Cell-autonomous IL6ST activation suppresses prostate cancer development via STAT3/ARF/p53-driven senescence and confers an immune-active tumor microenvironment.

BACKGROUND: Prostate cancer ranks as the second most frequently diagnosed cancer in men worldwide. Recent research highlights the crucial roles IL6ST-mediated signaling pathways play in the development and progression of various cancers, particularly through hyperactivated STAT3 signaling. However, the molecular programs mediated by IL6ST/STAT3 in prostate cancer are poorly understood. METHODS: To investigate the role of IL6ST signaling, we constitutively activated IL6ST signaling in the prostate epithelium of a Pten-deficient prostate cancer mouse model in vivo and examined IL6ST expression in large cohorts of prostate cancer patients. We complemented these data with in-depth transcriptomic and multiplex histopathological analyses. RESULTS: Genetic cell-autonomous activation of the IL6ST receptor in prostate epithelial cells triggers active STAT3 signaling and significantly reduces tumor growth in vivo. Mechanistically, genetic activation of IL6ST signaling mediates senescence via the STAT3/ARF/p53 axis and recruitment of cytotoxic T-cells, ultimately impeding tumor progression. In prostate cancer patients, high IL6ST mRNA expression levels correlate with better recurrence-free survival, increased senescence signals and a transition from an immune-cold to an immune-hot tumor. CONCLUSIONS: Our findings demonstrate a context-dependent role of IL6ST/STAT3 in carcinogenesis and a tumor-suppressive function in prostate cancer development by inducing senescence and immune cell attraction. We challenge the prevailing concept of blocking IL6ST/STAT3 signaling as a functional prostate cancer treatment and instead propose cell-autonomous IL6ST activation as a novel therapeutic strategy.

Transcriptome analysis of thermomorphogenesis in ovules and during early seed development in Brassica napus.

BACKGROUND: Plant sexual reproduction is highly sensitive to elevated ambient temperatures, impacting seed development and production. We previously phenotyped this effect on three rapeseed cultivars (DH12075, Topas DH4079, and Westar). This work describes the transcriptional response associated with the phenotypic changes induced by heat stress during early seed development in Brassica napus. RESULTS: We compared the differential transcriptional response in unfertilized ovules and seeds bearing embryos at 8-cell and globular developmental stages of the three cultivars exposed to high temperatures. We identified that all tissues and cultivars shared a common transcriptional response with the upregulation of genes linked to heat stress, protein folding and binding to heat shock proteins, and the downregulation of cell metabolism. The comparative analysis identified an enrichment for a response to reactive oxygen species (ROS) in the heat-tolerant cultivar Topas, correlating with the phenotypic changes. The highest heat-induced transcriptional response in Topas seeds was detected for genes encoding various peroxidases, temperature-induced lipocalin (TIL1), or protein SAG21/LEA5. On the contrary, the transcriptional response in the two heat-sensitive cultivars, DH12075 and Westar, was characterized by heat-induced cellular damages with the upregulation of genes involved in the photosynthesis and plant hormone signaling pathways. Particularly, the TIFY/JAZ genes involved in jasmonate signaling were induced by stress, specifically in ovules of heat-sensitive cultivars. Using a weighted gene co-expression network analysis (WGCNA), we identified key modules and hub genes involved in the heat stress response in studied tissues of either heat-tolerant or sensitive cultivars. CONCLUSIONS: Our transcriptional analysis complements a previous phenotyping analysis by characterizing the growth response to elevated temperatures during early seed development and reveals the molecular mechanisms underlying the phenotypic response. The results demonstrated that response to ROS, seed photosynthesis, and hormonal regulation might be the critical factors for stress tolerance in oilseed rape.

Toll-Like Receptor 3 Overexpression Induces Invasion of Prostate Cancer Cells, whereas Its Activation Triggers Apoptosis.

