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Showing papers by "Jo Vandesompele published in 2017"


Journal ArticleDOI
Jan Van Deun, Pieter Mestdagh1, Patrizia Agostinis, Özden Akay, Sushma Anand2, Jasper Anckaert1, Zoraida Andreu Martinez, Tine Baetens, Els Beghein, Laurence Bertier, Geert Berx, Janneke Boere3, Stephanie Boukouris2, Michel Bremer, Dominik Buschmann, James Brian Byrd, Clara Casert, Lesley Cheng2, Anna Cmoch, Delphine Daveloose, Eva De Smedt, Seyma Demirsoy, Victoria Depoorter, Bert Dhondt, Tom A. P. Driedonks, Aleksandra M. Dudek, Abdou ElSharawy, Ilaria Floris, Andrew D Foers, Kathrin Gärtner, Abhishek D. Garg, Edward Geeurickx, Jan Gettemans, Farzaneh Ghazavi1, Bernd Giebel, Tom Groot Kormelink, Grace V. Hancock, Hetty Helsmoortel1, Andrew F. Hill2, Vincent Hyenne, Hina Kalra2, David Kim, Joanna Kowal4, Joanna Kowal5, Sandra Kraemer, Petra Leidinger, Carina Leonelli1, Yaxuan Liang, Lien Lippens, Shu Liu6, Alessandra Lo Cicero4, Alessandra Lo Cicero7, Shaun Martin, Suresh Mathivanan2, Prabhu Mathiyalagan, Tamás Matusek7, Gloria Milani1, Marta Monguió-Tortajada, Liselot Mus1, Dillon C. Muth, Andrea Németh, Esther N. M. Nolte-‘t Hoen, Lorraine O'Driscoll, Roberta Palmulli7, Roberta Palmulli4, Michael W. Pfaffl, Bjarke Primdal-Bengtson5, Bjarke Primdal-Bengtson4, Erminia Romano, Quentin Rousseau, Susmita Sahoo, Natalia G. Sampaio, Monisha Samuel2, Benjamin J. Scicluna2, Bieke Soen, Anneleen Steels, Johannes V. Swinnen8, Maarit Takatalo, Safia Thaminy, Clotilde Théry5, Clotilde Théry4, Joeri Tulkens, Isabel Van Audenhove, Susanne G. van der Grein, Alan Van Goethem1, Martijn J. C. van Herwijnen, Guillaume van Niel7, Guillaume van Niel4, Nadine Van Roy1, Alexander R. van Vliet, Niels Vandamme, Suzanne Vanhauwaert1, Glenn Vergauwen, Frederik J. Verweij7, Frederik J. Verweij4, Annelynn Wallaert1, Marca H. M. Wauben, Kenneth W. Witwer, Marijke I. Zonneveld, Olivier De Wever, Jo Vandesompele1, An Hendrix 
TL;DR: It is argued that the field of extracellular vesicle (EV) biology needs more transparent reporting to facilitate interpretation and replication of experiments and EV-TRACK, a crowdsourcing knowledgebase that centralizes EV biology and methodology, is described.
Abstract: We argue that the field of extracellular vesicle (EV) biology needs more transparent reporting to facilitate interpretation and replication of experiments. To achieve this, we describe EV-TRACK, a crowdsourcing knowledgebase (http://evtrack.org) that centralizes EV biology and methodology with the goal of stimulating authors, reviewers, editors and funders to put experimental guidelines into practice.

777 citations


Journal ArticleDOI
TL;DR: In this Article, Yvan Saeys is incorrectly listed as being affiliated with ‘Department of Biomedical Molecular Biology Ghent University, Ghent, Belgium’.
Abstract: Scientific Reports 6: Article number: 36111; published online: 26 October 2016; updated: 24 January 2017 In this Article, Yvan Saeys is incorrectly listed as being affiliated with ‘Department of Biomedical Molecular Biology Ghent University, Ghent, Belgium’. The correct affiliations are listed below:

178 citations


Journal ArticleDOI
TL;DR: In vitro and in vivo perturbation of miR‐218‐5p combined with RNA sequencing and gene set enrichment analysis was used to elucidate its functional role in COPD pathogenesis and highlight a role for miR-218‐ 5p in the pathogenesis of COPD.
Abstract: Rationale: Aberrant expression of microRNAs (miRNAs) can have a detrimental role in disease pathogenesis.Objectives: To identify dysregulated miRNAs in lung tissue of patients with chronic obstructive pulmonary disease (COPD).Methods: We performed miRNA and mRNA profiling using high throughput stem-loop reverse-transcriptase quantitative polymerase chain reaction and mRNA microarray, respectively, on lung tissue of 30 patients (screening cohort) encompassing 8 never-smokers, 10 smokers without airflow limitation, and 12 smokers with COPD. Differential expression of miRNA-218-5p (miR-218-5p) was validated by reverse-transcriptase quantitative polymerase chain reaction in an independent cohort of 71 patients, an in vivo murine model of COPD, and primary human bronchial epithelial cells. Localization of miR-218-5p was assessed by in situ hybridization. In vitro and in vivo perturbation of miR-218-5p combined with RNA sequencing and gene set enrichment analysis was used to elucidate its functional role in COP...

