Whole-genome Expression Profiling Research Articles

Differences of malignant proliferation and infiltrating growth related molecular changes in different pathological types of glioma

Objective To investigate the distribution of the cell cycle alteration and cell migration as well as infiltrating growth process and related genetic changes in each grade and each molecular subtype of gliomas. Methods A total of 300 glioma specimens(WHO grade Ⅱ-Ⅳ)in Chinese Glioma Genome Atlas(CGGA)were collected. Its tissue RNA and DNA were extract respectively. Sanger sequencing was used to detect the mutation status of PTEN, p53, and TERT promoter. The expression levels of MET and matrix metalloproteinase 9(MMP-9)were derived from whole-genome RNA microarray expression profile. The distribution differences of the mutations of PTEN, p53, TERT promoter and high expression of MET and MMP-9 were compared in each level and each molecular subtypes of glioma. Results (1)In WHO grade Ⅱ, Ⅲ and Ⅳ, the mutation frequencies of PTEN were 2.8%(2/72), 5.0%(1/20), and 23.0%(20/87), respectively; the mutation rates of p53 were 28.0%(21/75), 10.0%(2/20), and 20.7%(18/87), respectively; the mutation rates of TERT promoter were 30.2%(26/86), 47.1%(8/17), and 46.8%(29/62), respectively; the incidences of MET high expression were 28.9%(35/121), 33.3%(17/51), and 37.5%(48/128), respectively; and the high expression rates of MMP-9 were 3.3%(4/121), 39.2%(20/51), and 59.4%(76/128), respectively. There were significant differences in each grade of gliomas between the mutation rate of PTEN and the high expression rate of MMP-9(all P<0.01).(2)The mutation rates of PTEN in the proneural type, neural type, classical type and molecular type of mesenchymal glioma were 1.9%(1/52), 12.5%(4/32), 15.0%(3/20), and 20.0%(15/75), respectively; the mutation rates of p53 were 34.0%(18/53), 6.1%(2/33), 40.0%(8/20), and 17.1%(13/76), respectively; the mutation rates of TERT promoter were 37.5%(21/56), 34.5%(10/29), 31.3%(5/16), and 45.1%(23/51), respectively; the MET high expression rates were 25.6%(21/82), 34.5%(19/55), 28.9%(11/38), and 40.0%(38/95), respectively; the MMP-9 high expression rates were 9.8%(8/82), 1.8%(1/55), 44.7%(17/38), and 68.4%(65/95), respectively. There were significant differences in the mutation rates of PTEN and p53, and the MMP-9 high expression rates among each molecular subtype of glioma(all P<0.05). Conclusions The mutation rate of PTEN and the high expression rates of MMP-9 were associated with the malignant degree of gliomas. The differences of the mutation rates of PTEN and p53, and the high expression rates of MMP-9 in each molecular subtype of gliomas suggested that they could represent the molecular pathologic features of the specific molecular subtypes of gliomas. Key words: Glioma; Pathology; Molecular subtype; Malignant proliferation; Infiltrating growth

Filtered selection coupled with support vector machines generate a functionally relevant prediction model for colorectal cancer

PurposeThere has been considerable interest in using whole-genome expression profiles for the classification of colorectal cancer (CRC). The selection of important features is a crucial step before training a classifier.MethodsIn this study, we built a model that uses support vector machine (SVM) to classify cancer and normal samples using Affymetrix exon microarray data obtained from 90 samples of 48 patients diagnosed with CRC. From the 22,011 genes, we selected the 20, 30, 50, 100, 200, 300, and 500 genes most relevant to CRC using the minimum-redundancy–maximum-relevance (mRMR) technique. With these gene sets, an SVM model was designed using four different kernel types (linear, polynomial, radial basis function [RBF], and sigmoid).ResultsThe best model, which used 30 genes and RBF kernel, outperformed other combinations; it had an accuracy of 84% for both ten fold and leave-one-out cross validations in discriminating the cancer samples from the normal samples. With this 30 genes set from mRMR, six classifiers were trained using random forest (RF), Bayes net (BN), multilayer perceptron (MLP), naïve Bayes (NB), reduced error pruning tree (REPT), and SVM. Two hybrids, mRMR + SVM and mRMR + BN, were the best models when tested on other datasets, and they achieved a prediction accuracy of 95.27% and 91.99%, respectively, compared to other mRMR hybrid models (mRMR + RF, mRMR + NB, mRMR + REPT, and mRMR + MLP). Ingenuity pathway analysis was used to analyze the functions of the 30 genes selected for this model and their potential association with CRC: CDH3, CEACAM7, CLDN1, IL8, IL6R, MMP1, MMP7, and TGFB1 were predicted to be CRC biomarkers.ConclusionThis model could be used to further develop a diagnostic tool for predicting CRC based on gene expression data from patient samples.

