Background: To discover biomarker panels that could distinguish cancers (BC and RCC) from healthy controls (HCs) and bladder cancers (BC) from renal cell carcinoma (RCC), regardless of whether the patients have haematuria. In addition, we also explored the altered metabolomic pathways of BC and RCC.
Methods: In total, 403 participants were enrolled in our study, which included 146 BC patients (77 without haematuria and 69 with haematuria), 115 RCC patients (94 without haematuria and 21 with haematuria) and 142 sex- and age-matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways.
Results: The panel of α-CEHC, β-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the patients with cancer from the HCs (the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N'-formylkynurenine could differentiate BC from RCC without haematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with haematuria (AUC was 0.913). Pathway analyses revealed altered lipid and purine metabolisms between cancer patients and HCs, together with disordered amino acid and purine metabolisms between BC and RCC with haematuria.
Conclusions: UPLC-MS urine metabolomic analyses could not only differentiate cancers from HCs but also discriminate BC from RCC. In addition, pathway analyses demonstrated a deeper metabolic mechanism of BC and RCC.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6896793 | PMC |
http://dx.doi.org/10.1186/s12885-019-6354-1 | DOI Listing |
Objectives: To evaluate the utility of the HAS-BLED bleeding risk-estimation tool to predict for clinically significant postoperative haematuria in patients receiving transurethral resection of prostate (TURP).
Patients And Methods: A single-centre, retrospective cohort analysis of patients underwent TURP from April 2019 to December 2023 for treatment of symptomatic benign prostate hyperplasia. The primary objective was to evaluate reliability of HAS-BLED score in predicting postoperative bleeding event.
Objectives: To assess the contemporary malignancy rate in isolated de novo red patches in the bladder and associated risk factors for better selection of red patch biopsy.
Patients: Patients from the IDENTIFY dataset; Patients referred to secondary care with suspected urinary tract cancer and found to have isolated de novo red patches on cystoscopy.
Methods: We reported the unadjusted cancer prevalence in isolated de novo red patches that were biopsied; multivariable logistic regression was used to explore cancer-associated risk factors including age, sex, smoking, type of haematuria, LUTS, UTIs and a suspicious-looking red patch (as reported by the cystoscopist).
Clin Chem Lab Med
January 2025
Department of Nephrology, Ghent University Hospital Ghent, Belgium.
Objectives: We evaluated the performance of a novel flow cell morphology analyzer AUTION EYE AI-4510 for counting particles in urine.
Methods: Analytical performance was assessed according to the EFLM European Urinalysis Guideline 2023. Trueness was compared by analyzing 1.
Discov Oncol
January 2025
Institute of Clinical Medicine, Surgery, University of Eastern Finland, Kuopio, Finland.
Purpose: This retrospective single-center study aimed to determine the correlation between The Paris System (TPS) urine cytology classification, cystoscopy findings, and non-muscle-invasive bladder cancer diagnosis. In addition, we sought to identify factors that might explain the abnormal cytology classification in cases in which no malignancy was detected.
Methods: A Total of 855 patients evaluated with urine cytology between 2017 and 2020 at Kuopio University Hospital were included.
Emerg Radiol
January 2025
Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, 601 North Caroline Street, Baltimore, MD, 21287-0801, USA.
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