Repurposed floxacins targeting RSK4 prevent chemoresistance and metastasis in lung and bladder cancer.

Lung and bladder cancers are mostly incurable because of the early development of drug resistance and metastatic dissemination. Hence, improved therapies that tackle these two processes are urgently needed to improve clinical outcome. We have identified RSK4 as a promoter of drug resistance and metastasis in lung and bladder cancer cells. Silencing this kinase, through either RNA interference or CRISPR, sensitized tumor cells to chemotherapy and hindered metastasis in vitro and in vivo in a tail vein injection model. Drug screening revealed several floxacin antibiotics as potent RSK4 activation inhibitors, and trovafloxacin reproduced all effects of RSK4 silencing in vitro and in/ex vivo using lung cancer xenograft and genetically engineered mouse models and bladder tumor explants. Through x-ray structure determination and Markov transient and Deuterium exchange analyses, we identified the allosteric binding site and revealed how this compound blocks RSK4 kinase activation through binding to an allosteric site and mimicking a kinase autoinhibitory mechanism involving the RSK4's hydrophobic motif. Last, we show that patients undergoing chemotherapy and adhering to prophylactic levofloxacin in the large placebo-controlled randomized phase 3 SIGNIFICANT trial had significantly increased (P = 0.048) long-term overall survival times. Hence, we suggest that RSK4 inhibition may represent an effective therapeutic strategy for treating lung and bladder cancer.

The role of the p90 ribosomal S6 kinase family in prostate cancer progression and therapy resistance.

Prostate cancer (PCa) is the second most commonly occurring cancer in men, with over a million new cases every year worldwide. Tumor growth and disease progression is mainly dependent on the Androgen Receptor (AR), a ligand dependent transcription factor. Standard PCa therapeutic treatments include androgen-deprivation therapy and AR signaling inhibitors. Despite being successful in controlling the disease in the majority of men, the high frequency of disease progression to aggressive and therapy resistant stages (termed castrate resistant prostate cancer) has led to the search for new therapeutic targets. The p90 ribosomal S6 kinase (RSK1-4) family is a group of highly conserved Ser/Thr kinases that holds promise as a novel target. RSKs are effector kinases that lay downstream of the Ras/Raf/MEK/ERK signaling pathway, and aberrant activation or expression of RSKs has been reported in several malignancies, including PCa. Despite their structural similarities, RSK isoforms have been shown to perform nonredundant functions and target a wide range of substrates involved in regulation of transcription and translation. In this article we review the roles of the RSKs in proliferation and motility, cell cycle control and therapy resistance in PCa, highlighting the possible interplay between RSKs and AR in mediating disease progression. In addition, we summarize the current advances in RSK inhibitor development and discuss their potential clinical benefits.

Machine learning application for development of a data-driven predictive model able to investigate quality of life scores in a rare disease.

BACKGROUND: Alkaptonuria (AKU) is an ultra-rare autosomal recessive disease caused by a mutation in the homogentisate 1,2-dioxygenase (HGD) gene. One of the main obstacles in studying AKU, and other ultra-rare diseases, is the lack of a standardized methodology to assess disease severity or response to treatment. Quality of Life scores (QoL) are a reliable way to monitor patients' clinical condition and health status. QoL scores allow to monitor the evolution of diseases and assess the suitability of treatments by taking into account patients' symptoms, general health status and care satisfaction. However, more comprehensive tools to study a complex and multi-systemic disease like AKU are needed. In this study, a Machine Learning (ML) approach was implemented with the aim to perform a prediction of QoL scores based on clinical data deposited in the ApreciseKUre, an AKU- dedicated database. METHOD: Data derived from 129 AKU patients have been firstly examined through a preliminary statistical analysis (Pearson correlation coefficient) to measure the linear correlation between 11 QoL scores. The variable importance in QoL scores prediction of 110 ApreciseKUre biomarkers has been then calculated using XGBoost, with K-nearest neighbours algorithm (k-NN) approach. Due to the limited number of data available, this model has been validated using surrogate data analysis. RESULTS: We identified a direct correlation of 6 (age, Serum Amyloid A, Chitotriosidase, Advanced Oxidation Protein Products, S-thiolated proteins and Body Mass Index) out of 110 biomarkers with the QoL health status, in particular with the KOOS (Knee injury and Osteoarthritis Outcome Score) symptoms (Relative Absolute Error (RAE) 0.25). The error distribution of surrogate-model (RAE 0.38) was unequivocally higher than the true-model one (RAE of 0.25), confirming the consistency of our dataset. Our data showed that inflammation, oxidative stress, amyloidosis and lifestyle of patients correlates with the QoL scores for physical status, while no correlation between the biomarkers and patients' mental health was present (RAE 1.1). CONCLUSIONS: This proof of principle study for rare diseases confirms the importance of database, allowing data management and analysis, which can be used to predict more effective treatments.

Hybrid Methods in Iron-Sulfur Cluster Biogenesis.

