CORAL Models for Drug-Induced Nephrotoxicity.
Ontology highlight
ABSTRACT:
SUBMITTER: Toropov AA
PROVIDER: S-EPMC10142465 | biostudies-literature | 2023 Mar
REPOSITORIES: biostudies-literature
Publications
CORAL Models for Drug-Induced Nephrotoxicity.
Toropov Andrey A AA Barnes Devon A DA Toropova Alla P AP Roncaglioni Alessandra A Irvine Alasdair R AR Masereeuw Rosalinde R Benfenati Emilio E
Toxics 20230323 4
Drug-induced nephrotoxicity is a major cause of kidney dysfunction with potentially fatal consequences. The poor prediction of clinical responses based on preclinical research hampers the development of new pharmaceuticals. This emphasises the need for new methods for earlier and more accurate diagnosis to avoid drug-induced kidney injuries. Computational predictions of drug-induced nephrotoxicity are an attractive approach to facilitate such an assessment and such models could serve as robust a ...[more]
Similar Datasets
Project description:Nephrotoxicity induced by antimicrobial or anticancer drugs is a serious clinical problem. Megalin, an endocytic receptor expressed at the apical membranes of proximal tubules, mediates the nephrotoxicity of aminoglycosides and colistin, key antimicrobials for multidrug-resistant organisms. The mechanisms underlying the nephrotoxicity induced by vancomycin, an antimicrobial for methicillin-resistant Staphylococcus aureus, and cisplatin, an important anticancer drug, are unknown, although the nephrotoxicity of these drugs and gentamicin, an aminoglycoside, is suppressed experimentally with cilastatin. In the clinical setting, cilastatin has been used safely to suppress dehydropeptidase-I-mediated renal metabolism of imipenem, a carbapenem antimicrobial, and thereby limit tubular injury. Here, we tested the hypothesis that cilastatin also blocks megalin-mediated uptake of vancomycin, cisplatin, colistin, and aminoglycosides, thereby limiting the nephrotoxicity of these drugs. Quartz crystal microbalance analysis showed that megalin also binds vancomycin and cisplatin and that cilastatin competes with megalin for binding to gentamicin, colistin, vancomycin, and cisplatin. In kidney-specific mosaic megalin knockout mice treated with colistin, vancomycin, or cisplatin, the megalin-replete proximal tubule epithelial cells exhibited signs of injury, whereas the megalin-deficient cells did not. Furthermore, concomitant cilastatin administration suppressed colistin-induced nephrotoxicity in C57BL/6J mice. Notably, cilastatin did not inhibit the antibacterial activity of gentamicin, colistin, or vancomycin in vitro, just as cilastatin did not affect the anticancer activity of cisplatin in previous studies. In conclusion, megalin blockade with cilastatin efficiently suppresses the nephrotoxicity induced by gentamicin, colistin, vancomycin, or cisplatin. Cilastatin may be a promising agent for inhibiting various forms of drug-induced nephrotoxicity mediated via megalin in the clinical setting.
| S-EPMC5461786 | biostudies-literature
Project description:Improved biomarkers of acute nephrotoxicity are coveted by the drug development industry, regulatory agencies, and clinicians. In an effort to identify such biomarkers, urinary peptide profiles of rats treated with two different nephrotoxins were investigated. 493 marker candidates were defined that showed a significant response to cis-platin comparing a cis-platin treated cohort to controls. Next, urine samples from rats that received three consecutive daily doses of 150 or 300 mg/kg gentamicin were examined. 557 potential biomarkers were initially identified; 108 of these gentamicin-response markers showed a clear temporal response to treatment. 39 of the cisplatin-response markers also displayed a clear response to gentamicin. Of the combined 147 peptides, 101 were similarly regulated by gentamicin or cis-platin and 54 could be identified by tandem mass spectrometry. Most were collagen type I and type III fragments up-regulated in response to gentamicin treatment. Based on these peptides, classification models were generated and validated in a longitudinal study. In agreement with histopathology, the observed changes in classification scores were transient, initiated after the first dose, and generally persistent over a period of 10-20 days before returning to control levels. The data support the hypothesis that gentamicin-induced renal toxicity up-regulates protease activity, resulting in an increase in several specific urinary collagen fragments. Urinary proteomic biomarkers identified here, especially those common to both nephrotoxins, may serve as a valuable tool to investigate potential new drug candidates for the risk of nephrotoxicity.
