Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
Medical Department, Matridx Biotechnology Co., Ltd., Hangzhou, Zhejiang, China.
Front Cell Infect Microbiol. 2023 Aug 22;13:1211732. doi: 10.3389/fcimb.2023.1211732. eCollection 2023.
Differentiation between benign and malignant diseases in EBV-positive patients poses a significant challenge due to the lack of efficient diagnostic tools. Metagenomic Next-Generation Sequencing (mNGS) is commonly used to identify pathogens of patients with fevers of unknown-origin (FUO). Recent studies have extended the application of Next-Generation Sequencing (NGS) in identifying tumors in body fluids and cerebrospinal fluids. In light of these, we conducted this study to develop and apply metagenomic methods to validate their role in identifying EBV-associated malignant disease.
We enrolled 29 patients with positive EBV results in the cohort of FUO in the Department of Infectious Diseases of Huashan Hospital affiliated with Fudan University from 2018 to 2019. Upon enrollment, these patients were grouped for benign diseases, CAEBV, and malignant diseases according to their final diagnosis, and CNV analysis was retrospectively performed in 2022 using samples from 2018 to 2019.
Among the 29 patients. 16 of them were diagnosed with benign diseases, 3 patients were diagnosed with CAEBV and 10 patients were with malignant diseases. 29 blood samples from 29 patients were tested for mNGS. Among all 10 patients with malignant diagnosis, CNV analysis suggested neoplasms in 9 patients. Of all 19 patients with benign or CAEBV diagnosis, 2 patients showed abnormal CNV results. The sensitivity and specificity of CNV analysis for the identification for tumors were 90% and 89.5%, separately.
The application of mNGS could assist in the identification of microbial infection and malignancies in EBV-related diseases. Our results demonstrate that CNV detection through mNGS is faster compared to conventional oncology tests. Moreover, the convenient collection of peripheral blood samples adds to the advantages of this approach.
由于缺乏有效的诊断工具,EBV 阳性患者的良恶性疾病鉴别具有很大的挑战性。宏基因组下一代测序(mNGS)常用于识别不明原因发热(FUO)患者的病原体。最近的研究已经将下一代测序(NGS)的应用扩展到识别体液和脑脊液中的肿瘤。有鉴于此,我们开展了这项研究,以开发和应用宏基因组方法来验证其在识别 EBV 相关恶性疾病中的作用。
我们纳入了 2018 年至 2019 年复旦大学附属华山医院感染科 FUO 队列中 EBV 阳性的 29 例患者。入组时,根据最终诊断将这些患者分为良性疾病、CAEBV 和恶性疾病组,2022 年回顾性对 2018 年至 2019 年的样本进行 CNV 分析。
在 29 例患者中,16 例诊断为良性疾病,3 例诊断为 CAEBV,10 例诊断为恶性疾病。对 29 例患者的 29 份血液样本进行 mNGS 检测。在所有 10 例恶性诊断患者中,CNV 分析提示 9 例存在肿瘤。在所有 19 例良性或 CAEBV 诊断患者中,有 2 例显示异常 CNV 结果。CNV 分析对肿瘤的识别的敏感性和特异性分别为 90%和 89.5%。
mNGS 的应用可以辅助识别 EBV 相关疾病中的微生物感染和恶性肿瘤。我们的结果表明,与传统肿瘤学检测相比,通过 mNGS 进行 CNV 检测更快。此外,外周血样本的便捷采集增加了这种方法的优势。