WO2013188333A1 - Biomarkers related to nephrotoxicity and methods using the same - Google Patents

Abstract

Methods for identifying and evaluating biochemical entities useful as biomarkers for agent-induced nephrotoxicity, determining pre-disposition to agent-induced nephrotoxicity and monitoring nephrotoxicity are provided. Also provided are suites of small molecule entities as biomarkers for nephrotoxicity.

Description

BIOMARKERS RELATED TO NEPHROTOXICITY AND METHODS USING THE

SAME

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application No.

61/659,216, filed June 13, 2012, the entire contents of which is hereby incorporated by reference.

FIELD

[0002] The invention generally relates to biomarkers for nephrotoxicity and methods based on the same biomarkers.

BACKGROUND

[0003] There is a significant unmet clinical need in the oncology setting to prevent the occurrence of severe adverse events (SAE) in patients receiving a systemic chemotherapeutic regimen. The therapeutic efficacy of cytotoxic chemotherapeutic agents can be limited in practice by unacceptable levels of toxicity in a subset of patients. For example, cisplatin is one of the most effective chemotherapeutic agents available today and is used to treat a wide range of solid tumors (e.g., bladder cancer, testicular cancer, non-small cell lung cancer, etc.). However, cisplatin has well known nephrotoxic properties that are dose limiting and lead to severe nephrotoxic events in approximately 30-40% of patients, 10 to 20 days post-treatment. Cisplatin toxicity may result in serious loss of kidney function that, in turn, will significantly limit treatment options. A novel test that assesses and monitors a patient's renal tolerance for cisplatin would increase patients' safety during treatment with cisplatin, prevent cisplatin-induced kidney injury events and reduce the overall cost of treating chemotherapy-induced complications.

[0004] In the US, it is estimated that 70,500 patients were diagnosed with bladder cancer in 2010 and bladder cancer prevalence is estimated at 535,000 patients total (SEER's database). Approximately 70% of new patients present with superficial disease while 25% have muscle- invasive disease (T2- and higher stage) and roughly 5% have metastatic disease. Patients with T2-T4 bladder tumors face cystectomy with neoadjuvant and/or adjuvant chemotherapy and those with metastatic disease receive systemic chemotherapy. In bladder cancer, cisplatin is the main agent used to treat patients. It can be used as a part of different drug-combination regimens. Cisplatin-based regimens often use 21 or 28-day cycles (i.e. Gemcitabine-Cisplatin or GC regimen, Methotrexate-Vinblastin-Adriamycin-Cisplatin or MVAC regimen). Cisplatin can be administered intravenously at a dose of 70 mg/m² (range from 40 to 100 mg/m² depending on the regimen used). In the neoadjuvant/adjuvant setting, patients receive between 3 and 4 cycles of cisplatin-chemotherapy and in the metastatic setting, patients can receive 6 to 8 cycles and sometimes more as long as chemotherapy-induced toxicity is not preventing treatment.

[0005] In bladder cancer patients cisplatin is used in the neo-adjuvant (pre-cystectomy), adjuvant (post-surgery) and metastatic settings in 80%, 70% and 30% of patients, respectively. Three to 4 chemotherapy regimen cycles are used for patients in the neo-adjuvant and adjuvant settings and 6 to 8 cycles are used in the metastatic setting. As a conservative estimate, clinicians are likely to use a cisplatin tolerance test during patient work-up and then before each cycle of chemotherapy. At 85% accuracy a cisplatin tolerance test would be used in more than 80% of eligible patients.

[0006] A plasma or urine based test to monitor a patient's renal tolerance to cisplatin by measuring the levels of specific metabolites before each cycle of chemotherapy would be clinically useful. Such biomarkers could be used, in addition to current kidney function test results, by medical oncologists to assess the risk-benefit of cisplatin treatment in patients. The biomarkers could be used by medical oncologists treating bladder cancer patients and, more generally, any cancer patient (e.g., lung cancer, ovarian cancer) that may benefit from cisplatin- based therapy. The biomarkers could be used in, for example, a urine test that quantitatively measures a panel of biomarker metabolites whose levels are correlated with the risk of clinically relevant cisplatin-induced kidney injury. A test result for which the levels or the changes in these levels of metabolite biomarkers throughout therapy are within normal range would be indicative that a patient has a low risk of suffering a cisplatin-induced kidney SAE. A test result for which the levels or the changes in these levels of metabolite biomarkers throughout therapy are significantly but not excessively outside the normal range will be indicative that a patient has a moderate risk of suffering a cisplatin-induced kidney SAE. The treating clinician may elect to re-assess the risk-benefit of cisplatin treatment in this patient and change its management. A test result for which the levels of metabolite biomarkers or the changes in these levels throughout therapy are significantly and excessively outside the normal range will be indicative that a patient has a high risk of suffering a cisplatin-induced kidney SAE. Changes to the patient's management would be strongly advised (i.e. discontinue cisplatin, switch to carboplatin or other agents).

[0007] Current kidney function tests (e.g., serum creatinine, BUN, etc.) are late indicators of major toxicity/damage to the kidney. They do not enable clinicians to monitor precisely the progression in kidney injury until a major loss of function has occurred (i.e. more than 50% of total kidney function) and a new steady-state is reached. Serum creatinine (and eGFR) are used to diagnose an abnormal kidney function (chronic kidney disease - CKD) but their ability to assess the risk of kidney injury is limited (i.e. only if eGFR is below 60 units). In chronic kidney disease in the diabetes setting, serum creatinine above 120 μηιο1/1 has a sensitivity and specificity of 45.3% and 100%, respectively (based on a sample size of n=7596). The limitation of the current kidney function tests, demonstrates significant clinical need for a new diagnostic test for diagnosing or aiding in the diagnosis of nephrotoxicity.

SUMMARY

[0008] In one aspect, the present invention provides a method of determining susceptibility of a subject to nephrotoxicity, comprising analyzing a biological sample from a subject to determine the level(s) of one or more biomarkers for nephrotoxicity in the sample, where the one or more biomarkers are selected from Table 1 and comparing the level(s) of the one or more biomarkers in the sample to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels of the one or more biomarkers in order to determine whether the subject is susceptible to developing nephrotoxicity.

[0009] In another embodiment, the present invention provides a method of diagnosing drug-induced nephrotoxicity, comprising analyzing a biological sample from a subject to determine the level(s) of one or more biomarkers for nephrotoxicity in the sample, where the one or more biomarkers are selected from Tables 1 and/or 2 and comparing the level(s) of the one or more biomarkers in the sample to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels of the one or more biomarkers in order to diagnose whether the subject has nephrotoxicity. In an embodiment, the diagnosis of drug-induced nephrotoxicity is made earlier than possible with current tests.

[0010] In a further embodiment, the invention provides a method of diagnosing cisplatin- induced nephrotoxicity, comprising analyzing a biological sample from a subject to determine the level(s) of one or more biomarkers for nephrotoxicity in the sample, where the one or more biomarkers are selected from Tables 1 and/or 2 and comparing the level(s) of the one or more biomarkers in the sample to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels of the one or more biomarkers in order to diagnose whether the subject has nephrotoxicity. In an embodiment, the diagnosis of cisplatin-induced nephrotoxicity is made earlier than possible with current tests.

[0011] In another embodiment, the invention provides a method of monitoring the progression or regression of nephrotoxicity in a subject, the method comprising: analyzing the biological sample from the subject to determine the level(s) of one or more biomarkers, wherein the one or more biomarkers are selected from Tables 1, 2, and/or 4; and comparing the level(s) of the one or more biomarkers in the sample to nephrotoxicity-progression and/or nephrotoxicity- regression reference levels of the one or more biomarkers in order to monitor the progression or regression of nephrotoxicity in the subject.

[0012] In a further embodiment, a method of classifying a subject as having low susceptibility to nephrotoxicity, having intermediate susceptibility to nephrotoxicity, or having high susceptibility to nephrotoxicity, the method comprising: analyzing the biological sample from the subject to determine the level(s) of one or more biomarkers, wherein the one or more biomarkers are selected from Table 1; and comparing the level(s) of the one or more biomarkers in the sample to reference levels of the one or more biomarkers in order to classify the subject as having low susceptibility to nephrotoxicity or having high susceptibility to nephrotoxicity.

BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 is a flowchart of a medical algorithm for patient management prior to treatment using the metabolite biomarker test.

[0014] Figure 2 is a flowchart of a medical algorithm for patient management using the metabolite biomarker test.

[0015] Figure 3 is a chart illustrating the peak fold-change in serum creatinine for each subject. Figure 3 is associated with Examples 1, 3 and 4.

[0016] Figure 4 is a chart illustrating pair-wise analysis for gamma-glutamylleucine and butyrylcarnitine (two biomarkers for determining susceptibility to nephrotoxicity) in Example 2. [0017] Figure 5 is a chart illustrating pair-wise analysis for trigonelline and glutaroyl- carnitine (two biomarkers for determining susceptibility to nephrotoxity) in Example 2.

[0018] Figure 6A is a graphical illustration of line plots of the levels of biomarker metabolites 2-aminoadipate, adrosterone sulfate, gamma-glutamylphenylalanine and gamma- glutamylvaline measured in A 1 (broken line) vs. No AKI (solid line) subjects over time.

[0019] Figure 6B is a graphical illustration of line plots of the levels of biomarker metabolites histidine, N-acetylleucine, phenylacetylglutamine and threonine measured in AKI (broken line) vs. No AKI (solid line) subjects over time.

DETAILED DESCRIPTION

[0020] The present invention relates to biomarkers of nephrotoxicity, methods of determining susceptibility to nephrotoxicity, methods for diagnosis or aiding in diagnosis of nephrotoxicity, methods of monitoring progression/regression of nephrotoxicity, methods of classifying a subject according to the level of susceptibility to nephrotoxicity in a subject prior to drug treatment, methods of determining drug dosing, methods of determining susceptibility to nephrotoxicity following drug treatment.

[0021] Current blood tests for nephrotoxicity perform poorly for early detection of nephrotoxicity.

[0022] In one embodiment, groups (also referred to as "panels") of biomarker metabolites that can be used in a simple biological sample (e.g., blood, urine, etc.) test to predict pre-disposition to nephrotoxicity are identified using metabolomic analysis. Such biomarkers correlate with nephrotoxicity at a level similar to, or better than, or earlier than the correlation of serum creatinine (SCr) and/or blood urea nitrogen (BUN), the "gold standards" for determining kidney injury.

[0023] Prior to describing this invention in further detail, however, the following terms will be defined.

Definitions:

[0024] "Biomarker" means a compound, preferably a metabolite, that is differentially present (i.e., increased or decreased) in a biological sample from a subject or a group of subjects having a first phenotype (e.g., having a disease) as compared to a biological sample from a subject or group of subjects having a second phenotype (e.g., not having the disease). A biomarker may be differentially present at any level, but is generally present at a level that is increased by at least 5%, by at least 10%, by at least 15%, by at least 20%, by at least 25%, by at least 30%, by at least 35%, by at least 40%, by at least 45%, by at least 50%, by at least 55%, by at least 60%, by at least 65%, by at least 70%, by at least 75%, by at least 80%, by at least 85%, by at least 90%, by at least 95%, by at least 100%, by at least 1 10%, by at least 120%, by at least 130%, by at least 140%, by at least 150%, or more; or is generally present at a level that is decreased by at least 5%, by at least 10%, by at least 15%, by at least 20%, by at least 25%, by at least 30%, by at least 35%, by at least 40%, by at least 45%, by at least 50%, by at least 55%, by at least 60%, by at least 65%, by at least 70%, by at least 75%, by at least 80%, by at least 85%, by at least 90%, by at least 95%, or by 100% (i.e., absent). A biomarker is preferably differentially present at a level that is statistically significant (i.e., a p-value less than 0.05 and/or a q- value of less than 0.10 as determined using either Welch's T-test or Wilcoxon's rank-sum Test).

[0025] The "level" of one or more biomarkers means the absolute or relative amount or concentration of the biomarker measured in the sample.

[0026] "Sample" or "biological sample" means biological material isolated from a subject. The biological sample may contain any biological material suitable for detecting the desired biomarkers, and may comprise cellular and/or non-cellular material from the subject. The sample can be isolated from any suitable biological tissue or fluid such as, for example, kidney tissue, blood, blood plasma, urine, or cerebral spinal fluid (CSF).

[0027] "Subject" means any animal, but is preferably a mammal, such as, for example, a human, monkey, mouse, or rabbit.

[0028] A "reference level" of a biomarker means a level of the biomarker that is indicative of a particular disease state, phenotype, or lack thereof, as well as combinations of disease states, phenotypes, or lack thereof. A "positive" reference level of a biomarker means a level that is indicative of a particular disease state or phenotype. A "negative" reference level of a biomarker means a level that is indicative of a lack of a particular disease state or phenotype. For example, a "nephrotoxicity-positive reference level" of a biomarker means a level of a biomarker that is indicative of a positive diagnosis of nephrotoxicity in a subject, and a "nephrotoxicity-negative reference level" of a biomarker means a level of a biomarker that is indicative of a negative diagnosis of nephrotoxicity in a subject. A "reference level" of a biomarker may be an absolute or relative amount or concentration of the biomarker, a presence or absence of the biomarker, a range of amount or concentration of the biomarker, a minimum and/or maximum amount or concentration of the biomarker, a mean amount or concentration of the biomarker, and/or a median amount or concentration of the biomarker; and, in addition, "reference levels" of combinations of biomarkers may also be ratios of absolute or relative amounts or concentrations of two or more biomarkers with respect to each other. Appropriate positive and negative reference levels of biomarkers for a particular disease state, phenotype, or lack thereof may be determined by measuring levels of desired biomarkers in one or more appropriate subjects, and such reference levels may be tailored to specific populations of subjects (e.g., a reference level may be age-matched so that comparisons may be made between biomarker levels in samples from subjects of a certain age and reference levels for a particular disease state, phenotype, or lack thereof in a certain age group). Such reference levels may also be tailored to specific techniques that are used to measure levels of biomarkers in biological samples (e.g., LC-MS, GC-MS, etc.), where the levels of biomarkers may differ based on the specific technique that is used.

[0029] "Non-biomarker compound" means a compound that is not differentially present in a biological sample from a subject or a group of subjects having a first phenotype (e.g., having a first disease) as compared to a biological sample from a subject or group of subjects having a second phenotype (e.g., not having the first disease). Such non-biomarker compounds may, however, be biomarkers in a biological sample from a subject or a group of subjects having a third phenotype (e.g., having a second disease) as compared to the first phenotype (e.g., having the first disease) or the second phenotype (e.g., not having the first disease).

[0030] "Metabolite", or "small molecule", means organic and inorganic molecules which are present in a cell. The term does not include large macromolecules, such as large proteins (e.g., proteins with molecular weights over 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000), large nucleic acids (e.g., nucleic acids with molecular weights of over 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000), or large polysaccharides (e.g.,

polysaccharides with a molecular weights of over 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000). The small molecules of the cell are generally found free in solution in the cytoplasm or in other organelles, such as the mitochondria, where they form a pool of intermediates which can be metabolized further or used to generate large molecules, called macromolecules. The term "small molecules" includes signaling molecules and intermediates in the chemical reactions that transform energy derived from food into usable forms. Examples of small molecules include sugars, fatty acids, amino acids, nucleotides, intermediates formed during cellular processes, and other small molecules found within the cell.

[0031] "Metabolic profile", or "small molecule profile", means a complete or partial inventory of small molecules within a targeted cell, tissue, organ, organism, or fraction thereof (e.g., cellular compartment). The inventory may include the quantity and/or type of small molecules present. The "small molecule profile" may be determined using a single technique or multiple different techniques.

[0032] "Metabolome" means all of the small molecules present in a given organism.

[0033] "Nephrotoxicity" means the toxic effect of a substance on the kidneys that causes kidney injury. The kidney injury may be chronic or acute.

[0034] "Acute kidney injury" or "AKI" refers to a condition in which there is a rapid loss of kidney function. As used herein, AKI refers to kidney injury in subjects with at least a 50% increase in SCr following treatment. "AKI-50" refers to a group of subjects with AKI following treatment with an agent (e.g., cisplatin) as defined by at least a 50% increase but less than a 100% increase in SCr. "High" or "AKI-100" refers to a subgroup of AKI subjects with more severe AKI defined by at least a 100% increase in SCr. "No AKI" refers to a group of subjects without AKI following agent treatment (e.g., cisplatin) as defined by less than a 50% increase but more than a 10% increase in SCr. "Low" refers to a subgroup of No AKI subjects as defined by a 0-10% increase in SCr.

[0035] "Serum creatinine" or "SCr" refers to the measurement of creatinine in serum and is a well-recognized test used for determining AKI. This test is not able to determine subjects that are susceptible to nephrotoxicity and is not rapidly responsive in an acute injury situation.

[0036] "Blood urea nitrogen" or "BUN" refers to the measurement of the amount of nitrogen in the blood in the form of urea. BUN is a test used to measure kidney function and for determining AKI. This test is not able to determine subjects that are susceptible to

nephrotoxicity and is not rapidly responsive in an acute injury situation.

[0037] "Estimated glomerular filtration rate" or "eGFR" means a calculated estimate of the actual glomerular filtration rate based on serum creatinine concentration. eGFR is calculated to account for a subject's age, gender and race. Decreased glomerular filtration rate correlates with increased nephrotoxicity. Thus, eGFR is calculated when there is a risk for kidney damage such as when undergoing chemotherapy.

