Machine Learning-Based Classification of Transcriptome Signatures of Non-Ulcerative Bladder Pain Syndrome.

Lower urinary tract dysfunction (LUTD) presents a global health challenge with symptoms impacting a substantial percentage of the population. The absence of reliable biomarkers complicates the accurate classification of LUTD subtypes with shared symptoms such as non-ulcerative Bladder Pain Syndrome (BPS) and overactive bladder caused by bladder outlet obstruction with Detrusor Overactivity (DO). This study introduces a machine learning (ML)-based approach for the identification of mRNA signatures specific to non-ulcerative BPS. Using next-generation sequencing (NGS) transcriptome data from bladder biopsies of patients with BPS, benign prostatic obstruction with DO, and controls, our statistical approach successfully identified 13 candidate genes capable of discerning BPS from control and DO patients. This set was validated using Quantitative Polymerase Chain Reaction (QPCR) in a larger patient cohort. To confirm our findings, we applied both supervised and unsupervised ML approaches to the QPCR dataset. A three-mRNA signature TPPP3, FAT1, and NCALD, emerged as a robust classifier for non-ulcerative BPS. The ML-based framework used to define BPS classifiers establishes a solid foundation for comprehending the gene expression changes in the bladder during BPS and serves as a valuable resource and methodology for advancing signature identification in other fields. The proposed ML pipeline demonstrates its efficacy in handling challenges associated with limited sample sizes, offering a promising avenue for applications in similar domains.

De-obstruction of bladder outlet in humans reverses organ remodelling by normalizing the expression of key transcription factors.

BACKGROUND: Benign prostatic hyperplasia in elderly males often causes bladder outlet obstruction termed benign prostatic obstruction (BPO). BPO induces lower urinary tract symptoms and quantifiable urodynamic alterations in bladder function. When conservative medical treatments are exhausted, surgical interventions like transurethral resection of the prostate (TURP) are employed for bladder outlet de-obstruction. Elucidating the molecular changes in the human bladder resulting from BPO and their reversal post-de-obstruction is pivotal for defining the "point of no return", when the organ deterioration becomes irreversible. In this study we carried out a comprehensive molecular and urodynamic characterization of the bladders in men with BPO before TURP and 3 months after the relief of obstruction. METHODS: We report integrated transcriptome and proteome analysis of bladder samples from male patients with BPO before and 3 months after de-obstruction surgery (TURP). mRNA and protein profiles were correlated with urodynamic findings, specifically voiding detrusor pressure (PdetQmax) before TURP. We delineated the molecular classifiers of each group, pointing at the different pre-TURP bladder status. RESULTS: Age-matched patients with BPO without DO were divided into two groups based on the PdetQmax values recorded by UDI before de-obstruction: high and medium pressure (HP and MP) groups. Three months after de-obstruction surgery, the voiding parameters PdetQmax, Qmax and RV were significantly improved in both groups, without notable inter-group differences in the values after TURP. Patients with high PdetQmax showed less advanced remodeling and inflammatory changes than those with lower values. We detected significant dysregulation of gene expression, which was at least partially reversed by de-obstruction in both patients' groups. Transcription factor SOX21 and its target thrombospondin 4 (THBS4) demonstrated normalization post-TURP. CONCLUSIONS: Our findings reveal substantial yet incomplete reversal of cell signalling pathways three months after TURP, consistent with improved urodynamic parameters. We propose a set of biomarker genes, indicative of BPO, and possibly contributing to the bladder changes. This study unveils the stages of progressive obstruction-induced bladder decompensation and offers insights into selecting an optimal intervention point to mitigate loss of contractility.

Machine Learning-based Classification of transcriptome Signatures of non-ulcerative Bladder Pain Syndrome.

