Affymetrix Platform Research Articles

Dysregulation of gene expression in the striatum of BACHD rats expressing full-length mutant huntingtin and associated abnormalities on molecular and protein levels

Huntington disease (HD) is an autosomal dominantly inherited neurodegenerative disorder caused by a CAG repeat expansion in the gene coding for the huntingtin protein (HTT). Mutant HTT (mHTT) has been proposed to cause neuronal dysfunction and neuronal loss through multiple mechanisms. Transcriptional changes may be a core pathogenic feature of HD. Utilizing the Affymetrix platform we performed a genome-wide RNA expression analysis in two BACHD transgenic rat lines (TG5 and TG9) at 12 months of age, both of which carry full-length human mHTT but with different expression levels. By defining the threshold of significance at p < 0.01, we found 1608 genes and 871 genes differentially expressed in both TG5 and TG9 rats when compared to the wild type littermates, respectively. We only chose the highly up-/down-regulated genes for further analysis by setting an additional threshold of 1.5 fold change. Comparing gene expression profiles of human HD brains and BACHD rats revealed a high concordance in both functional and IPA (Ingenuity Pathway Analysis) canonical pathways relevant to HD. In addition, we investigated the causes leading to gene expression changes at molecular and protein levels in BACHD rats including the involvement of polyQ-containing transcription factors TATA box-binding protein (TBP), Sp1 and CBP as well as the chromatin structure. We demonstrate that the BACHD rat model recapitulates the gene expression changes of the human disease supporting its role as a preclinical research animal model. We also show for the first time that TFIID complex formation is reduced, while soluble TBP is increased in an HD model. This finding suggests that mHTT is a competitor instead of a recruiter of polyQ-containing transcription factors in the transcription process in HD.

Using miRNA-Analyzer for the Analysis of miRNA Data.

MicroRNAs (miRNAs) are small biological molecules that play an important role during the mechanisms of protein formation. Recent findings have demonstrated that they act as both positive and negative regulators of protein formation. Thus, the investigation of miRNAs, i.e., the determination of their level of expression, has developed a huge interest in the scientific community. One of the leading technologies for extracting miRNA data from biological samples is the miRNA Affymetrix platform. It provides the quantification of the level of expression of the miRNA in a sample, thus enabling the accumulation of data and allowing the determination of relationships among miRNA, genes, and diseases. Unfortunately, there is a lack of a comprehensive platform able to provide all the functions needed for the extraction of information from miRNA data. We here present miRNA-Analyzer, a complete software tool providing primary functionalities for miRNA data analysis. The current version of miRNA-Analyzer wraps the Affymetrix QCTool for the preprocessing of binary data files, and then provides feature selection (the filtering by species and by the associated p-value of preprocessed files). Finally, preprocessed and filtered data are analyzed by the Multiple Experiment Viewer (T-MEV) and Short Time Series Expression Miner (STEM) tools, which are also wrapped into miRNA-Analyzer, thus providing a unique environment for miRNA data analysis. The tool offers a plug-in interface so it is easily extensible by adding other algorithms as plug-ins. Users may download the tool freely for academic use at https://sites.google.com/site/mirnaanalyserproject/d.

Molecular Subgroups of Peripheral T-Cell Lymphoma Evolve By Distinct Genetic Pathways

