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Published on: April 11, 2016
The Added Value of Genome-Wide Copy Numbers to Objectively Resolve Clonality of Multiple Tumors With Pulmonary
Jurriaan Janssen1, Bárbara Andrade Barbosa1, Tim R Mocking1,2
1Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Introduction:
The incidence of patients presenting with multiple cancers (MCs) and pulmonary involvement is increasing. Although next-generation sequencing mutation panels can discern metastases (clonal) from separate primary cancers (nonclonal), it does not warrant a reliable diagnosis for all patients despite significant therapeutic implications. We evaluated the added value of genome-wide copy number aberrations (CNAs) for clonality diagnosis.
Methods:
Two cohorts were assembled: 41 clonal and 41 nonclonal pairs from the TRACERx cohort and 21 MC pairs that had sufficient DNA for whole-exome sequencing (WES) from 120 patients diagnosed using CNA analysis in our routine pathology practice between 2016 and 2022. Clonality was determined by comparing tumor pairs using (1) WES mutations as a definitive standard, (2) a conventional mutation panel with an adapted 2024 International Association for the Study of Lung Cancer algorithm, and (3) CNAs with log-likelihood ratio and Pearson correlation metrics.
Results:
All tumor pairs classified as definite "clonal" or "nonclonal" by mutation analysis (TRACERx: 35 of 82 [43%], MC cohort: 6 of 21 [29%]) were in concordance with WES and CNAs. Of the tumor pairs classified as "probable nonclonal" or "inconclusive" by mutation analysis (TRACERx: 47 of 82 [57%], MC cohort: 15 of 21 [71%]), most could be correctly reclassified by CNAs (TRACERx: 46 of 47 [98%], MC cohort: 15 of 16 [94%]). For each cohort, one tumor pair remained inconclusive. Furthermore, we present a CNA clonality workflow for implementation in molecular diagnostics.
Conclusion:
Genome-wide CNA analysis provides complementary information to resolve clonality of MCs with ambiguous mutational clonality status, enhancing clinical decision-making.
