Discovery of preventive drugs for cisplatin-induced acute kidney injury using big data analysis

Cisplatin is effective against many types of carcinoma. However, a high rate of renal damage is a clinical problem. Thus, there is a need to establish a method to prevent it. Although various compounds have been reported to be effective against cisplatin-induced renal injury, there are no examples of their clinical application. Therefore, we attempted to search for prophylactic agents with a high potential for clinical application. We used Cascade Eye to identify genes that are altered during cisplatin-induced renal injury, Library of Integrated Network-based Cellular Signatures (LINCS) to identify drugs that inhibit changes in gene expression, and a large database of spontaneous adverse drug reaction reports to identify drugs that could prevent cisplatin-induced kidney injury in clinical practice. In total, 10 candidate drugs were identified. Using the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS), we identified drugs that reduce cisplatin-induced kidney injury. Fenofibrate was selected as a candidate drug to prevent cisplatin-induced kidney injury based on the FAERS analysis. A model was used to evaluate the efficacy of fenofibrate against cisplatin-induced renal injury. Studies using HK2 cells and mouse models showed that fenofibrate significantly inhibited cisplatin-induced renal injury but did not inhibit the antitumor effect of cisplatin. Fenofibrate is a candidate prophylactic drug with high clinical applicability for cisplatin-induced renal injury. Analysis of data from multiple big databases will improve the search for novel prophylactic drugs with high clinical applicability. For the practical application of these findings, evaluation in prospective controlled trials is necessary.

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本論文は，著者Masaya Kandaの学位論文として提出され，学位審査・授与の対象となっている。

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