Characterization of circulating tumor cells in patients with metastatic bladder cancer utilizing functionalized microfluidics.

Assessing the molecular profiles of bladder cancer (BC) from patients with locally advanced or metastatic disease provides valuable insights, such as identification of invasive markers, to guide personalized treatment. Currently, most molecular profiling of BC is based on highly invasive biopsy or transurethral tumor resection. Liquid biopsy takes advantage of less-invasive procedures to longitudinally profile disease. Circulating tumor cells (CTCs) isolated from blood are one of the key analytes of liquid biopsy. In this study, we developed a protein and mRNA co-analysis workflow for BC CTCs utilizing the graphene oxide (GO) microfluidic chip. The GO chip was conjugated with antibodies against both EpCAM and EGFR to isolate CTCs from 1 mL of blood drawn from BC patients. Following CTC capture, protein and mRNA were analyzed using immunofluorescent staining and ion-torrent-based whole transcriptome sequencing, respectively. Elevated CTC counts were significantly associated with patient disease status at the time of blood draw. We found a count greater than 2.5 CTCs per mL was associated with shorter overall survival. The invasive markers EGFR, HER2, CD31, and ADAM15 were detected in CTC subpopulations. Whole transcriptome sequencing showed distinct RNA expression profiles from patients with or without tumor burden at the time of blood draw. In patients with advanced metastatic disease, we found significant upregulation of metastasis-related and chemotherapy-resistant genes. This methodology demonstrates the capability of GO chip-based assays to identify tumor-related RNA signatures, highlighting the prognostic potential of CTCs in metastatic BC patients.

STR mutations on chromosome 15q cause thyrotropin resistance by activating a primate-specific enhancer of MIR7-2/MIR1179.

Thyrotropin (TSH) is the master regulator of thyroid gland growth and function. Resistance to TSH (RTSH) describes conditions with reduced sensitivity to TSH. Dominantly inherited RTSH has been linked to a locus on chromosome 15q, but its genetic basis has remained elusive. Here we show that non-coding mutations in a (TTTG)4 short tandem repeat (STR) underlie dominantly inherited RTSH in all 82 affected participants from 12 unrelated families. The STR is contained in a primate-specific Alu retrotransposon with thyroid-specific cis-regulatory chromatin features. Fiber-seq and RNA-seq studies revealed that the mutant STR activates a thyroid-specific enhancer cluster, leading to haplotype-specific upregulation of the bicistronic MIR7-2/MIR1179 locus 35 kb downstream and overexpression of its microRNA products in the participants' thyrocytes. An imbalance in signaling pathways targeted by these micro-RNAs provides a working model for this cause of RTSH. This finding broadens our current knowledge of genetic defects altering pituitary-thyroid feedback regulation.

Blood and cerebellar abundance of ATXN3 splice variants in spinocerebellar ataxia type 3/Machado-Joseph disease.

Spinocerebellar ataxia type 3 (SCA3)/Machado-Joseph disease (MJD) is a heritable proteinopathy disorder, whose causative gene, ATXN3, undergoes alternative splicing. Ataxin-3 protein isoforms differ in their toxicity, suggesting that certain ATXN3 splice variants may be crucial in driving the selective toxicity in SCA3. Using RNA-seq datasets we identified and determined the abundance of annotated ATXN3 transcripts in blood (n = 60) and cerebellum (n = 12) of SCA3 subjects and controls. The reference transcript (ATXN3-251), translating into an ataxin-3 isoform harbouring three ubiquitin-interacting motifs (UIMs), showed the highest abundance in blood, while the most abundant transcript in the cerebellum (ATXN3-208) was of unclear function. Noteworthy, two of the four transcripts that encode full-length ataxin-3 isoforms but differ in the C-terminus were strongly related with tissue expression specificity: ATXN3-251 (3UIM) was expressed in blood 50-fold more than in the cerebellum, whereas ATXN3-214 (2UIM) was expressed in the cerebellum 20-fold more than in the blood. These findings shed light on ATXN3 alternative splicing, aiding in the comprehension of SCA3 pathogenesis and providing guidance in the design of future ATXN3 mRNA-lowering therapies.

Immunomodulatory differences between mesenchymal stem cells from different oral tissues.

