Minh Nam Nguyen

Mitochondria-targeted antioxidant MitoQ ameliorates experimental mouse colitis by suppressing NLRP3 inflammasome-mediated inflammatory cytokines

BackgroundMitoQ is a mitochondria-targeted derivative of the antioxidant ubiquinone, with antioxidant and anti-apoptotic functions. Reactive oxygen species are involved in many inflammatory diseases including inflammatory bowel disease. In this study, we assessed the therapeutic effects of MitoQ in a mouse model of experimental colitis and investigated the possible mechanisms underlying its effects on intestinal inflammation.MethodsReactive oxygen species levels and mitochondrial function were measured in blood mononuclear cells of patients with inflammatory bowel disease. The effects of MitoQ were evaluated in a dextran sulfate sodium-induced colitis mouse model. Clinical and pathological markers of disease severity and oxidative injury, and levels of inflammatory cytokines in mouse colonic tissue were measured. The effect of MitoQ on inflammatory cytokines released in the human macrophage-like cell line THP-1 was also analyzed.ResultsCellular and mitochondrial reactive oxygen species levels in mononuclear cells were significantly higher in patients with inflammatory bowel disease (P <0.003, cellular reactive oxygen species; P <0.001, mitochondrial reactive oxygen species). MitoQ significantly ameliorated colitis in the dextran sulfate sodium-induced mouse model in vivo, reduced the increased oxidative stress response (malondialdehyde and 3-nitrotyrosine formation), and suppressed mitochondrial and histopathological injury by decreasing levels of inflammatory cytokines IL-1 beta and IL-18 (P <0.001 and P <0.01 respectively). By decreasing mitochondrial reactive oxygen species, MitoQ also suppressed activation of the NLRP3 inflammasome that was responsible for maturation of IL-1 beta and IL-18. In vitro studies demonstrated that MitoQ decreases IL-1 beta and IL-18 production in human THP-1 cells.ConclusionTaken together, our results suggest that MitoQ may have potential as a novel therapeutic agent for the treatment of acute phases of inflammatory bowel disease.

Carbonyl reductase 1 is an essential regulator of skeletal muscle differentiation and regeneration.

It is well established that reactive oxygen species (ROS) are essential signaling molecules for muscle differentiation. Carbonyl reductase 1 (CBR1) reduces highly reactive lipid aldehydes and catalyzes a variety of endogenous and xenobiotic carbonyl compounds. However, the role of CBR1 in muscle differentiation remains unclear. In this study, we found that CBR1 plays a crucial role in differentiation of muscle-derived C2C12 cells. Our results clearly show that CBR1 is upregulated at the transcript level during differentiation. Consistently, CBR1 was increased during skeletal muscle regeneration in tibialis anterior muscle after injury induced by cardiotoxin. The transcriptional upregulation of CBR1 was found to be controlled by nuclear factor erythroid 2-related factor 2 (Nrf2), and Nrf2 knockdown with specific siRNA inhibited muscle differentiation. Furthermore, intracellular ROS levels and lipid peroxidation were increased in cells transfected with CBR1 siRNA, or in cells treated with the selective CBR1 inhibitor, Hydroxy-PP-Me. Subsequently, the increased ROS levels diminished muscle cell differentiation. All together, we conclude that CBR1 plays a critical role in controlling redox balance and detoxifying lipid peroxidation during muscle differentiation and regeneration.

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

Liver-targeted cyclosporine A-encapsulated poly (lactic-co-glycolic) acid nanoparticles inhibit hepatitis C virus replication.

Therapeutic options for hepatitis C virus (HCV) infection have been limited by drug resistance and adverse side effects. Targeting the host factor cyclophilin A (CypA), which is essential for HCV replication, offers a promising strategy for antiviral therapy. However, due to its immunosuppressive activity and severe side effects, clinical application of cyclosporine A (CsA) has been limited as an antiviral agent. To overcome these drawbacks, we have successfully developed a liver-specific, sustained drug delivery system by conjugating the liver-targeting peptide (LTP) to PEGylated CsA-encapsulated poly (lactic-co-glycolic) acid (PLGA) nanoparticles. Furthermore, our delivery system exhibited high specificity to liver, thus contributing to the reduced immunosuppressive effect and toxicity profile of CsA. Finally, targeted nanoparticles were able to effectively inhibit viral replication in vitro and in an HCV mouse model. As a proof of principle, we herein show that our delivery system is able to negate the adverse effects of CsA and produce therapeutic effects in an HCV mouse model.

The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer

Patient diagnosis and care would be significantly improved by understanding the mechanisms underlying platinum and taxane resistance in ovarian cancer. Here, we aim to establish a gene signature that can identify molecular pathways/transcription factors involved in ovarian cancer progression, poor clinical outcome, and chemotherapy resistance. To validate the robustness of the gene signature, a meta-analysis approach was applied to 1,020 patients from 7 datasets. A 97-gene signature was identified as an independent predictor of patient survival in association with other clinicopathological factors in univariate [hazard ratio (HR): 3.0, 95% Confidence Interval (CI) 1.66–5.44, p = 2.7E-4] and multivariate [HR: 2.88, 95% CI 1.57–5.2, p = 0.001] analyses. Subset analyses demonstrated that the signature could predict patients who would attain complete or partial remission or no-response to first-line chemotherapy. Pathway analyses revealed that the signature was regulated by HIF1α and TP53 and included nine HIF1α-regulated genes, which were highly expressed in non-responders and partial remission patients than in complete remission patients. We present the 97-gene signature as an accurate prognostic predictor of overall survival and chemoresponse. Our signature also provides information on potential candidate target genes for future treatment efforts in ovarian cancer.