Peripheral T-cell lymphoma (PTCL) is a group of clinically and pathologically heterogeneous non-Hodgkin lymphomas (NHL). Using gene expression profiling (GEP), we have defined molecular classifiers for PTCL subtypes reflecting their pathobiology and oncogenic pathways (Iqbal et al. 2014). We have also shown associations of specific mutations with the molecular subgroups (Wang et al. 2015). Although genomic information is increasing, the pathogenetic mechanisms of PTCLs remain largely unknown. Therefore, we analyzed copy number variation (CNV) and GEP to identify unique genetic abnormalities in the defined PTCL molecular subgroups.CNV data were generated on fresh frozen or formalin-fixed paraffin-embedded genomic DNA (n=114) on 3 Affymetrix platforms (SNP 6.0, 250K SNP, and OncoScan). Two published cohorts (PTCL-NOS, Hartmann et al. 2010; ALCL, Boi et al. 2013) were included for validation. The gene expression analysis, morphological review and clinical characteristics of these cases have been included in previous studies (Iqbal et al. 2010, 2014).Angioimmunoblastic T-cell lymphoma (AITL) represents 20% of all PTCL cases. The most recurrent CNV in AITL was chromosome (chr) 5 gain (39%), followed by chr 21 gain (21%). Interestingly, chr 21 gain co-occurred with chr 5 gain (p=0.003). No recurrent losses (≥20%) were identified among these cases. Molecularly re-classified AITL cases from morphologically classified PTCL-NOS cases showed concordant results with bonafide AITL cases. Of the commonly mutated genes, DNMT3A, IDH2, RHOA and TET2, only IDH2R172Kshowed a significant association (p=0.012) with chr 5 gain. GEP showed enrichment of gene signatures associated with oxidative phosphorylation (PGC-1α target genes) in cases with chr 5 gain.PTCL, not otherwise specified (PTCL-NOS) is the most common PTCL subtype and cannot be further sub-classified using conventional approaches; however, we have identified 2 molecular subgroups within PTCL-NOS, the GATA3 and TBX21 subgroups which are related to 2 distinct T-helper subsets (Iqbal et al. 2014), by employing GEP. Consistent with earlier observations (Hartmann et al. 2010), PTCL-NOS showed remarkably varied CNVs with nearly 50% of cases showing high CNV frequencies. When correlated with molecular subgroups, distinctive CNVs were observed in the molecular GATA3 and TBX21 subgroups. The GATA3 subgroup displayed a large assortment of CNVs. Complete or partial gain of chr 7 (57%) was the most recurrent gain in these cases. Losses affecting 17p, 10q and 9p21, encompassing tumor suppressors such as TP53 (57%), PTEN (43%) and CDKN2A (43%), were frequent in the GATA3 subgroup. The TBX21 subgroup had significantly fewer CNVs, as none were recurring (≥20%); but gains of 5p or 11p were observed in 14%. Additionally, PTCL-NOS cases with ≥10% abnormal genome had significantly poorer overall survival (p=0.012) compared to those with fewer abnormalities. This finding validates the GEP molecularly defined subgroups, as the GATA3 subgroup displayed more CNVs and has been associated with a worse prognosis compared to the TBX21 subgroup (Iqbal et al. 2014).We were able to distinguish CNVs characteristic of the different entities, including the co-occurrence of chr 5 and 21 gains specific in AITL. Gain of 1q (complete or partial) was identified in the GATA3 subgroup of PTCL-NOS and anaplastic lymphoma kinase (ALK) (-) ALCL with equal frequencies (~ 36%), but only 16% in ALK(+) ALCL. Complete or partial gain of chr 7 was also observed in ALCL, but at a considerably lower frequency than in the GATA3 subgroup. Additionally, gain of chr 18 or regions of 17q, and loss of 5q or regions on both arms of chr 9, were more frequent in the GATA3 subgroup compared to other entities. The TBX21 subgroup was primarily differentiated from the GATA3 subgroup by presence of fewer CNVs.Our analysis provides a framework for future investigations into the molecular pathogenesis of PTCL, and highlights potential candidate oncogenes and tumor suppressors deregulated by copy number aberrations. Comparative analysis revealed that certain chromosomal abnormalities are entity-specific. AITL cases with IDH2R172K also had trisomy 5 suggesting that these oncogenic events cooperate in malignant transformation. Thus, the complexity of PTCL is finally becoming clearer with the integration of high resolution molecular techniques for global genomic analysis. DisclosuresNo relevant conflicts of interest to declare.

Identifying Ultra-High Risk Myeloma By Integrated Molecular Genetic and Gene Expression Profiling

Introduction A significant proportion of myeloma patients relapse early and show short survival with current therapies. Molecular diagnostic tools are needed to identify these high risk patients at diagnosis to stratify treatment and offer the prospect of improving outcomes. Two validated molecular approaches for risk prediction are widely used: 1) molecular genetic risk profiling [e.g. del(17p), t(4;14)] 2) gene expression (GEP) risk profiling, [e.g. EMC92 (Kuiper et al., Leukemia 2012)]. We profiled patients from a large multicentric UK National trial using both approaches for integrated risk stratification. Methods A representative group of 221 newly diagnosed, transplant eligible patients (median age 64 years) treated on the UK NCRI Myeloma XI trial were molecularly profiled. DNA and RNA were extracted from immunomagnetically CD138-sorted bone marrow plasma cells. Molecular genetic profiles, including t(4;14), t(14;16), Del(17p), Gain(1q) were generated using MLPA (MRC Holland) and a TC-classification based qRT-PCR assay (Boyle EM, et al., Gen Chrom Canc 2015, Kaiser MF, et al., Leukemia 2013). GEP risk status as per EMC92 was profiled on a diagnostic Affymetrix platform using the U133plus2.0-based, CE-marked MMprofiler (SkylineDx) which generates a standardised EMC92 risk score, called 9SKY929. Progression-free (PFS) and overall survival (OS) were measured from initial randomization and median follow-up for the analysed group was 36 months. Statistical analyses were performed using R 3.3.0 and the 9survival9 package. Results were confirmed in an independent dataset, MRC Myeloma IX, for which median follow-up was 82.7 months. Results Of the 221 analysed patients, 116 were found to carry an established genetic high risk lesion [t(4;14), t(14;16), del(17p) or gain(1q)]. We and others have recently demonstrated that adverse lesions have an additive effect and that co-occurrence of ≥2 high risk lesions is specifically associated with adverse outcome (Boyd KD et al, Leukemia 2011). 39/221 patients (17.6%) were identified as genetic high risk with ≥2 risk lesions (termed HR2). By GEP, 53/221 patients (24.0%) were identified as SKY92 high risk. Genetic and GEP high risk co-occurred in 22 patients (10.0%), 31 patients (14.0%) were high risk only by GEP and 17 patients (7.7%) by genetics only. SKY92 high risk status was associated with significantly shorter PFS (median 17.1 vs. 34.3 months; P Importantly, by multivariate analysis GEP and genetic high risk status were independently associated with shorter PFS (P We next investigated interactions between genetic and gene expression high risk status. Three groups were defined: 1) Patients with both SKY92 and genetic (HR2) high risk status (n=22), 2) either GEP or genetic high risk (n=48) or 3) absence of GEP or genetic (HR2) high risk status (n=151). Co-occurring GEP and genetic high risk status was associated with very short PFS (median 12.5 vs. 20.0 vs. 38.3 months; P We confirmed this finding in 116 transplant-eligible patients from the MRC Myeloma IX trial. Patients carrying both EMC92 and genetic high risk status had a median PFS of 7.8 vs. 25.5 months and median OS of 9.5 vs. 62.1 months (both P Conclusion We demonstrate, for the first time, that combined genetic and gene expression risk profiling identifies a group of patients with ultra-high risk disease behaviour with high fidelity, using molecular features of the disease. Our results indicate that GEP and genetic high risk profiling identify independently relevant, but inter-related features of high risk disease biology. Integrated genetic and gene expression risk profiling could serve as a valuable tool for risk stratified, innovative treatment approaches in myeloma. Disclosures Jones: Celgene: Honoraria, Research Funding. Pawlyn: Takeda Oncology: Consultancy; Celgene: Consultancy, Honoraria, Other: Travel Support. Jenner: Amgen: Consultancy, Honoraria, Other: Travel support; Janssen: Consultancy, Honoraria, Other: Travel support, Research Funding; Novartis: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Other: Travel support; Celgene: Consultancy, Honoraria, Research Funding. Cook: Glycomimetics: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Drayson: Abingdon Health: Equity Ownership, Membership on an entity9s Board of Directors or advisory committees. Davies: Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Morgan: Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Univ of AR for Medical Sciences: Employment; Bristol Meyers: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Jackson: Celgene: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau; MSD: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau; Roche: Consultancy, Honoraria, Speakers Bureau. Kaiser: Takeda: Consultancy, Other: Travel Support; Amgen: Consultancy, Honoraria; BMS: Consultancy, Other: Travel Support; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Chugai: Consultancy.

