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Kidney cancer often diagnosed at late stages when treatment options are severely limited. Thus, greater understanding of tumor metabolism leading ultimately to novel approaches to diagnosis are needed. Our laboratory has been utilizing metabolomics to evaluate compounds appearing in kidney cancer patients’ biofluids at concentrations different from control patients. Here, we collected urine samples from kidney cancer patients and analyzed them by chromatography coupled to mass spectrometry. Once normalized to control for urinary concentration, samples were analyzed by two independent laboratories. After technical validation, we now show differential urinary concentrations of several acylcarnitines as a function of both cancer status and kidney cancer grade, with most acylcarnitines being increased in the urine of cancer patients and in those patients with high cancer grades. This finding was validated in a mouse xenograft model of human kidney cancer. Biological validation shows carbon chain length-dependent effects of the acylcarnitines on cytotoxicity in vitro, and higher chain length acylcarnitines demonstrated inhibitory effects on NF-κB activation, suggesting an immune modulatory effect of these compounds. Thus, acylcarnitines in the kidney cancer urine may reflect alterations in metabolism, cell component synthesis, and/or immune surveillance, and may help explain the profound chemotherapy resistance seen with this cancer. This study shows for the first time the value of a novel class of metabolites which may lead to new therapeutic approaches for cancer and may prove useful in cancer biomarker studies. Furthermore, these findings open up a new area of investigation into the metabolic basis of kidney cancer.
A cardinal necessity of a cancer cell and ultimately of the syncytium which becomes a tumor is to obtain sufficient energy to effect and sustain rapid growth and mitotic rates. This becomes most important at the point at which the conglomerate of clonal cells takes the form of a solid mass, due not only to fast growth but also to the scarcity of blood delivery which becomes apparent later in tumor growth. For these reasons, cancer cells need to be creative in their efficient generation and use of energy derived from basic metabolism. The use of metabolomics in cancer biology is a therefore a convenient means to study these alterations such that this technique can lead to novel findings concerning tumor metabolism and can ultimately lead to biomarker discovery.
Our metabolomics studies in kidney cancer (or renal cell carcinoma; RCC) have led to the identification of carnitine derivatives as being significantly altered in the urine of affected patients. Carnitine was first discovered in beef muscle in 1905 (hence its derivation: carne = meat in Spanish) and its structure was first elucidated in 1927. The most prominent function of carnitine is to mediate fatty acid metabolism in mitochrondria. For long chain fatty acid oxidation in mitochondria, fatty acids must be first activated with CoA. Once across the outer mitochondrial membrane, the acyl group is transferred to carnitine by carnitine acyltransferase to form acylcarnitine. The acylcarnitine then is shuttled across the inner mitochondrial membrane by a translocase and the acyl group is transferred back to CoA where it undergoes β-oxidation. In addition, carnitine participates in the catabolism of the branched chain amino acids, with branched chain acylcarnitines reflecting the status of the acyl-CoA intermediates via carnitine acyltransferases.
Glycolysis and fatty acid oxidation, through acetyl-CoA, are the major entry points into the citric acid cycle and subsequent energy production through electron transport. While it has been known since the early 20th century, as the Warburg effect, that most cancer cells preferentially utilize glycolysis over other forms of energy production 1;2, it is not clear whether, in some malignancies, fatty acid oxidation may predominate or at least have a higher presence. Very recent work has in fact demonstrated that mitochondrial “uncoupling” is linked to fatty acid β-oxidation and chemotherapy resistance3-5, the latter being a common and frustrating feature of RCC. Indeed, in our previous work on RCC proteomics derived from RCC tissue6, we have shown that fatty acid β-oxidation is a prominently featured process in this disease.
