Jo Vandesompele

Bio: Jo Vandesompele is an academic researcher from Ghent University. The author has contributed to research in topics: Neuroblastoma & microRNA. The author has an hindex of 88, co-authored 383 publications receiving 59368 citations. Previous affiliations of Jo Vandesompele include Washington University in St. Louis & Ghent University Hospital.

Modulation of Neuroblastoma Disease Pathogenesis by an Extensive Network of Epigenetically Regulated microRNAs

Abstract: MicroRNAs (miRNAs) contribute to the pathogenesis of many forms of cancer, including the pediatric cancer neuroblastoma, but the underlying mechanisms leading to altered miRNA expression are often unknown. Here, a novel integrated approach for analyzing DNA methylation coupled with miRNA and mRNA expression data sets identified 67 epigenetically regulated miRNA in neuroblastoma. A large proportion (42%) of these miRNAs was associated with poor patient survival when underexpressed in tumors. Moreover, we demonstrate that this panel of epigenetically silenced miRNAs targets a large set of genes that are overexpressed in tumors from patients with poor survival in a highly redundant manner. The genes targeted by the epigenetically regulated miRNAs are enriched for a number of biological processes, including regulation of cell differentiation. Functional studies involving ectopic overexpression of several of the epigenetically silenced miRNAs had a negative impact on neuroblastoma cell viability, providing further support to the concept that inactivation of these miRNAs is important for neuroblastoma disease pathogenesis. One locus, miR-340, induced either differentiation or apoptosis in a cell context dependent manner, indicating a tumor suppressive function for this miRNA. Intriguingly, it was determined that miR-340 is upregulated by demethylation of an upstream genomic region that occurs during the process of neuroblastoma cell differentiation induced by all-trans retinoic acid (ATRA). Further biological studies of miR-340 revealed that it directly represses the SOX2 transcription factor by targeting of its 3'-untranslated region, explaining the mechanism by which SOX2 is downregulated by ATRA. Although SOX2 contributes to the maintenance of stem cells in an undifferentiated state, we demonstrate that miR-340-mediated downregulation of SOX2 is not required for ATRA induced differentiation to occur. In summary, our results exemplify the dynamic nature of the miRNA epigenome and identify a remarkable network of miRNA/mRNA interactions that significantly contribute to neuroblastoma disease pathogenesis.

Influence of microRNAs and Long Non-Coding RNAs in Cancer Chemoresistance

Abstract: Innate and acquired chemoresistance exhibited by most tumours exposed to conventional chemotherapeutic agents account for the majority of relapse cases in cancer patients. Such chemoresistance phenotypes are of a multi-factorial nature from multiple key molecular players. The discovery of the RNA interference pathway in 1998 and the widespread gene regulatory influences exerted by microRNAs (miRNAs) and other non-coding RNAs have certainly expanded the level of intricacy present for the development of any single physiological phenotype, including cancer chemoresistance. This review article focuses on the latest research efforts in identifying and validating specific key molecular players from the two main families of non-coding RNAs, namely miRNAs and long non-coding RNAs (lncRNAs), having direct or indirect influences in the development of cancer drug resistance properties and how such knowledge can be utilised for novel theranostics in oncology.

MYCN and ALKF1174L are sufficient to drive neuroblastoma development from neural crest progenitor cells.

Abstract: Neuroblastoma is an embryonal tumor with a heterogeneous clinical course. The tumor is presumed to be derived from the neural crest, but the cells of origin remain to be determined. To date, few recurrent genetic changes contributing to neuroblastoma formation, such as amplification of the MYCN oncogene and activating mutations of the ALK oncogene, have been identified. The possibility to model neuroblastoma in mice allows investigation of the cell of origin hypothesis in further detail. Here we present the evidence that murine neural crest progenitor cells can give rise to neuroblastoma upon transformation with MYCN or ALK(F1174L). For this purpose we used JoMa1, a multipotent neural crest progenitor cell line, which is kept in a viable and undifferentiated state by a tamoxifen-activated c-Myc transgene (c-MycER(T)). Expression of MYCN or ALK(F1174L), one of the oncogenic ALK variants identified in primary neuroblastomas, enabled these cells to grow independently of c-MycER(T) activity in vitro and caused formation of neuroblastoma-like tumors in vivo in contrast to parental JoMa1 cells and JoMa1 cells-expressing TrkA or GFP. Tumorigenicity was enhanced upon serial transplantation of tumor-derived cells, and tumor cells remained susceptible to the MYC-inhibitor, NBT-272, indicating that cell growth depended on functional MYCN. Our findings support neural crest progenitor cells as the precursor cells of neuroblastoma, and indicate that neuroblastomas arise as their malignant progeny.

