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. 2022 Mar 3;20(1):66.
doi: 10.1186/s12957-022-02538-w.

Global analysis of miRNA-mRNA regulation pair in bladder cancer

Xingchen Fan #  1 , Xuan Zou #  2 , Cheng Liu #  3 , Shuang Peng  1 , Shiyu Zhang  1 , Xin Zhou  1 , Tongshan Wang  4 , Wei Zhu  5
Affiliations

Global analysis of miRNA-mRNA regulation pair in bladder cancer

Xingchen Fan et al. World J Surg Oncol. .

Abstract

Purpose: MicroRNA (miRNA) is a class of short non-coding RNA molecules that functions in RNA silencing and post-transcriptional regulation of gene expression. This study aims to identify critical miRNA-mRNA regulation pairs contributing to bladder cancer (BLCA) pathogenesis.

Patients and methods: MiRNA and mRNA microarray and RNA-sequencing datasets were downloaded from gene expression omnibus (GEO) and the cancer genome atlas (TCGA) databases. The tool of GEO2R and R packages were used to screen differential miRNAs (DE-miRNAs) and mRNAs (DE-mRNAs) and DAVID, DIANA, and Hiplot tools were used to perform gene enrichment analysis. The miRNA-mRNA regulation pair were screened from the experimentally validated miRNA-target interactions databases (miRTarbase and TarBase). Twenty-eight pairs of BLCA tissues were used to further verify the screened DE-miRNAs and DE-mRNAs by quantitative reverse transcription and polymerase chain reaction (qRT-PCR). The diagnostic value of the miRNA-mRNA regulation pairs was evaluated by receiver operating characteristic curve (ROC) and decision curve analysis (DCA). The correlation analysis between the selected miRNA-mRNAs regulation pair and clinical, survival and tumor-related phenotypes was performed in this study.

Results: After miRTarBase, the analysis of 2 miRNA datasets, 6 mRNA datasets, and TCGA-BLCA dataset, a total of 13 miRNAs (5 downregulated and 8 upregulated in BLCA tissues) and 181 mRNAs (72 upregulated and 109 downregulated in BLCA tissues) were screened out. The pairs of miR-17-5p (upregulated in BLCA tissues) and TGFBR2 (downregulated in BLCA tissues) were verified in the external validation cohort (28 BLCA vs. 28 NC) using qRT-PCR. Areas under the ROC curve of the miRNA-mRNA regulation pair panel were 0.929 (95% CI: 0.885-0.972, p < 0.0001) in TCGA-BLCA and 0.767 (95% CI: 0.643-0.891, p = 0.001) in the external validation. The DCA also showed that the miRNA-mRNA regulation pairs had an excellent diagnostic performance distinguishing BLCA from normal controls. Correlation analysis showed that miR-17-5p and TGFBR2 correlated with tumor immunity.

Conclusions: The research identified potential miRNA-mRNA regulation pairs, providing a new idea for exploring the genesis and development of BLCA.

Keywords: Bladder cancer; miRNA; miRNA-mRNA regulation pairs.

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Conflict of interest statement

The author reports no conflicts of interest in this work.

Figures

Fig. 1
Fig. 1
Flow chart for identifying the miRNA-mRNA regulatory pairs and the comprehensive analysis of regulatory pairs’ role in bladder cancer (BLCA)
Fig. 2
Fig. 2
The circular bar chart showing the datasets from different sources for screening differentially expressed miRNAs and mRNAs. A total of 8 datasets from the GEO database were included in the study, including 6 mRNA expression microarray datasets and 2 microarray datasets. Combined with GEO, miRCancer, and TCGA databases, 13 miRNAs and 181 mRNAs were selected as DE-miRNAs and DE-mRNAs
Fig. 3
Fig. 3
The screened miRNA-mRNA regulation pairs. A total of 11 miRNA-mRNA regulation pairs (miR-195-5p(down)/CDK1(up), miR-195-5p(down)/E2F3(up), miR-210-3p(up)/NCAM1(down), miR-93-5p(up)/DENND5B(down), miR-93-5p(up)/PPP1R12B(down), miR-93-5p(up)/TGFBR2(down), miR-130b-3p(up)/PRUNE2(down), miR-130b-3p(up)/TGFBR2(down), miR-17-5p(up)/DENND5B(down), miR-17-5p(up)/PPP1R12B(down), miR-17-5p(up)/TGFBR2(down)) were identified after verified in miRtarbase and Tarbase databases and the expression levels of 7 pairs of miRNA-mRNA (miR-195-5p(down)/CDK1(up), miR-130b-3p(up)/PRUNE2(down), miR-130b-3p(up)/TGFBR2(down), miR-93-5p(up)/PPP1R12B(down), miR-93-5p(up)/TGFBR2(down), miR-17-5p(up)/PPP1R12B(down), miR-17-5p(up)/TGFBR2(down)) in TCGA-BLCA showed significant negative correlation in Pearson’s correlation analysis (p < 0.05)
Fig. 4
Fig. 4
Validating the expression of the DE-miRNAs and DE-mRNAs by qRT-PCR (data are presented as mean ± SEM; *p < 0.05, **p < 0.01, ***p < 0.001). A: miR-195-5p; B: miR-93-5p; C: miR-130b-3p; D: miR-17-5p; E: CDK1; F: TGFBR2; G: PPP1R12B; H: PRUNE2; I: Pearson’s correlation analysis of miR-17-5p and TGFBR2
Fig. 5
Fig. 5
The ROC and DCA of the panel of miR-17-5p and TGFBR2 for discriminating BLCA patients from NCs. A: The ROC of the TCGA-BLCA (AUC = 0.929, 95% CI: 0.885-0.972, p < 0.0001); B: The ROC of the external validation (AUC = 0.767, 95% CI: 0.643–0.891, p = 0.001); C: The DCA of the TCGA-BLCA; D: The DCA of the external validation
Fig. 6
Fig. 6
Pearson’s correlation analysis of immune-related phenotypes and regulatory pairs in TCGA-BLCA. A: ssGSEA; B: Immune cells; C: Global methylation, tumor mutation burden and tumor microenvironment factors
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