| S-EPMC3324487 | biostudies-literature
Project description:The kidney plays a critical role in fluid homeostasis, glucose control, and drug excretion. Loss of kidney function due to drug-induced nephrotoxicity affects over 20% of the adult population. The kidney proximal tubule is a complex vascularized structure that is particularly vulnerable to drug-induced nephrotoxicity. Here, we introduce a model of vascularized human kidney spheroids with integrated tissue-embedded microsensors for oxygen, glucose, lactate, and glutamine, providing real-time assessment of cellular metabolism. Our model shows that both the immunosuppressive drug cyclosporine and the anticancer drug cisplatin disrupt proximal tubule polarity at subtoxic concentrations, leading to glucose accumulation and lipotoxicity. Impeding glucose reabsorption using glucose transport inhibitors blocked cyclosporine and cisplatin toxicity by 1000- to 3-fold, respectively. Retrospective study of 247 patients who were diagnosed with kidney damage receiving cyclosporine or cisplatin in combination with the sodium-glucose cotransporter-2 (SGLT2) inhibitor empagliflozin showed significant (P < 0.001) improvement of kidney function, as well as reduction in creatinine and uric acid, markers of kidney damage. These results demonstrate the potential of sensor-integrated kidney-on-chip platforms to elucidate mechanisms of action and rapidly reformulate effective therapeutic solutions, increasing drug safety and reducing the cost of clinical and commercial failures.
| S-EPMC8897043 | biostudies-literature
Project description:The need is critical and urgent for a real-time, highly specific, and sensitive acute kidney injury biomarker. This study sought to establish a sensitive and specific Miox-NanoLuc transgenic mouse for early detection of drug-induced nephrotoxicity. We generated Miox-NanoLuc transgenic mice with kidney-specific NanoLuc overexpression. Our data showed that Miox-NanoLuc-produced luminescence was kidney-specific and had good stability at room temperature, 4 °C, - 20 °C, and repeated freeze-thaw cycles. Serum levels of BUN and creatinine were significantly increased at day 2 or 3 in cisplatin-treated mice and at day 5 in aristolochic acid (AAI)-treated mice. Particularly, the serum and urine Miox-NanoLuc luminescence levels were significantly increased at day 1 in cisplatin-treated mice and at day 3 in AAI-treated mice. Renal pathological analysis showed that the kidney sections of cisplatin-treated mice at day 5 and AAI-treated mice at day 13 showed cytolysis and marked vacuolization of tubular cells. In conclusion, we developed a new platform to early quantify drug-induced nephrotoxicity before serum BUN and creatinine levels increased and pathological tubular cell injury occurred. This model may serve as an early detection for drug- and food-induced nephrotoxicity and as an animal model to investigate tubular cell injury.
| S-EPMC7428004 | biostudies-literature
Project description:Chemotherapy drug-induced nephrotoxicity limits clinical applications for treating cancers. Pyroptosis, a newly discovered programmed cell death, was recently reported to be associated with kidney diseases. However, the role of pyroptosis in chemotherapeutic drug-induced nephrotoxicity has not been fully clarified. Herein, we demonstrate that the chemotherapeutic drug cisplatin or doxorubicin, induces the cleavage of gasdermin E (GSDME) in cultured human renal tubular epithelial cells, in a time- and concentration-dependent manner. Morphologically, cisplatin- or doxorubicin-treated renal tubular epithelial cells exhibit large bubbles emerging from the cell membrane. Furthermore, activation of caspase 3, not caspase 9, is associated with GSDME cleavage in cisplatin- or doxorubicin-treated renal tubular epithelial cells. Meanwhile, silencing GSDME alleviates cisplatin- or doxorubicin-induced HK-2 cell pyroptosis by increasing cell viability and decreasing LDH release. In addition, treatment with Ac-DMLD-CMK, a polypeptide targeting mouse caspase 3-Gsdme signaling, inhibits caspase 3 and Gsdme activation, alleviates the deterioration of kidney function, attenuates renal tubular epithelial cell injury, and reduces inflammatory cytokine secretion in vivo. Specifically, GSDME cleavage depends on ERK and JNK signaling. NAC, a reactive oxygen species (ROS) inhibitor, reduces GSDME cleavage through JNK signaling in human renal tubular epithelial cells. Thus, we speculate that renal tubular epithelial cell pyroptosis induced by chemotherapy drugs is mediated by ROS-JNK-caspase 3-GSDME signaling, implying that therapies targeting GSDME may prove efficacious in overcoming chemotherapeutic drug-induced nephrotoxicity.