107 citations


Journal ArticleDOI
03 Mar 2017-Genes
TL;DR: 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-codingRNAs, 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.
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.

88 citations


Journal ArticleDOI
TL;DR: In this paper, the authors used an orthotopic preclinical model of lung cancer to dissect how the lung tumor micro-environment affects tissue-resident Dendritic cells (DCs) and extract novel biologically and clinically relevant information.
Abstract: Targeting immunomodulatory pathways has ushered a new era in lung cancer therapy. Further progress requires deeper insights into the biology of immune cells in the lung cancer micro-environment. Dendritic cells (DCs) represent a heterogeneous and highly plastic immune cell system with a central role in controlling immune responses. The intratumoral infiltration and activation status of DCs are emerging as clinically relevant parameters in lung cancer. In this study, we used an orthotopic preclinical model of lung cancer to dissect how the lung tumor micro-environment affects tissue-resident DCs and extract novel biologically and clinically relevant information. Lung tumor-infiltrating leukocytes expressing generic DC markers were found to predominantly consist of CD11b+ cells that, compare with peritumoral lung DC counterparts, strongly overexpress the T-cell inhibitory molecule PD-L1 and acquire classical surface markers of tumor-associated macrophages (TAMs). Transcriptome analysis of these CD11b+ tumor-infiltrating DCs (TIDCs) indicates impaired antitumoral immunogenicity, confirms the skewing toward TAM-related features, and indicates exposure to a hypoxic environment. In parallel, TIDCs display a specific microRNA (miRNA) signature dominated by the prototypical lung cancer oncomir miR-31. In vitro, hypoxia drives intrinsic miR-31 expression in CD11b+ DCs. Conditioned medium of miR-31 overexpressing CD11b+ DCs induces pro-invasive lung cancer cell shape changes and is enriched with pro-metastatic soluble factors. Finally, analysis of TCGA datasets reveals that the TIDC-associated miRNA signature has a negative prognostic impact in non-small cell lung cancer. Together, these data suggest a novel mechanism through which the lung cancer micro-environment exploits the plasticity of the DC system to support tumoral progression.

52 citations


Journal ArticleDOI
TL;DR: Results suggest that miR-184 may act as a downstream effector of albuminuria through LPP3 to promote tubulointerstitial fibrosis, and offer the rationale to investigate whether targeting miR -184 in association withalbuminuria-lowering drugs may be a new strategy to achieve fully anti-fibrotic effects in diabetic nephropathy.
Abstract: Renal fibrosis is a common complication of diabetic nephropathy and is a major cause of end-stage renal disease. Despite the suggested link between renal fibrosis and microRNA (miRNA) dysregulation in diabetic nephropathy, the identification of the specific miRNAs involved is still incomplete. The aim of this study was to investigate miRNA profiles in the diabetic kidney and to identify potential downstream targets implicated in renal fibrosis. miRNA expression profiling was investigated in the kidneys of 8-month-old Zucker diabetic fatty (ZDF) rats during overt nephropathy. Localisation of the most upregulated miRNA was established by in situ hybridisation. The candidate miRNA target was identified by in silico analysis and its expression documented in the diabetic kidney associated with fibrotic markers. Cultured tubule cells served to assess which of the profibrogenic stimuli acted as a trigger for the overexpressed miRNA, and to investigate underlying epigenetic mechanisms. In ZDF rats, miR-184 showed the strongest differential upregulation compared with lean rats (18-fold). Tubular localisation of miR-184 was associated with reduced expression of lipid phosphate phosphatase 3 (LPP3) and collagen accumulation. Transfection of NRK-52E cells with miR-184 mimic reduced LPP3, promoting a profibrotic phenotype. Albumin was a major trigger of miR-184 expression. Anti-miR-184 counteracted albumin-induced LPP3 downregulation and overexpression of plasminogen activator inhibitor-1. In ZDF rats, ACE-inhibitor treatment limited albuminuria and reduced miR-184, with tubular LPP3 preservation and tubulointerstitial fibrosis amelioration. Albumin-induced miR-184 expression in tubule cells was epigenetically regulated through DNA demethylation and histone lysine acetylation and was accompanied by binding of NF-κB p65 subunit to miR-184 promoter. These results suggest that miR-184 may act as a downstream effector of albuminuria through LPP3 to promote tubulointerstitial fibrosis, and offer the rationale to investigate whether targeting miR-184 in association with albuminuria-lowering drugs may be a new strategy to achieve fully anti-fibrotic effects in diabetic nephropathy.