Lower urinary tract dysfunction (LUTD) presents a global health challenge with symptoms impacting a substantial percentage of the population. The absence of reliable biomarkers complicates the accurate classification of LUTD subtypes with shared symptoms such as non-ulcerative Bladder Pain Syndrome (BPS) and overactive bladder caused by bladder outlet obstruction with Detrusor Overactivity (DO). This study introduces a machine learning (ML)-based approach for the identification of mRNA signatures specific to non-ulcerative BPS. Using next-generation sequencing (NGS) transcriptome data from bladder biopsies of patients with BPS, benign prostatic obstruction with DO and controls, our statistical approach successfully identified 13 candidate genes capable of discerning BPS from control and DO patients. This set was subsequently validated using Quantitative Polymerase Chain Reaction (QPCR) in a larger patient cohort. To confirm our findings, we applied both supervised and unsupervised ML approaches to the QPCR dataset. Notably, a three-mRNA signature TPPP3, FAT1, and NCALD, emerged as a robust classifier, effectively distinguishing patients with non-ulcerative BPS from controls and patients with DO. This signature was universally selected by both supervised and unsupervised approaches. The ML-based framework used to define BPS classifiers not only establishes a solid foundation for comprehending the specific gene expression changes in the bladder of the patients with BPS but also serves as a valuable resource and methodology for advancing signature identification in other fields. The proposed ML pipeline demonstrates its efficacy in handling challenges associated with limited sample sizes, offering a promising avenue for applications in similar domains.

Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis.

BACKGROUND: Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance. RESULTS: To address these challenges, we have developed a novel tool called Machine Learning Made Easy (MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating 4 essential functionalities-namely, Data Exploration, AutoML, CustomML, and Visualization-MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on 6 distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme's feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations. CONCLUSION: MLme serves as a valuable resource for leveraging ML to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available at https://github.com/FunctionalUrology/MLme.

SpheroScan: A User-Friendly Deep Learning Tool for Spheroid Image Analysis.

Background: In recent years, three-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional two-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays. Results: To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results. Conclusion: SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan.

Machine Learning Made Easy (MLme): A Comprehensive Toolkit for Machine Learning-Driven Data Analysis.

Background: Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance. Results: To address these challenges, we have developed a novel tool called Machine Learning Made Easy (MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating four essential functionalities, namely Data Exploration, AutoML, CustomML, and Visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on six distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme's feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations. Conclusion: MLme serves as a valuable resource for leveraging machine learning (ML) to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available at https://github.com/FunctionalUrology/MLme.

Molecular Characterization of Non-Neurogenic and Neurogenic Lower Urinary Tract Dysfunction (LUTD) in SCI-Induced and Partial Bladder Outlet Obstruction Mouse Models.

We examined bladder function following spinal cord injury (SCI) by repeated urodynamic investigation (UDI), including external urethral sphincter (EUS) electromyography (EMG) in awake restrained mice and correlated micturition parameters to gene expression and morphological changes in the bladder. A partial bladder outlet obstruction (pBOO) model was used for comparison to elucidate both the common and specific features of obstructive and neurogenic lower urinary tract dysfunction (LUTD). Thirty female C57Bl/6J mice in each group received an implanted bladder catheter with additional electrodes placed next to the EUS in the SCI group. UDI assessments were performed weekly for 7 weeks (pBOO group) or 8 weeks (SCI group), after which bladders were harvested for histological and transcriptome analysis. SCI mice developed detrusor sphincter dyssynergia (DSD) one week after injury with high-pressure oscillations and a significantly increased maximal bladder pressure Pmax and were unable to void spontaneously during the whole observation period. They showed an increased bladder-to-bodyweight ratio, bladder fibrosis, and transcriptome changes indicative of extracellular matrix remodeling and alterations of neuronal signaling and muscle contraction. In contrast, pBOO led to a significantly increased Pmax after one week, which normalized at later time points. Increased bladder-to-bodyweight ratio and pronounced gene expression changes involving immune and inflammatory pathways were observed 7 weeks after pBOO. Comparative transcriptome analysis of SCI and pBOO bladders revealed the activation of Wnt and TGF-beta signaling in both the neurogenic and obstructive LUTD and highlighted FGF2 as a major upregulated transcription factor during organ remodeling. We conclude that SCI-induced DSD in mice leads to profound changes in neuronal signaling and muscle contractility, leading to bladder fibrosis. In a similar time frame, significant bladder remodeling following pBOO allowed for functional compensation, preserving normal micturition parameters.

