Bladder Cancer Epidemiology in Latvia and Machine Learning-Based Evaluation of Urinary Exosomal microRNAs as Diagnostic Biomarkers. Doctoral Thesis

Bladder cancer (BC) is the most prevalent malignancy of the urinary system and ranks as the tenth most common cancer worldwide. Recent data indicate a significant increase in incidence, with hundreds of thousands of new cases diagnosed annually. Based on GLOBOCAN data, bladder cancer ranked 7th among cancers in Latvia in 2022, with 521 new cases. BC was the seventh most prevalent cancer in the world. The global burden of bladder cancer is considerable, with millions of individuals living with the disease. The overall global five-year prevalence was estimated at 1 700 000 in 2020. There is a substantial number of deaths attributed to it each year, making it the 13th leading cause of cancer mortality. Due to the main risk factors – smoking and chemical exposures – associated with BC, it is considered a largely preventable and avoidable cancer. BC is a heterogeneous disease with highly variable clinical, anatomic, and molecular pathology features, along with a high mutation burden. In recent years, microRNAs (miRNAs) have emerged as crucial regulators of cellular activities, and their dysregulation has been associated with the onset and progression of cancer. Although there are many studies on BC around the world, there is still no comprehensive analysis of the epidemiological trends and long-term survival rates of bladder cancer in Latvia, nor has there been an examination of the potential of exosomal microRNAs (miRNAs) as biomarkers for the diagnosis of BC. The aim of my PhD thesis was to carry out a population-based study on the epidemiological trends of bladder cancer in Latvia from 1990 to 2017, and to evaluate the diagnostic potential of urinary exosomal miRNAs in combination with clinical and laboratory data using machine learning approaches. The study also aimed at improving the understanding of cell-to-cell communication between bladder cells in patients with low-grade (LG) and high-grade (HG) BC, and the possible impact of the urinary exosomal miRNAs on the oncotransformation of normal cells. The results of the study showed that bladder cancer incidence, prevalence, and mortality increased in Latvia between 1990 and 2017. Findings revealed that the age-standardised incidence rate of bladder cancer increased from 6.8 per 100 000 in 1990 to 10.8 per 100 000 in 2017, with a statistically significant rise (APC 2.6 %) from 1990 to 2014, followed by a minor and statistically insignificant decline through 2017 (APC −3.6 %). The prevalence rates increased from 25.2 in 1990 to 69.7 in 2017, with an AAPC of 3.8 % ( 95 % CI 3.1 to 4.6) during the whole period. A statistically significant reduction was observed only in the ≥ 80-year age group, with an APC of −7.6% from 2013 to 2017. Mortality rates also increased from 3.9 to 4.4 per 100,000 during the same period, although a notable decrease was observed in the 40-59 age group, with an annual percentage change of −1.1%. Additionally, relative survival rates improved from 55.0% during 1990-2000 to 59.0% in the years 2013–2017, suggesting advancements in treatment or early detection strategies. These epidemiological findings – particularly the rising incidence and the persistent burden in older age groups – underscored the need for more sensitive, non-invasive diagnostic tools, motivating the subsequent investigation of urinary exosomal miRNAs as candidate biomarkers. Striking differences in the miRNA cargo of exosomes from the BC group as compared to the control group were identified. Among the up-regulated exosomal miRNAs, 7 miRNAs in the LG group and 3 miRNAs in the HG group were identified as directly targeting TP53. Twenty-two and 17 PTEN-targeting miRNAs were observed among the up-regulated miRNAs of the LG and HG groups, respectively. The target genes of these exosomal miRNAs and their interaction network predicted that TP53 is the strongest hub gene in both BC exosomal miRNA networks. Further, the possible role of exosomal miRNAs in synchronous BC development was discussed. Building on these differentially expressed candidates, 11 miRNAs were selected based on statistical significance and fold regulation to test whether combining these miRNAs with routine clinical and laboratory data improves diagnostic accuracy compared with using either data type alone. Machine learning was performed using the 11 specially selected miRNAs in 152 samples (89 bladder cancer patients and 63 controls), selected from an initial 210-participant cohort by applying the criterion of complete clinical data availability. Statistical analysis identified notable miRNAs, such as mir-455-3p, mir-30b-3p, and mir-429, as potential biomarkers. This study highlighted the potential of combining miRNA expression levels with laboratory tests and clinical data for improved BC diagnostics.