Svilen Tzonev
Bio-Rad Laboratories
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Publication
Featured researches published by Svilen Tzonev.
PLOS ONE | 2015
John F. Regan; Nolan Kamitaki; Tina C. Legler; Samantha Cooper; Niels Klitgord; George Karlin-Neumann; Catherine Wong; Shawn Hodges; Ryan Koehler; Svilen Tzonev; Steven A. McCarroll
Determining the chromosomal phase of pairs of sequence variants – the arrangement of specific alleles as haplotypes – is a routine challenge in molecular genetics. Here we describe Drop-Phase, a molecular method for quickly ascertaining the phase of pairs of DNA sequence variants (separated by 1-200 kb) without cloning or manual single-molecule dilution. In each Drop-Phase reaction, genomic DNA segments are isolated in tens of thousands of nanoliter-sized droplets together with allele-specific fluorescence probes, in a single reaction well. Physically linked alleles partition into the same droplets, revealing their chromosomal phase in the co-distribution of fluorophores across droplets. We demonstrated the accuracy of this method by phasing members of trios (revealing 100% concordance with inheritance information), and demonstrate a common clinical application by phasing CFTR alleles at genomic distances of 11–116 kb in the genomes of cystic fibrosis patients. Drop-Phase is rapid (requiring less than 4 hours), scalable (to hundreds of samples), and effective at long genomic distances (200 kb).
Biomolecular Detection and Quantification | 2016
Alexandra S. Whale; Jim F. Huggett; Svilen Tzonev
Over the past decade numerous publications have demonstrated how digital PCR (dPCR) enables precise and sensitive quantification of nucleic acids in a wide range of applications in both healthcare and environmental analysis. This has occurred in parallel with the advances in partitioning fluidics that enable a reaction to be subdivided into an increasing number of partitions. As the majority of dPCR systems are based on detection in two discrete optical channels, most research to date has focused on quantification of one or two targets within a single reaction. Here we describe ‘higher order multiplexing’ that is the unique ability of dPCR to precisely measure more than two targets in the same reaction. Using examples, we describe the different types of duplex and multiplex reactions that can be achieved. We also describe essential experimental considerations to ensure accurate quantification of multiple targets.
Analytical Chemistry | 2017
Alexandra S. Whale; Alison S. Devonshire; George Karlin-Neumann; Jack Regan; Leanne Javier; Simon Cowen; Ana Fernandez-Gonzalez; Gerwyn M. Jones; Nicholas Redshaw; Julia Beck; Andreas W. Berger; Valérie Combaret; Nina Dahl Kjersgaard; Lisa Davis; Frederic Fina; Tim Forshew; Rikke Fredslund Andersen; Silvia Galbiati; Álvaro González Hernández; Charles A. Haynes; Filip Janku; Roger Lacave; Justin Lee; Vilas Mistry; Alexandra Pender; Anne Pradines; Charlotte Proudhon; Lao H. Saal; Elliot Stieglitz; Bryan C. Ulrich
This study tested the claim that digital PCR (dPCR) can offer highly reproducible quantitative measurements in disparate laboratories. Twenty-one laboratories measured four blinded samples containing different quantities of a KRAS fragment encoding G12D, an important genetic marker for guiding therapy of certain cancers. This marker is challenging to quantify reproducibly using quantitative PCR (qPCR) or next generation sequencing (NGS) due to the presence of competing wild type sequences and the need for calibration. Using dPCR, 18 laboratories were able to quantify the G12D marker within 12% of each other in all samples. Three laboratories appeared to measure consistently outlying results; however, proper application of a follow-up analysis recommendation rectified their data. Our findings show that dPCR has demonstrable reproducibility across a large number of laboratories without calibration. This could enable the reproducible application of molecular stratification to guide therapy and, potentially, for molecular diagnostics.
