Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/16258
Title: Tumour procurement, DNA extraction, coverage analysis and optimisation of mutation-detection algorithms for human melanoma genomes
Austin Authors: Wilmott, James S;Field, Matthew A;Johansson, Peter A;Kakavand, Hojabr;Shang, Ping;De Paoli-Iseppi, Ricardo;Vilain, Ricardo E;Pupo, Gulietta M;Tembe, Varsha;Jakrot, Valerie;Shang, Catherine A;Cebon, Jonathan S ;Shackleton, Mark;Fitzgerald, Anna;Thompson, John F;Hayward, Nicholas K;Mann, Graham J;Scolyer, Richard A
Affiliation: Austin Health, Heidelberg, Victoria, Australia
Melanoma Institute Australia, North Sydney, NSW, Australia
Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia
Immunogenomics Laboratory, Australian National University, Canberra, ACT, Australia
Oncogenomics Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
Centre for Cancer Research, The University of Sydney at Westmead Millennium Institute, Westmead, NSW, Australia
Bioplatforms Australia, Macquarie University, North Ryde, NSW, Australia
Ludwig Institute for Cancer Research, Olivia Newton-John Cancer and Wellness Centre, Austin Health, Heidelberg, Victoria, Australia
The Cancer Development and Treatment Laboratory, Peter MacCallum Cancer Centre and Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria, Australia
Departments of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
Issue Date: Dec-2015
Date: 2016-02-19
Publication information: Pathology 2015; 47(7): 683-693
Abstract: Whole genome sequencing (WGS) of cancer patients' tumours offers the most comprehensive method of identifying both novel and known clinically-actionable genomic targets. However, the practicalities of performing WGS on clinical samples are poorly defined.This study was designed to test sample preparation, sequencing specifications and bioinformatic algorithms for their effect on accuracy and cost-efficiency in a large WGS analysis of human melanoma samples.WGS was performed on melanoma cell lines (n = 15) and melanoma fresh frozen tumours (n = 222). The appropriate level of coverage and the optimal mutation detection algorithm for the project pipeline were determined.An incremental increase in sequencing coverage from 36X to 132X in melanoma tissue samples and 30X to 103X for cell lines only resulted in a small increase (1-2%) in the number of mutations detected, and the quality scores of the additional mutations indicated a low probability that the mutations were real. The results suggest that 60X coverage for melanoma tissue and 40X for melanoma cell lines empower the detection of 98-99% of informative single nucleotide variants (SNVs), a sensitivity level at which clinical decision making or landscape research projects can be carried out with a high degree of confidence in the results. Likewise the bioinformatic mutation analysis methodology strongly influenced the number and quality of SNVs detected. Detecting mutations in the blood genomes separate to the tumour genomes generated 41% more SNVs than if the blood and melanoma tissue genomes were analysed simultaneously. Therefore, simultaneous analysis should be employed on matched melanoma tissue and blood genomes to reduce errors in mutation detection.This study provided valuable insights into the accuracy of SNV with WGS at various coverage levels in human clinical cancer specimens. Additionally, we investigated the accuracy of the publicly available mutation detection algorithms to detect cancer specific SNVs which will aid researchers and clinicians in study design and implementation of WGS for the identification of somatic mutations in other cancers.
Description: Erratum in: Erratum: Wilmott JS, Field MA, Johansson PA, et al. Tumour procurement, DNA extraction, coverage analysis and optimisation of mutation-detection algorithms for human melanoma genomes. Pathology 2015; 47: 683-93. Pathology 2016; 48(1): 104
URI: https://ahro.austin.org.au/austinjspui/handle/1/16258
DOI: 10.1097/PAT.0000000000000324
Journal: Pathology
PubMed URL: https://pubmed.ncbi.nlm.nih.gov/26517638
Type: Journal Article
Subjects: Algorithms
DNA Mutational Analysis
DNA, Neoplasm
Melanoma
Specimen Handling
Appears in Collections:Journal articles

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