Search

Background Urinary bladder cancer (UBC) is a common malignancy of the urinary tract; however, the mechanism underlying its high recurrence and responses to immunotherapy remains unclear, making clinical outcome predictions difficult. Epigenetic alterations, especially DNA methylation, play important roles in bladder cancer development and are increasingly being investigated as biomarkers for diagnostic or prognostic predictions. However, little is known about hydroxymethylation since previous studies based on bisulfite-sequencing approaches could not differentiate between 5mC and 5hmC signals, resulting in entangled methylation results. Methods Tissue samples of bladder cancer patients who underwent laparoscopic radical cystectomy (LRC), partial cystectomy (PC), or transurethral resection of bladder tumor (TURBT) were collected. We utilized a multi-omics approach to analyze both primary and recurrent bladder cancer samples. By integrating various techniques including RNA sequencing, oxidative reduced-representation bisulfite sequencing (oxRRBS), reduced-representation bisulfite sequencing (RRBS), and whole exome sequencing, a comprehensive analysis of the genome, transcriptome, methylome, and hydroxymethylome landscape of these cancers was possible. Results By whole exome sequencing, we identified driver mutations involved in the development of UBC, including those in FGFR3, KDMTA, and KDMT2C. However, few of these driver mutations were associated with the down-regulation of programmed death-ligand 1 (PD-L1) or recurrence in UBC. By integrating RRBS and oxRRBS data, we identified fatty acid oxidation-related genes significantly enriched in 5hmC-associated transcription alterations in recurrent bladder cancers. We also observed a series of 5mC hypo differentially methylated regions (DMRs) in the gene body of NFATC1, which is highly involved in T-cell immune responses in bladder cancer samples with high expression of PD-L1. Since 5mC and 5hmC alternations are globally anti-correlated, RRBS-seq-based markers that combine the 5mC and 5hmC signals, attenuate cancer-related signals, and therefore, are not optimal as clinical biomarkers. Conclusions By multi-omics profiling of UBC samples, we showed that epigenetic alternations are more involved compared to genetic mutations in the PD-L1 regulation and recurrence of UBC. As proof of principle, we demonstrated that the combined measurement of 5mC and 5hmC levels by the bisulfite-based method compromises the prediction accuracy of epigenetic biomarkers.

Despite the success of targeted therapies in cancer treatment, therapy-induced resistance remains a major obstacle to a complete cure. Tumor cells evade treatments and relapse via phenotypic switching driven by intrinsic or induced cell plasticity. Several reversible mechanisms have been proposed to circumvent tumor cell plasticity, including epigenetic modifications, regulation of transcription factors, activation or suppression of key signaling pathways, as well as modification of the tumor environment. Epithelial-to-mesenchymal transition, tumor cell and cancer stem cell formation also serve as roads towards tumor cell plasticity. Corresponding treatment strategies have recently been developed that either target plasticity-related mechanisms or employ combination treatments. In this review, we delineate the formation of tumor cell plasticity and its manipulation of tumor evasion from targeted therapy. We discuss the non-genetic mechanisms of targeted drug-induced tumor cell plasticity in various types of tumors and provide insights into the contribution of tumor cell plasticity to acquired drug resistance. New therapeutic strategies such as inhibition or reversal of tumor cell plasticity are also presented. We also discuss the multitude of clinical trials that are ongoing worldwide with the intention of improving clinical outcomes. These advances provide a direction for developing novel therapeutic strategies and combination therapy regimens that target tumor cell plasticity.