46 citations


Journal ArticleDOI
TL;DR: A model-based clustering method is introduced to estimate the probability that the target is present (absent) in a partition conditional on its observed fluorescence and the distributional shape in no-template control samples, providing a natural measure of precision, both at individual partition level and at the level of the global concentration.
Abstract: Standard data analysis pipelines for digital PCR estimate the concentration of a target nucleic acid by digitizing the end-point fluorescence of the parallel micro-PCR reactions, using an automated hard threshold. While it is known that misclassification has a major impact on the concentration estimate and substantially reduces accuracy, the uncertainty of this classification is typically ignored. We introduce a model-based clustering method to estimate the probability that the target is present (absent) in a partition conditional on its observed fluorescence and the distributional shape in no-template control samples. This methodology acknowledges the inherent uncertainty of the classification and provides a natural measure of precision, both at individual partition level and at the level of the global concentration. We illustrate our method on genetically modified organism, inhibition, dynamic range, and mutation detection experiments. We show that our method provides concentration estimates of similar ...

34 citations


Journal ArticleDOI
TL;DR: This work systematically excludes possible technical reasons underlying the absence of lncRNA-encoded proteins in mass spectrometry data sets, strongly suggesting that the large majority of lNCRNAs is indeed not translated.
Abstract: Over the past decade, long noncoding RNAs (lncRNAs) have emerged as novel functional entities of the eukaryotic genome. However, the scientific community remains divided over the amount of true noncoding transcripts among the large number of unannotated transcripts identified by recent large scale and deep RNA-sequencing efforts. Here, we systematically exclude possible technical reasons underlying the absence of lncRNA-encoded proteins in mass spectrometry data sets, strongly suggesting that the large majority of lncRNAs is indeed not translated.

34 citations


Journal ArticleDOI
TL;DR: This work presents 13 lncRNA genes involved in the pathogenesis of cutaneous melanoma through a variety of pathways and molecular interactions and suggests some of these lncRNAs are possible biomarkers or therapeutic targets for malignant melanoma.
Abstract: Metastatic melanoma of the skin has a high mortality despite the recent introduction of targeted therapy and immunotherapy. Long non-coding RNAs (lncRNAs) are defined as transcripts of more than 200 nucleotides in length that lack protein-coding potential. There is growing evidence that lncRNAs play an important role in gene regulation, including oncogenesis. We present 13 lncRNA genes involved in the pathogenesis of cutaneous melanoma through a variety of pathways and molecular interactions. Some of these lncRNAs are possible biomarkers or therapeutic targets for malignant melanoma.

33 citations


Journal ArticleDOI
01 Jan 2017-Database
TL;DR: DecodeRNA as mentioned in this paper provides functional contexts for both human lncRNAs and microRNAs in 29 cancer and 12 normal tissue types with state-of-the-art data mining and visualization options, easy access to results and a straightforward user interface.
Abstract: Although the long non-coding RNA (lncRNA) landscape is expanding rapidly, only a small number of lncRNAs have been functionally annotated. Here, we present decodeRNA (http://www.decoderna.org), a database providing functional contexts for both human lncRNAs and microRNAs in 29 cancer and 12 normal tissue types. With state-of-the-art data mining and visualization options, easy access to results and a straightforward user interface, decodeRNA aims to be a powerful tool for researchers in the ncRNA field.

21 citations


Journal ArticleDOI
TL;DR: The venetoclax/idasanutlin combination was consistently found to be highly synergistic in a diverse panel of neuroblastoma cell lines, including cells with high MCL1 expression levels and a more pronounced induction of apoptosis was found to underlie the synergistic interaction.
Abstract: Wild-type p53 tumor suppressor activity in neuroblastoma tumors is hampered by increased MDM2 activity, making selective MDM2 antagonists an attractive therapeutic strategy for this childhood malignancy. Since monotherapy in cancer is generally not providing long-lasting clinical responses, we here aimed to identify small molecule drugs that synergize with idasanutlin (RG7388). To this purpose we evaluated 15 targeted drugs in combination with idasanutlin in three p53 wild type neuroblastoma cell lines and identified the BCL2 inhibitor venetoclax (ABT-199) as a promising interaction partner. The venetoclax/idasanutlin combination was consistently found to be highly synergistic in a diverse panel of neuroblastoma cell lines, including cells with high MCL1 expression levels. A more pronounced induction of apoptosis was found to underlie the synergistic interaction, as evidenced by caspase-3/7 and cleaved PARP measurements. Mice carrying orthotopic xenografts of neuroblastoma cells treated with both idasanutlin and venetoclax had drastically lower tumor weights than mice treated with either treatment alone. In conclusion, these data strongly support the further evaluation of dual BCL2/MDM2 targeting as a therapeutic strategy in neuroblastoma.