MLcps: machine learning cumulative performance score for classification problems.

BACKGROUND: Assessing the performance of machine learning (ML) models requires careful consideration of the evaluation metrics used. It is often necessary to utilize multiple metrics to gain a comprehensive understanding of a trained model's performance, as each metric focuses on a specific aspect. However, comparing the scores of these individual metrics for each model to determine the best-performing model can be time-consuming and susceptible to subjective user preferences, potentially introducing bias. RESULTS: We propose the Machine Learning Cumulative Performance Score (MLcps), a novel evaluation metric for classification problems. MLcps integrates several precomputed evaluation metrics into a unified score, enabling a comprehensive assessment of the trained model's strengths and weaknesses. We tested MLcps on 4 publicly available datasets, and the results demonstrate that MLcps provides a holistic evaluation of the model's robustness, ensuring a thorough understanding of its overall performance. CONCLUSIONS: By utilizing MLcps, researchers and practitioners no longer need to individually examine and compare multiple metrics to identify the best-performing models. Instead, they can rely on a single MLcps value to assess the overall performance of their ML models. This streamlined evaluation process saves valuable time and effort, enhancing the efficiency of model evaluation. MLcps is available as a Python package at https://pypi.org/project/MLcps/.

SpheroScan: a user-friendly deep learning tool for spheroid image analysis.

BACKGROUND: In recent years, 3-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional 2-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays. RESULTS: To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results. CONCLUSION: SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan.

Integrated mRNA-miRNA transcriptome analysis of bladder biopsies from patients with bladder pain syndrome identifies signaling alterations contributing to the disease pathogenesis.

BACKGROUND: Interstitial cystitis, or bladder pain syndrome (IC/BPS), is a chronic bladder disorder characterized by lower abdominal pain associated with the urinary bladder and accompanied by urinary frequency and urgency in the absence of identifiable causes. IC/PBS can be separated into the classic Hunner's ulcerative type and the more prevalent non-ulcerative disease. Our aim was to unravel the biological processes and dysregulated cell signaling pathways leading to the bladder remodeling in non-ulcerative bladder pain syndrome (BPS) by studying the gene expression changes in the patients' biopsies. METHODS: We performed paired microRNA (miRNA) and mRNA expression profiling in the bladder biopsies of BPS patients with non-Hunner interstitial cystitis phenotype, using comprehensive Next-generation sequencing (NGS) and studied the activated pathways and altered biological processes based on the global gene expression changes. Paired mRNA-miRNA transcriptome analysis delineated the regulatory role of the dysregulated miRNAs by identifying their targets in the disease-induced pathways. RESULTS: EIF2 Signaling and Regulation of eIF4 and p70S6K Signaling, activated in response to cellular stress, were among the most significantly regulated processes during BPS. Leukotriene Biosynthesis nociceptive pathway, important in inflammatory diseases and neuropathic pain, was also significantly activated. The biological processes identified using Gene Ontology over-representation analysis were clustered into six main functional groups: cell cycle regulation, chemotaxis of immune cells, muscle development, muscle contraction, remodeling of extracellular matrix and peripheral nervous system organization and development. Compared to the Hunner's ulcerative type IC, activation of the immune pathways was modest in non-ulcerative BPS, limited to neutrophil chemotaxis and IFN-γ-mediated signaling. We identified 62 miRNAs, regulated and abundant in BPS and show that they target the mRNAs implicated in eIF2 signalling pathway. CONCLUSIONS: The bladders of non-ulcerative BPS patients recruited in this study had alterations consistent with a strong cell proliferative response and an up-regulation of smooth muscle contractility, while the contribution of inflammatory processes was modest. Pathway analysis of the integrated mRNA-miRNA NGS dataset pinpointed important regulatory miRNAs whose dysregulation might contribute to the pathogenesis. Observed molecular changes in the peripheral nervous system organization and development indicate the potential role of local bladder innervation in the pain perceived in this type of BPS.

