Abstract
Myelodysplastic syndrome (MDS) is difficult to diagnose and classify because it has the potential to evolve into acute myeloid leukemia (AML). Raman spectroscopy and orthogonal partial least squares discrimination analysis (OPLS-DA) are used to systematically analyze peripheral blood serum samples from 33 patients with MDS, 25 patients with AML, and 29 control volunteers to gain insight into the heterogeneity of serum metabolism in patients with MDS and AML. AML patients show unique serum spectral data compared to MDS patients with considerably greater peak intensities of collagen (859 and 1345 cm(-1)) and carbohydrate (920 and 1123 cm(-1)) compared to MDS patients. Screening and bioinformatics analysis of MDS- and AML-related genes based on the Gene Expression Omnibus (GEO) database shows that 1459 genes are differentially expressed, and the main signaling pathways are related to Th17 cell differentiation, pertussis, and cytokine receptor interaction. Statistical analysis of serological indexes related to glucose and lipid metabolism shows that patients with AML have increased serum triglyceride (TG) levels and decreased total protein levels. This study provides a spectral basis for the relationship between the massive serological data of patients and the typing of MDS and AML and provides important information for the rapid and early identification of MDS and AML.