The contribution of inherited genotype to breast cancer

The etiology of breast cancer is complex, and is likely to involve the actions of genes at multiple levels along the multistage carcinogenesis process. These inherited genotypes include those that affect the propensity to be exposed to breast carcinogens, and those associated with breast tumorigenesis directly. In addition, inherited genotypes may influence response to breast cancer chemoprevention and treatment. Studies relating inherited genotypes with breast cancer incidence and mortality should consider a broader spectrum of genes and their potential roles in multistage carcinogenesis than have been typically evaluated to date. Understanding the role of inherited genotype at different stages of carcinogenesis could improve our understanding of cancer biology, may identify specific exposures or events that correlate with carcinogenesis, or target relevant biochemical pathways for the development of preventive or therapeutic interventions

Replication of GWAS “Hits” by Race for Breast and Prostate Cancers in European Americans and African Americans

In this study, we assessed association of genome-wide association studies (GWAS) “hits” by race with adjustment for potential population stratification (PS) in two large, diverse study populations; the Carolina Breast Cancer Study (CBCS; N total = 3693 individuals) and the University of Pennsylvania Study of Clinical Outcomes, Risk, and Ethnicity (SCORE; N total = 1135 individuals). In both study populations, 136 ancestry information markers and GWAS “hits” (CBCS: FGFR2, 8q24; SCORE: JAZF1, MSMB, 8q24) were genotyped. Principal component analysis was used to assess ancestral differences by race. Multivariable unconditional logistic regression was used to assess differences in cancer risk with and without adjustment for the first ancestral principal component (PC1) and for an interaction effect between PC1 and the GWAS “hit” (SNP) of interest. PC1 explained 53.7% of the variance for CBCS and 49.5% of the variance for SCORE. European Americans and African Americans were similar in their ancestral structure between CBCS and SCORE and cases and controls were well matched by ancestry. In the CBCS European Americans, 9/11 SNPs were significant after PC1 adjustment, but after adjustment for the PC1 by SNP interaction effect, only one SNP remained significant (rs1219648 in FGFR2); for CBCS African Americans, 6/11 SNPs were significant after PC1 adjustment and after adjustment for the PC1 by SNP interaction effect, all six SNPs remained significant and an additional SNP now became significant. In the SCORE European Americans, 0/9 SNPs were significant after PC1 adjustment and no changes were seen after additional adjustment for the PC1 by SNP interaction effect; for SCORE African Americans, 2/9 SNPs were significant after PC1 adjustment and after adjustment for the PC1 by SNP interaction effect, only one SNP remained significant (rs16901979 at 8q24). We show that genetic associations by race are modified by interaction between individual SNPs and PS

Molecular hierarchy of mammary differentiation yields refined markers of mammary stem cells

The partial purification of mouse mammary gland stem cells (MaSCs) using combinatorial cell surface markers (Lin-CD24+CD29hCD49fh) has improved our understanding of their role in normal development and breast tumorigenesis. Despite the significant improvement in MaSC enrichment, there is presently no methodology that adequately isolates pure MaSCs. Seeking new markers of MaSCs, we characterized the stem-like properties and expression signature of label-retaining cells from the mammary gland of mice expressing a controllable H2b-GFP transgene. In this system, the transgene expression can be repressed in a doxycycline-dependent fashion, allowing isolation of slowly dividing cells with retained nuclear GFP signal. Here, we show that H2b-GFPh cells reside within the predicted MaSC compartment and display greater mammary reconstitution unit frequency compared with H2b-GFPneg MaSCs. According to their transcriptome profile, H2b-GFPh MaSCs are enriched for pathways thought to play important roles in adult stem cells. We found Cd1d, a glycoprotein expressed on the surface of antigen-presenting cells, to be highly expressed by H2b-GFPh MaSCs, and isolation of Cd1d+ MaSCs further improved the mammary reconstitution unit enrichment frequency to nearly a single-cell level. Additionally, we functionally characterized a set of MaSC-enriched genes, discovering factors controlling MaSC survival. Collectively, our data provide tools for isolating a more precisely defined population of MaSCs and point to potentially critical factors for MaSC maintenance