We now show that several species of acylcarnitines, compounds which are required for transport of fatty acids into the inner mitochondrial membrane, appear at a higher quantity in the urine of RCC patients as compared to a set of matched control patients, and we have confirmed this finding using a mouse xenograft model of human RCC. Furthermore, we have validated this data in vitro using several RCC cell lines and show that these acylcarnitines, as a function of carbon chain length, affect cell survival and markers of inflammation. Thus, the identification of acylcarnitines in urine sheds new light on the metabolic basis for RCC and possibly other cancers, and may lead to new therapeutic approaches for RCC as well as to possible biomarkers for kidney cancer.
After approval by the appropriate Institutional Review Boards, patients were consented for the study at their pre-operative visit to the UC Davis or Sacramento VA urology clinics. Urine samples were obtained in a uniform fashion from patients by one of 3 clinical coordinators in this project, as clean catch, mid-void specimens, and were aliquoted and frozen on dry ice or at -80°C within 30 minutes of collection. RCC patients were required to have CKD2 or better kidney function (eGFR > 60 ml/min), and control patients were matched as closely as possible for age, race, and gender, and were recruited from the same urology clinics among the pool of patients being evaluated for non-kidney cancer urological conditions (Supplemental Table 1). All urines were kept at -80°C until analyzed.
Four proximal tubule epithelial cancer cell lines, ACHN, A498, 786-O, and Caki-1, and one “normal” derived kidney epithelial cell line, HK-2, were obtained from the American Type Culture Collection. ACHN, A498 and HK-2 cells were maintained in Dulbecco's modified Eagle's medium supplemented with 10% FBS, 100units/ml streptomycin, and 100 μg/ml penicillin. Caki-1 and 786-O cells were maintained in RPMI supplemented with 10% FBS, 100units/ml streptomycin, and 100μg/ml penicillin. Cells were maintained at 5% CO2 at 37°C. Carnitine (C0), acetylcarnitine (C2), and palmitoylcarnitine (C16) were purchased from Sigma (St. Louis, MO). Propionylcarnitine (C3), octanoylcarnitine (C8), and decanoylcarnitine (C10) were obtained from Tocris (UK). All carnitines were prepared by diluting into endotoxin-free water. The β-gal plasmid and 2x-Nuclear Factor κB (NF-κB) reporter plasmid containing two consensus binding sites for NF-κB driving luciferase expression were generously provided by Daniel Hwang (UC Davis, CA).
A 200 μL aliquot of cells (1 × 104 cells/ml in 1% FBS containing media) was added to a 96 well plate and incubated for 20 hr at 37 °C in a humidified incubator containing 5% CO2 in air. After incubation with appropriate acylcarnitine for 24 hours, the medium was aspirated and a 20 μL MTT solution (5 mg/mL in phosphate buffer) was mixed with 180uL 10% containing media and added to each well and the incubation continued for 3 hr. After this time the solution in each well was carefully removed. The purple crystalline precipitate in each well was dissolved in 200μl of DMSO. The visible absorbance of each well was quantified at 560 nm using a microplate reader. Significance was determined by one-way analysis of variance (ANOVA) at a p-value<0.05; the analysis was conducted using SAS 9.1.
Total mRNA was collected and cDNA synthesized using a Qiagen RNeasykit (Valencia, CA) following manufacture's protocol. The PCR primers used are shown in Supplemental Table 2. Thermal cycling conditions are as follows: 94 degrees celsius for 4 minutes followed by 35 cycles of amplification at 56 degrees for 45 seconds, 72 degrees for 1 minute, and 95 degrees for 1 minute. DNA was analyzed by 2% ethidium bromide agarose gel electrophoresis.
Normal HK-2 cells (1 × 106 cells/ml) were plated in 1% serum containing medium in a 12 well plate and incubated at 37 °C. After 24 hours, cells were transiently transfected with two plasmids using genejuice (EMD, New Jersey) following manufacturer's instructions for an additional 24 hours. Cells were then treated with endotoxin free water (vehicle) or acylcarnitines for 16 hours in 1% serum containing medium. Both luciferase and betagalactosidase enzyme activities were assessed using respective assay systems (Promega) and following manufacture's instructions. Luciferase activity was normalized by dividing by betagalactosidase activity to correct for transfection efficiency. Significance was determined by one-way analysis of variance (ANOVA) at a p-value < 0.05; the analysis was conducted using SAS 9.1.