Changes in interconnected pathways implicating microRNAs are associated with the activity of apocynin in attenuating myocardial fibrogenesis

Myocardial fibrosis is the endpoint pathology common to many cardiovascular disorders. We have previously shown that apocynin (APO), a naturally occurring NADPH oxidase inhibitor, significantly prevents the development of isoproterenol (ISO)-induced myocardial injury and fibrogenesis. The current study investigated the changes in microRNAs (miRNAs) and their potential implication in the cardioprotective effects of APO. Integrative analyses of whole-genome miRNA and gene expression profiles were first performed, revealing that altered expression of miRNAs likely contributed to dysregulated expression of genes associated with multiple interconnected fibrogenic signaling pathways. Importantly, APO treatment exhibited a broad impact on these signaling pathways, which could in part be mediated through miRNA-mediated gene expression regulation. The expression of differentially expressed miRNAs was further validated by real-time PCR analyses. Consistent with the data from miRNA array, compared to that from vehicle-treated normal controls, significantly decreased expression of miR-10b, miR-29c*, miR-30c-1*, miR-30e*, miR-148b, miR-181d, miR-218 and miR-3107* was observed in ISO-challenged vehicle-treated mouse hearts. In contrast, significantly increased expression of these miRNAs was observed in ISO-challenged APO-treated hearts compared to that from ISO-challenged vehicle-treated mice. Moreover, increased expression of miR-21 was observed as a result of ISO administration, which was significantly reduced by APO treatment. Altered protein levels of Col1, TIMP1, Rac2 and gp91phox were also validated. Lastly, APO treatment was shown to attenuate pre-established myocardial fibrosis induced by ISO. The results therefore demonstrated for the first time that complex changes in miRNA-mRNA interactome network are associated with the protective effects of APO against ISO-induced myocardial injury and fibrogenesis.

Shiga toxin-producing Escherichia coli strains isolated from dairy products — Genetic diversity and virulence gene profiles

Shiga toxin-producing Escherichia coli (STEC) are widely recognized as pathogens causing food borne disease. Here we evaluate the genetic diversity of 197 strains, mainly STEC, from serotypes O157:H7, O26:H11, O103:H2, O111:H8 and O145:28 and compared strains recovered in dairy products against strains from human, meat and environment cases. For this purpose, we characterized a set of reference-collection STEC isolates from dairy products by PFGE DNA fingerprinting and a subset of these by virulence-gene profiling. PFGE profiles of restricted STEC total DNA showed high genomic variability (0.9976 on Simpson's discriminatory index), enabling all dairy isolates to be differentiated. High-throughput real-time PCR screening of STEC virulence genes were applied on the O157:H7 and O26:H11 STEC isolates from dairy products and human cases. The virulence gene profiles of dairy and human STEC strains were similar. Nevertheless, frequency-wise, stx1 was more prevalent among dairy O26:H11 isolates than in human cases ones (87% vs. 44%) while stx2 was more prevalent among O26:H11 human isolates (23% vs. 81%). For O157:H7 isolates, stx1 (0% vs. 39%), nleF (40% vs 94%) and Z6065 (40% vs 100%) were more prevalent among human than dairy strains. Our data point to differences between human and dairy strains but these differences were not sufficient to associate PFGE and virulence gene profiles to a putative lower pathogenicity of dairy strains based on their lower incidence in disease. Further comparison of whole-genome expression and virulence gene profiles should be investigated in cheese and intestinal tract samples.

Unique patterns of CD8+ T-cell-mediated organ damage in the Act-mOVA/OT-I model of acute graft-versus-host disease.

T-cell receptor (TCR)-transgenic models of acute graft-versus-host disease (aGvHD) offer a straightforward and highly controlled approach to study the mechanisms and consequences of T-cell activation following allogeneic hematopoietic stem cell transplantation (aHSCT). Here, we report that aHSCT involving OT-I mice as donors, carrying an ovalbumin-specific CD8+ TCR, and Act-mOVA mice as recipients, expressing membrane-bound ovalbumin driven by the β-actin promoter, induces lethal aGvHD in a CD8+ T-cell-dependent, highly reproducible manner, within 4-7days. Tracking of UBC-GFP/OT-I graft CD8+ T cells disclosed heavy infiltration of the gastrointestinal tract, liver, and lungs at the onset of the disease, and histology confirmed hallmark features of gastrointestinal aGVHD, hepatic aGvHD, and aGvHD-associated lymphocytic bronchitis in infiltrated organs. However, T-cell infiltration was virtually absent in the skin, a key target organ of human aGvHD, and histology confirmed the absence of cutaneous aGVHD, as well. We show that the model allows studying CD8+ T-cell responses in situ, as selective recovery of graft CD45.1/OT-I CD8+ T cells from target organs is simple and feasible by automated tissue dissociation and subsequent cell sorting. Assessment of interferon-gamma production by flow cytometry, granzyme-B release by ELISA, TREC assay, and whole-genome gene expression profiling confirmed that isolated graft CD8+ T cells remained intact, underwent clonal expansion, and exerted effector functions in all affected tissues. Taken together, these data demonstrate that the OT-I/Act-mOVA model is suitable to study the CD8+ T-cell-mediated effector mechanisms in a disease closely resembling fatal human gastrointestinal and hepatic aGVHD that may develop after aHSCT using HLA-matched unrelated donors.