Carbon nanotubes as carriers of Panax ginseng metabolites and enhancers of ginsenosides Rb1 and Rg1 anti-cancer activity

A major benefit to nanomaterial based-medicine is the ability to provide nanosized vehicles for sporadic metabolites. Here, we describe how the conjugation of valuable ginseng secondary metabolites (ginsenoside Rb1 or Rg1) with carbon nanotubes (CNT) can enhance their anti-proliferative and anti-cancer effects. Ginsenoside-CNT conjugate (Rb-CNT or Rg-CNT) permitted the ginsenosides to be used at a low dose, yet achieve a higher incidence of cancer killing. We were able to demonstrate that the ginsenoside-CNT conjugate can decrease cell viability up to 62% in breast cancer cells (MCF-7) and enhance antiproliferation of drug-resistant pancreatic cancer cells (PANC-1) by 61%. The interaction of the ginsenoside-CNT conjugate with breast cancer cells was studied using Raman Spectroscopy mapping. Total transcriptome profiling (Affymetrix platform) of MCF-7 cells treated with the ginsenoside-CNT conjugate shows that a number of cellular, apoptotic and response to stimulus processes were affected. Therefore, our data confirmed the potential use of CNT as a drug delivery system.

Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined-samples mega-analysis.

Blood-based microarray studies comparing individuals affected with autism spectrum disorder (ASD) and typically developing individuals help characterize differences in circulating immune cell functions and offer potential biomarker signal. We sought to combine the subject-level data from previously published studies by mega-analysis to increase the statistical power. We identified studies that compared ex vivo blood or lymphocytes from ASD-affected individuals and unrelated comparison subjects using Affymetrix or Illumina array platforms. Raw microarray data and clinical meta-data were obtained from seven studies, totaling 626 affected and 447 comparison subjects. Microarray data were processed using uniform methods. Covariate-controlled mixed-effect linear models were used to identify gene transcripts and co-expression network modules that were significantly associated with diagnostic status. Permutation-based gene-set analysis was used to identify functionally related sets of genes that were over- and under-expressed among ASD samples. Our results were consistent with diminished interferon-, EGF-, PDGF-, PI3K-AKT-mTOR-, and RAS-MAPK-signaling cascades, and increased ribosomal translation and NK-cell related activity in ASD. We explored evidence for sex-differences in the ASD-related transcriptomic signature. We also demonstrated that machine-learning classifiers using blood transcriptome data perform with moderate accuracy when data are combined across studies. Comparing our results with those from blood-based studies of protein biomarkers (e.g., cytokines and trophic factors), we propose that ASD may feature decoupling between certain circulating signaling proteins (higher in ASD samples) and the transcriptional cascades which they typically elicit within circulating immune cells (lower in ASD samples). These findings provide insight into ASD-related transcriptional differences in circulating immune cells. © 2016 Wiley Periodicals, Inc.

Global Transcriptome Abnormalities of the Eutopic Endometrium From Women With Adenomyosis.

