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.

Concordance among digital gene expression, microarrays, and qPCR when measuring differential expression of microRNAs.

Profiling microRNA (miRNA) expression is of widespread interest given the critical role of miRNAs in many cellular functions. Profiling can be achieved via hybridization-based (microarrays), sequencing-based, or amplification-based (quantitative reverse transcription-PCR, qPCR) technologies. Among these, microarrays face the significant challenge of accurately distinguishing between mature and immature miRNA forms, and different vendors have developed different methods to meet this challenge. Here we measure differential miRNA expression using the Affymetrix, Agilent, and Illumina microarray platforms, as well as qPCR (Applied Biosystems) and ultra high-throughput sequencing (Illumina). We show that the differential expression measurements are more divergent when the three types of microarrays are compared than when the Agilent microarray, qPCR, and sequencing technology measurements are compared, which exhibit a good overall concordance.

Single-cell gene-expression profiling reveals qualitatively distinct CD8 T cells elicited by different gene-based vaccines.

CD8 T cells play a key role in mediating protective immunity against selected pathogens after vaccination. Understanding the mechanism of this protection is dependent upon definition of the heterogeneity and complexity of cellular immune responses generated by different vaccines. Here, we identify previously unrecognized subsets of CD8 T cells based upon analysis of gene-expression patterns within single cells and show that they are differentially induced by different vaccines. Three prime-boost vector combinations encoding HIV Env stimulated antigen-specific CD8 T-cell populations of similar magnitude, phenotype, and functionality. Remarkably, however, analysis of single-cell gene-expression profiles enabled discrimination of a majority of central memory (CM) and effector memory (EM) CD8 T cells elicited by the three vaccines. Subsets of T cells could be defined based on their expression of Eomes, Cxcr3, and Ccr7, or Klrk1, Klrg1, and Ccr5 in CM and EM cells, respectively. Of CM cells elicited by DNA prime-recombinant adenoviral (rAd) boost vectors, 67% were Eomes(-) Ccr7(+) Cxcr3(-), in contrast to only 7% and 2% stimulated by rAd5-rAd5 or rAd-LCMV, respectively. Of EM cells elicited by DNA-rAd, 74% were Klrk1(-) Klrg1(-)Ccr5(-) compared with only 26% and 20% for rAd5-rAd5 or rAd5-LCMV. Definition by single-cell gene profiling of specific CM and EM CD8 T-cell subsets that are differentially induced by different gene-based vaccines will facilitate the design and evaluation of vaccines, as well as enable our understanding of mechanisms of protective immunity.

Differential expression of peroxisome proliferator-activated receptors (PPARs): tissue distribution of PPAR-alpha, -beta, and -gamma in the adult rat.

Peroxisome proliferator-activated receptors (PPARs) are members of the nuclear hormone receptor superfamily that can be activated by various xenobiotics and natural fatty acids. These transcription factors primarily regulate genes involved in lipid metabolism and also play a role in adipocyte differentiation. We present the expression patterns of the PPAR subtypes in the adult rat, determined by in situ hybridization using specific probes for PPAR-alpha, -beta and -gamma, and by immunohistochemistry using a polyclonal antibody that recognizes the three rat PPAR subtypes. In numerous cell types from either ectodermal, mesodermal, or endodermal origin, PPARs are coexpressed, with relative levels varying between them from one cell type to the other. PPAR-alpha is highly expressed in hepatocytes, cardiomyocytes, enterocytes, and the proximal tubule cells of kidney. PPAR-beta is expressed ubiquitously and often at higher levels than PPAR-alpha and -gamma. PPAR-gamma is expressed predominantly in adipose tissue and the immune system. Our results suggest new potential directions to investigate the functions of the different PPAR subtypes.