| S-EPMC7884686 | biostudies-literature
Project description:Drug induced nephrotoxicity is a major clinical challenge, and it is always associated with higher costs for the pharmaceutical industry and due to detection during the late stages of drug development. It is desirable for improving the health outcomes for patients to distinguish nephrotoxic structures at an early stage of drug development. In this study, we focused on in silico prediction and insights into the structural basis of drug induced nephrotoxicity, based on reliable data on human nephrotoxicity. We collected 565 diverse chemical structures, including 287 nephrotoxic drugs on humans in the real world, and 278 non-nephrotoxic approved drugs. Several different machine learning and deep learning algorithms were employed for in silico model building. Then, a consensus model was developed based on three best individual models (RFR_QNPR, XGBOOST_QNPR, and CNF). The consensus model performed much better than individual models on internal validation and it achieved prediction accuracy of 86.24% external validation. The results of analysis of molecular properties differences between nephrotoxic and non-nephrotoxic structures indicated that several key molecular properties differ significantly, including molecular weight (MW), molecular polar surface area (MPSA), AlogP, number of hydrogen bond acceptors (nHBA), molecular solubility (LogS), the number of rotatable bonds (nRotB), and the number of aromatic rings (nAR). These molecular properties may be able to play an important part in the identification of nephrotoxic chemicals. Finally, 87 structural alerts for chemical nephrotoxicity were mined with f-score and positive rate analysis of substructures from Klekota-Roth fingerprint (KRFP). These structural alerts can well identify nephrotoxic drug structures in the data set. The in silico models and the structural alerts could be freely accessed via https://ochem.eu/article/140251 and http://www.sapredictor.cn, respectively. We hope the results should provide useful tools for early nephrotoxicity estimation in drug development.
| S-EPMC8785686 | biostudies-literature
Project description:The detection of acute kidney injury (AKI) and the monitoring of chronic kidney disease (CKD) is becoming more important in industrialized countries. Because of the direct relation of kidney damage to the increasing age of the population, as well as the connection to other diseases like diabetes mellitus and congestive heart failure, renal diseases/failure has increased in the last decades. In addition, drug-induced kidney injury, especially of patients in intensive care units, is very often a cause of AKI. The need for diagnostic tools to identify drug-induced nephrotoxicity has been emphasized by the ICH-regulated agencies. This has lead to multiple national and international projects focusing on the identification of novel biomarkers to enhance drug development. Several parameters related to AKI or CKD are known and have been used for several decades. Most of these markers deliver information only when renal damage is well established, as is the case for serum creatinine. The field of molecular toxicology has spawned new options of the detection of nephrotoxicity. These new developments lead to the identification of urinary protein biomarkers, including Kim-1, clusterin, osteopontin or RPA-1, and other transcriptional biomarkers which enable the earlier detection of AKI and deliver further information about the area of nephron damage or the underlying mechanism. These biomarkers were mainly identified and qualified in rat but also for humans, several biomarkers have been described and now have to be validated. This review will give an overview of traditional and novel tools for the detection of renal damage.
