Katherina M Alsina, Lauren M Sholl, Kyle R Covington, Suzzette M Arnal, Michael A Durante, Christina L Decatur, John F Stone, Kristen M Oelschlager, J William Harbour, Federico A Monzon, Robert W Cook, Sherri Borman
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This study evaluated the analytical performance of a targeted custom NGS panel for mutational profiling of 7 genes commonly mutated in UM.</p><p><strong>Methods: </strong>One hundred five primary UM tumors were analyzed, including 37 formalin-fixed paraffin-embedded (FFPE) and 68 fine-needle aspiration biopsy specimens. Sequencing was performed on the Ion GeneStudio S5 platform to an average read depth of >500X per region of interest.</p><p><strong>Results: </strong>The 7-gene panel achieved a positive percent agreement of 100% for detection of both single-nucleotide variants and insertions/deletions, with a technical positive predictive value of 98.8% and 100%, respectively. Intra-assay and inter-assay concordance studies confirmed the assay's reproducibility and repeatability.</p><p><strong>Discussion/conclusion: </strong>The 7-gene panel is a robust, highly accurate NGS test that can be successfully performed, along with GEP, from a single small-gauge needle biopsy sample or FFPE specimen.</p>","PeriodicalId":19434,"journal":{"name":"Ocular Oncology and Pathology","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8739387/pdf/oop-0007-0428.pdf","citationCount":"0","resultStr":"{\"title\":\"Analytical Validation and Performance of a 7-Gene Next-Generation Sequencing Panel in Uveal Melanoma.\",\"authors\":\"Katherina M Alsina, Lauren M Sholl, Kyle R Covington, Suzzette M Arnal, Michael A Durante, Christina L Decatur, John F Stone, Kristen M Oelschlager, J William Harbour, Federico A Monzon, Robert W Cook, Sherri Borman\",\"doi\":\"10.1159/000518829\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Gene expression profiling (GEP) is widely used for prognostication in patients with uveal melanoma (UM). 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引用次数: 0
摘要
简介基因表达谱(GEP)被广泛用于葡萄膜黑色素瘤(UM)患者的预后判断。由于活检组织有限,因此从每个样本中获取尽可能多的基因组信息至关重要。结合应用 GEP 和新一代测序(NGS)可对单个活检样本的 RNA 和 DNA 进行分析,提供额外的预后信息,并有可能为治疗选择提供依据。本研究评估了有针对性的定制 NGS 面板的分析性能,以分析 UM 中常见的 7 个突变基因:分析了 105 例原发性 UM 肿瘤,包括 37 例福尔马林固定石蜡包埋(FFPE)和 68 例细针穿刺活检标本。测序在 Ion GeneStudio S5 平台上进行,每个感兴趣区的平均读取深度大于 500 倍:结果:7 个基因面板检测单核苷酸变异和插入/缺失的阳性率均为 100%,技术阳性预测值分别为 98.8%和 100%。测定内和测定间的一致性研究证实了该测定的再现性和可重复性:7 基因面板是一种稳健、高度准确的 NGS 检测方法,可与 GEP 一起从单个小号针活检样本或 FFPE 标本中成功进行检测。
Analytical Validation and Performance of a 7-Gene Next-Generation Sequencing Panel in Uveal Melanoma.
Introduction: Gene expression profiling (GEP) is widely used for prognostication in patients with uveal melanoma (UM). Because biopsy tissue is limited, it is critical to obtain as much genomic information as possible from each sample. Combined application of both GEP and next-generation sequencing (NGS) allows for analysis of RNA and DNA from a single biopsy sample, offers additional prognostic information, and can potentially inform therapy selection. This study evaluated the analytical performance of a targeted custom NGS panel for mutational profiling of 7 genes commonly mutated in UM.
Methods: One hundred five primary UM tumors were analyzed, including 37 formalin-fixed paraffin-embedded (FFPE) and 68 fine-needle aspiration biopsy specimens. Sequencing was performed on the Ion GeneStudio S5 platform to an average read depth of >500X per region of interest.
Results: The 7-gene panel achieved a positive percent agreement of 100% for detection of both single-nucleotide variants and insertions/deletions, with a technical positive predictive value of 98.8% and 100%, respectively. Intra-assay and inter-assay concordance studies confirmed the assay's reproducibility and repeatability.
Discussion/conclusion: The 7-gene panel is a robust, highly accurate NGS test that can be successfully performed, along with GEP, from a single small-gauge needle biopsy sample or FFPE specimen.