scholarly journals Clinically-weighted transcriptomic signatures for protein kinase inhibitor associated cardiotoxicity

2016 ◽  
Author(s):  
JGC van Hasselt ◽  
J Hansen ◽  
Y Xiong ◽  
J Shim ◽  
A Pickard ◽  
...  
Keyword(s):  
Adverse Event ◽  
Protein Kinase ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Adverse Event Reporting System ◽  
Cardiac Contractility ◽  
Digital Gene Expression ◽  
Adverse Event Reporting ◽  
Protein Kinase Inhibitors ◽  
Risk Scores

ABSTRACTCardiotoxicity (CT) involving diminished cardiac contractility and heart failure is a major adverse event associated with otherwise efficacious protein kinase inhibitors (KIs). Here, we sought to develop clinically-weighted transcriptomic signatures to predict risk of CT and to better understand the biological processes associated with CT risk. We obtained transcriptome-wide response profiles in four human primary cardiomyocyte cell lines that were treated with 22 different KIs using mRNA sequencing with 3’ digital gene expression. The FDA Adverse Event Reporting System was used to derive relative risk scores for four types of CT for different KIs. We used elastic net regression to associate these transcriptomic profiles with KI-associated risk scores for CT subtypes to obtain clinically-weighted transcriptomic signatures, which showed good predictive properties (cross-validation R2>0.87). Our clinically-weighted transcriptomic signatures for KI-associated CT may be of relevance in early drug development for the prediction of KI-associated CT.

scholarly journals Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
J. G. Coen van Hasselt ◽  
Rayees Rahman ◽  
Jens Hansen ◽  
Alan Stern ◽  
Jaehee V. Shim ◽  
...  
Keyword(s):  
Adverse Event ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Adverse Event Reporting System ◽  
Gene Signature ◽  
Adverse Event Reporting ◽  
Cardiac Cells ◽  
Risk Scores ◽  
Patient Reports ◽  
Future Drug

Abstract Kinase inhibitors (KIs) represent an important class of anti-cancer drugs. Although cardiotoxicity is a serious adverse event associated with several KIs, the reasons remain poorly understood, and its prediction remains challenging. We obtain transcriptional profiles of human heart-derived primary cardiomyocyte like cell lines treated with a panel of 26 FDA-approved KIs and classify their effects on subcellular pathways and processes. Individual cardiotoxicity patient reports for these KIs, obtained from the FDA Adverse Event Reporting System, are used to compute relative risk scores. These are then combined with the cell line-derived transcriptomic datasets through elastic net regression analysis to identify a gene signature that can predict risk of cardiotoxicity. We also identify relationships between cardiotoxicity risk and structural/binding profiles of individual KIs. We conclude that acute transcriptomic changes in cell-based assays combined with drug substructures are predictive of KI-induced cardiotoxicity risk, and that they can be informative for future drug discovery.

scholarly journals Effects of Sunitinib and Other Kinase Inhibitors on Cells Harboring a PDGFRB Mutation Associated with Infantile Myofibromatosis

2018 ◽  
Vol 19 (9) ◽  
pp. 2599 ◽  
Author(s):  
Martin Sramek ◽  
Jakub Neradil ◽  
Petra Macigova ◽  
Peter Mudry ◽  
Kristyna Polaskova ◽  
...  
Keyword(s):  
Protein Kinase ◽  
Cell Line ◽  
Tumor Cells ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Growth Factor Receptor ◽  
Tumor Cell Line ◽  
Protein Kinase Inhibitors ◽  
Infantile Myofibromatosis ◽  
Pdgfr Beta

Infantile myofibromatosis represents one of the most common proliferative fibrous tumors of infancy and childhood. More effective treatment is needed for drug-resistant patients, and targeted therapy using specific protein kinase inhibitors could be a promising strategy. To date, several studies have confirmed a connection between the p.R561C mutation in gene encoding platelet-derived growth factor receptor beta (PDGFR-beta) and the development of infantile myofibromatosis. This study aimed to analyze the phosphorylation of important kinases in the NSTS-47 cell line derived from a tumor of a boy with infantile myofibromatosis who harbored the p.R561C mutation in PDGFR-beta. The second aim of this study was to investigate the effects of selected protein kinase inhibitors on cell signaling and the proliferative activity of NSTS-47 cells. We confirmed that this tumor cell line showed very high phosphorylation levels of PDGFR-beta, extracellular signal-regulated kinases (ERK) 1/2 and several other protein kinases. We also observed that PDGFR-beta phosphorylation in tumor cells is reduced by the receptor tyrosine kinase inhibitor sunitinib. In contrast, MAPK/ERK kinases (MEK) 1/2 and ERK1/2 kinases remained constitutively phosphorylated after treatment with sunitinib and other relevant protein kinase inhibitors. Our study showed that sunitinib is a very promising agent that affects the proliferation of tumor cells with a p.R561C mutation in PDGFR-beta.