DIFFERENTIAL EXPRESSION OF GLUTARYL-CoA DEHYDROGENASE IN ADULT RAT CNS, PERIPHERAL TISSUES AND DURING EMBRYONIC DEVELOPMENT

Glutaryl-CoA dehydrogenase (GCDH, EC 1.3.99.7) deficiency, known as glutaric acidemia type I, is one of the more common organic acidurias. To investigate the role of this pathway in different organs we studied the tissue-specific expression pattern of rat Gcdh. The open reading frame cDNA of the rat Gcdh gene was cloned from rat brain mRNA by RT-PCR, allowing the synthesis of digoxigenin-labeled in situ hybridization (ISH) riboprobes. Gcdh mRNA expression was analyzed by ISH on cryosections of adult rat brain, kidney, liver, spleen and heart muscle, as well as on E15 and E18 rat embryos. Gcdh was found expressed in the whole rat brain, almost exclusively in neurons. Gcdh was absent from astrocytes but expressed in rare oligodendrocytes. Strong Gcdh expression was found in liver and spleen, where expression appears predominant to lymphatic nodules. In kidney, the highest Gcdh expression is found in the juxtamedullar cortex (but not in glomerula), and at lower levels in medulla. Heart muscle was negative. During embryonic development, Gcdh was found well expressed in liver, intestinal mucosa and skin, as well as at lower levels in CNS. Further studies are ongoing to provide evidence on the presence of the entire pathway in CNS in order to understand the mechanisms leading to neurotoxicity in glutaric aciduria. The high expression of Gcdh in kidney may explain why certain patients with residual enzyme activity are low excretors at the urine metabolite level.

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.

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.

Differential expression and modification of neurofilament triplet proteins during cat cerebellar development.

Neurofilament (NF) proteins consist of three subunits of different molecular weights defined as NF-H, NF-M, and NF-L. They are typical structures of the neuronal cytoskeleton. Their immunocytochemical distribution during postnatal development of cat cerebellum was studied with several monoclonal and polyclonal antibodies against phosphorylated or unmodified sites. Expression and distribution of the triplet neurofilament proteins changed with maturation. Afferent mossy and climbing fibers in the medullary layer contained NF-M and NF-L already at birth, whereas NF-H appeared later. Within the first three postnatal weeks, all three subunits appeared in mossy and climbing fibers in the internal granular and molecular layers and in the axons of Purkinje cells. Axons of local circuit neurons such as basket cells expressed these proteins at the end of the first month, whereas parallel fibers expressed them last, at the beginning of the third postnatal month. Differential localization was especially observed for NF-H. Depending on phosphorylation, NF-H proteins were found in different axon types in climbing, mossy, and basket fibers or additionally in parallel fibers. A nonphosphorylated NF-H subunit was exclusively located in some Purkinje cells at early developmental stages and in some smaller interneurons later. A novel finding is the presence of a phosphorylation site in the NF-H subunit that is localized in dendrites of Purkinje cells but not in axons. Expression and phosphorylation of the NF-H subunit, especially, is cell-type specific and possibly involved in the adult-type stabilization of the axonal and dendritic cytoskeleton.

Differential expression of triiodothyronine receptors in schwannoma and neurofibroma: role of Schwann cell-axon interaction.

Regulation of gene expression in Schwann cells may be determined, at least in part, by the interaction of these cells with axons. Two peripheral nerve tumors, neurofibroma and schwannoma, represent good tools for studying Schwann cell activity in the presence or absence of axon action. In the present work we studied the expression of triiodothyronine receptors (T3R) by Schwann cells in these two tumors and also in adult normal sciatic nerve. Confirming the results of the histological examination, immunostaining of the neurofilaments showed the presence of fascicles or scattered axons in all neurofibroma sections studied. In these neurofibromas, Schwann cells did not express T3R immunoreactivity. Furthermore, in adult normal sciatic nerve, Schwann cells which ensheathed axons were devoid of any T3R expression. In contrast, in schwannoma, the complete absence of axons was demonstrated by the lack of neurofilament immunostaining. Here, Schwann cells deprived of axonal interaction displayed clear T3R immunoreactivity. In schwannoma cell cultures, Schwann cells continued to express T3R, even in cultures treated with medium that had been conditioned with rat sensory neurons. On the basis of these results, we suggest that, beside the possible regulatory mechanisms for T3R, the synthesis of T3R is regulated, at least in part, by Schwann cell-axon interaction.

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.

Gene expression profiling of isolated tumour cells from anaplastic large cell lymphomas: insights into its cellular origin, pathogenesis and relation to Hodgkin lymphoma.

