Molecular purging of multiple myeloma cells by ex-vivo culture and retroviral transduction of mobilized-blood CD34+ cells

<p>Abstract</p> <p>Background</p> <p>Tumor cell contamination of the apheresis in multiple myeloma is likely to affect disease-free and overall survival after autografting.</p> <p>Objective</p> <p>To purge myeloma aphereses from tumor contaminants with a novel culture-based purging method.</p> <p>Methods</p> <p>We cultured myeloma-positive CD34⁺PB samples in conditions that retained multipotency of hematopoietic stem cells, but were unfavourable to survival of plasma cells. Moreover, we exploited the resistance of myeloma plasma cells to retroviral transduction by targeting the hematopoietic CD34⁺cell population with a retroviral vector carrying a selectable marker (the truncated form of the human receptor for nerve growth factor, ΔNGFR). We performed therefore a further myeloma purging step by selecting the transduced cells at the end of the culture.</p> <p>Results</p> <p>Overall recovery of CD34⁺cells after culture was 128.5%; ΔNGFR transduction rate was 28.8% for CD34⁺cells and 0% for CD138-selected primary myeloma cells, respectively. Recovery of CD34⁺cells after ΔNGFR selection was 22.3%. By patient-specific Ig-gene rearrangements, we assessed a decrease of 0.7–1.4 logs in tumor load after the CD34⁺cell selection, and up to 2.3 logs after culture and ΔNGFR selection.</p> <p>Conclusion</p> <p>We conclude that <it>ex-vivo </it>culture and retroviral-mediated transduction of myeloma leukaphereses provide an efficient tumor cell purging.</p

Signaling pathway networks mined from human pituitary adenoma proteomics data

Abstract Background We obtained a series of pituitary adenoma proteomic expression data, including protein-mapping data (111 proteins), comparative proteomic data (56 differentially expressed proteins), and nitroproteomic data (17 nitroproteins). There is a pressing need to clarify the significant signaling pathway networks that derive from those proteins in order to clarify and to better understand the molecular basis of pituitary adenoma pathogenesis and to discover biomarkers. Here, we describe the significant signaling pathway networks that were mined from human pituitary adenoma proteomic data with the Ingenuity pathway analysis system. Methods The Ingenuity pathway analysis system was used to analyze signal pathway networks and canonical pathways from protein-mapping data, comparative proteomic data, adenoma nitroproteomic data, and control nitroproteomic data. A Fisher's exact test was used to test the statistical significance with a significance level of 0.05. Statistical significant results were rationalized within the pituitary adenoma biological system with literature-based bioinformatics analyses. Results For the protein-mapping data, the top pathway networks were related to cancer, cell death, and lipid metabolism; the top canonical toxicity pathways included acute-phase response, oxidative-stress response, oxidative stress, and cell-cycle G2/M transition regulation. For the comparative proteomic data, top pathway networks were related to cancer, endocrine system development and function, and lipid metabolism; the top canonical toxicity pathways included mitochondrial dysfunction, oxidative phosphorylation, oxidative-stress response, and ERK/MAPK signaling. The nitroproteomic data from a pituitary adenoma were related to cancer, cell death, lipid metabolism, and reproductive system disease, and the top canonical toxicity pathways mainly related to p38 MAPK signaling and cell-cycle G2/M transition regulation. Nitroproteins from a pituitary control related to gene expression and cellular development, and no canonical toxicity pathways were identified. Conclusions This pathway network analysis demonstrated that mitochondrial dysfunction, oxidative stress, cell-cycle dysregulation, and the MAPK-signaling abnormality are significantly associated with a pituitary adenoma. These pathway-network data provide new insights into the molecular mechanisms of human pituitary adenoma pathogenesis, and new clues for an in-depth investigation of pituitary adenoma and biomarker discovery.</p

Discovery of an Auto-Regulation Mechanism for the Maltose ABC Transporter MalFGK2

The maltose transporter MalFGK2, together with the substrate-binding protein MalE, is one of the best-characterized ABC transporters. In the conventional model, MalE captures maltose in the periplasm and delivers the sugar to the transporter. Here, using nanodiscs and proteoliposomes, we instead find that MalE is bound with high-affinity to MalFGK2 to facilitate the acquisition of the sugar. When the maltose concentration exceeds the transport capacity, MalE captures maltose and dissociates from the transporter. This mechanism explains why the transport rate is high when MalE has low affinity for maltose, and low when MalE has high affinity for maltose. Transporter-bound MalE facilitates the acquisition of the sugar at low concentrations, but also captures and dissociates from the transporter past a threshold maltose concentration. In vivo, this maltose-forced dissociation limits the rate of transport. Given the conservation of the substrate-binding proteins, this mode of allosteric regulation may be universal to ABC importers