Urinary miRNA profiles discriminate between obstruction-induced bladder dysfunction and healthy controls.

Urgency, frequency and incomplete emptying are the troublesome symptoms often shared between benign prostatic obstruction-induced (BLUTD) and neurogenic (NLUTD) lower urinary tract dysfunction. Previously, using bladder biopsies, we suggested a panel of miRNA biomarkers for different functional phenotypes of the bladder. Urine is a good source of circulating miRNAs, but sex- and age-matched controls are important for urinary metabolite comparison. In two groups of healthy subjects (average age 32 and 57 years old, respectively) the total protein and RNA content was very similar between age groups, but the number of secreted extracellular vesicles (uEVs) and expression of several miRNAs were higher in the young healthy male volunteers. Timing of urine collection was not important for these parameters. We also evaluated the suitability of urinary miRNAs for non-invasive diagnosis of bladder outlet obstruction (BOO). A three urinary miRNA signature (miR-10a-5p, miR-301b-3p and miR-363-3p) could discriminate between controls and patients with LUTD (BLUTD and NLUTD). This panel of representative miRNAs can be further explored to develop a non-invasive diagnostic test for BOO. The age-related discrepancy in the urinary miRNA content observed in this study points to the importance of selecting appropriate, age-matched controls.

Effects of opioids and benzodiazepines on bladder function of awake restrained mice.

OBJECTIVE: We aimed to study the effects of anaesthetics on bladder function using repeated urodynamic investigation (UDI) including external urethral sphincter (EUS) electromyography (EMG) in awake restrained mice. MATERIALS AND METHODS: Female C57Bl/6J mice underwent either bladder catheter (n=6) or bladder catheter plus electrodes (n=10) implantation next to the EUS. A control group (n=3) was included for histological analysis. Following awake UDI, the effects of midazolam (5 mg/kg) and opioids (fentanyl (50 µg/kg) and hydromorphine (250 µg/kg)) on bladder function were studied. Mice were allowed to recover from drug application for at least one day before being subjected to the next drug and UDI. Bladder weight was assessed and fibrotic changes were analysed by Masson's trichrome staining. RESULTS: EUS-EMG activity during voiding was reduced compared to before and after voiding in baseline measurements. Threshold and maximal detrusor pressure were significantly increased in both midazolam and the opioids. The opioids lead to either a significantly increased bladder filling volume and micturition cycle duration (hydromorphine) or a complete loss of the voiding phase leading to overflow incontinence (fentanyl). Bladder-to bodyweight ratio was significantly increased in both groups with an implanted catheter compared to controls. No differences were observed between the groups with- or without implanted electrodes regarding bladder-to bodyweight ratio, bladder fibrosis and urodynamic parameters. CONCLUSIONS: Repeated UDIs combined with EUS-EMG are feasible in the awake mouse model. The presence of electrodes next to the EUS does not obstruct the bladder outlet. Opioids and benzodiazepines severely interfere with physiological bladder function: fentanyl and hydromorphine disrupted the voiding phase evidenced by the reduced coordination of EUS activity with detrusor contraction, while bladder emptying under midazolam was achieved by EUS relaxation only.

TASCI-transcutaneous tibial nerve stimulation in patients with acute spinal cord injury to prevent neurogenic detrusor overactivity: protocol for a nationwide, randomised, sham-controlled, double-blind clinical trial.

