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.

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.

The 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.

An analytical method using high-performance liquid chromatography/electrospray ionization tandem mass spectrometry has been developed and validated for simultaneous measurement of four tyrosine kinase inhibitors used for renal cell carcinoma and their metabolites in human plasma. Despite their similar structures, it is difficult to measure plasma levels of these compounds simultaneously using optimal MS parameters for each compound because a quantitative range exceeding 50,000-fold is required. To overcome this problem, we used a linear range shift technique using in-source collision-induced dissociation. Linearity ranges of sorafenib, sorafenib N-oxide, sunitinib, N-desethyl sunitinib, axitinib and pazopanib were 100-10,000, 10-1,000, 1-100, 1-100, 1-100 and 500-50,000 ng/mL, respectively. The intra- and inter-day precision and accuracy were high, and coefficients of variation and relative error were <10.3% and within ±11.8%, respectively. The matrix effects of all analytes ranged from 87.7 to 114.8%. Extraction recoveries and overall recoveries showed small extraction loss (<15.0%) for all analytes. Moreover, all cancer patient samples used in this study were successfully quantified and fell within the linear range of measurement. Therefore, this novel analytical system using in-source collision-induced dissociation has sufficient performance to measure plasma concentrations of these four tyrosine kinase inhibitors and their metabolites for therapeutic drug monitoring.