C.O.) - all in the Netherlands; the Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute (B.D.), and the Division of Cancer Epidemiology and Genetics, National Cancer Institute (T.A., S.J.C., X.R.Y., M.G.-C.), National Institutes of Health, Bethesda, MD; the Department of Pathology, Brigham and Women's Hospital, Harvard Medical School (B.D.), and the Department of Nutrition, Harvard T.H. Chan School of Public Health (R.M.V.D.), Boston; the Departments of Clinical Genetics (K.A.), Oncology (C. Blomqvist), and Obstetrics and Gynecology (H.N., M. Suvanto), Helsinki University Hospital, University of Helsinki, Helsinki, and the Unit of Clinical Oncology, Kuopio University Hospital (P. Auvinen), the Institute of Clinical Medicine, Oncology (P. Auvinen), the Translational Cancer Research Area (J.M.H., V.-M.K., A. Mannermaa), and the Institute of Clinical Medicine, Pathology, and Forensic Medicine (J.M.H., V.-M.K., A. Mannermaa), University of Eastern Finland, and the Biobank of Eastern Finland, Kuopio University Hospital (V.-M.K., A. Mannermaa), Kuopio - both in Finland; the N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus (N.N.A., N.V.B.); the Department of Gynecology and Obstetrics and Institute of Clinical Molecular Biology, University Hospital of Schleswig-Holstein, Campus Kiel, Christian-Albrechts University Kiel, Kiel (N.A.), the Institute of Medical Biometry and Epidemiology (H. Becher) and Cancer Epidemiology Group (T.M., J.C.-C.), University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, the Department of Gynecology and Obstetrics (M.W.B., P.A.F., L.H.) and Institute of Human Genetics (A.B.E.), University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-European Metropolitan Region of Nuremberg, Erlangen, the Division of Cancer Epidemiology (S.B., A. Jung, P.M.K., J.C.-C.), Molecular Epidemiology Group, C080 (B. Burwinkel, H.S.), Division of Pediatric Neurooncology (A.F.), and Molecular Genetics of Breast Cancer (U.H., M.M., M.U.R., D.T.), German Cancer Research Center, Molecular Biology of Breast Cancer, University Women's Clinic Heidelberg, University of Heidelberg (B. Burwinkel, A.S., H.S.), Hopp Children's Cancer Center (A.F.), Faculty of Medicine, University of Heidelberg (P.M.K.), and National Center for Tumor Diseases, University Hospital and German Cancer Research Center (A.S., C.S.), Heidelberg, the Department of Radiation Oncology (N.V.B., M. Bremer, H.C.) and the Gynecology Research Unit (N.V.B., T.D., P. Hillemanns, T.-W.P.-S., P.S.), Hannover Medical School, Hannover, the Institute of Human Genetics, University of Münster, Münster (N.B.-M.), Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart (H. Brauch, W.-Y.L.), iFIT-Cluster of Excellence, University of Tübingen, and the German Cancer Consortium, German Cancer Research Center, Partner Site Tübingen (H. Brauch), and the University of Tübingen (W.-Y.L.), Tübingen, Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum, Bochum (T.B.), Institute for Medical Informatics, Statistics, and Epidemiology, University of Leipzig, Leipzig (C.E.), Center for Hereditary Breast and Ovarian Cancer (E.H., R.K.S.) and Center for Integrated Oncology (E.H., R.K.S.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, the Department of Internal Medicine, Evangelische Kliniken Bonn, Johanniter Krankenhaus, Bonn (Y.-D.K.), the Department of Gynecology and Obstetrics, University of Munich, Campus Großhadern, Munich (A. Meindl), and the Institute of Pathology, Städtisches Klinikum Karlsruhe, Karlsruhe (T.R.) - all in Germany; the Gynecological Cancer Registry, Centre Georges-François Leclerc, Dijon (P. Arveux), and the Center for Research in Epidemiology and Population Health, Team Exposome and Heredity, INSERM, University Paris-Saclay, Villejuif (E.C.