Comprehensive diagnostics of acute myeloid leukemia by whole transcriptome RNA sequencing

Wibowo Arindrarto, Daniel M. Borràs, Ruben A.L. de Groen, Redmar R. van den Berg, Irene J. Locher, Saskia A.M.E. van Diessen, Peter J.M. Valk, Bart Janssen, Erik B. van den Akker

Research output: Contribution to journalArticleScientificpeer-review

43 Citations (Scopus)
101 Downloads (Pure)


Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide risk-adapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications in FLT3 and KMT2A were detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform.

Original languageEnglish
Pages (from-to)47-61
Number of pages15
Issue number1
Publication statusPublished - 2021


Dive into the research topics of 'Comprehensive diagnostics of acute myeloid leukemia by whole transcriptome RNA sequencing'. Together they form a unique fingerprint.

Cite this