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.