-D., P.G., T. Truong) - both in France; the Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences (M. Bermisheva, E.K.), the Department of Genetics and Fundamental Medicine, Bashkir State University (E.K., D.P., Y.V.), and the Ufa Research Institute of Occupational Health and Human Ecology (Y.V.), Ufa, Russia; the Department of Genetics and Pathology (K.B., A. Jakubowska, J. Lubiński, K.P.) and the Independent Laboratory of Molecular Biology and Genetic Diagnostics (A. Jakubowska), Pomeranian Medical University, Szczecin, Poland; the Copenhagen General Population Study, the Department of Clinical Biochemistry (S.E.B., B.G.N.), and the Department of Breast Surgery (H.F.), Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, and the Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen (S.E.B., B.G.N.) - both in Denmark; the Division of Cancer Prevention and Genetics, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) (B. Bonanni), the Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano (S. Manoukian), the Genome Diagnostics Program, FIRC Institute of Molecular Oncology (P.P.), and the Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (P.R.), Milan; the Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet (A.-L.B.-D., G.I.G.A., V.N.K.), and the Institute of Clinical Medicine, Faculty of Medicine, University of Oslo (A.-L.B.-D., V.N.K.), Oslo; Medical Faculty, Universidad de La Sabana (I.B.), and the Clinical Epidemiology and Biostatistics Department (F.G.) and Institute of Human Genetics (D.T.), Pontificia Universidad Javeriana, Bogota, Colombia; the Department of Internal Medicine and Huntsman Cancer Institute, University of Utah (N.J.C., M.J.M., J.A.W.), and the Intermountain Healthcare Biorepository and Department of Pathology, Intermountain Healthcare (M.H.C.), Salt Lake City; the David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California, Los Angeles (P.A.F.), and Moores Cancer Center (M.G.-D., M.E.M.) and the Department of Family Medicine and Public Health (M.E.M.), University of California San Diego, La Jolla; the Departments of Medical Oncology (V.G., D.M.) and Pathology (M.T.), University Hospital of Heraklion, Heraklion, and the Department of Oncology, University Hospital of Larissa, Larissa (E.S.) - both in Greece; the Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital (G.G., I.L.A.), the Departments of Laboratory Medicine and Pathobiology (A.M.M.) and Molecular Genetics (I.L.A.), University of Toronto, and the Laboratory Medicine Program, University Health Network (A.M.M.), Toronto, and the Genomics Center, Centre Hospitalier Universitaire de Québec-Université Laval Research Center, Québec City, QC (J.S.) - both in Canada; the Department of Electron Microscopy and Molecular Pathology (A. Hadjisavvas, K.K., M.A.L.), the Cyprus School of Molecular Medicine (A. Hadjisavvas, K.K., M.A.L., K. Michailidou), and the Biostatistics Unit (K. Michailidou), Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus; the Saw Swee Hock School of Public Health (M. Hartman, R.M.V.D.) and the Department of Medicine, Yong Loo Lin School of Medicine (R.M.V.D.), National University of Singapore, the Department of Surgery, National University Health System (M. Hartman, J. Li), and the Human Genetics Division, Genome Institute of Singapore (J. Li), Singapore; the Department of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia (W.K.H.), and the Breast Cancer Research Programme, Cancer Research Malaysia (W.K.H., P.S.N., S.-Y.Y., S.H.T.), Selangor, and the Breast Cancer Research Unit, Cancer Research Institute (N.A.M.T.), and the Department of Surgery, Faculty of Medicine (N.A.M.T., P.S.N., S.H.T.), University Malaya, Kuala Lumpur - both in Malaysia; Surgery, School of Medicine, National University of Ireland, Galway (M.J.K., N. Miller); the Department of Surgery, Daerim Saint Mary's Hospital (S.-W.K.), the Department of Surgery, Ulsan University College of Medicine and Asan Medical Center (J.W.L.), the Department of Surgery, Soonchunhyang University College of Medicine and Soonchunhyang University Hospital (M.H.L.), Integrated Major in Innovative Medical Science, Seoul National University College of Medicine (S.K.P.), and the Cancer Research Institute, Seoul National University (S.K.P.), Seoul, South Korea; the Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and Research Center, Lahore, Pakistan (M.U.R.); and the National Cancer Institute, Ministry of Public Health, Nonthaburi, Thailand (S.T.).