Toll-like receptor 3 (TLR3) is an endosomal receptor expressed in several immune and epithelial cells. Recent studies have highlighted its expression also in solid tumors, including prostate cancer (PCa), and have described its role primarily in the proinflammatory response and induction of apoptosis. It is up-regulated in some castration-resistant prostate cancers. However, the role of TLR3 in prostate cancer progression remains largely unknown. The current study experimentally demonstrated that exogenous TLR3 activation in PCa cell lines leads to a significant induction of secretion of the cytokines IL-6, IL-8, and interferon-ß, depending on the model and chemoresistance status. Transcriptomic analysis of TLR3-overexpressing cells revealed a functional program that is enriched for genes involved in the regulation of cell motility, migration, and tumor invasiveness. Increased motility, migration, and invasion in TLR3-overexpressing cell line were confirmed by several in vitro assays and using an orthotopic prostate xenograft model in vivo. Furthermore, TLR3-ligand induced apoptosis via cleavage of caspase-3/7 and poly (ADP-ribose) polymerase, predominantly in TLR3-overexpressing cells. These results indicate that TLR3 may be involved in prostate cancer progression and metastasis; however, it might also represent an Achilles heel of PCa, which can be exploited for targeted therapy.

Analysis of chimeric reads characterises the diverse targetome of AGO2-mediated regulation.

Argonaute proteins are instrumental in regulating RNA stability and translation. AGO2, the major mammalian Argonaute protein, is known to primarily associate with microRNAs, a family of small RNA 'guide' sequences, and identifies its targets primarily via a 'seed' mediated partial complementarity process. Despite numerous studies, a definitive experimental dataset of AGO2 'guide'-'target' interactions remains elusive. Our study employs two experimental methods-AGO2 CLASH and AGO2 eCLIP, to generate thousands of AGO2 target sites verified by chimeric reads. These chimeric reads contain both the AGO2 loaded small RNA 'guide' and the target sequence, providing a robust resource for modeling AGO2 binding preferences. Our novel analysis pipeline reveals thousands of AGO2 target sites driven by microRNAs and a significant number of AGO2 'guides' derived from fragments of other small RNAs such as tRNAs, YRNAs, snoRNAs, rRNAs, and more. We utilize convolutional neural networks to train machine learning models that accurately predict the binding potential for each 'guide' class and experimentally validate several interactions. In conclusion, our comprehensive analysis of the AGO2 targetome broadens our understanding of its 'guide' repertoire and potential function in development and disease. Moreover, we offer practical bioinformatic tools for future experiments and the prediction of AGO2 targets. All data and code from this study are freely available at https://github.com/ML-Bioinfo-CEITEC/HybriDetector/ .

EGFR stimulation enables IL-6 trans-signalling via iRhom2-dependent ADAM17 activation in mammary epithelial cells.

The cytokine interleukin-6 (IL-6) has considerable pro-inflammatory properties and is a driver of many physiological and pathophysiological processes. Cellular responses to IL-6 are mediated by membrane-bound or soluble forms of the IL-6 receptor (IL-6R) complexed with the signal-transducing subunit gp130. While expression of the membrane-bound IL-6R is restricted to selected cell types, soluble IL-6R (sIL-6R) enables gp130 engagement on all cells, a process termed IL-6 trans-signalling and considered to be pro-inflammatory. sIL-6R is predominantly generated through proteolytic processing by the metalloproteinase ADAM17. ADAM17 also liberates ligands of the epidermal growth factor receptor (EGFR), which is a prerequisite for EGFR activation and results in stimulation of proliferative signals. Hyperactivation of EGFR mostly due to activating mutations drives cancer development. Here, we reveal an important link between overshooting EGFR signalling and the IL-6 trans-signalling pathway. In epithelial cells, EGFR activity induces not only IL-6 expression but also the proteolytic release of sIL-6R from the cell membrane by increasing ADAM17 surface activity. We find that this derives from the transcriptional upregulation of iRhom2, a crucial regulator of ADAM17 trafficking and activation, upon EGFR engagement, which results in increased surface localization of ADAM17. Also, phosphorylation of the EGFR-downstream mediator ERK mediates ADAM17 activity via interaction with iRhom2. In sum, our study reveals an unforeseen interplay between EGFR activation and IL-6 trans-signalling, which has been shown to be fundamental in inflammation and cancer.

