BRCA1-deficient mammary tumor cells are dependent on EZH2 expression and sensitive to Polycomb Repressive Complex 2-inhibitor 3-deazaneplanocin A

10.1186/bcr2354Breast Cancer Research114R6

Epigenetic silencing and deletion of the BRCA1 gene in sporadic breast cancer

INTRODUCTION: BRCA1 or BRCA2 germline mutations increase the risk of developing breast cancer. Tumour cells from germline mutation carriers have frequently lost the wild-type allele. This is predicted to result in genomic instability where cell survival depends upon dysfunctional checkpoint mechanisms. Tumorigenic potential could then be acquired through further genomic alterations. Surprisingly, somatic BRCA mutations are not found in sporadic breast tumours. BRCA1 methylation has been shown to occur in sporadic breast tumours and to be associated with reduced gene expression. We examined the frequency of BRCA1 methylation in 143 primary sporadic breast tumours along with BRCA1 copy number alterations and tumour phenotype. METHODS: Primary sporadic breast tumours were analysed for BRCA1α promoter methylation by methylation specific PCR and for allelic imbalance (AI) at BRCA1 and BRCA2 loci by microsatellite analysis and TP53 (also known as p53) mutations by constant denaturing gel electrophoresis. The BRCA1 methylated tumours were analysed for BRCA1 copy alterations by fluorescence in situ hybridisation and BRCA1 expression by immunostaining. RESULTS: BRCA1 methylation was found in 13/143 (9.1%) sporadic breast tumours. The BRCA1 methylated tumours were significantly associated with estrogen receptor (ER) negativity (P = 0.0475) and displayed a trend for BRCA1 AI (P = 0.0731) as well as young-age at diagnosis (≤ 55; P = 0.0898). BRCA1 methylation was not associated with BRCA2 AI (P = 0.5420), although a significant association was found between BRCA1 AI and BRCA2 AI (P < 0.0001). Absent/markedly reduced BRCA1 expression was observed in 9/13 BRCA1 methylated tumours, most of which had BRCA1 deletion. An elevated TP53 mutation frequency was found among BRCA1 methylated tumours (38.5%) compared with non-methylated tumours (17.2%). The BRCA1 methylated tumours were mainly of tumour grade 3 (7/13) and infiltrating ductal type (12/13). Only one methylated tumour was of grade 1. CONCLUSION: BRCA1 methylation is frequent in primary sporadic breast tumours. We found an indication for BRCA1 methylation to be associated with AI at the BRCA1 locus. Almost all BRCA1 methylated tumours with absent/markedly reduced BRCA1 expression (8/9) displayed BRCA1 deletion. Thus, epigenetic silencing and deletion of the BRCA1 gene might serve as Knudson's two 'hits' in sporadic breast tumorigenesis. We observed phenotypic similarities between BRCA1 methylated and familial BRCA1 tumours, based on BRCA1 deletion, TP53 mutations, ER status, young age at diagnosis and tumour grade

p53 mutations in human cutaneous melanoma correlate with sun exposure but are not always involved in melanomagenesis

In melanoma, the relationship between sun exposure and the origin of mutations in either the N-ras oncogene or the p53 tumour-suppressor gene is not as clear as in other types of skin cancer. We have previously shown that mutations in the N-ras gene occur more frequently in melanomas originating from sun-exposed body sites, indicating that these mutations are UV induced. To investigate whether sun exposure also affects p53 in melanoma, we analysed 81 melanoma specimens for mutations in the p53 gene. The mutation frequency is higher than thus far reported: 17 specimens (21%) harbour one or more p53 mutations. Strikingly, 17 out of 22 mutations in p53 are of the C:G to T:A or CC:GG to TT:AA transitional type, strongly suggesting an aetiology involving UV exposure. Interestingly, the p53 mutation frequency in metastases was much lower than in primary tumours. In the case of metastases, a role for sun exposure was indicated by the finding that the mutations are present exclusively in skin metastases and not in internal metastases. Together with a relatively frequent occurrence of silent third-base pair mutations in primary melanomas, this indicates that the p53 mutations, at least in these tumours, have not contributed to melanomagenesis and may have originated after establishment of the primary tumour. 1999 Cancer Research Campaig

Predicting Transcriptional Activity of Multiple Site p53 Mutants Based on Hybrid Properties

As an important tumor suppressor protein, reactivate mutated p53 was found in many kinds of human cancers and that restoring active p53 would lead to tumor regression. In this work, we developed a new computational method to predict the transcriptional activity for one-, two-, three- and four-site p53 mutants, respectively. With the approach from the general form of pseudo amino acid composition, we used eight types of features to represent the mutation and then selected the optimal prediction features based on the maximum relevance, minimum redundancy, and incremental feature selection methods. The Mathew's correlation coefficients (MCC) obtained by using nearest neighbor algorithm and jackknife cross validation for one-, two-, three- and four-site p53 mutants were 0.678, 0.314, 0.705, and 0.907, respectively. It was revealed by the further optimal feature set analysis that the 2D (two-dimensional) structure features composed the largest part of the optimal feature set and maybe played the most important roles in all four types of p53 mutant active status prediction. It was also demonstrated by the optimal feature sets, especially those at the top level, that the 3D structure features, conservation, physicochemical and biochemical properties of amino acid near the mutation site, also played quite important roles for p53 mutant active status prediction. Our study has provided a new and promising approach for finding functionally important sites and the relevant features for in-depth study of p53 protein and its action mechanism