A Neighborhood-Wide Association Study (NWAS): Example of prostate cancer aggressiveness

Purpose Cancer results from complex interactions of multiple variables at the biologic, individual, and social levels. Compared to other levels, social effects that occur geospatially in neighborhoods are not as well-studied, and empiric methods to assess these effects are limited. We propose a novel Neighborhood-Wide Association Study(NWAS), analogous to genome-wide association studies(GWAS), that utilizes high-dimensional computing approaches from biology to comprehensively and empirically identify neighborhood factors associated with disease. Methods Pennsylvania Cancer Registry data were linked to U.S. Census data. In a successively more stringent multiphase approach, we evaluated the association between neighborhood (n = 14,663 census variables) and prostate cancer aggressiveness(PCA) with n = 6,416 aggressive (Stage≥3/Gleason grade≥7 cases) vs. n = 70,670 non-aggressive (Stage<3/Gleason grade<7) cases in White men. Analyses accounted for age, year of diagnosis, spatial correlation, and multiple-testing. We used generalized estimating equations in Phase 1 and Bayesian mixed effects models in Phase 2 to calculate odds ratios(OR) and confidence/credible intervals(CI). In Phase 3, principal components analysis grouped correlated variables. Results We identified 17 new neighborhood variables associated with PCA. These variables represented income, housing, employment, immigration, access to care, and social support. The top hits or most significant variables related to transportation (OR = 1.05;CI = 1.001–1.09) and poverty (OR = 1.07;CI = 1.01–1.12). Conclusions This study introduces the application of high-dimensional, computational methods to large-scale, publically-available geospatial data. Although NWAS requires further testing, it is hypothesis-generating and addresses gaps in geospatial analysis related to empiric assessment. Further, NWAS could have broad implications for many diseases and future precision medicine studies focused on multilevel risk factors of disease

Incorporating tumour pathology information into breast cancer risk prediction algorithms.

INTRODUCTION: Mutations in BRCA1 and BRCA2 confer high risks of breast cancer and ovarian cancer. The risk prediction algorithm BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) may be used to compute the probabilities of carrying mutations in BRCA1 and BRCA2 and help to target mutation screening. Tumours from BRCA1 and BRCA2 mutation carriers display distinctive pathological features that could be used to better discriminate between BRCA1 mutation carriers, BRCA2 mutation carriers and noncarriers. In particular, oestrogen receptor (ER)-negative status, triple-negative (TN) status, and expression of basal markers are predictive of BRCA1 mutation carrier status. METHODS: We extended BOADICEA by treating breast cancer subtypes as distinct disease end points. Age-specific expression of phenotypic markers in a series of tumours from 182 BRCA1 mutation carriers, 62 BRCA2 mutation carriers and 109 controls from the Breast Cancer Linkage Consortium, and over 300,000 tumours from the general population obtained from the Surveillance Epidemiology, and End Results database, were used to calculate age-specific and genotype-specific incidences of each disease end point. The probability that an individual carries a BRCA1 or BRCA2 mutation given their family history and tumour marker status of family members was computed in sample pedigrees. RESULTS: The cumulative risk of ER-negative breast cancer by age 70 for BRCA1 mutation carriers was estimated to be 55% and the risk of ER-positive disease was 18%. The corresponding risks for BRCA2 mutation carriers were 21% and 44% for ER-negative and ER-positive disease, respectively. The predicted BRCA1 carrier probabilities among ER-positive breast cancer cases were less than 1% at all ages. For women diagnosed with breast cancer below age 50 years, these probabilities rose to more than 5% in ER-negative breast cancer, 7% in TN disease and 24% in TN breast cancer expressing both CK5/6 and CK14 cytokeratins. Large differences in mutation probabilities were observed by combining ER status and other informative markers with family history. CONCLUSIONS: This approach combines both full pedigree and tumour subtype data to predict BRCA1/2 carrier probabilities. Prediction of BRCA1/2 carrier status, and hence selection of women for mutation screening, may be substantially improved by combining tumour pathology with family history of cancer.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Strengthening care and research for women's cancers in Sub-Saharan Africa