Adenomyosis is a clinical disorder defined by the presence of endometrial glands and stroma within the myometrium, the pathogenesis of which is poorly understood. We postulate that dysregulation of genes and pathways in eutopic endometrium may predispose to ectopic implantation. No study, to our knowledge, has examined the global transcriptome of isolated eutopic endometrium from women with clinically significant adenomyosis. Laboratory-based study with full institutional review board approval and consents. Endometrial sampling was performed on hysterectomy specimens (proliferative phase) from symptomatic women with pathologically confirmed diffuse adenomyosis (n = 3). Controls (n = 5) were normo-ovulatory patients without adenomyosis. All patients were free from leiomyoma, endometriosis, and hormonal exposures. Isolated purified total RNA was subjected to microarray analysis using the Gene 1.0 ST Affymetrix platform. Data were analyzed with GeneSpring and Ingenuity Pathway analysis. Validation of several genes was undertaken by quantitative real-time reverse transcriptase polymerase chain reaction. Comparison of transcriptomes of proliferative endometrium from women with and without adenomyosis revealed 140 upregulated and 884 downregulated genes in samples from women with adenomyosis compared to controls. Highly differentially expressed genes include those involved in regulation of apoptosis, steroid hormone responsiveness, and proteins involved in extracellular matrix remodeling as well as microRNAs of unknown significance. Affected canonical pathways included eukaryotic initiation factor 2 signaling, oxidative phosphorylation, mitochondrial dysfunction, estrogen receptor signaling, and mammalian target of rapamycin signaling. The eutopic endometrium in patients with adenomyosis has fundamental abnormalities that may predispose to invasion and survival beyond the myometrial interface.

Optimization of signal-to-noise ratio for efficient microarray probe design.

Target-specific hybridization depends on oligo-probe characteristics that improve hybridization specificity and minimize genome-wide cross-hybridization. Interplay between specific hybridization and genome-wide cross-hybridization has been insufficiently studied, despite its crucial role in efficient probe design and in data analysis. In this study, we defined hybridization specificity as a ratio between oligo target-specific hybridization and oligo genome-wide cross-hybridization. A microarray database, derived from the Genomic Comparison Hybridization (GCH) experiment and performed using the Affymetrix platform, contains two different types of probes. The first type of oligo-probes does not have a specific target on the genome and their hybridization signals are derived from genome-wide cross-hybridization alone. The second type includes oligonucleotides that have a specific target on the genomic DNA and their signals are derived from specific and cross-hybridization components combined together in a total signal. A comparative analysis of hybridization specificity of oligo-probes, as well as their nucleotide sequences and thermodynamic features was performed on the database. The comparison has revealed that hybridization specificity was negatively affected by low stability of the fully-paired oligo-target duplex, stable probe self-folding, G-rich content, including GGG motifs, low sequence complexity and nucleotide composition symmetry. Filtering out the probes with defined 'negative' characteristics significantly increases specific hybridization and dramatically decreasing genome-wide cross-hybridization. Selected oligo-probes have two times higher hybridization specificity on average, compared to the probes that were filtered from the analysis by applying suggested cutoff thresholds to the described parameters. A new approach for efficient oligo-probe design is described in our study. shabalin@ncbi.nlm.nih.gov or olga.matveeva@gmail.com Supplementary data are available at Bioinformatics online.

Associations of rare nicotinic cholinergic receptor gene variants to nicotine and alcohol dependence.

Nicotine's rewarding effects are mediated through distinct subunits of nAChRs, encoded by different nicotinic cholinergic receptor (CHRN) genes and expressed in discrete regions in the brain. In the present study, we aimed to test the associations between rare variants at CHRN genes and nicotine dependence (ND), and alcohol dependence (AD). A total of 26,498 subjects with nine different neuropsychiatric disorders in 15 independent cohorts, which were genotyped on Illumina, Affymetrix, or PERLEGEN microarray platforms, were analyzed. Associations between rare variants (minor allele frequency (MAF) <0.05) at CHRN genes and nicotine dependence, and alcohol dependence were tested. The mRNA expression of all Chrn genes in whole mouse brain and 10 specific brain areas was investigated. All CHRN genes except the muscle-type CHRNB1, including eight genomic regions containing 11 neuronal CHRN genes and three genomic regions containing four muscle-type CHRN genes, were significantly associated with ND, and/or AD. All of these genes were expressed in the mouse brain. We conclude that CHRNs are associated with ND (mainly) and AD, supporting the hypothesis that the full catalog of ND/AD risk genes may contain most neuronal nAChRs-encoding genes. © 2016 Wiley Periodicals, Inc.

Abstract 3189: The alternate activation of hedgehog pathway, either in CD138+ or in CD138-CD19+ multiple myeloma primary cells, impacts on disease outcome

