College of Medicine & Biological Information Engineering, Northeastern University, No. 500 Wisdom Street, Shenyang, 110169, China.
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, No. 500 Wisdom Street, Shenyang, 110169, China.
Nanomedicine (Lond). 2021 Sep;16(21):1873-1885. doi: 10.2217/nnm-2021-0199. Epub 2021 Jul 16.
To develop a timely and accurate method for predicting acute myeloid leukemia (AML) prognosis after chemotherapy treatment by surface-enhanced Raman spectroscopy (SERS). Biomolecular differences between AML patients with good and poor prognosis and individuals without AML were investigated based on SERS measurements of bone marrow supernatant fluid samples. Multivariate analysis was implemented on the SERS measurements to establish an AML prognostic model. Significant differences in amino acid, saccharide and lipid levels were observed between AML patients with good and poor prognoses. The AML prognostic model achieved a prediction accuracy of 84.78%. The proposed method could be a potential diagnostic tool for timely and precise prediction of AML prognosis.
通过表面增强拉曼光谱（SERS）开发一种用于预测化疗后急性髓系白血病（AML）预后的及时、准确的方法。 基于骨髓上清液样本的 SERS 测量，研究了预后良好和预后不良的 AML 患者与无 AML 个体之间的生物分子差异。对 SERS 测量值进行了多变量分析，以建立 AML 预后模型。 预后良好和预后不良的 AML 患者之间在氨基酸、糖和脂质水平上存在显著差异。AML 预后模型的预测准确率达到 84.78%。 该方法可能成为一种用于及时、准确预测 AML 预后的潜在诊断工具。
