Simple deep sequencing-based post-remission MRD surveillance predicts clinical relapse in B-ALL. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Next-generation sequencing (NGS) of the rearranged immunoglobulin heavy-chain gene has emerged as a highly sensitive method to detect minimal residual disease (MRD) in B acute lymphoblastic leukemia/lymphoma (B-ALL). However, a sensitive and easily implemented NGS methodology for routine clinical laboratories is lacking and clinical utility of NGS-MRD surveillance in a post-remission setting to predict clinical relapse has not been determined. METHODS: Here we described a simple and quantitative NGS platform and assessed its performance characteristics, quantified NGS-MRD levels in 122 B-ALL samples from 30 B-ALL patients, and explored the clinical merit of NGS-based MRD surveillance. RESULTS: The current NGS platform has an analytic sensitivity of 0.0001% with excellent specificity and reproducibility. Overall, it performs better than routine multi-color flow cytometry (MCF) in detecting MRD. Utilizing this assay in MRD surveillance in a post-remission setting showed that it detected conversion to positive MRD (CPMRD) in patients with NGS-based molecular remission much earlier than MCF, and that positive MRD conversion could be detected as early as 25.6 weeks prior to clinical relapse in closely surveilled patients. Post-remission CPMRD, but not NGS-based MRD positivity at end of induction, can accurately predict clinical relapse in our limited cohort of B-ALL patients. CONCLUSIONS: This pilot proof-of-concept study illustrates the clinical utility of a simple, sensitive, and clinically feasible MRD detection platform in post-remission NGS-based MRD surveillance and early relapse detection in B-ALL patients.

publication date

  • August 22, 2018

Research

keywords

  • Neoplasm, Residual
  • Precursor Cell Lymphoblastic Leukemia-Lymphoma

Identity

PubMed Central ID

  • PMC6103872

Scopus Document Identifier

  • 85051929919

Digital Object Identifier (DOI)

  • 10.1038/sj.leu.2405072

PubMed ID

  • 30134947

Additional Document Info

volume

  • 11

issue

  • 1