The aggregation of early-onset melanoma in young Western Australian families.

BACKGROUND: Few studies have examined the familial aggregation of melanoma or its co-aggregation with other cancers using whole-population based designs. This study aimed to investigate aggregation patterns in young Western Australian families, using population-based linked health data to identify individuals born in Western Australia between 1974 and 2007, their known relatives, and all incident cancer diagnoses within the resulting 1,506,961 individuals. METHODS: Cox proportional hazards regression models were used to compare the risk of melanoma for first-degree relatives of melanoma cases to that for first-degree relatives of controls, with bootstrapping used to account for correlations within families. The risk of (i) developing melanoma based on the number of first-degree relatives with other cancers, and (ii) developing non-melanoma cancers based on the number of first-degree relatives diagnosed with melanoma was also investigated. RESULTS: First-degree relatives of melanoma cases had a significantly greater incidence of melanoma than first-degree relatives of individuals not affected with melanoma (Hazard Ratio (HR)=3.58, 95% bootstrap confidence interval (CI): 2.43-5.43). Sensitivity analyses produced a higher hazard ratio estimate when restricted to melanoma cases diagnosed before 40 years of age (HR=3.77, bootstrap 95% CI: 2.49-6.39) and a lower estimate when only later-onset cases (>40 years) were considered (HR=2.45, bootstrap 95% CI: 1.23-4.82). No significant evidence was found for co-aggregation between melanoma and any other cancers. CONCLUSIONS: Results indicated a strong familial basis of melanoma, with the higher than expected hazard ratio observed likely to reflect early-age at onset cases in this young cohort, supported by the results of the sensitivity analyses. Exploratory analyses suggested that the determinants of melanoma causing the observed aggregation within families may be independent of other malignancies, although these analyses were limited by the young age of the sample. Determining familial aggregation patterns will provide valuable knowledge regarding improved clinical risk prediction and the underlying biological mechanisms of melanoma and other cancers.

Estimating risks for variants of unknown significance according to their predicted pathogenicity classes with application to BRCA1.

Sequence-based testing of disease-susceptibility genes has identified many variants of unknown significance (VUSs) whose pathogenicity is unknown at the time of their measurement. Female breast cancer cases aged 20-49 years at diagnosis and who have VUSs in BRCA1 and no mutations in BRCA2 have previously been identified through the population-based Los Angeles County Cancer Surveillance Program. These nominal BRCA1 VUSs have been classified as "low," "medium," and "high" risk by four classification methods: Align-GVGD, Polyphen, Grantham matrix scores, and sequence conservation in mammalian species. Average hazard ratios (HRs) for classes of variants, i.e., the age-specific incidences of cancer for carriers of such variants divided by the population incidences, were estimated from the cancer family histories of first- and second-degree relatives of the index cases using modified segregation analysis. The study sample comprised 270 index cases and 4,543 of their relatives. There was weak evidence that the risk of breast cancer increases with the degree of sequence conservation (P = 0.03) and that missense variants at highly conserved sites are associated with a 5.6-fold (95 % confidence interval 1.4-22.2; P = 0.05) increased incidence of breast cancer. An upper bound of 2.3 is given for the average breast cancer HRs corresponding to variants classified as "low risk" by any of the four VUS classification methods. In summary, we have given a method to estimate cancer risks for groups of VUSs by combining existing classification methods with traditional penetrance analyses. This analysis suggests that classification methods for BRCA1 variants based on sequence conservation might be useful in a clinical setting. We have shown in principle that our method can be used to classify VUSs into clinically useful risk categories, but our specific findings should not be put into clinical practice unless confirmed by larger studies.

Prospective validation of the breast cancer risk prediction model BOADICEA and a batch-mode version BOADICEACentre.

BACKGROUND: Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is a risk prediction algorithm that can be used to compute estimates of age-specific risk of breast cancer. It is uncertain whether BOADICEA performs adequately for populations outside the United Kingdom. METHODS: Using a batch mode version of BOADICEA that we developed (BOADICEACentre), we calculated the cumulative 10-year invasive breast cancer risk for 4176 Australian women of European ancestry unaffected at baseline from 1601 case and control families in the Australian Breast Cancer Family Registry. Based on 115 incident breast cancers, we investigated calibration, discrimination (using receiver-operating characteristic (ROC) curves) and accuracy at the individual level. RESULTS: The ratio of expected to observed number of breast cancers was 0.92 (95% confidence interval (CI) 0.76-1.10). The E/O ratios by subgroups of the participant's relationship to the index case and by the reported number of affected relatives ranged between 0.83 and 0.98 and all 95% CIs included 1.00. The area under the ROC curve was 0.70 (95% CI 0.66-0.75) and there was no evidence of systematic under- or over-dispersion (P=0.2). CONCLUSION: BOADICEA is well calibrated for Australian women, and had good discrimination and accuracy at the individual level.

Tumour morphology predicts PALB2 germline mutation status.

