Impact of normalization on miRNA microarray expression profiling.

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Molecular risk assessment of BIG 1-98 participants by expression profiling using RNA from archival tissue.

Background: The purpose of the work reported here is to test reliable molecular profiles using routinely processed formalin-fixed paraffin-embedded (FFPE) tissues from participants of the clinical trial BIG 1-98 with a median follow-up of 60 months. Methods: RNA from fresh frozen (FF) and FFPE tumor samples of 82 patients were used for quality control, and independent FFPE tissues of 342 postmenopausal participants of BIG 1-98 with ER-positive cancer were analyzed by measuring prospectively selected genes and computing scores representing the functions of the estrogen receptor (eight genes, ER_8), the progesterone receptor (five genes, PGR_5), Her2 (two genes, HER2_2), and proliferation (ten genes, PRO_10) by quantitative reverse transcription PCR (qRT-PCR) on TaqMan Low Density Arrays. Molecular scores were computed for each category and ER_8, PGR_5, HER2_2, and PRO_10 scores were combined into a RISK_25 score. Results: Pearson correlation coefficients between FF- and FFPE-derived scores were at least 0.94 and high concordance was observed between molecular scores and immunohistochemical data. The HER2_2, PGR_ 5, PRO_10 and RISK_25 scores were significant predictors of disease free-survival (DFS) in univariate Cox proportional hazard regression. PRO_10 and RISK_25 scores predicted DFS in patients with histological grade II breast cancer and in lymph node positive disease. The PRO_10 and PGR_ 5 scores were independent predictors of DFS in multivariate Cox regression models incorporating clinical risk indicators; PRO_10 outperformed Ki-67 labeling index in multivariate Cox proportional hazard analyses. Conclusions: Scores representing the endocrine responsiveness and proliferation status of breast cancers were developed from gene expression analyses based on RNA derived from FFPE tissues. The validation of the molecular scores with tumor samples of participants of the BIG 1-98 trial demonstrates that such scores can serve as independent prognostic factors to estimate disease free survival (DFS) in postmenopausal patients with estrogen receptor positive breast cancer.

Interest of qualitative and quantitative profiling of endocannabinoids for evaluation of their implication in drug addiction process

Introduction: In the middle of the 90's, the discovery of endogenous ligands for cannabinoid receptors opened a new era in this research field. Amides and esters of arachidonic acid have been identified as these endogenous ligands. Arachidonoylethanolamide (anandamide or AEA) and 2-Arachidonoylglycerol (2-AG) seem to be the most important of these lipid messengers. In addition, virodhamine (VA), noladin ether (2-AGE), and N-arachidonoyl dopamine (NADA) have been shown to bind to CB receptors with varying affinities. During recent years, it has become more evident that the EC system is part of fundamental regulatory mechanisms in many physiological processes such as stress and anxiety responses, depression, anorexia and bulimia, schizophrenia disorders, neuroprotection, Parkinson disease, anti-proliferative effects on cancer cells, drug addiction, and atherosclerosis. Aims: This work presents the problematic of EC analysis and the input of Information Dependant Acquisition based on hybrid triple quadrupole linear ion trap (QqQLIT) system for the profiling of these lipid mediators. Methods: The method was developed on a LC Ultimate 3000 series (Dionex, Sunnyvale, CA, USA) coupled to a QTrap 4000 system (Applied biosystems, Concord, ON, Canada). The ECs were separated on an XTerra C18 MS column (50 × 3.0 mm i.d., 3.5 μm) with a 5 min gradient elution. For confirmatory analysis, an information-dependant acquisition experiment was performed with selected reaction monitoring (SRM) as survey scan and enhanced produced ion (EPI) as dependant scan. Results: The assay was found to be linear in the concentration range of 0.1-5 ng/mL for AEA, 0.3-5 ng/mL for VA, 2-AGE, and NADA and 1-20 ng/mL for 2-AG using 0.5 mL of plasma. Repeatability and intermediate precision were found less than 15% over the tested concentration ranges. Under non-pathophysiological conditions, only AEA and 2-AG were actually detected in plasma with concentration ranges going from 104 to 537 pg/mL and from 2160 to 3990 pg/mL respectively. We have particularly focused our scopes on the evaluation of EC level changes in biological matrices through drug addiction and atherosclerosis processes. We will present preliminary data obtained during pilot study after administration of cannabis on human patients. Conclusion: ECs have been shown to play a key role in regulation of many pathophysiological processes. Medical research in these different fields continues to growth in order to understand and to highlight the predominant role of EC in the CNS and peripheral tissues signalisation. The profiling of these lipids needs to develop rapid, highly sensitive and selective analytical methods.

Analysis of prion strains by PrPSc profiling in sporadic Creutzfeldt-Jakob disease.

