Genomic sequencing for characterizing tumor minimal residual disease versus early cancer

Abstract

One of the most frequent translocations in leukemia involves the fusion of the KMT2A gene with numerous partner genes — this involves multiple breakpoint regions, spanning different exons. The *KMT2A *fusion is a target for a recently approved therapeutic for treating leukemia. This translocation’s structural complexity has hindered the genetic and epigenetic characterization of these gene fusions. Consequently, the relationship between the genetic and epigenetic variations of KMT2A fusions and the cellular physiology of leukemia remains unclear. To address this question, we characterized *KMT2A *gene fusions in two types of acute leukemia (lymphocytic and myelocytic). We relied on a targeted approach utilizing long nanopore sequencing reads to analyze gene fusions between *KMT2A *and partner genes. Our characterization identified the exact breakpoints with base-pair resolution, determining phased variants across contigs containing the wild-type and fusion alleles. In parallel, we discovered distinct epigenetic changes, seen as methylation haplotypes that occurred across the *KMT2A *translocation. To provide a deeper genomic perspective, we used single-cell multiomics to assess the epigenetic changes as evident in chromatin accessibility and gene expression. Single-cell analysis with nanopore sequencing revealed a diverse landscape of different transcript isoforms from the gene fusion. These new results revealed unexpected diverse patterns of rearrangement methylation haplotypes and transcript isoforms. This added layer of genomic complexity may contribute to the efficacy of targeted agents for this translocation in leukemias.

Biography

Dr. Ji is a physician scientist and Professor at Stanford University. His research addresses basic and translational questions about cancer genetics and genomics. Hanlee’s research group has developed numerous DNA sequencing technologies for the characterization of cancer genomes, several of which have been used for clinical diagnostics. Currently, he is applying new single-molecule and single-cell sequencing strategies to identify clinically relevant features and cancer drug targets.