1. INTRODUCTION
Cisplatin is an effective chemotherapeutic agent widely used for the treatment of a variety of malignancies, including head and neck, testicular, ovarian, cervical, and bladder cancers. Cisplatin is primarily eliminated by the kidneys through tubular secretion and glomerular filtration, and consequently accumulates in the kidneys to cause kidney injury. Cisplatin-induced nephrotoxicity presents as acute kidney injury (AKI) in approximately one-third of patients receiving cisplatin. AKI is characterized as a rapid decline in kidney function and has been associated with increased risk for chronic kidney disease, major cardiovascular events, and mortality. Clinical diagnosis of AKI is based on increases in serum creatinine (SCr) concentrations or a decrease in urine output. However, serum creatinine and decreased urine output are markers of functional impairment, only manifesting after significant kidney injury and impairment of glomerular filtration. Biomarkers for earlier detection or prediction of cisplatin-induced nephrotoxicity are needed to guide cisplatin therapy, improve AKI prognosis, and allow for development of nephroprotective interventions.
Novel markers for the early detection of AKI are currently under investigation, including neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, cystatin C, tissue inhibitor of metalloproteinase 2, and insulin-like growth factor binding protein 7. However, these markers are not necessarily specific to AKI, do not allow for discrimination of AKI etiology, and do not predict a patient’s predisposition to developing cisplatin-induced nephrotoxicity. There is consensus that a combination of kidney function or damage markers should be utilized to not only diagnose AKI, but to also discriminate AKI etiology, assess severity, and evaluate the prognosis of AKI.
In this study, we utilized untargeted metabolomics to analyze urine and serum samples from a cohort of adult head and neck cancer patients. We aimed to identify both early diagnostic markers of cisplatin-induced AKI, as well as predictive markers of patient predisposition to cisplatin-induced AKI. Although untargeted metabolomics has been used in rodent models of cisplatin-induced AKI, to our knowledge, our study is the first to use untargeted metabolomics in a cohort of patients receiving cisplatin therapy.