| S-EPMC3231866 | biostudies-literature
Project description:BackgroundDrug-induced nephrotoxicity causes acute kidney injury and chronic kidney diseases, and is a major reason for late-stage failures in the clinical trials of new drugs. Therefore, early, pre-clinical prediction of nephrotoxicity could help to prioritize drug candidates for further evaluations, and increase the success rates of clinical trials. Recently, an in vitro model for predicting renal-proximal-tubular-cell (PTC) toxicity based on the expression levels of two inflammatory markers, interleukin (IL)-6 and -8, has been described. However, this and other existing models usually use linear and manually determined thresholds to predict nephrotoxicity. Automated machine learning algorithms may improve these models, and produce more accurate and unbiased predictions.ResultsHere, we report a systematic comparison of the performances of four supervised classifiers, namely random forest, support vector machine, k-nearest-neighbor and naive Bayes classifiers, in predicting PTC toxicity based on IL-6 and -8 expression levels. Using a dataset of human primary PTCs treated with 41 well-characterized compounds that are toxic or not toxic to PTC, we found that random forest classifiers have the highest cross-validated classification performance (mean balanced accuracy = 87.8%, sensitivity = 89.4%, and specificity = 85.9%). Furthermore, we also found that IL-8 is more predictive than IL-6, but a combination of both markers gives higher classification accuracy. Finally, we also show that random forest classifiers trained automatically on the whole dataset have higher mean balanced accuracy than a previous threshold-based classifier constructed for the same dataset (99.3% vs. 80.7%).ConclusionsOur results suggest that a random forest classifier can be used to automatically predict drug-induced PTC toxicity based on the expression levels of IL-6 and -8.
| S-EPMC4290648 | biostudies-literature
Project description:Aminoglycoside antibiotics, in particular gentamicin and tobramycin, are still commonly used in paediatric clinical practice. These drugs cause nephrotoxicity, which particularly affects the proximal tubule epithelial cells due to selective endocytosis and accumulation of aminoglycosides via the multi-ligand receptor megalin. Recent epidemiological studies, using more widely accepted definitions of acute kidney injury (AKI), have suggested that AKI may occur in between 20 and 33 % of children exposed to aminoglycosides. A consensus set of phenotypic criteria for aminoglycoside-induced nephrotoxicity have recently been published. These are specifically designed to provide robust phenotyping for pharmacogenomic studies, but they can pave the way for standardisation for all clinical studies. Novel renal biomarkers, in particular kidney injury molecule-1, identify aminoglycoside-induced proximal tubular injury earlier than traditional markers and have shown promise in observational studies. Further studies need to demonstrate a clear association with clinically relevant outcomes to inform translation into clinical practice. Extended interval dosing of aminoglycosides results in a reduction in nephrotoxicity, but its use needs to become more widespread. Inhibition of megalin-mediated endocytosis by statins represents a novel approach to the prevention of aminoglycoside-induced nephrotoxicity which is currently being evaluated in a clinical trial. Recommendations for future directions are provided.
| S-EPMC5624973 | biostudies-literature
Project description:Cisplatin is a widely used cancer therapy drug that unfortunately has major side effects in normal tissues, notably nephrotoxicity in kidneys. Despite intensive research, the mechanism of cisplatin-induced nephrotoxicity remains unclear, and renoprotective approaches during cisplatin-based chemotherapy are lacking. Here we have identified PKCδ as a critical regulator of cisplatin nephrotoxicity, which can be effectively targeted for renoprotection during chemotherapy. We showed that early during cisplatin nephrotoxicity, Src interacted with, phosphorylated, and activated PKCδ in mouse kidney lysates. After activation, PKCδ regulated MAPKs, but not p53, to induce renal cell apoptosis. Thus, inhibition of PKCδ pharmacologically or genetically attenuated kidney cell apoptosis and tissue damage, preserving renal function during cisplatin treatment. Conversely, inhibition of PKCδ enhanced cisplatin-induced cell death in multiple cancer cell lines and, remarkably, enhanced the chemotherapeutic effects of cisplatin in several xenograft and syngeneic mouse tumor models while protecting kidneys from nephrotoxicity. Together these results demonstrate a role of PKCδ in cisplatin nephrotoxicity and support targeting PKCδ as an effective strategy for renoprotection during cisplatin-based cancer therapy.
| S-EPMC3223835 | biostudies-literature