Distinct p53 phosphorylation patterns in chronic lymphocytic leukemia patients are reflected in the activation of circumjacent pathways upon DNA damage.

TP53 gene abnormalities represent the most important biomarker in chronic lymphocytic leukemia (CLL). Altered protein modifications could also influence p53 function, even in the wild-type protein. We assessed the impact of p53 protein phosphorylations on p53 functions as an alternative inactivation mechanism. We studied p53 phospho-profiles induced by DNA-damaging agents (fludarabine, doxorubicin) in 71 TP53-intact primary CLL samples. Doxorubicin induced two distinct phospho-profiles: profile I (heavily phosphorylated) and profile II (hypophosphorylated). Profile II samples were less capable of activating p53 target genes upon doxorubicin exposure, resembling TP53-mutant samples at the transcriptomic level, whereas standard p53 signaling was triggered in profile I. ATM locus defects were more common in profile II. The samples also differed in the basal activity of the hypoxia pathway: the highest level was detected in TP53-mutant samples, followed by profile II and profile I. Our study suggests that wild-type TP53 CLL cells with less phosphorylated p53 show TP53-mutant-like behavior after DNA damage. p53 hypophosphorylation and the related lower ability to respond to DNA damage are linked to ATM locus defects and the higher basal activity of the hypoxia pathway.

Mimicking Tumor Cell Heterogeneity of Colorectal Cancer in a Patient-derived Organoid-Fibroblast Model.

BACKGROUND & AIMS: Patient-derived organoid cancer models are generated from epithelial tumor cells and reflect tumor characteristics. However, they lack the complexity of the tumor microenvironment, which is a key driver of tumorigenesis and therapy response. Here, we developed a colorectal cancer organoid model that incorporates matched epithelial cells and stromal fibroblasts. METHODS: Primary fibroblasts and tumor cells were isolated from colorectal cancer specimens. Fibroblasts were characterized for their proteome, secretome, and gene expression signatures. Fibroblast/organoid co-cultures were analyzed by immunohistochemistry and compared with their tissue of origin, as well as on gene expression levels compared with standard organoid models. Bioinformatics deconvolution was used to calculate cellular proportions of cell subsets in organoids based on single-cell RNA sequencing data. RESULTS: Normal primary fibroblasts, isolated from tumor adjacent tissue, and cancer associated fibroblasts retained their molecular characteristics in vitro, including higher motility of cancer associated compared with normal fibroblasts. Importantly, both cancer-associated fibroblasts and normal fibroblasts supported cancer cell proliferation in 3D co-cultures, without the addition of classical niche factors. Organoids grown together with fibroblasts displayed a larger cellular heterogeneity of tumor cells compared with mono-cultures and closely resembled the in vivo tumor morphology. Additionally, we observed a mutual crosstalk between tumor cells and fibroblasts in the co-cultures. This was manifested by considerably deregulated pathways such as cell-cell communication and extracellular matrix remodeling in the organoids. Thrombospondin-1 was identified as a critical factor for fibroblast invasiveness. CONCLUSION: We developed a physiological tumor/stroma model, which will be vital as a personalized tumor model to study disease mechanisms and therapy response in colorectal cancer.

miRBind: A Deep Learning Method for miRNA Binding Classification.

The binding of microRNAs (miRNAs) to their target sites is a complex process, mediated by the Argonaute (Ago) family of proteins. The prediction of miRNA:target site binding is an important first step for any miRNA target prediction algorithm. To date, the potential for miRNA:target site binding is evaluated using either co-folding free energy measures or heuristic approaches, based on the identification of binding 'seeds', i.e., continuous stretches of binding corresponding to specific parts of the miRNA. The limitations of both these families of methods have produced generations of miRNA target prediction algorithms that are primarily focused on 'canonical' seed targets, even though unbiased experimental methods have shown that only approximately half of in vivo miRNA targets are 'canonical'. Herein, we present miRBind, a deep learning method and web server that can be used to accurately predict the potential of miRNA:target site binding. We trained our method using seed-agnostic experimental data and show that our method outperforms both seed-based approaches and co-fold free energy approaches. The full code for the development of miRBind and a freely accessible web server are freely available.

