Dual Neuroprotective and Neurotoxic Effects of Cannabinoid Drugs in Vitro

Either protective or toxic effects of cannabinoids on cell survival have been reported extensively in the literature; however, the factors that determine the direction of the effect are still obscured. In this study we have used the neuroblastoma cell line N18TG2 that expresses CB1 cannabinoid receptors to investigate several factors that may determine the consequences of exposure to cannabinoid agonists. Cells that were grown under optimal, stressful, or differentiating conditions were exposed to cannabinoid agonists and then assayed for cell viability by measuring MTT, LDH, and caspase-3 activity. Various cannabinoid agonists (CP 55,940, ∆9-THC, HU-210, and WIN 55,212-2) failed to affect cell viability when the cells were grown under optimal conditions. On the other hand, the same agonists significantly reduced cell viability when the cells were grown under stressful conditions (glucose- and serum-free medium), while enhancing the viability of cells grown in differentiation medium (0.5% serum and 1.5% DMSO). The toxic/protective profile was not dependent on the type or the concentration of the cannabinoid agonist that was applied. The cannabinoid agonist CP 55,940 similarly affected the non-neuronal HEK-293 cells that were grown under stressful conditions only when they expressed CB1 receptors. Our results shed light on the conflicting reports regarding the protective or toxic effects of cannabinoids in vitro and indicate that cannabinoids may activate different intracellular signaling mechanisms, depending on the state of the cell, thus leading to different physiological consequences.     

Association between Oestrogens Receptor Expressions in Breast Cancer and Comorbidities: A Cross-Sectional,Population-Based Study

Background

Breast cancer with oestrogen receptor expression is common in older women. Several factors, such as age and reproductive hormone exposure, have been associated with oestrogen receptor expression in breast cancer. However, the association between comorbidities and the oestrogen receptor expression has been poorly studied. We hypothesized that there was an association between burden comorbidity and breast cancer with oestrogen receptor expression in older women.

Objective

To determine whether oestrogen receptor expression in breast cancer was associated with burden comorbidity in community-dwelling women.

Methods

A total of 1,707 women with breast cancer registered on the list of a breast cancer registry were included. The recorded data included: age, Charlson Comorbidity Index score≥1, breast cancer characteristics (coded according to the International Classification of Diseases for Oncology), and breast cancer pathological stage (the pathological-tumour-node-metastasis, Scarff Bloom Richardson, and hormonal status of oestrogen receptor, progesterone receptor, and human epidermal growth factor receptor).

Results

Breast cancer with oestrogen receptor expression was identified in 1,378 patients (80·7%). The fully-adjusted logistic regression showed that oestrogen receptor expression was associated with Charlson Comorbidity Index score≥1 (odds ratio [OR] = 1·91,95%confidence interval [CI] = [1.01–3.61], P = 0·048), progesterone receptor expression (OR = 16·64, 95%CI = [11.62–23.81], P<0·001), human epidermal growth factor receptor (OR = 0·54, 95%CI = [0.34–0.84], P = 0·007), age (OR = 1.02, 95%CI = [1.00–1.03], P = 0.008), Scarff Bloom Richardson grade II and grade III (OR = 0·21with 95%CI = [0.10–0.44] and OR = 0·06 with 95%CI = [0.03–0.12], P<0·001).

Conclusion

Our findings provide new data showing an independent positive association between burden comorbidity and breast cancer with oestrogen receptor expression. This result confirms that evaluation of oestrogen receptor expression in breast cancer should not be limited to hormonal factors stratified by age.     

Calorimetric study on pH-responsive block copolymer grafted lipid bilayers: rational design and development of liposomes

This study is focused on chimeric advanced drug delivery nanosystems and specifically on pH-sensitive liposomes, combining lipids and pH-responsive amphiphilic block copolymers. Chimeric liposomes composed of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and two different forms of block copolymers, i.e. poly(n-butylacrylate)-b-poly(acrylic acid) (PnBA-b-PAA) at 70 and 85% content of PAA at six different molar ratios, each form respectively. PAA block exhibits pH-responsiveness, because of the regulative group of –COOH. –COOH is protonated under acidic pH (pK_a ca. 4.2), while remains ionized under basic or neutral pH, leading to liposomes repulse and eventually stability. Lipid bilayers were prepared composed of DPPC and PnBA-b-PAA. Experiments were carried out using differential scanning calorimetry (DSC) in order to investigate their thermotropic properties. DSC indicated disappearance of pre-transition at all chimeric lipid bilayers and slight thermotropic changes of the main transition temperature. Chimeric liposomes have been prepared and their physicochemical characteristics have been explored by measuring the size, size distribution and ζ-potential, owned to the presence of pH-responsive polymer. At percentages containing medium to high amounts of the polymer, chimeric liposomes were found to retain their size during the stability studies. These results were well correlated with those indicated in the DSC measurements of lipid bilayers incorporating polymers in order to explain their physicochemical behavior. The incorporation of the appropriate amount of these novel pH-responsive block copolymers affects thus the cooperativity, the liposomal stabilization and imparts pH-responsiveness.     