Hybrid methods, which combine and integrate several biochemical and biophysical techniques, have rapidly caught up in the last twenty years to provide a way to obtain a fuller description of proteins and molecular complexes with sizes and complexity otherwise not easily affordable. Here, we review the use of a robust hybrid methodology based on a mixture of NMR, SAXS, site directed mutagenesis and molecular docking which we have developed to determine the structure of weakly interacting molecular complexes. We applied this technique to gain insights into the structure of complexes formed amongst proteins involved in the molecular machine, which produces the essential iron-sulfur cluster prosthetic groups. Our results were validated both by X-ray structures and by other groups who adopted the same approach. We discuss the advantages and the limitations of our methodology and propose new avenues, which could improve it.

Phosphoregulation of Ire1 RNase splicing activity.

Ire1 is activated in response to accumulation of misfolded proteins within the endoplasmic reticulum as part of the unfolded protein response (UPR). It is a unique enzyme, possessing both kinase and RNase activity that is required for specific splicing of Xbp1 mRNA leading to UPR activation. How phosphorylation impacts on the Ire1 splicing activity is unclear. In this study, we isolate distinct phosphorylated species of Ire1 and assess their effects on RNase splicing both in vitro and in vivo. We find that phosphorylation within the kinase activation loop significantly increases RNase splicing in vitro. Correspondingly, mutants of Ire1 that cannot be phosphorylated on the activation loop show decreased specific Xbp1 and promiscuous RNase splicing activity relative to wild-type Ire1 in cells. These data couple the kinase phosphorylation reaction to the activation state of the RNase, suggesting that phosphorylation of the activation loop is an important step in Ire1-mediated UPR activation.

Structural bases for the interaction of frataxin with the central components of iron-sulphur cluster assembly.

Reduced levels of frataxin, an essential protein of as yet unknown function, are responsible for causing the neurodegenerative pathology Friedreich's ataxia. Independent reports have linked frataxin to iron-sulphur cluster assembly through interactions with the two central components of this machinery: desulphurase Nfs1/IscS and the scaffold protein Isu/IscU. In this study, we use a combination of biophysical methods to define the structural bases of the interaction of CyaY (the bacterial orthologue of frataxin) with the IscS/IscU complex. We show that CyaY binds IscS as a monomer in a pocket between the active site and the IscS dimer interface. Recognition does not require iron and occurs through electrostatic interactions of complementary charged residues. Mutations at the complex interface affect the rates of enzymatic cluster formation. CyaY binding strengthens the affinity of the IscS/IscU complex. Our data suggest a new paradigm for understanding the role of frataxin as a regulator of IscS functions.

Of the vulnerability of orphan complex proteins: the case study of the E. coli IscU and IscS proteins.

IscS and IscU, the two central protein components of the iron sulfur cluster assembly machinery, form a complex that is still relatively poorly characterized. In an attempt to standardize the purification of these proteins for structural studies we have developed a protocol to produce them individually in high concentration and purity. We show that IscS is a rather robust protein as long as it is produced in a PLP loaded form and that this co-factor is essential for fold stability and enzyme activity. In contrast to previous evidence, we also propose that, in contrast with previous evidence, IscU is a thermodynamically stable protein with a well defined fold but, when produced in isolation, is a 'complex-orphan protein' that is prone to unfolding if not stabilised by a co-factor or a protein partner. Our work will facilitate further structural and functional studies of these proteins and eventually lead to a better understanding of the whole machinery.

Bacterial frataxin CyaY is the gatekeeper of iron-sulfur cluster formation catalyzed by IscS.

Frataxin is an essential mitochondrial protein whose reduced expression causes Friedreich's ataxia (FRDA), a lethal neurodegenerative disease. It is believed that frataxin is an iron chaperone that participates in iron metabolism. We have tested this hypothesis using the bacterial frataxin ortholog, CyaY, and different biochemical and biophysical techniques. We observe that CyaY participates in iron-sulfur (Fe-S) cluster assembly as an iron-dependent inhibitor of cluster formation, through binding to the desulfurase IscS. The interaction with IscS involves the iron binding surface of CyaY, which is conserved throughout the frataxin family. We propose that frataxins are iron sensors that act as regulators of Fe-S cluster formation to fine-tune the quantity of Fe-S cluster formed to the concentration of the available acceptors. Our observations provide new perspectives for understanding FRDA and a mechanistic model that rationalizes the available knowledge on frataxin.

Structurally driven selection of human hepatitis C virus mimotopes.

A structural genomics approach is proposed for the development of new diagnostic kits. It combines molecular modelling, peptide synthesis and immunological tests. The preliminary step is the development of a reliable three-dimensional structure of an immunodominant protein of the target pathogenic organism using the various bioinformatic strategies that are now available to structural biologists. Once the protein structure is obtained, the most surface-exposed fragments with minimal sequence variability among the different strains reported in the genomic data bank are reproduced synthetically as linear peptides. These peptides are then tested for immunoreactivity with the plasma of infected patients to determine whether the synthetic molecules have antigenic activity and can therefore be used to detect infecting agents. This structurally driven selection of mimotopes was successfully performed for the human hepatitis C virus, as five peptides that specifically interact with the plasma of HCV-infected patients were identified solely on the basis of the three-dimensional structure predicted for the E2 homodimer of the la viral subtype. A similar approach could easily be extended to a large variety of immunogenic proteins from other pathogenic organisms.