Comparative gene expression and phenotype analyses of skeletal muscle from aged wild-type and PAPP-A-deficient mice

Mice deficient in pregnancy-associated plasma protein-A (PAPP-A) have extended lifespan associated with decreased incidence and severity of degenerative diseases of age, such as cardiomyopathy and nephropathy. In this study, the effect of PAPP-A deficiency on aging skeletal muscle was investigated. Whole-genome expression profiling was performed on soleus muscles from 18-month-old wild-type (WT) and PAPP-A knock-out (KO) mice of the same sex and from the same litter (‘womb-mates’) to identify potential mechanisms of skeletal muscle aging and its retardation in PAPP-A deficiency. Top genes regulated in PAPP-A KO compared to WT muscle were associated with increased muscle function, increased metabolism, in particular lipid metabolism, and decreased stress. Fiber cross-sectional area was significantly increased in solei from PAPP-A KO mice. In vitro contractility experiments indicated increased specific force and decreased fatigue in solei from PAPP-A KO mice. Intrinsic mitochondrial oxidative capacity was significantly increased in skeletal muscle of aged PAPP-A KO compared to WT mice. Moreover, 18-month-old PAPP-A KO mice exhibited significantly enhanced endurance running on a treadmill. Thus, PAPP-A deficiency in mice is associated with indices of healthy skeletal muscle function with age.

Abstract A31: Genome-wide microRNA profiling analysis of breast cancer among African American and European American women

Abstract African American (AA) women are more likely than European American (EA) women to be diagnosed with aggressive, estrogen receptor (ER) negative breast cancer. Differences in microRNA (miRNA) expression patterns have not been well studied as potential mechanisms underlying this racial disparity. In this study, we performed a whole-genome miRNA expression profiling in 58 (29 AA and 29 EA) fresh-frozen breast tumors, with clinical characteristics (e.g., ER status, histological grade, stage) comparable between AA and EA samples, and in 10 (5 AA and 5 EA) normal breast tissues obtained from women undergoing reduction mammoplasty, with pathology determined free from any abnormalities. Unsupervised hierarchical clustering showed that miRNA expression patterns clearly distinguish breast cancer from normal breast tissue. In tumors, a number of miRNAs are significantly differentially expressed between tumor subtypes and are associated with other clinicopathological factors, such as tumor grade and lymph node status. We identified 64 differentially expressed (mean fold change&amp;gt;2 and FDR&amp;lt;0.05) miRNAs between ER negative and ER positive tumors. Interestingly, we observed that there were 13 miRNAs differentially expressed between ER negative and ER positive breast tumors regardless of race, 28 miRNAs differentially expressed only in EA tumors and 23 miRNAs were differentially expressed in AA samples only. Specifically, the top most differentially expressed miRNAs from EA women include: several members of miR-17-92 cluster (miR-17, miR-18a, miR-19a, miR-20a), miR-508, miR509, and miR514a that are up-regulated, and miR-1, miR-133a, miR133b and miR206, which are down-regulated, in ER negative compared to ER positive tumors. In AA women, however, up-regulated miRNAs include miR-105, miR-106b, miR-135b, miR-520b; down-regulated ones include miR-216a, miR217, miR342, miR375, and miR378a. Further, several of these miRNAs, such as miR-17, miR-18a, miR-133a, miR-206, have been shown to regulate various target genes involved in apoptosis, cell cycle, invasion, or angiogenesis. In summary, in this genome-wide miRNA expression profiling analysis by next generation sequencing, our results suggest that miRNA expression patterns may differ by tumor subtypes between AA and EA breast samples. These initial results will provide the basis for the functional analysis of the identified miRNAs, and findings could contribute to a better understanding of the biology of breast cancer disparities and more targeted preventative and therapeutic strategies. Citation Format: Zhihong Gong, Dan Wang, Allyson Espinal, Qiang Hu, Lara Sucheston-Campbell, Li Tang, Jo Freudenheim, Peter Shields, Carl Morrison, Steven Belinsky, Song Liu, Kitaw Demissie, Michael Higgins, Christine Ambrosone. Genome-wide microRNA profiling analysis of breast cancer among African American and European American women. [abstract]. In: Proceedings of the AACR Special Conference on Noncoding RNAs and Cancer: Mechanisms to Medicines ; 2015 Dec 4-7; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2016;76(6 Suppl):Abstract nr A31.