Immune fingerprinting through repertoire similarity

Immune repertoires provide a unique fingerprint reflecting the immune history of individuals, with potential applications in precision medicine. However, the question of how personal that information is and how it can be used to identify individuals has not been explored. Here, we show that individuals can be uniquely identified from repertoires of just a few thousands lymphocytes. We present “Immprint,” a classifier using an information-theoretic measure of repertoire similarity to distinguish pairs of repertoire samples coming from the same versus different individuals. Using published T-cell receptor repertoires and statistical modeling, we tested its ability to identify individuals with great accuracy, including identical twins, by computing false positive and false negative rates < 10⁻⁶ from samples composed of 10,000 T-cells. We verified through longitudinal datasets that the method is robust to acute infections and that the immune fingerprint is stable for at least three years. These results emphasize the private and personal nature of repertoire data.     

Coupled global and targeted proteomics of human embryonic stem cells during induced differentiation

Elucidating the complex combinations of growth factors and signaling molecules that maintain pluripotency or, alternatively, promote the controlled differentiation of human embryonic stem cells (hESCs) has important implications for the fundamental understanding of human development, devising cell replacement therapies, and cancer cell biology. hESCs are commonly grown on irradiated mouse embryonic fibroblasts (MEFs) or in conditioned medium from MEFs. These culture conditions interfere with many experimental conclusions and limit the ability to perform conclusive proteomics studies. The current investigation avoided the use of MEFs or MEF-conditioned medium for hESC culture, allowing global proteomics analysis without these confounding conditions, and elucidated neural cell-specific signaling pathways involved in noggin-induced hESC differentiation. Based on these analyses, we propose the following early markers of hESC neural differentiation: collapsin response mediator proteins 2 and 4 and the nuclear autoantigenic sperm protein as a marker of pluripotent hESCs. We then developed a directed mass spectrometry assay using multiple reaction monitoring (MRM) to identify and quantify these markers and in addition the epidermal ectoderm marker cytokeratin-8. Analysis of global proteomics, quantitative RT-PCR, and MRM data led to testing the isoform interference hypothesis where redundant peptides dilute quantification measurements of homologous proteins. These results show that targeted MRM analysis on non-redundant peptides provides more exact quantification of homologous proteins. This study describes the facile transition from discovery proteomics to targeted MRM analysis and allowed us to identify and verify several potential biomarkers for hESCs during noggin-induced neural and BMP4-induced epidermal ectoderm differentiation.     

Epistatic Gene-Based Interaction Analyses for Glaucoma in eMERGE and NEIGHBOR Consortium

Primary open angle glaucoma (POAG) is a complex disease and is one of the major leading causes of blindness worldwide. Genome-wide association studies have successfully identified several common variants associated with glaucoma; however, most of these variants only explain a small proportion of the genetic risk. Apart from the standard approach to identify main effects of variants across the genome, it is believed that gene-gene interactions can help elucidate part of the missing heritability by allowing for the test of interactions between genetic variants to mimic the complex nature of biology. To explain the etiology of glaucoma, we first performed a genome-wide association study (GWAS) on glaucoma case-control samples obtained from electronic medical records (EMR) to establish the utility of EMR data in detecting non-spurious and relevant associations; this analysis was aimed at confirming already known associations with glaucoma and validating the EMR derived glaucoma phenotype. Our findings from GWAS suggest consistent evidence of several known associations in POAG. We then performed an interaction analysis for variants found to be marginally associated with glaucoma (SNPs with main effect p-value <0.01) and observed interesting findings in the electronic MEdical Records and GEnomics Network (eMERGE) network dataset. Genes from the top epistatic interactions from eMERGE data (Likelihood Ratio Test i.e. LRT p-value <1e-05) were then tested for replication in the NEIGHBOR consortium dataset. To replicate our findings, we performed a gene-based SNP-SNP interaction analysis in NEIGHBOR and observed significant gene-gene interactions (p-value <0.001) among the top 17 gene-gene models identified in the discovery phase. Variants from gene-gene interaction analysis that we found to be associated with POAG explain 3.5% of additional genetic variance in eMERGE dataset above what is explained by the SNPs in genes that are replicated from previous GWAS studies (which was only 2.1% variance explained in eMERGE dataset); in the NEIGHBOR dataset, adding replicated SNPs from gene-gene interaction analysis explain 3.4% of total variance whereas GWAS SNPs alone explain only 2.8% of variance. Exploring gene-gene interactions may provide additional insights into many complex traits when explored in properly designed and powered association studies.