Validation study of the LAMBDA model for predicting the BRCA1 or BRCA2 mutation carrier status of North American Ashkenazi Jewish women

Genome-wide DNA methylation assessment of 'BRCA1-like' early-onset breast cancer: Data from the Australian Breast Cancer Family Registry

Breast cancers arising in women carrying a germline mutation in BRCA1 are typically high-grade, early-onset and have distinct morphological features (BRCA1-like). However, the majority of early-onset breast cancers of this morphological type are not associated with germline BRCA1 mutations or constitutional BRCA1 promoter methylation. We aimed to assess DNA methylation across the genome for associations with the "BRCA1-like" morphology. Genome-wide methylation in blood-derived DNA was measured using the Infinium HumanMethylation450K BeadChip assay for women under the age of 40 years participating in the Australian Breast Cancer Family Study (ABCFS) diagnosed with: i) BRCA1-like breast cancer (n = 30); and ii) breast cancer without BRCA1-like morphological features (non BRCA1-like; n = 30), and age-matched unaffected women (controls; n = 30). Corresponding tumour-derived DNA from 43 of the affected women was also assessed. Methylation of blood-derived DNA was found to be elevated across 17 consecutive marks in the BRCA1 promoter region and decreased at several other genomic regions (including TWIST2 and CTBP1) for 7 women (23%) diagnosed with BRCA1-like breast cancer compared with women in the other groups. Corresponding tumour-derived DNA available from 5 of these 7 women had elevated methylation within the BRCA1 and SPHK2 promoter region and decreased methylation within the ADAP1, IGF2BP3 and SPATA13 promoter region when compared with the other breast tumours. These methylation marks could be biomarkers of risk for BRCA1-like breast cancer, and could be responsible in part for their distinctive morphological features and biology. As such, they may assist with prevention and targeted therapies for this cancer subtype.

Increased genomic burden of germline copy number variants is associated with early onset breast cancer: Australian breast cancer family registry

BACKGROUND

Women with breast cancer who have multiple affected relatives are more likely to have inherited genetic risk factors for the disease. All the currently known genetic risk factors for breast cancer account for less than half of the average familial risk. Furthermore, the genetic factor(s) underlying an increased cancer risk for many women from multiple-case families remain unknown. Rare genomic duplications and deletions, known as copy number variants (CNVs), cover more than 10% of a human genome, are often not assessed in studies of genetic predisposition, and could account for some of the so-called "missing heritability".

METHODS

We carried out a hypothesis-generating case-control study of breast cancer diagnosed before age 40 years (200 cases, 293 controls) using population-based cases from the Australian Breast Cancer Family Study. Genome-wide scanning for CNVs was performed using the Human610-Quad BeadChip and fine-mapping was conducted using PennCNV.

RESULTS

We identified deletions overlapping two known cancer susceptibility genes, (BRCA1 and BLM), and a duplication overlapping SMARCB1, associated with risk. The number of deletions across the genome was 1.5-fold higher for cases than controls (P = 10^-16), and 2-fold higher when only rare deletions overlapping genes (frequency <1%) were assessed (P = 5 × 10^-4). Association tests of CNVs, followed by experimental validation of CNV calls, found deletions overlapping the OR4C11 and OR4P4 genes were associated with breast cancer (P = 0.02 and P = 0.03, respectively).

CONCLUSION

These results suggest rare CNVs might have a role in breast cancer susceptibility, at least for disease at a young age.

Methylation of Breast Cancer Predisposition Genes in Early-Onset Breast Cancer: Australian Breast Cancer Family Registry

