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Histone lysine methyltransferase NSD2 (WHSC1/MMSET) is overexpressed frequently in multiple myeloma due to the t(4;14) translocation associated with 15% to 20% of cases of this disease. NSD2 has been found to be involved in myelomagenesis, suggesting it may offer a novel therapeutic target. Here we show that NSD2 methyltransferase activity is crucial for clonogenicity, adherence, and proliferation of multiple myeloma cells on bone marrow stroma in vitro and that NSD2 is required for tumorigenesis of t(4;14)+ but not t(4;14)- multiple myeloma cells in vivo. The PHD domains in NSD2 were important for its cellular activity and biological function through recruiting NSD2 to its oncogenic target genes and driving their transcriptional activation. By strengthening its disease linkage and deepening insights into its mechanism of action, this study provides a strategy to therapeutically target NSD2 in multiple myeloma patients with a t(4;14) translocation. [ABSTRACT FROM AUTHOR]

Histone lysine methyltransferase NSD2 (WHSC1/MMSET) is overexpressed frequently in multiple myeloma due to the t(4;14) translocation associated with 15% to 20% of cases of this disease. NSD2 has been found to be involved in myelomagenesis, suggesting it may offer a novel therapeutic target. Here we show that NSD2 methyltransferase activity is crucial for clonogenicity, adherence, and proliferation of multiple myeloma cells on bone marrow stroma in vitro and that NSD2 is required for tumorigenesis of t(4;14)+ but not t(4;14)- multiple myeloma cells in vivo. The PHD domains in NSD2 were important for its cellular activity and biological function through recruiting NSD2 to its oncogenic target genes and driving their transcriptional activation. By strengthening its disease linkage and deepening insights into its mechanism of action, this study provides a strategy to therapeutically target NSD2 in multiple myeloma patients with a t(4;14) translocation., (©2013 AACR.)

Inherited BRCA1/2 mutations confer elevated ovarian cancer risk. Knowledge of factors that can improve ovarian cancer risk assessment in BRCA1/2 mutation carriers is important because no effective early detection for ovarian cancers exists. A cohort of 1,575 BRCA1 and 856 BRCA2 mutation carriers was used to evaluate haplotypes at ATM, BARD1, BRIP1, CTIP, MRE11, NBS1, RAD50, RAD51, and TOPBP1 in ovarian cancer risk. In BRCA1 carriers, no associations were observed with ATM, BARD1, CTIP, RAD50, RAD51, or TOPBP1. At BRIP1, an association was observed for one haplotype with a multiple testing corrected P (P(corr)) = 0.012, although no individual haplotype was significant. At MRE11, statistically significant associations were observed for one haplotype (P(corr) = 0.007). At NBS1, we observed a P(corr) = 0.024 for haplotypes. In BRCA2 carriers, no associations were observed with CTIP, NBS1, RAD50, or TOPBP1. Rare haplotypes at ATM (P(corr) = 0.044) and BARD1 (P(corr) = 0.012) were associated with ovarian cancer risk. At BRIP1, two common haplotypes were significantly associated with ovarian cancer risk (P(corr) = 0.011). At MRE11, we observed a significant haplotype association (P(corr) = 0.012), and at RAD51, one common haplotype was significantly associated with ovarian cancer risk (P(corr) = 0.026). Variants in genes that interact biologically withBRCA1 and/or BRCA2 may be associated with modified ovarian cancer risk in women who carry BRCA1/2 mutations.

Women who carry mutations in either the BRCA1 or BRCA2 genes are at risk for early-onset breast cancer and are recommended to begin screening mammography at age 25 to 30 years. Results of in vitro and animal studies suggest that BRCA1/BRCA2 mutation carriers are hypersensitive to ionizing radiation and possibly to radiation-induced breast cancer. This study was undertaken to investigate the association of low-dose radiation exposure from mammograms with breast cancer status in BRCA mutation carriers. One hundred sixty-two female mutation carriers provided information at time of genetic testing about exposure to mammograms before enrollment. Using unconditional logistic regression, breast cancer status was not associated with number of mammograms received before diagnosis (affected women) or ascertainment [unaffected women; adjusted odds ratio (OR), 0.94; P = not significant]. A larger group of 213 women provided information about lifetime number of mammograms. There was no association between mammogram exposure and risk in the group as a whole (adjusted OR, 1.04; P = not significant), although there was a modest association in BRCA1 carriers (adjusted OR, 1.08; P = 0.03). These findings indicate that screening mammography is unlikely to be associated with a large increase in breast cancer risk in this population.

Most gene expression profiling studies of mesothelioma have been based on relatively small sample numbers, limiting their statistical power. We did Affymetrix U133A microarray analysis on 99 pleural mesotheliomas, in which multivariate analysis showed advanced-stage, sarcomatous histology and P16/CDKN2A homozygous deletion to be significant independent adverse prognostic factors. Comparison of the expression profiles of epithelioid versus sarcomatous mesotheliomas identified many genes significantly overexpressed among the former, including previously unrecognized ones, such as uroplakins and kallikrein 11, both confirmed by immunohistochemistry. Examination of the gene expression correlates of survival showed that more aggressive mesotheliomas expressed higher levels of Aurora kinases A and B and functionally related genes involved in mitosis and cell cycle control. Independent confirmation of the negative effect of Aurora kinase B was obtained by immunohistochemistry in a separate patient cohort. A role for Aurora kinases in the aggressive behavior of mesotheliomas is of potential clinical interest because of the recent development of small-molecule inhibitors. We then used our data to develop microarray-based predictors of 1 year survival; these achieved a maximal accuracy of 68% in cross-validation. However, this was inferior to prognostic prediction based on standard clinicopathologic variables and P16/CDNK2A status (accuracy, 73%), and adding the microarray model to the latter did not improve overall accuracy. Finally, we evaluated three recently published microarray-based outcome prediction models, but their accuracies ranged from 63% to 67%, consistently lower than reported. Gene expression profiling of mesotheliomas is an important discovery tool, but its power in clinical prognostication has been overestimated.