Mesenchymal stem cells (MSCs) have recently been identified as having potentially therapeutic immunomodulatory properties. MSCs isolated from different oral tissues have similar morphology and immunophenotypes, however, direct comparisons of their gene expression and immunomodulatory properties have not been conducted. We isolated alveolar bone-derived MSCs (aBMSCs), dental pulp stem cells (DPSCs) and gingiva-derived MSCs (GMSCs) from the same patients and compared their immunophenotypes and transcriptomes. Additionally, we compared their production of soluble immunomodulatory cytokines as well as their immunoregulatory properties in coculture with THP-1 human monocytic cells. RNA sequencing revealed distinct gene expression in DPSCs while aBMSCs and GMSCs had less differentially expressed genes. DPSCs also had significantly less secretion of osteopontin compared to aBMSCs and GMSCs. Finally, DPSCs did not exhibit an immunosuppresive effect on THP-1 cells to the same degree as aBMSCs and GMSCs. These findings demonstrate that MSCs from different oral tissues have distinct transcriptomes and immunoregulatory properties.

Zinc Finger MYND-Type Containing 8 (ZMYND8) Is Epigenetically Regulated in Mutant Isocitrate Dehydrogenase 1 (IDH1) Glioma to Promote Radioresistance.

PURPOSE: Mutant isocitrate dehydrogenase 1 (mIDH1) alters the epigenetic regulation of chromatin, leading to a hypermethylation phenotype in adult glioma. This work focuses on identifying gene targets epigenetically dysregulated by mIDH1 to confer therapeutic resistance to ionizing radiation (IR). EXPERIMENTAL DESIGN: We evaluated changes in the transcriptome and epigenome in a radioresistant mIDH1 patient-derived glioma cell culture (GCC) following treatment with an mIDH1-specific inhibitor, AGI-5198. We identified Zinc Finger MYND-Type Containing 8 (ZMYND8) as a potential target of mIDH1 reprogramming. We suppressed ZMYND8 expression by shRNA knockdown and genetic knockout (KO) in mIDH1 glioma cells and then assessed cellular viability to IR. We assessed the sensitivity of mIDH1 GCCS to pharmacologic inhibition of ZMYND8-interacting partners: HDAC, BRD4, and PARP. RESULTS: Inhibition of mIDH1 leads to an upregulation of gene networks involved in replication stress. We found that the expression of ZMYND8, a regulator of DNA damage response, was decreased in three patient-derived mIDH1 GCCs after treatment with AGI-5198. Knockdown of ZMYND8 expression sensitized mIDH1 GCCs to radiotherapy marked by decreased cellular viability. Following IR, mIDH1 glioma cells with ZMYND8 KO exhibit significant phosphorylation of ATM and sustained γH2AX activation. ZMYND8 KO mIDH1 GCCs were further responsive to IR when treated with either BRD4 or HDAC inhibitors. PARP inhibition further enhanced the efficacy of radiotherapy in ZMYND8 KO mIDH1 glioma cells. CONCLUSIONS: These findings indicate the impact of ZMYND8 in the maintenance of genomic integrity and repair of IR-induced DNA damage in mIDH1 glioma. See related commentary by Sachdev et al., p. 1648.

Molecular Markers for Long-term Survival in Stage IIIA (N2) NSCLC Patients.

BACKGROUND: Survival rates among non-small cell lung cancer (NSCLC) stage IIIA (N2) patients are generally low and depend on the treatment. PATIENTS AND METHODS: We aimed to identify predictive markers for long term survival in responders and non-responders to chemotherapy, analyzing tumour and non-tumour samples by microarray (n=35) and whole exome sequencing (WES, n=25). RESULTS: WES data showed correlation of overall survival of all patients with rs9905892 in the SLFN12L gene. High frequency of mutations (4/6, 66.7%) was identified in members of SWI/SNF complex in responder patients and in patients that were alive after seven years. Microarray data for immune components showed that VISTA (VSIR) was down-regulated in tumoral tissue. CONCLUSION: Our research suggests that mutations in SWI/SNF complex associate with long term survival after multimodal treatment, while down-regulation of VISTA might indicate its immunomodulatory role in NSCLC stage III (N2) patients.

Assessment of the Cytoprotective Effects of High-Dose Valproic Acid Compared to a Clinically Used Lower Dose.

