Qifang Lei

Background: Bladder cancer is the most common malignant tumor in the urinary system. The acquisition of urine samples has the advantages of being rapid and painless, and it can directly contact the lesions. It is an ideal source of non‐invasive tumor markers. The problems with urine markers are low specificity, the propensity for false positives or missed detections, and there is no unified diagnostic standard to measure the test results, which limits the clinical application of urine markers. In this study, we evaluate the diagnostic values of Cytokeratin 19 fragment (CYFRA21‐1), Fibrin/fibrinogen degradation products (FDP) and CYFRA21‐1 + FDP in bladder cancer, with the objective to expand the application scope of urinary tumor markers in the diagnosis of bladder cancer. Methods: We evaluated the performances of the CYFRA21‐1 assay kit (electrochemiluminescence) and/or FDP assay kit (electrochemiluminescence) in detecting bladder cancer. CYFRA21‐1 and FDP levels were determined in urine samples from 467 participants in South China Hospital of Shenzhen University and Shenzhen Luohu People's Hospital. We performed performance validation of the CYFRA21‐1 and FDP kits, established normal biological reference intervals, and finally analyzed the data to assess their diagnostic efficacies alone or in combination. Results: The bladder cancer group had significantly higher urinary levels of CYFRA21‐1 and FDP than the control group. The areas under the receiver operating characteristic curves (ROC‐AUCs) of CYFRA21‐1, FDP, and CYFRA21‐1 + FDP were 0.929, 0.857, and 0.935, respectively, for discriminating bladder cancer cases from controls. The ROC‐AUC of CYFRA21‐1 and FDP in combination was higher than that of any index alone. Conclusions: Both CYFRA21‐1 and FDP have good diagnostic values in predicting bladder cancer. In addition, combined detection of urinary CYFRA21‐1 and FDP by electrochemiluminescence has better differentiation ability compared with each index alone and may be used for early screening and recurrence monitoring in bladder cancer.

Introduction: Urolithiasis is characterized by a high morbidity and recurrence rate, primarily attributed to metabolic disorders. The identification of more metabolic biomarkers would provide valuable insights into the etiology of stone formation and the assessment of disease risk. The present study aimed to seek potential organic acid (OA) biomarkers from morning urine samples and explore new methods based on machine learning (ML) for metabolic risk prediction of urolithiasis. Methods: Morning urine samples were collected from 117 healthy controls and 156 urolithiasis patients. Gas chromatography-mass spectrometry was used to obtain metabolic profiles. Principal component analysis and ML were carried out to screen robust markers and establish a prediction evaluation model. Results: There were 25 differential metabolites identified, such as palmitic acid, l-pyroglutamic acid, glyoxylate, and ketoglutarate, mainly involving arginine and proline metabolism, fatty acid degradation, glycine, serine, and threonine metabolism, glyoxylate and dicarboxylic acid metabolism. The urinary OA markers significantly improved the performance of the ML model. The sensitivity and specificity were up to 87.50% and 84.38%, respectively. The area under the receiver operating characteristic curve (AUC) was significantly improved (AUC = 0.9248). Conclusion: The results suggest that OA profiles in morning urine can improve the accuracy of predicting urolithiasis risk and possibly help understand the involvement of metabolic perturbations in metabolic pathways of stone formation and to provide new insights.

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Bladder cancer is a common malignant tumor of the urinary system. Cystoscopy, urine cytology, and CT are the routine diagnostic methods. However, there are some problems such as low sensitivity and difficulty in staging, which must be urgently supplemented by novel diagnostic methods. Surgery, intravesical instillation, systemic chemotherapy, and radiotherapy are the main clinical treatments for bladder cancer. It is difficult for conventional treatment to deal with tumor recurrence, progression and drug resistance. In addition, the treatment agents usually have the defects of poor specific distribution ability to target tumor tissues and side effects. The rapid development of nanomedicine has brought hope for the treatment of bladder cancer in reducing side effects, enhancing tumor inhibition effects, and anti-drug resistance. Overall, we review the new progression of nano-platforms in the diagnosis and treatment of bladder cancer.