Chromosomal aneuploidies induced upon Lamin B2 depletion are mislocalized in the interphase nucleus

Chromosome territories assume non-random positions in the interphase nucleus with gene-rich chromosomes localized toward the nuclear interior and gene-poor chromosome territories toward the nuclear periphery. Lamins are intermediate filament proteins of the inner nuclear membrane required for the maintenance of nuclear structure and function. Here, we show using whole-genome expression profiling that Lamin A/C or Lamin B2 depletion in an otherwise diploid colorectal cancer cell line (DLD1) deregulates transcript levels from specific chromosomes. Further, three-dimensional fluorescence in situ hybridization (3D-FISH) analyses of a subset of these transcriptionally deregulated chromosome territories revealed that the diploid chromosome territories in Lamin-depleted cells largely maintain conserved positions in the interphase nucleus in a gene-density-dependent manner. In addition, chromosomal aneuploidies were induced in ~25 % of Lamin A/C or Lamin B2-depleted cells. Sub-populations of these aneuploid cells consistently showed a mislocalization of the gene-rich aneuploid chromosome 19 territory toward the nuclear periphery, while gene-poor aneuploid chromosome 18 territory was mislocalized toward the nuclear interior predominantly upon Lamin B2 than Lamin A/C depletion. In addition, a candidate gene locus ZNF570 (Chr.19q13.12) significantly overexpressed upon Lamin B2 depletion was remarkably repositioned away from the nuclear lamina. Taken together, our studies strongly implicate an overarching role for Lamin B2 in the maintenance of nuclear architecture since loss of Lamin B2 relieves the spatial positional constraints required for maintaining conserved localization of aneuploid chromosome territories in the interphase nucleus.

Gene expression inference with deep learning.

Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online.

Toxoplasma gondii Arginine Methyltransferase 1 (PRMT1) Is Necessary for Centrosome Dynamics during Tachyzoite Cell Division

ABSTRACTThe arginine methyltransferase family (PRMT) has been implicated in a variety of cellular processes, including signal transduction, epigenetic regulation, and DNA repair pathways. PRMT1 is thought to be responsible for the majority of PRMT activity in Toxoplasma gondii, but its exact function is unknown. To further define the biological function of the PRMT family, we generated T. gondii mutants lacking PRMT1 (Δprmt1) by deletion of the PRMT1 gene. Δprmt1 parasites exhibit morphological defects during cell division and grow slowly, and this phenotype reverses in the Δprmt::PRMT1mRFP complemented strain. Tagged PRMT1 localizes primarily in the cytoplasm with enrichment at the pericentriolar material, and the strain lacking PRMT1 is unable to segregate progeny accurately. Unlike wild-type and complemented parasites, Δprmt1 parasites have abnormal daughter buds, perturbed centrosome stoichiometry, and loss of synchronous replication. Whole-genome expression profiling demonstrated differences in expression of cell-cycle-regulated genes in the Δprmt1 strain relative to the complemented Δprmt1::PRMT1mRFP and parental wild-type strains, but these changes do not correlate with a specific block in cell cycle. Although PRMT1’s primary biological function was previously proposed to be methylation of histones, our studies suggest that PRMT1 plays an important role within the centrosome to ensure the proper replication of the parasite.

Abstract A78: Serum metabolomics, cytokine measurements, and tumor RNA-seq identified phospholipids correlated with a molecular subclass as strong predictor for outcome in high-grade serous ovarian cancer.

