Linked-read whole-genome sequencing resolves common and private structural variants in multiple myeloma

Area of Science:

• Genomics
• Oncology
• Molecular Biology

Background:

• Multiple myeloma (MM) is an aggressive plasma cell cancer with complex genomic abnormalities.
• Accurate detection of structural variants (SVs) and copy-number variations (CNVs) is crucial for MM prognosis.
• Existing sequencing methods struggle to capture the full genomic complexity of MM.

Purpose of the Study:

• To evaluate linked-read whole-genome sequencing (lrWGS) for comprehensive genomic profiling of multiple myeloma.
• To establish a protocol for generating high-quality lrWGS data from sorted MM cells with minimal input.
• To assess the utility of lrWGS in identifying clinically relevant genomic aberrations in MM.

Main Methods:

• Developed a protocol for generating lrWGS data from fluorescence-activated cell sorting (FACS)-purified MM cells without DNA purification.
• Analyzed lrWGS data from 37 MM patients.
• Validated findings using fluorescence in situ hybridization (FISH) and compared results with existing methods.

Main Results:

• High-quality lrWGS data was successfully generated from low cell numbers.
• lrWGS showed high concordance with FISH for known translocations and CNVs.
• Identified over 150 novel SVs and CNVs, including structural rearrangements at MYC and t(11;14) loci.
• Discovered private SVs dysregulating IGH-translocated genes, impacting MM molecular classification.

Conclusions:

• lrWGS is a feasible and powerful tool for comprehensive genomic analysis in multiple myeloma.
• This method detects critical prognostic markers and improves understanding of MM genomic complexity.
• Implementing lrWGS can enhance clinical prognostics, advance genomic medicine, and refine patient stratification for clinical trials.