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To improve treatment outcomes in real practice, useful biomarkers are desired when predicting postoperative recurrence for renal cell carcinoma (RCC). We collected data from patients who underwent definitive surgery for RCC and for benign urological tumor at our department between November 2016 and December 2019. We evaluated the differences in pre‐ and postoperative urinary metabolites with our precise quantitative method and identified predictive factors for RCC recurrence. Additionally, to clarify the significance of metabolites, we measured the intracellular metabolite concentration of three RCC cell lines. Among the 56 patients with RCC, nine had a recurrence (16.0%). When comparing 27 patients with T1a RCC and 10 with benign tumor, a significant difference was observed between pre‐ and postoperative concentrations among 10 urinary metabolites. In these 10 metabolites, multiple logistic regression analysis identified five metabolites (lactic acid, glycine, 2‐hydroxyglutarate, succinic acid, and kynurenic acid) as factors to build our recurrence prediction model. The values of area under the receiver operating characteristic curve, sensitivity, and specificity in this predictive model were 0.894%, 88.9%, and 88.0%, respectively. When stratified into low and high risk groups of recurrence based on this model, we found a significant drop of recurrence‐free survival rates among the high risk group. In in vitro studies, intracellular metabolite concentrations of metastatic tumor cell lines were much higher than those of primary tumor cell lines. By using our quantitative evaluation of urinary metabolites, we could predict postoperative recurrence with high sensitivity and specificity. Urinary metabolites could be noninvasive biomarkers to improve patient outcome. Although the postoperative recurrence rate for nonmetastatic renal cell carcinoma (RCC) has been reported to be approximately 30%, there was no marker to predict recurrence. In this study, we evaluated urinary metabolites to identify new noninvasive biomarkers, and established a recurrence prediction model with high sensitivity and specificity by our accurate quantitative measurement system. Additionally, we undertook an in vitro study to investigate their intracellular concentrations in three RCC cell lines to understand their clinical significance.

Using surgically resected tissue, we identified characteristic metabolites related to the diagnosis and malignant status of clear cell renal cell carcinoma (ccRCC). Specifically, we quantified these metabolites in urine samples to evaluate their potential as clinically useful noninvasive biomarkers of ccRCC. Between January 2016 and August 2018, we collected urine samples from 87 patients who had pathologically diagnosed ccRCC and from 60 controls who were patients with benign urological conditions. Metabolite concentrations in urine samples were investigated using liquid chromatography‐mass spectrometry with an internal standard and adjustment based on urinary creatinine levels. We analyzed the association between metabolite concentration and predictability of diagnosis and of malignant status by multiple logistic regression and receiver operating characteristic (ROC) curves to establish ccRCC predictive models. Of the 47 metabolites identified in our previous study, we quantified 33 metabolites in the urine samples. Multiple logistic regression analysis revealed 5 metabolites (l‐glutamic acid, lactate, d‐sedoheptulose 7‐phosphate, 2‐hydroxyglutarate, and myoinositol) for a diagnostic predictive model and 4 metabolites (l‐kynurenine, l‐glutamine, fructose 6‐phosphate, and butyrylcarnitine) for a predictive model for clinical stage III/IV. The sensitivity and specificity of the diagnostic predictive model were 93.1% and 95.0%, respectively, yielding an area under the ROC curve (AUC) of 0.966. The sensitivity and specificity of the predictive model for clinical stage were 88.5% and 75.4%, respectively, with an AUC of 0.837. In conclusion, quantitative analysis of urinary metabolites yielded predictive models for diagnosis and malignant status of ccRCC. Urinary metabolites have the potential to be clinically useful noninvasive biomarkers of ccRCC to improve patient outcomes. Quantitative analysis of urinary metabolites yielded predictive models for diagnosis and malignant status of ccRCC.

