Xiaokang Pan , Huolin Tu , Nehad Mohamed , Matthew Avenarius , Sean Caruthers , Weiqiang Zhao , Dan Jones
{"title":"FindDNAFusion:多种软件工具的分析管道提高了基因组DNA中癌症相关基因融合的检测。","authors":"Xiaokang Pan , Huolin Tu , Nehad Mohamed , Matthew Avenarius , Sean Caruthers , Weiqiang Zhao , Dan Jones","doi":"10.1016/j.jmoldx.2023.11.004","DOIUrl":null,"url":null,"abstract":"<div><p>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 <em>in situ</em> 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.</p></div>","PeriodicalId":50128,"journal":{"name":"Journal of Molecular Diagnostics","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1525157823002751/pdfft?md5=7ffc0cf0a98d4d83957d178b88b5c556&pid=1-s2.0-S1525157823002751-main.pdf","citationCount":"0","resultStr":"{\"title\":\"FindDNAFusion\",\"authors\":\"Xiaokang Pan , Huolin Tu , Nehad Mohamed , Matthew Avenarius , Sean Caruthers , Weiqiang Zhao , Dan Jones\",\"doi\":\"10.1016/j.jmoldx.2023.11.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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 <em>in situ</em> 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.</p></div>\",\"PeriodicalId\":50128,\"journal\":{\"name\":\"Journal of Molecular Diagnostics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2023-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1525157823002751/pdfft?md5=7ffc0cf0a98d4d83957d178b88b5c556&pid=1-s2.0-S1525157823002751-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Molecular Diagnostics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1525157823002751\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PATHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Diagnostics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1525157823002751","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PATHOLOGY","Score":null,"Total":0}
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.
期刊介绍:
The Journal of Molecular Diagnostics, the official publication of the Association for Molecular Pathology (AMP), co-owned by the American Society for Investigative Pathology (ASIP), seeks to publish high quality original papers on scientific advances in the translation and validation of molecular discoveries in medicine into the clinical diagnostic setting, and the description and application of technological advances in the field of molecular diagnostic medicine. The editors welcome for review articles that contain: novel discoveries or clinicopathologic correlations including studies in oncology, infectious diseases, inherited diseases, predisposition to disease, clinical informatics, or the description of polymorphisms linked to disease states or normal variations; the application of diagnostic methodologies in clinical trials; or the development of new or improved molecular methods which may be applied to diagnosis or monitoring of disease or disease predisposition.