Haematology Department, Faculty of Medicine, King Abdulaziz University Hospital, King Abdulaziz University, Jeddah, Saudi Arabia.
Division of Pediatric Haematology Oncology, The Hospital for Sick Children, Toronto, Canada.
JCO Glob Oncol. 2024 May;10:e2300269. doi: 10.1200/GO.23.00269.
Molecular characterization is key to optimally diagnose and manage cancer. The complexity and cost of routine genomic analysis have unfortunately limited its use and denied many patients access to precision medicine. A possible solution is to rationalize use-creating a tiered approach to testing which uses inexpensive techniques for most patients and limits expensive testing to patients with the highest needs. Here, we tested the utility of this approach to molecularly characterize pediatric glioma in a cost- and time-sensitive manner.
We used a tiered testing pipeline of immunohistochemistry (IHC), customized fusion panels or fluorescence in situ hybridization (FISH), and targeted RNA sequencing in pediatric gliomas. Two distinct diagnostic algorithms were used for low- and high-grade gliomas (LGGs and HGGs). The percentage of driver alterations identified, associated testing costs, and turnaround time (TAT) are reported.
The tiered approach successfully characterized 96% (95 of 99) of gliomas. For 82 LGGs, IHC, targeted fusion panel or FISH, and targeted RNA sequencing solved 35% (29 of 82), 29% (24 of 82), and 30% (25 of 82) of cases, respectively. A total of 64% (53 of 82) of samples were characterized without targeted RNA sequencing. Of 17 HGG samples, 13 were characterized by IHC and four were characterized by targeted RNA sequencing. The average cost per sample was more affordable when using the tiered approach as compared with up-front targeted RNA sequencing in LGG ($405 US dollars [USD] $745 USD) and HGGs ($282 USD $745 USD). The average TAT per sample was also shorter using the tiered approach (10 days for LGG, 5 days for HGG 14 days for targeted RNA sequencing).
Our tiered approach molecularly characterized 96% of samples in a cost- and time-sensitive manner. Such an approach may be feasible in neuro-oncology centers worldwide, particularly in resource-limited settings.
分子特征分析对于优化癌症的诊断和治疗至关重要。然而，常规基因组分析的复杂性和成本限制了其应用，使许多患者无法获得精准医疗。一种可能的解决方案是合理利用资源——创建一个分层测试方法，该方法对大多数患者使用廉价技术，并将昂贵的测试限制在需求最高的患者。在此，我们以一种具有成本效益和时间效益的方式，测试了这种方法在小儿脑肿瘤分子特征分析中的实用性。
我们使用免疫组织化学（IHC）、定制融合面板或荧光原位杂交（FISH）以及靶向 RNA 测序的分层测试管道对小儿脑肿瘤进行分析。我们使用了两种不同的诊断算法用于低级别胶质瘤（LGG）和高级别胶质瘤（HGG）。报告了鉴定出的驱动突变的百分比、相关检测成本和周转时间（TAT）。
分层方法成功地对 96%（99 例中的 95 例）的脑肿瘤进行了特征分析。对于 82 例 LGG，IHC、靶向融合面板或 FISH 以及靶向 RNA 测序分别解决了 35%（29/82）、29%（24/82）和 30%（25/82）的病例。总共 64%（82 例中的 53 例）的样本无需靶向 RNA 测序即可进行特征分析。17 例 HGG 样本中，13 例通过 IHC 进行了特征分析，4 例通过靶向 RNA 测序进行了特征分析。与初始靶向 RNA 测序相比，使用分层方法时，LGG（405 美元至 745 美元）和 HGGs（282 美元至 745 美元）的每个样本的平均检测成本更具可承受性。使用分层方法时，每个样本的平均 TAT 也较短（LGG 为 10 天，HGG 为 5 天，靶向 RNA 测序为 14 天）。
我们的分层方法以具有成本效益和时间效益的方式对 96%的样本进行了分子特征分析。这种方法在全球神经肿瘤学中心，特别是在资源有限的环境中，可能是可行的。