[0038] "Medical algorithm" or "algorithm" means a computation, formula, statistical analysis, nomogram or look-up table, useful in the clinical practice of healthcare. Medical algorithms include decision tree approaches to diagnosis (e.g., if biomarkers A, B, and C are elevated relative to a reference level, then the patient is diagnosed as having disease X). Non- limiting examples include: Statistical models such as mathematical equations or formulas comprised of measured biomarker levels in a biological sample from a subject; Calculators such as those for Body Mass Index (BMI); Flowcharts such as a binary decision tree as illustrated in Figure 1 or Figure 2; Look-up Tables such as those for looking up nutrition content of foodstuffs or reference levels for diagnostic biomarkers; Nomograms such as the Partin Index used for diagnosis and staging of prostate cancer.

I. Biomarkers

[0039] The biomarkers described herein were discovered using metabolomic profiling techniques. Such metabolomic profiling techniques are described in more detail in the Examples set forth below as well as in U.S. Patents No. 7,005,255 and 7,329,489 and U.S. Patent

7,635,556, U.S. Patent 7,682,783, U.S. Patent 7,682,784, and U.S. Patent 7,550,258, the entire contents of all of which are hereby incorporated herein by reference.

[0040] Generally, metabolic profiles were determined for biological samples from human subjects diagnosed with nephrotoxicity or human subjects not diagnosed with nephrotoxicity (control cases). The metabolic profile for biological samples from a subject having

nephrotoxicity was compared to the metabolic profile for biological samples from one or more other groups of subjects not having nephrotoxicity. Those molecules differentially present, including those molecules differentially present at a level that is statistically significant, in the metabolic profile of samples from subjects with nephrotoxicity as compared to another group (e.g., subjects not diagnosed with nephrotoxicity) were identified as biomarkers to distinguish those groups.

[0041] The biomarkers are discussed in more detail herein. The identified biomarkers may be used to distinguish subjects having nephrotoxicity vs. control subjects not diagnosed with nephrotoxicity (see Tables 1 , 2, and/or 4). II. Methods

A. Determining Susceptibility to Nephrotoxicity

[0042] The biomarkers identified herein may also be used to determine or aid in determining whether a subject not exhibiting symptoms of nephrotoxicity is predisposed to developing such condition. For example, the biomarkers may be used to determine whether a subject is predisposed to developing nephrotoxicity in response to drug treatment. An exemplary method of determining whether a subject having no symptoms of nephrotoxicity, is predisposed to developing nephrotoxicity comprises (1) analyzing a biological sample from a subject to determine the level(s) of one or more biomarkers listed in Table 1 in the sample and (2) comparing the level(s) of the one or more biomarkers in the sample to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels of the one or more biomarkers in order to determine whether the subject is predisposed to developing nephrotoxicity. For example, identifying biomarkers for nephrotoxicity prior to initiating drug treatment allows for the determination of whether a subject having no symptoms of nephrotoxicity is predisposed to developing drug-induced nephrotoxicity. In another example, the one or more biomarkers may be selected from the group consisting of the following biomarkers: gamma-glutamylleucine, gamma-glutamylisoleucine, glutaroyl-carnitine, butyrylcarnitine, trigonelline (N- methylnicotinate), N(2)-furoyl-glycine, xanthurenate, N-acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, homovanillate-sulfate,

hydroxyisovaleroyl-carnitine, Nl -methyl guanosine, phenol sulfate, 3-methylhistidine, gamma- glutamyltyrosine, mandelate, Cortisol, N-methyl proline, sucrose, homocitrate, 7,8- dihydroneopterin, 3,7-dimethylurate, 3-dehydrocarnitine, pantothenate, 1 -methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7 -methylxanthine, N- acetylarginine, gamma-glutamylvaline, gamma-glutamylthreonine, N6-acetyllysine, isobutyrylcarnitine, 3 -methyl-2-oxo valerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, N-acetylhistidine, dimethylarginine (SDMA + ADMA), glucono- 1 ,5 -lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, and pregnen-diol disulfate. The results of the method may be used along with other methods (or the results thereof) that are useful in the clinical determination of whether a subject is predisposed to developing nephrotoxicity.

[0043] Any suitable method may be used to analyze the biological sample in order to determine the level(s) of the one or more biomarkers in the sample. Suitable methods include chromatography (e.g., HPLC, gas chromatography, liquid chromatography), mass spectrometry (e.g., MS, MS-MS), enzyme-linked immunosorbent assay (ELISA), antibody linkage, other immunochemical techniques, and combinations thereof.

[0044] A method of determining or aiding in determining susceptibility to nephrotoxicity comprises measuring the levels of one or more of the biomarkers of Table 1. For example, the level(s) of one biomarker, two or more biomarkers, three or more biomarkers, four or more biomarkers, five or more biomarkers, six or more biomarkers, seven or more biomarkers, eight or more biomarkers, nine or more biomarkers, ten or more biomarkers, etc., including a combination of all of the biomarkers in Table 1 and combinations thereof or any fraction thereof, may be determined and used in such methods. Determining levels of combinations of the biomarkers may allow greater sensitivity and specificity determining predisposition to nephrotoxicity. For example, pair- wise analysis of two biomarkers or ratios of the levels of certain biomarkers (and non-biomarker compounds) in biological samples may allow greater sensitivity and specificity in determining predisposition to nephrotoxicity.

[0045] After the level(s) of the one or more biomarkers in the sample are determined, the level(s) are compared to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels in order to determine whether the subject is predisposed to developing nephrotoxicity. Levels of the one or more biomarkers in a sample corresponding to the nephrotoxicity-positive reference levels (e.g., levels that are the same as the reference levels, substantially the same as the reference levels, above and/or below the minimum and/or maximum of the reference levels, and/or within the range of the reference levels) are indicative of the subject being predisposed to developing nephrotoxicity. Levels of the one or more biomarkers in a sample corresponding to nephrotoxicity -negative reference levels (e.g., levels that are the same as the reference levels, substantially the same as the reference levels, above and/or below the minimum and/or maximum of the reference levels, and/or within the range of the reference levels) are indicative of the subject not being predisposed to developing nephrotoxicity. In addition, levels of the one or more biomarkers that are differentially present (especially at a level that is statistically significant) in the sample as compared to nephrotoxicity-negative reference levels may be indicative of the subject being predisposed to developing nephrotoxicity. Levels of the one or more biomarkers that are differentially present (especially at a level that is statistically significant) in the sample as compared to nephrotoxicity-positive reference levels are indicative of the subject not being predisposed to developing nephrotoxicity.

[0046] Example 2 illustrates using the biomarkers in a mathematical model to determine if a subject is predisposed to nephrotoxicity prior to receiving drug. The determination is based on measurement of certain biomarkers that determine the probability of whether a subject will progress to having drug-induced nephrotoxicity. The drug used in Example 2 is cisplatin.

[0047] The level(s) of the one or more biomarkers may be compared to nephrotoxicity- positive and/ nephrotoxicity-negative reference levels using various techniques, including a simple comparison (e.g., a manual comparison) of the level(s) of the one or more biomarkers in the biological sample to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels. The level(s) of the one or more biomarkers in the biological sample may also be compared to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels using one or more statistical analyses (e.g., t-test, Welch's T-test, Wilcoxon's rank sum test, random forest).

[0048] Such methods could be used to develop an algorithm to diagnose nephrotoxicity in cancer patients. For example, an algorithm could be developed based on a panel of urine metabolite biomarkers from Tables 1, 2, and/or 4 that can be useful to assess the renal tolerance of a patient to chemotherapy by measuring the levels of specific biomarker metabolites before initiation of chemotherapy. An exemplary chemotherapy drug is cisplatin. Using the results of the biomarker algorithm in combination with current kidney function test results (i.e., SCr, BUN) a medical oncologist could assess the risk-benefit ratio of chemotherapy treatment in the patient. The biomarker algorithm could be used by medical oncologists treating not only bladder cancer patients but, more generally, any cancer patient (e.g., lung cancer, ovarian cancer, etc.) that may benefit from chemotherapy.

[0049] For example, a clinical practice algorithm (flow chart) was developed to diagnose nephrotoxicity using the levels of a panel of biomarkers for nephrotoxicity identified in Tables 1, 2, and/or 4. Figure 1 illustrates an example of a clinical practice biomarker algorithm. In the algorithm, a metabolite biomarker test wherein the levels of biomarkers for nephrotoxity can be measured and analyzed and can be used to classify individuals by risk level and enable a clinician to treat them based on their results to reduce the risk of kidney severe adverse events is illustrated. In Figure 1, the following acronyms are used: SAE = Severe Adverse Event;

KFT=Kidney Function Test; and Biomarker Test = Metabolite Biomarker Test.

[0050] In the algorithm, levels of nephrotoxicity biomarkers that are normal at baseline are indicative that the patient has a low risk of suffering a chemotherapy-induced AKI or kidney severe adverse event (SAE).

[0051] A result for which the metabolite biomarker levels at baseline are significantly but not excessively above normal range would indicate that a patient has a moderate risk of suffering a chemotherapy-induced kidney injury (AKI) or kidney-SAE. Based on this result the treating clinician may elect to re-assess the risk-benefit ratio of the planned treatment regimen (e.g., therapeutic agent, dose) in this patient and change the patient's management. A result for which the levels of metabolite biomarkers at baseline are significantly and excessively above normal range would indicate that a patient has a high risk of suffering a chemotherapy-induced AKI or kidney SAE. Changes to the patient's management would be strongly advised (e.g., start with another agent; start with a lower dose, forgo chemotherapy treatment).

B. Diagnosis of Nephrotoxicity

[0052] The identification of biomarkers for nephrotoxicity can be used for the diagnosis of (or for aiding in the diagnosis of) nephrotoxicity in subjects presenting with one or more symptoms consistent with the presence of nephrotoxicity and/or undergoing drug regimens likely to result in nephrotoxicity (e.g., chemotherapy) and includes the initial diagnosis of

nephrotoxicity in a subject not previously identified as having nephrotoxicity and diagnosis of recurrence of nephrotoxicity in a subject previously treated for nephrotoxicity. It will be understood that the identified biomarkers can be used to diagnose or aid in diagnosing nephrotoxicity in any subject. In an exemplary method, diagnosing (or aiding in diagnosing) whether a subject has nephrotoxicity comprises (1) analyzing a biological sample from a subject to determine the level(s) of one or more biomarkers of nephrotoxicity in the sample and (2) comparing the level(s) of the one or more biomarkers in the sample to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels of the one or more biomarkers in order to diagnose (or aid in the diagnosis of) whether the subject has nephrotoxicity. The one or more biomarkers that are used are selected from Tables 1 , 2, and/or 4 and combinations thereof. In another example, the one or more biomarkers may be selected from the group consisting of the following biomarkers: gamma-glutamylleucine, gamma-glutamylisoleucine, glutaroyl-carnitine, butyrylcarnitine, trigonelline (N-methylnicotinate), N(2)-furoyl-glycine, xanthurenate, N-acetyl- beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, homovanillate-sulfate, hydroxyisovaleroyl-camitine, Nl-methylguanosine, phenol sulfate, 3- methylhistidine, gamma-glutamyltyrosine, mandelate, Cortisol, N-methyl proline, sucrose, homocitrate, 7,8-dihydroneopterin, 3,7-dimethylurate, 3-dehydrocarnitine, pantothenate, 1- methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7- methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma-glutamylthreonine, N6- acetyllysine, isobutyryl carnitine, 3 -methyl-2-oxo valerate, tyramine, homocitrulline,

tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, N-acetylhistidine, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, pregnen-diol disulfate, gulono 1,4-lactone, glucuronate, quinate, isocitrate, 1-methylxanthine, 1-methylurate, 21-hydroxypregnenoione-disulfate, beta- hydroxypyruvate, threonylleucine, alanylleucine, andro-steroid-monosulfate-2, 1- methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5- carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2- hydroxyisobutyrate, 1-methylhistidine, 4-acetamidobutanoate, N-acetlyisoleucine, citrate, N2- methylguanosine, xylose, stachydrine, N4-acetylcytidine, tryptophan betaine, N-acetylvaline, thymine, 1 -methylimidazoleacetate, quinolinate, Isobar: sorbitol, mannitol, pyridoxal, xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxyacetate). When such a method is used to aid in the diagnosis of nephrotoxicity, the results of the method may be used along with other methods (or the results thereof) useful in the clinical determination of whether a subject has nephrotoxicity. Methods useful in the clinical determination of whether a subject has nephrotoxicity are known in the art. For example, methods useful in the clinical determination of whether a subject has nephrotoxicity include, for example, SCr, BUN, and estimated glomerular filtration rate.

[0053] Any suitable method may be used to analyze the biological sample in order to determine the level(s) of the one or more biomarkers in the sample. Suitable methods include chromatography (e.g., HPLC, gas chromatography, liquid chromatography), mass spectrometry (e.g., MS, MS-MS), enzyme-linked immunosorbent assay (ELISA), antibody linkage, other immunochemical techniques, and combinations thereof.

[0054] The levels of one or more of the biomarkers of Tables 1 , 2 and/or 4 may be determined in the methods of diagnosing and methods of aiding in diagnosing whether a subject has nephrotoxicity. For example, the level(s) of one biomarker, two or more biomarkers, three or more biomarkers, four or more biomarkers, five or more biomarkers, six or more biomarkers, seven or more biomarkers, eight or more biomarkers, nine or more biomarkers, ten or more biomarkers, etc., including a combination of all of the biomarkers in Tables 1, 2 and/or 4 and combinations thereof or any fraction thereof, may be determined and used in such methods. Determining levels of combinations of the biomarkers may allow greater sensitivity and specificity in diagnosing nephrotoxicity and aiding in the diagnosis of nephrotoxicity. For example, ratios of the levels of certain biomarkers (and non-biomarker compounds) in biological samples may allow greater sensitivity and specificity in diagnosing nephrotoxicity and aiding in the diagnosis of nephrotoxicity.

[0055] After the level(s) of the one or more biomarkers in the sample are determined, the level(s) are compared to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels to aid in diagnosing or to diagnose whether the subject has nephrotoxicity. Levels of the one or more biomarkers in a sample matching the nephrotoxicity-positive reference levels (e.g., levels that are the same as the reference levels, substantially the same as the reference levels, above and/or below the minimum and/or maximum of the reference levels, and/or within the range of the reference levels) are indicative of a diagnosis of nephrotoxicity in the subject. Levels of the one or more biomarkers in a sample matching the nephrotoxicity-negative reference levels (e.g., levels that are the same as the reference levels, substantially the same as the reference levels, above and/or below the minimum and/or maximum of the reference levels, and/or within the range of the reference levels) are indicative of a diagnosis of no nephrotoxicity in the subject. In addition, levels of the one or more biomarkers that are differentially present (especially at a level that is statistically significant) in the sample as compared to nephrotoxicity-negative reference levels are indicative of a diagnosis of nephrotoxicity in the subject. Levels of the one or more biomarkers that are differentially present (especially at a level that is statistically significant) in the sample as compared to nephrotoxicity-positive reference levels are indicative of a diagnosis of no nephrotoxicity in the subject. [0056] The level(s) of the one or more biomarkers may be compared to nephrotoxicity- positive and/or nephrotoxicity-negative reference levels using various techniques, including a simple comparison (e.g., a manual comparison) of the level(s) of the one or more biomarkers in the biological sample to nephrotoxicity-positive and/or nephrotoxicity-negative reference levels. The level(s) of the one or more biomarkers in the biological sample may also be compared to nephrotoxicity-positive and/or nephiOtoxicity-negative reference levels using one or more statistical analyses (e.g., t-test, Welch's T-test, Wilcoxon's rank sum test, random forest).

[0057] In another example, the biomarkers disclosed herein may be used in an algorithm to determine the nephrotoxicity level of a subject. For example, using metabolomic analysis, panels of metabolites, such as those provided in Tables 1, 2 and 4 that can be used in a simple test to predict nephrotoxicity as measured by the "gold standard" of SCr, were identified. An example of a specific algorithm that can be used in any of the methods disclosed herein is disclosed in the Examples.

