A Novel Mutation in the Upstream Open Reading Frame of the CDKN1B Gene Causes a MEN4 Phenotype

PubMed ID: 23555276This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

BRCA1/BRCA2 rearrangements and CHEK2 common mutations are infrequent in Italian male breast cancer cases.

Male breast cancer (MBC) is a rare and poorly known disease. Germ-line mutations of BRCA2 and, to lesser extent, BRCA1 genes are the highest risk factors associated with MBC. Interestingly, BRCA2 germ-line rearrangements have been described in high-risk breast/ovarian cancer families which included at least one MBC case. Germ-line mutations of CHEK2 gene have been also implicated in inherited MBC predisposition. The CHEK2 1100delC mutation has been shown to increase the risk of breast cancer in men lacking BRCA1/BRCA2 mutations. Intriguingly, two other CHEK2 mutations (IVS2+1G > A and I157T) and a CHEK2 large genomic deletion (del9-10) have been associated with an elevated risk for prostate cancer. Here, we investigated the contribution of BRCA1, BRCA2 and CHEK2 alterations to MBC predisposition in Italy by analysing a large series of MBC cases, unselected for breast cancer family history and all negative for BRCA1/BRCA2 germ-line mutations. A total of 102 unrelated Italian MBC cases were screened for deletions/duplications of BRCA1, BRCA2 and CHEK2 by multiplex ligation-dependent probe amplification. No BRCA1, BRCA2 and CHEK2 genomic rearrangements, including the CHEK2 del9-10, were found in the series analysed. Furthermore, none of the MBC cases and 263 male population controls, also included in this study, carried the CHEK2 1100delC, IVS2+1G > A and I157T common mutations. Overall, our data suggest that screening of BRCA1/2 rearrangements is not advantageous in MBC cases not belonging to high-risk breast cancer families and that common CHEK2 mutations play an irrelevant role in MBC predisposition in Italy

SULT1A1gene deletion inBRCA2-associated male breast cancer: a link between genes and environmental exposures?

SULT1A1, a member of sulfotransferase superfamily, is a drug and hormone metabolizing enzyme involved in the metabolism of a variety of potential mammary carcinogens of endogenous and exogenous origin. Interestingly, the metabolic activity of SULT1A1 can be affected by varia- tions in gene copy number. Male Breast Cancer (MBC) is a rare disease and less investigated disease compared to female BC (FBC). As in FBC, the concurrent effects of genetic risk factors, particularly BRCA2 mutations, increased exposure to estrogens and environmental carcinogens play a relevant role in MBC. By quantitative real-time PCR with TaqMan probes, we investigated the presence of SULT1A1 gene copy number variations (CNVs) in a series of 72 MBCs. SULT1A1 gene deletion was observed in 10 of the 72 MBCs (13.9%). In a multivariate analysis associ- ation between BRCA2 mutation and SULT1A1 gene deletion emerged (p = 0.0005). Based on the evidence that the level of SULT1A1 enzyme activity is correlated with CNV, our data suggest that in male breast tumors SULT1A1 activity may be decreased. Thus, it can be hypothesized that in a proportion of MBCs, particularly in BRCA2-associated MBCs, the level of estrogens and environmental carcinogens exposure might be increased suggesting a link between gene and environmental exposure in the pathogenesis of MBC

Male breast cancer

Male breast cancer (MBC) is a rare disease representing less than 1% of all breast cancers (BC) and less than 1% of cancers in men. Age at presentation is mostly in the late 60s. MBC is recognized as an estrogen-driven disease, specifically related to hyperestrogenism. About 20% of MBC patients have family history for BC. Mutations in BRCA1 and, predominantly, BRCA2, account for approximately 10% of MBC cases. Because of its rarity, MBC is often compared with female BC (FBC). Based on age-frequency distribution, age-specific incidence rate patterns and prognostic factors profiles, MBC is considered similar to late-onset, postmenopausal estrogen/progesterone receptor positive (ER+/PR+) FBC. However, clinical and pathological characteristics of MBC do not exactly overlap FBC. Compared with FBC, MBC has been reported to occur later in life, present at a higher stage, and display lower histologic grade, with a higher proportion of ER+ and PR+ tumors. Although rare, MBC remains a substantial cause for morbidity and mortality in men, probably because of its occurrence in advanced age and delayed diagnosis. Diagnosis and treatment of MBC generally is similar to that of FBC. Men tend to be treated with mastectomy rather than breast-conserving surgery. The backbone of adjuvant therapy or palliative treatment for advanced disease is endocrine, mostly tamoxifen. Use of FBC-based therapy led to the observation that treatment outcomes for MBC are worse and that survival rates for MBC do not improve like FBC. These different outcomes may suggest a non-appropriate utilization of treatments and that different underlying pathogenetic mechanisms may exist between male and female BC