Abstract Background: Currently, the field of ‘omics’ is still growing, giving step by step deeper insight into the biological system of cancer. Increasing evidence suggests that alterations in cancer metabolism might have a tremendous impact on survival and could guide new treatment strategies. Therefore, including metabolic phenotyping in a study design would allow better understanding of the biological function and status of tumor cells and their hosts. Epithelial ovarian cancer (EOC) is very heterogeneous in both, local tumor spread and survival. Molecular subtypes presenting with distinct whole-genome expression profiles and significant survival differences have been described and awareness of the molecular alterations is required to identify new targets for therapy. In this study, serum metabolite changes were identified and evaluated as potential prognostic markers in a test set of 65 high grade serous EOC (HGSOC) patients. The prognostic impact was validated in an independent cohort of 165 EOC patients. Methods: Targeted metabolomics was performed on serum using the AbsoluteIDQ p180 kit (Biocrates Life Sciences), measuring 188 metabolites. In addition to a test and validation set of 65 HGSOC and 165 serous advanced stage EOC patients, the metabolomics profile of 62 healthy women was determined. In a subset of patients 16 cancer biomarkers and 40 chemokines were measured using Luminex bead-based assays and whole genome transcriptomes were assessed from different tumor tissues (primary, metastatic, and ascitic) by RNA sequencing. Results: 53 metabolites were significantly negatively correlated to overall survival (OS). Thereof, the majority (43) constituted glycerophospholipids (GPhL), followed by five acylcarnitines, four sphingolipids and one biogenic amine. A non-linear dimensionality reduction approach was used to reduce the information of the 43 GPhLs to three dimensions. The first showed the strongest impact on OS and revealed, as GPhL predictor, a significant impact on OS in uni- and multivariate (HR 0.38; p&amp;lt;0.001) Cox regression analyses, i.e. low GPhL concentrations in blood lead to worse OS. To determine the biologic background of these changes in the serum lipidome, correlations to cytokines and tumor markers were evaluated. IL6, CXCL2, osteopontin, and CCL23 were significantly negatively and leptin and sEGFR positively correlated to the GPhL-predictor. In a next step, RNA sequencing of different tumor tissues identified 393 genes negatively correlated (i.e. the carbohydrate-responsive element-binding protein, ChREPB) and 429 genes positively correlated (i.e. complete respiratory chain, many histones) with the GPhL-predictor. To provide more profound survival analysis, a validation was performed using expression data initially used for validation of a molecular subclassification with a tremendous impact on OS in 165 serous advanced stage EOC patients (Pils et al. Cancer Sci. 103:1334). Using the 50 most significantly up- and the 50 down-regulated genes a robust predictor was built. This gene predictor represents the GPhL-predictor and had a significant independent impact on OS (HR 0.66; p=0.004). In addition to this validation of the survival impact, a very strong correlation between the observed GPhL changes (via the gene predictor) and the molecular subclass was found, indicating a functional connection between these molecular subclasses and the serum lipidome. Conclusion: Targetd metabolomics revealed a strong independent impact of the serum concentrations of glycerophospholipids on HGSOC outcome in the test and a validation cohort. Transcriptomics data indicate changes in the energy metabolism of the tumor. Interestingly, the lipidome-changes were strongly correlated to a previously described molecular subclass in serous EOC. Citation Format: Stefanie Aust, Anna Bachmayr-Heyda, Katharina Auer, Nyamdelger Sukhbaatar, Samuel M. Meier, Christopher Gerner, Dietmar Pils. Serum metabolomics, cytokine measurements, and tumor RNA-seq identified phospholipids correlated with a molecular subclass as strong predictor for outcome in high-grade serous ovarian cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr A78.

Gene expression profiling of prostate tissue based on variable expression of 5-alpha reductase 2.

143 Background: Androgen signaling plays a central role in the pathophysiology of both benign and malignant prostatic disease. We previously showed that some men carry epigenetic modifications of the 5-alpha reductase (AR) promoter that modulate gene expression, raising the hypothesis that there may be molecular heterogeneity underlying the variability in clinical response to 5-AR inhibitors for management of benign and malignant prostatic diseases. In this study, we performed whole-genome expression profiling of prostatic tissue based on variable expression of 5-AR2 to determine whether molecular subtypes of clinical relevance could be identified. Methods: Prostatic tissue specimens were obtained from 22 patients with symptomatic BPH undergoing prostate debulking surgery. 5-AR2 protein expression was measured by immunohistochemistry, and 5-AR2 promoter methylation determined by PCR. RNA was extracted from each specimen and whole-genome expression profiling was performed using Illumina Human BeadChip Arrays. Gene expression data was analyzed by unsupervised hierarchical clustering and Gene Set Enrichment Analysis. Results: Unsupervised hierarchical clustering identified two subtypes of patients with distinct gene expression signatures. Among the most differentially expressed genes were several notable androgen-regulated genes, including TMPRSS2, NKX3-1, AZGP1, KLK3 (encoding the PSA protein) and multiple other members of the kallikrein family of serine proteases (all P&lt; 0.001, FDR &lt; 0.02). Multiple gene sets composed of androgen-regulated genes and androgen receptor target genes were found to be significantly enriched in one of the two subtypes. Interestingly, patients from this Androgen-Up subtype were also noted to have a higher frequency of 5-AR2 promoter methylation (though not statistically significant). Conclusions: Our findings suggest that there are distinct molecular subtypes among prostatic tissues with variable expression of 5-AR2, driven by differences in androgen gene regulation. These differences may partially explain the variable response to 5-AR inhibitors and thereby inform clinical strategies for devising therapies for benign and malignant prostatic disease.

