Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota.
Ambry Genetics, Aliso Viejo, California.
Hum Mutat. 2020 Aug;41(8):e1-e6. doi: 10.1002/humu.24053. Epub 2020 Jul 9.
Multigene panel testing for cancer predisposition mutations is becoming routine in clinical care. However, the gene content of panels offered by testing laboratories vary significantly, and data on mutation detection rates by gene and by the panel is limited, causing confusion among clinicians on which test to order. Using results from 147,994 multigene panel tests conducted at Ambry Genetics, we built an interactive prevalence tool to explore how differences in ethnicity, age of onset, and personal and family history of different cancers affect the prevalence of pathogenic mutations in 31 cancer predisposition genes, across various clinically available hereditary cancer gene panels. Over 13,000 mutation carriers were identified in this high-risk population. Most were non-Hispanic white (74%, n = 109,537), but also Black (n = 10,875), Ashkenazi Jewish (n = 10,464), Hispanic (n = 10,028), and Asian (n = 7,090). The most prevalent cancer types were breast (50%), ovarian (6.6%), and colorectal (4.7%), which is expected based on genetic testing guidelines and clinician referral for testing. The Hereditary Cancer Multi-Gene Panel Prevalence Tool presented here can be used to provide insight into the prevalence of mutations on a per-gene and per-multigene panel basis, while conditioning on multiple custom phenotypic variables to include race and cancer type.
多基因panel 检测在癌症易感性突变中的应用已成为临床常规。然而,不同检测实验室提供的panel 基因内容存在显著差异,且有关基因和panel 突变检测率的数据有限,导致临床医生在选择哪种检测方法时感到困惑。利用安布瑞遗传学(Ambry Genetics)进行的 147994 次多基因panel 检测结果,我们构建了一个交互式流行率工具,以探讨不同种族、发病年龄以及个人和家族不同癌症史对 31 个癌症易感性基因中致病性突变流行率的影响,涵盖了各种临床可用的遗传性癌症基因panel。在这个高危人群中,发现了超过 13000 名突变携带者。大多数是非西班牙裔白人(74%,n=109537),也有黑人(n=10875)、阿什肯纳兹犹太人(n=10464)、西班牙裔(n=10028)和亚洲人(n=7090)。最常见的癌症类型是乳腺癌(50%)、卵巢癌(6.6%)和结直肠癌(4.7%),这与遗传检测指南和临床医生的检测推荐相符。这里介绍的遗传性癌症多基因panel 流行率工具可以用来提供基于单个基因和多基因panel 的突变流行率的深入了解,同时还可以根据多个自定义表型变量(包括种族和癌症类型)进行条件设置。