Multiclonal Profiling of FLT3-ITD in AML Using MinION Sequencing: A Tailored Clustering Approach to Enhance Subclonal...

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• FLT3-ITDs are key drivers in acute myeloid leukemia (AML), linked to poor prognosis and treatment resistance.
• Generic structural variant callers struggle to detect low-frequency FLT3-ITDs and resolve clonal diversity.
• There is a need for specialized bioinformatics tools to accurately identify FLT3-ITDs in AML.

Purpose of the Study:

• To develop a custom bioinformatics pipeline for sensitive and accurate detection of FLT3-ITDs in AML.
• To improve the characterization of clonal architecture and subclonal diversity in AML patients.
• To overcome the limitations of existing general-purpose structural variant callers for FLT3-ITD detection.

Main Methods:

• Developed a clustering-based bioinformatics pipeline leveraging Oxford Nanopore MinION sequencing.
• Focused on grouping near-identical FLT3-ITD insertions to identify subclones and low-frequency variants.
• Benchmarked the custom pipeline against capillary electrophoresis and the Sniffles caller, validating results with IGV inspection.

Main Results:

• The custom pipeline successfully detected FLT3-ITDs in all samples, including low-frequency variants missed by Sniffles.
• Identified complex multiclonal architectures with dominant and minor subclones exhibiting sequence and breakpoint variations.
• Detected very short duplications (as small as 15 bp) often overlooked by conventional callers.

Conclusions:

• Third-generation sequencing with a tailored clustering strategy enhances FLT3-ITD and clonal diversity detection in AML.
• This specialized approach provides critical insights into subclonal populations driving relapse and therapeutic resistance.
• The findings underscore the importance of dedicated pipelines for precision medicine in leukemia, especially for relapsed/refractory cases.