Human Caki-1 cells (106) were mixed with 30% of matrigel (BD) and injected into the right flanks of two donor nude mice. After the tumors reached 500 mm3 of size, mice were sacrificed and tumors excised to prepare tumor cell suspension. Tumors were minced and passed through 70 μM Nylon cell strainer (BD Falcon) and washed with PBS to collect cell pellets. Tumor cells were resuspended in 30% matrigel (106 cells /20 μl /mouse) for renal subcapsule implantation. Nude mice were anesthetized with isoflurane and the kidneys were exteriorized for sub capsule injection. The sham control group of mice received no injection of tumors. After injection, the kidney was returned to the abdominal cavity and the peritoneum and skin were closed by suture and metal wound clips, respectively. Mice were sacrificed when they became moribund, 5 weeks after subcapsule implantation. Tumor and normal kidney tissues (from sham surgery animals) were removed and split for snap freezing and 10% buffered formalin fixation at sacrifice. From the frozen tissue, tumors were dissected out from adjacent non-cancerous tissue, and this as well as sham control kidneys were sent to Laboratory A for metabolomic analysis.
The acylcarnitines in the urine were profiled by two different analytical technologies: untargeted metabolomic analysis (Laboratory A) and acylcarnitine quantitation (Laboratory B).
The untargeted metabolomic analysis was performed by Laboratory A (Metabolon, Inc., Durham, NC). The metabolomic platforms, including sample extraction process, instrumentation configurations and conditions, and software approaches for data handling, were previously described in detail 7. The major components of the process are summarized as follows:
The samples were extracted using an automated MicroLab STAR® system (Hamilton Company, Salt Lake City, UT) in 400 μl of methanol, containing the recovery standards. The samples were then separated into three equal aliquots for analysis in three independent platforms as described below.
The platform consisted of three platforms: ultra-high performance liquid chromatography/tandem mass spectrometry (UHLC/MS/MS2) optimized for basic species, UHLC/MS/MS2 optimized for acidic species, and gas chromatography/mass spectrometry (GC/MS). The samples destined for GC/MS analysis were dried under vacuum desiccation for a minimum of 24 h and then derivatized under dried nitrogen using bistrimethyl-silyl-triflouroacetamide (BSTFA). The GC column was 5% phenyl and the temperature ramp was from 40° to 300° C in a 16 minute period. Samples were analyzed on a Thermo-Finnigan Trace DSQ fast-scanning single-quadrupole mass spectrometer using electron impact ionization. UPLC/MS was carried out using a Waters Acquity UHPLC (Waters Corporation, Milford, MA) coupled to an LTQ mass spectrometer (Thermo Fisher Scientific Inc., Waltham, MA) equipped with an electrospray ionization source. Two separate UHPLC/MS injections were performed on each sample: one optimized for positive ions and one for negative ions. Chromatographic separation followed by full scan mass spectra was carried out to record retention time, molecular weight (m/z) and MS/MS2 of all detectable ions presented in the samples.
Metabolites were identified by automated comparison of the ion features in the experimental samples to a reference library of chemical standard entries that included retention time, molecular weight (m/z), preferred adducts, and in-source fragments as well as their associated MS/MS2 spectra. This library allowed the rapid identification of metabolites in the experimental with high confidence. For ions that were not covered by the standards, additional library entries were added based on their unique ion signatures (chromatographic and mass spectral) and also by virtue of their recurrent nature among samples. The unknown biochemicals have the potential to be identified by future acquisition of matching purified standards or by classical structural analysis.
