Rapid Cytotoxicity of Antimicrobial Peptide Tempoprin-1CEa in Breast Cancer Cells Through Membrane Destruction and Intracellular Calcium Mechanism.

Rapid Cytotoxicity of Antimicrobial Peptide Tempoprin-1CEa in Breast Cancer Cells through Membrane Destruction and Intracellular Calcium Mechanism.

PLoS One. 2013; 8(4): e60462
Wang C, Tian LL, Li S, Li HB, Zhou Y, Wang H, Yang QZ, Ma LJ, Shang DJ

Temporin-1CEa is an antimicrobial peptide isolated from the skin secretions of the Chinese brown frog (Rana chensinensis). We have previously reported the rapid and broad-spectrum anticancer activity of temporin-1CEa in vitro. However, the detailed mechanisms for temporin-1CEa-induced cancer cell death are still weakly understood. In the present study, the mechanisms of temporin-1CEa-induced rapid cytotoxicity on two human breast cancer cell lines, MDA-MB-231 and MCF-7, were investigated. The MTT assay and the LDH leakage assay indicated that one-hour of incubation with temporin-1CEa led to cytotoxicity in a dose-dependent manner. The morphological observation using electronic microscopes suggested that one-hour exposure of temporin-1CEa resulted in profound morphological changes in both MDA-MB-231 and MCF-7 cells. The membrane-disrupting property of temporin-1CEa was further characterized by induction of cell-surface exposure of phosphatidylserine, elevation of plasma membrane permeability and rapid depolarization of transmembrane potential. Moreover, temporin-1CEa evoked intracellular calcium ion and reactive oxygen species (ROS) elevations as well as collapse of mitochondrial membrane potential (??m). In summary, the present study indicates that temporin-1CEa triggers rapid cell death in breast cancer cells. This rapid cytotoxic activity might be mediated by both membrane destruction and intracellular calcium mechanism. HubMed – drug


Systematic identification of combinatorial drivers and targets in cancer cell lines.

PLoS One. 2013; 8(4): e60339
Tabchy A, Eltonsy N, Housman DE, Mills GB

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance. HubMed – drug


Population-Based Input Function Modeling for [(18)F]FMPEP-d 2, an Inverse Agonist Radioligand for Cannabinoid CB1 Receptors: Validation in Clinical Studies.

PLoS One. 2013; 8(4): e60231
Zanotti-Fregonara P, Hirvonen J, Lyoo CH, Zoghbi SS, Rallis-Frutos D, Huestis MA, Morse C, Pike VW, Innis RB

Population-based input function (PBIF) may be a valid alternative to full blood sampling for quantitative PET imaging. PBIF is typically validated by comparing its quantification results with those obtained via arterial sampling. However, for PBIF to be employed in actual clinical research studies, its ability to faithfully capture the whole spectrum of results must be assessed. The present study validated a PBIF for [(18)F]FMPEP-d 2, a cannabinoid CB1 receptor radioligand, in healthy volunteers, and also attempted to utilize PBIF to replicate three previously published clinical studies in which the input function was acquired with arterial sampling.The PBIF was first created and validated with data from 42 healthy volunteers. This PBIF was used to assess the retest variability of [(18)F]FMPEP-d 2, and then to quantify CB1 receptors in alcoholic patients (n?=?18) and chronic daily cannabis smokers (n?=?29). Both groups were scanned at baseline and after 2-4 weeks of monitored drug abstinence.PBIF yielded accurate results in the 42 healthy subjects (average Logan-distribution volume (V T) was 13.3±3.8 mL/cm(3) for full sampling and 13.2±3.8 mL/cm(3) for PBIF; R(2)?=?0.8765, p<0.0001) and test-retest results were comparable to those obtained with full sampling (variability: 16%; intraclass correlation coefficient: 0.89). PBIF accurately replicated the alcoholism study, showing a widespread ?20% reduction of CB1 receptors in alcoholic subjects, without significant change after abstinence. However, a small PBIF-V T bias of -9% was unexpectedly observed in cannabis smokers. This bias led to substantial errors, including a V T decrease in regions that had shown no downregulation in the full input function. Simulated data showed that the original findings could only have been replicated with a PBIF bias between -6% and +4%.Despite being initially well validated in healthy subjects, PBIF may misrepresent clinical protocol results and be a source of variability between different studies and institutions. HubMed – drug


Psychiatric disorders after epilepsy diagnosis: a population-based retrospective cohort study.

PLoS One. 2013; 8(4): e59999
Chang HJ, Liao CC, Hu CJ, Shen WW, Chen TL

Psychiatric manifestations after occurrence of epilepsy have often been noted. However, the association between newly diagnosed epilepsy and psychiatric disorders afterward is not completely understood. We conducted two longitudinal cohorts for patients with and without epilepsy to investigate the risk factors and hazard ratios of developing psychiatric disorders after patients were newly diagnosed with epilepsy.We identified 938 patients with a new diagnosis of epilepsy and 518,748 participants without epilepsy from the National Health Insurance Research Database in 2000-2002 and tracked them until 2008. We compared the incidence of developing psychiatric disorders between the two cohorts, evaluated risk factors and measured the associated hazard ratios (HRs) and 95% confidence intervals (CIs) of developing psychiatric disorders.The incidences of psychiatric disorders for people with and without epilepsy were 94.1 and 22.6 per 1000 person-years, respectively. After adjusting the covariates, the epilepsy cohort showed the highest risks in mental retardation (HR 31.5, 95% CI 18.9 to 52.4), bipolar disorder (HR 23.5, 95% CI 11.4 to 48.3) and alcohol or drug psychosis (HR 18.8, 95% CI 11.1 to 31.8) among psychiatric complications developed after newly diagnosed epilepsy. The risk increased with epileptic general seizure and frequency of outpatient visits for epilepsy, as well as with emergency room visits and hospitalizations for epilepsy, and with older age. Chronologically, the highest risk occurred in the first year after epilepsy diagnosis (HR 11.4, 95% CI 9.88 to 13.2).Various psychiatric disorders were demonstrated after newly diagnosed epilepsy and closely related to general seizure and use of medical services for epilepsy. This shows a need for integrated psychiatric care for patients newly diagnosed with epilepsy, especially in the first year. HubMed – drug