Molecular drivers of bladder remodelling in lower urinary tract dysfunction identified through integrated data analysis of patients’ biopsies and animal models
                            Our Functional Urology Group investigates the
                            molecular mechanisms underlying the functional and
                            morphological changes in the bladder during LUTD.
                            Our comprehensive transcriptome sequencing, the
                            first of its kind, of human bladder biopsy samples
                            from patients with benign prostatic obstruction
                            revealed activation of immune response and
                            proliferative signalling pathways, and suggested an
                            increasing involvement of regulatory small
                            non-coding miRNAs in the control of bladder
                            function. We identified 3 mRNA- and 3
                            miRNA-biomarker signatures sufficient to
                            discriminate between bladder functional states,
                            validated them in a blinded study and showed the
                            normalization of their expression in patients whose
                            bladder function improved after deobstruction. Early
                            identification of structural changes in the bladder
                            during LUTD can optimize the timing of treatment. We
                            are in the possession of a unique collection of
                            human biopsy samples from patients with
                            well-characterized bladder functional phenotypes
                            before and after deobstruction surgery. Many
                            different underlying pathogenetic mechanisms of
                            similar symptomatic complexes necessitate different
                            therapeutic strategies. The functional and molecular
                            progression of LUTD in the mouse models of pBOO,
                            SCI, and MS can be monitored longitudinally, in
                            different phases of the disease characterized by
                            distinct functional phenotypes. Genes identified in
                            the animal trials can be compared with the human
                            biopsy data to further validate the most promising
                            markers and pathways. Our approach relies on
                            generation and analysis of big gene expression data
                            to reveal the triggers of LUTD. To achieve our goal
                            of unbiased classification of LUTD and
                            identification of molecular drivers of pathologic
                            bladder remodelling, we apply machine learning
                            algorithms to the transcriptome data, clinical
                            information from the patients, and relevant animal
                            models.