Background The first global lipidomic profiles associated with urothelial cancer of the bladder (UCB) and its clinical stages associated with progression were identified. Objective To identify lipidomic signatures associated with survival and different clinical stages of UCB. Design, setting, and participants Pathologically confirmed 165 bladder-derived tissues (126 UCB, 39 benign adjacent or normal bladder tissues). UCB tissues included Ta (n = 16), T1 (n = 30), T2 (n = 43), T3 (n = 27), and T4 (n = 9); lymphovascular invasion (LVI) positive (n = 52) and negative (n = 69); and lymph node status N0 (n = 28), N1 (n = 11), N2 (n = 9), N3 (n = 3), and Nx (n = 75). Results and limitations UCB tissues have higher levels of phospholipids and fatty acids, and reduced levels of triglycerides compared with benign tissues. A total of 59 genes associated with altered lipids in UCB strongly correlate with patient survival in an UCB public dataset. Within UCB, there was a progressive decrease in the levels of phosphatidylserine (PS), phosphatidylethanolamines (PEs), and phosphocholines, whereas an increase in the levels of diacylglycerols (DGs) with tumor stage. Transcript and protein expression of phosphatidylserine synthase 1, which converts DGs to PSs, decreased progressively with tumor stage. Levels of DGs and lyso-PEs were significantly elevated in tumors with LVI and lymph node involvement, respectively. Lack of carcinoma in situ and treatment information is the limitation of our study. Conclusions To date, this is the first study describing the global lipidomic profiles associated with UCB and identifies lipids associated with tumor stages, LVI, and lymph node status. Our data suggest that triglycerides serve as the primary energy source in UCB, while phospholipid alterations could affect membrane structure and/or signaling associated with tumor progression. Patient summary Lipidomic alterations identified in this study set the stage for characterization of pathways associated with these altered lipids that, in turn, could inform the development of first-of-its-kind lipid-based noninvasive biomarkers and novel therapeutic targets for aggressive urothelial cancer of the bladder.
In the intestinal mucosa trefoil factors (TFF) and mucins (Muc) - primarily produced by goblet cells - are thought to play a major role in providing barrier function during infection and inflammation. To investigate their role in pediatric Crohn's disease (CD) and ulcerative colitis (UC) we obtained mucosal biopsies of children with CD, UC and healthy controls and analyzed genetic expression. Levels of TFF2 mRNA were lower in inflamed mucosal samples (terminal ileum (TI) and duodenum) of children with CD, but higher in non-inflamed mucosal samples when compared to healthy controls (p < 0.05). Similarly, TFF2 levels in the TI were significantly lower in inflamed UC tissue. Adjustment for goblet cell density revealed slightly less marked, yet significantly different gene expression in IBD and controls. Furthermore, TI expression of TFF2 and Muc2 was inversely correlated with interleukin-8 expression in CD (p = 0.027). In Summary, our data demonstrate significant changes in Muc and TFF mRNA expression in pediatric patients with IBD suggesting a role in mucosal healing. Further studies are needed to elucidate a potential use as biomarkers for disease progression.
Smoking is a major risk factor for the development of Bladder Cancer (BLCA); however, the functional consequences of the carcinogens in tobacco smoke and BLCA-associated metabolic alterations remains poorly defined. We assessed the metabolic profiles in BLCA smokers and non-smokers, and identified the key alterations in their metabolism. Liquid Chromatography – Mass Spectrometry (LC-MS), and bioinformatic analysis were performed to determine the metabolome associated with BLCA smokers and were further validated in cell line models. Smokers with BLCA were found to have elevated levels of methylated metabolites, polycyclic aromatic hydrocarbons (PAHs), DNA adducts and DNA damage. DNA methyltransferase 1 (DNMT1) expression was significantly higher in smokers than non-smokers with BLCA. An integromics approach, using multiple patient cohorts, revealed strong associations between smokers and high-grade BLCA. In vitro exposure to the tobacco smoke carcinogens, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and benzo[a]pyrene (BaP) led to increase in levels of methylated metabolites, DNA adducts, and extensive DNA damage in BLCA cells. Co-treatment of BLCA cells with these carcinogens and the methylation inhibitor 5-aza-2′-deoxycytidine (AZA) rewired the methylated metabolites, DNA adducts, DNA damage. These findings were confirmed through the isotopic labeled metabolic flux analysis. Screens using smoke associated metabolites and DNA adducts could provide robust biomarkers and improve individual risk prediction in BLCA smokers. Non-invasive predictive biomarkers that can stratify the risk of developing BLCA in smokers could aid in early detection and treatment.
PurposeWe used targeted mass spectrometry to study the metabolic fingerprint of urothelial cancer and determine whether the biochemical pathway analysis gene signature would have a predictive value in independent cohorts of patients with bladder cancer.Materials and MethodsPathologically evaluated, bladder derived tissues, including benign adjacent tissue from 14 patients and bladder cancer from 46, were analyzed by liquid chromatography based targeted mass spectrometry. Differential metabolites associated with tumor samples in comparison to benign tissue were identified by adjusting the p values for multiple testing at a false discovery rate threshold of 15%. Enrichment of pathways and processes associated with the metabolic signature were determined using the GO (Gene Ontology) Database and MSigDB (Molecular Signature Database). Integration of metabolite alterations with transcriptome data from TCGA (The Cancer Genome Atlas) was done to identify the molecular signature of 30 metabolic genes. Available outcome data from TCGA portal were used to determine the association with survival.ResultsWe identified 145 metabolites, of which analysis revealed 31 differential metabolites when comparing benign and tumor tissue samples. Using the KEGG (Kyoto Encyclopedia of Genes and Genomes) Database we identified a total of 174 genes that correlated with the altered metabolic pathways involved. By integrating these genes with the transcriptomic data from the corresponding TCGA data set we identified a metabolic signature consisting of 30 genes. The signature was significant in its prediction of survival in 95 patients with a low signature score vs 282 with a high signature score (p = 0.0458).ConclusionsTargeted mass spectrometry of bladder cancer is highly sensitive for detecting metabolic alterations. Applying transcriptome data allows for integration into larger data sets and identification of relevant metabolic pathways in bladder cancer progression.
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