Clinically actionable cancer somatic variants (CACSV): a tumor interpreted dataset for analytical workflows

Background: The recent development and enormous application of parallel sequencing technology in oncology has produced immense amounts of cell-specific genetic information. However, publicly available cell-specific genetic variants are not explained by well-established guidelines. Additionally, cell...

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Bibliographic Details
Main Authors: Al-Harbi, R. (Author), Bahussain, D. (Author), Sobahy, T.M (Author), Tashkandi, G. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2022
Subjects:
Online Access:View Fulltext in Publisher
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001 10.1186-s12920-022-01235-7
008 220510s2022 CNT 000 0 und d
020 |a 17558794 (ISSN) 
245 1 0 |a Clinically actionable cancer somatic variants (CACSV): a tumor interpreted dataset for analytical workflows 
260 0 |b BioMed Central Ltd  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1186/s12920-022-01235-7 
520 3 |a Background: The recent development and enormous application of parallel sequencing technology in oncology has produced immense amounts of cell-specific genetic information. However, publicly available cell-specific genetic variants are not explained by well-established guidelines. Additionally, cell-specific variants interpretation and classification has remained a challenging task and lacks standardization. The Association for Molecular Pathology (AMP), the American Society of Clinical Oncology (ASCO), and the College of American Pathologists (CAP) published the first consensus guidelines for cell-specific variants cataloging and clinical annotations. Methods: AMP–ASCO–CAP recommended sources and information were downloaded and used as follows: relative knowledge in oncology clinical practice guidelines; approved, investigative or preclinical drugs; supporting literature and each gene-tumor site correlation. All information was homogenized into a single knowledgebase. Finally, we incorporated the consensus recommendations into a new computational method. Results: A subset of cancer genetic variants was manually curated to benchmark our method and well-known computational algorithms. We applied the new method on freely available tumor-specific databases to produce a clinically actionable cancer somatic variants (CACSV) dataset in an easy-to-integrate format for most clinical analytical workflows. The research also showed the current challenges and limitations of using different classification systems or computational methods. Conclusion: CACSV is a step toward cell-specific genetic variants standardized interpretation as it is readily adaptable by most clinical laboratory pipelines for somatic variants clinical annotations. CACSV is freely accessible at (https://github.com/tsobahytm/CACSV/tree/main/dataset). © 2022, The Author(s). 
650 0 4 |a AMP–ASCO–CAP recommendations 
650 0 4 |a Genetic variant class 
650 0 4 |a Gene-tumor consensus 
650 0 4 |a Somatic genetic variants 
650 0 4 |a Tumor site(s) 
700 1 |a Al-Harbi, R.  |e author 
700 1 |a Bahussain, D.  |e author 
700 1 |a Sobahy, T.M.  |e author 
700 1 |a Tashkandi, G.  |e author 
773 |t BMC Medical Genomics