The acylcarnitine quantitation assay was performed by Laboratory B (Dr. C. Hoppel, Case Western Reserve University, Cleveland, OH, CLIA compliant laboratory, ID Number 36D0925804). Urine samples were thawed on ice, aliquoted, and shipped on dry ice for additional analysis. Total carnitine, free carnitine, and acylcarnitines were analyzed using 10μl of urine. A validated, highly accurate, precise and rigorously quantitative analysis method was use to quantify carnitine and individual acylcarnitines which is an extension of earlier published procedures 8;9. Carnitine and acylcarnitines were isolated by strong cation-exchange solid-phase extraction, derivatized with pentafluorophenacyl trifluoromethanesulfonate, separated by HPLC using sequential ion-exchange / reversed-phase chromatography, and detected by MS/MS using a scheduled multiple reaction monitoring (MRM) protocol with a triple quadrupole instrument. Reference standards were synthesized, purified and standardized, and then used to formulate multiple-point calibration curves. Scheduled MRM efficiently collected data from 77 transitions (65 compounds and 12 internal standards), generating 65 calibration curves containing 13 points over 200-fold concentration ranges for each acylcarnitine. The integrity of the analyses were maintained through the monitoring of quality control samples and system parameters under tight tolerance limits based on guidelines established for FDA methods used in human clinical pharmacology, bioavailability, and bioequivalence studies requiring pharmacokinetic evaluation (“Guidance for Industry - Bioanalytical Method Validation.” available at http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM070107.pdf). A representative output of this laboratory analysis is shown in the Supplemental Table 3.
Differences in mean acylcarnitine values between RCC and control patients were evaluated with permutation t-tests. Significance was determined based on a permutation null distribution of 1,000 permutations. Fisher's Least Significant Difference (LSD) tests were used to compare mean metabolite intensities among cancer grades (controls and grades 1, 2, 3). Raw intensity values were creatinine-normalized (to control for urinary concentration or dilution) for analysis and for the Laboratory A data set, values were also log2 transformed before statistical analysis. The correlations between carnitine values measured in the two different laboratories were evaluated using Spearman's rank correlation. These analyses were conducted in R 2.10 (R Development Core Team 2009).
Our initial study of urine from 29 RCC patients and 33 control patients carried out in Laboratory A (after normalization to account for urinary concentration or dilution) resulted in the identification of differential urinary concentrations of carnitine as well as 14 acylcarnitines. As technical validation, 6 RCC urines and 6 control urines all with CKD1 or 2 and randomly selected out of the original pool, were analyzed in another laboratory, Laboratory B (Supplemental Table 3). The results from these two laboratories showed a high degree of correlation (Supplemental Table 4).
In order to determine whether acylcarnitines in the urine correspond to cancer status and tumor grade, we examined these compounds as a function of (1) RCC grade and (2) the presence of RCC. Seven acylcarnitines were found to differ significantly (p<0.05) when compared among tumor grades (Fig. 1). The acylcarnitines that differed significantly between at least two tumor grades showed a similar pattern, with mean values in grade 1 tumors tending to be lower than in control patients while concentrations of these acylcarnitines steadily increased in the urine of patients with grades 2 and 3 tumors (Fig. 1). Other than free carnitine, these significantly grade-dependent acylcarnitines were those derived from both amino acid catabolism (2-methylbutyrlycarnitine, hydroxyisovalerylcarnitine, isobutyrylcarnitine, glutaroylcarnitine) and fatty acid oxidation (acetylcarnitine and propionylcarnitine). The significant differences were primarily between grade 1 tumors and the other three grades. Of the 7 significant acylcarnitines, most showed differences between controls and grade 1 tumors (6 of 7), grade 1 vs. grade 2 tumors (6 of 7) and/or grade 1 vs. grade 3 tumors (6 of 7).
We next analyzed the urinary acylcarnitines as a function of the presence or absence of RCC as compared to non-kidney cancer control patients. In this analysis, none of the acylcarnitines measured by Laboratory A achieved significance, however, the more extensive acylcarnitine data from Laboratory B showed two acylcarnitines (isobutyrylcarnitine and suberoylcarnitine) which differed significantly at a 0.05 significance level (Table 1; bolded metabolites), and two additional acylcarnitines (S-3-hydroxy-butyrylcarnitine, and acetylcarnitine) approached significance with raw p-values less than 0.1 (Table 1; italicized metabolites). Notably, 18 of the 20 acylcarnitines analyzed had higher mean concentrations in RCC patients than control patients, particularly those four acylcarnitines significant or suggestive (Table 1). Only cis-3,4-methylene-nonanoylcarnitine, a product of intestinal bacterial metabolism, and tiglylcarnitine had lower mean values in RCC patients as compared to controls.