Background: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

Methods: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.

Results: Protein-truncating variants in 5 genes (, , , , and ) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (, , , and ) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in and , odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in , , , , , and , odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in , , and were associated with a risk of breast cancer overall with a P value of less than 0.001. For , , and , missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.

Conclusions: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).
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http://dx.doi.org/10.1056/NEJMoa1913948DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611105PMC
February 2021

Epidemiological and ES cell-based functional evaluation of BRCA2 variants identified in families with breast cancer.

Hum Mutat 2021 Feb 31;42(2):200-212. Epub 2020 Dec 31.

Mouse Cancer Genetics Program, Center for Cancer Research, National Cancer Institute, Frederick, MD, 21702, USA.

The discovery of high-risk breast cancer susceptibility genes, such as Breast cancer associated gene 1 (BRCA1) and Breast cancer associated gene 2 (BRCA2) has led to accurate identification of individuals for risk management and targeted therapy. The rapid decline in sequencing costs has tremendously increased the number of individuals who are undergoing genetic testing world-wide. However, given the significant differences in population-specific variants, interpreting the results of these tests can be challenging especially for novel genetic variants in understudied populations. Here we report the characterization of novel variants in the Malaysian and Singaporean population that consist of different ethnic groups (Malays, Chinese, Indian, and other indigenous groups). We have evaluated the functional significance of 14 BRCA2 variants of uncertain clinical significance by using multiple in silico prediction tools and examined their frequency in a cohort of 7840 breast cancer cases and 7928 healthy controls. In addition, we have used a mouse embryonic stem cell (mESC)-based functional assay to assess the impact of these variants on BRCA2 function. We found these variants to be functionally indistinguishable from wild-type BRCA2. These variants could fully rescue the lethality of Brca2-null mESCs and exhibited no sensitivity to six different DNA damaging agents including a poly ADP ribose polymerase inhibitor. Our findings strongly suggest that all 14 evaluated variants are functionally neutral. Our findings should be valuable in risk assessment of individuals carrying these variants.
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http://dx.doi.org/10.1002/humu.24154DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919386PMC
February 2021

Presentation of breast cancer, help seeking behaviour and experience of patients in their cancer journey in Singapore: a qualitative study.

BMC Cancer 2020 Nov 10;20(1):1080. Epub 2020 Nov 10.

Department of Surgery, National University Health System, 1E Kent Ride Road, Tower Block, University Surgical Cluster, Level 8, Singapore City, 119228, Singapore.

Background: Little is known about the presentation, help seeking behaviour for breast cancer in Singapore. Nor was there a study exploring the experience of patients in their breast cancer journey.

Methods: A qualitative interview study with thematic analysis, conducted with 36 patients.

Results: There is no clear pattern of presentation for breast cancer by cancer stage at diagnosis, age and ethnicity in the cancer journey of this group of patients. Patients were diagnosed with early to advanced stages cancer regardless of when they presented or took up treatment in their cancer journey. The reasons patients sought medical attention also did not appear to differ between the stages of cancer diagnosed, ethnic and age. Without setting a measure to define early and late presentation, we found that women shared similar experience in their breast cancer journey, regardless of age, ethnicity and stage of cancer at diagnosis. Poor knowledge of breast cancer (symptoms and causes); few practised regular BSE; denial of symptom; fear of hospitalisation, diagnosis and treatment; worries and stress over financial burden of treatment; misinformation in magazine and online sources; diet; stress; caring responsibility; support network; and use of alternative medicine before and after diagnosis were identified in patients' narratives. Strong social support; fear of being an emotional and financial burden for the family; and financial worries during treatment were also the recurring themes after diagnosis.

Conclusion: A measure of breast cancer presentation - that accounts for the patient's experience in the cancer journey, the time interval and tumour biology - that is meaningful to patients, clinicians and researchers is needed. For research on late and delayed presentation, details on BSE practice - how often, when and was it done correctly - will improve the accuracy of time delay interval. For the public, concerted efforts to improve knowledge of breast cancer, survival and prognosis for early-diagnosed cancer, and the importance of regular and correct technique to perform BSE, are critical and urgent to address the rising breast cancer incidence in the country.
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http://dx.doi.org/10.1186/s12885-020-07585-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653763PMC
November 2020

Development and validation of a serum microRNA biomarker panel for detecting gastric cancer in a high-risk population.