[0058] In another example, the identification of biomarkers for nephrotoxicity allows for the diagnosis of (or for aiding in the diagnosis of) nephrotoxicity before nephrotoxicity can be diagnosed using the current standards for determining nephrotoxicity (i.e., SCr and/or BUN measurements) in subjects presenting one or more symptoms of nephrotoxicity and/or undergoing drug regimens likely to result in nephrotoxicity (e.g., chemotherapy). For example, a method of diagnosing (or aiding in diagnosing) whether a subject has early nephrotoxicity comprises (1) analyzing a biological sample from a subject to determine the level(s) of one or more biomarkers of early nephrotoxicity selected from the biomarkers listed in Tables 1 and/or 2, in the sample and (2) comparing the level(s) of the one or more biomarkers in the sample to early nephrotoxicity-positive and/or early nephrotoxicity-negative reference levels of the one or more biomarkers in order to diagnose (or aid in the diagnosis of) whether the subject has early nephrotoxicity. In another example, the one or more biomarkers may be selected from the group consisting of the following biomarkers: gamma-glutamylleucine, gamma-glutamylisoleucine, glutaroyl-carnitine, butyrylcarnitine, trigonelline (N-methylnicotinate), N(2)-furoyl-glycine, xanthurenate, N-acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, homovanillate-sulfate, hydroxyisovaleroyl-carnitine, Nl-methylguanosine, phenol sulfate, 3-methylhistidine, gamma-glutamyltyrosine, mandelate, Cortisol, N-methyl proline, sucrose, homocitrate, 7,8-dihydroneopterin, 3,7-dimethylurate, 3-dehydrocarnitine, pantothenate, 1- methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7- methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma-glutamylthreonine, N6- acetyllysine, isobutyrylcarnitine, 3-methyl-2-oxovalerate, tyramine, homocitrulline,

tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, N-acetylhistidine, dimethylarginine (SDMA + ADMA), glucono-l ,5-lactone, 3-hydroxyhippurate, tiglyl carnitine,

2- methylbutyroylcarnitine, pregnen-diol disulfate, gulono 1,4-lactone, glucuronate, quinate, isocitrate, 1-methylxanthine, 1 -methylurate, 21-hydroxypregnenoione-disulfate, beta- hydroxypyruvate, threonylleucine, alanylleucine, andro-steroid-monosulfate-2, 1- methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5- carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2- hydroxyisobutyrate, 1-methylhistidine, 4-acetamidobutanoate, N-acetlyisoleucine, citrate, N2- methylguanosine, xylose, stachydrine, N4-acetylcytidine, tryptophan betaine, N-acetylvaline, and thymine.

[0059] In another example, the identification of biomarkers for nephrotoxicity allows for the classification of subjects as having a low level of nephrotoxicity, a moderate level of nephrotoxicity or a high level of nephrotoxicity. As described in the Examples below, biomarkers were identified that may be used to classify subjects as having low, moderate, or high levels of nephrotoxicity. Thus, the biomarkers may indicate compounds that increase and/or decrease as the nephrotoxicity level increases. By determining appropriate reference levels of the biomarkers for each group (low, moderate, or high level of nephrotoxicity), subjects can be diagnosed (classified) appropriately. The results of this method may be combined with the results of clinical measurements to aid in the diagnosis of nephrotoxicity.

[0060] Increased nephrotoxicity correlates with decreased glomerular filtration rate as calculated from SCr. Metabolomic analysis can be used to identify biomarkers that correlate with the calculated eGFR. The identified biomarkers can be used in an algorithm to determine the nephrotoxicity level of a subject using a simple test rather than the serum creatinine level test which is not rapidly responsive in an acute injury situation. For example, using metabolomic analysis, panels of metabolites, such as those provided in Tables 1, 2 and 4 that can be used in a simple test to predict nephrotoxicity were discovered. Such methods and algorithms include those provided in the Examples below, such as Example 3. [0061] Studies were carried out to identify a set of biomarkers that can be used to detect or aid in the detection of nephrotoxicity in a subject. In one aspect, the biomarkers provided herein can be used to provide a physician with a probability score ("Nephrotoxicity Score") indicating the probability that a subject has nephrotoxicity. The score is based upon clinically significantly changed reference level(s) for a biomarker and/or combination of biomarkers. The reference level can be derived from an algorithm or computed from indices for impaired eGFR. The Nephrotoxicity Score can be used to place the subject in the range of nephrotoxicity from normal (i.e. no nephrotoxicity) to moderate nephrotoxicity to high nephrotoxicity. Non-limiting exemplary uses of the Nephrotoxicity Score include: monitoring disease progression or remission by periodic determination and monitoring of the Nephrotoxicity Score; assessing tolerance of chemotherapeutic agents; assessing response to therapeutic intervention; and evaluating drug efficacy.

[0062] Methods for determining a subject's Nephrotoxicity Score may be performed using one or more of the nephrotoxicity biomarkers (metabolites) identified in Tables 1, 2, and/or 4 in a biological sample. The method may comprise comparing the level(s) of the one or more nephrotoxicity biomarkers in the sample to nephrotoxicity reference levels of the one or more biomarkers in order to determine the subject's Nephrotoxicity Score. The method may employ any number of markers selected from those listed in Tables 1, 2, and/or 4, including 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more markers. Multiple biomarkers may be correlated with nephrotoxicity, by any method, including statistical methods such as regression analysis.

[0063] Any suitable method may be used to analyze the biological sample in order to determine the level(s) of the one or more biomarkers in the sample. Suitable methods include chromatography (e.g., HPLC, gas chromatography, liquid chromatography), mass spectrometry (e.g., MS, MS-MS), enzyme-linked immunosorbent assay (ELISA), antibody linkage, other immunochemical techniques, and combinations thereof.

[0064] After the level(s) of the one or more biomarker(s) is determined, the level(s) may be compared to nephrotoxicity reference level(s) or reference curves of the one or more biomarker(s) to determine a rating for each of the one or more biomarker(s) in the sample. The rating(s) may be aggregated using any algorithm to create a score, for example, a nephrotoxicity score, for the subject. The algorithm may take into account any factors relating to nephrotoxicity including the number of biomarkers, the correlation of the biomarkers to nephrotoxicity, etc. C. Monitoring Nephrotoxicity Progression / Regression

[0065] The identification of biomarkers for nephrotoxicity also allows for monitoring progression/regression of nephrotoxicity in a subject. A method of monitoring the

progression/regression of nephrotoxicity in a subject may comprise (1) analyzing a first biological sample from a subject to determine the level(s) of one or more biomarkers for nephrotoxicity selected from Tables 1, 2, and/or 4, the first sample obtained from the subject at a first time point, (2) analyzing a second biological sample from a subject to determine the level(s) of the one or more biomarkers, the second sample obtained from the subject at a second time point, and (3) comparing the level(s) of one or more biomarkers in the first sample to the level(s) of the one or more biomarkers in the second sample in order to monitor the

progression/regression of nephrotoxicity in the subject. In another example, the one or more biomarkers may be selected from the group consisting of the following biomarkers: gamma- glutamylleucine, gamma-glutamylisoleucine, glutaroyl-carnitine, butyrylcarnitine, trigonelline (N-methylnicotinate), N(2)-furoyl-glycine, xanthurenate, N-acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, homovanillate-sulfate,

hydroxyisovaleroyl-carnitine, Nl-methylguanosine, phenol sulfate, 3-methylhistidine, gamma- glutamyltyrosine, mandelate, Cortisol, N-methyl proline, sucrose, homocitrate, 7,8- dihydroneopterin, 3,7-dimethylurate, 3-dehydrocarnitine, pantothenate, 1-methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7-methylxanthine, N- acetylarginine, gamma-glutamylvaline, gamma-glutamylthreonine, N6-acetyllysine,

isobutyrylcarnitine, 3 -methyl-2-oxo valerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, N-acetylhistidine, dimethylarginine (SDMA + ADMA), glucono-l ,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, pregnen-diol disulfate, gulono 1 ,4-lactone, glucuronate, quinate, isocitrate, 1 -methylxanthine, 1 - methylurate, 21-hydroxypregnenoione-disulfate, beta-hydroxypyruvate, threonylleucine, alanylleucine, andro-steroid-monosulfate-2, 1 -methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5-carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2-hydroxyisobutyrate, 1-methylhistidine, 4- acetamidobutanoate, N-acetlyisoleucine, citrate, N2-methylguanosine, xylose, stachydrine, N4- acetylcytidine, tryptophan betaine, N-acetyl valine, thymine, 1-methylimidazoleacetate, quinolinate, Isobar: sorbitol, mannitol, pyridoxal, xanthine, inosine, adenosine, 2- hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxyacetate). The results of the method are indicative of the course of nephrotoxicity (i.e., progression or regression, if any change) in the subject.

[0066] The change (if any) in the level(s) of the one or more biomarkers over time may be indicative of progression or regression of nephrotoxicity in the subject. In order to characterize the course of nephrotoxicity in the subject, the level(s) of the one or more biomarkers in the first sample, the level(s) of the one or more biomarkers in the second sample, and/or the results of the comparison of the levels of the biomarkers in the first and second samples may be compared to nephrotoxicity-positive and nephrotoxicity-negative reference levels. If the comparisons indicate that the level(s) of the one or more biomarkers are increasing or decreasing over time (e.g., in the second sample as compared to the first sample) to become more similar to the nephrotoxicity- positive reference levels (or less similar to the nephrotoxicity-negative reference levels), then the results are indicative of nephrotoxicity progression. If the comparisons indicate that the level(s) of the one or more biomarkers are increasing or decreasing over time to become more similar to the nephrotoxicity-negative reference levels (or less similar to the nephrotoxicity-positive reference levels), then the results are indicative of nephrotoxicity regression.

[0067] As with the other methods described herein, the comparisons made in the methods of monitoring progression/regression of nephrotoxicity in a subject may be carried out using various techniques, including simple comparisons, one or more statistical analyses, and combinations thereof.

[0068] The results of the method may be used along with other methods (or the results thereof) useful in the clinical monitoring of progression/regression of nephrotoxicity in a subject.

[0069] As described above in connection with methods of determining susceptibility to nephrotoxicity, any suitable method may be used to analyze the biological samples in order to determine the level(s) of the one or more biomarkers in the samples. In addition, the level(s) one or more biomarkers, including a combination of all of the biomarkers in Tables 1 , 2, and/or 4 or any fraction thereof, may be determined and used in methods of monitoring

progression/regression of nephrotoxicity in a subject.

[0070[ Such methods could be conducted to monitor the course of nephrotoxicity in subjects having nephrotoxicity or could be used in subjects not having nephrotoxicity (e.g., subjects suspected of being predisposed to developing nephrotoxicity) in order to monitor levels of predisposition to nephrotoxicity.

[0071] In one embodiment, the results of the method may be based on a Nephrotoxicity

Score which is representative of the probability of nephrotoxicity in the subject and which can be monitored over time. By comparing the Nephrotoxicity Score from a first time point sample to the Nephrotoxicity Score from at least a second time point sample the progression or regression of nephrotoxicity can be determined. Such a method of monitoring the progression/regression of nephrotoxicity in a subject may comprise (1) analyzing a first biological sample from a subject to determine a Nephrotoxicity Score for the first sample obtained from the subject at a first time point, (2) analyzing a second biological sample from a subject to determine a second

Nephrotoxicity Score, the second sample obtained from the subject at a second time point, and (3) comparing the Nephrotoxicity Score in the first sample to the Nephrotoxicity Score in the second sample in order to monitor the progression/regression of nephrotoxicity in the subject. An increase in the probability of nephrotoxicity from the first to the second time point is indicative of the progression of nephrotoxicity in the subject, while a decrease in the probability from the first to the second time points is indicative of the regression of nephrotoxicity in the subject.

[0072] Such methods could be used to develop an algorithm to monitor nephrotoxicity in cancer patients. For example, an algorithm could be developed based on a panel of urine metabolite biomarkers from Tables 1, 2, and/or 4 that can be useful to assess and monitor the renal tolerance of a patient to chemotherapy by measuring the levels of specific biomarker metabolites before each cycle of chemotherapy. An exemplary chemotherapy drug is cisplatin. Using the results of the biomarker algorithm in combination with current kidney function test results (i.e., SCr, BUN) a medical oncologist could assess the risk-benefit ratio of chemotherapy treatment in the patient. The biomarker algorithm could be used by medical oncologists treating not only bladder cancer patients but, more generally, any cancer patient (e.g., lung cancer, ovarian cancer, etc.) that may benefit from chemotherapy.

[0073] For example, a clinical practice algorithm (flow chart) was developed to monitor nephrotoxicity using the levels of a panel of biomarkers for nephrotoxicity identified in Tables 1 , 2, and/or 4. Figure 2 illustrates an example of a clinical practice biomarker algorithm. In the algorithm, a metabolite biomarker test, a test wherein the levels of biomarkers for nephrotoxity can be measured and analyzed, can be used to identify individuals who may be at risk of suffering chemotherapy-induced AKI or SAE thereby enabling a clinician to treat them differently to reduce the risk. In Figure 2, the following acronyms are used: SAE = Severe Adverse Event; FT = Kidney Function Test; and New Test = Metabolite Biomarker Test.

[0074] Levels of nephrotoxicity biomarkers that are normal at baseline and remain within normal range throughout therapy, are indicative that the patient has a low risk of suffering a chemotherapy-induced AKI or kidney severe adverse event (SAE).

[0075] A result for which the metabolite biomarker levels at baseline or the changes in these levels throughout therapy are significantly but not excessively above normal range would indicate that a patient has a moderate risk of suffering a chemotherapy-induced kidney injury (AKI) or kidney-SAE. Based on this result the treating clinician may elect to re-assess the risk- benefit ratio of the current treatment regimen (e.g., therapeutic agent, dose) in this patient and change the patient's management.

[0076] A result for which the levels of metabolite biomarkers at baseline or the changes in these levels throughout therapy are significantly and excessively above normal range would indicate that a patient has a high risk of suffering a chemotherapy-induced AKI or kidney SAE. Changes to the patient's management would be strongly advised (e.g., discontinue treatment with particular drug; switch to another agent).

D. Determining Response to Drug Treatment

[0077] The biomarkers provided also allow for the determination of subjects in whom the composition for treating a disease or condition is nephrotoxic (i.e. patient develops kidney toxic effect). For example, the identification of biomarkers for nephrotoxicity also allows for assessment of the subject's response to a composition that induces nephrotoxicity as well as the assessment of the relative patient response to two or more compositions that induce

nephrotoxicity. Such assessments may be used, for example, in selection of compositions for treating cancer for certain subjects, or in the selection of subjects into a course of treatment or clinical trial.

[0078] Thus, also provided are methods of predicting the nephrotoxic response of a patient to a composition for treating a disease or condition comprising (1) analyzing, from a subject (or group of subjects) having a disease or condition and currently or previously being treated with a composition, a biological sample (or group of samples) to determine the level(s) of one or more biomarkers for nephrotoxicity selected from the biomarkers listed in Tables 1 , 2, and/or 4 and (2) comparing the level(s) of the one or more biomarkers in the sample to (a) level(s) of the one or more biomarkers in a previously-taken biological sample from the subject, wherein the previously-taken biological sample was obtained from the subject before being treated with the composition, (b) nephrotoxicity-positive reference levels of the one or more biomarkers, (c) nephrotoxicity-negative reference levels of the one or more biomarkers, (d) nephrotoxicity-progression-positive reference levels of the one or more biomarkers, and/or (e) nephrotoxicity-regression-positive reference levels of the one or more biomarkers. In another example, the one or more biomarkers may be selected from the group consisting of the following biomarkers: gamma-glutamylleucine, gamma-glutamylisoleucine, glutaroyl-carnitine, butyrylcamitine, trigonelline (N-methylnicotinate), N(2)-furoyl-glycine, xanthurenate, N-acetyl- beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, homovanillate-sulfate, hydroxyisovaleroyl-carnitine, Nl-methylguanosine, phenol sulfate, 3- methylhistidine, gamma-glutamyltyrosine, mandelate, Cortisol, N-methyl proline, sucrose, homocitrate, 7,8-dihydroneopterin, 3,7-dimethylurate, 3-dehydrocarnitine, pantothenate, 1- methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7- methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma-glutamylthreonine, N6- acetyllysine, isobutyrylcarnitine, 3-methyl-2-oxovalerate, tyramine, homocitrulline,

tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, N-acetylhistidine, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, pregnen-diol disulfate, gulono 1,4-lactone, glucuronate, quinate, isocitrate, 1 -methylxanthine, 1-methylurate, 21-hydroxypregnenoione-disulfate, beta- hydroxypyruvate, threonylleucine, alanylleucine, andro-steroid-monosulfate-2, 1- methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5- carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2- hydroxyisobutyrate, 1-methylhistidine, 4-acetamidobutanoate, N-acetlyisoleucine, citrate, N2- methylguanosine, xylose, stachydrine, N4-acetylcytidine, tryptophan betaine, N-acetylvaline, thymine, 1-methylimidazoleacetate, quinolinate, Isobar: sorbitol, mannitol, pyridoxal, xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxyacetate). The results of the comparison are indicative of the nephrotoxic response of the patient to the composition for treating the respective disease or condition. An exemplary disease or condition is cancer.

[0079] The change (if any) in the level(s) of the one or more biomarkers over time may be indicative of nephrotoxic response of the subject to the composition. To characterize the nephrotoxicity of a given composition in the subject, the level(s) of the one or more biomarkers in the first sample, the level(s) of the one or more biomarkers in the second sample, and/or the results of the comparison of the levels of the biomarkers in the first and second samples may be compared to the respective nephrotoxicity-positive and/or nephrotoxicity-negative reference levels of the one or more biomarkers. If the comparisons indicate that the level(s) of the one or more biomarkers are increasing or decreasing over time (e.g., in the second sample as compared to the first sample) to become more similar to the nephrotoxicity-positive reference levels (or less similar to the nephrotoxicity-negative reference levels), then the results are indicative of the patient developing nephrotoxicity in response to the composition. If the comparisons indicate that the level(s) of the one or more biomarkers are increasing or decreasing over time to become more similar to the nephrotoxicity-negative reference levels (or less similar to the

nephrotoxicity-positive reference levels), then the results are indicative of the patient not developing nephrotoxicity in response to the composition.