Journal ArticleDOI
TL;DR: The expression of HNRNPU processed transcript was increased in PDAC cell lines compared to noncancerous pancreatic cell lines; knockdown of this lncRNA further reduces proliferation and invasion/migration of pancreatic carcinoma cells.
Abstract: A gene array was used to profile the expression of 22,875 long non-coding RNAs (lncRNAs) and a large number of protein coding genes in 47 specimens of pancreatic ductal adenocarcinoma (PDAC), adjacent benign pancreas and the pancreas from patients without pancreatic disease. Of the lncRNAs profiled, the expression of 126 were significantly increased and 260 were decreased in the tumors (p < 0.05, 2-fold). The expression of one lncRNA in particular, heterogeneous nuclear ribonucleoprotein U (HNRNPU) processed transcript (also known as ncRNA00201) was among the most significantly deregulated (increased four-fold) in the tumors compared to normal/adjacent benign tissues. Increased expression of HNRNPU processed transcript was associated with poor prognosis for patients with PDAC. The expression of HNRNPU processed transcript was increased in PDAC cell lines compared to noncancerous pancreatic cell lines. LNATM gapmer mediated inhibition of HNRNPU processed transcript reduced cell proliferation in Patu-T and PL45 pancreatic cancer cell lines. Reduced invasion and migration was reported upon HNRNPU processed transcript knockdown in Patu-T cells. Small interfering RNA (siRNA) knockdown of the HNRNPU protein coding gene correlated with a 55% reduction in the HNRNPU processed transcript expression and a corresponding reduction in proliferation of Patu-T and PL45 cells. However, gapmer inhibition of HNRNPU processed transcript did not affect HNRNPU mRNA levels. The lncRNA HNRNPU processed transcript expression is increased in both PDAC tissues and cell lines; knockdown of this lncRNA further reduces proliferation and invasion/migration of pancreatic carcinoma cells.

Journal ArticleDOI
TL;DR: PrimerXL is an state-of-the-art, easy to use primer design webtool capable of generating high-quality targeted resequencing assays, and outperforming other target enrichment strategies and similar primer design tools when considering assay quality, coverage uniformity and target coverage.
Abstract: Although the sequencing landscape is rapidly evolving and sequencing costs are continuously decreasing, whole genome sequencing is still too expensive for use on a routine basis. Targeted resequencing of only the regions of interest decreases both costs and the complexity of the downstream data-analysis. Various target enrichment strategies are available, but none of them obtain the degree of coverage uniformity, flexibility and specificity of PCR-based enrichment. On the other hand, the biggest limitation of target enrichment by PCR is the need to design large numbers of partially overlapping assays to cover the target. To overcome the aforementioned hurdles, we have developed primerXL, a state-of-the-art PCR primer design pipeline for targeted resequencing. It uses an optimized design criteria relaxation cascade and a thorough downstream in silico evaluation process to generate high quality singleplex PCR assays, reducing the need for amplicon normalization, and outperforming other target enrichment strategies and similar primer design tools when considering assay quality, coverage uniformity and target coverage. Results of four different sequencing projects with 2348 amplicons in total covering 470 kb are presented. PrimerXL can be accessed at www.primerxl.org . PrimerXL is an state-of-the-art, easy to use primer design webtool capable of generating high-quality targeted resequencing assays. The workflow is fully customizable to suit every researchers’ needs, while an innovative relaxation cascade ensures maximal target coverage.

Journal ArticleDOI
TL;DR: The value of a highly optimized qPCR for the relative quantification of isoforms is shown, but cost efficiency and simplicity turned out to be better for RT-qPCR.

Journal ArticleDOI
TL;DR: This work characterizes the specific breast CAAT protein secretome and reveals its pro-proliferative potency in breast cancer.
Abstract: // Lapeire Lore 1, 2 , Hendrix An 2, 3 , Lecoutere Evelyne 4 , Van Bockstal Mieke 4 , Vandesompele Jo 2, 5 , Maynard Dawn 6 , Braems Geert 7 , Van Den Broecke Rudy 7 , Muller Catherine 8 , Bracke Marc 3 , Cocquyt Veronique 1 , Denys Hannelore 1, 2 and De Wever Olivier 2, 3 1 Department of Medical Oncology, Ghent University Hospital, Ghent, Belgium 2 Cancer Research Institute Ghent (CRIG), Ghent University Hospital, Ghent, Belgium 3 Laboratory of Experimental Cancer Research, Department of Radiation Oncology and Experimental Cancer Research, Ghent University Hospital, Ghent, Belgium 4 Department of Pathology, Ghent University Hospital, Ghent, Belgium 5 Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium 6 Medical Genetics Branch, National Human Genome Research Institute, Bethesda, Maryland, USA 7 Department of Gynecology, Ghent University Hospital, Ghent, Belgium 8 Institut de Pharmacologie et de Biologie Structurale, Universite de Toulouse, UPS, Toulouse, France Correspondence to: De Wever Olivier, email: olivier.dewever@ugent.be Keywords: adipose tissue, breast cancer, proliferation, secretome, palbociclib Received: November 01, 2016 Accepted: April 17, 2017 Published: May 03, 2017 ABSTRACT Adipose tissue secretes a plethora of adipokines as evidenced by characterization of subcutaneous and visceral adipose tissue secretomes. However, adipose tissue composition and secretion pattern is depot and disease dependent, influencing the adipose tissue secretome. We investigated the secretome of cancer-associated adipose tissue (CAAT) explants from breast cancer patients and explored its role in breast cancer proliferation. CAAT proteins were identified by LC-MS/MS and human protein antibody arrays and stimulated proliferation of three breast cancer cell lines. Kinomics and transcriptomics of MCF-7 breast cancer cells treated with the secretome of CAAT revealed activation of Akt-, ERK- and JNK-pathways and differential expression of activator protein 1 (AP-1) and cAMP responsive element-binding protein (CREB) target genes. The cyclin-dependent kinase (CDK)4/6-inhibitor palbociclib significantly abrogated CAAT-enhanced breast cancer cell proliferation. Our work characterizes the specific breast CAAT protein secretome and reveals its pro-proliferative potency in breast cancer.