OBJECTIVE: Valproic acid (VPA) treatment improves survival in animal models of injuries on doses higher than those allowed by Food and Drug Administration (FDA). We investigated the proteomic alterations induced by a single high-dose (140mg/kg) of VPA (VPA140) compared to the FDA-approved dose of 30mg/kg (VPA30) in healthy humans. We also describe the proteomic and transcriptomic changes induced by VPA140 in an injured patient. We hypothesized that VPA140 would induce cytoprotective changes in the study participants. METHODS: Serum samples were obtained from healthy subjects randomized to two groups; VPA140 and VPA30 at 3 timepoints: 0h(baseline), 2h, and 24h following infusion(n = 3/group). Samples were also obtained from an injured patient that received VPA140 at 0h, 6h and 24h following infusion. Proteomic analyses were performed using liquid chromatography-mass spectrometry (LC-MS/MS), and transcriptomic analysis was performed using RNA-sequencing. Differentially expressed (DE) proteins and genes were identified for functional annotation and pathway analysis using iPathwayGuide and gene set enrichment analysis (GSEA), respectively. RESULTS: For healthy individuals, a dose comparison was performed between VPA140 and VPA30 groups at 2 and 24 h. Functional annotation showed that top biological processes in VPA140 versus VPA30 analysis at 2 h included regulation of fatty acid (P = 0.002) and ATP biosynthesis (P = 0.007), response to hypoxia (P = 0.017), cell polarity regulation (P = 0.031), and sequestration of calcium ions (P = 0.031). Top processes at 24 h in VPA140 versus VPA30 analysis included amino acid metabolism (P = 0.023), collagen catabolism (P = 0.023), and regulation of protein breakdown (P = 0.023). In the injured patient, annotation of the DE proteins in the serum showed that top biological processes at 2 h included neutrophil chemotaxis (P = 0.002), regulation of cellular response to heat (P = 0.008), regulation of oxidative stress (P = 0.008) and regulation of apoptotic signaling pathway (P = 0.008). Top biological processes in the injured patient at 24 h included autophagy (P = 0.01), glycolysis (P = 0.01), regulation of apoptosis (P = 0.01) and neuron apoptotic processes (P = 0.02). CONCLUSIONS: VPA140 induces cytoprotective changes in human proteome not observed in VPA30. These changes may be responsible for its protective effects in response to injuries.

Modulation of Brain Transcriptome by Combined Histone Deacetylase Inhibition and Plasma Treatment Following Traumatic Brain Injury and Hemorrhagic Shock.

INTRODUCTION: We previously showed that the addition of valproic acid (VPA), a histone deacetylase inhibitor, to fresh frozen plasma (FFP) resuscitation attenuates brain lesion size and swelling following traumatic brain injury (TBI) and hemorrhagic shock (HS). The goal of this study was to use computational biology tools to investigate the effects of FFP+VPA on the brain transcriptome following TBI+HS. METHODS: Swine underwent TBI+HS, kept in shock for 2 h, and resuscitated with FFP or FFP + VPA (n = 5/group). After 6 h of observation, brain RNA was isolated and gene expression was analyzed using a microarray. iPathwayGuide, Gene Ontology (GO), Gene-Set Enrichment Analysis, and Enrichment Mapping were used to identify significantly impacted genes and transcriptomic networks. RESULTS: Eight hundred differentially expressed (DE) genes were identified out of a total of 9,118 genes. Upregulated genes were involved in promotion of cell division, proliferation, and survival, while downregulated genes were involved in autophagy, cell motility, neurodegenerative diseases, tumor suppression, and cell cycle arrest. Seven hundred ninety-one GO terms were significantly enriched. A few major transcription factors, such as TP53, NFKB3, and NEUROD1, were responsible for modulating hundreds of other DE genes. Network analysis revealed attenuation of interconnected genes involved in inflammation and tumor suppression, and an upregulation of those involved in cell proliferation and differentiation. CONCLUSION: Overall, these results suggest that VPA treatment creates an environment that favors production of new neurons, removal of damaged cells, and attenuation of inflammation, which could explain its previously observed neuroprotective effects.

Kinome Profiling Reveals Abnormal Activity of Kinases in Skeletal Muscle From Adults With Obesity and Insulin Resistance.