[0080] For example, in order to characterize the patient's nephrotoxic response to cisplatin for mesothelioma, the level(s) of the one or more biomarkers in the first sample, the level(s) of the one or more biomarkers in the second sample, and/or the results of the comparison of the levels of the biomarkers in the first and second samples were compared to nephrotoxicity- positive and/or nephrotoxicity-negative reference levels of the one or more biomarkers. If the comparisons indicate that the level(s) of the one or more biomarkers were increasing or decreasing over time (e.g., in the second sample as compared to the first sample) to become more similar to the nephrotoxicity-positive reference levels (or less similar to the nephrotoxicity- negative reference levels), then the results were indicative of the patient developing

nephrotoxicity in response to cisplatin. If the comparisons indicate that the level(s) of the one or more biomarkers were increasing or decreasing over time to become more similar to the nephrotoxicity-negative reference levels (or less similar to the nephrotoxicity-positive reference levels), then the results were indicative of the patient not developing nephrotoxicity in response to cisplatin. [0081] The second sample may be obtained from the subject any period of time after the first sample is obtained. In one aspect, the second sample is obtained 1, 2, 3, 4, 5, 6, or more days after the first sample. In another aspect, the second sample is obtained 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, or more weeks after the first sample or after the initiation of treatment with the composition. In another aspect, the second sample may be obtained 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more months after the first sample or after the initiation of treatment with the composition.

[0082] As with the other methods described herein, the comparisons made in the methods of determining a patient's nephrotoxic response to a composition may be carried out using various techniques, including simple comparisons, one or more statistical analyses, and combinations thereof.

[0083] The results of the method may be used along with other methods (or the results thereof) useful in determining a patient's nephrotoxic response to a composition for the disease or condition in a subject.

[0084] As described above in connection with methods of diagnosing (or aiding in the diagnosis of) nephrotoxicity, any suitable method may be used to analyze the biological samples in order to determine the level(s) of the one or more biomarkers in the samples. In addition, the level(s) one or more biomarkers, including a combination of all of the biomarkers in Table 1, 2, and/or 4, or any fraction thereof, may be determined and used in methods of monitoring progression/regression of nephrotoxicity in a subject.

Examples

I. General Methods

A. Identification of Metabolic Profiles

[0085] Each sample was analyzed to determine the concentration of several hundred metabolites. Analytical techniques such as GC- S (gas chromatography-mass spectrometry) and LC-MS (liquid chromatography-mass spectrometry) were used to analyze the metabolites. Multiple aliquots were simultaneously, and in parallel, analyzed, and, after appropriate quality control (QC), the information derived from each analysis was recombined. Every sample was characterized according to several thousand characteristics, which ultimately amount to several hundred chemical species. The techniques used were able to identify novel and chemically unnamed compounds.

B. Statistical Analysis:

[0086] The data was analyzed using Welch's two-sample t-tests to identify molecules

(either known, named metabolites or unnamed metabolites) present at differential levels in a definable population or subpopulation (e.g., biomarkers for subjects with susceptibility to nephrotoxicity compared to subjects not susceptible to nephrotoxicity) useful for distinguishing between the definable populations (e.g., susceptible to nephrotoxicity and not susceptible to nephrotoxicity). Other molecules (either known, named metabolites or unnamed metabolites) in the definable population or subpopulation were also identified.

[0087] Data was also analyzed using Random Forest Analysis. Random forests give an estimate of how well individuals in a new data set can be classified into existing groups.

Random forest analysis creates a set of classification trees based on continual sampling of the experimental units and compounds. Then each observation is classified based on the majority votes from all the classification trees. In statistics, a classification tree classifies the observations into groups based on combinations of the variables (in this instance variables are metabolites or compounds). There are many variations on the algorithms used to create trees. A tree algorithm searches for the metabolite (compound) that provides the largest split between the two groups. This produces nodes. Then at each node, the metabolite that provides the best split is used and so on. If the node cannot be improved on, then it stops at that node and any observation in that node is classified as the majority group.

[0088] Random forests classify based on a large number (e.g. thousands) of trees. A subset of compounds and a subset of observations are used to create each tree. The observations used to create the tree are called the in-bag samples, and the remaining samples are called the out-of-bag samples. The classification tree is created from the in-bag samples, and the out-of-bag samples are predicted from this tree. To get the final classification for an observation, the "votes" for each group are counted based on the times it was an out-of-bag sample. For example, suppose observation 1 was classified as a "Control" by 2,000 trees, but classified as "Disease" by 3,000 trees. Using "majority wins" as the criterion, this sample is classified as "Disease."

[0089] The results of the random forest are summarized in a confusion matrix. The rows correspond to the true grouping, and the columns correspond to the classification from the random forest. Thus, the diagonal elements indicate the correct classifications. A 50% error would occur by random chance for 2 groups, 66.67% error for three groups by random chance, etc. The "Out-of-Bag" (OOB) Error rate gives an estimate of how accurately new observations can be predicted using the random forest model (e.g., whether a sample is from a diseased subject or a control subject).

[0090] It is also of interest to see which variables are more "important" in the final classifications. The "importance plot" shows the top compounds ranked in terms of their importance. There are different criteria for ranking the importance, but the general idea is that removing an important variable will cause a greater decrease in accuracy than removal of a variable that is less important.

[0091] Statistical analyses were performed with the program "R" available on the worldwide web at the website cran.r-project.org and in JMP 6.0.2 (SAS^® Institute, Cary, NC).

C. Biomarker identification

[0092] Various peaks identified in the analyses (e.g. GC-MS, LC-MS, LC-MS-MS), including those identified as statistically significant, were subjected to a mass spectrometry based chemical identification process.

Example 1: Biomarkers to determine susceptibility to nephrotoxicity

[0093] Biomarkers were identified by (1) analyzing urine samples from different groups of human subjects to determine the levels of metabolites in the samples and then (2) statistically analyzing the results to determine those metabolites that were differentially present in the groups.

[0094] The samples used for the analysis were urine samples collected from 59 stage 4 mesothelioma patients before lung lobectomy and the initiation of treatment with the

chemotherapeutic agent cisplatin (i.e., baseline measurements). Following surgery and treatment with cisplatin, the patients were monitored for development of acute kidney injury (AKI) using serum creatinine (SCr) measurements. Figure 3 shows the peak fold change in SCr

measurements relative to the baseline SCr measurement for the 59 subjects and the

corresponding classification of the subjects into AKI diagnosis groups based upon these measurements. At seven days post-operation, the SCr levels increased at least 50% in 23 patients and these subjects were diagnosed as having kidney injury (AKI, n=23). The SCr levels exhibited less than a 50% increase in 36 patients and these subjects were diagnosed as having no kidney injury (No AKI, n=36). The AKI group was further sub-divided into patients diagnosed with a severe kidney injury event (SCr increase of at least 100%, High, n=7). The No AKI group was further sub-divided to include patients who had less than a 10% peak fold increase in SCr through 7 days post-operation (Low, n=9).

[0095] To identify biomarkers of susceptibility or pre-disposition to AKI, the levels of metabolites were measured in the baseline plasma samples (i.e., samples collected before surgery and chemotherapy treatment). After the levels of metabolites were determined, the data were analyzed using t-tests. Two comparisons were used to identify biomarkers for susceptibility to nephrotoxicity: 1) metabolite levels in subjects having kidney injury (AKI) vs. metabolite levels in subjects that had no kidney injury (No AKI) and 2) metabolite levels in subjects having severe kidney injury and greater than 100% increase in SCr (High) vs. metabolite levels in subjects having no kidney injury and less than or equal to 10% increase in SCr (Low). As listed in Table 1 below, the analysis resulted in the identification of biomarkers that are differentially present at baseline between 1) subjects having AKI and those subjects with No AKI and/or 2) subjects having severe AKI (High) and those with no AKI and a low increase in SCr (Low).

[0096] Table 1 includes, for each biomarker, the biochemical name of the biomarker, the fold change of the biomarker in subjects susceptible to kidney injury compared to subjects not susceptible to kidney injury (AKI No AKI and High/Low) which is the ratio of the mean level of the biomarker in kidney injury samples as compared to the no kidney injury mean level, and the p-value determined in the statistical analysis of the data concerning the biomarkers. Table 1 also lists the following: the internal identifier for the biomarker compound in the in-house chemical library of authentic standards (CompID); the identifier for the biomarker compound in the Kyoto Encyclopedia of Genes and Genomes (KEGG), if available; and the identifier for the biomarker compound in the Human Metabolome Database (HMDB), if available.

Table 1. Biomarkers to determine susceptibility to nephrotoxicity

Fold of Fold of

Biochemical Name P-value P-value Comp ID EGG HMDB

Change Change

trigonelline (Ν'-

0.68 0.024 0.58 0.3254 32401

methylnicotinate) HMDB00875

3-methylhistidine 0.49 0.0591 0.35 0.1 15677 C01152 HMDB00479 glutaroyl carnitine 0.76 0.0381 1.06 0.7121 35439 HMDB13130 gamma-glutamylleucine 1.7 0.0713 3.2 0.0445 18369 HMDB11171 homovanillate sulfate 0.77 0.0922 0,55 0.0206 38349

butyrylcarnitine 1.78 0.0014 1.32 0.576 32412

3,7-dimethylurate 0.56 0.0293 0.53 0.1444 34399 HMDB01982

N-acetylhistidine 0.81 0.1302 1.26 0.071 33946 C02997

sucrose 0.47 0.0315 0.2 0.0817 1519 C00089 HMDB00258 gamma-glutamylisoleucine 0.87 0.4559 1.63 0.0145 34456 HMDB11170

N1-methylguanosine 0.97 0.7514 1.37 0.0146 31609 . HMDB01563 hydroxyisovaleroyl carnitine 1.16 0.9653 1.58 0.0163 35433

mandelate 1.1 0.2086 1 .91 0.0213 22160 C01984 HMDB00703 gamma-glutamylvaline 1.05 0.9484 1.78 0.032 32393 HMDB11172 gamma-glutamylthreonine 1.16 0.459 1.72 0.0349 33364

N6-acetyllysine 1 0.6245 1.37 0.0389 36752 C02727 HMDB00206 isobutyrylcarnitine 1.12 0.3061 1.46 0.0391 33441

3-methyl-2-oxovalerate 1.1 0.5365 2.03 0.0402 15676 C00671 HMDB03736 glycocholate 1.11 0.54 4.14 0.0408 18476 C01921 HMDB00138 tyramine 1.11 0.7361 2.02 0.0431 1603 C00483 HMDB00306

Cortisol 1.74 0.0197 1.89 0.0465 1712 C00735 HMDB00063 homocitruliine 1.01 0.8312 1.44 0.0516 22138 C02427 HMDB00679 tetrahydrocortisone 0.86 0.5773 1.67 0.0537 38608 HMDB00903

N-methyl proline 0.61 0.0285 2.09 0.0571 37431

gamma-glutamyltyrosine 1.34 0.3378 2.24 0.0576 2734

xylitol 1.11 0.7996 1.89 0.0684 4966 C00379 HMDB00568

4-androsten-3beta, 17beta-

0.8 0.7496 2.52 0.0694 37202

diol disulfate 1 HMDB03818

C00392,

C01722,

C01697,

Isobar: sorbitol, mannitol 18.05 0.0177 81 0.0767 33004

C01489,

C00794,

C01507 H DB00247

HMDB01539 dimethylarginine (SDMA +

0.94 0.6875 1.26 0.08 36808

AD A) ,HMDB0333

C03626 4 glucono-1 ,5-lactone 1.15 0.4553 5.04 0.0831 32355 C00198 HMDB00150

3-hyd roxyhippu rate 0.85 0.3172 0.58 0.0845 39600 HMDB06116 tiglyl carnitine 1.04 0.7029 1.46 0.0878 35428 HMDB02366

N-acetyl-beta-alanine 1.24 0.1579 1.47 0.0928 37432 C01073 phenol sulfate 0.76 0.1071 1.72 0.0957 32553 C02180

2-methylbutyroylcarnitine 1.23 0.2771 1.55 0.0961 35431 HMDB00378 homocitrate 0.82 0.0665 0.64 0.098 39601 C01251 HMSB03518 pregnen-diol disulfate 0.74 0.7052 1.43 0.0988 32562 C05484 HMDB04025

C-g lycosyltryptophan 1.03 0.6479 1.29 0.1073 32675

N2-methylguanosine 0.95 0.7524 1.25 0.1086 35133 HMDB05862 azelate (nonanedioate) 0.74 0.2015 0.63 0.1098 18362 C08261 HMDB00784 thymine 1.02 0.6683 1.35 0.1102 604 C00178 HMDB00262 o rotate 0.94 0.4713 1.84 0.114 1505 C00295 HMDB00226 uracil 0.9 0.5396 1.52 0.1 152 605 C00106 HMDB00300 propionylcarnitine 1.83 0.1265 1.57 0.1165 32452 C03017 HMDB00824 pipecolate 0.9 0.3985 1.38 0.1167 1444 C00408 HMDB00070 ribitol 0.93 0.5686 1.33 0.1211 15772 C00474 HMDB00508 tryptamine 1.1 1 0.9069 1.68 0.1222 6104 C00398 HMDB0O303 xanthurenate 0.87 0.0546 0.69 0.1238 15679 C02470 HMDB00881 taurolithocholate 3-sulfate 1.46 0.3001 1.82 0.1245 36850 C03642 HMDB02580 itaconate

0.71 0.2564 0.48 0.1249 18373

(methylenesuccinate) C00490 HMDB02092 creatine 1.31 0.7494 6.69 0.129 27718 C00300 HMDB00064 indoleacetate 1.24 0.6315 1.67 0.1298 27513 C00954 HMDB00197

1 -methylimidazoleacetate 1.1 0.2188 1.37 0.1364 32350 C05828 HMDB02820 homostachydrine 0.93 0.7576 1.63 0.1379 33009 C08283

tryptophan betaine 0.89 0.593 1.97 0.1398 37097 C09213

7,8-dihydroneopterin 0.6 0.0513 0.3 0.142 15689 C04895 HMDB02275 cis-4-decenoyl carnitine 1.05 0.6912 1.44 0.1477 381 8

3-dehydrocarnitine 1.37 0.0596 1.5 0.1481 32654 C02636 HMDB12154 kynurenine 1.26 0.1339 2.95 0.1518 15140 C00328 HMDB00684

3-ureidopropionate 1.08 0.6886 1.44 0.1522 3155 C02642 HMDB00026

1-methylhistidine 0.55 0.1384 0.35 0.1553 30460 C01152 HMDB00001

N-acetyl-aspartyl-glutamate

1.11 0.2822 1.35 0.1661 35665

(NAAG) C12270 HMDB01067 cis-aconitate 0.98 0.8211 1.18 0.1714 12025 C00417 HMDB00072 hydantoin-5-propionic acid 1.19 0.4498 1.37 0.1734 40473 C05565 HMDB01212

2-aminoadipate 1.08 0.3716 1.21 0.1745 6146 C00956 HMDB00510 pro-hydroxy-pro 0.92 0.3867 1.21 0.1758 35127 HMDB06695 sarcosine (N-Methylglycine) 1.06 0.4666 1.98 0.1794 1516 CO0213 HMDB00271 dimethylglycine 1.09 0.4636 2.21 0.181 5086 C01026 HMDB00092 pyroglutamine 1.12 0.3423 1.15 0.1863 32672

21 -hyd roxypreg nenolone

0.91 0.8559 1.32 0.1941 37173

disulfate C05485 HMDB04026 pantothenate 1.43 0.098 1.23 0.1971 1508 C00864 HMDB00210 acetylphosphate 0.85 0.3491 0.76 0.1974 15488 CO0227 HMDB01494 allantoin 0.79 0.2001 0.86 0.2145 1107 C02350 HMDB00462 mesaconate 0.94 0.4803 1.25 0.2147 18493 C01732 HMDB00749 (met ylfumarate)

N2,N2-dimethylguanosine 0.92 0.5954 1.17 0.216 35137 HMDB04824 androsterone sulfate 0.8 0.992 1.39 0.2228 31591 C00523 HMDB02759

6-sialyl-N-acetyllactosamine 1.14 0.2295 1.22 0.2231 40428 HMDB06584 phenylpyruvate 0.94 0.895 1.25 0.2258 566 C00166 HMDB00205

N-acetyltryptophan 1.82 0.4679 3.88 0.2262 33959 C03137

phenylacetylglutamine 1.07 0.5019 1.43 0.23 35126 C05597 HMDB06344

4-methyl-2-oxopentanoate 0.97 0.8705 1.32 0,2338 22116 C00233 HMDB00695

3-methylcytidine 0.81 0.1518 1.33 0.238 35132

etiolate 0 52 0.9959 2.87 0.2466 22842 C00695 HMDB00619 ,3-diaminopropane 1.04 0.471 1.56 0.2525 1654 C00986 HMDB00002 valylleucine 1.1 1 0.6902 0.54 0.2566 39994

3-hydroxyisobutyrate 1.01 0.4495 1.23 0.2665 1549 C06001 HMDB00336 cortisone 1.1 0.6688 1.29 0.2734 1769 C00762 HMDB02802

N-acetylisoleucine 0.79 0.1777 1.26 0.2876 33967

C02953,

dihydrobiopterin 0.92 0.3967 0.85 0.2939 35129

C00268 HMDB00038

4-androsten-3beta,17beta-

0.81 0.364 1.21 0.2949 37203

diol disulfate 2 HMDB03818 fructose 0.8 0.3153 0.37 0.3056 577 C00095 HMDB00660 pseudouridine 0.95 0.8457 1.1 0.3056 33442 C02067 HMDB00767 isovalerylcarnitine 1.42 0.3301 1.58 0.3078 34407 HMDB00688