The increased levels of acylcarnitines seen in the urine of higher grade cancer patients are likely emanating either from the tumor itself, or their appearance is the result of a systemic response to the presence of the tumor cells. The tumor tissue from the patients in this study was not available to us, so that in order to distinguish between these possibilities, we utilized a RCC xenograft nude mouse model employing subcapsular implantation of Caki-1 cells. Due to severe renal disease at the end of the experiment, the urine from these animals was not reliable, but we analyzed tumor tissue taken from these animals compared with sham operated control animals. Of the 14 acylcarnitines (and carnitine) which were significantly altered in the tumor tissue (measured in laboratory A), 11 were increased (Table 2). While it would not be expected that the specific urinary acylcarnitines derived from patients with a variety of heterogenous human tumors would necessarily correlate with those seen in the Caki-1 mouse model, six acylcarnitines (acetylcarnitine, isobutyrylcarnitine, isovalerylcarnitine, 2-methyl-butyrylcarnitine, propionylcarnitine, and succinylcarnitine) which were significantly elevated in xenograft tissue were also increased in human urine, suggesting the likelihood of a tumoral original of the acylcarnitines.
During fatty acid metabolism through β-oxidation, each acyl-CoA is progressively dehydrogenated such that long-chain acyl-CoA esters are eventually metabolized to short-chain esters. Within the mitochondria, ATP is generated in a process which, at the end of each cycle, generates a new acyl-CoA, which is 2 carbon atoms shorter than its predecessor, plus an acetyl-CoA ester (reviewed in 10). Similarly, the catabolism of branched chain amino acids and lysine also involves acyl-CoA as intermediates. Most acyl-CoA metabolites can be converted to the corresponding acylcarnitine by carnitine acyltransferases 17.
In order to determine whether the acylcarnitines which appear in the urine of RCC patients, prior to their exit from the kidneys, are influencing growth of cancer cells, we examined separately the effect of long, intermediate, and short chain length acylcarnitines in several RCC cell lines. Several straight chain acylcarnitines were utilized in MTT (survival) assays, as those particular acylcarnitines were commercially available. After 24 h of acylcarnitine incubation at micromolar concentrations, there was minimal effect of the acylcarnitines regardless of chain length. However, at concentrations greater than 25 uM, there was consistent cytotoxicity of the highest chain-length acylcarnitine examined (palmitoylcarnitine; C16) in all 4 RCC cell lines and less pronounced toxicity in a normal proximal tubular epithelial-derived cell line HK-2 (Fig. 2). The p53 status did not appear to be significant, as 786-O is VHL mutant and thus p53 inactive while Caki-1 is p53 wt; these cells behaved similarly when incubated with acylcarnitines.
For many years before the discovery of targeted chemotherapy with kinase inhibitors, the treatment of RCC involved immune modulators such as interferon and the interleukins. While these therapies were not particularly efficacious (reviewed in 11), the occasional response with these agents suggests that immune surveillance may play some role in the pathogenesis of this cancer. For these reasons, we next attempted to validate our data by asking whether the acylcarnitines, as emanating from RCC and appearing in the urine, are involved in immune system modulation. NF-κB, a family of transcription factors that regulates both induction and resolution of inflammation in the kidney and other organs (reviewed in 12), has been shown to be activated by at least some acylcarnitines of varying chain lengths13. Since the toll-like receptors (TLRs), especially TLR414 and TLR615, expressed on tumor cells and within the kidney may be at least part of the mechanism by which these cancers avoid the immune system through NF-κB activation, we first examined the expression of TLRs 1, 4, and 6 in the RCC cell lines. All 4 cell lines examined in this study expressed TLRs 1, 4, and 6 as measured by RT-PCR (Fig. 3), thus the standard mechanism exists in these cells for NF-κB activation by means of transmembrane spanning receptors.