CONTEXT: Obesity-related insulin resistance (OIR) is one of the main contributors to type 2 diabetes and other metabolic diseases. Protein kinases are implicated in insulin signaling and glucose metabolism. Molecular mechanisms underlying OIR involving global kinase activities remain incompletely understood. OBJECTIVE: To investigate abnormal kinase activity associated with OIR in human skeletal muscle. DESIGN: Utilization of stable isotopic labeling-based quantitative proteomics combined with affinity-based active enzyme probes to profile in vivo kinase activity in skeletal muscle from lean control (Lean) and OIR participants. PARTICIPANTS: A total of 16 nondiabetic adults, 8 Lean and 8 with OIR, underwent hyperinsulinemic-euglycemic clamp with muscle biopsy. RESULTS: We identified the first active kinome, comprising 54 active protein kinases, in human skeletal muscle. The activities of 23 kinases were different in OIR muscle compared with Lean muscle (11 hyper- and 12 hypo-active), while their protein abundance was the same between the 2 groups. The activities of multiple kinases involved in adenosine monophosphate-activated protein kinase (AMPK) and p38 signaling were lower in OIR compared with Lean. On the contrary, multiple kinases in the c-Jun N-terminal kinase (JNK) signaling pathway exhibited higher activity in OIR vs Lean. The kinase-substrate-prediction based on experimental data further confirmed a potential downregulation of insulin signaling (eg, inhibited phosphorylation of insulin receptor substrate-1 and AKT1/2). CONCLUSIONS: These findings provide a global view of the kinome activity in OIR and Lean muscle, pinpoint novel specific impairment in kinase activities in signaling pathways important for skeletal muscle insulin resistance, and may provide potential drug targets (ie, abnormal kinase activities) to prevent and/or reverse skeletal muscle insulin resistance in humans.

Pilot deep RNA sequencing of worker blood samples from Singapore printing industry for occupational risk assessment.

Several engineered nanomaterials (ENMs) are used in toner-based printing equipment (TPE) including laser printers and photocopiers to improve toner performance. High concentration of airborne nanoparticles due to TPE emissions has been documented in copy centers and chamber studies. Recent animal inhalation studies by our group suggested exposure to laser printer-emitted nanoparticles (PEPs) increased cardiovascular risk by impairing ventricular performance and inducing hypertension and arrhythmia, consistent with global transcriptomic and metabolomic profiling results. There has been no genome-wide transcriptomic analysis of workers exposed to TPE emissions to systematically assess the occupational exposure health risks. In this pilot study, deep RNA sequencing of blood samples of workers in two printing companies in Singapore was performed. The genome-scale analysis of the blood samples from TPE exposed workers revealed perturbed transcriptional activities related to inflammatory and immune responses, metabolism, cardiovascular impairment, neurological diseases, oxidative stress, physical morphogenesis/deformation, and cancer, when compared with the control peers (office workers). Many of these disease risks associated with particle inhalation exposures in such work environments were consistent with the observation from the PEPs rat inhalation studies. In particular, the cell adhesion molecules (CAMs) was a top significantly perturbed pathway in blood samples from exposed workers compared with the office workers in both companies. The protein expression of sICAM was verified in plasma of exposed workers, showing a positive correlation with daily average nanoparticle concentration in indoor air measured in these two companies. Larger scale genomic and molecular epidemiology studies in copier operators are warranted in order to assess potential risks from such particulate matter exposures.

IDH1-R132H acts as a tumor suppressor in glioma via epigenetic up-regulation of the DNA damage response.