The mechanical regulation of RNA binding protein hnRNPC in the failing heart.

Cardiac pathologies are characterized by intense remodeling of the extracellular matrix (ECM) that eventually leads to heart failure. Cardiomyocytes respond to the ensuing biomechanical stress by reexpressing fetal contractile proteins via transcriptional and posttranscriptional processes, such as alternative splicing (AS). Here, we demonstrate that the heterogeneous nuclear ribonucleoprotein C (hnRNPC) is up-regulated and relocates to the sarcomeric Z-disc upon ECM pathological remodeling. We show that this is an active site of localized translation, where the ribonucleoprotein associates with the translation machinery. Alterations in hnRNPC expression, phosphorylation, and localization can be mechanically determined and affect the AS of mRNAs involved in mechanotransduction and cardiovascular diseases, including Hippo pathway effector Yes-associated protein 1. We propose that cardiac ECM remodeling serves as a switch in RNA metabolism by affecting an associated regulatory protein of the spliceosome apparatus. These findings offer new insights on the mechanism of mRNA homeostatic mechanoregulation in pathological conditions.

GDF11 inhibits adipogenesis and improves mature adipocytes metabolic function via WNT/ß-catenin and ALK5/SMAD2/3 pathways.

OBJECTIVE: GDF11 is a member of the TGF-ß superfamily that was recently implicated as potential "rejuvenating" factor, which can ameliorate metabolic disorders. The main objective of the presented study was to closely characterize the role of GDF11 signaling in the glucose homeostasis and in the differentiation of white adipose tissue. METHODS: We performed microscopy imaging, biochemical and transcriptomic analyses of adipose tissues of 9 weeks old ob/ob mice and murine and human pre-adipocyte cell lines. RESULTS: Our in vivo experiments employing GDF11 treatment in ob/ob mice showed improved glucose/insulin homeostasis, decreased weight gain and white adipocyte size. Furthermore, GDF11 treatment inhibited adipogenesis in pre-adipocytes by ALK5-SMAD2/3 activation in cooperation with the WNT/ß-catenin pathway, whose inhibition resulted in adipogenic differentiation. Lastly, we observed significantly elevated levels of the adipokine hormone adiponectin and increased glucose uptake by mature adipocytes upon GDF11 exposure. CONCLUSION: We show evidence that link GDF11 to adipogenic differentiation, glucose, and insulin homeostasis, which are pointing towards potential beneficial effects of GDF11-based "anti-obesity" therapy.

CDK9 activity is critical for maintaining MDM4 overexpression in tumor cells.

The identification of the essential role of cyclin-dependent kinases (CDKs) in the control of cell division has prompted the development of small-molecule CDK inhibitors as anticancer drugs. For many of these compounds, the precise mechanism of action in individual tumor types remains unclear as they simultaneously target different classes of CDKs - enzymes controlling the cell cycle progression as well as CDKs involved in the regulation of transcription. CDK inhibitors are also capable of activating p53 tumor suppressor in tumor cells retaining wild-type p53 gene by modulating MDM2 levels and activity. In the current study, we link, for the first time, CDK activity to the overexpression of the MDM4 (MDMX) oncogene in cancer cells. Small-molecule drugs targeting the CDK9 kinase, dinaciclib, flavopiridol, roscovitine, AT-7519, SNS-032, and DRB, diminished MDM4 levels and activated p53 in A375 melanoma and MCF7 breast carcinoma cells with only a limited effect on MDM2. These results suggest that MDM4, rather than MDM2, could be the primary transcriptional target of pharmacological CDK inhibitors in the p53 pathway. CDK9 inhibitor atuveciclib downregulated MDM4 and enhanced p53 activity induced by nutlin-3a, an inhibitor of p53-MDM2 interaction, and synergized with nutlin-3a in killing A375 melanoma cells. Furthermore, we found that human pluripotent stem cell lines express significant levels of MDM4, which are also maintained by CDK9 activity. In summary, we show that CDK9 activity is essential for the maintenance of high levels of MDM4 in human cells, and drugs targeting CDK9 might restore p53 tumor suppressor function in malignancies overexpressing MDM4.