Altered expression of mRNA profiles in blood of early-onset schizophrenia.

To identify gene expression abnormalities in schizophrenia (SZ), we generated whole-genome gene expression profiles using microarrays on peripheral blood mononuclear cells (PBMCs) from 18 early-onset SZ cases and 12 controls. We detected 84 transcripts differentially expressed by diagnostic status, with 82 genes being upregulated and 2 downregulated. We identified two SZ associated gene coexpression modules (green and red), including 446 genes . The green module is positively correlated with SZ, encompassing predominantly up-regulated genes in SZ; while the red module was negatively correlated with disease status, involving mostly nominally down-regulated genes in SZ. The olfactory transduction pathway was the most enriched pathways for the genes within the two modules. The expression levels of several hub genes, including AKT1, BRCA1, CCDC134, UBD, and ZIC2 were validated using real-time quantitative PCR. Our findings indicate that mRNA coexpression abnormalities may serve as a promising mechanism underlying the development of SZ.

Rapid Identification of Potential Drugs for Diabetic Nephropathy Using Whole-Genome Expression Profiles of Glomeruli.

Objective. To investigate potential drugs for diabetic nephropathy (DN) using whole-genome expression profiles and the Connectivity Map (CMAP). Methodology. Eighteen Chinese Han DN patients and six normal controls were included in this study. Whole-genome expression profiles of microdissected glomeruli were measured using the Affymetrix human U133 plus 2.0 chip. Differentially expressed genes (DEGs) between late stage and early stage DN samples and the CMAP database were used to identify potential drugs for DN using bioinformatics methods. Results. (1) A total of 1065 DEGs (FDR < 0.05 and fold change > 1.5) were found in late stage DN patients compared with early stage DN patients. (2) Piperlongumine, 15d-PGJ2 (15-delta prostaglandin J2), vorinostat, and trichostatin A were predicted to be the most promising potential drugs for DN, acting as NF-κB inhibitors, histone deacetylase inhibitors (HDACIs), PI3K pathway inhibitors, or PPARγ agonists, respectively. Conclusion. Using whole-genome expression profiles and the CMAP database, we rapidly predicted potential DN drugs, and therapeutic potential was confirmed by previously published studies. Animal experiments and clinical trials are needed to confirm both the safety and efficacy of these drugs in the treatment of DN.

Metabolomic and Gene Expression Profiles Exhibit Modular Genetic and Dietary Structure Linking Metabolic Syndrome Phenotypes in Drosophila.

Genetic and environmental factors influence complex disease in humans, such as metabolic syndrome, and Drosophila melanogaster serves as an excellent model in which to test these factors experimentally. Here we explore the modularity of endophenotypes with an in-depth reanalysis of a previous study by Reed et al. (2014), where we raised 20 wild-type genetic lines of Drosophila larvae on four diets and measured gross phenotypes of body weight, total sugar, and total triglycerides, as well as the endophenotypes of metabolomic and whole-genome expression profiles. We then perform new gene expression experiments to test for conservation of phenotype-expression correlations across different diets and populations. We find that transcript levels correlated with gross phenotypes were enriched for puparial adhesion, metamorphosis, and central energy metabolism functions. The specific metabolites L-DOPA and N-arachidonoyl dopamine make physiological links between the gross phenotypes across diets, whereas leucine and isoleucine thus exhibit genotype-by-diet interactions. Between diets, we find low conservation of the endophenotypes that correlate with the gross phenotypes. Through the follow-up expression study, we found that transcript-trait correlations are well conserved across populations raised on a familiar diet, but on a novel diet, the transcript-trait correlations are no longer conserved. Thus, physiological canalization of metabolic phenotypes breaks down in a novel environment exposing cryptic variation. We cannot predict the physiological basis of disease in a perturbing environment from profiles observed in the ancestral environment. This study demonstrates that variation for disease traits within a population is acquired through a multitude of physiological mechanisms, some of which transcend genetic and environmental influences, and others that are specific to an individual’s genetic and environmental context.