Using focus groups to design systems science models that promote oral health equity

Background While the US population overall has experienced improvements in oral health over the past 60 years, oral diseases remain among the most common chronic conditions across the life course. Further, lack of access to oral health care contributes to profound and enduring oral health inequities worldwide. Vulnerable and underserved populations who commonly lack access to oral health care include racial/ethnic minority older adults living in urban environments. The aim of this study was to use a systematic approach to explicate cause and effect relationships in creating a causal map, a type of concept map in which the links between nodes represent causality or influence. Methods To improve our mental models of the real world and devise strategies to promote oral health equity, methods including system dynamics, agent-based modeling, geographic information science, and social network simulation have been leveraged by the research team. The practice of systems science modeling is situated amidst an ongoing modeling process of observing the real world, formulating mental models of how it works, setting decision rules to guide behavior, and from these heuristics, making decisions that in turn affect the state of the real world. Qualitative data were obtained from focus groups conducted with community-dwelling older adults who self-identify as African American, Dominican, or Puerto Rican to elicit their lived experiences in accessing oral health care in their northern Manhattan neighborhoods. Results The findings of this study support the multi-dimensional and multi-level perspective of access to oral health care and affirm a theorized discrepancy in fit between available dental providers and patients. The lack of information about oral health at the community level may be compromising the use and quality of oral health care among racial/ethnic minority older adults. Conclusions Well-informed community members may fill critical roles in oral health promotion, as they are viewed as highly credible sources of information and recommendations for dental providers. The next phase of this research will involve incorporating the knowledge gained from this study into simulation models that will be used to explore alternative paths toward improving oral health and health care for racial/ethnic minority older adults

Sex Differences in the Brain: A Whole Body Perspective

Most writing on sexual differentiation of the mammalian brain (including our own) considers just two organs: the gonads and the brain. This perspective, which leaves out all other body parts, misleads us in several ways. First, there is accumulating evidence that all organs are sexually differentiated, and that sex differences in peripheral organs affect the brain. We demonstrate this by reviewing examples involving sex differences in muscles, adipose tissue, the liver, immune system, gut, kidneys, bladder, and placenta that affect the nervous system and behavior. The second consequence of ignoring other organs when considering neural sex differences is that we are likely to miss the fact that some brain sex differences develop to compensate for differences in the internal environment (i.e., because male and female brains operate in different bodies, sex differences are required to make output/function more similar in the two sexes). We also consider evidence that sex differences in sensory systems cause male and female brains to perceive different information about the world; the two sexes are also perceived by the world differently and therefore exposed to differences in experience via treatment by others. Although the topic of sex differences in the brain is often seen as much more emotionally charged than studies of sex differences in other organs, the dichotomy is largely false. By putting the brain firmly back in the body, sex differences in the brain are predictable and can be more completely understood

Ribosome-Dependent ATPase Interacts with Conserved Membrane Protein in Escherichia coli to Modulate Protein Synthesis and Oxidative Phosphorylation

Elongation factor RbbA is required for ATP-dependent deacyl-tRNA release presumably after each peptide bond formation; however, there is no information about the cellular role. Proteomic analysis in Escherichia coli revealed that RbbA reciprocally co-purified with a conserved inner membrane protein of unknown function, YhjD. Both proteins are also physically associated with the 30S ribosome and with members of the lipopolysaccharide transport machinery. Genome-wide genetic screens of rbbA and yhjD deletion mutants revealed aggravating genetic interactions with mutants deficient in the electron transport chain. Cells lacking both rbbA and yhjD exhibited reduced cell division, respiration and global protein synthesis as well as increased sensitivity to antibiotics targeting the ETC and the accuracy of protein synthesis. Our results suggest that RbbA appears to function together with YhjD as part of a regulatory network that impacts bacterial oxidative phosphorylation and translation efficiency

Genetic Control of Resistance to Trypanosoma brucei brucei Infection in Mice

Trypanosoma brucei are extracellular protozoa transmitted to mammalian host by the tsetse fly. They developed several mechanisms that subvert host's immune defenses. Therefore analysis of genes affecting host's resistance to infection can reveal critical aspects of host-parasite interactions. Trypanosoma brucei brucei infects many animal species including livestock, with particularly severe effects in horses and dogs. Mouse strains differ greatly in susceptibility to T. b. brucei. However, genes controlling susceptibility to this parasite have not been mapped. We analyzed the genetic control of survival after T. b. brucei infection using CcS/Dem recombinant congenic (RC) strains, each of which contains a different random set of 12.5% genes of their donor parental strain STS/A on the BALB/c genetic background. The RC strain CcS-11 is even more susceptible to parasites than BALB/c or STS/A. In F2 hybrids between BALB/c and CcS-11 we detected and mapped four loci, Tbbr1-4 (Trypanosoma brucei brucei response 1–4), that control survival after T. b. brucei infection. Tbbr1 (chromosome 3) and Tbbr2 (chromosome 12) have independent effects, Tbbr3 (chromosome 7) and Tbbr4 (chromosome 19) were detected by their mutual inter-genic interaction. Tbbr2 was precision mapped to a segment of 2.15 Mb that contains 26 genes