Atli Emine Ikbal, Gurkan Hakan, Atli Engin, Kirkizlar Hakki Onur, Yalcintepe Sinem, Demir Selma, Demirci Ufuk, Eker Damla, Mail Cisem, Kalkan Rasime, Demir Ahmet Muzaffer
Faculty of Medicine, Department of Medical Genetics, Edirne, Trakya University, Edirne, Turkey.
Faculty of Medicine, Department of Hematology, Trakya University, Edirne, Turkey.
Mediterr J Hematol Infect Dis. 2021 Jan 1;13(1):e2021013. doi: 10.4084/MJHID.2021.013. eCollection 2021.
Advanced diagnostic methods give an advantage for the identification of abnormalities in myeloid malignancies. Various researchers have shown the potential importance of genetic tests before the disease's onset and in remission. Large testing panels prevent false-negative results in myeloid malignancies. However, the critical question is how the results of conventional cytogenetic and molecular cytogenetic techniques can be merged with NGS technologies. In this paper, we drew an algorithm for the evaluation of myeloid malignancies. To evaluate genetic abnormalities, we performed cytogenetics, molecular cytogenetics, and NGS testing in myeloid malignancies. In this study, we analyzed 100 patients admitted to the Medical Genetics Laboratory with different myeloid malignancies. We highlighted the possible diagnostic algorithm for cytogenetically normal cases. We applied NGS 141 gene panel for cytogenetically normal patients, and we detected two or more pathogenic variations in 61 out of 100 patients (61%). NGS's pathogenic variation detection rate varies in disease groups: they were present in 85% of A.M.L. and 23% of M.D.S. Here, we identified 24 novel variations out of total pathogenic variations in myeloid malignancies. A total of 18 novel variations were identified in A.M.L., and 6 novel variations were identified in M.D.S. Despite long turnaround times, conventional techniques are still a golden standard for myeloid malignancies but sometimes cryptic gene fusions or complex abnormalities cannot be easily identified by conventional techniques. In these conditions, advanced technologies like NGS are highly recommended.
先进的诊断方法有助于识别髓系恶性肿瘤中的异常情况。众多研究人员已表明基因检测在疾病发作前及缓解期的潜在重要性。大型检测 panel 可防止髓系恶性肿瘤出现假阴性结果。然而，关键问题在于传统细胞遗传学和分子细胞遗传学技术的结果如何能与 NGS 技术相结合。在本文中，我们绘制了一种用于评估髓系恶性肿瘤的算法。为评估基因异常情况，我们在髓系恶性肿瘤中进行了细胞遗传学、分子细胞遗传学及 NGS 检测。在本研究中，我们分析了 100 名因不同髓系恶性肿瘤入住医学遗传学实验室的患者。我们突出了细胞遗传学正常病例可能的诊断算法。我们对细胞遗传学正常的患者应用了 NGS 141 基因 panel，在 100 名患者中有 61 名（61%）检测到两个或更多致病性变异。NGS 的致病性变异检测率在不同疾病组有所不同：在急性髓系白血病（A.M.L.）中为 85%，在骨髓增生异常综合征（M.D.S.）中为 23%。在此，我们在髓系恶性肿瘤的总致病性变异中鉴定出 24 种新变异。在 A.M.L. 中总共鉴定出 18 种新变异，在 M.D.S. 中鉴定出 6 种新变异。尽管周转时间长，但传统技术仍是髓系恶性肿瘤的黄金标准，但有时传统技术难以轻易识别隐匿性基因融合或复杂异常情况。在这些情况下，强烈推荐使用 NGS 等先进技术。