Anaplastic large cell lymphoma (ALCL) is a main type of T-cell lymphomas and comprises three distinct entities: systemic anaplastic lymphoma kinase (ALK) positive, systemic ALK(-) and cutaneous ALK(-) ALCL (cALCL). Little is known about their pathogenesis and their cellular origin, and morphological and immunophenotypical overlap exists between ALK(-) ALCL and classical Hodgkin lymphoma (cHL). We conducted gene expression profiling of microdissected lymphoma cells of five ALK(+) and four ALK(-) systemic ALCL, seven cALCL and sixteen cHL, and of eight subsets of normal T and NK cells. The analysis supports a derivation of ALCL from activated T cells, but the lymphoma cells acquired a gene expression pattern hampering an assignment to a CD4(+), CD8(+) or CD30(+) T-cell origin. Indeed, ALCL display a down-modulation of many T-cell characteristic molecules. All ALCL types show significant expression of NFkappaB target genes and upregulation of genes involved in oncogenesis (e.g. EZH2). Surprisingly, few genes are differentially expressed between systemic and cALCL despite their different clinical behaviour, and between ALK(-) ALCL and cHL despite their different cellular origin. ALK(+) ALCL are characterized by expression of genes regulated by pathways constitutively activated by ALK. This study provides multiple novel insights into the molecular biology and pathogenesis of ALCL.

Gene expression profiling of human glioblastomas for the identification of predictive factors and characterisation of molecular mechanism implicated in response to therapy and outcome

ABSTRACT Poor outcome for glioblastoma patients is largely due to resistance to chemoradiation therapy. While epigenetic inactivation of MGMT mediated DNA repair is highly predictive for benefit from the alkylating agent therapy Temozolomide, additional mechanisms for resistance associated with molecular alterations exist. Furthermore, new concepts in cancer suggest that resistance to treatment may be linked to cancer stem cells that escape therapy and act as source for tumour recurrence. We determined gene expression signatures associated with outcome in glioblastoma patients enrolled in a phase II and phase III clinical trial establishing the new combination therapy of radiation plus concomitant and adjuvant Temozolomide. Correlating stable gene clusters emerging from unsupervised analysis with survival of 42 treated patients identified a number of biological processes associated with outcome. Most prominent, a gene cluster dominated by HOX genes and comprising PROM1, was associated with resistance. PROM1 encodes CD133, a marker for a subpopulation of tumour cells enriched for glioblastoma stem- like cells. The core of this correlated HOX cluster was comprised in the top genes of a "self-renewal signature" defined in a mouse model for MLL-AF9 initiated leukaemia. The association of the HOX gene cluster with tumour resistance was confirmed in two external data sets of 146 malignant glioma As additional resistance factors we identified over-expression of the epidermal growth factor receptor gene, EGFR, while increased gene expression related to biological features of tumour host interaction, including markers for tumour vascular and cell adhesion, and innate immune response, were associated with better outcome. The "self-renewal" signature associated with resistance to the new combination chemoradiation therapy provides first clinical evidence that glioma stem like cells may implicated in resistance in a uniformly treated cohort of glioblastoma patients. This study underlines the need to target the tumour stem cell compartment, and provides some testable hypothesis for biological mechanisms relevant for malignant behaviour of glioblastoma that may be targeted in new treatment approaches. Résumé Le glioblastome, tumeur cérébrale primaire maligne la plus fréquente, est connue pour son mauvais pronostique. Des avancées chimiothérapeutiques récentes avec des agents alkylants comme le témozolomide (TMZ), ont permis une amélioration notable dans la survie de certains patients. Les bénéficiaires ont la caractéristique commune de présenter une particularité génétique, la methylation du MGMT (methylguanine methyltransferase). Néanmoins, d'autres mécanismes de résistance en fonction des aberrations moléculaires existent. Nous avons établi les profils d'expressions génétiques des patients traités par irradiation et TMZ dans des études cliniques de phase II et III. En combinant des méthodes non-supervisées et supervisées, de l'étude de la cohorte des patients traités nous avons découvert des groupes de gènes associés à la survie. Un ensemble de gènes contenant les gènes Hox semble lié au mécanisme de résistance au traitement. Récemment, les gènes Hox ont été décrits comme faisant partie d"une signature d'autorenouvellement (self-renewal) des cellules souches cancéreuses de la leucémie. L'autorenouvellement est un processus grâce auquel les cellules souches se maintiennent tout au long de la vie. Cette association à la résistance est confirmée dans deux autres études indépendantes. Un autre facteur de résistance au traitement est la surexpression du gène EGFR. D'autre part, deux groupes de gènes associés à la relation entre hôte-tumeur tels que les marqueurs des vaisseaux tumoraux et de la réponse immunitaire innée s'avèrent avoir un effet positif sur la survie des patients traités. La découverte de la signature d'autorenouvellement comme facteur de résistance à la nouvelle chimio-radiothérapie offre une preuve clinique que les cellules souches cancéreuses sont impliquées dans la résistance au traitement. If est donc logique de penser que le traitement ciblé contre des cellules souches cancéreuses va dans l'avenir permettre des thérapies anticancéreuses plus performantes.

