Abstract

PURPOSEClinical targeted sequencing panels are important for identifying actionable variants for patients with cancer; however, existing approaches do not provide transparent and rationally designed clinical panels to accommodate the rapidly growing knowledge within oncology.MATERIALS AND METHODSWe used the Clinical Interpretations of Variants in Cancer (CIViC) database to develop an Open-Sourced CIViC Annotation Pipeline (OpenCAP). OpenCAP provides methods to identify variants within the CIViC database, build probes for variant capture, use probes on prospective samples, and link somatic variants to CIViC clinical relevance statements. OpenCAP was tested using a single-molecule molecular inversion probe (smMIP) capture design on 27 cancer samples from 5 tumor types. In total, 2,027 smMIPs were designed to target 111 eligible CIViC variants (61.5 kb of genomic space).RESULTSWhen compared with orthogonal sequencing, CIViC smMIP sequencing demonstrated a 95% sensitivity for variant detection (n = 61 of 64 variants). Variant allele frequencies for variants identified on both sequencing platforms were highly concordant (Pearson’s r = 0.885; n = 61 variants). Moreover, for individuals with paired tumor and normal samples (n = 12), 182 clinically relevant variants missed by orthogonal sequencing were discovered by CIViC smMIP sequencing.CONCLUSIONThe OpenCAP design paradigm demonstrates the utility of an open-source and open-access database built on attendant community contributions with peer-reviewed interpretations. Use of a public repository for variant identification, probe development, and variant interpretation provides a transparent approach to build dynamic next-generation sequencing–based oncology panels.

Highlights

  • Despite recognition that genomics plays an important role in tumor prognosis, diagnosis, and treatment, scaling genetic analysis for routine analysis of most tumor specimens has been unattainable.[1,2] Barriers preventing widespread incorporation of genomic analysis into treatment protocols include costs associated with genomic sequencing and analysis,[3] computational limitations preventing timely identification of relevant variants,[3] and rapidly evolving knowledge of the clinical actionability of variants.[4]

  • For individuals with paired tumor and normal samples (n = 12), 182 clinically relevant variants missed by orthogonal sequencing were discovered by Clinical Interpretations of Variants in Cancer (CIViC) single-molecule molecular inversion probe (smMIP) sequencing

  • The Open-Sourced CIViC Annotation Pipeline (OpenCAP) design paradigm demonstrates the utility of an open-source and open-access database built on attendant community contributions with peer-reviewed interpretations

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Summary

Introduction

Despite recognition that genomics plays an important role in tumor prognosis, diagnosis, and treatment, scaling genetic analysis for routine analysis of most tumor specimens has been unattainable.[1,2] Barriers preventing widespread incorporation of genomic analysis into treatment protocols include costs associated with genomic sequencing and analysis,[3] computational limitations preventing timely identification of relevant variants,[3] and rapidly evolving knowledge of the clinical actionability of variants.[4]. More than 22% of oncologists have acknowledged limited confidence in their own understanding of how genomic knowledge applies to patients’ treatment, and 18% reported testing patients’ genetics infrequently.[5] In the face of exponential growth in clinically relevant genomic findings, driven by precision oncology efforts, there will likely be increased inability for physicians to command the most current information, resulting in increasing delay between academic discovery and clinical utility. This information gap has been described as the interpretation bottleneck.[4,5,6]

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