Investigation of the 1758G>C and 2880A>G variants within the NCOA3 gene in a breast cancer affected Australian population

Classification of Homo sapiens gene behavior using linear discriminant analysis fused with minimum entropy mapping

Classification of Homo sapiens gene behavior employing computational biology is a recent research trend. But monitoring gene activity profile and genetic behavior from the alphabetic DNA sequence using a non-invasive method is a tremendous challenge in functional genomics. The present paper addresses such issue and attempts to differentiate Homo sapiens genes using linear discriminant analysis (LDA) method. Annotated protein coding sequences of Homo sapiens genes, collected from NCBI, are taken as test samples. Minimum entropy-based mapping (MEM) technique assists to extract highest information from the numerical DNA sequences. The proposed LDA technique has successfully classified Homo sapiens genes based on the following features: composition of hydrophilic amino acids, dominance of arginine amino acid, and magnitude and size of individual amino acids. The proposed algorithm is successfully tested on 84 Homo sapiens healthy and cancer genes of the prostate and breast cells. Classification performance of the proposed LDA technique is judged by sensitivity (89.12%), specificity (91.9%), accuracy (90.87%), F1 score (92.03%), Matthews' correlation coefficients (81.04%), and miss rate (9.12%), and it outperforms other four existing classifiers. The results are cross-validated through Rayleigh PDF and mutual information technique. Fisher test, 2-sample T-test, and relative entropy test are considered to verify the efficacy of the present classifier.

Prognostic Significance of CHEK2 Mutation in Progression of Breast Cancer

Breast cancer (BC) is one of the most common cancers among women; genetic mutations reflect the development of this disease. Mutations in cell signaling factors can be the main cause of BC development. In this study, we focused on mutations in checkpoint kinase 2 (CHEK2) and their impact as a prognostic factor in the pathogenesis of BC. CHEK2 is controlled in cell signaling pathways through the influence of upstream genes. Also, several downstream genes are regulated by CHEK2. In addition, mutations in CHEK2 lead to resistance of BC cells to chemotherapy and metastasis of cancer cells to other parts of the body. Finally, detection of mutations in CHEK2 can be used as a prognostic factor for patient response to treatment and for targeting downstream molecules of CHEK2 that are involved in the proliferation of breast tumor cells. Mutations such as c.1100delC and I157T can distinguish which patients are susceptible to metastasis.

Association of NCOA3 polymorphisms with Dyslipidemia in the Chinese Han population

Background

Nuclear receptor coactivator-3 (NCOA3) is involved in various physiological processes. Emerging evidence from previous studies using animal models suggests that the NCOA3 gene (NCOA3) plays a critical role in lipid metabolism as well as adipogenesis and obesity. The present study aims to investigate the association between NCOA3 SNPs and dyslipidemia in the Chinese Han population.

Methods

Five hundred and twenty-nine (529) Chinese Han subjects were recruited. Four tag SNPs (rs2425955G > T, rs6066394T > C, rs10485463C > G, and rs6094753G > A) in NCOA3, selected from the HapMap website, were genotyped using MALDI-TOF mass spectrometry. Data analysis was performed using SPSS 16.0, SNPStats and haploview 4.2.

Results

Four SNPs (rs2425955, rs6066394, rs10485463, and rs6094753) were associated with triglyceride levels. Except for SNP rs10485463, genotype distributions and allele frequencies of the other three NCOA3 SNPs (rs2425955, rs6066394, and rs6094753) were significantly different between hypertriglyceridemia subjects and normal group. Significant differences were also observed in allele frequencies and genotype distributions of SNP rs10485463 between low-HDL cholesterolemia subjects and normal group. Carriers of rs2425955 T allele had a lower risk of hypertriglyceridemia compared to GG genotype. Similar results were observed from rs6094753. Subjects with rs6066394 CT genotype had a lower risk of hypertriglyceridemia than those with the TT genotype; however, CC and TT genotypes showed no significant difference in the risk of hypertriglyceridemia. Similar results were found in the association between rs6066394 and hypercholesterolemia. The variant alleles of rs2425955, rs6066394 and rs6094753 were associated with a lower risk of hypertriglyceridemia compared with the wild-type alleles. The G allele of rs10485463 was associated with an increased risk of low-HDL cholesterolemia. In the log-additive model the association between rs2425955 and hypertriglyceridemia remained significant after Bonferroni correction, and genotypes with variant alleles were associated with a lower risk of hypertriglyceridemia.