Renal microRNA- and RNA-profiles in progressive chronic kidney disease

Abstract: Background MicroRNAs (miRNAs) contribute to chronic kidney disease (CKD) progression via regulating mRNAs involved in renal homeostasis. However, their association with clinical outcome remains poorly understood. Materials and methods We performed miRNA and mRNA expression profiling on renal biopsy sections by qPCR (miRNA) and microarrays (mRNA) in a discovery (n = 43) and in a validation (n = 29) cohort. miRNAs differentiating stable and progressive cases were inversely correlated with putative target mRNAs, which were further characterized by pathway analysis using KEGG pathways. Results miR-30d, miR-140-3p, miR-532-3p, miR-194, miR-190, miR-204 and miR-206 were downregulated in progressive cases. These seven miRNAs correlated with upregulated 29 target mRNAs involved in inflammatory response, cell–cell interaction, apoptosis and intra-cellular signalling. In particular, miR-206 and miR-532-3p were associated with distinct biological processes via the expression of their target mRNAs: Reduced expression of miR-206 in progressive disease correlated with the upregulation of target mRNAs participating in inflammatory pathways (CCL19, CXCL1, IFNAR2, NCK2, PTK2B, PTPRC, RASGRP1 and TNFRSF25). Progressive cases also showed a lower expression of miR-532-3p and an increased expression of target transcripts involved in apoptosis pathways (MAP3K14, TNFRSF10B/TRAIL-R2, TRADD and TRAF2). In the validation cohort, we confirmed the decreased expression of miR-206 and miR-532-3p, and the inverse correlation of these miRNAs with the expression of nine of the 12 target genes. The levels of the identified miRNAs and the target mRNAs correlated with clinical parameters and histological damage indices. Conclusions These results suggest the involvement of specific miRNAs and mRNAs in biological pathways associated with the progression of CKD.

Characteristic pattern of chromosomal gains and losses in Merkel cell carcinoma detected by comparative genomic hybridization.

Abstract: Merkel cell carcinoma or small cell carcinoma of the skin is a rare skin cancer seen in increasing numbers in Queensland, Australia. In its clinical course and histopathology, it resembles small cell lung carcinoma (SCLC). Little is known of the genetic basis of this disease except for a number of cytogenetic studies and three loss of heterozygosity studies. Therefore, comparative genomic hybridization was performed to determine the characteristic DNA gains and losses that occur in this tumor. Comparative genomic hybridization analysis of 34 specimens from 24 patients revealed a pattern of gains and losses that closely resembles that seen in SCLC. Overall frequent loss was seen for chromosomes 3p (46%), 5q (21%), 8p (21%), 10 (33%), 11q (17%), 13q (33%), and 17p (25%). Significant gains were seen for chromosomes 1 (63%), 3q (33%), 5p (38%), 8q (38%), 19 (63%), and X (41%), with smaller numbers having gains for chromosomes 6, 7, 20, and 21. In contrast to SCLC, amplification in Merkel cell carcinoma is a rare event.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

Cutadapt removes adapter sequences from high-throughput sequencing reads

Abstract: When small RNA is sequenced on current sequencing machines, the resulting reads are usually longer than the RNA and therefore contain parts of the 3' adapter. That adapter must be found and removed error-tolerantly from each read before read mapping. Previous solutions are either hard to use or do not offer required features, in particular support for color space data. As an easy to use alternative, we developed the command-line tool cutadapt, which supports 454, Illumina and SOLiD (color space) data, offers two adapter trimming algorithms, and has other useful features. Cutadapt, including its MIT-licensed source code, is available for download at http://code.google.com/p/cutadapt/

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes

Abstract: Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem. We outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data. The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which, among other things, opens up the possibility of studying the biological relevance of small expression differences.