Automated Detection of Arm-Level Alterations for Individual Cancer Patients in the Clinical Setting

Abstract

Copy number alterations are genetic events that promote tumor initiation and progression and are used in clinical care as diagnostic, prognostic, and predictive biomarkers. Based on the length of the alteration, they are roughly classified as focal and arm-level alterations. Although genome-wide techniques to detect arm-level alterations are gaining momentum in hospital laboratories, the high precision and novelty of these techniques pose new challenges: there is no consensus on the definition of an arm-level alteration and there is a lack of tools to compute them for individual patients. Based on 376 clinical samples analyzed with the OncoScan formalin-fixed, paraffin-embedded assay, a bimodal distribution of the percentage of bases with copy number alterations within a chromosomal arm was observed, with the second peak starting at 90% of arm length. Two approaches were tested for the definition of arm-level alterations: sum of altered segments (SoS) >90%, or the longest segment (LS) >90%. These approaches were validated against expert annotation of 25 clinical cases. The SoS method outperformed the LS method as indicated by a higher concordance (SoS, 95.2%; LS, 79.9%). Some of the discordances ultimately were attributed to human error, highlighting the advantages of automation. The increase in reliability led to the development of publicly available software and its inclusion into routine clinical practice at Geneva University Hospitals.