Detection of Hybrid Fusion Transcripts, Aberrant Transcript Expression and Specific Single Nucleotide Variants in Acute Leukemia and Myeloid Disorders with Recurrent Gene Rearrangements. Academic Article uri icon

Overview

abstract

  • INTRODUCTION: A variety of gene rearrangements and molecular alterations are key drivers in the pathobiology of acute leukemia and myeloid disorders; current classification systems increasingly incorporate these findings in diagnostic algorithms. Therefore, clinical laboratories require versatile tools, which can detect an increasing number and variety of molecular and cytogenetic alterations of clinical significance. METHODS: We validated an RNA-based NGS assay that enables the detection of: i) numerous hybrid fusion transcripts (including rare/novel gene partners), ii) aberrantly expressed EVI1(MECOM) and IKZF1 (Del Exons 4-7) transcripts, and iii) hotspot variants in KIT, ABL1, NPM1 (relevant in the context of gene rearrangement status). RESULTS: For hybrid fusion transcripts, the assay showed 98-100% concordance for known positive and negative samples, with an analytical sensitivity (ie, limit of detection) of approximately 0.8% cells. Cases with underlying EVI1 (MECOM) translocations demonstrated increased EVI1(MECOM) expression. Aberrant IKZF1 (Del Exons 4-7) transcripts detectable with the assay were also present on orthogonal RT-PCR. Specific hotspot mutations in KIT, ABL1 and NPM1 detected with the assay showed 100% concordance with orthogonal testing. Lastly, several illustrative cases are included to highlight the assay's clinically relevant contributions to patient work-up. DISCUSSION/CONCLUSION: Through its ability to simultaneously detect various gene rearrangements, aberrantly expressed transcripts and hotspot mutations, this RNA-based NGS assay is a valuable tool for clinical laboratories to supplement other molecular and cytogenetic methods used in the diagnostic workup, and in clinical research, for patients with acute leukemia and myeloid disorders.

publication date

  • July 25, 2023

Research

keywords

  • Leukemia, Myeloid, Acute

Identity

Digital Object Identifier (DOI)

  • 10.1159/000532085

PubMed ID

  • 37490880