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Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
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Available resources and challenges for the clinical annotation of somatic variations
1Department of Pathology, Virginia Commonwealth University, Richmond, Virginia.
Cancer Cytopathology
|August 12, 2014
Summary
Next-generation sequencing (NGS) identifies genetic variants for inherited disorders and cancer. This review focuses on somatic variation databases crucial for interpreting cancer sequencing data and clinical reporting.
Area of Science:
- Genomics
- Bioinformatics
- Clinical Oncology
Background:
- Next-generation sequencing (NGS) is vital for identifying clinically relevant genetic variants in inherited diseases and cancer.
- Variant annotation relies on diverse public databases, including those for germline variants.
- Analyzing tumor specimens requires specialized resources for somatic variants and actionable mutations.
Purpose of the Study:
- To review the current landscape of somatic variation databases for clinical oncology.
- To discuss the interpretation of NGS-based assays in cancer using these databases.
- To highlight the need for integrated annotation solutions.
Main Methods:
- Literature review of existing somatic variation databases.
- Analysis of current practices in clinical variant annotation for oncology.
- Discussion of challenges and future directions in database integration.
Main Results:
- Numerous databases exist for germline variants, but specialized resources are needed for somatic variants in cancer.
- Somatic variation databases aid in identifying actionable mutations with clinical and treatment implications.
- Current annotation processes often involve multiple disparate resources.
Conclusions:
- Somatic variation databases are essential for the clinical interpretation of NGS in oncology.
- There is a growing need for consolidated, "one-stop" annotation solutions.
- Improved integration of databases into laboratory information systems is necessary for efficient clinical workflows.
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