NF-κB is held in an inactive form in the cytosol when bound by inhibitor proteins (IκB). Upon phosphorylation and subsequent proteosomal degradation of these inhibitor proteins by the IKK complex, NF-κB is free to translocate to the nucleus where many target genes are regulated. Among its many functions, the NF-κB family of nuclear receptors is most widely studied in the context of inflammation. To measure NF-κB activation, immortalized proximal tubule epithelial cell line HK-2 from a normal human kidney16 were transfected with a reporter plasmid concurrently with a plasmid with two consensus binding sites for NF-κB driving luciferase expression. After proteosomal degradation of the inhibitor proteins, active NF-κB is free to bind to the consensus binding site upstream of luciferase which would result in increased luciferase expression. By exposing the normal cells to elevated levels of the different acylcarnitines, the cells are effectively in the same environment as tumor cells with respect to acylcarnitine content. Exposure to acetylcarnitine (C2 chain length) shows a small, but not significant, increase in NF-κB transcription with a p-value of 0.29 (Fig. 4A), while exposure to propionylcarnitine (C3 chain length), which is increased in tumor tissue as well as human urine, inhibits on NF-κB induction from 25 μM, a dose that is not cytotoxic as demonstrated by the MTT assay (Fig. 4B, compare Fig. 2d). The longest chain length carnitine examined, palmitoylcarnitine (C16 chain length), which was increased 4.6-fold in mouse tumor (although not found in urine likely due to hydrophobicity), showed the most potent inhibition of NF-κB induction: a dose of 5μM is sufficient to reduce NF-κB induction by roughly forty percent compared to the vehicle treated control. Thus, the acylcarnitines emanating from kidney cancers may function to decrease the inflammatory response, providing a mechanism by which these cells are able to evade immune surveillance. Further experiments to examine more details of the immune modulatory response are currently underway in our laboratory.
There currently exist no serological or urinary signatures for RCC, such that this disease is frequently discovered at later stages when the chances for recovery are grim. The use of urine metabolomics to discover novel metabolic pathways leading ultimately to biofluid signatures of RCC has shown promise in our earlier work17;18, and we now extend this research to show that acylcarnitines, which are intermediates in the key energy metabolic pathways of fatty acid β-oxidation and amino acid catabolism, appear at different quantities in the urine of RCC patients as compared to matched control patients without RCC. While our data is premature at this point to indicate that acylcarnitines will be useful as biomarkers, the identification of the signature of a novel metabolic pathway in RCC is, we believe, the strength of our study. While there exist a small number of extant studies of biofluid carnitine profiles in cancer patients, those available studies 19;20 were carried out in patients who had already had chemotherapy so that the findings thus reported may not be indicative of tumors in their native state but may indicate the effects of toxic drugs. Given the variation inherent in any metabolomics study as a function of site of collection and handling of specimens as we have confirmed in our laboratory17, these parameters were kept extremely consistent in our study in order to minimize variation which is a common and often poorly addressed problem in metabolomics. To our knowledge, ours is the first published description of acylcarnitine changes in any untreated cancer, and in particular, in kidney cancer.
The Warburg effect describes a feature of many tumor cells to preferentially undergo glycolysis to produce ATP rather than using the oxidative capacity of the mitochondria for energy production 22. Interestingly, increased cellular levels of acylcarnitines indicate a higher degree of fatty acid metabolism, since mitochondria β-oxidation of fatty acids occurs in a stepwise fashion upon acyl-CoA intermediates. Indeed, in a proteomics analysis of human RCC tissue, we have previously observed that fatty acid β-oxidation is a highly represented metabolic process6, and others have shown increased fatty acid β-oxidation in prostate cancer 21 and colon cancer 22. From a biochemical perspective, it has been recently demonstrated that those cancers which exhibit the transition to aerobic respiration in conjunction with elevated mitochondrial fatty acid oxidation, as would be expected to occur in the presence of high levels of acylcarnitines, are highly chemoresistant due to a decrease in the mitochondrial permeability transition3;5; such a finding is entirely consistent with the data presented in this study and might explain this clinically challenging property of chemoresistance in RCC. Also, for this reason, inhibitors of fatty acid β-oxidation are currently being evaluated in our laboratory to test whether they have salutary effects on RCC cells in vitro.