N-acetylmannosamine 1.16 0.9755 3.23 0.3112 15060 C00140 HMDB00835

N 1 -Methyl-2-pyridone-5-

1.17 0.5287 1.19 0.3142 40469

carboxamide C05842 HMDB04193

2-met ylcitrate 0.91 0.4067 1.36 0.3178 37483 C02225 HMDB00379

3-aminoisobutyrate 1.13 0.9229 0.45 0.3183 1566 C05145 HMDB03911 threonylleucine 0.93 0.859 1.33 0.3224 40051

arabinose 0.89 0.713 1.18 0.3258 575 C00181 HMDB00646 hypoxanthine 0.89 0.751 0.79 0.3291 3127 C00262 HMDB00157

7-ketodeoxycholate 1.19 0.2445 4.76 0.3332 31904 HMDB00391 glutarate (pentanedioate) 0.71 0.2334 1.07 0.3354 396 C00489 HMDB00661 lactate 0.87 0.8258 0.47 0.3394 527 C00186 HMDB00190 urate 0.99 0.7828 1.13 0.3394 1604 C00366 HMDB00289

3-methoxytyrosine 0.9 0.8672 1.18 0.3433 12017 HMDB01434

5alpha-pregnan- 3alpha,20beta-diol disulfate 0.86 0.4093 0.81 0.3434 37201

1

pregn steroid monosulfate 0.69 0.3885 0.66 0.3434 32619 C 18044 HMDB00774

4-aminohippurate 0.91 0.9835 0.54 0.3434 32406 D01421 HMDB01867 dihydroferulic acid 0.73 0.3513 0.44 0.3434 40481

beta-hydroxypyruvate 1.01 0.9439 1.86 0.3559 15686 C00168 HMDB01352

3-hydroxy-2-ethylpropionate 0.98 0.9038 1.06 0.3582 32397 HMDB00396

2- ydroxybutyrate (AHB) 1.33 0.3445 1.34 0.3591 21044 C05984 HMDB00008 alpha-hydroxyisovalerate 1.61 0.5661 1.81 0.3701 33937 HMDB00407

N-acetylthreonine 0.94 0.8221 1.14 0.373 33939 C01118

1-methylxanthine 0.57 0.0465 0.74 0.3745 34389

3-metrtylglutarate 1.1 0.6113 1.1 0.3795 1557 HMDB00752 vanillate 1.41 0.3768 0.77 0.3805 35639 C06672 HMDB00484 guanine 1.02 0.3711 1.41 0.3972 32352 C00242 HMDB00132 kynurenate 0.92 0.5931 1.08 0.3976 1417 C01717 HMDB00715

N-acetylputrescine 0.87 0.2969 1.13 0.398 37496 C02714 HMDB02064 indolelactate 1 0.4035 1.6 0.4084 18349 C02043 HMDB00671

4-guanidinobutanoate 0.7 0.1088 1.36 0.4092 15681 C01035 HMDB03464 homovanillate (HVA) 0.96 0.4612 0.78 0.4128 1101 C05582 HMDB00118

N-6-trimethyllysine 0.78 0.2564 1.06 0.4138 1498 C03793 HMDB01325 quinate 0.7 0.244 1.04 0.4148 18335 C00296 HMDB03072 xylose 1.04 0.5518 1.28 0.4169 15835 C00181 HMDB00098 phenylacetylglycine 1.01 0.7486 0.79 0.4221 33945 C05598 HMDB00821 alpha-hydroxyisocaproate 1.05 0.8929 1.31 0.4239 22132 C03264 HMDB00746

N6-

0.97 0.9604 1.13 0.4268 35157

carbamoylthreonyladenosine

glycoiithocholate sulfate 1.2 0.7107 1.41 0.4343 32620 C11301 HMDB02639

N-acetylvaline 0.8 0.2339 1.13 0.4429 1591 HMDB11757 imidazole lactate 0.92 0.5582 1.1 0.451 15716 C05568 HMDB02320

3-hydroxyglutarate 0.85 0.3661 1.1 0.4544 36863 HMDB00428

3-hydroxykynurenine 0.71 0.7386 3.04 0.4578 22110 C02794 HMDB00732 methylglutaroylcamitine 0.95 0.3192 0.78 0.4578 37060 HMDB00552

Isobar: pimelate, 3-

0.81 0.1998 0.81 0.4604 36769

methyladipate

HMDB00621 ribulose 0.93 0.7571 1.31 0.4649 35855 ,HMDB0337

C00309 1 suberylglycine 0.48 0.8106 0.29 0.4651 35419 HMDB00953 taurine 2.04 0.279 2.95 0.4656 2125 C00245 HMDB00251

1 ,3,7-trimethylurate 0.66 0.1895 0.95 0.4737 34404 C16361 HMDB02123 isovalerylglycine 0.88 0.4606 1.35 0.4761 35107 HMDB00678 succinylcarnitine 0.89 0.3091 1 ,07 0.4774 37058

2-hydroxyglutarate 0.82 0.5657 1.05 0.4815 37253 C02630 HMDB00606

1-methylnicotinamide 0.77 0.1064 0.89 0.4823 27665 C02918 HMDB00699

HMDB

vanilpyruvate 0.93 0.6694 0.74 0.4905 40087

11714 cis-urocanate 0.95 0.4202 0.97 0.4909 40410

gulono-1 ,4-lactone 1.03 0.7459 1.16 0,504 33454 C01040 HMDB03466

3-sialyllactose 0.78 0.281 0.81 0.5064 40424 HMDB00825 neopterin 1.01 0.9003 1.13 0.5097 35131 C05926 HMDB00845 arabitol 0.89 0.556 1.13 0.51 38075 C00474 HMDB01851 N-acetylp enylalanine 0.8 0.5636 0.5 0.5136 33950 C03519 HMDB00512 pyroglutamylvaline 0.98 0.9315 1.13 0.514 32394

xylulose 1.11 0.885 1.36 0.518 18344 C00310 HMDB00654

4-hyd roxypheny Ipyruvate 0.59 0.8069 1.36 0.5194 1669 C01179 HMDB00707 pregnanediol-3-glucuronide 0.81 0.1759 1.26 0.5214 40708

5-acetylamino-6-

0.82 0.5502 0.61 0.5266 34401

formylamino-3-methyluracil C16365 HMDB11105 phenyllactate (PLA) 0.88 0.7231 0.49 0.5288 22130 C05607 HMDB00779 octanoylcarnitine 1.11 0.7257 0.83 0.5292 33936

N-(2-furoyl)glycine 1.15 0.2412 1.23 0.5341 31536 HMDB00439

N-acetylmethionine 0.91 0.6417 0.89 0.5344 1589 C02712 HMDB11745 cortisone monosulfate 0.78 0.7044 1.03 0.5388 37540 C00762 HMDB02802

5-oxoproline 0.91 0.4838 1.07 0.546 1494 C01879 HMDB00267 imidazole propionate 0.66 0.575 1.06 0.5474 40730 HMDB02271

4-hyd roxymandelate 0.88 0.475 1.27 0.5544 1568 C03198 HMDB00822 xanthosine 0.82 0.2658 0.85 0.5595 15136 C01762 HMDB00299 erythronate 0.99 0.9757 1.08 0,5616 33477 HMDB00613 citrate 1 0.9505 0.87 0.5631 1564 C00158 HMDB00094

4-hydroxyphenylacetate 1.14 0.8349 0.61 0.5687 541 C00642 HMDB00020

N-acetylglutamine 0.84 0.3618 1.03 0.5712 33943 C02716 HMDB06029 glucuronate 0.91 0.771 1.05 0.572 15443 C00191 HMDB00127 vanillylmandelate (VMA) 0.9 0.4777 0.87 0.5747 1567 C05584 HMDB00291 nicotinamide 0.81 0.0426 1.08 0.5804 594 C00153 HMDB01406

N-acetylglutamate 0.99 0.8238 0.99 0.588 15720 C00624 HMDB01138 isobutyrylglycine 1.15 0.9119 1.64 0.5897 35437 HMDB00730 theophylline 0.64 0.0435 1 0.5912 18394 C07130 HMDB01889 stachydrins 0.69 0.1017 0.84 0.5988 34384 C10172 HMDB04827

N1-methyladenosine 0.82 0.1212 1.07 0.5999 15650 C02494 HMDB03331

C02612,

citramalate 1.1 1 0.8456 1.27 0.6028 22158

C00815 HMDB00426

5alpha-pregnan-

1.06 0.5423 1.44 0.61 37198

3beta,20alpha-diol disulfate

andro steroid monosulfate 2 0.55 0.2184 1.1 0.6121 32792 C04555 HMDB02759 leucylleucine 1.05 0.4933 1.12 0.6164 36756 C11332

1,6-anhydroglucose 0.7 0.3462 0.73 0.619 21049 HMDB00640 lactose 0.98 0.7988 1.21 0.6219 11454 C00243 HMDB00186

1 ,7-dimethylurate 0.64 0.1144 0.88 0.623 34400 C16356 HMDB11103

N2-acetyllysine 0.81 0.238 1.08 0.6237 36751 C12989 HMDB00446

2-hydroxyadipate 0.99 0.4893 1.01 0.6242 31934 C02360 HMDB00321

S-methylcysteine 1.41 0.5868 1.41 0.6275 40262 HMDB02108

3-methylcrotonylglycine 1.2 0.4319 1.04 0.6329 31940 HMDB00459

C00717,

1 ,2-propanediol 1.02 0.9675 1.53 0.6344 38002

C02912, HMDB01881

L-urobilin 2.02 0.4988 1.48 0.7794 40173 C05793 HMDB04159

H DB00193 isocitrate 0.97 0.6297 1.03 0,7832 12110 ,HMDB0187

C00311 4 glucarate (saccharate) 0.82 0.8133 0.98 0.7862 1476 C00818 HMDB00663 alp a-ketoglutarate 0.69 0.6678 0.64 0.7882 528 C00026 HMDB00208 prolylglycine 1.1 0.1848 1.15 0.79 40703

pyruvate 1.05 0.8373 1.23 0.7908 599 C00022 HMDB00243 tigloylglycine 0.94 0.4451 1.12 0.792 1598 HMDB00959

2-hydroxyphenylacetate 1.08 0.8001 1.01 0.7958 11837 C05852 HMDB00669

N-acetylleucine 0.88 0.5296 1 0.7963 1587 C02710 HMDB11756 panose 1.13 0.3772 1.15 0.7991 37284 C00713 HMDB11729

2-aminobutyrate 1.1 0.198 1 29 0.8008 1577 C02261 HMDB00650 fumarate 0.98 0.8845 0 78 0.8082 1643 C00122 HMDB00134 isoleucylphenylalanine 1.01 0.9254 1.06 0.8135 40067

glycine 0.86 0.3472 0.9 0.8139 11777 C00037 HMDB00123

2-methylbutyrylglycine 0.9 0.4439 1.03 0.8155 31928 HMDB00339 quinolinate 1.1 0.5389 0.83 0.8197 1899 C03722 HMDB0O232 beta-hydroxyisovalerate 1.33 0.5019 1.2 0.8258 12129 HMDB00754

N-acetylasparagine 0.86 0.4073 0.9 0.8371 33942 HMDB06028

2-hydroxyisobutyrate 0.74 0.7724 0.93 0.8371 22030 HMDB00729 theobromine 0.81 0.3101 0.84 0.8524 18392 C07480 HMDB02825 dehydroisoandrosterone

0.82 0.4987 1.34 0.8582 32425

sulfate (DHEA-S) C04555 HMDB01032 isomaltose 1.15 0.0986 1 0.865 39942 C00252 HMDB02923

3-methylxanthine 0.73 0.3032 1.02 0.8721 32445 C16357 HMDB01886 threonylphenylalanine 1.19 0.5421 0.98 0.875 31530

2-oxindole-3-acetate 0.74 0.1606 1.09 0.8751 40479

7-methylxanthine 0.48 0.0597 0.57 0.8752 34390 C16353 HMDB01991

C00502,

xylonate 1.02 0.6129 0.99 0.8755 35638

C05411

beta-alanine 1.25 0.6565 1.52 0.8765 55 C00099 HMDB00056 sebacate (decanedioate) 0.45 0.5208 0.3 0.8837 32398 C08277 HMDB00792 catechol sulfate 2.76 0.7792 7.81 0.8858 35320 C00090

scyllo-inositol 0.96 0.5878 1.17 0.8903 32379 C06153 HMDB06088

N6-methyladenosine 1.19 0 8846 1.05 0.8922 37114 HMDB04044 cytosine 0.85 0.9952 1.63 0.8969 573 C00380 H DB00630

N-acetylglycine 1.1 0.5735 1.04 0.8997 27710 HMDB00532

12-dehydrocholate 1.19 0.5624 0.93 0.9013 31887 HMDB00400 chiro-inositol 0.73 0.1199 1.89 0.9027 371 12

hexanoylglycine 0.72 0.834 0.52 0.903 35436 HMDB00701 caffeine 0.56 0.3251 0.95 0.9037 569 C07481 HMDB01847

4-vinylphenol sulfate 0.82 0.7815 0.68 0.9046 36098 C05627 HMDB04072

Example 2: Evaluation of Biomarkers and Development of Predictive Models for

Identifying Subjects with Susceptibility to Nephrotoxicity

[0097] To evaluate the identified biomarkers for determining the susceptibility of a subject to nephrotoxicity, biomarkers selected from Table 1 were evaluated using pair-wise analysis. Several non-limiting models are presented here to exemplify the invention. In one exemplary model, gamma-glutamylleucine and butyrylcarnitine were selected for pair-wise analysis. As seen in Table 1 , butyrylcarnitine and gamma-glutamylleucine were significantly altered at baseline for the AKI vs. No AKI and High vs. Low comparisons, respectively. Figure 4 provides a pair-wise analysis for gamma-glutamylleucine and butyrylcarnitine. In Figure 4, the relative level of butyrylcarnitine is shown on the x-axis and the relative level of gamma- glutamylleucine is shown on the y-axis as measured in each sample. In Figure 4, AKI subjects are indicated by solid stars and non-AKI subjects are indicated by open circles. [0098] Using these two biomarkers in a model, the following prediction of risk of AKI following chemotherapy was determined. The model using these two biomarkers predicted that, when used on a new set of subjects, 80% of the subjects with butyrylcarnitine levels of greater than 1.5 or gamma-glutamylleucine levels of greater than 3.5 would be susceptible to nephrotoxicity, indicating that subjects with levels of butyrylcarnitine greater than 1.5 or gamma- glutamylleucine levels greater than 3.5 would be at a high risk for developing nephrotoxicity following chemotherapy treatment. The model using these two biomarkers predicted that, when used on a new set of subjects, 38% of the subjects with butyrylcarnitine levels between 0.5 and 1.5 and gamma-glutamylleucine levels less than 3.5 would be susceptible to nephrotoxicity indicating that subjects with levels of butyrylcarnitine between 0.5 and 1.5 and gamma- glutamylleucine less than 3.5 would be at a moderate risk for developing nephrotoxicity. The model using these two biomarkers predicted that, when used on a new set of subjects, 0% of the subjects with butyrylcarnitine levels less than 0.5 and gamma-glutamylleucine levels less than 3.5 would be susceptible to nephrotoxicity indicating that subjects with levels of butyrylcarnitine less than 0.5 and gamma-glutamylleucine less than 3.5 would be at low risk for developing nephrotoxicity.

[0099] In another exemplary model, trigonelline and glutaroylcarnitine were selected for pair- wise analysis. As seen in Table 1, trigonelline and glutaroylcarnitine were both

significantly lower at baseline in AKI subjects compared to No AKI subjects. Figure 5 illustrates pair- wise analysis for trigonelline and glutaroyl-carnitine. In Figure 5, the relative level of trigonelline is shown on the x-axis and the relative level of glutaroylcarnitine is shown on the y- axis as measured in each sample. In Figure 5, AKI subjects are indicated by solid stars and non- AKI subjects are indicated by open circles.

[00100] Using these two biomarkers in a model, the following prediction of risk of AKI following chemotherapy was determined. The model using these two biomarkers predicted that, when used on a new set of subjects only 16% of the subjects with trigonelline levels of greater than 4.1 or glutaroylcarnitine levels of greater than 2.0 would be susceptible to nephrotoxicity, indicating that subjects with trigonelline levels of greater than 4.1 or glutaroylcarnitine levels of greater than 2.0 would be at low risk for developing nephrotoxicity following chemotherapy treatment. The model using these two biomarkers predicted that, when used on a new set of subjects, 47% of the subjects with trigonelline levels between 1.5 and 4.1 and glutaroylcarnitine levels less than 2.0 would be susceptible to nephrotoxicity indicating that subjects with levels of trigonelline between 1.5 and 4.1 and glutaroylcarnitine less than 2.0 would be at a moderate risk for developing nephrotoxicity. The model using these two biomarkers predicted that, when used on a new set of subjects, 71% of the subjects with trigonelline levels less than 1.5 and glutaroylcarnitine levels less than 2.0 would be susceptible to nephrotoxicity indicating that subjects with levels of trigonelline less than 1.5 and glutaroylcarnitine less than 2.0 would be at high risk for developing nephrotoxicity.