Abstract The iperactivation of Hedgehog (Hh) pathway, which controls the refuel of the tumor clone, might be critical to Multiple Myeloma (MM) recurrence. In order to dissect the role played by Hh pathway in different MM cells compartments, and to evaluate its clinical impact on patient outcomes, here we explore the transcriptomic and genomic profiles in both CD138+ plasma cells and CD138-19+ B progenitors cells obtained from newly diagnosed MM patients (pts), The study included a cohort of 126 pts, homogenously treated with bortezomib-based regimens and ASCT. DNA and RNA were obtained from both CD138+ plasma cell fraction and CD19+ B cells. Gene expression profiling (GEP) (HG U133 Plus 2.0) and genomic analysis (SNP 6.0) were performed on Affymetrix platform. Data were analysed by employing several software: dChip (GEP clustering), Ingenuity Pathway Analysis (GEP Enrichment) and Nexus (Copy number). By unsupervised hierarchical clustering, an Hh signature of 10 genes - SHH, IHH, DHH, SMO, PTCH1, PTCH2, SUFU, GLI1, GLI2 and GLI3 - was identified, and it was able to significantly cluster pts in two subgroups: cluster 1 (70 pts) and cluster 2 (56 pts. An overall significant activation of Hh pathway was shown in cluster 2, as compared to cluster 1. Of note, the Hh pathway was down regulated in CD19+ B cells obtained from pts included in cluster 2, while it was overexpressed in cluster 1 pts. Western blots on both cell fractions confirmed this opposite Hh genes behavior. A higher genomic instability (e.g. higher frequencies of both t(4;14) and del(17p)) was demonstrated in CD138+ cells from cluster 2 pts and, at least 5 known tumor suppressor genes, such as RB1, BRCA2, PDX1, FOXO1 and TP53 were affected. Conversely, cluster 1 pts were mainly characterized by hyperdiploid karyotypes. The more aggressive phenotype of cluster 2 pts was confirmed by an overall deregulation of cell adhesion processes (CD44, LIMS1, COL4A2, CTGF, COL1A1, FN1), increased proliferation (MYCBP, IL22, SDPR, SOX2, SOX6) and DNA repair mechanisms (SP1, SMARCD3, FOXA3). Hh pathway activation significantly influenced pts’ outcome, since those included in cluster 2 had a shorter PFS and OS compared to cluster 1. In fact, the 5-year PFS estimates were 31% vs 56% (p = 0.0062), whereas the OS probabilities were 66% and 83%, respectively (p = 0.0071). Of note, both hazard ratios for PFS and OS were doubled in pts included in cluster 2, as compared to pts included in cluster 1. Finally, multivariate analyses confirmed that being part of cluster 2 was an independent prognostic factor for both PFS and OS, along with del(17p) and ISS 3. Two alternate Hh-driven subtypes of MM might be identified at diagnosis, which correlated with pts outcomes. Stratification of pts according to their molecular background might help the fine-tuning of future clinical studies. Acknowledgements: FP7 NGS-PTL project, Progetto Regione-Università 2010/2012 L. Bolondi. Citation Format: Marina Martello, Daniel Remondini, Enrica Borsi, Mauro Procacci, Barbara Santacroce, Angela Flores Dico, Annalisa Pezzi, Elena Zamagni, Paola Tacchetti, Lucia Pantani, Giulia Marzocchi, Serena Rocchi, Katia Mancuso, Beatrice Anna Zannetti, Giovanni Martinelli, Michele Cavo, Carolina Terragna. The alternate activation of hedgehog pathway, either in CD138+ or in CD138-CD19+ multiple myeloma primary cells, impacts on disease outcome. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3189.

Computational Systems Biology Approach Predicts Regulators and Targets of microRNAs and Their Genomic Hotspots in Apoptosis Process.

Novel computational systems biology tools such as common targets analysis, common regulators analysis, pathway discovery, and transcriptomic-based hotspot discovery provide new opportunities in understanding of apoptosis molecular mechanisms. In this study, after measuring the global contribution of microRNAs in the course of apoptosis by Affymetrix platform, systems biology tools were utilized to obtain a comprehensive view on the role of microRNAs in apoptosis process. Network analysis and pathway discovery highlighted the crosstalk between transcription factors and microRNAs in apoptosis. Within the transcription factors, PRDM1 showed the highest upregulation during the course of apoptosis, with more than 9-fold expression increase compared to non-apoptotic condition. Within the microRNAs, MIR1208 showed the highest expression in non-apoptotic condition and downregulated by more than 6 fold during apoptosis. Common regulators algorithm showed that TNF receptor is the key upstream regulator with a high number of regulatory interactions with the differentially expressed microRNAs. BCL2 and AKT1 were the key downstream targets of differentially expressed microRNAs. Enrichment analysis of the genomic locations of differentially expressed microRNAs led us to the discovery of chromosome bands which were highly enriched (p<0.01) with the apoptosis-related microRNAs, such as 13q31.3, 19p13.13, and Xq27.3 This study opens a new avenue in understanding regulatory mechanisms and downstream functions in the course of apoptosis as well as distinguishing genomic-enriched hotspots for apoptosis process.

Snail-induced epithelial-to-mesenchymal transition of MCF-7 breast cancer cells: systems analysis of molecular changes and their effect on radiation and drug sensitivity.