Gut 2021 May 7;70(5):829-837. Epub 2020 Oct 7.

Department of Medicine, Yong Loo Lin School of Medicine, National University Singapore, Singapore

Objective: An unmet need exists for a non-invasive biomarker assay to aid gastric cancer diagnosis. We aimed to develop a serum microRNA (miRNA) panel for identifying patients with all stages of gastric cancer from a high-risk population.

Design: We conducted a three-phase, multicentre study comprising 5248 subjects from Singapore and Korea. Biomarker discovery and verification phases were done through comprehensive serum miRNA profiling and multivariant analysis of 578 miRNA candidates in retrospective cohorts of 682 subjects. A clinical assay was developed and validated in a prospective cohort of 4566 symptomatic subjects who underwent endoscopy. Assay performance was confirmed with histological diagnosis and compared with (HP) serology, serum pepsinogens (PGs), 'ABC' method, carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA19-9). Cost-effectiveness was analysed using a Markov decision model.

Results: We developed a clinical assay for detection of gastric cancer based on a 12-miRNA biomarker panel. The 12-miRNA panel had area under the curve (AUC)=0.93 (95% CI 0.90 to 0.95) and AUC=0.92 (95% CI 0.88 to 0.96) in the discovery and verification cohorts, respectively. In the prospective study, overall sensitivity was 87.0% (95% CI 79.4% to 92.5%) at specificity of 68.4% (95% CI 67.0% to 69.8%). AUC was 0.848 (95% CI 0.81 to 0.88), higher than HP serology (0.635), PG 1/2 ratio (0.641), PG index (0.576), ABC method (0.647), CEA (0.576) and CA19-9 (0.595). The number needed to screen is 489 annually. It is cost-effective for mass screening relative to current practice (incremental cost-effectiveness ratio=US$44 531/quality-of-life year).

Conclusion: We developed and validated a serum 12-miRNA biomarker assay, which may be a cost-effective risk assessment for gastric cancer.

Trial Registration Number: This study is registered with ClinicalTrials.gov (Registration number: NCT04329299).
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http://dx.doi.org/10.1136/gutjnl-2020-322065DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8040159PMC
May 2021

Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk.

Am J Hum Genet 2020 11 5;107(5):837-848. Epub 2020 Oct 5.

Hong Kong Hereditary Breast Cancer Family Registry, Hong Kong; Hong Kong Sanatorium and Hospital, Department of Pathology, Happy Valley, Hong Kong.

Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS was quantified using Cox regression analyses. We assessed PRS interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10 percentile and 20.5% at the 90 percentile of PRS. We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies.
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http://dx.doi.org/10.1016/j.ajhg.2020.09.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7675034PMC
November 2020

European polygenic risk score for prediction of breast cancer shows similar performance in Asian women.

Nat Commun 2020 07 31;11(1):3833. Epub 2020 Jul 31.

Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore, Singapore.

Polygenic risk scores (PRS) have been shown to predict breast cancer risk in European women, but their utility in Asian women is unclear. Here we evaluate the best performing PRSs for European-ancestry women using data from 17,262 breast cancer cases and 17,695 controls of Asian ancestry from 13 case-control studies, and 10,255 Chinese women from a prospective cohort (413 incident breast cancers). Compared to women in the middle quintile of the risk distribution, women in the highest 1% of PRS distribution have a ~2.7-fold risk and women in the lowest 1% of PRS distribution has ~0.4-fold risk of developing breast cancer. There is no evidence of heterogeneity in PRS performance in Chinese, Malay and Indian women. A PRS developed for European-ancestry women is also predictive of breast cancer risk in Asian women and can help in developing risk-stratified screening programmes in Asia.
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http://dx.doi.org/10.1038/s41467-020-17680-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7395776PMC
July 2020

Germline HOXB13 mutations p.G84E and p.R217C do not confer an increased breast cancer risk.

Sci Rep 2020 06 16;10(1):9688. Epub 2020 Jun 16.

Department of Gynecology and Obstetrics, University of Tübingen, Tübingen, Germany.