INTRODUCTION: Neurogenic lower urinary tract dysfunction (NLUTD), including neurogenic detrusor overactivity (NDO) and detrusor sphincter dyssynergia, is one of the most frequent and devastating sequelae of spinal cord injury (SCI), as it can lead to urinary incontinence and secondary damage such as renal failure. Transcutaneous tibial nerve stimulation (TTNS) is a promising, non-invasive neuromodulatory intervention that may prevent the emergence of the C-fibre evoked bladder reflexes that are thought to cause NDO. This paper presents the protocol for TTNS in acute SCI (TASCI), which will evaluate the efficacy of TTNS in preventing NDO. Furthermore, TASCI will provide insight into the mechanisms underlying TTNS, and the course of NLUTD development after SCI. METHODS AND ANALYSIS: TASCI is a nationwide, randomised, sham-controlled, double-blind clinical trial, conducted at all four SCI centres in Switzerland. The longitudinal design includes a baseline assessment period 5-39 days after acute SCI and follow-up assessments occurring 3, 6 and 12 months after SCI. A planned 114 participants will be randomised into verum or sham TTNS groups (1:1 ratio), stratified on study centre and lower extremity motor score. TTNS is performed for 30 min/day, 5 days/week, for 6-9 weeks starting within 40 days after SCI. The primary outcome is the occurrence of NDO jeopardising the upper urinary tract at 1 year after SCI, assessed by urodynamic investigation. Secondary outcome measures assess bladder and bowel function and symptoms, sexual function, neurological structure and function, functional independence, quality of life, as well as changes in biomarkers in the urine, blood, stool and bladder tissue. Safety of TTNS is the tertiary outcome. ETHICS AND DISSEMINATION: TASCI is approved by the Swiss Ethics Committee for Northwest/Central Switzerland, the Swiss Ethics Committee Vaud and the Swiss Ethics Committee Zürich (#2019-00074). Findings will be disseminated through peer-reviewed publications. TRIAL REGISTRATION NUMBER: NCT03965299.

Tumor Necrosis Factor-α Initiates miRNA-mRNA Signaling Cascades in Obstruction-Induced Bladder Dysfunction.

Bladder outlet obstruction (BOO) and the ensuing clinical lower urinary tract dysfunction are common in elderly patients. BOO is accompanied by urodynamic changes in bladder function and leads to organ fibrosis and ultimately loss of contractility. Comprehensive transcriptome analysis of bladder samples from human patients with different urodynamically defined phenotypes of BOO revealed tumor necrosis factor (TNF)-α as the top upstream signaling pathway regulator. Herein, we validated next-generation sequencing and pathway analysis in cell-based models using bladder smooth muscle and urothelial cells exposed to TNF-α. miRNA profiling and transcriptome analysis of TNF-α-treated bladder smooth muscle cells revealed striking similarities with human BOO. Using a comparative approach, TNF-specific and TNF-independent pathways were delineated in human biopsy specimens. Concomitant down-regulation of smooth muscle cell-specific miRNAs and smooth muscle markers after TNF-α treatment was in accordance with the loss of contractility in humans in advanced obstruction-induced bladder remodeling. The expression levels of four abundant TNF-regulated miRNAs were modulated; the compensatory up-regulation of miR-199a-5p reduced NF-κB signaling. Essential hubs of TNF-α signaling pathways mitogen-activated protein kinase kinase kinase (apoptosis signal-regulating kinase 1) and inhibitor of nuclear factor κ B kinase subunit ß (IκB kinase ß) were targeted by miR-199a-5p. miR-199a-5p might be part of a negative feedback loop, reducing the impact of TNF, whereas its down-regulation in acontractile bladders from BOO patients advances the disease. The compensatory up-regulation of miR-199a-5p together with TNF-α inhibition may be therapeutically beneficial.

Improved isolation strategies to increase the yield and purity of human urinary exosomes for biomarker discovery.

Circulating miRNAs are detected in extracellular space and body fluids such as urine. Circulating RNAs can be packaged in secreted urinary extracellular vesicles (uEVs) and thus protected from degradation. Urinary exosome preparations might contain specific miRNAs, relevant as biomarkers in renal and bladder diseases. Major difficulties in application of uEVs into the clinical environment are the high variability and low reproducibility of uEV isolation methods. Here we used five different methods to isolate uEVs and compared the size distribution, morphology, yield, presence of exosomal protein markers and RNA content of uEVs. We present an optimized ultracentrifugation and size exclusion chromatography approach for highly reproducible isolation for 50-150 nm uEVs, corresponding to the exosomes, from 50 ml urine. We profiled the miRNA content of uEVs and total urine from the same samples with the NanoString platform and validated the data using qPCR. Our results indicate that 18 miRNAs, robustly detected in uEVs were always present in the total urine. However, 15 miRNAs could be detected only in the total urine preparations and might represent naked circulating miRNA species. This is a novel unbiased and reproducible strategy for uEVs isolation, content normalization and miRNA cargo analysis, suitable for biomarker discovery studies.

miR-19b enhances proliferation and apoptosis resistance via the EGFR signaling pathway by targeting PP2A and BIM in non-small cell lung cancer.

