Aim: To develop a timely and accurate method for predicting acute myeloid leukemia (AML) prognosis after chemotherapy treatment by surface-enhanced Raman spectroscopy (SERS). Methods: 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. Results: 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%. Conclusion: The proposed method could be a potential diagnostic tool for timely and precise prediction of AML prognosis.
Keywords: acute myeloid leukemia; cancer; hematology; multivariate analysis; oncology; prognosis; surface-enhanced Raman spectroscopy.
Lay abstract Acute myeloid leukemia (AML) is a disease in which too many immature white blood cells are found in the blood and bone marrow. Prognosis (the chance of recovery) for this disease is not favorable. However, if the disease can be quickly and precisely assessed, a personalized chemotherapy plan can be used. This could significantly improve the cure rate. In this study, a technique known as surface-enhanced Raman spectroscopy was used to analyze bone marrow samples from patients with and without AML. The samples were looked at to find biological molecules that could act as indicators for the disease and for disease prognosis. Using the collected data, models were established to predict whether a patient had AML and, if so, whether they had good or poor prognosis.