The Association between Leptin Level and Breast Cancer: A Meta-Analysis

Background

Contradictory results have been reported regarding the association between leptin level and breast cancer. Therefore, a meta-analysis was performed to investigate this issue.

Methods

Published literature from PubMed and the Chinese National Knowledge Infrastructure (CNKI) Database was retrieved. This study was performed based on different cases and control groups. The combined effect () with 95% confidence interval (CI) was calculated using fixed-effects or random-effects model analysis.

Results

Overall, the mean serum leptin level of case groups was significantly higher than that of control groups. A) For 9 studies comparing breast cancer cases and healthy controls the combined effect was 0.58 with 95% CI (0.48, 0.68). B) For 4 studies comparing premenopausal breast cancer cases and healthy controls the was 0.32 (0.12, 0.52). C) For 5 studies comparing postmenopausal cases and healthy controls the was 0.65 (0.46, 0.84). D) For 4 studies comparing breast cancer cases and breast benign controls the was 0.38 (0.17, 0.59). E) For 2 studies comparing premenopausal breast cancer cases and breast benign controls the was 0.33 (-0.25, 0.91). F) For 6 studies comparing postmenopausal breast cancer cases and breast benign controls the was 0.39 (0.19, 0.60). G) For 4 studies comparing lymph node metastasis positive cases and negative controls the was 0.72 (0.45, 1.00). H) For 3 studies comparing breast benign cases and healthy controls the was 0.71 (0.41, 1.01).

Conclusion

This meta-analysis suggests that leptin level plays a role in breast cancer and has potential for development as a diagnostic tool.     

The Embedding Problem for Markov Models of Nucleotide Substitution

Continuous-time Markov processes are often used to model the complex natural phenomenon of sequence evolution. To make the process of sequence evolution tractable, simplifying assumptions are often made about the sequence properties and the underlying process. The validity of one such assumption, time-homogeneity, has never been explored. Violations of this assumption can be found by identifying non-embeddability. A process is non-embeddable if it can not be embedded in a continuous time-homogeneous Markov process. In this study, non-embeddability was demonstrated to exist when modelling sequence evolution with Markov models. Evidence of non-embeddability was found primarily at the third codon position, possibly resulting from changes in mutation rate over time. Outgroup edges and those with a deeper time depth were found to have an increased probability of the underlying process being non-embeddable. Overall, low levels of non-embeddability were detected when examining individual edges of triads across a diverse set of alignments. Subsequent phylogenetic reconstruction analyses demonstrated that non-embeddability could impact on the correct prediction of phylogenies, but at extremely low levels. Despite the existence of non-embeddability, there is minimal evidence of violations of the local time homogeneity assumption and consequently the impact is likely to be minor.     

Effects of extraction methods on physicochemical properties and hypoglycemic activities of polysaccharides from coarse green tea

Glycoconjugate Journal - Coarse tea is made of mature tea plant (Camellia sinensis L.) shoots and is generally discarded as a worthless crop product, but has been proved an excellent material for...     

Nicotinamide increases the sensitivity of chronic myeloid leukemia cells to doxorubicin via the inhibition of SIRT1

The NAD-dependent deacetylase Sirtuin 1 (SIRT1) plays a vital role in leukemogenesis. Nicotinamide (NAM) is the principal NAD⁺ precursor and a noncompetitive inhibitor of SIRT1. In our study, we showed that NAM enhanced the sensitivity of chronic myeloid leukemia (CML) to doxorubicin (DOX) via SIRT1. We found that SIRT1 high expression in CML patients was associated with disease progression and drug resistance. Exogenous NAM efficiently repressed the deacetylation activity of SIRT1 and induced the apoptosis of DOX-resistant K562 cells (K562R) in a dose-dependent manner. Notably, the combination of NAM and DOX significantly inhibited tumor cell proliferation and induced cell apoptosis. The knockdown of SIRT1 in K562R cells enhanced NAM+DOX-induced apoptosis. SIRT1 rescue in K562R reduced the NAM+DOX-induced apoptosis. Mechanistically, the combinatory treatment significantly increased the cleavage of caspase-3 and PARP in K562R in vitro and in vivo. These results suggest the potential role of NAM in increasing the sensitivity of CML to DOX via the inhibition of SIRT1.     

GPR50 Distribution in the Mouse Cortex and Hippocampus

Neurochemical Research - G protein-coupled receptor 50 (GPR50) belongs to the G protein-coupled receptor which is highly homologous with the sequence of melatonin receptor MT1 and MT2. GPR50...     

Survival analysis for long noncoding RNAs identifies TP53TG1 as an antioncogenic target for the breast cancer

Breast carcinoma is one of the most commonly diagnosed tumors and also one of the deadliest cancers in the female. Long noncoding RNAs (lncRNAs) are emerging as novel targets and biomarkers for breast cancer diagnosis and treatment. In this study, we aimed to study the lncRNAs associated with the outcomes in patients using the breast invasive carcinoma datasets from The Cancer Genome Atlas. The Cox proportional hazards regression model was fitted to each lncRNA. Hierarchy clustering was carried out using these survival-related lncRNAs and the log-rank test was carried out for the clustered groups. DNA methylation status was utilized to identify the lncRNAs regulated by epigenetics. Finally, the coexpressed messenger RNA with the potential lncRNAs were utilized to study the possible functions and mechanisms of lncRNAs. In total, 182 lncRNAs had an impact on the survival time of the patients with a cutoff <0.01. The patients were clustered into three groups using these survival-related genes, which performed significantly different prognosis. Two lncRNAs, which were significantly correlated with the outcomes of breast cancer and were regulated by methylation status, were obtained. These two lncRNAs were TP53TG1 and RP5-1061H20.4. We proposed that TP53TG1 was activated by the wild-type TP53 and performed an impact on the PI3Ks family by binding YBX2 in breast cancer.     

Genetic variants associated with breast cancer risk for Ashkenazi Jewish women with strong family histories but no identifiable BRCA1/2 mutation

The ability to establish genetic risk models is critical for early identification and optimal treatment of breast cancer. For such a model to gain clinical utility, more variants must be identified beyond those discovered in previous genome-wide association studies (GWAS). This is especially true for women at high risk because of family history, but without BRCA1/2 mutations. This study incorporates three datasets in a GWAS analysis of women with Ashkenazi Jewish (AJ) homogeneous ancestry. Two independent discovery cohorts comprised 239 and 238 AJ women with invasive breast cancer or preinvasive ductal carcinoma in situ and strong family histories of breast cancer, but lacking the three BRCA1/2 founder mutations, along with 294 and 230 AJ controls, respectively. An independent, third cohort of 203 AJ cases with familial breast cancer history and 263 healthy controls of AJ women was used for validation. A total of 19 SNPs were identified as associated with familial breast cancer risk in AJ women. Among these SNPs, 13 were identified from a panel of 109 discovery SNPs, including an FGFR2 haplotype. In addition, six previously identified breast cancer GWAS SNPs were confirmed in this population. Seven of the 19 markers were significant in a multivariate predictive model of familial breast cancer in AJ women, three novel SNPs [rs17663555(5q13.2), rs566164(6q21), and rs11075884(16q22.2)], the FGFR2 haplotype, and three previously published SNPs [rs13387042(2q35), rs2046210(ESR1), and rs3112612(TOX3)], yielding moderate predictive power with an area under the curve (AUC) of the ROC (receiver-operator characteristic curve) of 0.74. Population-specific genetic variants in addition to variants shared with populations of European ancestry may improve breast cancer risk prediction among AJ women from high-risk families without founder BRCA1/2 mutations.