BACKGROUND: Prion diseases are a group of invariably fatal neurodegenerative disorders affecting humans and a wide range of mammals. An essential part of the infectious agent, termed the prion, is composed of an abnormal isoform (PrPSc) of a host-encoded normal cellular protein (PrPC). The conversion of PrPC to PrPSc is thought to play a crucial role in the development of prion diseases and leads to PrPSc deposition, mainly in the central nervous system. Sporadic Creutzfeldt-Jakob disease (sCJD), the most common form of human prion disease, presents with a marked clinical heterogeneity. This diversity is accompanied by a molecular signature which can be defined by histological, biochemical, and genetic means. The molecular classification of sCJD is an important tool to aid in the understanding of underlying disease mechanisms and the development of therapy protocols. Comparability of classifications is hampered by disparity of applied methods and inter-observer variability. METHODS AND FINDINGS: To overcome these difficulties, we developed a new quantification protocol for PrPSc by using internal standards on each Western blot, which allows for generation and direct comparison of individual PrPSc profiles. By studying PrPSc profiles and PrPSc type expression within nine defined central nervous system areas of 50 patients with sCJD, we were able to show distinct PrPSc distribution patterns in diverse subtypes of sCJD. Furthermore, we were able to demonstrate the co-existence of more than one PrPSc type in individuals with sCJD in about 20% of all patients and in more than 50% of patients heterozygous for a polymorphism on codon 129 of the gene encoding the prion protein (PRNP). CONCLUSION: PrPSc profiling represents a valuable tool for the molecular classification of human prion diseases and has important implications for their diagnosis by brain biopsy. Our results show that the co-existence of more than one PrPSc type might be influenced by genetic and brain region-specific determinants. These findings provide valuable insights into the generation of distinct PrPSc types.

The profiling of MDMA tablets: a study of the combination of physical characteristics and organic impurities as sources of information

The profiling of MDMA tablets can be carried out using different sets of characteristics. The first type of measurements performed on MDMA tablets are physical characteristics (i.e. post-tabletting characteristics). They yield preliminary profiling data that may be valuable in a first stage for investigation purposes. However organic impurities (i.e. pre-tabletting characteristics) are generally considered to bring more reliable information, particularly for presentation of evidence in court. This work aimed therefore at evaluating the added value of combining pre-tabletting characteristics and post-tabletting characteristics of seized MDMA tablets. In approximately half of the investigated cases, the post-tabletting links were confirmed with organic impurities analyses. In the remaining cases, post-tabletting batches (post-TBs) were divided in several pre-tabletting batches (pre-TBs), thus supporting the hypothesis that several production batches of MDMA powder (pre-TBs) were used to produce one single post-TB (i.e. tablets having the same shape, diameter, thickness, weight and score; but different organic impurities composition). In view of the obtained results, the hypotheses were discussed through illustrating examples. In conclusion, both sets of characteristics were found relevant alone and combined together. They actually provide distinct information about MDMA illicit production and trafficking.

TNF-alpha blockers in inflammatory bowel diseases: practical consensus recommendations and a user's guide.

More than seventy years after their initial characterisation, the aetiology of inflammatory bowel diseases remains elusive. A recent review evaluating the incidence trends of the last 25 years concluded that an increasing incidence has been observed almost worldwide. A north-south gradient is still found in Europe. Genetic associations are variably reproduced worldwide and indicate a strong impact of environmental factors. Tumour necrosis factor alpha (TNF-alpha) has been shown to play a critical role in the pathogenesis of inflammatory bowel disease (IBD). TNF-alpha blockers are biological agents that specifically target this key cytokine in the inflammatory process and have become a mainstay in the therapy of inflammatory bowel diseases. This paper reviews the necessary investigations before using such agents, the use of such agents in pregnancy and lactation, the role of co-immunosuppression, how to monitor efficacy and safety, dose-adaptation, and the decision as to when to switch to another TNF-alpha blocker. Finally it gives recommendations for special situations. Currently there are three TNF-alpha blockers available for clinical use in IBD in Switzerland: infliximab (Remicade), adalimumab (Humira) and certolizumab pegol (Cimzia). Infliximab is a chimeric monoclonal antibody composed of a human IgG1 constant region and a murine variable region and is administered intravenously. Adalimumab is a humanised monoclonal antibody, with both human IgG1 constant and variable regions. Certolizumab pegol is a pegylated, humanised monoclonal anti-TNF fragment antigen binding fragment. Both adalimumab and certolizumab pegol are administered by subcutaneous injection. The efficacy and safety of TNF-alpha blockers in Crohn's disease has been reviewed. The authors conclude that the three above-mentioned agents are effective in luminal Crohn's disease. In fistulizing Crohn's disease, TNF-alpha blockers other than infliximab require additional investigation.

Small nucleolar RNA expression profiling identifies potential prognostic markers in peripheral T-cell lymphoma.

