A reduced panel of eight genes (ATM, SF3B1, NOTCH1, BIRC3, XPO1, MYD88, TNFAIP3, and TP53) as an estimator of the tumor mutational burden in chronic lymphocytic leukemia. (16th December 2020)

• Record Type: Journal Article
• Authors: Chauzeix, Jasmine; Pastoret, Cédric; Donaty, Lucie; Gachard, Nathalie; Fest, Thierry; Feuillard, Jean; Rizzo, David
• Is Part Of: International journal of laboratory hematology. Volume 43:Number 4(2021)
• Page Start: 683
• Page End: 692
• Publication Date: 2020-12-16
• Subjects: chronic lymphocytic leukemia -- high‐throughput sequencing -- prognosis -- tumor mutational burden; Hematology -- Periodicals; Blood -- Diseases -- Periodicals; Hematology -- Periodicals; 616.15005
• DOI: 10.1111/ijlh.13435
• Languages: English
• ISSNs: 1751-5521

Abstract

Abstract: Introduction: Mutational complexity or tumor mutational burden (TMB) influences the course of chronic lymphocytic leukemia (CLL). However, this information is not routinely used because TMB is usually obtained from whole genome or exome, or from large gene panel high‐throughput sequencing. Methods: Here, we used the C‐Harrel concordance index to determine the minimum panel of genes for which mutations predict treatment‐free survival (TFS) as well as large resequencing panels. Results: An eight gene estimator was defined encompassing ATM, SF3B1, NOTCH1, BIRC3, XPO1, MYD88, TNFAIP3, and TP53 . TMB estimated from either a large panel of genes or the eight gene estimator was increased in treated patients or in those with a short TFS (<2 years), unmutated IGHV gene or with an unfavorable karyotype. Being an independent prognostic parameter, any mutation in the eight gene estimator predicted a shorter TFS better than Binet stage and IGHV mutational status among patients with an apparently non‐progressive disease (TFS >6 months). Strikingly, the eight gene estimator was also highly informative for patients with Binet stage A CLL or with a good prognosis karyotype. Conclusion: These results suggest that the eight gene estimator, that is easily achievable by high‐throughput resequencing, brings robust and valuable information that predicts evolution of untreated patients at diagnosis better than any other parameter.