Year: 2026
Type: article
Abstract: Urothelial carcinoma (UC) is a major cancer globally and disproportionately frequent among hemodialysis (HD) patients. Currently, there are no reliable blood-based clinical markers to detect or monitor this cancer in HD population. In this research, we investigate the functional roles of these miRNAs in UC cells and refine the miRNA-based prediction model within a physiology-informed framework. Cell-based assays including colony formation, soft agar, wound healing, and sphere assays were performed to investigate the functional role of candidate miRNAs in UC cells. The plasma samples were collected from 156 HD patients. The expression levels of UC-associated miRNAs were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR). A physiology-informed prediction model was constructed by integrating miRNA expression ratios with blood biochemistry parameters reflecting uremic metabolic burden. Six UC-associated miRNAs from our previous study have crucial roles in UC cells. Overexpression of miR-19b-1-5p, miR-155-5p, miR-210-3p, and miR-378a-3p reduced proliferation and anchorage-independent growth in J82 and RT4 cells. Additionally, miR-155-5p and miR-150-5p impaired RT4 cell migration, while miR-155-5p and miR-636 reduced cancer stem cell formation of both cell lines. IFN-α/β signaling pathway is highlighted through their target genes and miRNA-compound interaction network. By integrating eight miRNA ratios with blood biochemistry parameters, the physiology-informed miRNA framework demonstrated promising diagnostic performance in the HD population. These findings link circulating miRNA signatures to UC-associated pathophysiology and support their potential for clinical detection, pending further external validation.
Source: Renal Failure
Authors: Kun-Lin Wu, Yi-Yang Liu, Jen-Chieh Tsai, Mai-Huong Thi Nguyen, Wu-Chang Yang, Chih-Hsun Wu, Anlun Li, Pei-Jung Chung, Yu-Chen Fung, Pin-Hsuan Huang, Hui-Ying Liu, Yin-Lun Chang, Hui-Yin Chang, Yu-Juei Hsu, Hao-Lun Luo, Nianhan Ma
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,306
OpenAlex ID: W7166672715
