Stanislav Dmitrievich Gorbunkov

The stability of miRNAs in biological fluids and their association with pathological conditions position them as promising biomarkers for non-invasive cancer diagnostics, including those for non-small cell lung cancer (NSCLC). However, variability in miRNA expression and technical aspects of quantitative reverse transcription PCR (RT-qPCR) require effective normalization to accurately assess miRNA levels and identify biological differences. Despite the availability of multiple normalization methods, there is no consensus on the optimal approach for circulating miRNA data. This study provides a systematic methodological benchmarking of five normalization strategies—pairwise normalization, Tres normalization, Quadro normalization, normalization to the overall mean, and normalization to the exclusive mean—applied to RT-qPCR data of 17 miRNAs from plasma EVs of NSCLC patients and healthy donors. The aim was to evaluate their impact on the performance of machine learning models. For each normalization method, Random Forest models were built. Models were evaluated using accuracy, F1 score, AUC-ROC, AUPRC, precision, sensitivity, specificity, MCC, and overfitting gap. Pairwise normalization consistently outperformed all other methods across most metrics, achieving the highest AUC-ROC and AUPRC and the lowest overfitting gap, with statistically significant differences compared to other methods. Pairwise normalization offers a computationally simple, high-performing option for such benchmarking applications.

Background. The patients satisfaction assessment based on an anonymous questionnaire is an essential component of managing the quality of medical services of the medical organization. The aim: to study the indicators of satisfaction with the quality and availability of medical services provided in a medical institution, according to an anonymous survey of patients to improve the system of organizing medical care (МС) in the profile of pulmonology. Materials and methods. Original questionnaires were developed for an anonymous survey of patients who applied for outpatient and hospital MС. The survey was conducted among 289 patients, of which 84 people those who applied for an outpatient appointment with a specialist at the Clinical Diagnostic Center (CDC) and 205 people from clinical departments (СD) for the period from 01.06.2025 to 30.06.2025 years. Statistical processing of questionnaire data was carried out using the Statistica (version 10), Epinfo (version 7) software package. To assess the differences in qualitative parameters in the two compared groups, the Mentel–Henszel test χ2 was used. The differences between the two indicators with the level of significance p lt; 0,05 were considered significant. Results. High ratings of patient satisfaction with the medical care (MC) provided, as well as stay in the consultative and diagnostic center and departments of the clinic of the Federal State Budgetary Institution Research Institute of Pulmonology FMBA of Russia were established. The indicators good and excellent were indicated in the CDC by 93.9% of respondents and in CDs — 98.1%. The patients sent 31 proposals to the Administration of the Institute to improve the medical services provided. Conclusions. Anonymous questioning of patients is an effective method for obtaining information on the quality of MC and medical services in order to improve the activities of a medical institution.

Lung cancer (LC) remains a leading cause of global cancer mortality, driving the need for novel timely detection strategies, i.e., stages I–II detection when tumor curation is efficient. Circulating microRNA (miRNAs), with their unique stability in biofluids, offer a powerful approach for non-invasive detection. This review compiles validated miRNAs implicated in the early stages of non-small-cell lung cancer (NSCLC), elucidating their roles in key oncogenic pathways such as epithelial-mesenchymal transition (EMT), PI3K/AKT/mTOR, and JAK-STAT, which regulate proliferation, apoptosis, and metastasis. Furthermore, we critically evaluate developed miRNA panels with a specific focus on advanced quantification and normalization strategies, including exogenous spike-in controls and data-driven methods like pairwise normalization, to enhance diagnostic accuracy. Consequently, we identify and rank the most viable miRNA candidates according to key analytical and clinical metrics, providing a clear roadmap for translating these biomarkers into effective panels for the timely detection of NSCLC.

The stability of miRNAs in biological fluids and their association with pathological conditions make miRNAs promising biomarkers for non-invasive disease diagnostics, including non-small cell lung cancer (NSCLC). However, variability in miRNA expression and technical aspects of quantitative reverse transcription PCR (RT-qPCR) necessitate effective normalization methods to ensure accurate evaluation of miRNA levels and identification of biological differences. In this study, we performed a comparative analysis of several miRNA normalization approaches applied to extracellular vesicles isolated from plasma of NSCLC patients, including pairwise normalization, “Tres” and “Quadro” normalization strategies, normalization to the mean, and normalization considering miRNA functional groups. Method effectiveness was evaluated using quality metrics of diagnostic models. The most robust results were observed with normalization methods utilizing miRNA pairs, triplets, and quadruplets, which provided high accuracy, model stability, and minimal overfitting. In contrast, normalization to the general or exclusive mean and functional group-based normalization showed lower efficiency in terms of classification performance and feature selection stability. These findings highlight the critical importance of normalization strategy choice to improve the accuracy and interpretability of RT-qPCR-based diagnostic models, particularly in the development of biomarker panels for NSCLC diagnostics. Pairwise normalization, combining computational simplicity and high efficiency, appears optimal for practical applications.