BackgroundThe aim was to investigate the relationships between total sunitinib plasma concentrations (sunitinib plus its active metabolite; N-desethyl sunitinib) and clinical outcomes in Japanese patients with metastatic renal cell carcinoma (mRCC).MethodsTwenty patients with mRCC were enrolled following treatment with sunitinib. To assess safety, the total sunitinib concentration range up to discontinuation of treatment and dosage reduction associated with adverse events within 6 weeks from initiating administration were analyzed. The longest administered sunitinib dosage was defined as the maintenance dose, and the relationship between total sunitinib concentration at the maintenance dosage and sunitinib efficacy was investigated.ResultsTotal sunitinib concentration was significantly higher in patients who discontinued treatment or had dosage reduction due to adverse events within 6 weeks after initiation of sunitinib than in patients who continued treatment with the initial dosage. The time to treatment failure, progression-free survival, and overall survival were better in patients with total sunitinib concentrations < 50 ng/mL than in those with concentrations ≥ 50 ng/mL.ConclusionsThe present study demonstrated that the effective range of total sunitinib concentration in Japanese patients with mRCC was lower than 50–100 ng/mL which was previously reported. These results indicate that therapeutic drug monitoring could maintain the therapeutic effect of sunitinib while minimizing adverse events by personalizing sunitinib dosages for Japanese patients with mRCC.

Tyrosine kinase inhibitors (TKIs) play a crucial role in the treatment of advanced renal cell carcinoma (RCC). However, there is a lack of useful biomarkers for assessing treatment efficacy. Through urinary metabolite analysis, we identified the metabolites and pathways involved in TKI resistance and elucidated the mechanism of TKI resistance. To verify the involvement of the identified metabolites obtained from urine metabolite analysis, we established sunitinib-resistant RCC cells and elucidated the antitumor effects of controlling the identified metabolic pathways in sunitinib-resistant RCC cells. Through the analysis of VEGFR signaling, we aimed to explore the mechanisms underlying the antitumor effects of metabolic control. Glutamine metabolism has emerged as a significant pathway in urinary metabolite analyses. In vitro and in vivo studies have revealed the antitumor effects of sunitinib-resistant RCC cells via knockdown of glutamine transporters. Furthermore, this antitumor effect is mediated by the control of VEGFR signaling via PTEN. Our findings highlight the involvement of glutamine metabolism in the prognosis and sunitinib resistance in patients with advanced RCC. Additionally, the regulating glutamine metabolism resulted in antitumor effects through sunitinib re-sensitivity in sunitinib-resistant RCC. Our results are expected to contribute to the more effective utilization of TKIs with further improvements in prognosis through current drug therapies.

Metabolomics analysis possibly identifies new therapeutic targets in treatment resistance by measuring changes in metabolites accompanying cancer progression. We previously conducted a global metabolomics (G-Met) study of renal cell carcinoma (RCC) and identified metabolites that may be involved in sunitinib resistance in RCC. Here, we aimed to elucidate possible mechanisms of sunitinib resistance in RCC through intracellular metabolites. We established sunitinib-resistant and control RCC cell lines from tumor tissues of RCC cell (786-O)-injected mice. We also quantified characteristic metabolites identified in our G-Met study to compare intracellular metabolism between the two cell lines using liquid chromatography-mass spectrometry. The established sunitinib-resistant RCC cell line demonstrated significantly desuppressed protein kinase B (Akt) and mesenchymal-to-epithelial transition (MET) phosphorylation compared with the control RCC cell line under sunitinib exposure. Among identified metabolites, glutamine, glutamic acid, and α-KG (involved in glutamine uptake into the tricarboxylic acid (TCA) cycle for energy metabolism); fructose 6-phosphate, D-sedoheptulose 7-phosphate, and glucose 1-phosphate (involved in increased glycolysis and its intermediate metabolites); and glutathione and myoinositol (antioxidant effects) were significantly increased in the sunitinib-resistant RCC cell line. Particularly, glutamine transporter (SLC1A5) expression was significantly increased in sunitinib-resistant RCC cells compared with control cells. In this study, we demonstrated energy metabolism with glutamine uptake and glycolysis upregulation, as well as antioxidant activity, was also associated with sunitinib resistance in RCC cells.

