Nanocurcumin preserves kidney function and haematology parameters in DMBA-induced ovarian cancer treated with cisplatin via its antioxidative and anti-inflammatory effect in rats

CONTEXT

Cisplatin, as a first-line treatment for ovarian cancer, is associated with debilitating adverse effects, including nephrotoxic and haematotoxic effects.

OBJECTIVE

This study determines whether nanocurcumin, combined with cisplatin, would give additional benefit to kidney function and haematological parameters in rats with ovarian cancer.

MATERIALS AND METHODS

Twenty-five Wistar rats were divided into five untreated rats and 20-dimethylbenz(a)anthracene (DMBA)-induced ovarian cancer rats. The 20 ovarian cancer rats were divided into four treatment groups: vehicle, cisplatin, cisplatin-curcumin, and cisplatin-nanocurcumin. Cisplatin was given at the dose of 4 mg/kg BW once weekly, while curcumin or nanocurcumin was administered at 100 mg/kg BW daily for four weeks. At the end of treatment, we analysed kidney function, haematological parameters, and inflammatory and oxidative stress markers from plasma.

RESULTS

Nanocurcumin alleviates the increase in kidney function markers and abnormalities in haematological indices in rats treated with cisplatin. Compared to cisplatin-treated rats, plasma urea levels decreased from 66.4 to 47.7 mg/dL, creatinine levels lowered from 0.87 to 0.82 mg/dL, and neutrophil gelatinase-associated lipocalin (NGAL) levels declined from 8.51 to 3.59 mIU/mg protein. Furthermore, the therapy increased glutathione activities (from 2.02 to 3.23 U/µL), reduced lipid peroxidation (from 0.54 to 0.45 nmol/mL), and decreased plasma TNF-α (from 270.6 to 217.8 pg/mL).

CONCLUSIONS

Cisplatin with nanocurcumin in an ovarian cancer rat model may provide additional benefits as a preventive agent against renal impairment and cisplatin-induced haematological toxicity. However, further research is required to prove that using nanocurcumin for a more extended time would not affect its anticancer properties.

Deep Learning in Toxicologic Pathology: A New Approach to Evaluate Rodent Retinal Atrophy

Quantification of retinal atrophy, caused by therapeutics and/or light, by manual measurement of retinal layers is labor intensive and time-consuming. In this study, we explored the role of deep learning (DL) in automating the assessment of retinal atrophy, particularly of the outer and inner nuclear layers, in rats. Herein, we report our experience creating and employing a hybrid approach, which combines conventional image processing and DL to quantify rodent retinal atrophy. Utilizing a DL approach based upon the VGG16 model architecture, models were trained, tested, and validated using 10,746 image patches scanned from whole slide images (WSIs) of hematoxylin-eosin stained rodent retina. The accuracy of this computational method was validated using pathologist annotated WSIs throughout and used to separately quantify the thickness of the outer and inner nuclear layers of the retina. Our results show that DL can facilitate the evaluation of therapeutic and/or light-induced atrophy, particularly of the outer retina, efficiently in rodents. In addition, this study provides a template which can be used to train, validate, and analyze the results of toxicologic pathology DL models across different animal species used in preclinical efficacy and safety studies.

Renal glycosuria as a novel early sign of colistin-induced kidney damage in mice

The polymyxin colistin represents a last-resort antibiotic for multidrug-resistant infections, but its use is limited by the frequent onset of acute drug-induced kidney injury (DIKI). It is essential to closely monitor kidney function prior to and during colistin treatment in order to pinpoint early signs of injury and minimize long-term renal dysfunction. To facilitate this, a mouse model of colistin-induced nephrotoxicity was used to uncover novel early markers of colistin-induced DIKI.

The polymyxin colistin represents a last-resort antibiotic for multidrug-resistant infections, but its use is limited by the frequent onset of acute drug-induced kidney injury (DIKI). It is essential to closely monitor kidney function prior to and during colistin treatment in order to pinpoint early signs of injury and minimize long-term renal dysfunction. To facilitate this, a mouse model of colistin-induced nephrotoxicity was used to uncover novel early markers of colistin-induced DIKI. Increased urinary levels of kidney injury molecule-1 (Kim-1) as well as glycosuria were observed in colistin-treated mice, where alterations of established clinical markers of acute kidney injury (serum creatinine and albuminuria) and emerging markers such as cystatin C were inaccurate in flagging renal damage as confirmed by histology. A direct interaction of colistin with renal glucose reabsorption was ruled out by a cis-inhibition assay in mouse brush border membrane vesicles (BBMV). Immunohistochemical examination and protein quantification by Western blotting showed a marked reduction in the protein amount of sodium-glucose transporter 2 (Sglt2), the main kidney glucose transporter, in renal tissue from colistin-treated mice in comparison to that in control animals. Consistently, BBMV isolated from treated mouse kidneys also showed a reduction in ex vivo glucose uptake compared to that in BBMV isolated from control kidneys. These findings support pathology observations of colistin-induced proximal tubule damage at the site of the brush border membrane, where Sglt2 is expressed, and open avenues for the study of glycosuria as a sensitive, specific, and accessible marker of DIKI during colistin therapy.

Translating New Science Into the Drug Review Process: The US FDA's Division of Applied Regulatory Science

In 2011, the US Food and drug Administration (FDA) developed a strategic plan for regulatory science that focuses on developing new tools, standards, and approaches to assess the safety, efficacy, quality, and performance of FDA-regulated products. In line with this, the Division of Applied Regulatory Science was created to move new science into the Center for Drug Evaluation and Research (CDER) review process and close the gap between scientific innovation and drug review. The Division, located in the Office of Clinical Pharmacology, is unique in that it performs mission-critical applied research and review across the translational research spectrum including in vitro and in vivo laboratory research, in silico computational modeling and informatics, and integrated clinical research covering clinical pharmacology, experimental medicine, and postmarket analyses. The Division collaborates with Offices throughout CDER, across the FDA, other government agencies, academia, and industry. The Division is able to rapidly form interdisciplinary teams of pharmacologists, biologists, chemists, computational scientists, and clinicians to respond to challenging regulatory questions for specific review issues and for longer-range projects requiring the development of predictive models, tools, and biomarkers to speed the development and regulatory evaluation of safe and effective drugs. This article reviews the Division's recent work and future directions, highlighting development and validation of biomarkers; novel humanized animal models; translational predictive safety combining in vitro, in silico, and in vivo clinical biomarkers; chemical and biomedical informatics tools for safety predictions; novel approaches to speed the development of complex generic drugs, biosimilars, and antibiotics; and precision medicine.

Impact of Pathologists and Evaluation Methods on Performance Assessment of the Kidney Injury Biomarker, Kim-1

Attempts to characterize and formally qualify biomarkers for regulatory purposes have raised questions about how histological and histopathological methods impact the evaluation of biomarker performance. A group of pathologists was asked to analyze digitized images prepared from rodent kidney injury experiments in studies designed to investigate sources of variability in histopathology evaluations. Study A maximized variability by using samples from diverse studies and providing minimal guidance, contextual information, or opportunities for pathologist interaction. Study B was designed to limit interpathologist variability by using more uniform image sets from different locations within the same kidneys and allowing pathologist selected interactions to discuss and identify the location and injury to be evaluated but without providing a lexicon or peer review. Results from this study suggest that differences between pathologists and across models of disease are the largest sources of variability in evaluations and that blind evaluations do not generally make a significant difference. Results of this study generally align with recommendations from both industry and the U.S. Food and Drug Administration and should inform future studies examining the effects of common lexicons and scoring criteria, peer review, and blind evaluations in the context of biomarker performance assessment.