BackgroundEpithelial-to-mesenchymal transition (EMT) has been associated with the acquisition of metastatic potential and the resistance of cancer cells to therapeutic treatments. MCF-7 breast cancer cells engineered to constitutively express the zinc-finger transcriptional repressor gene Snail (MCF-7-Snail cells) have been previously shown to display morphological and molecular changes characteristic of EMT. We report here the results of a comprehensive systems level molecular analysis of changes in global patterns of gene expression and levels of glutathione and reactive oxygen species (ROS) in MCF-7-Snail cells and the consequence of these changes on the sensitivity of cells to radiation treatment and therapeutic drugs.MethodsSnail-induced changes in global patterns of gene expression were identified by microarray profiling using the Affymetrix platform (U133 Plus 2.0). The resulting data were processed and analyzed by a variety of system level analytical methods. Levels of ROS and glutathione (GSH) were determined by fluorescent and luminescence assays, and nuclear levels of NF-κB protein were determined by an ELISA based method. The sensitivity of cells to ionizing radiation and anticancer drugs was determined using a resazurin-based cell cytotoxicity assay.ResultsConstitutive ectopic expression of Snail in epithelial-like, luminal A-type MCF-7 cells induced significant changes in the expression of >7600 genes including gene and miRNA regulators of EMT. Mesenchymal-like MCF-7-Snail cells acquired molecular profiles characteristic of triple-negative, claudin-low breast cancer cells, and displayed increased sensitivity to radiation treatment, and increased, decreased or no change in sensitivity to a variety of anticancer drugs. Elevated ROS levels in MCF-7-Snail cells were unexpectedly not positively correlated with NF-κB activity.ConclusionsEctopic expression of Snail in MCF-7 cells resulted in morphological and molecular changes previously associated with EMT. The results underscore the complexity and cell-type dependent nature of the EMT process and indicate that EMT is not necessarily predictive of decreased resistance to radiation and drug-based therapies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-016-2274-5) contains supplementary material, which is available to authorized users.

Differential contribution of genomic regions to marked genetic variation and prediction of quantitative traits in broiler chickens.

BackgroundGenome-wide association studies in humans have found enrichment of trait-associated single nucleotide polymorphisms (SNPs) in coding regions of the genome and depletion of these in intergenic regions. However, a recent release of the ENCyclopedia of DNA elements showed that ~80 % of the human genome has a biochemical function. Similar studies on the chicken genome are lacking, thus assessing the relative contribution of its genic and non-genic regions to variation is relevant for biological studies and genetic improvement of chicken populations.MethodsA dataset including 1351 birds that were genotyped with the 600K Affymetrix platform was used. We partitioned SNPs according to genome annotation data into six classes to characterize the relative contribution of genic and non-genic regions to genetic variation as well as their predictive power using all available quality-filtered SNPs. Target traits were body weight, ultrasound measurement of breast muscle and hen house egg production in broiler chickens. Six genomic regions were considered: intergenic regions, introns, missense, synonymous, 5′ and 3′ untranslated regions, and regions that are located 5 kb upstream and downstream of coding genes. Genomic relationship matrices were constructed for each genomic region and fitted in the models, separately or simultaneously. Kernel-based ridge regression was used to estimate variance components and assess predictive ability. Contribution of each class of genomic regions to dominance variance was also considered.ResultsVariance component estimates indicated that all genomic regions contributed to marked additive genetic variation and that the class of synonymous regions tended to have the greatest contribution. The marked dominance genetic variation explained by each class of genomic regions was similar and negligible (~0.05). In terms of prediction mean-square error, the whole-genome approach showed the best predictive ability.ConclusionsAll genic and non-genic regions contributed to phenotypic variation for the three traits studied. Overall, the contribution of additive genetic variance to the total genetic variance was much greater than that of dominance variance. Our results show that all genomic regions are important for the prediction of the targeted traits, and the whole-genome approach was reaffirmed as the best tool for genome-enabled prediction of quantitative traits.

Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer.

The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment naïve (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p<0.05). The meta-analysis approach adopted in this study has identified candidate markers correlated with disease outcome in HNSCC; further validation in a larger cohort of patients will establish their clinical relevance.

Selecting Reliable mRNA Expression Measurements Across Platforms Improves Downstream Analysis.

With increasing use of publicly available gene expression data sets, the quality of the expression data is a critical issue for downstream analysis, gene signature development, and cross-validation of data sets. Thus, identifying reliable expression measurements by leveraging multiple mRNA expression platforms is an important analytical task. In this study, we propose a statistical framework for selecting reliable measurements between platforms by modeling the correlations of mRNA expression levels using a beta-mixture model. The model-based selection provides an effective and objective way to separate good probes from probes with low quality, thereby improving the efficiency and accuracy of the analysis. The proposed method can be used to compare two microarray technologies or microarray and RNA sequencing measurements. We tested the approach in two matched profiling data sets, using microarray gene expression measurements from the same samples profiled on both Affymetrix and Illumina platforms. We also applied the algorithm to mRNA expression data to compare Affymetrix microarray data with RNA sequencing measurements. The algorithm successfully identified probes/genes with reliable measurements. Removing the unreliable measurements resulted in significant improvements for gene signature development and functional annotations.

