Department of Pediatrics, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kawaramachi-Hirokoji Kamigyo-ku, Kyoto 602-8566, Japan.
Jpn J Clin Oncol. 2019 Aug 1;49(8):743-748. doi: 10.1093/jjco/hyz063.
Our previous study reported a method for determining MYCN gene amplification (MNA) status using cell-free DNA in serum. We prospectively analyzed the serum MNA status using sera obtained before the initial diagnosis from patients with neuroblastoma and evaluated the utility of this method.
Eighty patients were enrolled in the study. The serum MYCN/NAGK ratio was assessed for all cases.
Fifteen cases showed serum MNA, while 65 did not. Of the 80 total patients, tumor samples for a genetic analysis were not obtained from 27 due to the patients' condition or other reasons. For the 43 of 80 cases that had both serum and tumor samples analyzed, the serum-based MNA status matched to tumor-based MNA status (P < 0.001). The sensitivity and the specificity were 100%, respectively. Seven of 15 cases who diagnosed as MNA by serum-based MNA status were <18 months of age, and tumor samples were not obtained from 4 of these cases. Based on the serum MNA status, these cases were able to start treatment immediately. The 4-year event-free survival rates of cases with and without MNA in sera were 37.5% and 84.8%, respectively (P < 0.001).
The serum-based MNA status was useful for precisely predicting the MNA status in tumor and it has clinical benefits for predicting risk stratification in patients for whom obtaining tumor samples is difficult.
我们之前的研究报道了一种使用血清中的游离 DNA 来确定 MYCN 基因扩增 (MNA) 状态的方法。我们前瞻性地分析了神经母细胞瘤患者初始诊断前获得的血清中的血清 MNA 状态,并评估了该方法的实用性。
本研究纳入了 80 例患者。对所有病例均评估血清 MYCN/NAGK 比值。
15 例显示血清 MNA,而 65 例未显示。在 80 例总患者中,由于患者的病情或其他原因,有 27 例无法获得肿瘤样本进行基因分析。对于 80 例中有血清和肿瘤样本分析的 43 例患者,基于血清的 MNA 状态与基于肿瘤的 MNA 状态相匹配(P < 0.001)。敏感性和特异性分别为 100%。通过基于血清的 MNA 状态诊断为 MNA 的 15 例病例中,有 7 例年龄<18 个月,其中 4 例无法获得肿瘤样本。根据血清 MNA 状态,这些病例可以立即开始治疗。血清中存在和不存在 MNA 的病例的 4 年无事件生存率分别为 37.5%和 84.8%(P < 0.001)。
基于血清的 MNA 状态可用于准确预测肿瘤中的 MNA 状态,对于预测难以获得肿瘤样本的患者的风险分层具有临床意义。