Using Decision Forest to Classify Prostate Cancer Samples on the Basis of SELDI-TOF MS Data: Assessing Chance Correlation and Prediction Confidence

Class prediction using “omics” data is playing an increasing role in toxicogenomics, diagnosis/prognosis, and risk assessment. These data are usually noisy and represented by relatively few samples and a very large number of predictor variables (e.g., genes of DNA microarray data or m/z peaks of mass spectrometry data). These characteristics manifest the importance of assessing potential random correlation and overfitting of noise for a classification model based on omics data. We present a novel classification method, decision forest (DF), for class prediction using omics data. DF combines the results of multiple heterogeneous but comparable decision tree (DT) models to produce a consensus prediction. The method is less prone to overfitting of noise and chance correlation. A DF model was developed to predict presence of prostate cancer using a proteomic data set generated from surface-enhanced laser deposition/ionization time-of-flight mass spectrometry (SELDI-TOF MS). The degree of chance correlation and prediction confidence of the model was rigorously assessed by extensive cross-validation and randomization testing. Comparison of model prediction with imposed random correlation demonstrated biologic relevance of the model and the reduction of overfitting in DF. Furthermore, two confidence levels (high and low confidences) were assigned to each prediction, where most misclassifications were associated with the low-confidence region. For the high-confidence prediction, the model achieved 99.2% sensitivity and 98.2% specificity. The model also identified a list of significant peaks that could be useful for biomarker identification. DF should be equally applicable to other omics data such as gene expression data or metabolomic data. The DF algorithm is available upon request

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms

A hierarchical kinetic theory of birth, death, and fission in age-structured interacting populations

We study mathematical models describing the evolution of stochastic age-structured populations. After reviewing existing approaches, we develop a complete kinetic framework for age-structured interacting populations undergoing birth, death and fission processes in spatially dependent environments. We define the full probability density for the population-size age chart and find results under specific conditions. Connections with more classical models are also explicitly derived. In particular, we show that factorial moments for non-interacting processes are described by a natural generalization of the McKendrick-von Foerster equation, which describes mean-field deterministic behavior. Our approach utilizes mixed-type, multidimensional probability distributions similar to those employed in the study of gas kinetics and with terms that satisfy BBGKY-like equation hierarchies

Blockade of Mast Cell Activation Reduces Cutaneous Scar Formation

Damage to the skin initiates a cascade of well-orchestrated events that ultimately leads to repair of the wound. The inflammatory response is key to wound healing both through preventing infection and stimulating proliferation and remodeling of the skin. Mast cells within the tissue are one of the first immune cells to respond to trauma, and upon activation they release pro-inflammatory molecules to initiate recruitment of leukocytes and promote a vascular response in the tissue. Additionally, mast cells stimulate collagen synthesis by dermal fibroblasts, suggesting they may also influence scar formation. To examine the contribution of mast cells in tissue repair, we determined the effects the mast cell inhibitor, disodium cromoglycate (DSCG), on several parameters of dermal repair including, inflammation, re-epithelialization, collagen fiber organization, collagen ultrastructure, scar width and wound breaking strength. Mice treated with DSCG had significantly reduced levels of the inflammatory cytokines IL-1a, IL-1b, and CXCL1. Although DSCG treatment reduced the production of inflammatory mediators, the rate of re-epithelialization was not affected. Compared to control, inhibition of mast cell activity caused a significant decrease in scar width along with accelerated collagen re-organization. Despite the reduced scar width, DSCG treatment did not affect the breaking strength of the healed tissue. Tryptase b1 exclusively produced by mast cells was found to increase significantly in the course of wound healing. However, DSCG treatment did not change its level in the wounds. These results indicate that blockade of mast cell activation reduces scar formation and inflammation without further weakening the healed wound

Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer

Genome-wide association studies have reported 56 independently associated colorectal cancer (CRC) risk variants, most of which are non-coding and believed to exert their effects by modulating gene expression. The computational method PrediXcan uses cis-regulatory variant predictors to impute expression and perform gene-level association tests in GWAS without directly measured transcriptomes. In this study, we used reference datasets from colon (n = 169) and whole blood (n = 922) transcriptomes to test CRC association with genetically determined expression levels in a genome-wide analysis of 12,186 cases and 14,718 controls. Three novel associations were discovered from colon transverse models at FDR ≤ 0.2 and further evaluated in an independent replication including 32,825 cases and 39,933 controls. After adjusting for multiple comparisons, we found statistically significant associations using colon transcriptome models with TRIM4 (discovery P = 2.2 × 10- 4, replication P = 0.01), and PYGL (discovery P = 2.3 × 10- 4, replication P = 6.7 × 10- 4). Interestingly, both genes encode proteins that influence redox homeostasis and are related to cellular metabolic reprogramming in tumors, implicating a novel CRC pathway linked to cell growth and proliferation. Defining CRC risk regions as one megabase up- and downstream of one of the 56 independent risk variants, we defined 44 non-overlapping CRC-risk regions. Among these risk regions, we identified genes associated with CRC (P < 0.05) in 34/44 CRC-risk regions. Importantly, CRC association was found for two genes in the previously reported 2q25 locus, CXCR1 and CXCR2, which are potential cancer therapeutic targets. These findings provide strong candidate genes to prioritize for subsequent laboratory follow-up of GWAS loci. This study is the first to implement PrediXcan in a large colorectal cancer study and findings highlight the utility of integrating transcriptome data in GWAS for discovery of, and biological insight into, risk loci

One-step hydrothermal synthesis of graphene decorated V2O5 nanobelts for enhanced electrochemical energy storage

Graphene-decorated V2O5 nanobelts (GVNBs) were synthesized via a low-temperature hydrothermal method in a single step. V2O5 nanobelts (VNBs) were formed in the presence of graphene oxide, a mild oxidant, which also enhanced the conductivity of GVNBs. From the electron energy loss spectroscopy analysis, the reduced graphene oxide (rGO) are inserted into the layered crystal structure of V2O5 nanobelts, which further confirmed the enhanced conductivity of the nanobelts. The electrochemical energy-storage capacity of GVNBs was investigated for supercapacitor applications. The specific capacitance of GVNBs was evaluated using cyclic voltammetry (CV) and charge/discharge (CD) studies. The GVNBs having V2O5-rich composite, namely, V(3)G(1) (VO/GO = 3:1), showed superior specific capacitance in comparison to the other composites (V(1)G(1) and V(1)G(3)) and the pure materials. Moreover, the V(3)G(1) composite showed excellent cyclic stability and the capacitance retention of about 82% was observed even after 5000 cycles.open