Autonomous Targeting of Infectious Superspreaders Using Engineered Transmissible Therapies

Infectious disease treatments, both pharmaceutical and vaccine, face three universal challenges: the difficulty of targeting treatments to high-risk ‘superspreader’ populations who drive the great majority of disease spread, behavioral barriers in the host population (such as poor compliance and risk disinhibition), and the evolution of pathogen resistance. Here, we describe a proposed intervention that would overcome these challenges by capitalizing upon Therapeutic Interfering Particles (TIPs) that are engineered to replicate conditionally in the presence of the pathogen and spread between individuals — analogous to ‘transmissible immunization’ that occurs with live-attenuated vaccines (but without the potential for reversion to virulence). Building on analyses of HIV field data from sub-Saharan Africa, we construct a multi-scale model, beginning at the single-cell level, to predict the effect of TIPs on individual patient viral loads and ultimately population-level disease prevalence. Our results show that a TIP, engineered with properties based on a recent HIV gene-therapy trial, could stably lower HIV/AIDS prevalence by ∼30-fold within 50 years and could complement current therapies. In contrast, optimistic antiretroviral therapy or vaccination campaigns alone could only lower HIV/AIDS prevalence by <2-fold over 50 years. The TIP's efficacy arises from its exploitation of the same risk factors as the pathogen, allowing it to autonomously penetrate superspreader populations, maintain efficacy despite behavioral disinhibition, and limit viral resistance. While demonstrated here for HIV, the TIP concept could apply broadly to many viral infectious diseases and would represent a new paradigm for disease control, away from pathogen eradication but toward robust disease suppression

Gene therapy for monogenic liver diseases: clinical successes, current challenges and future prospects

Over the last decade, pioneering liver-directed gene therapy trials for haemophilia B have achieved sustained clinical improvement after a single systemic injection of adeno-associated virus (AAV) derived vectors encoding the human factor IX cDNA. These trials demonstrate the potential of AAV technology to provide long-lasting clinical benefit in the treatment of monogenic liver disorders. Indeed, with more than ten ongoing or planned clinical trials for haemophilia A and B and dozens of trials planned for other inherited genetic/metabolic liver diseases, clinical translation is expanding rapidly. Gene therapy is likely to become an option for routine care of a subset of severe inherited genetic/metabolic liver diseases in the relatively near term. In this review, we aim to summarise the milestones in the development of gene therapy, present the different vector tools and their clinical applications for liver-directed gene therapy. AAV-derived vectors are emerging as the leading candidates for clinical translation of gene delivery to the liver. Therefore, we focus on clinical applications of AAV vectors in providing the most recent update on clinical outcomes of completed and ongoing gene therapy trials and comment on the current challenges that the field is facing for large-scale clinical translation. There is clearly an urgent need for more efficient therapies in many severe monogenic liver disorders, which will require careful risk-benefit analysis for each indication, especially in paediatrics

Regularized Fuzzy Neural Network Based on Or Neuron for Time Series Forecasting

This paper presents a training algorithm for regularized fuzzy neural networks which is able to generate consistent and accurate models while adding some level of interpretation to applied problems to act in the prediction of time series. Learning is achieved through extreme learning machines to estimate the parameters and a technique of selection of characteristics using regularization concept and resampling, which is able to perform the definition of the network topology through the selection of subsets of fuzzy neuron more significant to the problem. Numerical experiments are presented for time series problems using benchmark bases on machine learning problems. The results obtained are compared to other techniques of prediction of reference series in the literature. The model made rough estimates of the responses obtained by the models of fuzzy neural networks for time series forecasting with fewer fuzzy rules

Stripe disorder and dynamics in the hole-doped antiferromagnetic insulator La5/3Sr1/3CoO4

We investigate the magnetic ordering and dynamics of the stripe phase of La5/3Sr1/3CoO4, a material shown to have an hourglass magnetic excitation spectrum. A combination of muon-spin relaxation, nuclear magnetic resonance, and magnetic susceptibility measurements strongly suggest that the physics is determined by a partially disordered configuration of charge and spin stripes whose frustrated magnetic degrees of freedom are dynamic at high temperature and which undergo an ordering transition around 35 K with coexisting dynamics that freeze out in a glassy manner as the temperature is further reduced. © 2014 American Physical Society