Journal ArticleDOI
TL;DR: It is found that a robust weighted least-squares approach is highly advisable, yet may also suffer from an inflated false-positive rate and the proposed assessments are also applicable to other analyses, such as the comparison of results obtained from qPCR and dPCR.
Abstract: Digital polymerase chain reaction (digital PCR, dPCR) is a direct nucleic acid quantification method, thus requiring no standard curves unlike quantitative real-time PCR (qPCR). Nevertheless, evaluation of the linear dynamic range, accuracy, and precision of an assay or platform is recommended, as there are several potential causes of important non-linearity, bias, and imprecision. Ignoring these quality issues may lead to erroneous quantification. This necessitates an approach akin to the construction of standard curves. We study the pitfalls associated with the evaluation of such an experiment, and provide guidelines for the assessment of linearity, accuracy, and precision in dPCR experiments. We present simulation results and a case study supporting the importance of a thorough evaluation. Further, typically presented plots and statistics may not reveal problems with linearity, accuracy, or precision. We find that a robust weighted least-squares approach is highly advisable, yet may also suffer from an inflated false-positive rate. The proposed assessments are also applicable to other analyses, such as the comparison of results obtained from qPCR and dPCR. A web tool for quality evaluation, dPCalibRate, is available.

Journal ArticleDOI
17 Aug 2017-PLOS ONE
TL;DR: This work proposes a novel method that unites preprocessing and differential expression analysis in a single statistical model that provides a rigorous way for handling undetermined Cq values and shows that this method outperforms traditional RT-qPCR differential expressionAnalysis pipelines in the presence of undetermined values, both in terms of accuracy and precision.
Abstract: Reverse transcription quantitative polymerase chain reaction (RT-qPCR) is considered as the gold standard for accurate, sensitive, and fast measurement of gene expression. Prior to downstream statistical analysis, RT-qPCR fluorescence amplification curves are summarized into one single value, the quantification cycle (Cq). When RT-qPCR does not reach the limit of detection, the Cq is labeled as "undetermined". Current state of the art qPCR data analysis pipelines acknowledge the importance of normalization for removing non-biological sample to sample variation in the Cq values. However, their strategies for handling undetermined Cq values are very ad hoc. We show that popular methods for handling undetermined values can have a severe impact on the downstream differential expression analysis. They introduce a considerable bias and suffer from a lower precision. We propose a novel method that unites preprocessing and differential expression analysis in a single statistical model that provides a rigorous way for handling undetermined Cq values. We compare our method with existing approaches in a simulation study and on published microRNA and mRNA gene expression datasets. We show that our method outperforms traditional RT-qPCR differential expression analysis pipelines in the presence of undetermined values, both in terms of accuracy and precision.

Journal ArticleDOI
TL;DR: The Zipper plot as discussed by the authors is a visualization and analysis method that enables users to simultaneously interrogate thousands of human putative transcription start sites (TSSs) in relation to various features that are indicative for transcriptional activity.
Abstract: Reconstructing transcript models from RNA-sequencing (RNA-seq) data and establishing these as independent transcriptional units can be a challenging task. Current state-of-the-art tools for long non-coding RNA (lncRNA) annotation are mainly based on evolutionary constraints, which may result in false negatives due to the overall limited conservation of lncRNAs. To tackle this problem we have developed the Zipper plot, a novel visualization and analysis method that enables users to simultaneously interrogate thousands of human putative transcription start sites (TSSs) in relation to various features that are indicative for transcriptional activity. These include publicly available CAGE-sequencing, ChIP-sequencing and DNase-sequencing datasets. Our method only requires three tab-separated fields (chromosome, genomic coordinate of the TSS and strand) as input and generates a report that includes a detailed summary table, a Zipper plot and several statistics derived from this plot. Using the Zipper plot, we found evidence of transcription for a set of well-characterized lncRNAs and observed that fewer mono-exonic lncRNAs have CAGE peaks overlapping with their TSSs compared to multi-exonic lncRNAs. Using publicly available RNA-seq data, we found more than one hundred cases where junction reads connected protein-coding gene exons with a downstream mono-exonic lncRNA, revealing the need for a careful evaluation of lncRNA 5′-boundaries. Our method is implemented using the statistical programming language R and is freely available as a webtool.