Gene expression profiling in the human pathogenic dermatophyte Trichophyton rubrum during growth on proteins.

Dermatophytes are highly specialized filamentous fungi which cause the majority of superficial mycoses in humans and animals. The high secreted proteolytic activity of these microorganisms during growth on proteins is assumed to be linked to their particular ability to exclusively infect keratinized host structures such as the skin stratum corneum, hair, and nails. Individual secreted dermatophyte proteases were recently described and linked with the in vitro digestion of keratin. However, the overall adaptation and transcriptional response of dermatophytes during protein degradation are largely unknown. To address this question, we constructed a cDNA microarray for the human pathogenic dermatophyte Trichophyton rubrum that was based on transcripts of the fungus grown on proteins. Profiles of gene expression during the growth of T. rubrum on soy and keratin protein displayed the activation of a large set of genes that encode secreted endo- and exoproteases. In addition, other specifically induced factors potentially implicated in protein utilization were identified, including heat shock proteins, transporters, metabolic enzymes, transcription factors, and hypothetical proteins with unknown functions. Of particular interest is the strong upregulation of key enzymes of the glyoxylate cycle in T. rubrum during growth on soy and keratin, namely, isocitrate lyase and malate synthase. This broad-scale transcriptional analysis of dermatophytes during growth on proteins reveals new putative pathogenicity-related host adaptation mechanisms of these human pathogenic fungi.

Chronic wound healing by fetal cell therapy may be explained by differential gene profiling observed in fetal versus old skin cells.

Engineering of fetal tissue has a high potential for the treatment of acute and chronic wounds of the skin in humans as these cells have high expansion capacity under simple culture conditions and one organ donation can produce Master Cell Banks which can fabricate over 900 million biological bandages (9 x 12cm). In a Phase 1 clinical safety study, cases are presented for the treatment of therapy resistant leg ulcers. All eight patients, representing 13 ulcers, tolerated multiple treatments with fetal biological bandages showing no negative secondary effects and repair processes similar to that seen in 3rd degree burns. Differential gene profiling using Affymetrix gene chips (analyzing 12,500 genes) were accomplished on these banked fetal dermal skin cells compared to banked dermal skin cells of an aged donor in order to point to potential indicators of wound healing. Families of genes involved in cell adhesion and extracellular matrix, cell cycle, cellular signaling, development and immune response show significant differences in regulation between banked fetal and those from banked old skin cells: with approximately 47.0% of genes over-expressed in fetal fibroblasts. It is perhaps these differences which contribute to efficient tissue repair seen in the clinic with fetal cell therapy.

A comparison of methods for differential expression analysis of RNA-seq data.

BACKGROUND: Finding genes that are differentially expressed between conditions is an integral part of understanding the molecular basis of phenotypic variation. In the past decades, DNA microarrays have been used extensively to quantify the abundance of mRNA corresponding to different genes, and more recently high-throughput sequencing of cDNA (RNA-seq) has emerged as a powerful competitor. As the cost of sequencing decreases, it is conceivable that the use of RNA-seq for differential expression analysis will increase rapidly. To exploit the possibilities and address the challenges posed by this relatively new type of data, a number of software packages have been developed especially for differential expression analysis of RNA-seq data. RESULTS: We conducted an extensive comparison of eleven methods for differential expression analysis of RNA-seq data. All methods are freely available within the R framework and take as input a matrix of counts, i.e. the number of reads mapping to each genomic feature of interest in each of a number of samples. We evaluate the methods based on both simulated data and real RNA-seq data. CONCLUSIONS: Very small sample sizes, which are still common in RNA-seq experiments, impose problems for all evaluated methods and any results obtained under such conditions should be interpreted with caution. For larger sample sizes, the methods combining a variance-stabilizing transformation with the 'limma' method for differential expression analysis perform well under many different conditions, as does the nonparametric SAMseq method.