BACKGROUND: Epidermal growth factor receptor (EGFR) mutations enable constitutive active downstream signaling of PI3K/AKT, KRAS/ERK and JAK/STAT pathways, and promote tumor progression by inducing uncontrolled proliferation, evasion of apoptosis and migration of non-small cell lung cancer (NSCLC). In addition, such EGFR mutations increase the susceptibility of patients with NSCLC to tyrosine kinase inhibitor (TKI) therapy, but treated patients will invariably relapse with resistant disease. A global understanding of underlying molecular mechanisms of EGFR signaling may improve the management of NSCLC patients. METHODS: microarray analysis was performed to identify PI3K/AKT-regulated miRNAs. Phosphoproteomic analysis and cell based assays were performed using NSCLC cell lines lentivirally transduced with anti-miR or miR overexpressing constructs. RESULTS: Here, we show that 17 miRNAs including members of the miR-17~ 92 cluster are dysregulated following PI3K/AKT inhibition of EGFR mutant NSCLC cells. Bioinformatics analysis revealed that dysregulated miRNAs act in a concerted manner to enhance the activity of the EGFR signaling pathway. These findings were closely mirrored by attenuation of miR-17~ 92 family member miR-19b in NSCLC cell lines which resulted in reduced phosphorylation of ERK, AKT and STAT and effector proteins in EGFR mutant NSCLC cells. Consistent with this finding, cell cycle progression, clonogenic growth and migration were reduced and apoptosis was enhanced. Co-treatment of NSCLC cells with the tyrosine kinase inhibitor (TKI) gefitinib and anti-miR-19b construct reduced migration and clonogenic growth in a synergistic manner suggesting that EGFR and miR-19b act together to control oncogenic processes. Serine/threonine phosphatase PP2A subunit PPP2R5E and BCL2L11 encoding BIM were identified as major targets of miR-19b by target validation assays. Consistent with this finding, PP2A activity was strongly enhanced in NSCLC transduced with anti-miR-19b construct, but not in cells co-transduced with anti-miR-19b and shPPP2R5E, suggesting that PPP2R5E is a major constituent of the PP2A complex. Accordingly, enhanced proliferation by miR-19b was due to targeting PPP2R5E. In contrast, apoptosis resistance was mainly due to targeting BCL2L11. CONCLUSION: Our results provide insight into the importance of targeting PPP2R5E and BCL2L11 by miR-19b in oncogenic processes of NSCLC. Attenuation of miR-19b expression could potentially be exploited in adjuvant therapy of EGFR mutant NSCLC.

Functional Association between Regulatory RNAs and the Annexins.

Cells respond to pathophysiological states by activation of stress-induced signalling. Regulatory non-coding microRNAs (miRNAs) often form stable feed-forward loops which ensure prolongation of the signal, contributing to sustained activation. Members of the annexin protein family act as sensors for Ca2+, pH, and lipid second messengers, and regulate various signalling pathways. Recently, annexins were reported to participate in feedback loops, suppressing miRNA synthesis and attenuating stress-induced dysregulation of gene expression. They can directly or indirectly associate with RNAs, and are transferred between the cells in exosomes and shed microvesicles. The ability of annexins to recruit other proteins and miRNAs into exosomes implicates them in control of cell-cell interactions, affecting the adaptive responses and remodelling processes during disease. The studies summarized in this Review point to an emerging role of annexins in influencing the synthesis, localisation, and transfer of regulatory RNAs.

Concordant miRNA and mRNA expression profiles in humans and mice with bladder outlet obstruction.