Journal ArticleDOI
TL;DR: In this paper, the authors evaluated the circulating AR gene copy number (CN) gain using droplet digital polymerase chain reaction in 21 control and 91 prostate cancer serum samples and its prognostic and therapeutic implications in prostate cancer.

Journal ArticleDOI
TL;DR: The further genomic characterization through exome sequencing and DNA copy number analysis of four of the currently available murine neuroblastoma model systems supports the validity of the tested mouse models for mechanistic and preclinical studies of human Neuroblastoma.
Abstract: // Bram De Wilde 1, 2 , Anneleen Beckers 1 , Sven Lindner 3 , Althoff Kristina 3 , Katleen De Preter 1, 2 , Pauline Depuydt 1, 2 , Pieter Mestdagh 1, 2 , Tom Sante 1 , Steve Lefever 1, 2 , Falk Hertwig 4, 5 , Zhiyu Peng 6 , Le-Ming Shi 7 , Sangkyun Lee 8 , Elien Vandermarliere 9, 10 , Lennart Martens 9, 10 , Bjorn Menten 1 , Alexander Schramm 3 , Matthias Fischer 4, 5 , Johannes Schulte 11 , Jo Vandesompele 1, 2 and Frank Speleman 1, 2 1 Center for Medical Genetics, Ghent University, Ghent, Belgium 2 Cancer Research Institute Ghent, Ghent University, Ghent, Belgium 3 Department of Pediatric Oncology and Hematology, University Children’s Hospital, Essen, Germany 4 Department of Experimental Pediatric Oncology, University Children's Hospital of Cologne, Cologne, Germany 5 Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany 6 BGI-Shenzhen, Bei Shan Industrial Zone, Yantian District, Shenzhen, Guangdong, China 7 Center for Pharmacogenomics and Fudan-Zhangjiang Center for Clinical Genomics, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China 8 Department of Computer Science, Artificial Intelligence Group, TU Dortmund, Dortmund, Germany 9 Medical Biotechnology Center, VIB, Ghent, Belgium 10 Department of Biochemistry, Ghent University, Ghent, Belgium 11 Pediatric Oncology and Hematology, Charite University Medicine, Berlin, Germany Correspondence to: Frank Speleman, email: Franki.Speleman@UGent.be Keywords: neuroblastoma; mouse model; exome sequencing; array CGH Received: March 01, 2017 Accepted: October 28, 2017 Published: December 22, 2017 ABSTRACT Genetically engineered mouse models have proven to be essential tools for unraveling fundamental aspects of cancer biology and for testing novel therapeutic strategies. To optimally serve these goals, it is essential that the mouse model faithfully recapitulates the human disease. Recently, novel mouse models for neuroblastoma have been developed. Here, we report on the further genomic characterization through exome sequencing and DNA copy number analysis of four of the currently available murine neuroblastoma model systems ( ALK, Th- MYCN, Dbh- MYCN and Lin28b ). The murine tumors revealed a low number of genomic alterations – in keeping with human neuroblastoma - and a positive correlation of the number of genetic lesions with the time to onset of tumor formation was observed. Gene copy number alterations are the hallmark of both murine and human disease and frequently affect syntenic genomic regions. Despite low mutational load, the genes mutated in murine disease were found to be enriched for genes mutated in human disease. Taken together, our study further supports the validity of the tested mouse models for mechanistic and preclinical studies of human neuroblastoma.

Journal ArticleDOI
25 May 2017-PLOS ONE
TL;DR: A novel thermodynamics approach is introduced and a framework to exploit the specific detection capabilities of nucleic acid hybridization, using generic principles applicable to any platform is developed, with many potential applications in molecular diagnostics and the field of personalised medicine.
Abstract: The knowledge of genomic DNA variations in patient samples has a high and increasing value for human diagnostics in its broadest sense Although many methods and sensors to detect or quantify these variations are available or under development, the number of underlying physico-chemical detection principles is limited One of these principles is the hybridization of sample target DNA versus nucleic acid probes We introduce a novel thermodynamics approach and develop a framework to exploit the specific detection capabilities of nucleic acid hybridization, using generic principles applicable to any platform As a case study, we detect point mutations in the KRAS oncogene on a microarray platform For the given platform and hybridization conditions, we demonstrate the multiplex detection capability of hybridization and assess the detection limit using thermodynamic considerations; DNA containing point mutations in a background of wild type sequences can be identified down to at least 1% relative concentration In order to show the clinical relevance, the detection capabilities are confirmed on challenging formalin-fixed paraffin-embedded clinical tumor samples This enzyme-free detection framework contains the accuracy and efficiency to screen for hundreds of mutations in a single run with many potential applications in molecular diagnostics and the field of personalised medicine

