Rodney J. Ouellette

Medulloblastoma exosome proteomics yield functional roles for extracellular vesicles.

Medulloblastomas are the most prevalent malignant pediatric brain tumors. Survival for these patients has remained largely the same for approximately 20 years, and our therapies for these cancers cause significant health, cognitive, behavioral and developmental sequelae for those who survive the tumor and their treatments. We obviously need a better understanding of the biology of these tumors, particularly with regard to their migratory/invasive behaviors, their proliferative propensity, and their abilities to deflect immune responses. Exosomes, virus-sized membrane vesicles released extracellularly from cells after formation in, and transit thru, the endosomal pathway, may play roles in medulloblastoma pathogenesis but are as yet unstudied in this disease. Here we characterized exosomes from a medulloblastoma cell line with biochemical and proteomic analyses, and included characterization of patient serum exosomes. Further scrutiny of the proteomic data suggested functional properties of the exosomes that are relevant to medulloblastoma tumor biology, including their roles as proliferation stimulants, their activities as attractants for tumor cell migration, and their immune modulatory impacts on lymphocytes. Aspects of this held true for exosomes from other medulloblastoma cell lines as well. Additionally, pathway analyses suggested a possible role for the transcription factor hepatocyte nuclear factor 4 alpha (HNF4A); however, inhibition of the protein’s activity actually increased D283MED cell proliferation/clonogenecity, suggesting that HNF4A may act as a tumor suppressor in this cell line. Our work demonstrates that relevant functional properties of exosomes may be derived from appropriate proteomic analyses, which translate into mechanisms of tumor pathophysiology harbored in these extracellular vesicles.

Fuzzy J-Means and VNS methods for clustering genes from microarray data

MOTIVATION In the interpretation of gene expression data from a group of microarray experiments that include samples from either different patients or conditions, special consideration must be given to the pleiotropic and epistatic roles of genes, as observed in the variation of gene coexpression patterns. Crisp clustering methods assign each gene to one cluster, thereby omitting information about the multiple roles of genes. RESULTS Here, we present the application of a local search heuristic, Fuzzy J-Means, embedded into the variable neighborhood search metaheuristic for the clustering of microarray gene expression data. We show that for all the datasets studied this algorithm outperforms the standard Fuzzy C-Means heuristic. Different methods for the utilization of cluster membership information in determining gene coregulation are presented. The clustering and data analyses were performed on simulated datasets as well as experimental cDNA microarray data for breast cancer and human blood from the Stanford Microarray Database. AVAILABILITY The source code of the clustering software (C programming language) is freely available from Nabil.Belacel@nrc-cnrc.gc.ca

The Pax-5 Gene: A Pluripotent Regulator of B-cell Differentiation and Cancer Disease

The Pax-5 oncogene encodes a potent transcription factor that plays a key role in B-cell development and cancerous processes. In normal B-lymphopoiesis, Pax-5 accomplishes a dual function by activating B-cell commitment genes while concomitantly repressing non-B-lineage genes. Given the pivotal importance of Pax-5-mediated processes in B-cell development, an aberrant regulation of Pax5 expression has consistently been associated with B-cell cancers, namely, lymphoma and lymphocytic leukemias. More recently, Pax-5 gene expression has been proposed to influence carcinogenic events in tissues of nonlymphoid origin by promoting cell growth and survival. However, in other cases, Pax-5 products have opposing effects on proliferative activity, thus redefining its generally accepted role as an oncogene in cancer. In this review, we attempt to summarize recent findings about the function and regulation of Pax-5 gene products in B-cell development and related cancers. In addition, we present new findings that highlight the pleiotropic effects of Pax-5 activity in a number of other cancer types.