Highlights • The burden of gynecologic cancers in low resource settings is overwhelming. • Areas with the highest needs have few human resources and limited infrastructure. • Cancer specialists can best help by leveraging ongoing work to assist local leaders

Associations of common breast cancer susceptibility alleles with risk of breast cancer subtypes in BRCA1 and BRCA2 mutation carriers

Peer reviewedPublisher PD

Evaluation of models to predict BRCA germline mutations

The selection of candidates for BRCA germline mutation testing is an important clinical issue yet it remains a significant challenge. A number of risk prediction models have been developed to assist in pretest counselling. We have evaluated the performance and the inter-rater reliability of four of these models (BRCAPRO, Manchester, Penn and the Myriad-Frank). The four risk assessment models were applied to 380 pedigrees of families who had undergone BRCA1/2 mutation analysis. Sensitivity, specificity, positive and negative predictive values, likelihood ratios and area under the receiver operator characteristic (ROC) curve were calculated for each model. Using a greater than 10% probability threshold, the likelihood that a BRCA test result was positive in a mutation carrier compared to the likelihood that the same result would be expected in an individual without a BRCA mutation was 2.10 (95% confidence interval (CI) 1.66–2.67) for Penn, 1.74 (95% CI 1.48–2.04) for Myriad, 1.35 (95% CI 1.19–1.53) for Manchester and 1.68 (95% CI 1.39–2.03) for BRCAPRO. Application of these models, therefore, did not rule in BRCA mutation carrier status. Similar trends were observed for separate BRCA1/2 performance measures except BRCA2 assessment in the Penn model where the positive likelihood ratio was 5.93. The area under the ROC curve for each model was close to 0.75. In conclusion, the four models had very little impact on the pre-test probability of disease; there were significant clinical barriers to using some models and risk estimates varied between experts. Use of models for predicting BRCA mutation status is not currently justified for populations such as that evaluated in the current study

Implementation of a novel stratified PAthway of CarE for common musculoskeletal (MSK) conditions in primary care: Protocol for a multicentre pragmatic randomised controlled trial (the PACE MSK trial)

Introduction Musculoskeletal (MSK) conditions constitute the highest burden of disease globally, with healthcare services often utilised inappropriately and overburdened. The aim of this trial is to evaluate the effectiveness of a novel clinical PAthway of CarE programme (PACE programme), where care is provided based on people's risk of poor outcome. Methods and analysis Multicentre randomised controlled trial. 716 people with MSK conditions (low back pain, neck pain or knee osteoarthritis) will be recruited in primary care. They will be stratified for risk of a poor outcome (low risk/high risk) using the Short Form Örebro Musculoskeletal Pain Screening Questionnaire (SF-ÖMSPQ) then randomised to usual care (n=358) or the PACE programme (n=358). Participants at low risk in the PACE programme will receive up to 3 sessions of guideline based care from their primary healthcare professional (HCP) supported by a custom designed website (mypainhub.com). Those at high risk will be referred to an allied health MSK specialist who will conduct a comprehensive patient-centred assessment then liaise with the primary HCP to determine further care. Primary outcome (SF 12-item PCS) and secondary outcomes (eg, pain self-efficacy, psychological health) will be collected at baseline, 3, 6 and 12 months. Cost-effectiveness will be measured as cost per quality-Adjusted life-year gained. Health economic analysis will include direct and indirect costs. Analyses will be conducted on an intention-To-Treat basis. Primary and secondary outcomes will be analysed independently, using generalised linear models. Qualitative and mixed-methods studies embedded within the trial will evaluate patient experience, health professional practice and interprofessional collaboration. Ethics and dissemination Ethics approval has been received from the following Human Research Ethics Committees: The University of Sydney (2018/926), The University of Queensland (2019000700/2018/926), University of Melbourne (1954239), Curtin University (HRE2019-0263) and Northern Sydney Local Health District (2019/ETH03632). Dissemination of findings will occur via peer-reviewed publications, conference presentations and social media. Trial registration number ACTRN12619000871145