The Alternate Activation of Hedgehog Pathway, Either in CD138+ or in CD138-CD19+ Multiple Myeloma Primary Cells, Impacts on Disease Outcome

INTRODUCTION. Although remarkable advances have been reported in Multiple Myeloma (MM) therapy, mainly due to the introduction of novel agents, the disease remains incurable in most of the patients. The iperactivation of self-renewal mechanisms, like Hedgehog (Hh) pathway, which controls the refuel of the tumor clone, might be critical to disease recurrence. Whilst several studies suggestthatHh pathway is activated in the putative CD138- Myeloma Propagating Cells (MPCs), it is likely that also terminally differentiated CD138+ plasma cells might contribute to drug resistance, by reverting to an immature phenotype.AIM. In order to dissect the role played by Hh pathway in different MM cells compartments, and to evaluate the impact of Hh pathway expression on patientsÕ clinical outcomes, a high-throughput molecular characterization was employed to explore the transcriptomic and genomic profiles in both CD138+ plasma cells and CD138-19+ B cells progenitors obtained from newly diagnosed MM patients.PATIENTS AND METHODS. The study included a cohort of 126 patients, homogenously treated with bortezomib-based regimens and ASCT, who were randomly included in a training set and a test set. For each patient, the CD138+ plasma cell fraction was isolated by immunomagnetic beads method; CD19+ B cells were isolated in 18 patients. Gene expression profiling (GEP) (HG U133 Plus 2.0 chip) and genomic analysis (SNP 6.0 chip) were performed on Affymetrix platform. dChip analysis software was used to perform GEP clustering. Expression data were analyzed by Ingenuity Pathway Analysis software and were validated by Western Blot assays. Copy number analysis was carried out using Nexus Copy Number software.RESULTS. The expression of Hh pathway genes resulted deregulated in both CD138+ and CD19+ cells, as compared to their normal counterparts. By unsupervised hierarchical clustering, an Hh signature of 10 genes - SHH, IHH, DHH, SMO, PTCH1, PTCH2, SUFU, GLI1, GLI2 and GLI3 - was identified, and was able to significantly cluster patients in two subgroups: cluster 1 included 39 patients while 37 were included in cluster 2. Clustering robustness was validated in an independent cohort of 50 patients (test set), of whom 31 were assigned to cluster 1 and 19 to cluster 2. An overall significant activation of Hh pathway was shown in cluster 2, as compared to cluster 1. Of note, the Hh pathway was down regulated in CD19+ B cells obtained from patients included in cluster 2, while it was overexpressed in cluster 1 patients. Western blots on both cell fractions confirmed this opposite Hh genes behavior.Peculiar genomic and transcriptomic profiles characterized patients included in clusters 1 and 2: indeed, a higher genomic instability (e.g. higher frequencies of both t(4;14) and del(17p)) was demonstrated in CD138+ plasma cells from cluster 2 patients and, at least 5 known tumor suppressor genes, such as RB1, BRCA2, PDX1, FOXO1 and TP53 were included in deleted regions. Conversely, cluster 1 patients were mainly characterized by hyperdiploid karyotypes. The more aggressive phenotype of cluster 2 patients was confirmed by an overall deregulation of cell adhesion processes (CD44, LIMS1, COL4A2, CTGF, COL1A1, FN1), increased proliferation (MYCBP, IL22, SDPR, SOX2, SOX6) and impaired DNA repair mechanisms (SP1, SMARCD3, FOXA3).Hh pathway activation significantly influenced patientsÕ outcome, since those included in cluster 2 had a shorter PFS and OS compared to cluster 1. In fact, the 5-year PFS estimates were 31% vs 56% (P =0.0062), whereas the OS probabilities were 66% and 83%, respectively (P =0.0071) (Fig.1,2). Of note, both hazard ratios for PFS and OS were doubled in patients included in cluster 2, as compared to patients included in cluster 1. Finally, multivariate analyses confirmed that being included in cluster 2 was an independent prognostic factor for both PFS and OS, along with del(17p) and ISS 3 (Tab. 1).CONCLUSION. Sorts of Òying -yang Ó effect of Hh pathway between mature CD138+ plasma cells and immature CD138-CD19+ MPCs could be hypothesized, where two alternate Hh-driven subtypes of MM at diagnosis correlated well with patientsÕ outcomes. Stratification of patients according to their molecular background might help the fine-tuning of future clinical studies.Supported by Regione-Universita 2010-12 (L. Bolondi), FP7 NGS-PTL project. [Display omitted] [Display omitted] [Display omitted] DisclosuresZamagni:Celgene Corporation: Honoraria, Speakers Bureau; Janssen Pharmaceuticals: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau. Martinelli:AMGEN: Consultancy; BMS: Consultancy, Speakers Bureau; Ariad: Consultancy; Novartis: Consultancy, Speakers Bureau; MSD: Consultancy; Pfizer: Consultancy; ROCHE: Consultancy. Cavo:Janssen-Cilag, Celgene, Amgen, BMS: Honoraria.

Integrating data from heterogeneous DNA microarray platforms

Summary DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.

Identification of polymorphic variants associated with erlotinib-related skin toxicity in advanced non-small cell lung cancer patients by DMET microarray analysis.

