Upregulation of miR­132­3p in cholangiocarcinoma tissues: A study based on RT­qPCR, The Cancer Genome Atlas miRNA sequencing, Gene Expression Omnibus microarray data and bioinformatics analyses.

MicroRNAs (miRNAs/miRs) have been reported to be closely associated with numerous human diseases, including cholangiocarcinoma (CCA). However, the number of miRNAs known to be involved in CCA is limited, and the association between miR­132­3p and CCA remains unknown. In the present study, the clinical role of miR­132­3p and its potential signaling pathways were investigated by multiple approaches. Reverse transcription­quantitative PCR (RT­qPCR), CCA­associated Gene Expression Omnibus (GEO), ArrayExpress and Sequence Read Archive (SRA) miRNA­microarray or miRNA­sequencing data were screened, and meta­analyses were conducted, in order to calculate the receiver operating characteristic (ROC) curve and standardized mean difference (SMD). The predicted target genes of miR­132­3p were obtained from 12 online databases and were combined with the downregulated differentially expressed genes identified in the RNA­sequencing data of CCA. Gene Ontology annotation and pathway analysis were performed in WebGestalt. Protein­protein interaction analyses were conducted in STRING. The Cancer Genome Atlas (TCGA) mRNA expression profiles were used to validate the expression levels of hub genes at the mRNA level. The Human Protein Atlas was used to identify the protein expression levels of hub genes in CCA tissues and non­tumor biliary epithelium. The meta­analyses comprised 10 groups of RT­qPCR data, eight GEO microarray datasets and one TCGA miRNA­sequencing dataset. The SMD of miR­132­3p in CCA was 0.75 (95% CI: 0.25, 1.24), which indicated that miR­132­3p was overexpressed in CCA tissues. This finding was supported by a summary ROC value of 0.80 (95% CI: 0.76, 0.83). The pooled sensitivity and specificity were 0.81 (95% CI: 0.59, 0.93) and 0.71 (95% CI: 0.58, 0.81), respectively. The relative expression level of miR­132­3p in the early stage of CCA (stages I­II) was 6.8754±0.5279, which was markedly lower than that in the advanced stage (stages III­IVB), 7.3034±0.3267 (P=0.003). Consistently, the miR­132­3p level in low­grade CCA (grades G1­G2) was 6.7581±0.5297, whereas it was 7.1191±0.4651 in patients with high­grade CCA (grades G3­G4) (P=0.037). Furthermore, 555 potential target genes of miR­132­3p in CCA were mainly enriched in the 'Focal Adhesion­PI3K­Akt­mTOR­signaling pathway'. In conclusion, upregulation of miR­132­3p may serve a pivotal role in the tumorigenesis and progression of CCA by targeting different pathways. Further in vitro and in vivo studies are required to support the current findings.

Construction of a model to predict the prognosis of patients with cholangiocarcinoma using alternative splicing events.

Cholangiocarcinoma (CCA) is a type of malignant tumor that originates in the mucosal epithelial cells of the biliary system. It is a highly aggressive cancer that progresses rapidly, has low surgical resection rates and a high recurrence. At present, no prognostic molecular biomarker for CCA has been identified. However, CCA progression is affected by mRNA precursors that modify gene expression levels and protein structures through alternative splicing (AS) events, which create molecular indicators that may potentially be used to predict CCA outcomes. The present study aimed to construct a model to predict CCA prognosis based on AS events. Using prognostic data available from The Cancer Genome Atlas, including the percent spliced index of AS events obtained from TCGASpliceSeq in 32 CCA cases, univariate and multivariate Cox regression analyses were performed to assess the associations between AS events and the overall survival (OS) rates of patients with CCA. Additional multivariate Cox regression analyses were used to identify AS events that were significantly associated with prognosis, which were used to construct a prediction model with a prognostic index (PI). A receiver operating characteristic (ROC) curve was used to determine the predictive value of the PI, and Pearson's correlation analysis was used to determine the association between OS-related AS events and splicing factors. A total of 38,804 AS events were identified in 9,673 CCA genes, among which univariate Cox regression analysis identified 1,639 AS events associated with OS (P<0.05); multivariate Cox regression analysis narrowed this list to 23 CCA AS events (P<0.001). The final PI model was constructed to predict the survival of patients with CCA; the ROC curve demonstrated that it had a high predictive power for CCA prognosis, with a highest area under the curve of 0.986. Correlations between 23 OS-related AS events and splicing factors were also noted, and may thus, these AS events may be used to improve predictions of OS. In conclusion, AS events exhibited potential for predicting the prognosis of patients with CCA, and thus, the effects of AS events in CCA required further examination.