Back to Search
Start Over
Evaluation of next-generation sequencing versus next-generation flow cytometry for minimal-residual-disease detection in Chinese patients with multiple myeloma
- Source :
- Discover Oncology, Vol 15, Iss 1, Pp 1-14 (2024)
- Publication Year :
- 2024
- Publisher :
- Springer, 2024.
-
Abstract
- Abstract Purpose To evaluate the efficacy of next-generation sequencing (NGS) in minimal-residual-disease (MRD) monitoring in Chinese patients with multiple myeloma (MM). Methods This study analyzed 60 Chinese MM patients. During MRD monitoring in these patients’ post-therapy, clonal immunoglobulin heavy chain (IGH) rearrangements were detected via NGS using LymphoTrack assays. MRD monitoring was performed using NGS or next-generation flow cytometry (NGF), and the results were compared. Additionally, the sensitivity and reproducibility of the NGS method were assessed. Results The MRD detection range of the NGS method was 10–6–10–1, which suggested good linearity, with a Pearson correlation coefficient of 0.985 and a limit of detection of 10–6. Intra- and inter-assay reproducibility analyses showed that NGS exhibited 100% reproducibility with low variability in clonal cells. At diagnosis, unique clones were found in 42 patients (70.0%) with clonal IGH rearrangements, which were used as clonality markers for MRD monitoring post-therapy. Comparison of NGS and NGF for MRD monitoring showed 79.1% concordance. No samples that tested MRD-positive via NGF were found negative via NGS, indicating the higher sensitivity of NGS. MRD could be detected using NGS in 6 of 7 samples before autologous hematopoietic stem-cell transplantation, and 5 of them tested negative post-transplantation. In contrast, the NGF method could detect MRD in only 1 sample pre-transplantation. Conclusion Compared with NGF, NGS exhibits higher sensitivity and reproducibility in MRD detection and can be an effective strategy for MRD monitoring in Chinese MM patients.
Details
- Language :
- English
- ISSN :
- 27306011
- Volume :
- 15
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Discover Oncology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.4c49dee806fa4d6e9bcfdf495e6537b9
- Document Type :
- article
- Full Text :
- https://doi.org/10.1007/s12672-024-00938-w