BioTechniques | 2015
Wei Yang; Dawne N. Shelton; Jennifer R. Berman; Bin Zhang; Samantha Cooper; Svilen Tzonev; Eli Hefner; John F. Regan
Targeted therapies in many cancers have allowed unprecedented progress in the treatment of disease. However, routine implementation of genomic testing is constrained due to: 1) limited amounts of sample (pg–ng range) per biological specimen, 2) diagnostic turnaround time and workflow, 3) cost, and 4) difficulties in detection of mutational loads below 5%. KRAS is mutated in approximately 40% of colorectal cancers (CRCs). The majority of mutations affect codons 12, 13, and 61 and indicate a negative response to anti–epidermal growth factor receptor (EGFR) therapy. To optimize therapy strategies for personalized care, it is critical to rapidly screen patient samples for the presence of multiple KRAS mutations.
Archive | 2018
Svilen Tzonev
Current commercially available digital PCR (dPCR) systems and assays are capable of detecting individual target molecules with considerable reliability. As tests are developed and validated for use on clinical samples, the need to understand and develop robust statistical analysis routines increases. This chapter covers the fundamental processes and limitations of detecting and reporting on single molecule detection. We cover the basics of quantification of targets and sources of imprecision. We describe the basic test concepts: sensitivity, specificity, limit of blank, limit of detection, and limit of quantification in the context of dPCR. We provide basic guidelines how to determine those, how to choose and interpret the operating point, and what factors may influence overall test performance in practice.
Cancer Research | 2014
Wei Yang; Dawne N. Shelton; Samantha Cooper; Jennifer R. Berman; Svilen Tzonev; Eli Hefner; John F. Regan
Targeted therapies in many forms of cancer today have allowed unprecedented progress in the treatment of disease. Despite these advances, routine implementation of genomic testing is still limited by: 1) methods to detect, with confidence, mutational loads below 10%, 2) limited amounts of sample (pg-ng range) per biological specimen, 3) diagnostic turnaround time, and 4) cost. In metastatic colorectal cancer (mCRC), anti-epidermal growth factor receptor antibodies (αEGFR) are used to target the wild-type EGFR receptor. However, KRAS is mutated in approximately 40% of colorectal cancers and is indicative of a negative response to αEGFR therapy. BRAF and PIK3CA mutations are also associated with poor response in the remaining patients with KRAS wild-type genotype. To optimize therapy strategies for personalized care, it is therefore critical to rapidly screen patient samples during the course of disease for the presence of multiple mutations. The low abundance of mutants and limited amount and quality of available clinical samples (FFPE and cfDNA) render it difficult to reliably detect multiple mutations with current platforms and methods. We have developed a multiplexing strategy for screening clinically-actionable KRAS, BRAF, and PIK3CA mutations in mCRC clinical samples using digital PCR. No pre-amplification step was required. This sensitive and inexpensive method reduces the risk of contamination and can be easily implemented in molecular diagnostic laboratories for rapid, routine screening and monitoring of residual disease in cancer patients. Citation Format: Wei Yang, Dawne N. Shelton, Samantha Cooper, Jennifer Berman, Svilen Tzonev, Eli Hefner, John F. Regan. Ultrasensitive detection of cancer mutations in metastatic colorectal cancer FFPE and cell-free DNA samples using multiplexed droplet digital PCR. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-115. doi:10.1158/1538-7445.AM2014-LB-115
Analytical Chemistry | 2013
Geoffrey P. McDermott; Duc Do; Claudia Litterst; Dianna Maar; Christopher M. Hindson; Erin Steenblock; Tina C. Legler; Yann Jouvenot; Samuel H. Marrs; Adam Bemis; Pallavi Shah; Josephine Wong; Shenglong Wang; David Sally; Leanne Javier; Theresa Dinio; Chunxiao Han; Timothy P. Brackbill; Shawn Hodges; Yunfeng Ling; Niels Klitgord; George Carman; Jennifer R. Berman; Ryan Koehler; Amy L. Hiddessen; Pramod Walse; Luc J. Bousse; Svilen Tzonev; Eli Hefner; Benjamin J. Hindson
Archive | 2012
Serge Saxonov; Svilen Tzonev; Michael Y. Lucero; Ryan Koehler; Benjamin J. Hindson
Archive | 2013
Svilen Tzonev
Archive | 2012
Austin P. So; Svilen Tzonev; Serge Saxonov; Benjamin J. Hindson; Michael Y. Lucero