Example 3: Biomarkers to Diagnose Acute Kidney Injury Early

[00101] Metabolomic analysis was carried out on urine samples to identify biomarkers to distinguish subjects with cisplatin-induced kidney injury from subjects without cisplatin-induced kidney injury. The urine samples used for the analysis were from 59 patients with stage 4 mesothelioma collected at four timepoints after lung lobectomy and the initiation of cisplatin treatment. This is the same cohort described in detail in Example 1. The urine samples were collected 2 hours after treatment (T2); 4 hours after treatment (T3); 8 hours after treatment (T4); 12 hours after treatment (T5). The peak fold change SCr measurements shown in Figure 3 were calculated by dividing the maximum SCr measured within 7 days post-operation by the baseline SCr measurement. The earliest time that SCr reflected AKI for any subject in this cohort was at 2 days after cisplatin treatment. The timepoints used in this example (2h, 4h, 8h, 12h) represent measurable endpoints before kidney injury can be diagnosed using a currently available test (i.e., SCr). At seven days post-operation, 23 patients were diagnosed as having kidney injury based upon an increase in SCr >50% (AKI, n=23) and 36 patients were diagnosed as having no kidney injury (SCr<50%) (No AKI, n=36).

[00102] After the levels of metabolites were determined, the data were analyzed using t- tests to identify biomarkers that differed between subjects with kidney injury and subjects without kidney injury (AKI vs. No AKI). The biomarkers are listed in Table 2.

[00103] Table 2 includes, for each biomarker, the biochemical name of the biomarker, the fold change of the biomarker in 1) AKI compared to No AKI 2 hours after treatment, 2) AKI compared to No AKI 4 hours after treatment, 3) AKI compared to No AKI 8 hours after treatment, 4) AKI compared to No AKI 12 hours after treatment, and the p- value determined in the statistical analysis of the data concerning the biomarkers for AKI compared to No AKI 2 hours after treatment. The fold changes where p<0.1 are indicated in bold font in Table 2.

Table 2 also lists the following: the internal identifier for that biomarker compound in the in- house chemical library of authentic standards (CompID); the identifier for that biomarker compound in the Kyoto Encyclopedia of Genes and Genomes (KEGG), if available; and the identifier for that biomarker compound in the Human Metabolome Database (HMDB), if available.

Table 2. Biomarkers for early identification of acute kidney injury

4h AKI 8h AKI 12hAKI

2h AKI

4h No 8h No 12h No

2h No AKI

AKI AKI AKI

Fold of Fold of Fold of Fold of Comp

Biochemical Name p- KEGG HMDB

Change value Change Change Change ID

trigonelline (Ν'-

0.75 0.0631 0.59 0.53 0.7 32401 methylnicotinate) HMDB00875

3-methylhistidine 0.71 0.0908 0.46 0.24 0.45 15677 C01152 HMDB00479 glutaroyl carnitine 0.68 0.0035 0.75 0.85 0.93 35439 HMDB 13130

3,7-dimethylurate 0.75 0.1529 0.55 1.03 0.95 34399 HMDB01982

N-acetylhistidine 0.71 0.0272 0.59 0.71 0.86 33946 C02997

sucrose 0.79 0.1929 0.9 0.69 0.69 1519 C00089 HMDB00258 gulono-l,4-lactone 0.58 0.0008 0.55 0.78 0.98 33454 CO 1040 HMDB03466

7-methylxanthine 0.44 0.0009 0.53 0.43 0.6 34390 C16353 HMDB01991 o-cresol sulfate 0.67 0.0013 0.93 0.85 0.4 36845

N2-methylguanosine 0.63 0.0023 0.69 0.7 0.73 35133 HMDB05862

1-methylxanthine 0.53 0.0026 0.65 0.71 0.91 34389

glucono- 1 , 5-lactone 0.36 0.0028 0.37 0.77 0.91 32355 COO 198 HMDB00150

4-androsten- 3beta,17beta-diol 0.54 0.0058 0.48 0.53 0.51 37203

disulfate 2 HMDB03818 cis-aconitate 0.7 0.0064 0.86 0.94 1.02 12025 C00417 HMDB00072

HMDB00193 isocitrate 0.72 0.0071 0.99 0.97 0.83 12110 ,HMDB0187

C0031 1 4

N-acetylarginine 0.55 0.008 0.66 0.65 0.91 33953 C02562 HMDB04620

N-acetylputrescine 0.6 0.0083 0.68 0.77 0.85 37496 C02714 HMDB02064 pregnanediol-3-

0.66 0.0097 0.61 0.72 0.94 40708 glucuronide

itaconate

0.42 0.0099 0.75 0.52 1 18373

(methylenesuccinate) C00490 HMDB02092 fructose 0.68 0.0107 0.86 0.75 0.89 577 C00095 HMDB00660

4-vinylphenol sulfate 0.48 0.01 16 0.83 0.63 0.55 36098 C05627 HMDB04072 beta-hydroxypyruvate 0.53 0.0122 0.5 0.79 1.03 15686 COO 168 HMDB01352 xylose 0.35 0.0128 0.27 0.38 0.5 15835 C00181 HMDB00098 pro-hydroxy-pro 0.65 0.0195 0.69 0.94 0.88 35127 HMDB06695 pregnen-diol disulfate 0.56 0.0203 0.43 0.59 0.61 32562 C05484 HMDB04025 adenosine 3',5'-cyclic

monophosphate 0.76 0.0206 0.62 0.76 0.79 2831

(cAMP) C00575 HMDB00058

5-oxoproline 0.77 0.022 0.82 0.99 0.98 1494 CO 1879 HMDB00267 stachydrine 0.56 0.022 0.58 0.68 0.6 34384 C10172 HMDB04827

1 ,6-anhydroglucose 0.64 0.0229 0.68 0.71 0.85 21049 HMDB00640

2-methylcitrate 0.65 0.0234 0.69 0.97 1 37483 C02225 HMDB00379

1,7-dimethylurate 0.6 0.0249 0.67 0.68 0.77 34400 C16356 HMDB11103

C00502

xylonate 0.67 0.0274 0.55 0.75 0.81 35638 ,C0541

1

21- hydroxypregnenolone 0.68 0.0291 0.62 0.64 0.71 37173

disulfate C05485 HMDB04026

3 -methy lxanthine 0.64 0.0292 0.65 0.71 0.93 32445 C16357 HMDB01886

N4-acetylcytidine 0.69 0.0306 0.65 0.61 0.65 35130 HMDB05923

HMDB01539 dimethylarginine

0.72 0.031 0.6 0.9 0.8 36808 ,HMDB0333 (SDMA + ADMA)

C03626 4 quinate 0.61 0.0313 0.42 0.45 0.39 18335 C00296 HMDB03072 androsterone sulfate 0.63 0.0315 0.32 0.59 0.42 31591 C00523 HMDB02759

N-6-trimethyllysine 0.75 0.0386 0.85 0.99 1.05 1498 C03793 HMDB01325

3-hydroxymandelate 3.58 0.04 1.77 1.77 1.39 22112 HMDB00750

N2-acetyllysine 0.69 0.0404 0.8 0.96 0.95 36751 C12989 HMDB00446 methyl-4-

0.61 0.0423 1.14 0.98 1.19 34386 hydroxybenzoate D01400

methylglutaroylcarnitin

0.96 0.0425 0.75 1.1 1 1.03 37060 e HMDB00552

1 -methymicotinamide 0.78 0.045 0.54 0.88 1.04 27665 C02918 HMDB00699 allantoin 0.59 0.0451 1.11 1.04 1.09 1107 C02350 HMDB00462 succinylcarnitine 0.68 0.0452 0.71 0.78 0.88 37058

N-formylmethionine 0.73 0.046 0.69 0.66 0.6 2829 C03145 HMDB01015 xanthosine 0.75 0.046 0.79 0.86 0.82 15136 CO 1762 HMDB00299 threonate 0.83 0.0461 0.7 0.9 0.93 27738 CO 1620 H DB00943

1 -methy lurate 0.83 0.0487 0.83 1.04 1.15 34395 HMDB03099 alpha-

0.73 0.0488 0.83 1.51 0.98 22132 hydroxyi socaproate C03264 HMDB00746 theobromine 0.68 0.0506 0.55 1.05 0.76 18392 C07480 HMDB02825 quinolinate 0.61 0.0519 0.76 0.9 0.99 1899 C03722 HMDB00232 imidazole lactate 0.8 0.0534 0.84 0.81 0.72 15716 C05568 HMDB02320 glucuronate 0.65 0.0557 0.71 0.57 0.99 15443 C00191 HMDB00127

7-methylguanine 0.78 0.0559 0.78 0.95 0.94 35114 C02242 HMDB00897

3 -hydroxyanthranilate 0.82 0.1283 0.89 0.83 0.54 32353 C00632 HMDB01476 homovanillate (HVA) 0.5 0.1322 0.58 0.66 0.37 1101 C05582 HMDB001 18

N-acetylglutamine 0.67 0.1328 0.79 0.83 0.69 33943 C02716 HMDB06029 homocitrate 0.65 0.137 0.27 0.73 0.7 39601 CO 1251 HMSB03518

5 -hydroxy indoleacetate 0.9 0.1466 0.66 1.07 1.07 437 C05635 HMDB00763 phenylpyruvate 0.95 0.1502 0.75 0.68 0.37 566 COO 166 HMDB00205

4-guanidinobutanoate 0.61 0.1505 0.56 0.87 0.97 15681 C01035 HMDB03464 allo-threonine 0.73 0.1523 0.61 0.95 0.81 15142 C05519 HMDB04041 tartarate 0.76 0.1523 0.62 0.96 1.21 15336 C00898 HMDB00956

N-methyl proline 0.85 0.1645 0.38 0.43 0.74 37431

C00717

,C0291

2,C005

1,2-propanediol 0.76 0.1726 1.28 0.62 1 38002

83.C01

506.C0

2917 HMDB01881 phenylacetylglycine 0.8 0.1759 0.78 0.88 1.09 33945 C05598 HMDB00821

1-methylhistidine 1.46 0.1819 0.18 0.59 1.12 30460 C01152 HMDB00001 ribitol 1.05 0.1959 0.88 1.05 0.61 15772 C00474 HMDB00508 uracil 0.66 0.2012 0.47 0.63 0.71 605 COO 106 HMDB00300

3 -hydroxyisobutyrate 0.88 0.2091 0.79 0.57 0.68 1549 C06001 HMDB00336 pyruvate 0.9 0.2095 0.91 0.82 0.91 599 C00022 HMDB00243

N-acetyl-beta-alanine 0.77 0.2125 0.78 0.16 0.98 37432 CO 1073

cinnamoylglycine 0.65 0.2217 1.01 1.55 1.8 38637

dehydroisoandrosterone

0.22 0.2359 0.36 0.16 0.28 32425 sulfate (DHEA-S) C04555 HMDB01032 homocitrulline 0.79 0.236 0.71 0.65 0.75 22138 C02427 HMDB00679 sorbose 0.76 0.2362 0.49 1.24 0.89 563 C00247 HMDB01266

N-acetyl-aspartyl-

0.85 0.2538 0.61 0.87 0.97 35665 glutamate (NAAG) C 12270 HMDB01067

N-acetylleucine 0.77 0.2549 0.76 0.75 0.77 1587 C02710 HMDB1 1756

5alpha-pregnan- 3alpha,20beta-diol 0.95 0.2676 0.56 0.81 0.79 37201

disulfate 1

mesaconate

0.84 0.2685 0.58 1.09 1.17 1 8493

(methylfumarate) C01732 HMDB00749

3-methoxytyrosine 0.75 0.281 0.54 0.63 1.13 12017 HMDB01434 nicotinamide 0.73 0.2978 0.56 1 0.86 594 C00153 HMDB01406 pregn steroid

0.75 0.3242 0.74 0.27 0.73 32619 monosulfate CI 8044 HMDB00774 cis-4-decenoyl carnitine 0.59 0.3257 0.63 0.56 0.68 38178

N6-acetyllysine 0.76 0.355 0.75 0.73 0.71 36752 C02727 HMDB00206 glycerol 3 -phosphate

1.02 0.358

(G3P) 0.36 0.86 0.82 15365

C00093 HMDB00126 kynurenine 0.73 0.3588 0.66 0.82 0.72 15140 C00328 HMDB00684

2-aminobutyrate 0.93 0.3734 0.79 0.5 0.57 1577 C02261 HMDB00650 C00392

,C0172

2.C016

Isobar: sorbitol,

1.73 0.4073 2.29 1.46 1.13 33004 97,C01

mannitol

489,C0

0794,C

01507 HMDB00247

N-acetylthreonine 0.92 0.4075 0.96 0.87 0.8 33939 C01118

2-aminoadipate 0.96 0.4411 0.86 0.69 0.57 6146 C00956 HMDB00510

3-methylcytidine 0.76 0.4641 0.59 0.58 0.5 35132

beta-alanine 0.94 0.4994 0.65 0.73 0.51 55 C00099 HMDB00056 azelate (nonanedioate) 0.78 0.5088 0.79 0.69 0.67 18362 C08261 HMDB00784

4-androsten- 3beta,17beta-diol 0.61 0.5199 0.41 0.43 0.51 37202

disulfate 1 HMDB03818 succinate 0.83 0.5519 0.47 0.58 0.84 1437 C00042 HMDB00254 chiro-inositol 1.98 0.5926 0.71 0.26 0.78 37112

mandelate 0.97 0.6713 0.8 0.88 0.84 22160 CO 1984 HMDB00703 alpha-ketoglutarate 0.57 0.6922 0.27 0.97 1.4 528 C00026 HMDB00208 choline 1.75 0.7087 0.61 0.75 0.87 15506

alanylleucine 0.89 0.7604 0.94 1.85 2.29 37093

sarcosine (N-

0.87 0.7617 0.54 0.72 1.05 1516

Methylglycine) C00213 HMDB00271

L-urobilin 0.77 0.7923 1.01 0.72 0.73 40173 C05793 HMDB04159

3 -methy lglutaconate 0.87 0.798 0.25 1.1 1 0.97 38667 H DB00522 glycine 0.62 0.7987 0.28 0.55 0.56 11777 C00037 HMDB00123 taurine 0.92 0.8331 0.71 0.43 1.03 2125 C00245 HMDB00251

N-acetyltryptophan 1.26 0.8735 1.8 1.54 1.1 1 33959 C03137

malonylcarnitine 0.98 0.8741 0.86 1.09 1.1 1 37059 HMDB02095

3-hydroxyproline 0.59 0.8823 0.31 0.39 0.48 38635

1-

1.08 0.8839 0.94 1.18 1.28 32350 methylimidazoleacetate C05828 HMDB02820 scyllo-inositol 0.95 0.8954 0.61 0.5 0.55 32379 C06153 HMDB06088

N6-methyladenosine 0.97 0.9274 0.48 0.82 0.61 37114 HMDB04044

2,3-

1.07 0.9329 0.87 1.23 0.66 38276 dihydroxyisovalerate C04039

homostachydrine 1.03 0.9368 0.82 0.79 0.61 33009 C08283

dimethylglycine 0.9 0.981 0.64 0.4 0.61 5086 CO 1026 HMDB00092 pipecolate 1.01 0.9949 0.97 0.91 0.77 1444 C00408 HMDB00070 cystathionine 1 0.75 1.52 0.3 15705 C02291 HMDB00099

[00104] The biomarkers in Table 2 were used to create a statistical model to classify the subjects. Using Random Forest analysis, the biomarkers were used in a mathematical model to classify subjects as having cisplatin-induced kidney injury (AKI) or no kidney injury (No AKI). The Random Forest results showed that the subjects were classified with 66% prediction accuracy. The confusion matrix presented in Table 3 shows the number of samples predicted for each classification and the actual in each group (cisplatin-induced kidney injury or no kidney injury). The "Out-of-Bag" (OOB) Error rate gives an estimate of how accurately new observations can be predicted using the Random Forest model (e.g., whether a sample is from a subject with cisplatin-induced kidney injury or no kidney injury). The OOB error was approximately 34%, and the model estimated that, when used on a new set of subjects, the identity of subjects with cisplatin-induced kidney injury could be predicted correctly 57% of the time and subjects with no kidney injury could be predicted 72%) of the time as presented in Table 3.

Table 3. Results of Random Forest analysis using the biomarkers to predict acute kidney injury vs. no kidney injury 2 hours after treatment

[00105] Based on the OOB Error rate of 34%), the Random Forest model that was created predicted whether a sample was from an individual with cisplatin-induced kidney injury with about 66% accuracy by measuring the levels of the biomarkers in samples from the subject. Exemplary biomarkers for distinguishing the groups include gulono 1,4-lactone, glucuronate, isocitrate, 7-methylxanthine, 1 -methylxanthine, butyrylcarnitine, 1-methylurate, glutaroyl- carnitine, quinate, 21-hydroxypregnenoione-disulfate, beta-hydroxypyruvate, xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, glycolate (hydroxy acetate).

