Next-Generation Sequencing for Comprehensive Genomic Profiling in Plasma Cell Disorders

Overview

This study demonstrates a targeted next-generation sequencing (NGS) assay that simultaneously detects structural variants, copy number abnormalities, and mutations in multiple myeloma (MM). The NGS approach showed high sensitivity and specificity compared to FISH, identifying additional clinically relevant abnormalities missed by standard testing.

Background

Multiple myeloma is a plasma cell malignancy characterized by recurrent genetic abnormalities that influence prognosis and treatment response. Current risk stratification incorporates cytogenetic FISH testing and TP53 mutation status, but FISH has limitations in detecting subclonal events and certain rearrangements. Comprehensive genomic profiling using NGS may overcome these limitations by detecting a broader range of genomic alterations in a single assay.

Data Highlights

Key Findings

• The NGS panel detected a median of two mutated genes per sample, with KRAS (34%), NRAS (25%), and TP53 (11%) among the most frequent mutations.
• NGS showed 100% sensitivity and specificity for detecting key IGH translocations t(4;14), t(6;14), t(14;16), and t(14;20), and 97% sensitivity for t(11;14).
• NGS identified MYC rearrangements involving immunoglobulin light chain loci (IGK and IGL) not routinely detected by FISH.
• The assay detected hyperdiploid MM with 95% sensitivity and 85% specificity, including cases missed or incompletely assessed by FISH.
• NGS improved detection of del(17p) by assessing focal deletions through multiple coverage regions, increasing sensitivity from 59% to 78%.
• NGS detected clinically relevant abnormalities in samples lacking complete FISH data, demonstrating its utility in comprehensive genomic profiling.

Clinical Implications

The comprehensive NGS assay offers a single-platform solution for detecting mutations, copy number changes, and structural variants in MM, potentially replacing or complementing FISH. This approach enhances detection of subclonal and rare abnormalities, enabling more accurate risk stratification and personalized treatment planning. Incorporating NGS into clinical workflows may improve prognostication and guide targeted therapies in plasma cell disorders.

Conclusion

Targeted NGS provides a sensitive and specific method for comprehensive genomic characterization in multiple myeloma, surpassing limitations of FISH and enabling improved detection of clinically relevant genomic alterations. This approach supports refined risk stratification and personalized management in plasma cell disorders.

References

1. IMWG/IMS 2025 Consensus Genomic Staging
2. Risk-prediction model combining clinical and genomic variables in MM
3. Limitations of FISH in detecting subclonal CNAs and SVs
4. MYC rearrangements and prognosis in MM
5. MuTect2 and GATK variant annotation methods