Abstract B1: Gene expression and TP53 mutation analysis predict sensitivity of leukemia cells to MDM2 inhibition by DS-3032b

Abstract Background: MDM2 overexpression, by preventing p53 activation, contributes to the growth and development of a variety of solid tumors and hematologic malignancies; hence, MDM2 inhibition could be a promising novel therapeutic strategy. Several MDM2 inhibitors have shown promise in early clinical trials. While preclinical studies generally reveal a requirement of wild-type (wt) TP53 for activity, tumor response to MDM2 inhibitors varies widely in the clinic and may not be strictly linked to TP53 mutational status. Identification of predictive biomarkers is therefore needed to enrich for patients with high likelihood of response. We here propose two gene signature-based models to predict the sensitivity of AML cells to MDM2 inhibition using two different methods. Methods: Leukemia samples isolated from peripheral blood or bone marrow of patients with newly diagnosed or relapsed/refractory AML were treated using DS-3032b (Daiichi-Sankyo), a dispiropyrrolidine-based, highly potent MDM2 inhibitor currently undergoing clinical trials in solid and hematological malignancies. Forty-one primary AML samples were treated ex vivo for 48 hours with DS-3032b (0, 25, 50, 100, 250, 500, and 1000 nM), and live cell numbers were determined. To define drug sensitivity/resistance, area under the curve (AUC) values, based on%live cell number measured at each concentration, were calculated. Baseline whole-genome RNA expression profile (Affymetrix Human Genome U133 Plus 2.0 Array) and TP53 mutation status (next generation sequencing) were determined. In the first model, we validated a predictive 175-gene signature that was established in a wide range of cancer cells by Daiichi Sankyo. In the second model, we used the random forest method with cross validation to establish a new predictive gene signature. Results: Eight samples (20%) had TP53 mutations. 6/8 (75%) p53 mutant and 8/33 (24%) of p53 wt samples were resistant (p = 0.01). In the first model, 11 each p53 wt samples were selected as sensitive or resistant to DS-3032 based on AUC values, and the 175-gene signature was applied. The prediction accuracy was 72%. In the genotype mixed samples, 14 each sensitive and resistant samples were selected, and the prediction accuracy was 79%. In the second model, we focused on 33 p53 wt samples and trichotomize the samples in the same way as in the first model, and investigated the accuracy of gene expression-derived prediction model with (A) 1500 gene set with the highest variance in mRNA expression (unbiased approach), (B) 32 gene set derived from previous studies (referenced approach), (C) combined (A+B) gene set. The sensitivities to predict cases with high drug sensitivity were 72%, 73% and 82% in scenarios (A), (B) and (C), respectively. The analysis was then extended to all 41 samples and the sensitivity to predict cases with high drug sensitivity remained high (64%, 64% and 72%). The results indicate that an unbiased approach can create a prediction model as accurate as the referenced approach, and moreover, that the combining approach can provide the highest prediction of sensitivity to the MDM2 inhibitor. Conclusion: The two models reported here could provide a novel strategy to identify the optimal gene signatures for predicting the cases most sensitive to MDM2 inhibitors prior to therapy. These models will be tested in an ongoing AML phase 1 clinical study of DS-3032b. Citation Format: Jo Ishizawa, Kenji Nakamaru, Takahiko Seki, Koichi Tazaki, Kensuke Kojima, Dhruv Chachad, Archie Tse, Arvind Rao, Michael Andreeff. Gene expression and TP53 mutation analysis predict sensitivity of leukemia cells to MDM2 inhibition by DS-3032b. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr B1.

Gene Expression Signatures Predictive of Bevacizumab/Erlotinib Therapeutic Benefit in Advanced Nonsquamous Non-Small Cell Lung Cancer Patients (SAKK 19/05 trial).

We aimed to identify gene expression signatures associated with angiogenesis and hypoxia pathways with predictive value for treatment response to bevacizumab/erlotinib (BE) of nonsquamous advanced non-small cell lung cancer (NSCLC) patients. Whole-genome gene expression profiling was performed on 42 biopsy samples (from SAKK 19/05 trial) using Affymetrix exon arrays, and associations with the following endpoints: time-to-progression (TTP) under therapy, tumor-shrinkage (TS), and overall survival (OS) were investigated. Next, we performed gene set enrichment analyses using genes associated with the angiogenic process and hypoxia response to evaluate their predictive value for patients' outcome. Our analysis revealed that both the angiogenic and hypoxia response signatures were enriched within the genes predictive of BE response, TS, and OS. Higher gene expression levels (GEL) of the 10-gene angiogenesis-associated signature and lower levels of the 10-gene hypoxia response signature predicted improved TTP under BE, 7.1 months versus 2.1 months for low versus high-risk patients (P = 0.005), and median TTP 6.9 months versus 2.9 months (P = 0.016), respectively. The hypoxia response signature associated with higher TS at 12 weeks and improved OS (17.8 months vs. 9.9 months for low vs. high-risk patients, P = 0.001). We were able to identify gene expression signatures derived from the angiogenesis and hypoxia response pathways with predictive value for clinical outcome in advanced nonsquamous NSCLC patients. This could lead to the identification of clinically relevant biomarkers, which will allow for selecting the subset of patients who benefit from the treatment and predict drug response.

