Artemyev Dmitry N, Kukushkin Vladimir I, Avraamova Sofia T, Aleksandrov Nikolay S, Kirillov Yuri A
Laser and Biotechnical Systems Department, Samara National Research University, 443086 Samara, Russia.
Laboratory of Non-Equilibrium Electronic Processes, Institute of Solid State Physics Russian Academy of Sciences, 142432 Chernogolovka, Russia.
Molecules. 2021 Mar 31;26(7):1961. doi: 10.3390/molecules26071961.
The possibilities of using optical spectroscopy methods in the differential diagnosis of prostate cancer were investigated. Analytical discrimination models of Raman spectra of prostate tissue were constructed by using the projections onto latent structures data analysis(PLS-DA) method for different wavelengths of exciting radiation-532 and 785 nm. These models allowed us to divide the Raman spectra of prostate cancer and the spectra of hyperplasia sites for validation datasets with the accuracy of 70-80%, depending on the specificity value. Meanwhile, for the calibration datasets, the accuracy values reached 100% for the excitation of a laser with a wavelength of 785 nm. Due to the registration of Raman "fingerprints", the main features of cellular metabolism occurring in the tissue of a malignant prostate tumor were confirmed, namely the absence of aerobic glycolysis, over-expression of markers (FASN, SREBP1, stearoyl-CoA desaturase, etc.), and a strong increase in the concentration of cholesterol and its esters, as well as fatty acids and glutamic acid. The presence of an ensemble of Raman peaks with increased intensity, inherent in fatty acid, beta-glucose, glutamic acid, and cholesterol, is a fundamental factor for the identification of prostate cancer.
研究了光学光谱方法在前列腺癌鉴别诊断中的应用可能性。利用潜在结构数据分析(PLS - DA)方法,针对532和785 nm不同激发辐射波长构建了前列腺组织拉曼光谱的分析鉴别模型。这些模型使我们能够根据特异性值,以70 - 80%的准确率区分验证数据集中前列腺癌的拉曼光谱和增生部位的光谱。同时,对于校准数据集,在785 nm波长激光激发下准确率达到100%。由于拉曼“指纹”的记录,证实了恶性前列腺肿瘤组织中细胞代谢的主要特征,即无氧糖酵解缺失、标志物(FASN、SREBP1、硬脂酰辅酶A去饱和酶等)过表达,以及胆固醇及其酯类、脂肪酸和谷氨酸浓度大幅增加。脂肪酸、β - 葡萄糖、谷氨酸和胆固醇所特有的强度增加的拉曼峰组合的存在是鉴定前列腺癌的基本因素。