scholarly journals New tools for carbohydrate sulfation analysis: heparan sulfate 2-O-sulfotransferase (HS2ST) is a target for small-molecule protein kinase inhibitors

2018 ◽  
Vol 475 (15) ◽  
pp. 2417-2433 ◽  
Author(s):  
Dominic P. Byrne ◽  
Yong Li ◽  
Krithika Ramakrishnan ◽  
Igor L. Barsukov ◽  
Edwin A. Yates ◽  
...  
Keyword(s):  
Protein Kinase ◽  
Heparan Sulfate ◽  
Small Molecule ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Protein Kinase Inhibitors ◽  
Fluorescent Substrate ◽  
Raf Kinase ◽  
Shift Analysis

Sulfation of carbohydrate residues occurs on a variety of glycans destined for secretion, and this modification is essential for efficient matrix-based signal transduction. Heparan sulfate (HS) glycosaminoglycans control physiological functions ranging from blood coagulation to cell proliferation. HS biosynthesis involves membrane-bound Golgi sulfotransferases, including HS 2-O-sulfotransferase (HS2ST), which transfers sulfate from the cofactor PAPS (3′-phosphoadenosine 5′-phosphosulfate) to the 2-O position of α-l-iduronate in the maturing polysaccharide chain. The current lack of simple non-radioactive enzyme assays that can be used to quantify the levels of carbohydrate sulfation hampers kinetic analysis of this process and the discovery of HS2ST inhibitors. In the present paper, we describe a new procedure for thermal shift analysis of purified HS2ST. Using this approach, we quantify HS2ST-catalysed oligosaccharide sulfation using a novel synthetic fluorescent substrate and screen the Published Kinase Inhibitor Set, to evaluate compounds that inhibit catalysis. We report the susceptibility of HS2ST to a variety of cell-permeable compounds in vitro, including polyanionic polar molecules, the protein kinase inhibitor rottlerin and oxindole-based RAF kinase inhibitors. In a related study, published back-to-back with the present study, we demonstrated that tyrosyl protein sulfotranferases are also inhibited by a variety of protein kinase inhibitors. We propose that appropriately validated small-molecule compounds could become new tools for rapid inhibition of glycan (and protein) sulfation in cells, and that protein kinase inhibitors might be repurposed or redesigned for the specific inhibition of HS2ST.

Comparison of Adverse Drug Reactions for Patients Treated with Tyrosine Kinase Inhibitors: Data Mining of the Public Version of the FDA Adverse Event Reporting System (AERS)

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 1698-1698
Author(s):  
Tetsuya Tanimoto ◽  
Yasuo Oshima ◽  
Koichiro Yuji ◽  
Masahiro Kami
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Odds Ratio ◽  
Kinase Inhibitors ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Drug Reactions ◽  
Suspected Drug ◽  
Event Reporting

Abstract Abstract 1698 Backgrounds: The consecutive approvals of tyrosine kinase inhibitors (TKIs) have been changing the landscape of treatment strategy for patients with chronic myeloid leukemia (CML). Currently, three TKIs are available worldwide, including imatinib (Glivec/Gleevec; Novartis Pharmaceuticals, East hanover, NJ), nilotinib (Tasigna; Novartis Pharmaceuticals) and dasatinib (Sprycel; Bristol-Myers Squibb, Princeton, NJ). Although second generation TKIs (nilotinib and dasatinib) have shown their efficacy and safety in recent clinical trials, additional data are needed for better understanding and differences in their safety profiles may be helpful when choosing a TKI. We compared the adverse drug reactions (ADRs) for patients treated with three TKIs using spontaneous adverse event reporting after approval to investigate the characteristics of safety profiles. Method: To compare adverse events characteristics among three TKIs, the case/noncase adverse events reports associated with TKIs use were retrieved from the U.S. Food and Drug Administration Adverse Event Reporting System (AERS) between 2004 and 2010. We calculated the reporting odds ratio (ROR), which is known as one of data mining algorithms for signal detection techniques of ADRs, characterized by providing a fast and cost-efficient way of detecting possible ADR signals. All events in the AERS have been coded for data entry in accordance with the standardized terminology, known as Preferred Terms, in the Medical Dictionary for Regulatory Activities. The ROR is similar to the idea of odds ratio, calculating the odds of exposure of the suspected drug in patients who had events divided by the odds of exposure of the suspected drug in those without events. The ROR -1.96 standard error greater than 1 with at least 4 ADR reports was used as a signal criterion in this study. Results: We identified 18,979 ADRs for imatinib, 5,388 ADRs for nilotinib, and 2,482 ADRs for dasatinib. The number of ADRs flagged by our signal criterion was 91 for imatinib, 82 for nilotinib, and 109 for dasatinib. Top 10 lists of ADRs with higher ROR are shown in Table for each TKI. The safety profiles were almost different among TKIs. ADRs related to skin and hepatic function were noted for imatinib, whereas ADRs related to cardiac events were prominent for nilotinib, and ADRs related to lymphocytosis, edema and effusion were noticeable for dasatinib. The different dosing requirements of dasatinib and nilotinib may be an additional factor of ADRs. Conclusions: ADRs reported in the AERS for each TKI were relatively consistent with known characteristics of ADRs reported in previous clinical trials. Our information would be supportive data for choosing a TKI for CML patients based on comorbidities and drug safety profiles. The choice of therapy in a given patient with CML may depend on age, past history and comorbidities as well as disease risk score and mutational analysis. Disclosures: Oshima: Sanofi Aventis: Employment.

