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. 2023 Dec;55(1):736-745.
doi: 10.1080/07853890.2023.2172206.

A serum miRNAs signature for early diagnosis of bladder cancer

Zuhu Yu  1 , Chong Lu  2   3 , Yongqing Lai  2
Affiliations

A serum miRNAs signature for early diagnosis of bladder cancer

Zuhu Yu et al. Ann Med. 2023 Dec.

Abstract

Background: Bladder cancer accounts for the most common type of urologic malignancy and presents high recurrence rate after surgical resection and adjuvant intravesical therapy. We aim to search for an early diagnostic biomarker in serum for bladder cancer in this study.

Methods: The expression profiles of miRNAs in serum samples of 112 bladder cancer patients and 112 healthy controls were detected with real-time polymerase chain reaction (RT-qPCR). Receiver operating characteristic (ROC) curve and area under curve (AUC) analysis were performed to assess the diagnostic efficiency of miRNAs. Stepwise logic regression analysis was used to construct a diagnostic signature with highest sensitivity and specificity. Bioinformatics analysis was applied to explore the potential biological functions and mechanisms of candidate miRNAs.

Results: Five miRNAs including miR-451a, miR-381-3p, miR-223-3p, miR-142-5p and miR-27b-3p were found differentially expressed in serum samples of bladder patients and healthy subjects. The diagnostic signature was constructed with miR-27b-3p, miR-381-3p and miR-451a. AUC of the three-miRNA signature was 0.894 (0.837-0.936, p < 0.001). The sensitivity and specificity of this signature were 86.90% and 77.38%, respectively, indicating that this signature has a good ability to diagnose bladder cancer.

Conclusion: The three-miRNA signature we constructed has favorable diagnostic capacity and may be a promising non-invasive biomarker in the early diagnosis of bladder cancer.KEY MESSAGESThere is still no clinical utilization of serum miRNAs in the early detection of bladder cancer.We screened and constructed a three-miRNA signature with the sensitivity of 86.90% and specificity of 77.38% which may be a promising non-invasive biomarker in the early diagnosis of bladder cancer.

Keywords: Bladder cancer; diagnosis; miRNA; serum biomarker.

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Conflict of interest statement

No potential conflict of interest was reported by the author(s).

Figures

Figure 1.
Figure 1.
The expression levels of 10 candidate miRNAs in the training phase. Screening conditions: p-value <0.05, * represents p < 0.05, ** represents p < 0.01, *** represents p < 0.001.
Figure 2.
Figure 2.
The relative expression of 5 candidate miRNAs and the corresponding ROC curves. The expression of miR-142-5p (C), miR-223-3p (E), miR-381-3p (G) and miR-451a (I) in serum sample of bladder cancer were significantly lower than in HCs. The expression of miR-27b-3p in cancerous serum samples was significantly higher than in HCs. AUCs of miR-27b-3p (B), miR-142-5p (D), miR-223-3p (F), miR-381-3p (H) and miR-451a (J) were 0.664 (p < 0.001), 0.614 (p = 0.010), 0.603 (p = 0.018), 0.723 (p < 0.001) and 0.766 (p < 0.001), respectively. * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 3.
Figure 3.
Receiver operating characteristic (ROC) curve of the three-miRNA signature including miR-27b-3p, miR-381-3p and miR-451a. The AUC of the signature is 0.894 (95%CI: 0.837-0.936, p < 0.001).
Figure 4.
Figure 4.
Target prediction of the miRNAs in the signature. (A) In total, 168 target genes of the three miRNAs were predicted by miRDB, miRTarBase and TargetScan simultaneously. (B) The subnetwork and top ten hub genes obtained using CytoHubba of Cytoscape. (C) GEPIA database showed that SMAD4 and FOXO1 were down-regulated in bladder cancer tissues compared to normal tissues (p < 0.05). BLCA: Bladder Urothelial carcinoma. T: Tumor tissues. N: Normal tissues. * p < 0.05.
Figure 5.
Figure 5.
GO annotations and KEGG pathway enrichment analysis of the target genes of miR-27b-3p, miR-381-3p and miR-451a. (A) Cellular component enrichment; (B) Molecular function enrichment; (C) Biological Process enrichment; (D) KEGG Pathway enrichment analysis.
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Grants and funding

This research was funded by the Scientific Research Project of Health System of Guangming District, Shenzhen [No. 2020R01034].