Introduction:

The analysis of somatic hypermutation (SHM) in the immunoglobulin heavy chain variable region (IGHV) is crucial for managing chronic lymphocytic leukemia (CLL). Traditional methods such as Sanger sequencing (SS) or second-generation sequencing (NGS) are reliable but labour-intensive. This study aims to evaluate the efficacy and accuracy of the new MinION Kit 14 chemistry, nanopore sequencing (NS), using POD5 files and duplex basecalling with the Dorado software, compared to standard methods (SS).

Methods:

CLL patient samples were analysed using a custom pipeline that includes conversion of POD5 to BAM files with Dorado, BAM to FASTQ conversion, optional quality filtering, clustering by similarity with VSEARCH, generating consensus sequences, and querying IMGT/V-Quest for mutation status assessment. Statistical analysis for comparison between the NS and SS methods was performed using Spearman correlation test.

Results:

We included 15 CLL patient samples comparing our new NS method with SS. Results showed high concordance between NS and SS in terms of the percentage of SHM of IGHV (ρ=0.99; p<0.001) and 100% agreement in mutated/unmutated status definition, with NS detecting additional productive subclones. Even using Flongle flow cells, the quality of sequencing was sufficient to identify correct rearrangements with a single sample, ensuring high accuracy. The Kit 14 chemistry, which includes the E8.2 motor protein and R10.4.1 flow cells, achieved Q12-Q16+ accuracy with simplex data, significantly improving with duplex basecalling, making it suitable for SHM IGHV testing even for rapid results from individual samples. Generating 50,000 sequences per sample ensured sufficient coverage for reliable SHM detection and subclonal analysis, unlike Additionally, we provide results in less than 24 hours including just 1 hour sequencing, enabling a low-cost procedure that compares favorably with SS or second generation NGS.

Conclusions:

The new MinION chemistry and duplex basecalling offer a precise, faster, and cost-effective alternative to traditional SHM analysis methods. This approach enhances the detection of SHM and subclonal populations in CLL in the short-term, allowing for affordable real-time clinical decisions.

Disclosures

No relevant conflicts of interest to declare.

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