Patients with glioma whose tumors carry a mutation in isocitrate dehydrogenase 1 (IDH1R132H) are younger at diagnosis and live longer. IDH1 mutations co-occur with other molecular lesions, such as 1p/19q codeletion, inactivating mutations in the tumor suppressor protein 53 (TP53) gene, and loss-of-function mutations in alpha thalassemia/mental retardation syndrome X-linked gene (ATRX). All adult low-grade gliomas (LGGs) harboring ATRX loss also express the IDH1R132H mutation. The current molecular classification of LGGs is based, partly, on the distribution of these mutations. We developed a genetically engineered mouse model harboring IDH1R132H, TP53 and ATRX inactivating mutations, and activated NRAS G12V. Previously, we established that ATRX deficiency, in the context of wild-type IDH1, induces genomic instability, impairs nonhomologous end-joining DNA repair, and increases sensitivity to DNA-damaging therapies. In this study, using our mouse model and primary patient-derived glioma cultures with IDH1 mutations, we investigated the function of IDH1R132H in the context of TP53 and ATRX loss. We discovered that IDH1R132H expression in the genetic context of ATRX and TP53 gene inactivation (i) increases median survival in the absence of treatment, (ii) enhances DNA damage response (DDR) via epigenetic up-regulation of the ataxia-telangiectasia-mutated (ATM) signaling pathway, and (iii) elicits tumor radioresistance. Accordingly, pharmacological inhibition of ATM or checkpoint kinases 1 and 2, essential kinases in the DDR, restored the tumors' radiosensitivity. Translation of these findings to patients with IDH1132H glioma harboring TP53 and ATRX loss could improve the therapeutic efficacy of radiotherapy and, consequently, patient survival.

T Helper 1 Cellular Immunity Toward Recoverin Is Enhanced in Patients With Active Autoimmune Retinopathy.

Autoimmune retinopathy (AIR) causes rapidly progressive vision loss that is treatable but often is confused with other forms of retinal degeneration including retinitis pigmentosa (RP). Measurement of anti-retinal antibodies (ARA) by Western blot is a commonly used laboratory assay that supports the diagnosis yet does not reflect current disease activity. To search for better diagnostic indicators, this study was designed to compare immune biomarkers and responses toward the retinal protein, recoverin, between newly diagnosed AIR patients, slow progressing RP patients and healthy controls. All individuals had measurable anti-recoverin IgG and IgM antibodies by ELISA regardless of disease status or Western blot results. Many AIR patients had elevated anti-recoverin IgG1 levels and a strong cellular response toward recoverin dominated by IFNγ. RP patients and controls responded to recoverin with a lower IFNγ response that was balanced by IL-10 production. Both AIR and RP patients displayed lower levels of total peripheral blood mononuclear cells that were due to reductions of CD4+ TH cells. A comparison of messenger RNA (mRNA) for immune-related genes in whole blood of AIR patients versus RP patients or controls indicated lower expression of ATG5 and PTPN22 and higher expression of several genes involved in TH cell signaling/transcription and adhesion. These data indicate that an immune response toward recoverin is normal in humans, but that in AIR patients the balance shifts dramatically toward higher IFNγ production and cellular activation.

Dural Cells Release Factors Which Promote Cancer Cell Malignancy and Induce Immunosuppressive Markers in Bone Marrow Myeloid Cells.

BACKGROUND: Thirty per cent of cancer patients develop spine metastases with a substantial number leading to spinal cord compression and neurological deficits. Many demonstrate a propensity toward metastasis to the posterior third of the vertebral body. The dura, the outer layer of the meninges, lies in intimate contact with the posterior border of the vertebral body and has been shown to influence adjacent bone. The effects of the dura on bone marrow and cancer cells have not been examined. Understanding the biology of spinal metastasis will provide insights into mechanisms of cancer growth and allow for new treatment strategies. OBJECTIVE: To examine the extent to which dura influences bone marrow/tumor cell metastatic characteristics. METHODS: Dura conditioned media (DCM) from primary dura was examined for the ability to stimulate tumor cell proliferation/invasion and to alter bone marrow cell populations. RNA sequencing of dural fibroblasts was performed to examine expression of cytokines and growth factors. RESULTS: DCM induced a significant increase in invasion and proliferation of multiple tumor cell lines, and of patient-derived primary spinal metastatic cells. DCM also increased the proliferation of bone marrow myeloid cells, inducing expression of immunosuppressive markers. RNA sequencing of dural fibroblasts demonstrated abundant expression of cytokines and growth factors involved in cancer/immune pathways. CONCLUSION: Factors released by primary dural cells induce proliferation of tumor cells and alter bone marrow to create a fertile environment for tumor growth. The dura therefore may play an important role in the increased incidence of metastases to adjacent bone.

A novel approach for data integration and disease subtyping.