An 8-gene signature for prediction of prognosis and chemoresponse in non-small cell lung cancer

Identification of a potential gene signature for improved diagnosis in non-small cell lung cancer (NSCLC) patient is necessary. Here, we aim to establish and validate the prognostic efficacy of a gene set that can predict prognosis and benefits of adjuvant chemotherapy (ACT) in NSCLC patients from various ethnicities. An 8-gene signature was calculated from the gene expression of 181 patients using univariate Cox proportional hazard regression analysis. The prognostic value of the signature was robustly validated in 1,477 patients from five microarray independent data sets and one RNA-seq data set. The 8-gene signature was identified as an independent predictor of patient survival in the presence of clinical parameters in univariate and multivariate analyses [hazard ratio (HR): 2.84, 95% confidence interval CI (1.74-4.65), p=3.06e-05, [HR] 2.62, 95% CI (1.51-4.53), p=0.001], respectively. Subset analysis demonstrated that the 8-gene signature could identify high-risk patients in stage II-III with improved survival from ACT [(HR) 1.47, 95% CI (1.01-2.14), p=0.044]. The 8-gene signature also stratified risk groups in EGFR-mutated and wild-type patients. In conclusion, the 8-gene signature is a strong and independent predictor that can significantly stratify patients into low- and high-risk groups. Our gene signature also has the potential to predict patients in stage II-III that are likely to benefit from ACT.

Prognostic value and their clinical implication of 89-gene signature in glioma

Gliomas are the most common and aggressive primary tumors in adults. The current approaches, such as histological classification and molecular genetics, have limitation in prediction of individual therapeutic outcomes due to heterogeneity within the tumor groups. Recent studies have proposed several gene signatures to predict gliomas prognosis. However, most of the gene expression profiling studies have been performed on relatively small number of patients and combined probes from diverse microarray chips. Here, we identified prognostic 89 common genes from diverse microarray chips. The 89-gene signature classified patients into good and bad prognostic groups which differed in the overall survival significantly, reflecting the biological characteristics and heterogeneity. The robustness and accuracy of the gene signature as an independent prognostic factor was validated in three microarray and one RNA-seq data sets independently. By incorporating into histological classification and molecular marker, the 89-gene signature could further stratify patients with 1p/19q co-deletion and IDH1 mutation. Additionally, subset analyses suggested that the 89-gene signature could predict patients who would benefit from adjuvant chemotherapy. Conclusively, we propose that the 89-gene signature would have an independent and accurate prognostic value for clinical use. This study also offers opportunities for novel targeted treatment of individual patients.

Hosting virtual machines on a cloud datacenter: A matching theoretic approach

In this paper, the problem of resource allocation in cloud datacenters, that own highly complex and heterogeneous tasks and servers, is considered. To address this problem, a novel framework, dubbed joint operation cost and network traffic cost (JOT) framework, is proposed. This framework combines notions from Gibbs sampling and matching theory to find an efficient solution addressing the NP-hard problem JOT. The proposed model is shown to be capable of controlling the active server set, in a coordinated manner while allocating VMs in order to reduce both operation cost and network traffic cost of the cloud datacenter. We also conduct a case-study to validate our proposed algorithm and the results show that JOT can reduce the total incurred cost by up to 19% compared to the existing non-coordinated approach.

Hosting Virtual Machines on Distributed Datacenters

Almost of cloud services nowadays are built at top geographically distributed infrastructure for better reliability and performance. These cloud providers need an efficient method to control and direct user workload to suitable datacenter, depending on many factors such as: network traffic cost, operation cost budget, energy consumption, etc. In the virtual machine placement problem, current works mainly focus on the efficiency of packing virtual machines into servers and ignore the distributed scenario of datacenters. In this paper, we consider the problem of placing virtual machines to host applications on a shared resource pool based on distributed cloud platforms. We formulate the problem of hosting virtual machines on distributed datacenters as an optimization problem, and propose a distributed framework DHC that can dynamically direct workload between datacenters to maximize total utility of entire datacenters. We also conduct many case studies to validate our method, and evaluate its effectiveness and practicality, using real-workload traffic traces. The simulation results show that our algorithm can dynamically optimize the total utility, depending on various workload of users.

Cyclophilin B induces chemoresistance by degrading wild-type p53 via interaction with MDM2 in colorectal cancer: Cyclophilin B in CRC chemoresistance

Colorectal cancer (CRC) is one of the leading causes of cancer‐related deaths worldwide. Chemoresistance is a major problem for effective therapy in CRC. Here, we investigated the mechanism by which peptidylprolyl isomerase B (PPIB; cyclophilin B, CypB) regulates chemoresistance in CRC. We found that CypB is a novel wild‐type p53 (p53WT)‐inducible gene but a negative regulator of p53WT in response to oxaliplatin treatment. Overexpression of CypB shortens the half‐life of p53WT and inhibits oxaliplatin‐induced apoptosis in CRC cells, whereas knockdown of CypB lengthens the half‐life of p53WT and stimulates p53WT‐dependent apoptosis. CypB interacts directly with MDM2, and enhances MDM2‐dependent p53WT ubiquitination and degradation. Furthermore, we firmly validated, using bioinformatics analyses, that overexpression of CypB is associated with poor prognosis in CRC progression and chemoresistance. Hence, we suggest a novel mechanism of chemoresistance caused by overexpressed CypB, which may help to develop new anti‐cancer drugs. We also propose that CypB may be utilized as a predictive biomarker in CRC patients. Copyright