Logo qPCR dPCR & NGS 2017

Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Session Overview
LB2: Liquid Biopsies & Molecular Dx 1
Monday, 03/Apr/2017:
2:00pm - 6:00pm

Session Chair: Jo Vandesompele, Biogazelle, Belgium
Session Chair: An Hendrix, Ghent University, Belgium
Location: Lecture hall 14
650 participants, TUM Weihenstephan

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mRNA capture sequencing enabled liquid biopsy precision oncology

Jo Vandesompele

Biogazelle, Belgium

In contrast to general belief, a substantial part of the human protein coding transcriptome is abundantly present in the blood as extracellular mRNA, ready to exploited. Here, I present probe based mRNA capture as a sensitive RNA sequencing workflow to study thousands of mRNA genes in cell-free RNA from cancer patients’ plasma. Apart from RNA abundance profiling, this type of data can also be use to detect structural RNA variants, such as somatic mutations, and RNA editing events, all known to play an important role in cancer. RNA capture sequencing enables liquid biopsy guided precision oncology, such as therapy stratification, treatment response monitoring and early detection of relapse. I will also discuss the preanalytical jungle of RNA targeted liquid biopsies and need for standardization, as part of the ongoing exRNAQC study.

Sensitive NGS method for the analysis of microbial and viral nucleic acid in cell free RNA

Martin Heine

NuGEN Technologies, United States of America

Finding the causative agent of an infection can be challenging. Low RNA quantity, poor quality, low viral titers, and high background from the host negatively impact viral detection from biofluids (blood, nasal swabs, CSF). PCR can be an effective means of detecting specific, well characterized organisms but only if primers are closely spaced and those organisms are represented in the test panel. RNA-Seq is an alternative unbiased method that has previously been used with cfRNA to identify unknown infections in an impartial manner. However, this method typically requires higher RNA input and quality than typically exist in clinical samples. Further, the low titers of the pathogen RNA relative to the host and non-pathogen RNA necessitate deep sequencing of the libraries. Several reports have described the use of NuGEN’s isothermal amplification technology (SPIA) to overcome the low yields and poor RNA quality for the detection of viruses in human biological fluids but these methods are still burdened with uninformative host transcripts.

Here we describe a single workflow that combines NuGEN’s; SPIA amplification technology, enzymatic fragmentation, and AnyDeplete (InDA-C targeted depletion method) to study the causative agent(s) and host response in nasal samples obtained from asthmatic and non-asthmatic children with presumptive respiratory infections. This unbiased method enabled efficient viral detection and detection of lowly expressed human transcripts with <1 million reads per sample. Data illustrating the efficiency of the depletion method and the coverage of the viral genomes will be presented.

Identification Of Extracellular Vesicle-Specific Biomarkers

Jan Van Deun1,3, Glenn Vergauwen1,3, Pieter Mestdagh2,3, Jo Vandesompele2,3, Olivier De Wever1,2, An Hendrix1,2

1Laboratory of Experimental Cancer Research, Department of Radiation Oncology and Experimental Cancer Research, Ghent University, Ghent, Belgium; 2Department of Medical Genetics, Ghent University, Ghent, Belgium; 3Cancer Research Institute Ghent, Ghent, Belgium

Extracellular vesicles (EVs) transmit information (nucleic acids, proteins and lipids) between different cell types, organs and even organisms, and have been detected in multiple body fluids. The connection of EVs to many aspects of human disease stimulated many researchers to explore their biomarker potential. The rapid expansion of the EV research field resulted in a struggle to cope with heterogeneity in the implementation and reporting of isolation protocols and characterization methods, delaying the introduction of EV-specific biomarkers in clinical setting. We carried out a comparative study of commonly implemented EV isolation methods which revealed a method dependent outcome using omics approaches. Density gradient centrifugation minimized the co-isolation of (non)-membranous contaminants of different origin and obtained a unique proteome and transcriptome signature. In addition, pre-analytical parameters that are commonly implemented but often vary among research groups, such as centrifugal filter types, were shown to have an impact on EV analysis and should be carefully considered and reported. To help overcome these issues in EV research, we established the EV-TRACK knowledgebase (www.evtrack.org), a crowdsourcing database that centralizes EV biology and methodology. It currently comprises experimental parameters of over 1200 EV-related publications. The EV-TRACK platform aims to stimulate authors, reviewers, editors and funders to put experimental guidelines into practice, which is a prerequisite to realize the clinical potential of EV-related biomarkers.