Proceedings ArticleDOI
TL;DR: The EV-TRACK platform aims to ensure that experimental guidelines are timely and transparently met, improving the validation of extracellular vesicle biomarkers in cancer research and involves users in decision-making on future improvements to the platform.
Abstract: Extracellular vesicles (EVs), also termed exosomes, mediate communication between cells and organisms through local and distant transport of proteins, nucleic acids and lipids. EVs are reported as biomarkers in cancer. However, transparent reporting is a prerequisite to facilitate interpretation and validation of EV biomarkers in cancer. We convened an international consortium to develop a resource to improve the rigor and interpretation of experiments, record the evolution of EV research and create a dialogue with researchers about relevant experimental parameters. We analyzed 1226 articles with keywords “exosomes” or “extracellular vesicles” published in 2010-2015. Publications that included multiple sample types or isolation methods were separated into multiple entries, resulting in 1742 experiments. Experiments were analyzed using a matrix containing 115 parameters related to sample type, EV isolation and characterization methods. The database is freely accessible and expandable, allowing online deposition of new experiments (http://evtrack.org). To assess current practice in EV experiments, we performed an in-depth analysis of recorded data in the EV-TRACK knowledgebase. This revealed heterogeneity in EV isolation methods and inconsistent reporting of experimental parameters. Differential ultracentrifugation is the most used method (>50%) but with a large heterogeneity in centrifugation steps. In less than 20% of experiments a density gradient was implemented to obtain or at least validate results. Quality controls are often omitted, with more than 2 proteins being checked in 40% and non-EV enriched proteins in less than 15% of experiments (dependent on sample type). From these analyses, 9 relevant experimental parameters were extracted and condensed into a single metric, the EV-METRIC (to MEasure Transparent Reporting of Isolation and Characterization methods). It represents a checklist to assess the completeness of reporting of generic and method-specific information necessary to interpret and validate an experiment. The EV-TRACK platform is a knowledge center for EV biology and methodology that allows data queries, coaches users by providing EV-METRICs and involves them in decision-making on future improvements to the platform. In conclusion, established for and supported by the EV research community, the EV-TRACK platform aims to ensure that experimental guidelines are timely and transparently met, improving the validation of EV biomarkers in cancer. Citation Format: Jan Van Deun, Pieter Mestdagh, Olivier De Wever, Jo Vandesompele, An Hendrix. EV-TRACK: transparent reporting and centralizing knowledge of extracellular vesicles to support the validation of extracellular vesicle biomarkers in cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-107. doi:10.1158/1538-7445.AM2017-LB-107

Posted ContentDOI
16 Nov 2017-bioRxiv
TL;DR: The linear modeling with empirical Bayes moderation and the nonparametric approach (SAMSeq) showed best performance: good control of the false discovery rate (FDR) and reasonable sensitivity, however, for achieving a sensitivity of at least 50%, more than 80 samples are required when studying expression levels in a realistic clinical settings such as in cancer research.
Abstract: Background: Protein-coding RNAs (mRNA) have been the primary target of most transcriptome studies in the past, but in recent years, attention has expanded to include long non-coding RNAs (lncRNA). lncRNAs are typically expressed at low levels, and are inherently highly variable. This is a fundamental challenge for differential expression (DE) analysis. In this study, the performance of 14 popular tools for testing DE in RNA-seq data along with their normalization methods is comprehensively evaluated, with a particular focus on lncRNAs and low abundant mRNAs. Results: Thirteen performance metrics were used to evaluate DE tools and normalization methods using simulations and analyses of six diverse RNA-seq datasets. Non-parametric procedures are used to simulate gene expression data in such a way that realistic levels of expression and variability are preserved in the simulated data. Throughout the assessment, we kept track of the results for mRNA and lncRNA separately. All statistical models exhibited inferior performance for lncRNAs compared to mRNAs across all simulated scenarios and analysis of benchmark RNA-seq datasets. No single tool uniformly outperformed the others. Conclusion: Overall, the linear modeling with empirical Bayes moderation (limma) and the nonparametric approach (SAMSeq) showed best performance: good control of the false discovery rate (FDR) and reasonable sensitivity. However, for achieving a sensitivity of at least 50\%, more than 80 samples are required when studying expression levels in a realistic clinical settings such as in cancer research. About half of the methods showed severe excess of false discoveries, making these methods unreliable for differential expression analysis and jeopardizing reproducible science. The detailed results of our study can be consulted through a user-friendly web application, http://statapps.ugent.be/tools/AppDGE/ .


Book ChapterDOI
TL;DR: This chapter presents two different technologies for miRNA quantification: small RNA sequencing and RT-qPCR.
Abstract: miRNAs are small noncoding RNA molecules that function as regulators of gene expression. Deregulated miRNA expression has been reported in various diseases including cancer. Due to their small size and high degree of homology, accurate quantification of miRNA expression is technically challenging. In this chapter, we present two different technologies for miRNA quantification: small RNA sequencing and RT-qPCR.


