Clinical Scorecard: A comprehensive next-generation sequencing approach for identifying driver mutations, genomic rearrangements, and copy number variations in plasma cell disorders

At a Glance

Key Highlights

• NGS panel simultaneously detects mutations, CNAs, and SVs including rare and subclonal abnormalities not fully captured by FISH.
• High concordance with FISH for common translocations and CNAs with improved detection of MYC rearrangements and TP53 mutations.
• Sequencing approach improves sensitivity for focal del(17p) detection and identifies additional genomic abnormalities missed by standard FISH panels.

Guideline-Based Recommendations

Diagnosis

• Use of targeted NGS panel to complement or enhance FISH testing for comprehensive genomic profiling in MM.
• Incorporate genomic data including TP53 mutational status and copy number changes into risk stratification per IMWG/IMS guidelines.

Management

• Integrate genomic findings with clinical and biomarker data to guide risk-adapted therapy decisions.
• Consider detection of high-risk features such as 1q gain/amplification, del(17p), and MYC rearrangements for prognosis and treatment planning.

Monitoring & Follow-up

• Use genomic profiling at diagnosis and relapse to assess clonal evolution and emerging high-risk mutations.
• Repeat genomic testing may be warranted to detect subclonal changes impacting treatment response.

Risks

• Limitations of FISH include inability to detect single nucleotide variants and subclonal CNAs.
• NGS panel sensitivity may be affected by subclonal events; combining coverage analysis improves detection.

Patient & Prescribing Data

264 patients including newly diagnosed MM (81%), relapsed MM (19%), smoldering MM (3%), and MGUS (2%)

Genomic profiling identifies mutations in KRAS, NRAS, TP53, and others that may influence targeted therapy and prognosis.

Clinical Best Practices

• Perform comprehensive genomic profiling using targeted NGS panels alongside FISH for accurate detection of driver mutations and structural variants.
• Apply IMWG/IMS Consensus Genomic Staging integrating cytogenetics, mutation status, and biomarkers for risk stratification.
• Use sequencing data to identify rare and subclonal abnormalities such as MYC rearrangements involving immunoglobulin light chains.
• Increase sensitivity for del(17p) detection by analyzing multiple coverage regions within TP53 locus.
• Ensure informed consent and ethical sample collection in accordance with institutional review board approvals.

References

• IMWG/IMS Consensus Genomic Staging for high-risk MM
• Risk-prediction model for newly diagnosed MM combining clinical and genomic variables
• Limitations of FISH in detecting subclonal CNAs and rare abnormalities
• Use of MuTect2 and GATK for somatic mutation calling
• MYC rearrangements and prognosis in MM