RT-PCR for mammaglobin genes, MGB1 and MGB2, identifies breast cancer micrometastases in sentinel lymph nodes

In the present study, we examined the expression of the mammaglobin genes, MGB1 and MGB2, in the sentinel lymph nodes (SLNs) of patients with breast cancer and compared our results with the histologic status of the same SLNs. Compared with immunohistochemical staining for cytokeratin 8, which detected metastases in 17 of 42 patients, reverse transcription-polymerase chain reaction (RT-PCR) for MGB1 or MGB2 genes was positive in 22 patients. The concordance between the expression of any mammaglobin and histologic status was 79% (33/42), with a sensitivity of 88% and specificity of 72%. The detection of patients with metastases was more sensitive when testing for both MGB1 and MGB2 (P < .0001) rather than MGB2 (P < .0005) or MGB1 (P < .05) alone. The increased detection rate relative to histologic examination suggests that using RT-PCR for the mammaglobin genes might identify patients at higher risk compared with patients with negative RT-PCR results.

Rapid isolation of extracellular vesicles from cell culture and biological fluids using a synthetic peptide with specific affinity for heat shock proteins.

Recent studies indicate that extracellular vesicles are an important source material for many clinical applications, including minimally-invasive disease diagnosis. However, challenges for rapid and simple extracellular vesicle collection have hindered their application. We have developed and validated a novel class of peptides (which we named venceremin, or Vn) that exhibit nucleotide-independent specific affinity for canonical heat shock proteins. The Vn peptides were validated to specifically and efficiently capture HSP-containing extracellular vesicles from cell culture growth media, plasma, and urine by electron microscopy, atomic force microscopy, sequencing of nucleic acid cargo, proteomic profiling, immunoblotting, and nanoparticle tracking analysis. All of these analyses confirmed the material captured by the Vn peptides was comparable to those purified by the standard ultracentrifugation method. We show that the Vn peptides are a useful tool for the rapid isolation of extracellular vesicles using standard laboratory equipment. Moreover, the Vn peptides are adaptable to diverse platforms and therefore represent an excellent solution to the challenge of extracellular vesicle isolation for research and clinical applications.

Development and Experimental Validation of a 20K Atlantic Cod (Gadus morhua) Oligonucleotide Microarray Based on a Collection of over 150,000 ESTs

The collapse of Atlantic cod (Gadus morhua) wild populations strongly impacted the Atlantic cod fishery and led to the development of cod aquaculture. In order to improve aquaculture and broodstock quality, we need to gain knowledge of genes and pathways involved in Atlantic cod responses to pathogens and other stressors. The Atlantic Cod Genomics and Broodstock Development Project has generated over 150,000 expressed sequence tags from 42 cDNA libraries representing various tissues, developmental stages, and stimuli. We used this resource to develop an Atlantic cod oligonucleotide microarray containing 20,000 unique probes. Selection of sequences from the full range of cDNA libraries enables application of the microarray for a broad spectrum of Atlantic cod functional genomics studies. We included sequences that were highly abundant in suppression subtractive hybridization (SSH) libraries, which were enriched for transcripts responsive to pathogens or other stressors. These sequences represent genes that potentially play an important role in stress and/or immune responses, making the microarray particularly useful for studies of Atlantic cod gene expression responses to immune stimuli and other stressors. To demonstrate its value, we used the microarray to analyze the Atlantic cod spleen response to stimulation with formalin-killed, atypical Aeromonas salmonicida, resulting in a gene expression profile that indicates a strong innate immune response. These results were further validated by quantitative PCR analysis and comparison to results from previous analysis of an SSH library. This study shows that the Atlantic cod 20K oligonucleotide microarray is a valuable new tool for Atlantic cod functional genomics research.

Determination of tumour marker genes from gene expression data.

Cancer classification has traditionally been based on the morphological study of tumours. However, tumours with similar histological appearances can exhibit different responses to therapy, indicating differences in tumour characteristics on the molecular level. Thus, development of a novel, reliable and precise method for classification of tumours is essential for more successful diagnosis and treatment. The high-throughput gene expression data obtained using microarray technology are currently being investigated for diagnostic applications. However, these large datasets introduce a range of challenges, making data analysis a major part of every experiment for any application, including cancer classification and diagnosis. One of the major concerns in the application of microarrays to tumour diagnostics is the fact that the expression levels of many genes are not measurably affected by carcinogenic changes in the cells. Thus, a crucial step in the application of microarrays to cancer diagnostics is the selection of diagnostic marker genes from the gene expression profiles. These molecular markers give valuable additional information for tumour diagnosis, prognosis and therapy development.

