Serum SERS Analysis Reveals Amino Acid- and Protein-Associated Vibrational Features for Subtype Identification in...

Acute lymphoblastic leukemia (ALL) is the most common hematologic malignancy in children. Current clinical diagnosis primarily relies on invasive detection methods, while molecular subtyping remains a complex and time-consuming process. This study innovatively employed silver nanoparticle-based surface-enhanced Raman spectroscopy (SERS) technology to systematically analyze 116 serum samples, including those with breakpoint cluster region-Abelson (BCR-ABL) fusion genotype, mixed-lineage leukemia (MLL, also known as lysine methyltransferase 2A, KMT2A) gene rearrangement subtype, T-lymphoblastic ALL, and healthy controls. By integration of supervised and unsupervised learning algorithms, the performance of whole-spectrum and band intensity analysis in identifying different ALL subtypes was confirmed. Results demonstrated significant differences in the intensity and intensity ratios of specific spectral bands among groups, which were associated with the discrimination between ALL subtypes and healthy controls. The multiindex receiver operating characteristic curve analysis based on band intensity ratios exhibited outstanding performance in distinguishing ALL patients from healthy controls. Our results demonstrated the significant potential of SERS technology as a rapid and miniaturized detection method in clinical laboratories, serving as a novel and powerful tool for analyzing human serum.