DNA methylation can mimic the effects of both germline and somatic mutations for cancer predisposition genes such as BRCA1 and p16^INK4a. Constitutional DNA methylation of the BRCA1 promoter has been well described and is associated with an increased risk of early-onset breast cancers that have BRCA1-mutation associated histological features. The role of methylation in the context of other breast cancer predisposition genes has been less well studied and often with conflicting or ambiguous outcomes. We examined the role of methylation in known breast cancer susceptibility genes in breast cancer predisposition and tumor development. We applied the Infinium HumanMethylation450 Beadchip (HM450K) array to blood and tumor-derived DNA from 43 women diagnosed with breast cancer before the age of 40 years and measured the methylation profiles across promoter regions of BRCA1, BRCA2, ATM, PALB2, CDH1, TP53, FANCM, CHEK2, MLH1, MSH2, MSH6 and PMS2. Prior genetic testing had demonstrated that these women did not carry a germline mutation in BRCA1, ATM, CHEK2, PALB2, TP53, BRCA2, CDH1 or FANCM. In addition to the BRCA1 promoter region, this work identified regions with variable methylation at multiple breast cancer susceptibility genes including PALB2 and MLH1. Methylation at the region of MLH1 in these breast cancers was not associated with microsatellite instability. This work informs future studies of the role of methylation in breast cancer susceptibility gene silencing.

Predictive accuracy of the Liverpool Lung Project risk model for stratifying patients for computed tomography screening for lung cancer: a case-control and cohort validation study

BACKGROUND

External validation of existing lung cancer risk prediction models is limited. Using such models in clinical practice to guide the referral of patients for computed tomography (CT) screening for lung cancer depends on external validation and evidence of predicted clinical benefit.

OBJECTIVE

To evaluate the discrimination of the Liverpool Lung Project (LLP) risk model and demonstrate its predicted benefit for stratifying patients for CT screening by using data from 3 independent studies from Europe and North America.

DESIGN

Case-control and prospective cohort study.

SETTING

Europe and North America.

PATIENTS

Participants in the European Early Lung Cancer (EUELC) and Harvard case-control studies and the LLP population-based prospective cohort (LLPC) study.

MEASUREMENTS

5-year absolute risks for lung cancer predicted by the LLP model.

RESULTS

The LLP risk model had good discrimination in both the Harvard (area under the receiver-operating characteristic curve [AUC], 0.76 [95% CI, 0.75 to 0.78]) and the LLPC (AUC, 0.82 [CI, 0.80 to 0.85]) studies and modest discrimination in the EUELC (AUC, 0.67 [CI, 0.64 to 0.69]) study. The decision utility analysis, which incorporates the harms and benefit of using a risk model to make clinical decisions, indicates that the LLP risk model performed better than smoking duration or family history alone in stratifying high-risk patients for lung cancer CT screening.

LIMITATIONS

The model cannot assess whether including other risk factors, such as lung function or genetic markers, would improve accuracy. Lack of information on asbestos exposure in the LLPC limited the ability to validate the complete LLP risk model.

CONCLUSION

Validation of the LLP risk model in 3 independent external data sets demonstrated good discrimination and evidence of predicted benefits for stratifying patients for lung cancer CT screening. Further studies are needed to prospectively evaluate model performance and evaluate the optimal population risk thresholds for initiating lung cancer screening.

Morphological predictors of BRCA1 germline mutations in young women with breast cancer

Background:

Knowing a young woman with newly diagnosed breast cancer has a germline BRCA1 mutation informs her clinical management and that of her relatives. We sought an optimal strategy for identifying carriers using family history, breast cancer morphology and hormone receptor status data.

Methods:

We studied a population-based sample of 452 Australian women with invasive breast cancer diagnosed before age 40 years for whom we conducted extensive germline mutation testing (29 carried a BRCA1 mutation) and a systematic pathology review, and collected three-generational family history and tumour ER and PR status. Predictors of mutation status were identified using multiple logistic regression. Areas under receiver operator characteristic (ROC) curves were estimated using five-fold stratified cross-validation.

Results:

The probability of being a BRCA1 mutation carrier increased with number of selected histology features even after adjusting for family history and ER and PR status (P<0.0001). From the most parsimonious multivariate model, the odds ratio for being a carrier were: 9.7 (95% confidence interval: 2.6–47.0) for trabecular growth pattern (P=0.001); 7.8 (2.7–25.7) for mitotic index over 50 mitoses per 10 high-powered field (P=0.0003); and 2.7 (1.3–5.9) for each first-degree relative with breast cancer diagnosed before age 60 years (P=0.01).The area under the ROC curve was 0.87 (0.83–0.90).

Conclusion:

Pathology review, with attention to a few specific morphological features of invasive breast cancers, can identify almost all BRCA1 germline mutation carriers among women with early-onset breast cancer without taking into account family history.