Conclusions

In summary, this study demonstrated that variation in NCOA3 might influence the risk of dyslipidemia and serum lipid levels in Chinese Han population.

Identification of a novel BRCA2 and CHEK2 A-C-G-C haplotype in Turkish patients affected with breast cancer

BACKGROUND

Many breast cancers are caused by certain rare and familial mutations in the high or moderate penetrance genes BRCA1, BRCA2 and CHEK2. The aim of this study was to examine the allele and genotype frequencies of seven mutations in BRCA1, BRCA2 and CHEK2 genes in breast cancer patients and to investigate their isolated and combined associations with breast cancer risk.

METHODS

We genotyped seven mutations in BRCA1, BRCA2 and CHEK2 genes and then analyzed single variations and haplotype associations in 106 breast cancer patients and 80 healthy controls.

RESULTS

We found significant associations in the analyses of CHEK2- 1100delC (p=0.001) and BRCA1-5382insC (p=0.021) mutations in breast cancer patients compared to controls. The highest risk was observed among breast cancer patients carrying both CHEK2-1100delC and BRCA2- Met784Val mutations (OR=0.093; 95%CI 0.021-0.423; p=0.001). We identified one previously undescribed BRCA2 and a CHEK2 four-marker haplotype of A-C-G-C which was overrepresented (?2=7.655; p=0.0057) in the patient group compared to controls.

CONCLUSION

In this study, we identified a previously undescribed BRCA2 and CHEK2 A-C-G-C haplotype in association with the breast cancer in our population. Our results further suggest that the CHEK2-1100delC mutation in combination with BRCA2-Met784Val may lead to an unexpected high risk which needs to be confirmed in larger cohorts in order to better understand their role in the development and prognosis of breast cancer.

A behavioral study of healthy and cancer genes by modeling electrical network

In recent years, gene network modeling is gaining popularity in genomics to monitor the activity profile of genes. More specifically, the objective of the network modeling concept is to study the genetic behavior associated with disease. Previous researchers have designed network model at nucleotide level which produces more complexity for designing circuits mostly in case of gene expression studies. Whereas the authors have designed the present network model, based on amino acid level which is simpler as well as more appropriate for prediction of the genetic abnormality. In the present concept, SISO continuous and discrete system models of genes are realized using Foster network. The model is designed based on hydropathy index value of amino acids to study the biological system behavior. The time and phase response in continuous (s) domain and pole-zero distribution in discrete (z) domain are used as measurement metric in the present study. The simulated responses of the system show genetic instability for cancer genes which truly reflects the medical reports. The proposed modeling concept can be used, to accurately identify or separate out the diseased genes from healthy genes.

AIB1 polymorphisms with breast cancer susceptibility: a pooled analysis of variation in BRCA1/2 mutation carriers and non-carriers

The AIB1 gene (amplified in breast cancer 1), coding for a member of steroid receptor co-activator p160 protein family is involved in regulation of estrogen receptor transactivation influencing the estrogen-dependent gene expression. It contains a glutamine repeat polymorphism and several single nucleotide polymorphisms that may alter the transcriptional activation of the receptor and affect susceptibility to breast cancer. Previous studies have shown that these polymorphisms may modify the breast cancer risk in women carrying BRCA1/2 mutations. However, the results remained controversial. This meta-analysis of literatures was performed to derive a more precise estimation of the relationship. A total of 22 studies were identified, including 3,742 cases and 3,491 controls for AIB1 polyglutamine repeat polymorphism, 2,170 cases and 3,309 controls for Q586H polymorphism, and 2,183 cases and 3,319 controls for T960T polymorphism. Overall, we found no evidence of association for individuals who carried at least one AIB1 allele of 28 or 29 or more repeat with breast cancer risk. But we found increased breast cancer risk in BRCA1/2 mutation carriers for individuals with both alleles ≥29 polyglutamine repeat (OR, 1.64; 95% CI 1.24-2.17). And reduced risk was found to be associated with the Q586H polymorphism among the variant homozygote genotype carriers (OR, 0.42; 95% CI 0.23-0.77). Our results do not support the direct association of AIB1 polyglutamine repeat length and breast cancer. However, we found that BRCA1/2 mutation carriers with both alleles ≥29 repeats have a higher risk of breast cancer.