Haptoglobin promoter polymorphism rs5472 as a prognostic biomarker for peptide vaccine efficacy in castration-resistant prostate cancer patients.

Personalized peptide vaccination (PPV) is an attractive approach to cancer immunotherapy with strong immune-boosting effects conferring significant clinical benefit. However, as with most therapeutic agents, there is a difference in clinical efficacy among patients receiving PPV. Therefore, a useful biomarker is urgently needed for prognosticating clinical outcomes to preselect patients who would benefit the most from PPV. In this retrospective study, to detect a molecular prognosticator of clinical outcomes for PPV, we analyzed whole-genome gene expression profiles of peripheral blood mononuclear cells (PBMCs) in castration-resistant prostate cancer (CRPC) patients before administration of PPV. Cox regression analysis revealed that mRNA expression of myeloperoxidase, haptoglobin, and neutrophil elastase was significantly associated with overall survival (OS) among vaccinated CRPC patients (adjusted P < 0.01). By promoter sequence analysis of these three genes, we found that rs5472 of haptoglobin (HP), an acute-phase plasma glycoprotein, was strongly correlated to OS of vaccinated CRPC patients (P = 0.0047, hazard ratio 0.47; 95 % confidence interval 0.28-0.80). Furthermore, both HP mRNA expression in PBMCs and protein level in plasma of CRPC patients before administration of PPV exhibited rs5472 dependence (P < 0.001 for mRNA expression and P < 0.05 for protein level). Our findings suggest that rs5472 may play an important role in the immune response to PPV via regulation of HP. Thus, we concluded that rs5472 is a potential prognostic biomarker for PPV.

Genome Expression Profiling-Based Identification and Administration Efficacy of Host-Directed Antimicrobial Drugs against Respiratory Infection by Nontypeable Haemophilus influenzae.

Therapies that are safe, effective, and not vulnerable to developing resistance are highly desirable to counteract bacterial infections. Host-directed therapeutics is an antimicrobial approach alternative to conventional antibiotics based on perturbing host pathways subverted by pathogens during their life cycle by using host-directed drugs. In this study, we identified and evaluated the efficacy of a panel of host-directed drugs against respiratory infection by nontypeable Haemophilus influenzae (NTHi). NTHi is an opportunistic pathogen that is an important cause of exacerbation of chronic obstructive pulmonary disease (COPD). We screened for host genes differentially expressed upon infection by the clinical isolate NTHi375 by analyzing cell whole-genome expression profiling and identified a repertoire of host target candidates that were pharmacologically modulated. Based on the proposed relationship between NTHi intracellular location and persistence, we hypothesized that drugs perturbing host pathways used by NTHi to enter epithelial cells could have antimicrobial potential against NTHi infection. Interfering drugs were tested for their effects on bacterial and cellular viability, on NTHi-epithelial cell interplay, and on mouse pulmonary infection. Glucocorticoids and statins lacked in vitro and/or in vivo efficacy. Conversely, the sirtuin-1 activator resveratrol showed a bactericidal effect against NTHi, and the PDE4 inhibitor rolipram showed therapeutic efficacy by lowering NTHi375 counts intracellularly and in the lungs of infected mice. PDE4 inhibition is currently prescribed in COPD, and resveratrol is an attractive geroprotector for COPD treatment. Together, these results expand our knowledge of NTHi-triggered host subversion and frame the antimicrobial potential of rolipram and resveratrol against NTHi respiratory infection.

Igf1 and Pacap rescue cerebellar granule neurons from apoptosis via a common transcriptional program

A shift of the delicate balance between apoptosis and survival-inducing signals determines the fate of neurons during the development of the central nervous system and its homeostasis throughout adulthood. Both pathways, promoting or protecting from apoptosis, trigger a transcriptional program. We conducted whole-genome expression profiling to decipher the transcriptional regulatory elements controlling the apoptotic/survival switch in cerebellar granule neurons following the induction of apoptosis by serum and potassium deprivation or their rescue by either insulin-like growth factor-1 (Igf1) or pituitary adenylyl cyclase-activating polypeptide (Pacap). Although depending on different upstream signaling pathways, the survival effects of Igf1 and Pacap converged into common transcriptional cascades, thus suggesting the existence of a general transcriptional program underlying neuronal survival.