Javascript must be enabled to continue!
PB1695 ACCURATE DETECTION OF PATHOGENIC FUSION TRANSCRIPTS IN HEMATOLOGICAL MALIGNANCIES USING RNA‐SEQ AND STAR‐FUSION
View through CrossRef
Background: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.Aims: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.Methods: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.Results: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.Summary/Conclusion: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.image
Title: PB1695 ACCURATE DETECTION OF PATHOGENIC FUSION TRANSCRIPTS IN HEMATOLOGICAL MALIGNANCIES USING RNA‐SEQ AND STAR‐FUSION
Description:
Background: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.
Aims: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.
Methods: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.
Results: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.
Summary/Conclusion: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.
image.
Related Results
Abstract 4180: Protocol-specific and coverage-based RNA-seq metrics characterize RNA integrity signatures across cohorts
Abstract 4180: Protocol-specific and coverage-based RNA-seq metrics characterize RNA integrity signatures across cohorts
Abstract
Background:
RNA degradation profoundly impacts transcript quantification and downstream biological interpretatio...
Diagnostic Validation of a Clinical Laboratory-Oriented Targeted RNA Sequencing System As a Comprehensive Assay for Hematologic Malignancies
Diagnostic Validation of a Clinical Laboratory-Oriented Targeted RNA Sequencing System As a Comprehensive Assay for Hematologic Malignancies
Introduction Targeted RNA sequencing (RNA-seq) is a highly accurate method for sequencing transcripts of interest and can overcome limitations regarding resolution, throughput, and...
Are Cervical Ribs Indicators of Childhood Cancer? A Narrative Review
Are Cervical Ribs Indicators of Childhood Cancer? A Narrative Review
Abstract
A cervical rib (CR), also known as a supernumerary or extra rib, is an additional rib that forms above the first rib, resulting from the overgrowth of the transverse proce...
RNA Sequencing Based Whole Transcriptome Analysis Detected Precisely All Fusion Transcripts in Leukemias
RNA Sequencing Based Whole Transcriptome Analysis Detected Precisely All Fusion Transcripts in Leukemias
Abstract
Introduction: Fusion transcript is a chimeric RNA encoded by a fusion gene or by two different genes by subsequent trans-splicing. Detection of fusion trans...
MARS-seq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing v1
MARS-seq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing v1
Human tissues comprise trillions of cells that populate a complex space of molecular phenotypes and functions and that vary in abundance by 4–9 orders of magnitude. Relying solely ...
Long-read single-cell isoform sequencing for cell type-specific detection of genomic rearrangement-dependent and -independent fusion transcripts
Long-read single-cell isoform sequencing for cell type-specific detection of genomic rearrangement-dependent and -independent fusion transcripts
Abstract
Background: Fusion transcripts are formed by combining exons from two different genes, often due to structural ...
Abstract P1-05-23: Utilities and challenges of RNA-Seq based expression and variant calling in a clinical setting
Abstract P1-05-23: Utilities and challenges of RNA-Seq based expression and variant calling in a clinical setting
Abstract
Introduction
Variant calling based on DNA samples has been the gold standard of clinical testing since the advent of Sanger sequencing. The u...
The Diverse Landscape of Fusion Transcripts in 25 Different Hematological Entities
The Diverse Landscape of Fusion Transcripts in 25 Different Hematological Entities
Background: Genomic alterations are a hallmark of hematological malignancies and comprise small nucleotide variants, copy number alterations and structural variants (SV). SV lead t...