Background Renal function and use of concomitant medications should be carefully monitored in patients subjected to treatment with direct oral anticoagulants (DOACs); the dose should be individually designed for each patient. Owing to the complex therapeutic indications and dose reduction criteria, pharmacists exercise caution when determining the optimal dose for each patient. A DOAC check sheet has been developed that is automatically printed in the dispensing room at the same time as the prescription and can be used by pharmacists to dispense DOACs promptly and correctly. The purpose of this study was to evaluate the system for dispensing DOACs using a check sheet. Methods The study was conducted at Tohoku University Hospital in Japan; prescriptions containing DOACs dispensed by the hospital pharmacists were evaluated. The DOAC check sheet described indications, dosage regimens, dose reduction criteria, and contraindications for each drug and included the patient’s information. The check sheet was set to print automatically in the dispensing room at the same time as the prescription when an inpatient was prescribed DOACs. This check sheet was evaluated using a prescription survey and a questionnaire for pharmacists. Results The usefulness of this check sheet for the correct use of DOACs was evaluated. There were four inquiries out of 642 (0.6%) prescriptions from pharmacists to physicians regarding DOAC prescriptions, such as the dose introduced before DOAC check sheet utilization, and there were 21 out of 905 (2.3%) prescriptions when the DOAC check sheet was used it, showing a significant increase ( p  = 0.0089). After the introduction of this sheet, overdoses of DOACs were identified at the time of dispensing. Of the 52 pharmacists who responded to the questionnaire, 51 (98%) stated that the check sheet was useful. Conclusion The use of the DOAC check sheet is likely to render safety to DOAC drug therapy for individual patients.

Background Everolimus is an oral inhibitor of mammalian target of rapamycin, approved for metastatic renal cell carcinoma (mRCC). Recently, personalized medicine through therapeutic drug monitoring (TDM) is recommended in cancer therapy. In this study, the relationship between everolimus blood concentration and clinical outcomes on a long-term were evaluated in Japanese patients with mRCC. Methods Patients with mRCC were enrolled following treatment with everolimus at Tohoku University Hospital between April 2012 and December 2016. The relationship between everolimus trough blood concentration on day 8 of everolimus therapy and just before discontinuation or dose reduction, and their adverse events were evaluated. Patients were divided into two groups based on the median of everolimus blood concentration on day 8 of treatment, and the profiles of adverse events, and efficacy [time to treatment failure (TTF) and progression-free survival (PFS)] were evaluated. Results The median (range) everolimus blood concentrations on day 8 after starting everolimus administration and just before discontinuation or dose reduction were 15.3 (8.1–28.0) ng/mL and 14.8 (6.4–58.4) ng/mL, respectively, with no significant difference between these values ( P  = 0.3594). Patients ( n  = 6) with discontinuation or dose reduction following adverse events in everolimus therapy had significantly higher blood concentrations than patients ( n  = 4) with dose maintenance on both day 8 (median, 18.0 vs 8.2 ng/mL; P  = 0.0139) and just before discontinuation or dose reduction (median, 22.9 vs 9.7 ng/mL; P  = 0.0142). Median TTF and PFS of the total patients ( n  = 10) were 96 days (95% confidence interval [CI], 26–288) and 235 days (95% CI, 28–291), respectively. Subgroup analysis showed that TTF of the patients with > 15.3 ng/mL ( n  = 5) was not significantly different from that of the patients with ≤15.3 ng/mL ( n  = 5; P  = 0.5622). Similarly, PFS of the patients with > 15.3 ng/mL was not significantly different from that of the patients with ≤15.3 ng/mL ( P  = 0.3436). Conclusions This study demonstrated the long-term relationship between everolimus blood level and clinical outcomes and adverse events in Japanese patients with mRCC. Thus, TDM in everolimus therapy could be a useful tool for the early prediction of adverse events for Japanese patients with mRCC.