Peripheral T-cell lymphoma (PTCL) is a rare, heterogeneous type of non-Hodgkin lymphoma (NHL) that, in general, is associated with a poor clinical outcome. Therefore, a current major challenge is the discovery of new prognostic tools for this disease. In the present study, a cohort of 122 patients with PTCL was collected from a multicentric T-cell lymphoma consortium (TENOMIC). We analyzed the expression of 80 small nucleolar RNAs (snoRNAs) using high-throughput quantitative PCR. We demonstrate that snoRNA expression analysis may be useful in both the diagnosis of some subtypes of PTCL and the prognostication of both PTCL-not otherwise specified (PTCL-NOS; n = 26) and angio-immunoblastic T-cell lymphoma (AITL; n = 46) patients treated with chemotherapy. Like miRNAs, snoRNAs are globally down-regulated in tumor cells compared with their normal counterparts. In the present study, the snoRNA signature was robust enough to differentiate anaplastic large cell lymphoma (n = 32) from other PTCLs. For PTCL-NOS and AITL, we obtained 2 distinct prognostic signatures with a reduced set of 3 genes. Of particular interest was the prognostic value of HBII-239 snoRNA, which was significantly over-expressed in cases of AITL and PTCL-NOS that had favorable outcomes. Our results suggest that snoRNA expression profiles may have a diagnostic and prognostic significance for PTCL, offering new tools for patient care and follow-up.

Update of the FANTOM web resource: from mammalian transcriptional landscape to its dynamic regulation.

The international Functional Annotation Of the Mammalian Genomes 4 (FANTOM4) research collaboration set out to better understand the transcriptional network that regulates macrophage differentiation and to uncover novel components of the transcriptome employing a series of high-throughput experiments. The primary and unique technique is cap analysis of gene expression (CAGE), sequencing mRNA 5'-ends with a second-generation sequencer to quantify promoter activities even in the absence of gene annotation. Additional genome-wide experiments complement the setup including short RNA sequencing, microarray gene expression profiling on large-scale perturbation experiments and ChIP-chip for epigenetic marks and transcription factors. All the experiments are performed in a differentiation time course of the THP-1 human leukemic cell line. Furthermore, we performed a large-scale mammalian two-hybrid (M2H) assay between transcription factors and monitored their expression profile across human and mouse tissues with qRT-PCR to address combinatorial effects of regulation by transcription factors. These interdependent data have been analyzed individually and in combination with each other and are published in related but distinct papers. We provide all data together with systematic annotation in an integrated view as resource for the scientific community (http://fantom.gsc.riken.jp/4/). Additionally, we assembled a rich set of derived analysis results including published predicted and validated regulatory interactions. Here we introduce the resource and its update after the initial release.

In vivo metabolic profiling of glioma-initiating cells using proton magnetic resonance spectroscopy at 14.1 Tesla.

In the last decade, evidence has emerged indicating that the growth of a vast majority of tumors including gliomas is sustained by a subpopulation of cancer cells with stem cell properties called cancer initiating cells. These cells are able to initiate and propagate tumors and constitute only a fraction of all tumor cells. In the present study, we showed that intracerebral injection of cultured glioma-initiating cells into nude mice produced fast growing tumors showing necrosis and gadolinium enhancement in MR images, whereas gliomas produced by injecting freshly purified glioma-initiating cells grew slowly and showed no necrosis and very little gadolinium enhancement. Using proton localized spectroscopy at 14.1 Tesla, decreasing trends of N-acetylaspartate, glutamate and glucose concentrations and an increasing trend of glycine concentration were observed near the injection site after injecting cultured glioma-initiating cells. In contrast to the spectra of tumors grown from fresh cells, those from cultured cells showed intense peaks of lipids, increased absolute concentrations of glycine and choline-containing compounds, and decreased concentrations of glutamine, taurine and total creatine, when compared with a contralateral non-tumor-bearing brain tissue. A decrease in concentrations of N-acetylaspartate and γ-aminobutyrate was found in both tumor phenotypes after solid tumor formation. Further investigation is needed to determine the cause of the dissimilarities between the tumors grown from cultured glioma-initiating cells and those from freshly purified glioma-initiating cells, both derived from human glioblastomas.

Object-oriented Bayesian networks for evaluating DIP-STR profiling results from unbalanced DNA mixtures.

The genetic characterization of unbalanced mixed stains remains an important area where improvement is imperative. In fact, with current methods for DNA analysis (Polymerase Chain Reaction with the SGM Plus™ multiplex kit), it is generally not possible to obtain a conventional autosomal DNA profile of the minor contributor if the ratio between the two contributors in a mixture is smaller than 1:10. This is a consequence of the fact that the major contributor's profile 'masks' that of the minor contributor. Besides known remedies to this problem, such as Y-STR analysis, a new compound genetic marker that consists of a Deletion/Insertion Polymorphism (DIP), linked to a Short Tandem Repeat (STR) polymorphism, has recently been developed and proposed elsewhere in literature [1]. The present paper reports on the derivation of an approach for the probabilistic evaluation of DIP-STR profiling results obtained from unbalanced DNA mixtures. The procedure is based on object-oriented Bayesian networks (OOBNs) and uses the likelihood ratio as an expression of the probative value. OOBNs are retained in this paper because they allow one to provide a clear description of the genotypic configuration observed for the mixed stain as well as for the various potential contributors (e.g., victim and suspect). These models also allow one to depict the assumed relevance relationships and perform the necessary probabilistic computations.

Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.

BACKGROUND: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profiles of breast cancers and whether such profiles could be used to improve histologic grading. METHODS: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. RESULTS: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P < .001, log-rank test). CONCLUSIONS: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value.