So far, no common environmental and/or phenotypic factor has been associated with melanoma and renal cell carcinoma (RCC). The known risk factors for melanoma include sun exposure, pigmentation and nevus phenotypes; risk factors associated with RCC include smoking, obesity and hypertension. A recent study of coexisting melanoma and RCC in the same patients supports a genetic predisposition underlying the association between these two cancers. The microphthalmia-associated transcription factor (MITF) has been proposed to act as a melanoma oncogene; it also stimulates the transcription of hypoxia inducible factor (HIF1A), the pathway of which is targeted by kidney cancer susceptibility genes. We therefore proposed that MITF might have a role in conferring a genetic predisposition to co-occurring melanoma and RCC. Here we identify a germline missense substitution in MITF (Mi-E318K) that occurred at a significantly higher frequency in genetically enriched patients affected with melanoma, RCC or both cancers, when compared with controls. Overall, Mi-E318K carriers had a higher than fivefold increased risk of developing melanoma, RCC or both cancers. Codon 318 is located in a small-ubiquitin-like modifier (SUMO) consensus site (ΨKXE) and Mi-E318K severely impaired SUMOylation of MITF. Mi-E318K enhanced MITF protein binding to the HIF1A promoter and increased its transcriptional activity compared to wild-type MITF. Further, we observed a global increase in Mi-E318K-occupied loci. In an RCC cell line, gene expression profiling identified a Mi-E318K signature related to cell growth, proliferation and inflammation. Lastly, the mutant protein enhanced melanocytic and renal cell clonogenicity, migration and invasion, consistent with a gain-of-function role in tumorigenesis. Our data provide insights into the link between SUMOylation, transcription and cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3, 9q31.1) and one for endometrioid EOC (5q12.3). We then meta-analysed the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified an additional three loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a novel susceptibility gene for low grade/borderline serous EOC.

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease1. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10−8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 14% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

The prevalence and spectrum of germline mutations in BRCA1 and BRCA2 have been reported in single populations, with the majority of reports focused on White in Europe and North America. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) has assembled data on 18,435 families with BRCA1 mutations and 11,351 families with BRCA2 mutations ascertained from 69 centers in 49 countries on six continents. This study comprehensively describes the characteristics of the 1,650 unique BRCA1 and 1,731 unique BRCA2 deleterious (disease‐associated) mutations identified in the CIMBA database. We observed substantial variation in mutation type and frequency by geographical region and race/ethnicity. In addition to known founder mutations, mutations of relatively high frequency were identified in specific racial/ethnic or geographic groups that may reflect founder mutations and which could be used in targeted (panel) first pass genotyping for specific populations. Knowledge of the population‐specific mutational spectrum in BRCA1 and BRCA2 could inform efficient strategies for genetic testing and may justify a more broad‐based oncogenetic testing in some populations.

PURPOSE To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized. METHODS We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes. RESULTS We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 × 10−76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 × 10−3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 × 10−3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 × 10−2). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age ( P for trend = 2.0 × 10−3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies ( P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer. CONCLUSION These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer risk management of PALB2 PV carriers.

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For the Mutation Pathogenicity Special IssueGenetic testing for mutations in high-risk cancer susceptibility genes often reveals missense substitutions that are not easily classified as pathogenic or neutral. Among the methods that can help in their classification are computational analyses. Predictions of pathogenic vs. neutral, or the probability that a variant is pathogenic, can be made based on: 1) inferences from evolutionary conservation using protein multiple sequence alignments (PMSAs) of the gene of interest for almost any missense sequence variant; and 2) for many variants, structural features of wild-type and variant proteins. These in silico methods have improved considerably in recent years.In this work, we review and/or make suggestions with respect to: 1) the rationale for using in silico methods to help predict the consequences of missense variants; 2) important aspects of creating PMSAs that are informative for classification; 3) specific features of algorithms that have been used for classification of clinically-observed variants; 4) validation studies demonstrating that computational analyses can have predictive values (PVs) of $75 to 95%; 5) current limitations of data sets and algorithms that need to be addressed to improve the computational classifiers; and 6) how in silico algorithms can be a part of the ''integrated analysis'' of multiple lines of evidence to help classify variants. We conclude that carefully validated computational algorithms, in the context of other evidence, can be an important tool for classification of missense variants. Hum Mutat 29(11), [1327][1328][1329][1330][1331][1332][1333][1334][1335][1336] 2008. r r

Familial nonmedullary thyroid cancer (FNMTC) is a clinical entity characterized by a phenotype more aggressive than that of its sporadic counterpart. Families with recurrence of nonmedullary thyroid cancer (NMTC) have been repeatedly reported in the literature, and epidemiological data show a very high relative risk for first-degree relatives of probands with thyroid cancer. The transmission of susceptibility to FNMTC is compatible with autosomal dominant inheritance with reduced penetrance, or with complex inheritance. Cases of benign thyroid disease are often found in FNMTC kindreds. We report both the identification of a new entity of FNMTC and the mapping of the responsible gene, named "TCO" (thyroid tumors with cell oxyphilia), in a French pedigree with multiple cases of multinodular goiter and NMTC. TCO was mapped to chromosome 19p13.2 by linkage analysis with a whole-genome panel of microsatellite markers. Interestingly, both the benign and malignant thyroid tumors in this family exhibit some extent of cell oxyphilia, which, until now, had not been described in the FNMTC. These findings suggest that the relatives of patients affected with sporadic NMTC with cell oxyphilia should be carefully investigated.