NMR metabolic analysis of samples using fuzzy K-means clustering

The global analysis of metabolites can be used to define the phenotypes of cells, tissues or organisms. Classifying groups of samples based on their metabolic profile is one of the main topics of metabolomics research. Crisp clustering methods assign each feature to one cluster, thereby omitting information about the multiplicity of sample subtypes. Here, we present the application of fuzzy K‐means clustering method for the classification of samples based on metabolomics 1D 1H NMR fingerprints. The sample classification was performed on NMR spectra of cancer cell line extracts and of urine samples of type 2 diabetes patients and animal models. The cell line dataset included NMR spectra of lipophilic cell extracts for two normal and three cancer cell lines with cancer cell lines including two invasive and one non‐invasive cancers. The second dataset included previously published NMR spectra of urine samples of human type 2 diabetics and healthy controls, mouse wild type and diabetes model and rat obese and lean phenotypes. The fuzzy K‐means clustering method allowed more accurate sample classification in both datasets relative to the other tested methods including principal component analysis (PCA), hierarchical clustering (HCL) and K‐means clustering. In the cell line samples, fuzzy clustering provided a clear separation of individual cell lines, groups of cancer and normal cell lines as well as non‐invasive and invasive tumour cell lines. In the diabetes dataset, clear separation of healthy controls and diabetics in all three models was possible only by using the fuzzy clustering method. Copyright

Human Pax-5 C-terminal isoforms possess distinct transactivation properties and are differentially modulated in normal and malignant B cells.

The transcription factor Pax-5 occupies a central role in B cell differentiation and has been implicated in the development of B cell lymphoma. The transcriptional activation function of Pax-5 requires an intact N-terminal DNA-binding domain and is strongly influenced by the C-terminal transactivation domain. We report the identification and characterization of five human Pax-5 isoforms, which occur through the alternative splicing of exons that encode for the C-terminal transactivation domain. These isoforms arise from the inclusion or exclusion of exon 7, exon 8, and/or exon 9. Three of the Pax-5 isoforms generate novel protein sequences rich in proline, serine, and threonine amino acids that are the hallmarks of transactivation domains. The Pax-5 isoforms are expressed in peripheral blood mononuclear cells, cancerous and non-cancerous B cell lines, as well as in primary B cell lymphoma tissue. Electrophoretic mobility shift assays demonstrate that the isoforms possess specific DNA binding activity and recognize the PAX-5 consensus binding sites. In reporter assays using the CD19 promoter, the transactivation properties of the various isoforms were significantly influenced by the changes in the C-terminal protein sequence. Finally, we demonstrate, for the first time, that human Pax-5 isoform expression is modulated by specific signaling pathways in B lymphocytes.

1H NMR metabolomics analysis of the effect of dichloroacetate and allopurinol on breast cancers

Metabolomics analysis was used to determine the effect of two well known, non-proprietary metabolic modulators, dichloroacetate and allopurinol on breast cancer cell lines. Dichloroacetate, a pyruvate dehydrogenase kinase inhibitor and allopurinol, a xanthine oxidase/dehydrogenase inhibitor, have been previously explored as chemotherapeutics showing potential in some cancer subtypes while at the same time leading to unexpected increase in proliferation in others. In this work, metabolic effects of these drugs, applied singly and in combination, were explored in three different breast cell lines including cancer cells, MDA-MB-231 and MCF-7 and normal control cell line, MCF-10A. The metabolic changes induced by these drugs were monitored by (1)H NMR metabolic profiling. Analyses were performed on complete spectral data as well as quantified metabolic data in intracellular fractions and extracellular media leading to the determination of the most significantly affected metabolites. The effect of dichloroacetate and allopurinol is the most apparent in the metabolic profile of extracellular media. In MCF-7 cells, dichloroacetate treatment is dominant with only a minor observed influence of allopurinol in combined treatment. In MDA-MB-231 cells, both allopurinol and DCA lead to a metabolic shift with the allopurinol change dominating the effect of combined treatment. Results show the power of metabolomics as a tool for fast molecular profiling of drug effects in cells. In summary, treatments of breast cancer cells with DCA and allopurinol result in larger changes in metabolites found in extracellular medium than intracellular pools.