NEEMP: software for validation, accurate calculation and fast parameterization of EEM charges.

BACKGROUND: The concept of partial atomic charges was first applied in physical and organic chemistry and was later also adopted in computational chemistry, bioinformatics and chemoinformatics. The electronegativity equalization method (EEM) is the most frequently used approach for calculating partial atomic charges. EEM is fast and its accuracy is comparable to the quantum mechanical charge calculation method for which it was parameterized. Several EEM parameter sets for various types of molecules and QM charge calculation approaches have been published and new ones are still needed and produced. Methodologies for EEM parameterization have been described in a few articles, but a software tool for EEM parameterization and EEM parameter sets validation has not been available until now. RESULTS: We provide the software tool NEEMP (http://ncbr.muni.cz/NEEMP), which offers three main functionalities: EEM parameterization [via linear regression (LR) and differential evolution with local minimization (DE-MIN)]; EEM parameter set validation (i.e., validation of coverage and quality) and EEM charge calculation. NEEMP functionality is shown using a parameterization and a validation case study. The parameterization case study demonstrated that LR is an appropriate approach for smaller and homogeneous datasets and DE-MIN is a suitable solution for larger and heterogeneous datasets. The validation case study showed that EEM parameter set coverage and quality can still be problematic. Therefore, it makes sense to verify the coverage and quality of EEM parameter sets before their use, and NEEMP is an appropriate tool for such verification. Moreover, it seems from both case studies that new EEM parameterizations need to be performed and new EEM parameter sets obtained with high quality and coverage for key structural databases. CONCLUSION: We provide the software tool NEEMP, which is to the best of our knowledge the only available software package that enables EEM parameterization and EEM parameter set validation. Additionally, its DE-MIN parameterization method is an innovative approach, developed by ourselves and first published in this work. In addition, we also prepared four high-quality EEM parameter sets tailored to ligand molecules.Graphical abstract.

High-quality and universal empirical atomic charges for chemoinformatics applications.

BACKGROUND: Partial atomic charges describe the distribution of electron density in a molecule and therefore provide clues to the chemical behaviour of molecules. Recently, these charges have become popular in chemoinformatics, as they are informative descriptors that can be utilised in pharmacophore design, virtual screening, similarity searches etc. Especially conformationally-dependent charges perform very successfully. In particular, their fast and accurate calculation via the Electronegativity Equalization Method (EEM) seems very promising for chemoinformatics applications. Unfortunately, published EEM parameter sets include only parameters for basic atom types and they often miss parameters for halogens, phosphorus, sulphur, triple bonded carbon etc. Therefore their applicability for drug-like molecules is limited. RESULTS: We have prepared six EEM parameter sets which enable the user to calculate EEM charges in a quality comparable to quantum mechanics (QM) charges based on the most common charge calculation schemes (i.e., MPA, NPA and AIM) and a robust QM approach (HF/6-311G, B3LYP/6-311G). The calculated EEM parameters exhibited very good quality on a training set ([Formula: see text]) and also on a test set ([Formula: see text]). They are applicable for at least 95 % of molecules in key drug databases (DrugBank, ChEMBL, Pubchem and ZINC) compared to less than 60 % of the molecules from these databases for which currently used EEM parameters are applicable. CONCLUSIONS: We developed EEM parameters enabling the fast calculation of high-quality partial atomic charges for almost all drug-like molecules. In parallel, we provide a software solution for their easy computation (http://ncbr.muni.cz/eem_parameters). It enables the direct application of EEM in chemoinformatics.