[00106] The Random Forest analysis demonstrated that by using the biomarkers, subjects with cisplatin-induced kidney injury were distinguished from subjects with no kidney injury with 57% sensitivity, 72% specificity, 57% PPV and 72% NPV. Example 4: Biomarkers to Diagnose Acute Kidney Injury After Twelve Hours of Cisplatin Treatment

[00107] Metabolomic analysis was carried out on urine samples to identify biomarkers to distinguish subjects with cisplatin-induced kidney injury from subjects without cisplatin-induced kidney injury. The urine samples used for the analysis were from 59 patients with stage 4 mesothelioma collected at five timepoints after lung lobectomy and the initiation of cisplatin treatment. The urine samples were collected at 24 hours after treatment (T6); 48 hours after treatment (T7); 72 hours after treatment (T8); 96 hours after treatment (T9); 120 hours after treatment (T10). The peak fold change SCr measurements shown in Figure 3 were calculated by dividing the maximum SCr measured within 7 days post-operation by the baseline SCr measurement. The earliest time that SCr reflected AKI for any subject in this cohort was at 2 days after cisplatin treatment. The timepoints used in this example (24h, 48h, 72h, 96h, 120h) represent measurable endpoints after the time when a currently available test (i.e., SCr) is able to diagnose kidney injury. At seven days post-operation, 23 patients were diagnosed as having kidney injury (AKI, n=23) and 36 patients were diagnosed as having no kidney injury (No AKI, n=36).

[00108] After the levels of metabolites were determined, the data were analyzed using t- tests to identify biomarkers that differed between subjects with kidney injury (AKI) and subjects without kidney injury (No AKI). The identified biomarkers are listed in Table 4.

[00109] Table 4 includes, for each biomarker, the biochemical name of the biomarker, the fold change (FC) of the biomarker in 1) AKI compared to No AKI 24 hours after treatment, 2) AKI compared to No AKI 48 hours after treatment, 3) AKI compared to No AKI 72 hours after treatment, 4) AKI compared to No AKI 96 hours after treatment, 5) AKI compared to No AKI 120 hours after treatment and the p-value determined in the statistical analysis of the data concerning the biomarkers for AKI compared to No AKI 24 hours after treatment. The fold changes where p<0.1 are indicated in bold font in Table 4. Table 4 also lists the following: the internal identifier for that biomarker compound in the in-house chemical library of authentic standards (CompID); the identifier for that biomarker compound in the Kyoto Encyclopedia of Genes and Genomes (KEGG), if available; and the identifier for that biomarker compound in the Human Metabolome Database (HMDB), if available. Table 4. Biomarkers for diagnosis of acute kidney injury

48h 72h 96h T120h

AKI/ AKI/ AKI/ AKI/

24h AKI

48h 72h 96h 120h

24h No AKI

No No No No

AKI AKI AKI AKI

Comp

Biochemical Name FC P-value FC FC FC FC KEGG HMDB

ID

trigonelline (N¹-

0.98 0.9696 0.56 0.33 0.66 0.43 32401 methylnicotinate) HMDB00875

3-methylhistidine 0.77 0.4655 0.67 0.51 0.57 0.82 15677 C01 152 HMDB00479 gamma-glutamylleucine 0.48 0.0715 0.46 0.85 0.73 1.09 18369 HMDB11 171 homovanillate sulfate 1.48 0.0588 2.31 8.75 6.06 6.18 38349

1-

1.61 0.0003 1.42 1.57 1.41 1.72 32350 methylimidazoleacetate C05828 HMDB02820

1-methylurate 1.56 0.0005 1.72 1.83 1.45 1.73 34395 HMDB03099 androsterone sulfate 0.34 0.0005 0.41 0.55 0.48 0.7 31591 C00523 HMDB02759 alanylleucine 4.2 0.0007 1.69 2 3.51 1.44 37093

threonylleucine 3 0.0008 1.48 1.92 3.65 1.35 40051

phenylacetylglutamine 1.7 0.0009 1.36 1.46 1.41 1.4 35126 C05597 HMDB06344 isoleucylphenylalanine 1.9 0.0015 1.4 1.79 2.28 1.67 40067

glucono- 1 ,5-lactone 2.2 0.0017 1.74 2.55 0.38 1.47 32355 C00198 HMDB00150 quinolinate 1.53 0.002 1.43 1.42 1.65 1.36 1899 C03722 HMDB00232

2-hydroxyisobutyrate 0.55 0.0023 0.56 2.26 1.58 3.34 22030 HMDB00729 neopterin 1.44 0.0025 1.39 1.37 1.16 1.24 35131 C05926 HMDB00845 andro steroid

0.28 0.0037 0.42 0.59 0.44 0.48 32792 monosulfate 2 C04555 HMDB02759 lactate 1.9 0.0038 2.27 5.49 1.84 2.21 527 COO 186 HMDB00190

N-formylmethionine 0.47 0.0042 0.55 0.84 0.75 1.31 2829 C03145 HMDB01015

2-hydroxyphenylacetate 0.34 0.0054 0.65 1.02 0.44 0.98 11837 C05852 HMDB00669

4-acetamidobutanoate 1.77 0.0059 1.4 1.51 1.21 1.44 1558 C02946 HMDB03681

N6-acetyllysine 0.69 0.0073 0.75 0.77 0.75 0.94 36752 C02727 HMDB00206 citrate 0.5 0.0075 0.68 0.83 0.61 1.13 1564 C00158 HMDB00094

1-methylhistidine 0.55 0.0098 0.63 0.87 0.85 1.25 30460 C01152 HMDB00001 thymine 0.57 0.0101 0.59 0.71 0.56 0.91 604 COO 178 HMDB00262 glucuronate 1.69 0.0122 1.3 1.52 1.52 1.39 15443 C00191 HMDB00127

3 -hydroxyisobutyrate 0.6 0.0123 0.55 0.8 0.61 1.05 1549 C06001 HMDB00336

HMDB

vanilpyruvate 1.5 0.0127 1.24 1.51 1.15 0.95 40087

11714

4-androsten- 3beta,17beta-diol 0.61 0.0138 0.58 0.78 0.75 1.04 37203

disulfate 2 HMDB03818 sebacate (decanedioate) 0.33 0.0162 0.58 0.7 0.15 0.39 32398 C08277 HMDB00792

Isobar: sorbitol, 11.34 0.0165 72.97 37.59 6.69 4.72 33004 C00392, HMDB00247 mannitol CO 1722,

CO 1697,

C01489,

C00794,

CO 1507

N2,N2-

1.37 0.0165 1.1 1.12 1.02 1.12 35137 dimethylguanosine HMDB04824

3-hydroxy-2-

0.57 0.0167 0.53 0.71 0.51 0.85 32397 ethylpropionate HMDB00396

3-hydroxyproline 0.24 0.0168 0.36 0.83 0.49 0.62 38635

N-acetylisoleucine 0.7 0.0171 0.73 0.77 0.81 0.81 33967

N-methyl proline 0.64 0.0175 0.97 0.41 0.29 0.4 37431

N-acetylleucine 0.67 0.0177 0.59 0.68 0.83 0.69 1587 C02710 HMDB 1 1756

N-acetylglutamine 0.61 0.0178 0.68 0.8 0.68 0.77 33943 C02716 HMDB06029

3 -hydroxy seb acate 1.64 0.0188 1.09 1.21 2.07 1.04 31943 HMDB00350 butyrylglycine 0.61 0.0192 0.97 0.68 0.49 0.72 31850 HMDB00808

N4-acetylcytidine 0.73 0.0196 0.91 1.13 0.98 1.38 35130 HMDB05923

N-acetylasparagine 0.64 0.0198 0.75 0.75 0.78 0.85 33942 HMDB06028 cystathionine 0.61 0.0199 0.61 0.45 0.52 0.29 15705 C02291 HMDB00099

N 1 -Methyl-2-pyridone-

1.81 0.0199 1.61 1.37 1.33 1.45 40469

5-carboxamide C05842 HMDB04193 pyridoxal 1.33 0.02 1.44 1.45 1.65 1.37 1651 C00250 H DB01545

3 -methy lcrotonylglycine 1.56 0.0205 1.16 1.13 1.19 1.04 31940 HMDB00459

Isobar: pimelate, 3-

1.34 0.0207 1.1 1.06 1.02 1.26 36769 methyladipate

N6- carbamoylthreonyladen 1.34 0.021 1 1 1.18 0.91 1.48 35157

osine

N-acetylthreonine 0.72 0.0219 0.69 0.75 0.78 0.95 33939 COl l 18

stachydrine 0.6 0.022 0.61 0.65 0.8 1 34384 C10172 HMDB04827 kynurenate 1.64 0.024 1.28 1.34 1.26 1.3 1417 C01717 HMDB00715 beta-hydroxypyruvate 1.55 0.025 0.8 1.14 1.15 1.27 15686 COO 168 HMDB01352 dimethylglycine 0.54 0.0257 0.48 0.85 0.45 1.1 5086 C01026 HMDB00092 leucylleucine 1.54 0.0268 0.9 1.56 1.78 2.08 36756 C11332

glucarate (saccharate) 1.24 0.0276 1.37 1.98 1.76 1.97 1476 C00818 HMDB00663

3-oxoadipate 3.02 0.0297 2.12 2 2.47 2.06 38311 C00846 HMDB00398

N2-methylguanosine 0.8 0.0308 0.85 0.82 0.66 0.9 35133 HMDB05862

3 -hydroxyanthranilate 0.64 0.0321 0.58 0.74 0.47 0.97 32353 C00632 HMDB01476 cortisone 1.28 0.0329 1.15 1.07 1.14 1 1769 C00762 HMDB02802

C02612,

citramalate 1.5 0.0342 1.02 1.02 1.1 1.38 22158

C00815 HMDB00426

3 -hydroxykynurenine 0.51 0.0343 0.55 0.62 0.83 0.95 221 10 C02794 HMDB00732

2-methylbutyrylglycine 1.33 0.0374 1.15 1.1 0.96 1.05 31928 HMDB00339

N-acetylvaline 0.72 0.0395 0.61 0.87 0.82 1 1591 HMDB 1 1757 dehydroisoandrosterone

0.27 0.0407 0.5 0.77 0.53 0.45 32425 sulfate (DHEA-S) C04555 HMDB01032 valylleucine 2.24 0.0414 1.25 1.32 1.44 0.89 39994

homocitrate 0.75 0.0424 0.52 1.03 0.83 1.12 39601 C01251 HMSB03518 taurine 0.39 0.0425 0.25 0.33 0.51 0.31 2125 C00245 HMDB00251

N-acetyl-beta-alanine 0.69 0.0426 0.81 0.69 0.48 0.84 37432 CO 1073

12-dehydrocholate 0.74 0.0436 0.35 1.16 0.51 0.66 31887 HMDB00400

7-methylxanthine 0.63 0.0472 0.86 0.64 2.15 1.76 34390 C16353 HMDB01991 creatinine 1.33 0.0472 1.1 1.15 1.22 1.4 513 C00791 HMDB00562

4-androsten- 3beta, 17beta-diol 0.53 0.0477 0.4 0.68 0.52 0.68 37202

disulfate 1 HMDB03818 h danto in-5 -prop ionic

1.44 0.0505 1.38 1.36 1.28 1.16 40473 acid C05565 HMDB01212

2-aminoadipate 0.72 0.0526 0.67 0.62 0.52 0.69 6146 C00956 HMDB00510 levulinate (4-

2.01 0.0539 1.55 1.06 1.34 1.48 22177 oxovalerate) HMDB00720

3-hydroxymandelate 7.56 0.0546 16.48 4.66 3.87 0.7 22112 HMDB00750

4-aminohippurate 0.72 0.0563 0.78 1.52 1.05 1.83 32406 D01421 HMDB01867 homocitrulline 0.79 0.0577 0.89 0.98 0.76 0.94 22138 C02427 HMDB00679 methyl indole-3 -acetate 0.64 0.059 1.45 0.75 0.94 3.38 1584

tigloylglycine 1.43 0.0682 0.99 0.93 0.83 0.83 1598 HMDB00959 phenyllactate (PLA) 0.61 0.0687 0.66 0.77 0.97 0.92 22130 C05607 HMDB00779 pyroglutamine 0.6 0.0694 0.95 0.92 0.91 1.46 32672

beta-hydroxyisovalerate 0.79 0.0702 0.77 0.8 0.68 0.91 12129 HMDB00754 uracil 0.82 0.0715 0.66 0.7 0.72 0.81 605 COO 106 HMDB00300 homostachydrine 0.71 0.075 0.72 0.76 0.64 1.22 33009 C08283

6-sialyl-N-

1.27 0.0752 1.15 1.33 1.11 1.3 40428 acetyllactosamine HMDB06584 threonylphenylalanine 2.67 0.0801 2.32 1.44 1.45 0.38 31530

sarcosine (N-

1.46 0.0836 1.1 1 1.5 1.32 1.96 1516

Methylglycine) C00213 HMDB00271 gamma-glutamylvaline 0.8 0.0867 0.75 0.85 0.76 0.85 32393 HMDB 1 1 172

5-oxoproline 1.21 0.0894 1.02 1.2 1.04 1.15 1494 C01879 HMDB00267 kynurenine 0.67 0.0934 0.73 0.87 0.78 1.12 15140 C00328 HMDB00684 cinnamoylglycine 1.39 0.0961 1.69 1.5 1.41 0.8 38637

pregn steroid

1.53 0.1058 1.15 1.09 0.8 0.79 32619 monosulfate CI 8044 HMDB00774 succinylcarnitine 1.17 0.1242 1.08 1.16 1.1 1 1.21 37058

C-glycosyltryptophan 1.22 0.1355 1.05 1.12 0.87 1.33 32675

N-acetyltryptophan 1.49 0.1524 1.17 1.25 22.12 1.42 33959 C03137

N-(2-furoyl)glycine 1.14 0.1534 1.39 0.32 0.35 1.85 31536 HMDB00439

3-sialyllactose 1.26 0.1663 1.18 1.46 1.36 1.34 40424 HMDB00825 cis-4-decenoyl carnitine 0.92 0.1731 0.71 0.86 0.6 0.76 38178

choline 0.91 0.1748 0.84 0.9 0.89 1.09 15506

gulono-l,4-lactone 1.22 0.1775 0.98 1.3 1.12 1.34 33454 CO 1040 HMDB03466

[00110] The biomarkers in Table 4 were used to create a statistical model to classify subjects. Using Random Forest analysis, the biomarkers were used in a mathematical model to classify subjects as having cisplatin-induced kidney injury (AKI) or no kidney injury (No AKI). The Random Forest results showed that the subjects were classified with 78% prediction accuracy. The confusion matrix presented in Table 5 shows the number of samples predicted for each classification and the actual in each group (cisplatin-induced kidney injury or no kidney injury). The "Out-of-Bag" (OOB) Error rate gives an estimate of how accurately new observations can be predicted using the Random Forest model (e.g., whether a sample is from a subject with cisplatin-induced kidney injury or no kidney injury). The OOB error was approximately 22%, and the model estimated that, when used on a new set of subjects, the identity of subjects with cisplatin-induced kidney injury could be predicted correctly 78% of the time and subjects with no kidney injury could be predicted 78% of the time as presented in Table 5.

Table 5. Results of Random Forest analysis using biomarkers to classify subjects as having acute kidney injury or no kidney injury 24 hours after treatment

[00111] Based on the OOB Error rate of 22%, the Random Forest model that was created predicted whether a sample was from an individual with cisplatin-induced kidney injury with about 78% accuracy by measuring the levels of the biomarkers in samples from the subject. Exemplary biomarkers for distinguishing the groups include threonylleucine, alanylleucine, N6- acetyllysine, andro-steroid-monosulfate-2, 1-methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5-carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2-hydroxyisobutyrate, 1 -methylhistidine, 1- methylurate, hexaethylene-glycol, 4-acetamidobutanoate, N-acetlyisoleucine, and citrate.

[00112] The Random Forest analysis demonstrated that by using the biomarkers, subjects with cisplatin-induced kidney injury were distinguished from subjects with no kidney injury with 78% sensitivity, 78% specificity, 69%, PPV and 85% NPV.

Example 5: Biomarkers to monitor progression of acute kidney injury

[00113] Metabolic profiling analysis was performed to determine the effect of cisplatin on the levels of exemplary biomarkers over time. Urine samples were collected from 60 subjects at ten time-points for metabolic profiling. The urine samples were collected at baseline (Tl, before lung lobectomy and the initiation of cisplatin treatment; n=58) and post-lung lobectomy, post- initiation of cisplatin treatment at the following time-points: T2, 2 hours after treatment, n=60; T3, 4 hours after treatment, n=57; T4, 8 hours after treatment, n=57; T5, 12 hours after treatment, n=60; T6, 24 hours after treatment, n=60; T7, 48 hours after treatment, n=60; T8, 72 hours after treatment, n=56; T9, 96 hours after treatment, n=48; T10, 120 hours after treatment, n=43.

[00114] Exemplary biomarkers for analysis were selected from Tables 1, 2, and/or 4. The exemplary biomarker levels were measured at time points Tl to T10. Figures 6A and 6B show the measured levels of the exemplary biomarkers in graphical form. In Figures 6A and 6B, the x-axis represents time (in hours) following cisplatin treatment, and the y-axis represents the relative metabolite level. Bl represents baseline measurement. Further, in the Figures, subjects with AKI are shown in broken line, and subjects with no AKI are shown in solid line. The exemplary biomarkers that were measured include the following: 2-aminoadipate, androsterone sulfate, gamma-glutamylphenylalanine, gamma-glutamylvaline, histidine, N-acetylleucine, phenylacetylglutamine, and threonine. As shown in Figures 6A and 6B, the levels of the exemplary biomarkers changed over the course of cisplatin treatment from baseline to 120 hours after treatment. Additionally, as shown, the change differed between subjects with kidney injury and subjects with no kidney injury.