Bladder outlet obstruction (BOO) leads to lower urinary tract symptoms (LUTS) and urodynamic changes of the bladder function. Previously we identified microRNA (miRNA) and mRNA expression profiles associated with different states of BOO-induced LUTD in human patients. Bladder wall remodeling resulting from obstruction is widely studied in animal models of experimentally-induced partial BOO (pBOO). Here we determined the expression profiles of miRNAs and selected mRNAs in pBOO mice and compared the observed changes to human patients. Similar to results from human patients, we observed a down-regulation of smooth muscle-associated miRNAs mmu-miR-1, mmu-miR-143, mmu-miR-145, mmu-miR-486 and mmu-miR-133a in pBOO mouse bladders. Pro-fibrotic miRNAs mmu-miR-142-3p and mmu-miR-21 were up-regulated, and anti-fibrotic miRNA mmu-miR-29c was down-regulated. Pathway analysis in human BOO patients identified TNF-alpha as the top upstream regulator. Although there was evidence of hypertrophic changes in pBOO mice, contrary to human data, we observed no regulation of TNF-responsive genes in the mouse model. Experimentally-induced pBOO in mice led to significant gene expression changes, including alteration of pro-fibrotic mRNAs and miRNAs resembling human BOO patients. Gene expression changes were also validated in a mouse model of bladder inflammation. Lack of evidence of TNF-alpha-induced miRNA and mRNA regulation might indicate a different pathophysiological mechanism of organ remodeling in pBOO model compared to the human disease.

Role of hepatic Annexin A6 in fatty acid-induced lipid droplet formation.

Annexin A6 (AnxA6) has been implicated in the regulation of endo-/exocytic pathways, cholesterol transport, and the formation of multifactorial signaling complexes in many different cell types. More recently, AnxA6 has also been linked to triglyceride storage in adipocytes. Here we investigated the potential role of AnxA6 in fatty acid (FA) - induced lipid droplet (LD) formation in hepatocytes. AnxA6 was associated with LD from rat liver and HuH7 hepatocytes. In oleic acid (OA) -loaded HuH7 cells, substantial amounts of AnxA6 bound to LD in a Ca2+-independent manner. Remarkably, stable or transient AnxA6 overexpression in HuH7 cells led to elevated LD numbers/size and neutral lipid staining under control conditions as well as after OA loading compared to controls. In contrast, overexpression of AnxA1, AnxA2 and AnxA8 did not impact on OA-induced lipid accumulation. On the other hand, incubation of AnxA6-depleted HuH7 cells or primary hepatocytes from AnxA6 KO-mice with OA led to reduced FA accumulation and LD numbers. Furthermore, morphological analysis of liver sections from A6-KO mice revealed significantly lower LD numbers compared to wildtype animals. Interestingly, pharmacological inhibition of cytoplasmic phospholipase A2α (cPLA2α)-dependent LD formation was ineffective in AnxA6-depleted HuH7 cells. We conclude that cPLA2α-dependent pathways contribute to the novel regulatory role of hepatic AnxA6 in LD formation.

Characterization of miRNA-regulated networks, hubs of signaling, and biomarkers in obstruction-induced bladder dysfunction.

Bladder outlet obstruction (BOO) induces significant organ remodeling, leading to lower urinary tract symptoms accompanied by urodynamic changes in bladder function. Here, we report mRNA and miRNA transcriptome sequencing of bladder samples from human patients with different urodynamically defined states of BOO. Patients' miRNA and mRNA expression profiles correlated with urodynamic findings. Validation of RNA sequencing results in an independent patient cohort identified combinations of 3 mRNAs (NRXN3, BMP7, UPK1A) and 3 miRNAs (miR-103a-3p, miR-10a-5p, miR-199a-3p) sufficient to discriminate between bladder functional states. All BOO patients shared cytokine and immune response pathways, TGF-ß and NO signaling pathways, and hypertrophic PI3K/AKT signaling pathways. AP-1 and NFkB were dominant transcription factors, and TNF-α was the top upstream regulator. Integrated miRNA-mRNA expression analysis identified pathways and molecules targeted by differentially expressed miRNAs. Molecular changes in BOO suggest an increasing involvement of miRNAs in the control of bladder function from the overactive to underactive/acontractile states.