Minnelide effectively eliminates CD133+ side population in pancreatic cancer

BACKGROUND: Pancreatic Ductal Adenocarcinoma (PDAC) is a devastating disease hallmarked by limited patient survival. Resistance to chemotherapy, a major cause of treatment failure in PDAC patients, is often attributed to Cancer Stem Cells (CSCs). Pancreatic CSCs are a small subset of quiescent cells within a tumor represented by surface markers like CD133. These cells are responsible not only for tumor recurrence, but also poor prognosis based on their “stem-like” characteristics. At present, conventional therapy is directed towards rapidly dividing PDAC cells and thus fails to target the CSC population. METHODS: MIA PaCa-2, S2-013 and AsPC-1 were treated with 12.5 nM triptolide (12 T cells) for 7 days. The surviving cells were recovered briefly in drug-free growth media and then transferred to Cancer Stem cell Media (CSM). As a control, untreated cells were also transferred to CSM media (CSM). The 12 T and CSM cells were tested for stemness properties using RNA and protein markers. Low numbers of CSM and 12 T cells were implanted subcutaneously in athymic nude mice to study their tumorigenic potential. 12 T and CSM cells were sorted for CD133 expression and assayed for their colony forming ability and sphere forming ability. Invasiveness of 12 T cells, CSM and MIA PaCa-2 were compared using Boyden chamber assays. RESULTS: Treated 12 T cells displayed increased expression of the surface marker CD133 and the drug transporter ABCG2 compared to untreated cells (CSM cells). Both 12 T and CSM cells formed subcutaneous tumors in mice confirming their tumor-initiating properties. When tested for invasion, 12 T cells had increased invasiveness compared to CSM cells. CD133(+) cells in both CSM and 12 T showed greater colony and sphere forming ability compared to CD133(−) cells from each group. Consistent with these data, when injected subcutaneously in mice, CD133(−) cells from CSM or 12 T did not form any tumors whereas CD133(+) cells from both groups showed tumor formation at a very low cell number. Despite pre-exposure to triptolide in 12 T CD133(+) cells, treatment of tumors formed by these cells with Minnelide, a triptolide pro-drug, showed significant tumor regression. CONCLUSION: Our results indicated that triptolide enhanced and enriched the “stemness” in the PDAC cell lines at a low dose of 12.5 nM, but also resulted in the regression of tumors derived from these cells. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12943-015-0470-6) contains supplementary material, which is available to authorized users

Implication of 4E-BP1 protein dephosphorylation and accumulation in pancreatic cancer cell death induced by combined gemcitabine and TRAIL

Pancreatic cancer cells show varying sensitivity to the anticancer effects of gemcitabine. However, as a chemotherapeutic agent, gemcitabine can cause intolerably high levels of toxicity and patients often develop resistance to the beneficial effects of this drug. Combination studies show that use of gemcitabine with the pro-apoptotic cytokine TRAIL can enhance the inhibition of survival and induction of apoptosis of pancreatic cancer cells. Additionally, following combination treatment there is a dramatic increase in the level of the hypophosphorylated form of the tumour suppressor protein 4E-BP1. This is associated with inhibition of mTOR activity, resulting from caspase-mediated cleavage of the Raptor and Rictor components of mTOR. Use of the pan-caspase inhibitor Z-VAD-FMK indicates that the increase in level of 4E-BP1 is also caspase-mediated. ShRNA-silencing of 4E-BP1 expression renders cells more resistant to cell death induced by the combination treatment. Since the levels of 4E-BP1 are relatively low in untreated pancreatic cancer cells these results suggest that combined therapy with gemcitabine and TRAIL could improve the responsiveness of tumours to treatment by elevating the expression of 4E-BP1

The nuclear receptor LXR modulates interleukin-18 levels through multiple mechanisms

IL-18 is a member of the IL-1 family involved in innate immunity and inflammation. Deregulated levels of IL-18 are involved in the pathogenesis of multiple disorders including inflammatory and metabolic diseases, yet relatively little is known regarding its regulation. Liver X receptors or LXRs are key modulators of macrophage cholesterol homeostasis and immune responses. Here we show that LXR ligands negatively regulate LPS-induced mRNA and protein expression of IL-18 in bone marrow-derived macrophages. Consistent with this being an LXR-mediated process, inhibition is abolished in the presence of a specific LXR antagonist and in LXR-deficient macrophages. Additionally, IL-18 processing of its precursor inactive form to its bioactive state is inhibited by LXR through negative regulation of both pro-caspase 1 expression and activation. Finally, LXR ligands further modulate IL-18 levels by inducing the expression of IL-18BP, a potent endogenous inhibitor of IL-18. This regulation occurs via the transcription factor IRF8, thus identifying IL-18BP as a novel LXR and IRF8 target gene. In conclusion, LXR activation inhibits IL-18 production through regulation of its transcription and maturation into an active pro-inflammatory cytokine. This novel regulation of IL-18 by LXR could be applied to modulate the severity of IL-18 driven metabolic and inflammatory disorders