2016 Articles
Pathogenic Mutations in Cancer-Predisposing Genes: A Survey of 300 Patients with Whole-Genome Sequencing and Lifetime Electronic Health Records
Background: It is unclear whether and how whole-genome sequencing (WGS) data can be used to implement genomic medicine. Our objective is to retrospectively evaluate whether WGS can facilitate improving prevention and care for patients with susceptibility to cancer syndromes.
Methods and Findings: We analyzed genetic mutations in 60 autosomal dominant cancer-predisposition genes in 300 deceased patients with WGS data and nearly complete long-term (over 30 years) medical records. To infer biological insights from massive amounts of WGS data and comprehensive clinical data in a short period of time, we developed an in-house analysis pipeline within the SeqHBase software framework to quickly identify pathogenic or likely pathogenic variants. The clinical data of the patients who carried pathogenic and/or likely pathogenic variants were further reviewed to assess their clinical conditions using their lifetime EHRs. Among the 300 participants, 5 (1.7%) carried pathogenic or likely pathogenic variants in 5 cancer-predisposing genes: one in APC, BRCA1, BRCA2, NF1, and TP53 each. When assessing the clinical data, each of the 5 patients had one or more different types of cancers, fully consistent with their genetic profiles. Among these 5 patients, 2 died due to cancer while the others had multiple disorders later in their lifetimes; however, they may have benefited from early diagnosis and treatment for healthier lives, had the patients had genetic testing in their earlier lifetimes.
Conclusions: We demonstrated a case study where the discovery of pathogenic or likely pathogenic germline mutations from population-wide WGS correlates with clinical outcome. The use of WGS may have clinical impacts to improve healthcare delivery.
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- journal.pone.0167847.pdf application/pdf 908 KB Download File
Also Published In
- Title
- PLoS ONE
- DOI
- https://doi.org/10.1371/journal.pone.0167847
More About This Work
- Academic Units
- Biomedical Informatics
- Publisher
- Public Library of Science
- Published Here
- February 8, 2017