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

Turki M. Sobahy, Ghassan Tashkandi, Donya Bahussain, Raneem Al-Harbi

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


BackgroundThe 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.MethodsAMP-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.ResultsA 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.ConclusionCACSV 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 ( ).
Original languageEnglish (US)
JournalBMC Medical Genomics
Issue number1
StatePublished - Apr 25 2022
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-05-23
Acknowledgements: For computer time, this research used the resources of the Supercomputing Laboratory at King Abdullah University of Science & Technology (KAUST) in Thuwal, Saudi Arabia. The authors would like to thank the following: Samar A. Zailaie for reviewing the manuscript, Emily L. Heaphy for manuscript English review, Dalia Anbari for references formatting, Saja Basha and Salouf Al-Madani for their help in result tables’ designs.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)


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