Publication Only: Acute myeloid leukemia - Biology & translational research
As driver gene fusions that cause hematological malignancy continues to be discovered, appropriate detection methods are needed to diagnose it. Although the conventional multiplex RT-PCR method showed high sensitivity and specificity, there was a limitation in detecting various newly discovered fusion transcripts. Recently, the next-generation sequencing (NGS) method introduced into clinical laboratories has been successfully applied to DNA sequencing, while RNA sequencing (RNA-Seq) have not yet been widely used. This is because of the concerns about sensitivity and specificity, although RNA-Seq based test have the advantage of being able to detect various novel fusion transcripts.
The aim of this study was to develop an optimized fusion transcript detection method that can accurately detect clinically important pathogenic gene fusions and minimize false positive results by analyzing RNA-Seq results in various hematological malignancies.
RNA-Seq was performed in 11 patients with hematologic malignancies (4 AML, 2 APL, 2 ALL, and 3 CML) diagnosed at Chonnam National University Hwasun Hospital, using RNA samples extracted from bone marrow aspirates at the diagnosis. Library were prepared with 1 ug of total RNA for each sample by TruSeq mRNA Sample Prep kit (Illumina, San Diego, USA). Indexed libraries were sequenced using HiSeq2500 platform (Illumina). The data obtained from the sequencing was analyzed using STAR-Fusion (v1.2.0) and the final pathogenic fusion transcripts were selected by applying the filtering algorithm developed in this study.
A total of 12594 fusion transcripts were detected from RNA-Seq results in 11 subjects, which was 1144.9 per patient. An average of 1.8 final pathogenic fusion transcripts were detected per sample using the optimized filtering algorithm from step 1 to step 4 (fig. 1). The results were consistent with those of conventional multiplex RT-PCR. The analytical performances of the RNA-Seq assay for pathogenic fusion detection were a sensitivity of 100% and a specificity of 99.98%. Though the clinical significance was not clear, the presence of five novel fusion transcripts has been demonstrated by direct sequencing.
By applying the filtering algorithm developed in this study, it was possible to find all the pathogenic fusion transcripts with the sensitivity and specificity comparable to the conventional multiplex RT-PCR method. Using RNA-Seq, it is possible to identify the exact nucleotide sequence of the fusion transcript and to predict the amino acid sequence of the fusion protein. Therefore RNA-Seq can be used to establish accurate targets for diagnosis, treatment, and prognosis, and this will open new horizons for future diagnosis and treatment of hematologic malignancies.