Another possibility for our observation of increased acylcarnitines in RCC patients’ urine is that these compounds are appearing as a signature of branched-chain amino acid (BCAA) metabolism 23. It is conceivable that due to the demands of increasing rates of cell proliferation due to the tumor, there exists a higher requirement for nutrients including BCAAs. Whatever the reason, the changes in acylcarnitines in RCC indicate alterations in key metabolic pathways related to cell proliferation and energy metabolism in the tumor, and these metabolic changes may profoundly impact chemotherapy resistance.
In the cell survival assays shown in this study, several patterns emerge with respect to cell line and acylcarnitine chain length. Incubation of cells with the longest chain acylcarnitine (C16: palmitoylcarnitine) resulted in significant reduction in cell survival in the cancer cell lines, but the HK-2 cells which were derived from normal adult human kidney16 were the least sensitive to this compound. The variation in response between cell lines may reflect the importance of genetic background in cellular response. However, the cytotoxity of the acylcarnitines observed in this study is consistent with acylcarnitines’ known adverse effects. For example, palmitoylcarnitine at micromolar concentration can cause metabolic, electrical, and mechanical cardiac malfunction 24-26. Thus, from our data it appears likely that RCCs must juggle the cytotoxic effects of the long chain length acylcarnitines with their immune modulatory effects and mitochondrial uncoupling effects. Indeed, inhibition of NF-κB activation offers protection from cell death, promotion of apoptosis, or decrease in inflammatory signaling, any of which is beneficial for tumor cell survival27.
Our findings suggest that urinary acylcarnitine appearance varies widely as a function of tumor grade, with grade 1 tumors having consistently lower levels of acylcarnitines as compared to both normal tissue as well as higher grade tumors. Obviously, this finding negatively impacts the possibility of using acylcarnitines as early RCC biomarkers (unless they prove to be useful as lower than control in early stage disease after validation), however the consistent increase in urinary acylcarnitines with high grade as compared to low grade tumors, besides contributing to the basic knowledge of RCC metabolism, may lead to these compounds being useful for classification of tumor behavior and response to therapy. A possible explanation for these changes is that highly undifferentiated cells (as would be seen in higher grade tumors) require more energy and hence more fatty acid β-oxidation to sustain higher rates of cell division and growth, as compared to lower grade tumors. Indeed, in our proteomic study of RCC tissues 6, c-Myc, a global regulator of cell division and apoptosis, was overexpressed in a grade dependent fashion.
In summary, we have shown that urinary acylcarnitines are increased in a grade-dependent fashion in the urine of kidney cancer patients and, based on a mouse xenograft RCC model, these compounds are likely emanating from the tumor tissue itself. Validation experiments show that acylcarnitines have both cytotoxicity and immune modulatory properties which could be beneficial to the tumor in terms of growth and survival in situ. Further work in our laboratory is focused on translating these findings into biomarkers as well as furthering the understanding of fatty acid β-oxidation and possible mitochondrial uncoupling as it relates to RCC pathogenesis and chemoresistance in order to introduce new therapeutic paradigms.
We thank Maria Stoll and Paul Minkler for the quantitative acylcarnitine analysis. This work was supported by NIH grants UL1 RR024146 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research; NIH grants 5UO1CA86402 (Early Detection Research Network), 1R01CA135401-01A1, and 1R01DK082690-01A1 (all to R.H.W.), and the Medical Service of the US Department of Veterans’ Affairs (R.H.W.).