In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.
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http://dx.doi.org/10.1038/s41598-020-65665-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297796PMC
June 2020

Robust estimation of the effect of an exposure on the change in a continuous outcome.

BMC Med Res Methodol 2020 06 6;20(1):145. Epub 2020 Jun 6.

Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Tahir Foundation Building, Singapore, 117549, Singapore.

Background: The change in two measurements of a continuous outcome can be modelled directly with a linear regression model, or indirectly with a random effects model (REM) of the individual measurements. These methods are susceptible to model misspecifications, which are commonly addressed by applying monotonic transformations (e.g., Box-Cox transformation) to the outcomes. However, transforming the outcomes complicates the data analysis, especially when variable selection is involved. We propose a robust alternative through a novel application of the conditional probit (cprobit) model.

Methods: The cprobit model analyzes the ordered outcomes within each subject, making the estimate invariant to monotonic transformation on the outcome. By scaling the estimate from the cprobit model, we obtain the exposure effect on the change in the observed or Box-Cox transformed outcome, pending the adequacy of the normality assumption on the raw or transformed scale.

Results: Using simulated data, we demonstrated a similar good performance of the cprobit model and REM with and without transformation, except for some bias from both methods when the Box-Cox transformation was applied to scenarios with small sample size and strong effects. Only the cprobit model was robust to skewed subject-specific intercept terms when a Box-Cox transformation was used. Using two real datasets from the breast cancer and inpatient glycemic variability studies which utilize electronic medical records, we illustrated the application of our proposed robust approach as a seamless three-step workflow that facilitates the use of Box-Cox transformation to address non-normality with a common underlying model.

Conclusions: The cprobit model provides a seamless and robust inference on the change in continuous outcomes, and its three-step workflow is implemented in an R package for easy accessibility.
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http://dx.doi.org/10.1186/s12874-020-01027-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7275496PMC
June 2020

Identification of novel breast cancer susceptibility loci in meta-analyses conducted among Asian and European descendants.

Nat Commun 2020 03 5;11(1):1217. Epub 2020 Mar 5.

Departments of Health Research and Policy, School of Medicine, Stanford University, California, CA, USA.

Known risk variants explain only a small proportion of breast cancer heritability, particularly in Asian women. To search for additional genetic susceptibility loci for breast cancer, here we perform a meta-analysis of data from genome-wide association studies (GWAS) conducted in Asians (24,206 cases and 24,775 controls) and European descendants (122,977 cases and 105,974 controls). We identified 31 potential novel loci with the lead variant showing an association with breast cancer risk at P < 5 × 10. The associations for 10 of these loci were replicated in an independent sample of 16,787 cases and 16,680 controls of Asian women (P < 0.05). In addition, we replicated the associations for 78 of the 166 known risk variants at P < 0.05 in Asians. These findings improve our understanding of breast cancer genetics and etiology and extend previous findings from studies of European descendants to Asian women.
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http://dx.doi.org/10.1038/s41467-020-15046-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057957PMC
March 2020

Impact of delayed treatment in women diagnosed with breast cancer: A population-based study.

Cancer Med 2020 04 13;9(7):2435-2444. Epub 2020 Feb 13.

Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore, Singapore.

The impact of timely treatment on breast cancer-specific survival may differ by tumor stage. We aim to study the impact of delayed first treatment on overall survival across different tumor stages. In addition, we studied the impact of delayed adjuvant treatments on survival in patients with invasive nonmetastatic breast cancer who had surgery ≤90 days postdiagnosis. This population-based study includes 11 175 breast cancer patients, of whom, 2318 (20.7%) died (median overall survival = 7.9 years). To study the impact of delayed treatment on survival, hazard ratios and corresponding 95% confidence intervals were estimated using Cox proportional-hazards models. The highest proportion of delayed first treatment (>30 days postdiagnosis) was in patients with noninvasive breast cancer (61%), followed by metastatic breast cancer (50%) and invasive nonmetastatic breast cancer (22%). Delayed first treatment (>90 vs ≤30 days postdiagnosis) was associated with worse overall survival in patients with invasive nonmetastatic (HR: 2.25, 95% CI 1.55-3.28) and metastatic (HR: 2.09, 95% CI 1.66-2.64) breast cancer. Delayed adjuvant treatment (>90 vs 31-60 days postsurgery) was associated with worse survival in patients with invasive nonmetastatic (HR: 1.50, 95% CI 1.29-1.74). Results for the Cox proportional-hazards models were similar for breast cancer-specific death. A longer time to first treatment (31-90 days postdiagnosis) may be viable for more extensive diagnostic workup and patient-doctor decision-making process, without compromising survival. However, patients' preference and anxiety status need to be considered.
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http://dx.doi.org/10.1002/cam4.2830DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7131859PMC
April 2020

