Abstract

Systematic tumour profiling is essential for biomarker research and clinically for assessing response to therapy. Solving the challenge of delivering informative copy number (CN) profiles from formalin-fixed paraffin embedded (FFPE) material, the only likely readily available biospecimen for most cancers, involves successful processing of small quantities of degraded DNA. To investigate the potential for analysis of such lesions, whole-genome CNVseq was applied to 300 FFPE primary tumour samples, obtained from a large-scale epidemiological study of melanoma. The quality and the discriminatory power of CNVseq was assessed. Libraries were successfully generated for 93% of blocks, with input DNA quantity being the only predictor of success (success rate dropped to 65% if <20 ng available); 3% of libraries were dropped because of low sequence alignment rates. Technical replicates showed high reproducibility. Comparison with targeted CN assessment showed consistency with the Next Generation Sequencing (NGS) analysis. We were able to detect and distinguish CN changes with a resolution of ≤10 kb. To demonstrate performance, we report the spectrum of genomic CN alterations (CNAs) detected at 9p21, the major site of CN change in melanoma. This successful analysis of CN in FFPE material using NGS provides proof of principle for intensive examination of population-based samples.

Details

Title
High-Resolution Copy Number Patterns From Clinically Relevant FFPE Material
Author
Filia, Anastasia 1 ; Droop, Alastair 2 ; Harland, Mark 3 ; Thygesen, Helene 3 ; Randerson-Moor, Juliette 3   VIAFID ORCID Logo  ; Snowden, Helen 3 ; Taylor, Claire 3 ; Diaz, Joey Mark S 3   VIAFID ORCID Logo  ; Pozniak, Joanna 3 ; Nsengimana, Jérémie 3 ; Laye, Jon 3 ; Newton-Bishop, Julia A 3 ; Bishop, D Timothy 3   VIAFID ORCID Logo 

 Section of Epidemiology and Biostatistics, Leeds Institute of Medical Research at St James’s, University of Leeds, Leeds, United Kingdom; Centre for Translational Research, Biomedical Research Foundation of the Academy of Athens (BRFAA), Athens, Greece 
 MRC Medical Bioinformatics Centre, Leeds Institute of Data Analytics, University of Leeds, Leeds, United Kingdom 
 Section of Epidemiology and Biostatistics, Leeds Institute of Medical Research at St James’s, University of Leeds, Leeds, United Kingdom 
Pages
1-9
Publication year
2019
Publication date
Jun 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2244134418
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.