NGS and qPCR analysis of RNA and microRNA in Biofluids and Exosomes

Michael Thorsen

Exiqon, Denmark

Biofluids contain a multitude of RNA molecules some of which may serve as biomarkers for altered conditions in the body and be applied in diagnosis of disease. Many biofluids are easily collected and liquid biopsies hold the promise of developing non- or minimal invasive diagnostic tests for screening and monitoring diseases such as cancer. Though rather unstable by nature, RNA in biofluids or a fraction of these appear relatively stable, possibly because they are protected from degradation within exosomes or within protein aggregates.

We are developing technologies and offer Services to analyze RNA in biofluids which is challenged by the low content of RNA and the presence of substances that interfere with the analyses. Exosomes are of particular interest, as the RNA cargo that these vesicles carry are derived from cells throughout the body and in particular the cells in contact with the biofluid. Currently, we are able to robustly analyze RNA including microRNA in different biofluids and exosomes using both next generation sequencing and LNA™ enhanced qPCR. Data will be presented showing how miRCURY LNA™ Universal RT microRNA PCR may be applied successfully to validate NGS data. We will also share data on applying qPCR analysis of urinary exosomes to discover microRNA biomarkers for prostate cancer and how a three-microRNA signature now has been validated in independent cohorts.

Routine Next-Generation-Sequencing of Brain Tumors

Felix Sahm

University Hospital Heidelberg, Germany

With the numbers of prognostic and predictive genetic markers in neuro-oncology steadily growing, the need for comprehensive molecular analysis of neuropathology samples has vastly increased. We developed an enrichment/hybrid capture-based next-generation sequencing (NGS) gene panel comprising the entire coding and selected intronic and promoter regions of 130 genes recurrently altered in brain tumors, allowing for the detection of single nucleotide variations, fusions, and copy number variations. Information derived from NGS data identified potential targets for experimental therapy in about 75% of diagnostic samples. Such an approach will likely become highly valuable in the near future for treatment decision making, as more therapeutic targets emerge and genetic information enters the classification of brain tumors.

BD Genomics: An Integrated Workflow For Single Cell Analysis That Helps To Uncover Tumor Heterogeneity

Wieland Keilholz

BD, Germany

Following the paradigm of easy-to-use tools for genomics analyses, BD Genomics offers a suite of products that focus on single cell applications.

The Tumor Dissociation reagent makes solid tumors from a variety of tissues accessible to FACS technology.

The FACSMelodyTM is a benchtop cell sorter that enables inexperienced FACS users to successfully run a sorting experiment through automation of complex tasks.

BD Precise™ Assays are designed for transcriptome analysis on the single cell level using an efficient workflow that seamlessly integrates with sorted cells. The assays ensure highest precision in gene expression analysis by using molecular indexes to remove PCR bias introduced during library preparation.

The assay is combined with access to efficient and widely automated tools for the analysis of genomics data.

A case study will be presented on the integrated workflow of tumor dissociation, FACS sorting and transcriptome analysis. New insights into tumor biology at a currently unprecedented resolution are revealed through this powerful approach.

Nucleosome association of cell-free DNA informs about gene expression

Peter Ulz1, Gerhard Thallinger2, Martina Auer1, Ricarda Graf1, Karl Kashofer3, Stephan Wenzel Jahn3, Luca Abete3, Gunda Pristauz4, Edgar Petru4, Jochen Geigl1, Ellen Heitzer1, Michael Speicher1

1Institute of Human Genetics, Medical University Graz, Austria; 2Institute of Molecular Biotechnology, University of Technology, Graz, Austria; 3Institute of Pathology, Medical University of Graz, Graz, Austria; 4Department of Obstetrics and Gynecology, Medical University of Graz, Graz, Austria

Cell-free DNA (cfDNA) consists predominantly of nucleosome-protected DNA shed into the bloodstream by cells undergoing apoptosis. By whole-genome sequencing of cfDNA fragments two regions which inform about nucleosome occupancy were identified. Since nucleosome occupancy is a marker of gene expression at transcription start sites (TSS), read depth differences may also inform about gene expression.

By a machine learning approach, gene expression was predicted from a pool of non-cancer controls and compared to previous gene expression results from studies of circulating RNA in healthy donors.

In tumor patients, this approach was applied to circulating tumor DNA (ctDNA) whole-genome sequencing from regions exhibiting copy-number alterations. Gene expression prediction was compared to RNA-Seq from matching primary tumors and yielded high concordance.

Our analyses provide functional information about tumor cells from DNA sequencing and adds an additional layer of information to the analysis of ctDNA.

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