Clinical and pathologic characteristics of BRCA-positive and BRCA-negative male breast cancer patients: results from a collaborative multicenter study in Italy

Recently, the number of studies on male breast cancer (MBC) has been increasing. However, as MBC is a rare disease there are difficulties to undertake studies to identify specific MBC subgroups. At present, it is still largely unknown whether BRCA-related breast cancer (BC) in men may display specific characteristics as it is for BRCA-related BC in women. To investigate the clinical-pathologic features of MBC in association with BRCA mutations we established a collaborative Italian Multicenter Study on MBC with the aim to recruit a large series of MBCs. A total of 382 MBCs, including 50 BRCA carriers, were collected from ten Italian Investigation Centres covering the whole country. In MBC patients, BRCA2 mutations were associated with family history of breast/ovarian cancer (p < 0.0001), personal history of other cancers (p = 0.044) and contralateral BC (p = 0.001). BRCA2-associated MBCs presented with high tumor grade (p = 0.001), PR- (p = 0.026) and HER2+ (p = 0.001) status. In a multivariate logistic model BRCA2 mutations showed positive association with personal history of other cancers (OR 11.42, 95 % CI 1.79-73.08) and high tumor grade (OR 4.93, 95 % CI 1.02-23.88) and inverse association with PR+ status (OR 0.19, 95 % CI 0.04-0.92). Based on immunohistochemical (IHC) profile, four molecular subtypes of MBC were identified. Luminal A was the most common subtype (67.7 %), luminal B was observed in 26.5 % of the cases and HER2 positive and triple negative were represented by 2.1 % and 3.7 % of tumors, respectively. Intriguingly, we found that both luminal B and HER2 positive subtypes were associated with high tumor grade (p = 0.003 and 0.006, respectively) and with BRCA2 mutations (p = 0.016 and 0.001, respectively). In conclusion, our findings indicate that BRCA2-related MBCs represent a subgroup of tumors with a peculiar phenotype characterized by aggressive behavior. The identification of a BRCA2-associated phenotype might define a subset of MBC patients eligible for personalized clinical management

Multiple endocrine neoplasia type 2 syndromes (MEN 2): results from the ItaMEN network analysis on the prevalence of different genotypes and phenotypes.

OBJECTIVE: Multiple endocrine neoplasia type 2 (MEN 2) is a genetic disease characterized by medullary thyroid carcinoma (MTC) associated (MEN 2A and 2B) or not familial MTC (FMTC) with other endocrine neoplasia due to germline RET gene mutations. The prevalence of these rare genetic diseases and their corresponding RET mutations are unknown due to the small size of the study population. METHODS: We collected data on germline RET mutations of 250 families with hereditary MTC followed in 20 different Italian centres. RESULTS AND CONCLUSIONS: The most frequent RET amino acid substitution was Val804Met (19.6%) followed by Cys634Arg (13.6%). A total of 40 different germline RET mutations were present. Six families (2.4%) were negative for germline RET mutations. The comparison of the prevalence of RET germline mutations in the present study with those published by other European studies showed a higher prevalence of Val804Met and Ser891Ala mutations and a lower prevalence of Leu790Phe and Tyr791Phe (P<0.0001). A statistically significant higher prevalence of mutations affecting non-cysteine codons was also found (P<0.0001). Furthermore, the phenotype data collection showed an unexpected higher prevalence of FMTC (57.6%) with respect to other MEN 2 syndromes (34% MEN 2A and 6.8% of MEN 2B). In conclusion, we observed a statistically significant different pattern of RET mutations in Italian MEN 2 families with respect to other European studies and a higher prevalence of FMTC phenotype. The different ethnic origins of the patients and the particular attention given to analysing apparently sporadic MTC for RET germline mutations may explain these findings

