Abstract：
Next generation sequencing for oncology patient management is now routine in clinical pathology laboratories. Although wet lab, sequencing and pipeline tasks are largely automated, the analysis of variants for clinical reporting remains largely a manual task. The increasing volume of sequencing data and the limited availability of genetic experts to analyse and report on variants in the data is a key scalability limit for molecular diagnostics.
To determine the impact and size of the issue, we examined the longitudinally compiled genetic variants from 48,036 cancer patients over a six year period in a large cancer hospital from ten targeted cancer panel tests in germline, solid tumour and haematology contexts using hybridization capture and amplicon assays. This testing generated 24,168,398 sequenced variants of which 23,255 (8214 unique) were clinically reported.
Of the reported variants, 17,240 (74.1%) were identified in more than one assay which allowed curated variant data to be reused in later reports. The remainder, 6015 (25.9%) were not subsequently seen in later assays and did not provide any reuse benefit. The number of new variants requiring curation has significantly increased over time from 1.72 to 3.73 variants per sample (292 curated variants per month). Analysis of the 23,255 variants reported, showed 28.6% (n = 2356) were not present in common public variant resources and therefore required de novo curation. These in-house only variants were enriched for indels, tumour suppressor genes and from solid tumour assays.
This analysis highlights the significant percentage of variants not present within common public variant resources and the level of non-recurrent variants that consequently require greater curation effort. Many of these variants are unique to a single patient and unlikely to appear in other patients reflecting the personalised nature of cancer genomics. This study depicts the real-world situation for pathology laboratories faced with curating increasing numbers of low-recurrence variants while needing to expedite the process of manual variant curation. In the absence of suitably accurate automated methods, new approaches are needed to scale oncology diagnostics for future genetic testing volumes.
To determine the impact and size of the issue, we examined the longitudinally compiled genetic variants from 48,036 cancer patients over a six year period in a large cancer hospital from ten targeted cancer panel tests in germline, solid tumour and haematology contexts using hybridization capture and amplicon assays. This testing generated 24,168,398 sequenced variants of which 23,255 (8214 unique) were clinically reported.
Of the reported variants, 17,240 (74.1%) were identified in more than one assay which allowed curated variant data to be reused in later reports. The remainder, 6015 (25.9%) were not subsequently seen in later assays and did not provide any reuse benefit. The number of new variants requiring curation has significantly increased over time from 1.72 to 3.73 variants per sample (292 curated variants per month). Analysis of the 23,255 variants reported, showed 28.6% (n = 2356) were not present in common public variant resources and therefore required de novo curation. These in-house only variants were enriched for indels, tumour suppressor genes and from solid tumour assays.
This analysis highlights the significant percentage of variants not present within common public variant resources and the level of non-recurrent variants that consequently require greater curation effort. Many of these variants are unique to a single patient and unlikely to appear in other patients reflecting the personalised nature of cancer genomics. This study depicts the real-world situation for pathology laboratories faced with curating increasing numbers of low-recurrence variants while needing to expedite the process of manual variant curation. In the absence of suitably accurate automated methods, new approaches are needed to scale oncology diagnostics for future genetic testing volumes.
摘要：
用于肿瘤患者管理的下一代测序现在在临床病理学实验室中是常规的。虽然潮湿的实验室，排序和流水线任务基本上是自动化的，临床报告的变异分析在很大程度上仍是一项人工任务.测序数据量的增加和遗传专家分析和报告数据中变异的有限可用性是分子诊断的关键可扩展性限制。
要确定问题的影响和大小，我们检查了纵向汇编的遗传变异从48,036癌症患者在一个大的癌症医院在六年期间从10个靶向癌症小组测试在种系,使用杂交捕获和扩增子测定的实体瘤和血液学背景。该测试产生了24,168,398个测序变体,其中23,255个(8214个独特)被临床报道。
在报告的变体中，在一个以上的测定中鉴定出17,240(74.1%),这允许在以后的报告中重新使用所策划的变体数据。剩下的,6015(25.9%)随后在随后的测定中没有看到,并且没有提供任何再使用益处。需要策展的新变体的数量随着时间的推移从每个样品的1.72个显著增加至3.73个变体(每月292个策展的变体)。对报告的23,255种变体进行分析，显示28.6%(n=2356)不存在于公共变异资源中，因此需要从头管理。这些仅在内部的变体被丰富用于indel，肿瘤抑制基因和来自实体瘤测定。
该分析突出了常见公共变体资源中不存在的变体的显著百分比以及因此需要更大的管理努力的非复发变体的水平。这些变体中的许多对于单个患者是独特的,并且不太可能出现在反映癌症基因组学的个性化性质的其他患者中。这项研究描述了病理学实验室面临的现实世界中的情况，在需要加快手动变体策展过程的同时，策划了越来越多的低复发变体。在缺乏适当准确的自动化方法的情况下，需要新的方法来扩展未来基因检测量的肿瘤学诊断.
要确定问题的影响和大小，我们检查了纵向汇编的遗传变异从48,036癌症患者在一个大的癌症医院在六年期间从10个靶向癌症小组测试在种系,使用杂交捕获和扩增子测定的实体瘤和血液学背景。该测试产生了24,168,398个测序变体,其中23,255个(8214个独特)被临床报道。
在报告的变体中，在一个以上的测定中鉴定出17,240(74.1%),这允许在以后的报告中重新使用所策划的变体数据。剩下的,6015(25.9%)随后在随后的测定中没有看到,并且没有提供任何再使用益处。需要策展的新变体的数量随着时间的推移从每个样品的1.72个显著增加至3.73个变体(每月292个策展的变体)。对报告的23,255种变体进行分析，显示28.6%(n=2356)不存在于公共变异资源中，因此需要从头管理。这些仅在内部的变体被丰富用于indel，肿瘤抑制基因和来自实体瘤测定。
该分析突出了常见公共变体资源中不存在的变体的显著百分比以及因此需要更大的管理努力的非复发变体的水平。这些变体中的许多对于单个患者是独特的,并且不太可能出现在反映癌症基因组学的个性化性质的其他患者中。这项研究描述了病理学实验室面临的现实世界中的情况，在需要加快手动变体策展过程的同时，策划了越来越多的低复发变体。在缺乏适当准确的自动化方法的情况下，需要新的方法来扩展未来基因检测量的肿瘤学诊断.