01 Jan 2017
TL;DR: The results demonstrate the efficacy of SAMMSON inhibition as a novel treatment option for uveal melanoma and demonstrate its synergism with MEK inhibition making SAMMSon a promising anti-cancer target for uvo melanoma patients.
Abstract: Uveal melanoma is the most common intraocular malignancy in adults. The lack of an effective treatment results in a median survival time less than one year for patients with metastatic disease. Recently, our lab identified the melanoma-specific long non-coding RNA (lncRNA) SAMMSON as a novel therapeutic target in skin melanoma. Analysis of a PAN cancer RNA-sequencing dataset revealed consistent expression of SAMMSON in uveal melanoma tumors. Although SAMMSON expression was lower in uveal compared to skin melanoma, over 90% of uveal melanoma tumors showed detectable SAMMSON expression. Further analysis also revealed SAMMSON expression in conjunctival melanoma, another form of ocular melanoma. To evaluate the therapeutic potential of SAMMSON inhibition in uveal and conjunctival melanoma, we treated 8 representative cell lines with SAMMSON-specific ASOs and observed a strong reduction in cell viability, accompanied by induction of apoptosis. In line with the role of SAMMSON in modulating mitochondrial metabolism, SAMMSON knock down resulted in decreased mitochondrial oxygen consumption. Uveal melanomas are characterized by activated MEK-signaling through mutations in GNA11/GNAQ. Combining SAMMSON-specific ASOs with the MEK-inhibitor Trametinib, induced strong synergistic effects, resulting in a nearly complete abrogation of tumor cells at nanomolar concentrations of Trametinib. The in vivo effects of SAMMSON inhibition, whether or not in combination with Trametinib, are currently being investigated in a uveal melanoma PDX model. Together, our results demonstrate the efficacy of SAMMSON inhibition as a novel treatment option for uveal melanoma and demonstrate its synergism with MEK inhibition making SAMMSON a promising anti-cancer target for uveal melanoma patients.


01 Jan 2017
TL;DR: It is demonstrated that lncRNAs add a new dimension to the HIV-host interplay and exhibit an independent transcriptionally regulated response.
Abstract: Studying the effects of HIV infection on the host transcriptome has typically focused on protein-coding genes. However, recent advances in the field of RNA sequencing revealed that long non-coding RNAs (lncRNAs) add an extensive additional layer to the cell’s molecular network and are crucial for normal cellular function. lncRNAs exert the ability to control a wide range of (post-)transcriptional processes and offer unique possibilities for pathogens like HIV to hijack the cellular machinery and reshape gene expression in their favor. Therefore, lncRNA discovery can result in new insights into the HIV-host interplay. We performed transcriptome profiling throughout a characterized primary HIV infection in vitro to investigate lncRNA expression at the different HIV replication cycle processes (reverse transcription, integration and particle production). Subsequently, guilt-by-association, transcription factor and co-expression analysis were performed to infer biological roles for the lncRNAs identified in the HIV-host interplay. Throughout the HIV replication cycle we identified 387 lncRNAs that were differentially expressed with the majority observed at the viral integration phase. Many of these lncRNAs (173) were suggested to play a role in mechanisms at the heart of HIV-host interplay that rely on proteasomal and ubiquitination pathways (113), apoptosis inhibition (12), BRCA1/2 DNA damage responses and ATR cell cycle regulation (12). Through transcription factor binding analysis, we found that lncRNAs display a distinct transcriptional regulation profile (ao. TAF1/3/7, CHD1 and AT3) as compared to protein coding mRNAs (ao. KLF4, SUZ12 and SOX2), suggesting that mRNAs and lncRNAs are independently modulated during HIV replication. In addition, we identified five differentially expressed lncRNA-mRNA pairs with mRNA involvement in HIV pathogenesis with possible cis regulatory lncRNAs that control nearby mRNA expression and function (ao. lnc-HES5-1 and TNFRSF14). Altogether, the present study demonstrates that lncRNAs add a new dimension to the HIV-host interplay and exhibit an independent transcriptionally regulated response. These identified lncRNAs are involved in viral and antiviral response pathways and should be further investigated as they may represent possible biomarkers or targets for controlling HIV replication.

Posted ContentDOI
03 Mar 2017-bioRxiv
TL;DR: By screening a panel of 80 cancer cell lines, this work detected numerous focal aberrations targeting one or multiple lncRNAs without affecting neighboring protein-coding genes, highly suggestive for a tumor suppressive or oncogenic role of the targeted lncRNA gene.
Abstract: The landscape of somatic copy-number alterations (SCNAs) affecting long non-coding RNAs (lncRNAs) in human cancer remains largely unexplored. While the majority of lncRNAs remains to be functionally characterized, several have been implicated in cancer development and metastasis. Considering the plethora of lncRNAs genes that is currently reported, it is conceivable that several lncRNAs might function as oncogenes or tumor suppressor genes. We devised a strategy to detect focal lncRNA SCNAs using a custom DNA microarray platform probing 20 418 lncRNA genes. By screening a panel of 80 cancer cell lines, we detected numerous focal aberrations targeting one or multiple lncRNAs without affecting neighboring protein-coding genes. These focal aberrations are highly suggestive for a tumor suppressive or oncogenic role of the targeted lncRNA gene. Although functional validation remains an essential step in the further characterization of the involved candidate cancer lncRNAs, our results provide a direct way of prioritizing candidate lncRNAs involved in cancer pathogenesis.