The aim of the work is to study the metabolic characteristics of saliva in lung cancer for use in early diagnosis and determining the prognosis of the disease. The patient group included 425 lung cancer patients, 168 patients with non-cancerous lung diseases, and 550 healthy volunteers. Saliva samples were collected from all participants in the experiment before treatment and 34 biochemical saliva parameters were determined. Participants were monitored for six years to assess survival rates. The statistical analysis was performed by means of Statistica 10.0 (StatSoft) program and R package (version 3.2.3). To construct the classifier, the Random Forest method was used; the classification quality was assessed using the cross-validation method. Prognostic factors were analyzed by multivariate analysis using Cox’s proportional hazard model in a backward step-wise fashion to adjust for potential confounding factors. A complex of metabolic changes occurring in saliva in lung cancer is described. Seven biochemical parameters were identified (catalase, triene conjugates, Schiff bases, pH, sialic acids, alkaline phosphatase, chlorides), which were used to construct the classifier. The sensitivity and specificity of the method were 69.5% and 87.5%, which is practically not inferior to the diagnostic characteristics of markers routinely used in the diagnosis of lung cancer. Significant independent factors in the poor prognosis of lung cancer are imidazole compounds (ICs) above 0.478 mmol/L and salivary lactate dehydrogenase activity below 545 U/L. Saliva has been shown to have great potential for the development of diagnostic and prognostic tests for lung cancer.

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Background: Recently, the attention of researchers to the study of the properties of human saliva, as a material with unique properties and diagnostic capabilities, has increased. Research objective: to study the connection of the biochemical composition of saliva and blood plasma in the norm, depending on gender and age. Methods: 107 volunteers took part in the study, including 46 female (37.2 ± 3.9 years old) and 61 male (36.1 ± 2.8 years old). In all samples of saliva and blood plasma, 16 biochemical parameters were determined, including mineral and protein composition, enzyme activity. Non-parametric statistical methods were used to process the data. Results: It has been shown that it is difficult to establish an unambiguous relation between biochemical parameters of saliva and blood plasma. The calculation of the Spearman correlation coefficients showed that only 7 of the 16 parameters demonstrate the presence of a weak correlation between the content in saliva and plasma. Conclusion: In general, the determination of the composition of saliva may have an independent diagnostic value; in this case, drawing a parallel with the composition of serum and blood plasma is not advisable. Nevertheless, the use of saliva in clinical laboratory diagnostics is associated with the need to establish criteria for the norm and pathology for each biochemical parameter.

Background: The study of processes in the drying drops of biological fluids (dried drop patterns) and the method of dynamic surface tensiometry can be attributed to integral methods of assessing the state of the organism. Research objective: to establish the relationship between the type of crystallization patterns and the surface tension of human saliva in normal conditions. Methods: 100 volunteers (40 males, 60 females) that were aged 30–59 participated in the study. In all saliva samples, the parameters of dynamic tensiometry, types of crystallization patterns and 11 biochemical parameters were determined. Results: No statistically significant differences in the saliva crystallization patterns were observed, depending on the age and gender characteristics of the volunteers. A negative correlation of the area of the crystallization zone and the surface tension of saliva is shown. When considering the crystallization patterns, their considerable variability was noted; on this basis, the entire studied sample was divided into four clusters by surface tension. Conclusion: In general, the crystallization patterns that are inside the selected groups remain quite heterogeneous. This increases the likelihood of making an incorrect diagnosis when using visual methods to evaluate the crystallization patterns, which significantly limits the use of such diagnostic methods in clinical practice.

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The aim of the study was to compare the metabolic characteristics of the salivary composition in lung cancer, chronic obstructive pulmonary disease (COPD) and their combination, depending on the smoking history. The study group included 392 patients with lung cancer of various histological types. The division into subgroups was carried out in accordance with the severity of COPD and smoking experience. Salivary biochemical composition was determined according to 34 indicators. For data processing, the principal component method was used. Different groups of biochemical saliva markers are informative when separately accounting for the smoking factor and the presence of COPD in lung cancer. For smoking, antioxidant enzymes and electrolyte components of saliva are informative; for COPD metabolic enzymes, lipid peroxidation products, sialic acids and electrolyte components are informative. While taking into account the smoking factor and the presence of COPD, biochemical markers corresponding to the presence/absence and severity of COPD are the priority. Changes occurring in the background of smoking are of a secondary nature, manifesting as much as possible with a smoking history of more than 50 pack-years. Thus, the metabolic changes that occur in lung cancer in combination with COPD, depending on the smoking factor, can be estimated using saliva.

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