Journal Article

Raman Spectroscopy of Blood Serum for Essential Thrombocythemia Diagnosis: Correlation with Genetic Mutations and Optimization of Laser Wavelengths

Cebulski, Jozef, Aday, Aynur, Bayrak, Ayşe Gül, Toraman, Suat, Depciuch, Joanna, Guleken, Zozan, Nalçacı, Meliha, Hindilerden, İpek Yönal

2024

Overview

Essential thrombocythemia (ET) is a type of myeloproliferative neoplasm that increases the risk of thrombosis. To diagnose this disease, the analysis of mutations in the Janus Kinase 2 (JAK2), thrombopoietin receptor (MPL), or calreticulin (CALR) gene is recommended. Disease poses diagnostic challenges due to overlapping mutations with other neoplasms and the presence of triple-negative cases. This study explores the potential of Raman spectroscopy combined with machine learning for ET diagnosis. We assessed two laser wavelengths (785, 1064 nm) to differentiate between ET patients and healthy controls. The PCR results indicate that approximately 50% of patients in our group have a mutation in the JAK2 gene, while only 5% of patients harbor a mutation in the ASXL1 gene. Additionally, only one patient had a mutation in the IDH1 and one had a mutation in IDH2 gene. Consequently, patients having no mutations were also observed in our group, making diagnosis challenging. Raman spectra at 1064 nm showed lower amide, polysaccharide, and lipid vibrations in ET patients, while 785 nm spectra indicated significant decreases in amide II and C-H lipid vibrations. Principal Component Analysis (PCA) confirmed that both wavelengths could distinguish ET from healthy subjects. Support Vector Machine (SVM) analysis revealed that the 800–1800 cm −1 range provided the highest diagnostic accuracy, with 89% for 785 nm and 72% for 1064 nm. These findings suggest that FT-Raman spectroscopy, paired with multivariate and machine learning analyses, offers a promising method for diagnosing ET with high accuracy by detecting specific molecular changes in serum. Principal Component Analysis (PCA) confirmed that both wavelengths could distinguish ET from healthy subjects. Support Vector Machine (SVM) analysis revealed that the 800–1800 cm −1 range provided the highest diagnostic accuracy, with 89% for 785 nm and 72% for 1064 nm. These findings suggest that FT-Raman spectroscopy, paired with multivariate and machine learning analyses, offers a promising method for diagnosing ET with high accuracy by detecting specific molecular changes in serum. Highlights Mutations in the JAK2 gene are present in 50% of patients, while mutations in the ASXL1, IDH1 , and IDH 2 genes are present in 5, 1.2 and 1.2% of patients. A strong correlation to the mutations in JAK2 , ASXL1 and IDH1 genes. The accuracy of the 785 nm laser was 89%, while that of the 1064 nm laser was 66%.

• Publisher: Springer US,Springer Nature B.V
• Subject: Accuracy / Adult / Aged / Biochemistry / Biological and Medical Physics / Biomedical and Life Sciences / Biophysics / Biotechnology / Calreticulin / Calreticulin - blood / Calreticulin - genetics / Case-Control Studies / Cell Biology / Diagnosis / Diagnostic systems / Female / Genes / Humans / IDH2 gene / Isocitrate Dehydrogenase - genetics / Janus kinase / Janus kinase 2 / Janus Kinase 2 - genetics / Kinases / Lasers / Learning algorithms / Life Sciences / Lipids / Machine Learning / Male / Middle Aged / Multivariate analysis / Mutation / Neoplasms / Original Paper / Pharmacology/Toxicology / Polysaccharides / Principal Component Analysis / Principal components analysis / Raman spectra / Raman spectroscopy / Receptors, Thrombopoietin - genetics / Spectroscopic analysis / Spectroscopy / Spectrum analysis / Spectrum Analysis, Raman - methods / Support Vector Machine / Support vector machines / Thrombocythemia, Essential - blood / Thrombocythemia, Essential - diagnosis / Thrombocythemia, Essential - genetics / Thromboembolism / Thrombopoietin / Thrombosis / Vibrations / Wavelengths