scholarly journals New tools for carbohydrate sulphation analysis: Heparan Sulphate 2-O-sulphotranserase (HS2ST) is a target for small molecule protein kinase inhibitors

2018 ◽  
Author(s):  
Dominic P Byrne ◽  
Yong Li ◽  
Krithika Ramakrishnan ◽  
Igor L Barsukov ◽  
Edwin A Yates ◽  
...  
Keyword(s):  
Protein Kinase ◽  
Small Molecule ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Heparan Sulphate ◽  
Protein Kinase Inhibitors ◽  
Fluorescent Substrate ◽  
Shift Analysis ◽  
In Cells

ABSTRACTSulphation of carbohydrate residues occurs on a variety of glycans destined for secretion, and this modification is essential for efficient matrix-based signal transduction. Heparan sulphate (HS) glycosaminoglycans control physiological functions ranging from blood coagulation to cell proliferation. HS biosynthesis involves membrane-bound Golgi sulphotransferases, including heparan sulphate 2-O-sulphotransferase (HS2ST), which transfers sulphate from the co-factor PAPS (3’-phosphoadenosine 5’-phosphosulphate) to the 2-Oposition of α-L-iduronate in the maturing oligosaccharide chain. The current lack of simple non-radioactive enzyme assays that can be used to quantify the levels of carbohydrate sulphation hampers kinetic analysis of this process and the discovery of HS2ST inhibitors. In this paper, we describe a new procedure for thermal shift analysis of purified HS2ST. Using this approach, we quantify HS2ST-catalyzed oligosaccharide sulphation using a novel synthetic fluorescent substrate and screen the Published Kinase Inhibitor Set (PKIS), to evaluate compounds that inhibit catalysis. We report the susceptibility of HS2ST to a variety of cell permeable compoundsin vitro, including polyanionic polar molecules, the protein kinase inhibitor rottlerin and oxindole-based RAF kinase inhibitors. In a related study, published back-to-back with this article, we demonstrate that Tyrosyl Protein Sulpho Tranferases (TPSTs) are also inhibited by a variety of protein kinase inhibitors. We propose that appropriately validated small molecule compounds could become new tools for rapid inhibition of glycan (and protein) sulphation in cells, and that protein kinase inhibitors might be repurposed or redesigned for the specific inhibition of HS2ST.SUMMARY STATEMENTWe report that HS2ST, which is a PAPS-dependent glycan sulphotransferase, can be assayed using a variety of novel biochemical procedures, including a non-radioactive enzyme-based assay that detects glycan substrate sulphation in real time. HS2ST activity can be inhibited by different classes of compounds, including known protein kinase inhibitors, suggesting new approaches to evaluate the roles of HS2ST-dependent sulphation with small molecules in cells.

scholarly journals A novel graph convolutional neural network for predicting interaction sites on protein kinase inhibitors in phosphorylation

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Feiqi Wang ◽  
Yun-Ti Chen ◽  
Jinn-Moon Yang ◽  
Tatsuya Akutsu
Keyword(s):  
Neural Network ◽  
Protein Kinase ◽  
Convolutional Neural Network ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Protein Kinase Inhibitors ◽  
Superior Performance ◽  
Interaction Sites ◽  
Mechanism Research ◽  
Ablation Study

AbstractProtein kinase-inhibitor interactions are key to the phosphorylation of proteins involved in cell proliferation, differentiation, and apoptosis, which shows the importance of binding mechanism research and kinase inhibitor design. In this study, a novel machine learning module (i.e., the WL Box) was designed and assembled to the Prediction of Interaction Sites of Protein Kinase Inhibitors (PISPKI) model, which is a graph convolutional neural network (GCN) to predict the interaction sites of protein kinase inhibitors. The WL Box is a novel module based on the well-known Weisfeiler-Lehman algorithm, which assembles multiple switch weights to effectively compute graph features. The PISPKI model was evaluated by testing with shuffled datasets and ablation analysis using 11 kinase classes. The accuracy of the PISPKI model with the shuffled datasets varied from 83 to 86%, demonstrating superior performance compared to two baseline models. The effectiveness of the model was confirmed by testing with shuffled datasets. Furthermore, the performance of each component of the model was analyzed via the ablation study, which demonstrated that the WL Box module was critical. The code is available at https://github.com/feiqiwang/PISPKI.

