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Resources for Interpreting Variants in Precision Genomic Oncology Applications
Hsinyi Tsang1,2, KanakaDurga Addepalli1,2, Sean R Davis3
1Center for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Gaithersburg, MD, United States.
Precision genomic oncology uses high-throughput sequencing (HTS) to guide cancer treatment. This review covers tools for interpreting genomic variants to personalize patient care and discover new therapeutic hypotheses.
Area of Science:
- Genomic Medicine
- Oncology
- Bioinformatics
Background:
- Precision genomic oncology, utilizing high-throughput sequencing (HTS) at the point-of-care, is an emerging precision medicine approach with increasing clinical adoption.
- Advancements in targeted therapies and immunotherapy offer benefits to patients with comprehensive genomic characterization.
- Identifying germline and somatic variants is established, but individual variant interpretation remains a significant challenge.
Purpose of the Study:
- To review data and software resources for interpreting genomic variants in oncology.
- To discuss tools for assessing variant clinical actionability and augmenting data for decision-making.
- To highlight resources for both ad hoc research sample analysis and formal clinical reporting platforms.
Main Methods:
- Review of existing variant catalogs.
- Assessment of variant and functional annotation software and tools.
- Compilation of databases for clinically actionable variants.
Main Results:
- A range of resources exist to aid in the interpretation of genomic variants.
- These tools facilitate the determination of clinical actionability and provide ancillary information.
- The reviewed resources can be applied in research settings or integrated into clinical reporting systems.
Conclusions:
- Effective interpretation of genomic variants is crucial for precision oncology.
- Available data and software resources support clinical decision-making and hypothesis generation.
- A systematic approach to variant interpretation enhances the utility of genomic data in patient care.
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