Next Generation Sequencing Provides More Precise Prognostic Data in CLL

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The authors state that NGS “resolves the diagnostic uncertainties in a significant number of patients.”
The authors state that NGS “resolves the diagnostic uncertainties in a significant number of patients.”

Deep next generation sequencing of the immunoglobulin heavy chain (IgHV-NGS) may increase the prognostic accuracy of cell mutation analysis in chronic lymphocytic leukemia (CLL), according to a study accepted for publication in Leukemia.1

Somatic mutation in the IgHV offers prognostic markers in CLL; there is, for example, some positive correlation between “unmutated” IgHV and inferior prognosis. VH3-21 genetic expression also predicts poor survival.

Analysis of the IgHV locus is difficult, and differentiating among leukemic cell clones has a high failure rate (9% to 18%). For the present study, researchers performed IgHV-NGS in an attempt to more precisely and reliably analyze IgHV mutation.

Two cohorts were used: the first included 270 “highly purified

CD19+CD5+ leukemia cells obtained at diagnosis,” while the second included 227 patients with CLL. IgHV-NGS results were compared against patient overall survival and treatment-free survival.

NGS showed that nearly a quarter of patients had IgHV subclonal rearrangements that may contribute to the heterogeneity of CLL. The authors state that NGS “resolves the diagnostic uncertainties in a significant number of patients.”

RELATED: MRD Assessment Improves PFS Prediction for Patients With CLL

A NGS-IgHV-based classification system, using 5 categories, is proposed: A) multiple “hypermutated” clones, B) 1 hypermutated clone, C) a mix of hypermutated and unmutated clones, D) 1 unmutated clone, and E) multiple unmutated clones. Patients in A had the best prognosis; patients in E had the worst.

Reference

  1. Stamatopoulos B, Timbs A, Bruce D, et al. Targeted deep sequencing reveals clinically relevant subclonal IgHV rearrangements in chronic lymphocytic leukemia. Leukemia. In press. doi: 10.1038/leu.2016.307 [Epub ahead of print]

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