FindDNAFusion : An Analytical Pipeline with Multiple Software Tools Improves Detection of Cancer-Associated Gene Fusions from Genomic DNA
Copyright © 2024 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved..
Detection of cancer-associated gene fusions is crucial for diagnosis, prognosis, and treatment selection. Many bioinformatics tools are available for the detection of fusion transcripts by RNA sequencing, but there are fewer well-validated software tools for DNA next-generation sequencing (NGS). A 542-gene solid tumor NGS panel was designed, with exonic probes supplemented with intronic bait probes against genes commonly involved in oncogenic fusions, with a focus on lung cancer. Three software tools for the detecting gene fusions in this DNA-NGS panel were selected and evaluated. The performance of these tools was compared after a pilot study, and each was configured for optimal batch analysis and detection rate. A blacklist for filtering common tool-specific artifacts, and criteria for selecting clinically reportable fusions, were established. Visualization tools for annotating and confirming somatic fusions were applied. Subsequently, a full clinical validation was used for comparing the results to those from in situ hybridization and/or RNA sequencing. With JuLI, Factera, and GeneFuse, 94.1%, 88.2%, and 66.7% of expected fusions were detected, respectively. With a combinatorial pipeline (termed FindDNAFusion), developed by integrating fusion-calling tools with methods for fusion filtering, annotating, and flagging reportable calls, the accuracy of detection of intron-tiled genes was improved to 98.0%. FindDNAFusion is an accurate and efficient tool in detecting somatic fusions in DNA-NGS panels with intron-tiled bait probes when RNA is unavailable.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:26 |
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| Enthalten in: |
The Journal of molecular diagnostics : JMD - 26(2024), 2 vom: 01. Jan., Seite 140-149 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Pan, Xiaokang [VerfasserIn] |
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| Anmerkungen: |
Date Completed 26.01.2024 Date Revised 26.01.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jmoldx.2023.11.004 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Detection of cancer-associated gene fusions is crucial for diagnosis, prognosis, and treatment selection. Many bioinformatics tools are available for the detection of fusion transcripts by RNA sequencing, but there are fewer well-validated software tools for DNA next-generation sequencing (NGS). A 542-gene solid tumor NGS panel was designed, with exonic probes supplemented with intronic bait probes against genes commonly involved in oncogenic fusions, with a focus on lung cancer. Three software tools for the detecting gene fusions in this DNA-NGS panel were selected and evaluated. The performance of these tools was compared after a pilot study, and each was configured for optimal batch analysis and detection rate. A blacklist for filtering common tool-specific artifacts, and criteria for selecting clinically reportable fusions, were established. Visualization tools for annotating and confirming somatic fusions were applied. Subsequently, a full clinical validation was used for comparing the results to those from in situ hybridization and/or RNA sequencing. With JuLI, Factera, and GeneFuse, 94.1%, 88.2%, and 66.7% of expected fusions were detected, respectively. With a combinatorial pipeline (termed FindDNAFusion), developed by integrating fusion-calling tools with methods for fusion filtering, annotating, and flagging reportable calls, the accuracy of detection of intron-tiled genes was improved to 98.0%. FindDNAFusion is an accurate and efficient tool in detecting somatic fusions in DNA-NGS panels with intron-tiled bait probes when RNA is unavailable | ||
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