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Whole exome sequencing for cancer – is there evidence of clinical utility?

Authors Malhotra A, Levine S, Allingham-Hawkins D

Received 27 March 2014

Accepted for publication 13 May 2014

Published 22 August 2014 Volume 2014:4 Pages 115—128

DOI https://doi.org/10.2147/AGG.S58809

Checked for plagiarism Yes

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Peer reviewer comments 3


Video abstract presented by Diane Allingham-Hawkins.

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Alka Malhotra, Susan Levine, Diane Allingham-Hawkins

Genetic Test Evaluation Program, Winifred S Hayes, Inc., Lansdale, PA, USA

Background: In recent years, whole exome sequencing (WES), which allows detection of 85% of disease-causing variants, has been used to compare tumor and normal DNA to allow the identification of variants specific to the tumor. Genetic changes in cancer are increasingly used for diagnosis and may guide treatment decisions. In this paper, we explore whether there is evidence that WES improves outcomes for patients with cancer.
Methods: Published evidence was evaluated using a methodology that combines the analytical validity, clinical validity, clinical utility and ethical, legal, and social implications (ACCE) model for genetic test evaluations with internationally accepted health technology assessment methodology. Conclusions were based on peer-reviewed published studies of >10 patients, with ≥3 studies for a given phenotype.
Results: WES has been conducted most extensively (seven studies to date) in breast cancer patients, with fewer studies of other types of cancers (eg, leukemia, prostate cancer, and ovarian cancer). Studies evaluating somatic alterations showed high intratumor and intertumor heterogeneity. In addition, both novel and previously implicated variants were identified. However, only three studies with >10 individuals have shown potential for clinical utility of WES; whereby, variants identified through WES may determine response to drug treatment.
Conclusion: Despite evidence for clinical validity of WES in cancers, clinical utility is very limited and needs to be further evaluated in large clinical studies.

Keywords: next-generation sequencing, exons, evidence-based, ACCE model, health technology assessment

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