Background Mycophenolic acid (MPA) treatment requires therapeutic drug monitoring to improve the outcome after organ transplantation. The aim of this study was to compare two methods, a particle enhanced turbidimetric inhibition immunoassay (PETINIA) and a reference liquid chromatography tandem mass spectrometry (LC-MS/MS) for determining plasma MPA concentrations from Japanese lung transplant recipients. Methods Plasma MPA concentrations were determined from 20 Japanese lung transplant recipients using LC-MS/MS and the PETINIA on the Dimension Xpand Plus-HM analyzer. Results The mean MPA concentration measured by PETINIA was significantly higher than that measured by LC-MS/MS (3.26 ± 2.73 μg/mL versus 2.82 ± 2.71 μg/mL, P  < 0.0001). The result of the Passing Bablok analysis was a slope of 1.104 (95% confidence interval [CI], 1.036–1.150) and an intercept of 0.229 (95%CI, 0.144–0.315). Bland–Altman analysis revealed PETINIA overestimates plasma MPA concentration by 26.25% and 95%CI from 21.43 to 31.07%. Conclusion The measurement of MPA by the PETINIA in Japanese lung transplant patients should evaluate the result with attention to positive bias.

Paclitaxel is one of the most extensively used anticancer agents, however, its use is often limited by severe hypersensitivity reactions, including respiratory distress, bronchospasm, and hypotension, which can occur despite premedication with dexamethasone and histamine H1 and H2 antagonists. The present study was designed to determine the mechanisms of paclitaxel hypersensitivity. In rats, paclitaxel (15 mg/kg, intravenously) caused a marked increase in pulmonary vascular permeability and edema. PaO2 decreased, whereas PaCO2 increased, transiently after paclitaxel injection. The paclitaxel-induced pulmonary vascular hyperpermeability was blocked by dexamethasone but not by histamine H1 or H2 antagonists. Paclitaxel increased the vascular permeability in lungs of mast cell-deficient rats Ws/Ws(-/-) to almost the similar extent as that elicited in wild-type rats. On the other hand, the paclitaxel-induced pulmonary vascular hyperpermeability was reversed by sensory denervation with capsaicin or pretreatment with LY303870 and SR48968, NK1 and NK2 antagonists, respectively. Consistent with these findings, a marked elevation of sensory neuropeptides such as substance P, neurokinin A, and calcitonin gene-related peptide was observed in rat bronchoalveolar lavage fluid after paclitaxel injection. These findings suggest that sensory nerves rather than mast cells are implicated in the etiology of paclitaxel hypersensitivity.

Background Sunitinib is a multi-targeted tyrosine kinase inhibitor that is approved for treatment of renal cell carcinoma as an oral anticancer drug. Therapeutic drug monitoring of total sunitinib (sunitinib and N -desethyl sunitinib) is used in our hospital to improve therapeutic efficacy, while preventing adverse effects. Here, we report the first case of a patient with metastatic renal cell carcinoma undergoing hemodialysis and presenting severe adverse events induced by the accumulation of N -desethyl sunitinib. Case presentation A 60-year-old Japanese man was diagnosed with metastatic renal cell carcinoma requiring hemodialysis. On day 26 of the first cycle of sunitinib therapy, our patient presented grade 3 thrombocytopenia and leukopenia, which required interruption of therapy although the plasma levels of total sunitinib in the patient were less than the effective concentration of 50 ng/mL. The elimination half-life of sunitinib was normal at 50.8 hours, but that of N -desethyl sunitinib was an extended 211.4 hours. Moreover, the N -desethyl sunitinib/sunitinib trough level ratio was higher than 1.0. We attribute our patient’s severe adverse events to the excessive accumulation of N -desethyl sunitinib owing to its delayed excretion. Although the reason for the delayed excretion of N -desethyl sunitinib in this patient was unknown, it may have been caused by genetic polymorphisms related to the pharmacokinetics of sunitinib rather than the hemodialysis. In this case, the patient was homozygous for the ABCG2 421C allele, but was capable of potentially harboring polymorphisms in other genes, such as ABCB1 , an efflux pump of sunitinib. In addition, even though there is no clear evidence, urinary excretion of the metabolic products of N -desethyl sunitinib could be inhibited by the interaction of transporters such as the organic ion transporter. Conclusions The monitoring of not only total sunitinib concentration but also N -desethyl sunitinib concentration and their elimination half-lives during sunitinib therapy is recommended to avoid critical adverse events.