Yonar Dilek, Severcan Mete, Gurbanov Rafig, Sandal Abdulsamet, Yilmaz Ulku, Emri Salih, Severcan Feride
Middle East Technical University, Department of Biological Sciences, Ankara, Turkey; Yuksek Ihtisas University, Faculty of Medicine, Biophysics Department, Ankara, Turkey.
Middle East Technical University, Department of Electrical and Electronics Engineering, Ankara, Turkey.
Biochim Biophys Acta Mol Basis Dis. 2022 Oct 1;1868(10):166473. doi: 10.1016/j.bbadis.2022.166473. Epub 2022 Jun 23.
Malignant pleural mesothelioma (MPM), an aggressive cancer associated with exposure to fibrous minerals, can only be diagnosed in the advanced stage because its early symptoms are also connected with other respiratory diseases. Hence, understanding the molecular mechanism and the discrimination of MPM from other lung diseases at an early stage is important to apply effective treatment strategies and for the increase in survival rate. This study aims to develop a new approach for characterization and diagnosis of MPM among lung diseases from serum by Fourier transform infrared spectroscopy (FTIR) coupled with multivariate analysis. The detailed spectral characterization studies indicated the changes in lipid biosynthesis and nucleic acids levels in the malignant serum samples. Furthermore, the results showed that healthy, benign exudative effusion, lung cancer, and MPM groups were successfully separated from each other by applying principal component analysis (PCA), support vector machine (SVM), and especially linear discriminant analysis (LDA) to infrared spectra.
恶性胸膜间皮瘤(MPM)是一种与接触纤维状矿物质相关的侵袭性癌症,由于其早期症状也与其他呼吸道疾病有关,所以只能在晚期才能确诊。因此,了解MPM的分子机制以及在早期将其与其他肺部疾病区分开来,对于应用有效的治疗策略和提高生存率至关重要。本研究旨在开发一种新方法,通过傅里叶变换红外光谱(FTIR)结合多变量分析,从血清中对MPM进行表征和诊断,以区分肺部疾病。详细的光谱表征研究表明,恶性血清样本中脂质生物合成和核酸水平发生了变化。此外,结果显示,通过对红外光谱应用主成分分析(PCA)、支持向量机(SVM),尤其是线性判别分析(LDA),健康组、良性渗出性积液组、肺癌组和MPM组成功地相互区分开来。