Erlotinib is a targeted agent commonly used in advanced non-small cell lung cancer (aNSCLC). However, drug-related skin toxicity often may affect the quality of life of cancer patients and lead to treatment discontinuation. Genetic polymorphisms in drug transporters and metabolizing enzymes play a major role in the interindividual variability in terms of efficacy and toxicity of erlotinib treatment. The aim of our study was to identify genetic determinants in adsorption, distribution, metabolism, and excretion genes influencing skin rash (SR) by the novel drug-metabolizing enzyme and transporter (DMET) microarray Affymetrix platform in aNSCLC patients. In a retrospective study, 34 erlotinib-treated aNSCLC patients were genotyped by DMET Plus chip: 23 patients experienced SR (cases), while 11 patients did not (controls). Peripheral blood DNA was genotyped. Genotype association was analyzed by Fisher's exact test, and the toxicity-associated gene sets underwent Ingenuity Pathway Analysis (IPA). Seven SNPs in six genes (CYP27B1, MAT1A1, CHST1, CYP4B1, ADH6, and SLC22A1) were associated with the occurrence of SR or with a protective effect. Specifically, the rs8176345 in CYP27B1 gene was significantly correlated with SR (p = 0.0003, OR 55.55, 95% CI 2.7036-1141.1707). The IPA on SR-related genes highlighted the role of a variety of canonical pathways including 1,25-dihydroxyvitamin D3 biosynthesis, S-adenosyl-L-methionine biosynthesis, and methionine degradation I (to homocysteine) in SR development. Although exploratory, this study indicates rs8176345 in CYP27B1 gene as significantly correlated with erlotinib-induced SR in aNSCLC patients probably through a mechanism mediated by vitamin D3 and inflammation at skin level.

Ultra-highly diluted plant extracts of Hydrastis canadensis and Marsdenia condurango induce epigenetic modifications and alter gene expression profiles in HeLa cells in vitro

ObjectiveMethylation-specific epigenetic process and gene expression profiles of HeLa cells treated with ultra-high dilutions (HDs) of two plant extracts, Hydrastis canadensis (HC-30) and Marsdenia condurango (Condu-30), diluted 1060 times, were analyzed against placebo 30C (Pl-30) for alterations in gene profiles linked to epigenetic modifications. MethodsSeparate groups of cells were subjected to treatment of Condu-30, HC-30, and Pl-30 prepared by serial dilutions and succussions. Global microarray data recorded on Affymetrix platform, using 25-mer probes were provided by iLifeDiscoveries, India. Slides were scanned with 3000 7G microarray scanner and raw data sets were extracted from Cel (raw intensity) files. Analyses of global microarray data profile, differential gene expression, fold change and clusters were made using GeneSpring GX12.5 software and standard normalization procedure. Before microarray study, concentration of RNA (ng/µL), RIN value and rRNA ratio for all the samples were analysed by Agilant Bioanalyzer 2100. Reverse transcriptase polymerase chain reaction (RT-PCR) and quantitative RT-PCR were done for analyzing SMAD-4 expression. Fluorescence-activated cell sorting study was further made to elucidate fate of cells at divisional stages. Methylation-specific restriction enzyme assay was conducted for ascertaining methylation status of DNA at specific sites. ResultsHDs of HC-30 and Condu-30 differentially altered methylation in specific regions of DNA and expression profiles of certain genes linked to carcinogenesis, as compared to Pl-30. Two separate cut sites were found in genomic DNA of untreated and placebo-treated HeLa cells when digested with McrBC, compared to a single cut observed in Condu-30-treated genomic DNA. SMAD-4 gene expression validated the expression pattern observed in microarray profile. Methylation-specific restriction enzyme assay elucidated differential epigenetic modifications in drug-treated and control cells. ConclusionHDs triggered epigenetic modifications and alterations in microarray gene expression profiles of many genes associated with carcinogenesis in HeLa cells in vitro.

Blood transcriptomics of drug-naïve sporadic Parkinson's disease patients.

BackgroundParkinson’s disease (PD) is a chronic progressive neurodegenerative disorder that is clinically defined in terms of motor symptoms. These are preceded by prodromal non-motor manifestations that prove the systemic nature of the disease. Identifying genes and pathways altered in living patients provide new information on the diagnosis and pathogenesis of sporadic PD.MethodsChanges in gene expression in the blood of 40 sporadic PD patients and 20 healthy controls ("Discovery set") were analyzed by taking advantage of the Affymetrix platform. Patients were at the onset of motor symptoms and before initiating any pharmacological treatment. Data analysis was performed by applying Ranking-Principal Component Analysis, PUMA and Significance Analysis of Microarrays. Functional annotations were assigned using GO, DAVID, GSEA to unveil significant enriched biological processes in the differentially expressed genes. The expressions of selected genes were validated using RT-qPCR and samples from an independent cohort of 12 patients and controls ("Validation set").ResultsGene expression profiling of blood samples discriminates PD patients from healthy controls and identifies differentially expressed genes in blood. The majority of these are also present in dopaminergic neurons of the Substantia Nigra, the key site of neurodegeneration. Together with neuronal apoptosis, lymphocyte activation and mitochondrial dysfunction, already found in previous analysis of PD blood and post-mortem brains, we unveiled transcriptome changes enriched in biological terms related to epigenetic modifications including chromatin remodeling and methylation. Candidate transcripts as CBX5, TCF3, MAN1C1 and DOCK10 were validated by RT-qPCR. ConclusionsOur data support the use of blood transcriptomics to study neurodegenerative diseases. It identifies changes in crucial components of chromatin remodeling and methylation machineries as early events in sporadic PD suggesting epigenetics as target for therapeutic intervention.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2058-3) contains supplementary material, which is available to authorized users.