[00115] While the invention has been described in detail and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that various changes and modifications can be made without departing from the spirit and scope of the invention.

Claims

Claims We claim:

1. A method of determining susceptibility of a subject to drug-induced

nephrotoxicity, the method comprising: analyzing a biological sample from the subject prior to treatment with a drug to determine the level(s) of one or more biomarkers, wherein the one or more biomarkers are selected from Table 1 ; and

comparing the level(s) of the one or more biomarkers in the sample to nephrotoxicity- positive and/or nephrotoxicity-negative reference levels of the one or more biomarkers in order to determine whether the subject is susceptible to developing nephrotoxicity.

2. The method of claim 1 wherein the one or more biomarkers are selected from the group consisting of: trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma-glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7-dimethylurate, N- acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N- acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl-carnitine, Nl-methylguanosine, phenol sulfate, gamma-glutamyltyrosine, mandelate, Cortisol, N-methyl proline, homocitrate, 7,8-dihydroneopterin, 3-dehydrocarnitine, pantothenate, 1 -methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7-methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma- glutamylthreonine, N6-acetyllysine, isobutyrylcarnitine, 3-methyl-2-oxovalerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, and pregnen-diol disulfate.

3. The method of claim 2, wherein the method comprises analyzing the biological sample to determine the level of two or more biomarkers selected from the group consisting of: trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma- glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7-dimethylurate, N-acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N-acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl- carnitine, Nl -methyl guanosine, phenol sulfate, gamma-glutamyltyrosine, mandelate, Cortisol, N- methyl proline, homocitrate, 7,8-dihydroneopterin, 3-dehydrocarnitine, pantothenate, 1- methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7- methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma-glutamylthreonine, N6- acetyllysine, isobutyrylcarnitine, 3 -methyl-2-oxo valerate, tyramine, homocitrulline,

tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, and pregnen-diol disulfate.

4. The method of claim 2, wherein the method comprises analyzing the biological sample to determine the level of three or more biomarkers selected from the group consisting of: trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma- glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7-dimethylurate, N-acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N-acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl- carnitine, Nl-methylguanosine, phenol sulfate, gamma-glutamyltyrosine, mandelate, Cortisol, N- methyl proline, homocitrate, 7,8-dihydroneopterin, 3-dehydrocarnitine, pantothenate, 1- methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7- methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma-glutamylthreonine, N6- acetyllysine, isobutyrylcarnitine, 3-methyl-2-oxovalerate, tyramine, homocitrulline,

tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, and pregnen-diol disulfate.

5. The method of claim 1 , wherein the method comprises analyzing the biological sample to determine the level of two or more biomarkers selected from Table 1.

6. The method of claim 1, wherein the method comprises analyzing the biological sample to determine the level of three or more biomarkers selected from Table 1.

7. The method of claim 1, wherein the sample is analyzed using one or more techniques selected from the group consisting of mass spectrometry, ELISA, and antibody linkage.

8. The method of claim 1, wherein the method further comprises determining the subject's measurements of BUN, SCr and/or eGFR.

9. A method of classifying a subject as having low susceptibility to nephrotoxicity, intermediate susceptibility to nephrotoxicity or high susceptibility to nephrotoxicity, the method comprising:

analyzing the biological sample from the subject to determine the level(s) of one or more biomarkers, wherein the one or more biomarkers are selected from Table 1 ; and

comparing the level(s) of the one or more biomarkers in the sample to reference levels of the one or more biomarkers in order to classify the subject as having low susceptibility to nephrotoxicity, intermediate susceptibility to nephrotoxicity or high susceptibility to nephrotoxicity.

10. The method of claim 9 wherein the one or more biomarkers are selected from the group consisting of: trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma-glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7-dimethylurate, N- acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N- acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl-carnitine, Nl -methyl guanosine, phenol sulfate, gamma-glutamyltyrosine, mandelate, Cortisol, N-methyl proline, homocitrate, 7,8-dihydroneopterin, 3-dehydrocarnitine, pantothenate, 1-methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7-methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma- glutamylthreonine, N6-acetyllysine, isobutyrylcarnitine, 3 -methyl -2-oxo valerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta, 17beta-diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcaraitine, and pregnen-diol disulfate.

11. The method of claim 9, wherein the method comprises analyzing the biological sample to determine the level of two or more biomarkers selected from Table 1 and/or the group consisting of trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma- glutamylleucine, homovanillate-sulfate, butyryl carnitine, 3,7-dimethylurate, N-acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N-acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl- carnitine, Nl-methylguanosine, phenol sulfate, gamma-glutamyltyrosine, mandelate, Cortisol, N- methyl proline, homocitrate, 7,8-dihydroneopterin, 3-dehydrocarnitine, pantothenate, 1- methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7- methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma-glutamylthreonine, N6- acetyllysine, isobutyrylcarnitine, 3 -methyl-2-oxo valerate, tyramine, homocitrulline,

tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l ,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, and pregnen-diol disulfate.

12. The method of claim 9, wherein the method comprises analyzing the biological sample to determine the level of three or more biomarkers selected from Tables 1 and/or the group consisting of trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma-glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7-dimethylurate, N- acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N- acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl-carnitine, Nl-methylguanosine, phenol sulfate, gamma-glutamyltyrosine, mandelate, Cortisol, N-methyl proline, homocitrate, 7,8-dihydroneopterin, 3-dehydrocarnitine, pantothenate, 1-methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7-methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma- glutamylthreonine, N6-acetyllysine, isobutyrylcarnitine, 3-methyl-2-oxovalerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, and pregnen-diol disulfate.

13. The method of claim 9, wherein the sample is analyzed using one or more techniques selected from the group consisting of mass spectrometry, ELISA, and antibody linkage.

14. The method of claim 9, wherein the comparing step comprises generating nephrotoxicity score for the subject in order to classify the subject as having high, intermediate or low susceptibility to nephrotoxicity.

15. The method of claim 9, wherein the method further comprises determining the subject's measurements of BUN, SCr and/or eGFR.

16. The method of claim 9, wherein the subject has received treatment with a therapeutic agent.

17. The method of claim 9, wherein the subject has not received treatment with a therapeutic agent.

18. A method of monitoring the progression or regression of nephrotoxicity in a subject treated with a therapeutic agent, the method comprising:

analyzing a biological sample from the subject to determine the level(s) of one or more biomarkers, wherein the one or more biomarkers are selected from Tables 1, 2, and 4 and from xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxy acetate); and

comparing the level(s) of the one or more biomarkers in the sample to nephrotoxicity progression and/or nephrotoxicity-regression reference levels of the one or more biomarkers in order to monitor the progression or regression of nephrotoxicity in the subject.

19. The method of claim 18 wherein the one or more biomarkers are selected from the group consisting of: trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma-glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7-dimethylurate, N- acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N- acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl-carnitine, Nl-methylguanosine, phenol sulfate, gamma-glutamyltyrosine, mandelate, Cortisol, N-methyl proline, homocitrate, 7,8-dihydroneopterin, 3-dehydrocarnitine, pantothenate, 1-methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7-methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma- glutamylthreonine, N6-acetyllysine, isobutyrylcarnitine, 3-methyl-2-oxovalerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, dimethylarginme (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, pregnen-diol disulfate, gulono 1 ,4-lactone, glucuronate, quinate, isocitrate, 1-methylxanthine, 1 -methylurate, 21-hydroxypregnenoione-disulfate, beta- hydroxypyruvate, threonylleucine, alanylleucine, andro-steroid-monosulfate-2, 1 - methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5- carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2- hydroxyisobutyrate, 1 -methylhistidine, 4-acetamidobutanoate, N-acetlyisoleucine, citrate, N2- methylguanosine, xylose, stachydrine, N4-acetylcytidine, tryptophan betaine, N-acetylvaline, thymine, 1-methylimidazoleacetate, quinolinate, Isobar: sorbitol, mannitol, pyridoxal, xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxyacetate).

20. The method of claim 18, wherein the sample is analyzed using one or more techniques selected from the group consisting of mass spectrometry, ELISA, and antibody linkage.

21. The method of claim 18, wherein the comparing step comprises generating a nephrotoxicity score for the subject in order to classify the subject as having a high, moderate or low level of nephrotoxicity.

22. The method of claim 18, wherein the comparing step comprises generating an nephrotoxicity score for the subject in order to monitor the progression or regression of nephrotoxicity in the subject.

23. A method for diagnosing or aiding in the diagnosis of nephrotoxicity in a subject treated with a therapuetic agent, the method comprising:

obtaining a biological sample from a subject;

analyzing the biological sample from the subject to determine the level(s) of one or more biomarkers, wherein the one or more biomarkers are selected from Tables 1, 2, and 4 and from xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxyacetate); and

comparing the level(s) of the one or more biomarkers in the sample to nephrotoxicity- positive and/or nephrotoxicity-negative reference levels of the one or more biomarkers in order to diagnose or aid in diagnosing nephrotoxicity in a subject treated with a therapeutic agent.

24. The method of claim 23 wherein the one or more biomarkers are selected from the group consisting of: trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma-glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7-dimethylurate, N- acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N- acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl-carnitine, Nl-methylguanosine, phenol sulfate, gamma-glutamyltyrosine, mandelate, Cortisol, N-methyl proline, homocitrate, 7,8-dihydroneopterin, 3-dehydrocamitine, pantothenate, 1 -methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7-methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma- glutamylthreonine, N6-acetyllysine, isobutyrylcarnitine, 3-methyl-2-oxovalerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta, 17beta-diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, pregnen-diol disulfate, gulono 1 ,4-lactone, glucuronate, quinate, isocitrate, 1 -methylxanthine, 1-methylurate, 21-hydroxypregnenoione-disulfate, beta- hydroxypyruvate, threonylleucine, alanylleucine, andro-steroid-monosulfate-2, 1- methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5- carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2- hydroxyisobutyrate, 1 -methylhistidine, 4-acetamidobutanoate, N-acetlyisoleucine, citrate, N2- methylguanosine, xylose, stachydrine, N4-acetylcytidine, tryptophan betaine, N-acetylvaline, thymine, 1 -methylimidazoleacetate, quinolinate, Isobar: sorbitol, mannitol, pyridoxal, xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxyacetate).

25. The method of claim 23, wherein the method comprises analyzing the biological sample to determine the level of two or more biomarkers selected from Tables 1, 2, 4 and/or the group of biomarkers consisting of: trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma-glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7- dimethylurate, N-acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N-acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl-carnitine, Nl-methylguanosine, phenol sulfate, gamma- glutamyltyrosine, mandelate, Cortisol, N-methyl proline, homocitrate, 7,8-dihydroneopterin, 3- dehydrocarnitine, pantothenate, 1-methylxanthine, nicotinamide, adenosine 3 ',5 '-cyclic monophosphate (cAMP), isomaltose, 7-methylxanthine, N-acetylarginine, gamma- glutamylvaline, gamma-glutamylthreonine, N6-acetyllysine, isobutyrylcarnitine, 3-methyl-2- oxovalerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta- diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, pregnen-diol disulfate, gulono 1 ,4-lactone, glucuronate, quinate, isocitrate, 1-methylxanthine, 1-methylurate, 21 -hydroxypregnenoione- disulfate, beta-hydroxypyruvate, threonylleucine, alanylleucine, andro-steroid-monosulfate-2, 1- methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5- carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2- hydroxyisobutyrate, 1 -methylhistidine, 4-acetamidobutanoate, N-acetlyisoleucine, citrate, N2- methylguanosine, xylose, stachydrine, N4-acetylcytidine, tryptophan betaine, N-acetylvaline, thymine, 1-methylimidazoleacetate, quinolinate, Isobar: sorbitol, mannitol, pyridoxal, xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glvcolate (hydroxyacetate).

26. The method of claim 23, wherein the method comprises analyzing the biological sample to determine the level of three or more biomarkers selected from Tables 1, 2, 4 and/or the group of biomarkers consisting of: trigonelline (N-methylnicotinate), 3 -methylhistidine, glutaroyl-carnitine, gamma-glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7- dimethylurate, N-acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N-acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl-carnitine, Nl-methylguanosine, phenol sulfate, gamma- glutamyltyrosine, mandelate, Cortisol, N-methyl proline, homocitrate, 7,8-dihydroneopterin, 3- dehydrocarnitine, pantothenate, 1-methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7-methylxanthine, N-acetylarginine, gamma- glutamylvaline, gamma-glutamylthreonine, N6-acetyllysine, isobutyrylcarnitine, 3-methyl-2- oxovalerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta- diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, pregnen-diol disulfate, gulono 1 ,4-lactone, glucuronate, quinate, isocitrate, 1-methylxanthine, 1-methylurate, 21-hydroxypregnenoione- disulfate, beta-hydroxypyruvate, threonylleucine, alanylleucine, andro-steroid-monosulfate-2, 1- methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5- carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2- hydroxyisobutyrate, 1 -methylhistidine, 4-acetamidobutanoate, N-acetlyisoleucine, citrate, N2- methylguanosine, 4-androsten-3beta, 17beta-diol disulfate 2, xylose, stachydrine, N4- acetylcytidine, tryptophan betaine, trigonelline (N'-methylnicotinate), N-acetylvaline, andro steroid raonosulfate 2, thymine, 1-methylimidazoleacetate, quinolinate, Isobar: sorbitol, mannitol, pyridoxal, xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxyacetate).

27. The method of claim 23, wherein the sample is analyzed using one or more techniques selected from the group consisting of mass spectrometry, ELISA, and antibody linkage.

28. A method of classifying a subject treated with a therapeutic agent as having a low level of nephrotoxicity, a moderate level of nephrotoxicity or a high level of nephrotoxicity, the method comprising:

analyzing the biological sample from the subject to determine the level(s) of one or more biomarkers, wherein the one or more biomarkers are selected from Tables 1, 2, and 4 and from xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxyacetate); and

comparing the level(s) of the one or more biomarkers in the sample to reference levels of the one or more biomarkers in order to classify the subject as having a low level of

nephrotoxicity, a moderate level of nephrotoxicity or a high level of nephrotoxicity.

29. The method of claim 28 wherein the one or more biomarkers are selected from the group consisting of: trigonelline (N-methylnicotinate), 3-methylhistidine, glutaroyl-carnitine, gamma-glutamylleucine, homovanillate-sulfate, butyrylcarnitine, 3,7-dimethylurate, N- acetylhistidine, sucrose, gamma-glutamylisoleucine, N(2)-furoyl-glycine, xanthurenate, N- acetyl-beta-alanine, acetylphosphate, theophylline, taurine, S-methylcysteine, glycocholate, hydroxyisovaleroyl-carnitine, Nl -methyl guanosine, phenol sulfate, gamma-glutamyltyrosine, mandelate, Cortisol, N-methyl proline, homocitrate, 7,8-dihydroneopterin, 3-dehydrocarnitine, pantothenate, 1-methylxanthine, nicotinamide, adenosine 3',5'-cyclic monophosphate (cAMP), isomaltose, 7-methylxanthine, N-acetylarginine, gamma-glutamylvaline, gamma- glutamylthreonine, N6-acetyllysine, isobutyrylcarnitine, 3-methyl-2-oxovalerate, tyramine, homocitrulline, tetrahydrocortisone, xylitol, 4-androsten-3beta,17beta-diol disulfate 1, dimethylarginine (SDMA + ADMA), glucono-l ,5-lactone, 3-hydroxyhippurate, tiglyl carnitine, 2-methylbutyroylcarnitine, pregnen-diol disulfate, gulono 1 ,4-lactone, glucuronate, quinate, isocitrate, 1-methylxanthine, 1-methylurate, 21-hydroxypregnenoione-disulfate, beta- hydroxypyruvate, threonylleucine, alanylleucine, andro-steroid-monosulfate-2, 1- methylimidazole acetate, androsterone sulfate, phenylacetylglutamine, Nl-methyl-2-pyridone-5- carboxamide, isoleucylphenylalanine, lactate, 4-androsten-3beta-17beta-diol-disulfate-2, 2- hydroxyisobutyrate, 1-methylhistidine, 4-acetamidobutanoate, N-acetlyisoleucine, citrate, N2- methylguanosine, xylose, stachydrine, N4-acetylcytidine, tryptophan betaine, N-acetylvaline, thymine, 1 -methylimidazoleacetate, quinolinate, Isobar: sorbitol, mannitol, pyridoxal, xanthine, inosine, adenosine, 2-hydroxyhippurate (salicylurate), gluconate, and glycolate (hydroxyacetate).

30. The method of claim 28, wherein the sample is analyzed using one or more techniques selected from the group consisting of mass spectrometry, ELISA, and antibody linkage.

31. The method of claim 28, wherein the comparing step comprises generating a nephrotoxicity score for the subject in order to classify the subject as having a high, moderate or low level of nephrotoxicity.

32. The method of claim 28, wherein the method further comprises determining the subject's measurements of BUN, SCr and/or eGFR.