scholarly journals Screening of Microbial Extracts for Anticancer Compounds Using Streptomyces Kinase Inhibitor Assay

2015 ◽  
Vol 10 (7) ◽  
pp. 1934578X1501000 ◽  
Author(s):  
Prashant Shanbhag ◽  
Sarita Bhave ◽  
Ashwini Vartak ◽  
Asha Kulkarni-Almeida ◽  
Girish Mahajan ◽  
...  
Keyword(s):  
Protein Kinase ◽  
Anticancer Agents ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Protein Kinase Inhibitors ◽  
Kinase Assay ◽  
Diffusion Method ◽  
Eukaryotic Protein Kinase ◽  
Eukaryotic Protein ◽  
Microbial Extracts

Eukaryotic kinases are known to play an important role in signal transduction pathways by phosphorylating their respective substrates. Abnormal phosphorylations by these kinases have resulted in diseases. Hence inhibitors of kinases are of considerable pharmaceutical interest for a wide variety of disease targets, especially cancers. A number of reports have been published which indicate that eukaryotic-like kinases may complement two-component kinase systems in several bacteria. In Streptomyces sp. such kinases have been found to have a role in formation of aerial hyphae, spores, pigmentation & even in antibiotic production in some strains. Eukaryotic kinase inhibitors are seen to inhibit formation of aerial mycelia in Streptomyces without inhibiting vegetative mycelia. This property has been used to design an assay to screen for eukaryotic kinase inhibitors. The assay involves testing of compounds against Streptomyces 85E ATCC 55824 using agar well diffusion method. Inhibitors of kinases give rise to “bald” colonies where aerial mycelia and sporulation inhibition is seen. The assay has been standardized using known eukaryotic protein kinase inhibiting anticancer agents like AG-490, AG-1295, AG-1478, Flavopiridol and Imatinib as positive controls, at a concentration ranging from 10 μg/well to 100 μg/well. Anti-infective compounds which are not reported to inhibit eukaryotic protein kinases were used as negative controls. A number of microbial cultures have been screened for novel eukaryotic protein kinase inhibitors. Further these microbial extracts were tested in various cancer cell lines like Panc1, HCT116, Calu1, ACHN and H460 at a concentration of 10 μg/mL/ well. The anticancer data was seen correlating well with the Streptomyces kinase assay thus validating the assay.

scholarly journals Comparative Assessment of Protein Kinase Inhibitors in Public Databases and in PKIDB

Molecules ◽  
2020 ◽  
Vol 25 (14) ◽  
pp. 3226 ◽  
Author(s):  
Colin Bournez ◽  
Fabrice Carles ◽  
Gautier Peyrat ◽  
Samia Aci-Sèche ◽  
Stéphane Bourg ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Protein Kinase ◽  
Protein Kinases ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Chemical Space ◽  
Principal Component ◽  
Great Majority ◽  
Protein Kinase Inhibitors ◽  
Principal Moments Of Inertia

Since the first approval of a protein kinase inhibitor (PKI) by the Food and Drug Administration (FDA) in 2001, 55 new PKIs have reached the market, and many inhibitors are currently being evaluated in clinical trials. This is a clear indication that protein kinases still represent major drug targets for the pharmaceutical industry. In a previous work, we have introduced PKIDB, a publicly available database, gathering PKIs that have already been approved (Phase 4), as well as those currently in clinical trials (Phases 0 to 3). This database is updated frequently, and an analysis of the new data is presented here. In addition, we compared the set of PKIs present in PKIDB with the PKIs in early preclinical studies found in ChEMBL, the largest publicly available chemical database. For each dataset, the distribution of physicochemical descriptors related to drug-likeness is presented. From these results, updated guidelines to prioritize compounds for targeting protein kinases are proposed. The results of a principal component analysis (PCA) show that the PKIDB dataset is fully encompassed within all PKIs found in the public database. This observation is reinforced by a principal moments of inertia (PMI) analysis of all molecules. Interestingly, we notice that PKIs in clinical trials tend to explore new 3D chemical space. While a great majority of PKIs is located on the area of “flatland”, we find few compounds exploring the 3D structural space. Finally, a scaffold diversity analysis of the two datasets, based on frequency counts was performed. The results give insight into the chemical space of PKIs, and can guide researchers to reach out new unexplored areas. PKIDB is freely accessible from the following website: http://www.icoa.fr/pkidb.

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