1. Plasma miRNA profile is a biomarker associated with urothelial carcinoma in chronic hemodialysis patients
- Author
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Nianhan Ma, An Lun Li, Pei Luen Fang, Yun Ru Chiang, Chiu Ching Huang, Wu Chang Yang, Biing Yir Shen, Jorng-Tzong Horng, Huan Cheng Chang, Chien Lung Chen, Chen Huan Lin, and Kay Lun Li
- Subjects
Male ,0301 basic medicine ,Oncology ,Urologic Neoplasms ,medicine.medical_specialty ,Physiology ,Population ,Taiwan ,Risk Assessment ,03 medical and health sciences ,0302 clinical medicine ,Predictive Value of Tests ,Renal Dialysis ,Risk Factors ,Internal medicine ,microRNA ,Biomarkers, Tumor ,medicine ,Humans ,Chronic hemodialysis ,In patient ,Circulating MicroRNA ,education ,Early Detection of Cancer ,Aged ,Urothelial carcinoma ,education.field_of_study ,business.industry ,Gene Expression Profiling ,Incidence ,Incidence (epidemiology) ,Carcinoma ,Reproducibility of Results ,Middle Aged ,030104 developmental biology ,Chronic dialysis ,030220 oncology & carcinogenesis ,Biomarker (medicine) ,Female ,Urothelium ,Transcriptome ,business - Abstract
The incidence of urothelial carcinoma (UC) is higher in patients undergoing chronic dialysis than in the general population. This study investigated plasma miRNA profiling as the ancillary diagnosis biomarker associated with UC in patients undergoing chronic hemodialysis. We successfully screened out and detected miRNA expression from plasma in eight patients undergoing dialysis through quantitative real-time PCR array analysis and identified eight candidate miRNAs. The candidate miRNAs were then validated using single quantitative RT-PCR assays from 52 plasma samples. The miRNA classifier for ancillary UC detection was developed by multiple logistic regression analyses. Moreover, we validated the classifier by testing another nine samples. Expression levels of miR-150-5p, miR-150-5p/miR-155-5p, miR-378a-3p/miR-150-5p, miR-636/miR-150-5p, miR-150-5p/miR-210-3p, and miR-19b-1–5p/miR-378a-3p were shown to be significantly different between UC and non-UC samples ( P = 0.035, 0.0048, 0.016, 0.024, 0.038, and 0.048). Kaplan-Meier curve analysis also showed that low miR-19b-1-5p expression was associated with a worse prognosis ( P = 0.0382). We also developed a miRNA classifier based on five miRNA expression levels to predict UC and found that the area under curve was 0.882. The classifier had a sensitivity of 80% (95% confidence interval: 0.5191% to 0.9567%) and a specificity of 83.7% (95% confidence interval: 0.6799% to 0.9381%). This classifier was tested by nine samples with 100% accuracy. The miRNA classifier offers higher sensitivity and specificity than the existing makers. Thus, this approach will improve the prospective diagnosis of UC in patients undergoing chronic hemodialysis.
- Published
- 2019