Label‐Free SERS for the Diagnosis of Myeloid Leukaemia From Blood Serum Samples Using Gold Nanoparticles as Substrates

Myeloid leukaemia (ML) is a myeloproliferative disorder, characterised by the over‐proliferation of myeloid cells within the bone marrow, which mostly occurs in adults over age 50 years and results in higher mortality. Early detection of this disease is very important to lower the mortality rate of ML patients. In this study, surface‐enhanced Raman spectroscopy (SERS) is used to characterise and diagnose disease in blood serum samples of 40 clinically confirmed ML patients and 20 healthy people. The gold nanoparticles (AuNPs) are used as a SERS substrate for the identification of SERS spectral features, differentiating between healthy and ML patients. The characteristic SERS features identified in the samples of acute myeloid leukaemia (AML) include 534, 546 and 575 cm −1 and in the chronic levels of myeloid leukaemia (CML) consist of 625, 800, 929, 990, 1305, 1329, 1538 and 1588 cm −1 . For the differentiation and classification of the SERS spectral groups of the healthy, acute and CML samples, multivariate chemometric tools including principal component analysis (PCA) and partial least square discriminant analysis (PLS‐DA) are employed. The PLS‐DA model showed good classification performance, with an overall mean accuracy of 86.7%, mean sensitivity of 86.7%, mean specificity of 93.3% and AUC values of 0.994, 1.000 and 0.854 for healthy, AML and CML, respectively.