Abstract: PO0234
Quantitative Prediction of Cisplatin-Induced AKI Using RENAsym, a Mechanistic Quantitative Systems Toxicology Model, and Renal Proximal Tubule Epithelial Cell In Vitro Assays
Session Information
- AKI Mechanisms - 3
October 22, 2020 | Location: On-Demand
Abstract Time: 10:00 AM - 12:00 PM
Category: Acute Kidney Injury
- 103 AKI: Mechanisms
Authors
- Gebremichael, Yeshitila, DILIsym Services Inc., a Simulations Plus Company, Durham, North Carolina, United States
- Hamzavi, Nader, DILIsym Services Inc., a Simulations Plus Company, Durham, North Carolina, United States
- Woodhead, Jeffrey L., DILIsym Services Inc., a Simulations Plus Company, Durham, North Carolina, United States
- Tallapaka, Shailendra, DILIsym Services Inc., a Simulations Plus Company, Durham, North Carolina, United States
- Siler, Scott Q., DILIsym Services Inc., a Simulations Plus Company, Durham, North Carolina, United States
- Howell, Brett A., DILIsym Services Inc., a Simulations Plus Company, Durham, North Carolina, United States
Background
Nephrotoxic drugs like cisplatin cause acute kidney injury (AKI) through complex cellular mechanisms that include mitochondrial dysfunction, oxidative stress, and immune mediated injury pathways. However, quantitative prediction of the underlying toxicity mechanisms remains a challenge. Quantitative system toxicology (QST) modeling offers a promise for quantitative description of toxicity mechanisms leading to drug-induced AKI. We developed a QST model of cisplatin induced AKI using in vitro assays to characterize key cellular injury mechanisms.
Methods
RENAsym was used to quantify cisplatin induced AKI. The model represents aspects of renal proximal tubule epithelial cells (RPTEC) including cell life cycle and death pathways, bioenergetics, immune signaling pathways and biomarker responses. In vitro data related to cisplatin mitochondrial toxicity and oxidative stress generation were measured using RPTEC assays incubated with cisplatin (Cyprotex Inc.). To quantify cisplatin-induced mitochondrial dysfunction, oxygen consumption rate (OCR) was measured using the Seahorse XF analyzer. Cisplatin-induced oxidative stress was measured using high content imaging (HCI).
Results
The Seahorse study shows substantial OCR decline at 24 hours, suggesting cisplatin-induced electron transport chain (ETC) inhibition. Similarly, HCI reveals significant oxidative stress elevation after 9 days. Toxicity parameters for cisplatin-induced mitochondrial dysfunction and oxidative stress mechanisms were determined using the in vitro data. Simulations predict dose-dependent cisplatin toxicity as quantified by elevations in αGST, a biomarker that marks RPTEC death. A simulated single high dose of 533 mg/m2 i.v. cisplatin results in 14-fold change in αGST, while a simulated clinical dose of 100 mg/m2 shows 7-fold increase. The 100 mg/m2 result is in qualitative agreement with 3.4-fold change observed in a clinical study where patients administered 100 mg/m2 i.v. cisplatin exhibited 20% incidence of AKI (Ummer. 2012, IJBBB).
Conclusion
RENAsym simulations predicted dose-dependent cisplatin-induced AKI that is in qualitative agreement with clinical data. RENAsym shows promise in providing a unique tool for drug-induced AKI prediction.
Funding
- NIDDK Support