A relocatable ocean model in support of environmental emergencies

During the Costa Concordia emergency case, regional, subregional, and relocatable ocean models have been used together with the oil spill model, MEDSLIK-II, to provide ocean currents forecasts, possible oil spill scenarios, and drifters trajectories simulations. The models results together with the evaluation of their performances are presented in this paper. In particular, we focused this work on the implementation of the Interactive Relocatable Nested Ocean Model (IRENOM), based on the Harvard Ocean Prediction System (HOPS), for the Costa Concordia emergency and on its validation using drifters released in the area of the accident. It is shown that thanks to the capability of improving easily and quickly its configuration, the IRENOM results are of greater accuracy than the results achieved using regional or subregional model products. The model topography, and to the initialization procedures, and the horizontal resolution are the key model settings to be configured. Furthermore, the IRENOM currents and the MEDSLIK-II simulated trajectories showed to be sensitive to the spatial resolution of the meteorological fields used, providing higher prediction skills with higher resolution wind forcing.MEDESS4MS Project; TESSA Project; MyOcean2 Projectinfo:eu-repo/semantics/publishedVersio

A Neural network based observation operator for coupled ocean acoustic variational data assimilation

Variational data assimilation requires implementing the tangent-linear and adjoint (TA/AD) version of any operator. This intrinsically hampers the use of complicated observations.Here, we assess a new data-driven approach to assimilate acoustic underwater propagation measurements [transmission loss (TL)] into a regional ocean forecasting system. TL measurements depend on the underlying sound speed fields, mostly temperature, and their inversion would require heavy coding of the TA/AD of an acoustic underwater propagation model. In this study, the nonlinear version of the acoustic model is applied to an ensemble of perturbed oceanic conditions. TL outputs are used to formulate both a statistical linear operator based on canonical correlation analysis (CCA), and a neural network based (NN) operator. For the latter, two linearization strategies are compared, the best-performing one relying on reverse-mode automatic differentiation. The new observation operator is applied in data assimilation experiments over the Ligurian Sea (Mediterranean Sea), using the observing system simulation experiments (OSSE) methodology to assess the impact of TL observations onto oceanic fields. TL observations are extracted from a nature run with perturbed surface boundary conditions and stochastic ocean physics. Sensitivity analyses indicate that theNNreconstruction of TL is significantly better than CCA. BothCCAandNNare able to improve the upper-ocean skill scores in forecast experiments, with NN outperforming CCA on the average. The use of the NN observation operator is computationally affordable, and its general formulation appears promising for the adjoint-free assimilation of any remote sensing observing network. SIGNIFICANCE STATEMENT: Deep learning algorithms are now widely spread in a diverse range of fields to help with solving automatic classification and regression problems. Here, we present and assess a strategy aimed at introducing an observation operator based on neural networks in data assimilation. Linearization of such an operator, required by variational schemes, is also discussed and implemented. The methodology is applied to the coupled oceanic acoustic data assimilation problem, and provides promising results. Our approach may be extended in the future to assimilate any remotely sensed type of observations

Assessing the Impact of Different Ocean Analysis Schemes on Oceanic and Underwater Acoustic Predictions

Assimilating oceanic observations into prediction systems is an advantageous approach for real-time ocean environment characterization. However, its benefits to underwater acoustic predictions are not trivial due to the nonlinearity and sensitivity of underwater acoustic propagation to small-scale oceanic features. In order to assess the potential of oceanic data assimilation, integrated ocean-acoustic Observing System Simulation Experiments are conducted. Synthetic altimetry and in situ data were assimilated through a variational oceanographic data assimilation system. The predicted sound speed fields are then ingested in a range-dependent acoustic model for transmission loss (TL) predictions. The predicted TLs are analyzed for the purpose of (i) evaluating the contributions of different sources to the uncertainties of oceanic and acoustic forecasts and (ii) comparing the impact of different oceanic analysis schemes on the TL prediction accuracy. Using ensemble member clustering techniques, the contributions of boundary conditions, ocean parameterizations, and geoacoustic characterization to acoustic prediction uncertainties are addressed. Subsequently, the impact of three-dimensional variational (3DVAR), 4DVAR, and hybrid ensemble-3DVAR data assimilation on acoustic TL prediction at two signal frequencies (75 and 2,500&nbsp;Hz) and different ranges (30 and 60&nbsp;km) are compared. 3DVAR significantly improves the predicted TL accuracy compared to the control run. Promisingly, 4DVAR and hybrid data assimilation further improve the TL forecasts, the hybrid scheme achieving the highest skill scores for all cases, while being the most computationally intensive scheme. The optimal scheme choice thus depends on requirements on the accuracy and computational constraints. These findings foster developments of coupled data assimilation for operational underwater acoustic propagation