Advances in high-throughput technologies allow for measurements of many types of omics data, yet the meaningful integration of several different data types remains a significant challenge. Another important and difficult problem is the discovery of molecular disease subtypes characterized by relevant clinical differences, such as survival. Here we present a novel approach, called perturbation clustering for data integration and disease subtyping (PINS), which is able to address both challenges. The framework has been validated on thousands of cancer samples, using gene expression, DNA methylation, noncoding microRNA, and copy number variation data available from the Gene Expression Omnibus, the Broad Institute, The Cancer Genome Atlas (TCGA), and the European Genome-Phenome Archive. This simultaneous subtyping approach accurately identifies known cancer subtypes and novel subgroups of patients with significantly different survival profiles. The results were obtained from genome-scale molecular data without any other type of prior knowledge. The approach is sufficiently general to replace existing unsupervised clustering approaches outside the scope of bio-medical research, with the additional ability to integrate multiple types of data.

A novel pathway analysis approach based on the unexplained disregulation of genes.

A crucial step in the understanding of any phenotype is the correct identification of the signaling pathways that are significantly impacted in that phenotype. However, most current pathway analysis methods produce both false positives as well as false negatives in certain circumstances. We hypothesized that such incorrect results are due to the fact that the existing methods fail to distinguish between the primary dis-regulation of a given gene itself and the effects of signaling coming from upstream. Furthermore, a modern whole-genome experiment performed with a next-generation technology spends a great deal of effort to measure the entire set of 30,000-100,000 transcripts in the genome. This is followed by the selection of a few hundreds differentially expressed genes, step that literally discards more than 99% of the collected data. We also hypothesized that such a drastic filtering could discard many genes that play crucial roles in the phenotype. We propose a novel topology-based pathway analysis method that identifies significantly impacted pathways using the entire set of measurements, thus allowing the full use of the data provided by NGS techniques. The results obtained on 24 real data sets involving 12 different human diseases, as well as on 8 yeast knock-out data sets show that the proposed method yields significant improvements with respect to the state-of-the-art methods: SPIA, GSEA and GSA. AVAILABILITY: Primary dis-regulation analysis is implemented in R and included in ROntoTools Bioconductor package (versions ≥ 2.0.0). https://www.bioconductor.org/packages/release/bioc/html/ROntoTools.html.

DANUBE: Data-driven meta-ANalysis using UnBiased Empirical distributions-applied to biological pathway analysis.

Identifying the pathways and mechanisms that are significantly impacted in a given phenotype is challenging. Issues include patient heterogeneity and noise. Many experiments do not have a large enough sample size to achieve the statistical power necessary to identify significantly impacted pathways. Meta-analysis based on combining p-values from individual experiments has been used to improve power. However, all classical meta-analysis approaches work under the assumption that the p-values produced by experiment-level statistical tests follow a uniform distribution under the null hypothesis. Here we show that this assumption does not hold for three mainstream pathway analysis methods, and significant bias is likely to affect many, if not all such meta-analysis studies. We introduce DANUBE, a novel and unbiased approach to combine statistics computed from individual studies. Our framework uses control samples to construct empirical null distributions, from which empirical p-values of individual studies are calculated and combined using either a Central Limit Theorem approach or the additive method. We assess the performance of DANUBE using four different pathway analysis methods. DANUBE is compared with five meta-analysis approaches, as well as with a pathway analysis approach that employs multiple datasets (MetaPath). The 25 approaches have been tested on 16 different datasets related to two human diseases, Alzheimer's disease (7 datasets) and acute myeloid leukemia (9 datasets). We demonstrate that DANUBE overcomes bias in order to consistently identify relevant pathways. We also show how the framework improves results in more general cases, compared to classical meta-analysis performed with common experiment-level statistical tests such as Wilcoxon and t-test.

Overcoming the matched-sample bottleneck: an orthogonal approach to integrate omic data.

