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.

Renal cell carcinoma (RCC) is a malignant tumor that currently lacks clinically useful biomarkers indicative of early diagnosis or disease status. RCC has commonly been diagnosed based on imaging results. Metabolomics offers a potential technology for discovering biomarkers and therapeutic targets by comprehensive screening of metabolites from patients with various cancers. We aimed to identify metabolites associated with early diagnosis and clinicopathological factors in RCC using global metabolomics (G‐Met). Tumor and nontumor tissues were sampled from 20 cases of surgically resected clear cell RCC. G‐Met was performed by liquid chromatography mass spectrometry and important metabolites specific to RCC were analyzed by multivariate statistical analysis for cancer diagnostic ability based on area under the curve (AUC) and clinicopathological factors (tumor volume, pathological T stage, Fuhrman grade, presence of coagulation necrosis and distant metastasis). We identified 58 metabolites showing significantly increased levels in tumor tissues, 34 of which showed potential early diagnostic ability (AUC >0.8), but 24 did not discriminate between tumor and nontumor tissues (AUC ≤0.8). We recognized 6 pathways from 9 metabolites with AUC >0.8 and 7 pathways from 10 metabolites with AUC ≤0.8 about malignant status. Clinicopathological factors involving malignant status correlated significantly with metabolites showing AUC ≤0.8 (p = 0.0279). The tricarboxylic acid cycle (TCA) cycle, TCA cycle intermediates, nucleotide sugar pathway and inositol pathway were characteristic pathways for the malignant status of RCC. In conclusion, our study found that metabolites and their pathways allowed discrimination between early diagnosis and malignant status in RCC according to our G‐Met protocol.

A 73-year-old male with a history of diabetes mellitus was admitted to our hospital for acute renal failure. An ultrasonogram revealed bilateral hydronephrosis, which worsened despite insertion of a bladder catheter. Nephrostomy catheters were positioned bilaterally, and Candida albicans was found in the urine culture. The patient was successfully treated with intermittent direct irrigation and i.v. antifungal agent therapy. Since 1977, approximately 50 cases of fungus balls or fungal bezoars in the urinary tract have been reported, but the majority of these cases have been characterized by unilateral ureteral or bladder involvement. Herein, we report a case of acute renal failure as a result of bilateral ureteral obstruction by Candida albicans fungus balls.

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.

About one third of renal cell carcinoma (RCC) patients exhibit metastasis upon initial presentation. However, the molecular basis for RCC metastasis is not fully understood. A ganglioside, disialosyl globopentaosylceramide (DSGb5), was originally isolated from RCC tissue extracts, and its expression is correlated with RCC metastatic potential. DSGb5 is synthesized by GalNAc α2,6-sialyltransferase VI (ST6GalNAcVI) and is expressed on the surface of RCC cells. Importantly, DSGb5 binds to sialic acidbinding Ig-like lectin-7 (Siglec-7) expressed on natural killer (NK) cells, thereby inhibiting NK-cell cytotoxicity. However, the role of DSGb5 in RCC progression remains obscure. To address this issue, we used ACHN cells derived from malignant pleural effusion of a patient with metastatic RCC. Using the limiting dilution method, we isolated three independent clones with different DSGb5 expression levels. Comparison of these clones indicated that the cloned cells with high DSGb5 expression levels exhibited greater migration potential, compared to the clone with low DSGb5 expression levels. In contrast, DSGb5 expression levels exerted no significant effect on cell proliferation. We then established the ACHN-derived cell lines that stably expressed siRNA against ST6GalNAcVI mRNA or control siRNA. Importantly, the ST6GalNAcVI-knockdown cells expressed low levels of DSGb5. We thus demonstrated the significantly decreased migration potential of the ST6GalNAcVI-knockdown cells with low DSGb5 expression levels, compared to the control siRNA-transfected cells expressing high DSGb5 levels, but no significant difference in the cell proliferation. Thus, DSGb5 expression may ensure the migration of RCC cells. We propose that DSGb5 expressed on RCC cells may determine their metastatic capability.