Performance of prediction models for BRCA mutation carriage in three racial/ethnic groups: findings from the Northern California Breast Cancer Family Registry

PURPOSE

Patients with early-onset breast and/or ovarian cancer frequently wish to know if they inherited a mutation in one of the cancer susceptibility genes, BRCA1 or BRCA2. Accurate carrier prediction models are needed to target costly testing. Two widely used models, BRCAPRO and BOADICEA, were developed using data from non-Hispanic Whites (NHW), but their accuracies have not been evaluated in other racial/ethnic populations.

METHODS

We evaluated the BRCAPRO and BOADICEA models in a population-based series of African American, Hispanic, and NHW breast cancer patients tested for BRCA1 and BRCA2 mutations. We assessed model calibration by evaluating observed versus predicted mutations and attribute diagrams, and model discrimination using areas under the receiver operating characteristic curves.

RESULTS

Both models were well-calibrated within each racial/ethnic group, with some exceptions. BOADICEA overpredicted mutations in African Americans and older NHWs, and BRCAPRO underpredicted in Hispanics. In all racial/ethnic groups, the models overpredicted in cases whose personal and family histories indicated >80% probability of carriage. The two models showed similar discrimination in each racial/ethnic group, discriminating least well in Hispanics. For example, BRCAPRO's areas under the receiver operating characteristic curves were 83% (95% confidence interval, 63-93%) for NHWs, compared with 74% (59-85%) for African Americans and 58% (45-70%) for Hispanics.

CONCLUSIONS

The poor performance of the model for Hispanics may be due to model misspecification in this racial/ethnic group. However, it may also reflect racial/ethnic differences in the distributions of personal and family histories among breast cancer cases in the Northern California population.

Prediction of BRCA Mutations Using the BRCAPRO Model in Clinic-Based African American, Hispanic, and Other Minority Families in the United States

PURPOSE

BRCAPRO, a BRCA mutation carrier prediction model, was developed on the basis of studies in individuals of Ashkenazi Jewish and European ancestry. We evaluated the performance of the BRCAPRO model among clinic-based minority families. We also assessed the clinical utility of mutation status of probands (the first individual tested in a family) in the recommendation of BRCA mutation testing for other at-risk family members.

PATIENTS AND METHODS

A total of 292 minority families with at least one member who was tested for BRCA mutations were identified through the Breast Cancer Family Registry and the University of Chicago. Using the BRCAPRO model, the predicted likelihood of carrying BRCA mutations was generated. Area under the receiver operating characteristic curves (AUCs) were calculated.

RESULTS

There were 104 African American, 130 Hispanic, 37 Asian-American, and 21 other minority families. The AUC was 0.748 (95% CI, 0.672 to 0.823) for all minorities combined. There was a statistically nonsignificant trend for BRCAPRO to perform better in Hispanic families than in other minority families. After taking into account the mutation status of probands, BRCAPRO performance in additional tested family members was improved: the AUC increased from 0.760 to 0.902.

CONCLUSION

The findings support the use of BRCAPRO in pretest BRCA mutation prediction among minority families in clinical settings, but there is room for improvement in ethnic groups other than Hispanics. Knowledge of the mutation status of the proband provides additional predictive value, which may guide genetic counselors in recommending BRCA testing of additional relatives when a proband has tested negative.

How to implement grid technology in tissue-based diagnosis: diagnostic surgical pathology

BACKGROUND

Tissue-based diagnosis or diagnostic surgical pathology is a highly accurate, sensitive and specific medical diagnostic technique that has expanded rapidly in using both molecular biology and computer technology.

OBJECTIVE

The objective is to analyze the present stage and potential influence of distributed data acquisition, analysis and presentation in tissue-based diagnosis by using recently developed standardized network systems such as grids.

METHODS

Interpretation of medical data is often based upon specialized examination, visual information acquisition and transfer as well as upon data collected from various sources. Efficient and accurate diagnostics require standardized data and transfer modes, which can be provided by a grid environment. The medical requirements, construction of an adequate grid environment, practical experiences in various medical disciplines and potential use in tissue-based diagnosis are described.

CONCLUSIONS

Grid technology is probably a useful tool to meet the conditions of tissue-based diagnosis in the near future, and will probably play a significant role in its further development.