BACKGROUND: Population-based studies of breast cancer have estimated that at least some PALB2 mutations are associated with high breast cancer risk. For women carrying PALB2 mutations, knowing their carrier status could be useful in directing them towards effective cancer risk management and therapeutic strategies. We sought to determine whether morphological features of breast tumours can predict PALB2 germline mutation status. METHODS: Systematic pathology review was conducted on breast tumours from 28 female carriers of PALB2 mutations (non-carriers of other known high-risk mutations, recruited through various resources with varying ascertainment) and on breast tumours from a population-based sample of 828 Australian women diagnosed before the age of 60 years (which included 40 BRCA1 and 18 BRCA2 mutation carriers). Tumour morphological features of the 28 PALB2 mutation carriers were compared with those of 770 women without high-risk mutations. RESULTS: Tumours arising in PALB2 mutation carriers were associated with minimal sclerosis (odds ratio (OR)=19.7; 95% confidence interval (CI)=6.0-64.6; P=5 × 10(-7)). Minimal sclerosis was also a feature that distinguished PALB2 mutation carriers from BRCA1 (P=0.05) and BRCA2 (P=0.04) mutation carriers. CONCLUSION: This study identified minimal sclerosis to be a predictor of germline PALB2 mutation status. Morphological review can therefore facilitate the identification of women most likely to carry mutations in PALB2.

Using tumour pathology to identify people at high genetic risk of breast and colorectal cancers.

Genes have been identified for which germline mutations are associated with high lifetime risks of breast, colorectal and other cancers. Identification of mutation carriers through genetic testing is important as it could help lower cancer incidence and mortality. The translation of genetic information into better health outcomes is expensive because of the costs of genetic counselling as well as laboratory testing. Approaches to triage for mutation screening of known genes which rely on cancer family history are not necessarily sensitive and specific or the most cost-effective. Recent population-based research has shown that the cancers and precancerous lesions arising in mutation carriers have specific molecular and morphological characteristics. People with colorectal cancer, especially those diagnosed at a young age, whose tumours exhibit microsatellite instability and some specific pathology and immunohistochemically-defined features are more likely to carry a germline mutation in one of four mismatch repair genes. Some morphological and immunohistochemically-defined features are associated with breast cancers arising in women who carry BRCA1 or BRCA2 germline mutations, especially if at a young age. Screening paradigms based on molecular and morphological features that predict mutation status, especially if focused on early-onset disease, have the potential to identify mutation carriers with greater sensitivity and specificity, and in a more cost-effective way, than those based on family history alone. Genetic testing results could help inform treatment if those affected are tested soon after diagnosis using pathology-led selection strategies to identify cases most likely to carry germline mutations. We propose how this new approach could be undertaken by having genetic testing and counselling prioritised to those with the greatest probability of carrying a germline mutation in these known cancer predisposition genes.

Body mass index in early adulthood and colorectal cancer risk for carriers and non-carriers of germline mutations in DNA mismatch repair genes.

BACKGROUND: Carriers of germline mutations in DNA mismatch repair (MMR) genes have a high risk of colorectal cancer (CRC), but the modifiers of this risk are not well established. We estimated an association between body mass index (BMI) in early adulthood and subsequent risk of CRC for carriers and, as a comparison, estimated the association for non-carriers. METHODS: A weighted Cox regression was used to analyse height and weight at 20 years reported by 1324 carriers of MMR gene mutations (500 MLH1, 648 MSH2, 117 MSH6 and 59 PMS2) and 1219 non-carriers from the Colon Cancer Family Registry. RESULTS: During 122,304 person-years of observation, we observed diagnoses of CRC for 659 carriers (50%) and 36 non-carriers (3%). For carriers, the risk of CRC increased by 30% for each 5 kg m(-2) increment in BMI in early adulthood (hazard ratio, HR: 1.30; 95% confidence interval, CI: 1.08-1.58; P=0.01), and increased by 64% for non-carriers (HR: 1.64; 95% CI: 1.02-2.64; P=0.04) after adjusting for sex, country, cigarette smoking and alcohol drinking (and the MMR gene that was mutated in carriers). The difference in HRs for carriers and non-carriers was not statistically significant (P=0.50). For MLH1 and PMS2 (MutLα heterodimer) mutation carriers combined, the corresponding increase was 36% (HR: 1.36; 95% CI: 1.05-1.76; P=0.02). For MSH2 and MSH6 (MutSα heterodimer) mutation carriers combined, the HR was 1.26 (95% CI: 0.96-1.65; P=0.09). There was no significant difference between the HRs for MutLα and MutSα heterodimer carriers (P=0.56). CONCLUSION: Body mass index in early adulthood is positively associated with risk of CRC for MMR gene mutation carriers and non-carriers.

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.

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

LAMBDA is a model that estimates the probability an Ashkenazi Jewish (AJ) woman carries an ancestral BRCA1 or BRCA2 mutation from her personal and family cancer history. LAMBDA is relevant to clinical practice, and its implementation does not require a computer. It was developed principally from Australian and UK data. We conducted a validation study using 1286 North American AJ women tested for the mutations 185delAG and 5382insC in BRCA1 and 6174delT in BRCA2. Most had a personal or family history of breast cancer. We observed 197 carriers. The area under the receiver operator characteristic (ROC) curve (a measure of ranking) was 0.79 [95% confidence interval (CI) = 0.77-0.81], similar to that for the model-generating data (0.78; 95% CI = 0.75-0.82). LAMBDA predicted 232 carriers (18% more than observed; p = 0.002) and was overdispersed (p = 0.009). The Bayesian computer program BRCAPRO gave a similar area under the ROC curve (0.78; 95% CI = 0.76-0.80), but predicted 367 carriers (86% more than observed; p < 0.0001), and was substantially overdispersed (p < 0.0001). Therefore, LAMBDA is comparable to BRCAPRO for ranking AJ women according to their probability of being a BRCA1 or BRCA2 mutation carrier and is more accurate than brcapro which substantially overpredicts carriers in this population.