Background Clear cell renal cell carcinoma (ccRCC) is one of the most lethal urological malignancies, but the pathogenesis and prognosis of ccRCC remain obscure, which need to be better understand. Methods Differentially expressed genes were identified and function enrichment analyses were performed using three publicly available ccRCC gene expression profiles downloaded from the Gene Expression Omnibus database. The protein-protein interaction and the competing endogenous RNA (ceRNA) networks were visualized by Cytoscape. Multivariate Cox analysis was used to predict an optimal risk mode, and the survival analysis was performed with the Kaplan-Meier curve and log-rank test. Protein expression data were downloaded from Clinical Proteomic Tumor Analysis Consortium database and Human Protein Atlas database, and the clinical information as well as the corresponding lncRNA and miRNA expression data were obtained via The Cancer Genome Atlas database. The co-expressed genes and potential function of candidate genes were explored using data exacted from the Cancer Cell Line Encyclopedia database. Results Of the 1044 differentially expressed genes shared across the three datasets, 461 were upregulated, and 583 were downregulated, which significantly enriched in multiple immunoregulatory-related biological process and tumor-associated pathways, such as HIF-1, PI3K-AKT, P53 and Rap1 signaling pathways. In the most significant module, 36 hub genes were identified and were predominantly enriched in inflammatory response and immune and biotic stimulus pathways. Survival analysis and validation of the hub genes at the mRNA and protein expression levels suggested that these genes, particularly complement component 3 (C3) and fibronectin 1 (FN1), were primarily responsible for ccRCC tumorigenesis and progression. Increased expression of C3 or FN1 was also associated with advanced clinical stage, high pathological grade, and poor survival in patients with ccRCC. Univariate and multivariate Cox regression analysis qualified the expression levels of the two genes as candidate biomarkers for predicting poor survival. FN1 was potentially regulated by miR-429, miR-216b and miR-217, and constructed a bridge to C3 and C3AR1 in the ceRNA network, indicating a critical position of FN1. Conclusions The biomarkers C3 and FN1 could provide theoretical support for the development of a novel prognostic tool to advance ccRCC diagnosis and targeted therapy.

We describe a method for solid-phase extraction of biogenic thiols using multi-walled carbon nanotubes as adsorbent, and their subsequent determination via HPLC and fluorescence detection. The fluorogenic reagent N-(4,4-difluoro-5,7-dimethyl-4-bora-3a,4a-diaza-s-indacene-3-yl)methyl) iodoacetamide was applied to derivatizate the thiols. The type of eluent and its volume, the sample pH, extraction time and sample volume were optimized. The calibration curves of the thiols are linear in the range from 0.5 to 200 nM (for glutathione), 0.02 to 5 nM (for cysteine), and 2 to 500 nM (for acetylcysteine), and the correlation coefficients range between 0.9955 and 0.9997. The respective limits of detection are 20 pM, 4 pM and 80 pM (at an SNR of 3), and the limits of quatification are 67 pM, 13 pM, and 267 pM (at an SNR of 10). Recoveries range from 85.0% to 113.1% for human urine and plasma samples spiked with the three thiols, and relative standard deviations are in the range from 2.1 to 7.4%.

Solid-phase extraction (SPE) coupled with high-performance liquid chromatography–fluorescence detection (LC–FL) was developed for the determination of three thiol compounds including glutathione, cysteine and acetylcysteine. 4-(Aminosulfonyl)-7-fluoro-2,1,3-benzoxadiazole was used for derivatization of thiols. Factors affecting derivatization and extraction efficiency were optimized. Sample solution (2 mL) was extracted on a SPE column for 2 min and then eluted with 400 μL methanol. The analytes were injected onto the LC system for separation on a C18 column, and eluted with methanol–acetate buffer. The analytes were detected by fluorescence at an emission wavelength of 515 nm with excitation at 385 nm. The linearity of the method was in the range of 0.1–60 μM, with correlation coefficients ranging from 0.9979 to 0.9990. The detection limits of the method were in the range of 5–20 nM. The proposed method was applied to the analysis of human plasma samples with recoveries of 86–112.9%.

Solid-phase extraction coupled with LC-fluorescence detection was used for the extraction and determination of three thiol compounds including glutathione (GSH), cysteine (Cys) and acetylcysteine (NAc). Fluorescence probe N-(4,4-difluoro-5,7-dimethyl-4-bora-3a,4a-diaza-s-indacene-3-yl)methyl)iodoacetamide (BODIPY Fl-C1-IA) was applied for derivatization of thiols. The derivatization and extraction conditions have been investigated in detail. The calibration graph of the proposed method was linear in the range of 1–200 nM (GSH and Cys) and 20–2,000 nM (NAc). The limits of detection were in the range of 0.2–4.0 nM. The usefulness of the proposed method has been validated by measuring thiol-containing compounds in human urine and blood samples from healthy persons, with recoveries of 92.5–110%.