Zeidan Amer M, Prebet Thomas, Saad Aldin Ehab, Gore Steven David
Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21287, USA.
Expert Rev Hematol. 2014 Apr;7(2):191-4. doi: 10.1586/17474086.2014.891437. Epub 2014 Feb 24.
Evaluation of: Pellagatti A, Benner A, Mills KI et al. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes. J. Clin. Oncol. 31(28), 3557-3564 (2013). Patients with myelodysplastic syndromes (MDS) exhibit wide heterogeneity in clinical outcomes making accurate risk-stratification an integral part of the risk-adaptive management paradigm. Current prognostic schemes for MDS rely on clinicopathological parameters. Despite the increasing knowledge of the genetic landscape of MDS and the prognostic impact of many newly discovered molecular aberrations, none to date has been incorporated formally into the major risk models. Efforts are ongoing to use data generated from genome-wide high-throughput techniques to improve the 'individualized' outcome prediction for patients. We here discuss an important paper in which gene expression profiling (GEP) technology was applied to marrow CD34(+) cells from 125 MDS patients to generate and validate a standardized GEP-based prognostic signature.
佩拉加蒂 A、本纳 A、米尔斯 KI 等。骨髓增生异常综合征患者造血干细胞中基于基因表达的预后标志物的鉴定。《临床肿瘤学杂志》31(28)，3557 - 3564(2013 年)。骨髓增生异常综合征(MDS)患者的临床结局表现出广泛的异质性，使得准确的风险分层成为风险适应性管理模式的一个组成部分。目前 MDS 的预后方案依赖于临床病理参数。尽管对 MDS 的基因图谱以及许多新发现的分子异常的预后影响的了解不断增加，但迄今为止，尚无任何一项被正式纳入主要风险模型。目前正在努力利用全基因组高通量技术产生的数据来改善患者的“个体化”结局预测。我们在此讨论一篇重要论文，其中基因表达谱(GEP)技术应用于 125 例 MDS 患者的骨髓 CD34(+)细胞，以生成并验证基于 GEP 的标准化预后特征。
