Thomas Butters, Dahmane Oukrif, Punn Tannirandorn, Ianthe Aem van Belzen, Jianan Chen, Christopher Davies, Runtian Lin, Solange De Noon, Dalil Taher, Chloe Cutler, Mark Markov, Anna Tollit, Fatine Oumlil, Christopher D Steele, Matthew Fittall, Yanping Guo, Isidro Cortés-Ciriano, Peter Van Loo, Adrienne M Flanagan, Nischalan Pillay, Maxime Tarabichi
DNA ploidy is an important predictor of tumor behavior and prognosis, and its accurate estimation is essential for robust genomic analysis in translational cancer research and diagnostics. However, the most common in silico methods for ploidy estimation using next-generation-sequencing-based copy-number aberration (CNA)-calling algorithms are often inaccurate due to inherent ambiguity in fitting ploidy solutions. This study evaluates the accuracy of state-of-the-art CNA callers using whole-genome sequencing by comparing their ploidy estimates with gold-standard ploidy measurements derived by flow cytometry (FC). We demonstrate that CNA callers are up to 38% inaccurate in cancers with complex genomes, which impacts the accurate estimation of copy number of cancer genes and could have clinical implications and impacts on inferences of tumor evolution. Critically, flow-cytometry-based calibration of CNA callers yields highly accurate ploidy estimates (ρPearson = 0.92, p < 0.001), providing a robust solution to the substantial inaccuracies that compromise clinical decision-making and evolutionary inference in complex cancers.