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Published on: March 13, 2019
From somatic variants towards precision oncology: Evidence-driven reporting of treatment options in molecular tumor
Júlia Perera-Bel1, Barbara Hutter2, Christoph Heining3
1Department of Medical Statistics, University Medical Center Göttingen, 37073, Göttingen, Germany.
Background:
A comprehensive understanding of cancer has been furthered with technological improvements and decreasing costs of next-generation sequencing (NGS). However, the complexity of interpreting genomic data is hindering the implementation of high-throughput technologies in the clinical context: increasing evidence on gene-drug interactions complicates the task of assigning clinical significance to genomic variants.
Methods:
Here we present a method that automatically matches patient-specific genomic alterations to treatment options. The method relies entirely on public knowledge of somatic variants with predictive evidence on drug response. The output report is aimed at supporting clinicians in the task of finding the clinical meaning of genomic variants. We applied the method to 1) The Cancer Genome Atlas (TCGA) and Genomics Evidence Neoplasia Information Exchange (GENIE) cohorts and 2) 11 patients from the NCT MASTER trial whose treatment discussions included information on their genomic profiles.
Results:
Our reporting strategy showed a substantial number of patients with actionable variants in the analyses of TCGA and GENIE samples. Notably, it was able to reproduce experts' treatment suggestions in a retrospective study of 11 patients from the NCT MASTER trial. Our results establish a proof of concept for comprehensive, evidence-based reports as a supporting tool for discussing treatment options in tumor boards.
Conclusions:
We believe that a standardized method to report actionable somatic variants will smooth the incorporation of NGS in the clinical context. We anticipate that tools like the one we present here will become essential in summarizing for clinicians the growing evidence in the field of precision medicine. The R code of the presented method is provided in Additional file 6 and available at https://github.com/jperera-bel/MTB-Report .
Insights
A new method automatically matches patient genomic alterations to cancer treatments using public data. This tool aids clinicians in interpreting genomic variants for precision medicine, supporting tumor board discussions and treatment decisions.
Area of Science:
- Genomic Medicine
- Bioinformatics
- Computational Biology
Background:
- Next-generation sequencing (NGS) advances cancer understanding but genomic data interpretation remains complex.
- Identifying clinical significance of genomic variants is challenging due to intricate gene-drug interactions.
Purpose of the Study:
- To develop an automated method for matching patient-specific genomic alterations to potential cancer treatment options.
- To support clinicians in assigning clinical significance to genomic variants for improved patient care.
Main Methods:
- The method utilizes public knowledge of somatic variants and their predictive evidence on drug response.
- Applied to The Cancer Genome Atlas (TCGA) and Genomics Evidence Neoplasia Information Exchange (GENIE) cohorts.
- Validated on 11 patients from the NCT MASTER trial with genomic profile information.
Main Results:
- The reporting strategy identified a significant number of actionable variants in TCGA and GENIE samples.
- The method successfully reproduced expert treatment suggestions in a retrospective analysis of NCT MASTER trial patients.
- Established proof of concept for evidence-based reports to aid tumor board discussions.
Conclusions:
- A standardized method for reporting actionable somatic variants can facilitate NGS integration into clinical practice.
- Tools summarizing precision medicine evidence are crucial for clinicians.
- The presented method and code aim to streamline genomic data interpretation for targeted therapies.
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