Impact of deviation from guideline recommended treatment on breast cancer survival in Asia.

Sci Rep 2020 Jan 28;10(1):1330. Epub 2020 Jan 28.

Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 117549, Singapore.

Breast cancer survival has improved with significant progress in treatment and disease management. However, compliance with treatment varies. Treatment guidelines for older patients are unclear. We aim to identify predictors of noncompliance with recommended therapy in a large breast cancer population and assess the impact of noncompliance on survival. Our study included 19,241 non-metastatic female breast cancer patients, of whom 3,158 (16%) died within 10 years post-diagnosis (median survival = 5.8 years). We studied the association between treatment noncompliance and factors with logistic regression, and the impact of treatment noncompliance on survival with a flexible parametric survival model framework. The highest proportion of noncompliance was observed for chemotherapy (18%). Predictors of noncompliance with chemotherapy, radiotherapy and endocrine therapy included age, tumor size, nodal involvement and subtype (except radiotherapy). Factors associated with not receiving surgery included age and subtype. Treatment noncompliance was associated with worse overall survival for surgery (HR: 2.26 [1.80-2.83]), chemotherapy (1.25 [1.11-1.41]), radiotherapy (2.28 [1.94-2.69]) and endocrine therapy (1.70 [1.41-2.04]). Worse survival was similarly observed in older patients for whom guidelines generally do not apply. Our results highlight the importance of following appropriate treatment as recommended by current guidelines. Older patients may benefit from similar recommendations.
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http://dx.doi.org/10.1038/s41598-020-58007-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6987174PMC
January 2020

Incidence of breast cancer attributable to breast density, modifiable and non-modifiable breast cancer risk factors in Singapore.

Sci Rep 2020 01 16;10(1):503. Epub 2020 Jan 16.

Genome Institute of Singapore, 60 Biopolis Street, Genome, #02-01, Singapore, 138672, Singapore.

Incidence of breast cancer is rising rapidly in Asia. Some breast cancer risk factors are modifiable. We examined the impact of known breast cancer risk factors, including body mass index (BMI), reproductive and hormonal risk factors, and breast density on the incidence of breast cancer, in Singapore. The study population was a population-based prospective trial of screening mammography - Singapore Breast Cancer Screening Project. Population attributable risk and absolute risks of breast cancer due to various risk factors were calculated. Among 28,130 women, 474 women (1.7%) developed breast cancer. The population attributable risk was highest for ethnicity (49.4%) and lowest for family history of breast cancer (3.8%). The proportion of breast cancers that is attributable to modifiable risk factor BMI was 16.2%. The proportion of breast cancers that is attributable to reproductive risk factors were low; 9.2% for age at menarche and 4.2% for number of live births. Up to 45.9% of all breast cancers could be avoided if all women had breast density <12% and BMI <25 kg/m. Notably, sixty percent of women with the lowest risk based on non-modifiable risk factors will never reach the risk level recommended for mammography screening. A combination of easily assessable breast cancer risk factors can help to identify women at high risk of developing breast cancer for targeted screening. A large number of high-risk women could benefit from risk-reduction and risk stratification strategies.
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http://dx.doi.org/10.1038/s41598-019-57341-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6965174PMC
January 2020

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Nat Genet 2020 01 7;52(1):56-73. Epub 2020 Jan 7.

Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
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http://dx.doi.org/10.1038/s41588-019-0537-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974400PMC
January 2020

Ultrasound Guided Optoacoustic Tomography in Assessment of Tumor Margins for Lumpectomies.

Transl Oncol 2020 Feb 21;13(2):254-261. Epub 2019 Dec 21.

