APR 12, 2018 09:00 AM PDT

QIAseq Digital Sequencing and Biomedical Genomics Workbench: Application to Liquid Biopsy in Bladder Cancer Research

  • Senior Scientist, Biomedical Genomics, QIAGEN
      Dr. Francesco Lescai graduated in Medical Biotechnology at the University of Bologna and was a awarded a Ph.D. in experimental pathology, with studies in genetics of human ageing and Alzheimer Disease. He then pioneered the analysis of human exomes at University College London, first at UCL Genomics and then at the Centre for Translational Genomics, Institute of Child Health and Great Ormond Street Hospital. Francesco then took on the position of Associate Professor of Human Genomics and Bioinformatics at the Department of Biomedicine of Aarhus University, where his main research focus was the use of genome sequencing in the area of precision medicine, and in particular the genetic causes of psychiatric disorders such as schizophrenia and autism. He joined QIAGEN in November 2017 as a Senior Scientist for Biomedical Genomics, in the Global Product Management team for CLC Workbenches.
      Francesco has been a member of the Executive Board of the European Federation of Biotechnology, is in the Editorial Board of several journals and has been in different Expert Groups at the European Commission. He also coordinates a Horizon2020 project on responsible industrial innovation.


    This presentation illustrates the features of QIAGEN sample to insight approach, and how it combines a powerful chemistry based on unique molecular indexes (UMIs) and a UMI-aware bioinformatics workflow in the Biomedical Genomics Workbench with QIAseq Panel Analysis Plugin. This approach reaches impressive performances in detecting low allele-fraction variants, and the integration with other QIAGEN solutions such as Ingenuity Variant Analysis (IVA) and QCI Interpret allows to further explore the results for their biological and pathological relevance.

    The use of DNA panels is a cost-effective approach to reach the high coverage needed for research  applications like liquid biopsy. In such scenarios, the capability to distinguish between sequencing or amplification errors and real findings is crucial, in order to detect clinically relevant mutations at low allele-fraction levels. UMIs address this challenge, if combined with bioinformatics capable of exploiting their added value. 

    Liquid biopsy is emerging as a new and non-invasive approach to characterize cancer mutation profiles. However, some tumours like urothelial cancer are particularly challenging, due to their location and biology. In this work we explore the performance of our workflow and its insights on bladder cancer. 

    We compared the results from tissue and plasma libraries extracted with QIAGEN QIAamp MinElute ccfDNA and QIAamp Circulating Nucleic Acid kits from individuals with bladder cancer, and show that the recovery of variants (i.e. variants identified in the tissue also called in the plasma) ranges above 70% for SNVs. A very good achievement, in the biological context of urothelial cancer. We further explore the results from a pathological perspective, and show the success in capturing biologically relevant mutations, classified by their pathogenicity and actionability according to existing guidelines.

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