MicroRNAs (miRNAs) are small non-coding RNA molecules whose primary function is to regulate the expression of gene products via hybridization to mRNA transcripts, resulting in suppression of translation or mRNA degradation. Although miRNAs have been implicated in complex diseases, including cancer, their impact on distinct biological pathways and phenotypes is largely unknown. Current integration approaches require sample-matched miRNA/mRNA datasets, resulting in limited applicability in practice. Since these approaches cannot integrate heterogeneous information available across independent experiments, they neither account for bias inherent in individual studies, nor do they benefit from increased sample size. Here we present a novel framework able to integrate miRNA and mRNA data (vertical data integration) available in independent studies (horizontal meta-analysis) allowing for a comprehensive analysis of the given phenotypes. To demonstrate the utility of our method, we conducted a meta-analysis of pancreatic and colorectal cancer, using 1,471 samples from 15 mRNA and 14 miRNA expression datasets. Our two-dimensional data integration approach greatly increases the power of statistical analysis and correctly identifies pathways known to be implicated in the phenotypes. The proposed framework is sufficiently general to integrate other types of data obtained from high-throughput assays.

SPATIAL: A System-level PAThway Impact AnaLysis approach.

The goal of pathway analysis is to identify the pathways that are significantly impacted when a biological system is perturbed, e.g. by a disease or drug. Current methods treat pathways as independent entities. However, many signals are constantly sent from one pathway to another, essentially linking all pathways into a global, system-wide complex. In this work, we propose a set of three pathway analysis methods based on the impact analysis, that performs a system-level analysis by considering all signals between pathways, as well as their overlaps. Briefly, the global system is modeled in two ways: (i) considering the inter-pathway interaction exchange for each individual pathways, and (ii) combining all individual pathways to form a global, system-wide graph. The third analysis method is a hybrid of these two models. The new methods were compared with DAVID, GSEA, GSA, PathNet, Crosstalk and SPIA on 23 GEO data sets involving 19 tissues investigated in 12 conditions. The results show that both the ranking and the P-values of the target pathways are substantially improved when the analysis considers the system-wide dependencies and interactions between pathways.

Quantitative proteomics reveals novel protein interaction partners of PP2A catalytic subunit in pancreatic ß-cells.

Protein phosphatase 2A (PP2A) is one of the major serine/threonine phosphatases. We hypothesize that PP2A regulates signaling cascades in pancreatic ß-cells in the context of glucose-stimulated insulin secretion (GSIS). Using co-immunoprecipitation (co-IP) and tandem mass spectrometry, we globally identified the protein interaction partners of the PP2A catalytic subunit (PP2Ac) in insulin-secreting pancreatic ß-cells. Among the 514 identified PP2Ac interaction partners, 476 were novel. This represents the first global view of PP2Ac protein-protein interactions caused by hyperglycemic conditions. Additionally, numerous PP2Ac partners were found involved in a variety of signaling pathways in the ß-cell function, such as insulin secretion. Our data suggest that PP2A interacts with various signaling proteins necessary for physiological insulin secretion as well as signaling proteins known to regulate cell dysfunction and apoptosis in the pancreatic ß-cells.

A novel bi-level meta-analysis approach: applied to biological pathway analysis.

MOTIVATION: The accumulation of high-throughput data in public repositories creates a pressing need for integrative analysis of multiple datasets from independent experiments. However, study heterogeneity, study bias, outliers and the lack of power of available methods present real challenge in integrating genomic data. One practical drawback of many P-value-based meta-analysis methods, including Fisher's, Stouffer's, minP and maxP, is that they are sensitive to outliers. Another drawback is that, because they perform just one statistical test for each individual experiment, they may not fully exploit the potentially large number of samples within each study. RESULTS: We propose a novel bi-level meta-analysis approach that employs the additive method and the Central Limit Theorem within each individual experiment and also across multiple experiments. We prove that the bi-level framework is robust against bias, less sensitive to outliers than other methods, and more sensitive to small changes in signal. For comparative analysis, we demonstrate that the intra-experiment analysis has more power than the equivalent statistical test performed on a single large experiment. For pathway analysis, we compare the proposed framework versus classical meta-analysis approaches (Fisher's, Stouffer's and the additive method) as well as against a dedicated pathway meta-analysis package (MetaPath), using 1252 samples from 21 datasets related to three human diseases, acute myeloid leukemia (9 datasets), type II diabetes (5 datasets) and Alzheimer's disease (7 datasets). Our framework outperforms its competitors to correctly identify pathways relevant to the phenotypes. The framework is sufficiently general to be applied to any type of statistical meta-analysis. AVAILABILITY AND IMPLEMENTATION: The R scripts are available on demand from the authors. CONTACT: sorin@wayne.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.