Laboratory of Bio-Optical Imaging, Singapore Bioimaging Consortium, Singapore. Electronic address:

Purpose: To determine the accuracy of a handheld ultrasound-guided optoacoustic tomography (US-OT) probe developed for human deep-tissue imaging in ex vivo assessment of tumor margins postlumpectomy.

Methods: A custom-built two-dimensional (2D) US-OT-handheld probe was used to scan 15 lumpectomy breast specimens. Optoacoustic signals acquired at multiple wavelengths between 700 and 1100 nm were reconstructed using model linear algorithm, followed by spectral unmixing for lipid and deoxyhemoglobin (Hb). Distribution maps of lipid and Hb on the anterior, posterior, superior, inferior, medial, and lateral margins of the specimens were inspected for margin involvement, and results were correlated with histopathologic findings. The agreement in tumor margin assessment between US-OT and histopathology was determined using the Bland-Altman plot. Accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of margin assessment using US-OT were calculated.

Results: Ninety margins (6 × 15 specimens) were assessed. The US-OT probe resolved blood vessels and lipid up to a depth of 6 mm. Negative and positive margins were discriminated by marked differences in the distribution patterns of lipid and Hb. US-OT assessments were concordant with histopathologic findings in 87 of 89 margins assessed (one margin was uninterpretable and excluded), with diagnostic accuracy of 97.9% (kappa = 0.79). The sensitivity, specificity, PPV, and NPV were 100% (4/4), 97.6% (83/85), 66.7% (4/6), and 100% (83/83), respectively.

Conclusion: US-OT was capable of providing distribution maps of lipid and Hb in lumpectomy specimens that predicted tumor margins with high sensitivity and specificity, making it a potential tool for intraoperative tumor margin assessment.
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http://dx.doi.org/10.1016/j.tranon.2019.11.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6931190PMC
February 2020

Re-evaluating genetic variants identified in candidate gene studies of breast cancer risk using data from nearly 280,000 women of Asian and European ancestry.

EBioMedicine 2019 Oct 16;48:203-211. Epub 2019 Oct 16.

Department of Epidemiology, Cancer Prevention Institute of California, Fremont, CA, USA; Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.

Background: We previously conducted a systematic field synopsis of 1059 breast cancer candidate gene studies and investigated 279 genetic variants, 51 of which showed associations. The major limitation of this work was the small sample size, even pooling data from all 1059 studies. Thereafter, genome-wide association studies (GWAS) have accumulated data for hundreds of thousands of subjects. It's necessary to re-evaluate these variants in large GWAS datasets.

Methods: Of these 279 variants, data were obtained for 228 from GWAS conducted within the Asian Breast Cancer Consortium (24,206 cases and 24,775 controls) and the Breast Cancer Association Consortium (122,977 cases and 105,974 controls of European ancestry). Meta-analyses were conducted to combine the results from these two datasets.

Findings: Of those 228 variants, an association was observed for 12 variants in 10 genes at a Bonferroni-corrected threshold of P < 2·19 × 10. The associations for four variants reached P < 5 × 10 and have been reported by previous GWAS, including rs6435074 and rs6723097 (CASP8), rs17879961 (CHEK2) and rs2853669 (TERT). The remaining eight variants were rs676387 (HSD17B1), rs762551 (CYP1A2), rs1045485 (CASP8), rs9340799 (ESR1), rs7931342 (CHR11), rs1050450 (GPX1), rs13010627 (CASP10) and rs9344 (CCND1). Further investigating these 10 genes identified associations for two additional variants at P < 5 × 10, including rs4793090 (near HSD17B1), and rs9210 (near CYP1A2), which have not been identified by previous GWAS.

Interpretation: Though most candidate gene variants were not associated with breast cancer risk, we found 14 variants showing an association. Our findings warrant further functional investigation of these variants. FUND: National Institutes of Health.
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http://dx.doi.org/10.1016/j.ebiom.2019.09.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838373PMC
October 2019

Two truncating variants in FANCC and breast cancer risk.

Sci Rep 2019 08 29;9(1):12524. Epub 2019 Aug 29.

Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia.

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.
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http://dx.doi.org/10.1038/s41598-019-48804-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715680PMC
August 2019
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