Contributed equally
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 miR-132-3p and CCA remains unknown. In the present study, the clinical role of miR-132-3p and its potential signaling pathways were investigated by multiple approaches. Reverse transcription-quantitative PCR (RT-qPCR), CCA-associated Gene Expression Omnibus (GEO), ArrayExpress and Sequence Read Archive (SRA) miRNA-microarray or miRNA-sequencing data were screened, and meta-analyses were conducted, in order to calculate the receiver operating characteristic (ROC) curve and standardized mean difference (SMD). The predicted target genes of miR-132-3p were obtained from 12 online databases and were combined with the downregulated differentially expressed genes identified in the RNA-sequencing data of CCA. Gene Ontology annotation and pathway analysis were performed in WebGestalt. Protein-protein 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 non-tumor biliary epithelium. The meta-analyses comprised 10 groups of RT-qPCR data, eight GEO microarray datasets and one TCGA miRNA-sequencing dataset. The SMD of miR-132-3p in CCA was 0.75 (95% CI: 0.25, 1.24), which indicated that miR-132-3p 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 miR-132-3p in the early stage of CCA (stages I–II) was 6.8754±0.5279, which was markedly lower than that in the advanced stage (stages III–IVB), 7.3034±0.3267 (P=0.003). Consistently, the miR-132-3p level in low-grade CCA (grades G1-G2) was 6.7581±0.5297, whereas it was 7.1191±0.4651 in patients with high-grade CCA (grades G3-G4) (P=0.037). Furthermore, 555 potential target genes of miR-132-3p in CCA were mainly enriched in the ‘Focal Adhesion-PI3K-Akt-mTOR-signaling pathway’. In conclusion, upregulation of miR-132-3p may serve a pivotal role in the tumorigenesis and progression of CCA by targeting different pathways. Further
Cholangiocarcinoma (CCA) is a malignant tumor derived from the intrahepatic and extrahepatic bile duct (
Among all possible molecular events involved in the tumorigenesis and development of CCA, microRNAs (miRNAs/miRs) have been documented to serve essential roles. As small noncoding single-stranded RNA molecules, miRNAs participate in biological processes by functioning as post-transcriptional regulatory factors (
miR-132-3p has been reported to be differentially expressed in several cancer types, and to participate in the formation and metastasis of several malignant tumors. miR-132-3p has been associated with the post-transcriptional regulation of BCRP/ABCG2 in renal cell carcinoma (
Our preliminary work mining miRNA microarray and miRNA-sequencing data of CCA revealed several aberrantly expressed miRNAs (Wu
Samples were collected from patients with CCA from the First Affiliated Hospital, Guangxi Medical University between December 2010 and September 2017. In total, 25 CCA and 22 paracarcinoma bile duct tissues were collected, which included 16 males and 9 females with the ages ranging from 34 to 65 years old. In three patients, paracarcinoma bile duct tissue was not collected. This study was approved by the Ethics Committee of First Affiliated Hospital, Guangxi Medical University, China. Informed written consent was obtained from all patients participating in the study. Total RNA from fixed (overnight with 10% neutral-buffered formalin at 25°C) and paraffin embedded samples was extracted from sections using the miRNeasy FFPE kit (Qiagen GmbH). For RT into cDNA, the All-in-One™ miRNA First-Strand cDNA Synthesis kit (QP013, GeneCopoeia, Inc.) was used to transcribe 10 µl purified RNA. The prepared reaction mixture was gently mixed, incubated at 37°C for 60 min after brief centrifugation, followed by incubation at 85°C for 5 min for RT. qPCR, using miR-specific primers and universal adaptor PCR primers purchased from GeneCopoeia, Inc. with confidential sequences, was performed using the Applied Biosystems 7500 Real-Time PCR system (cat. no. QP010; Applied Biosystems; Thermo Fisher Scientific, Inc.). The All-in-one miRNA qPCR kit was used for the qPCR (cat. no. QP013; GeneCopoeia, Inc.). The reactions were incubated in a 96-well plate at 95°C for 10 min, followed by 40 cycles at 95°C for 10 sec, 60°C for 20 sec and 72°C for 34 sec, fluorescent signals were measured during the extension phase. The results were normalized to the reference of U6RNA and calculated using the 2−ΔΔCq method (
The flowchart of the present study is shown in
For the statistical analysis, the present study first explored the association between miR-132-3p and clinicopathological features of CCA, and the miR-132-3p expression profile data acquired from each public database and RT-qPCR data were analyzed with independent sample Student's t-test or a paired samples t-test in SPSS 22.0 (IBM Corp.). The data were presented as the means ± standard deviation. P<0.05 was considered to indicate a statistically significant difference. In addition, the possibility of miR-132-3p being used as a biomarker for distinguishing CCA tumor tissues from normal tissues was evaluated using a receiver operating characteristic (ROC) curve analysis. The present study also performed a continuous variable meta-analysis in Stata12.0 (StataCorp LP) to calculate the standardized mean difference (SMD). This meta-analysis initially used a fixed effect model; if heterogeneity was present, a random effect model was selected instead. The heterogeneity was evaluated with a χ2 test. The result would be regarded as heterogeneous if P<0.05 or I2>50%. A Begg's test was performed to evaluate potential publication bias. Subsequently, a summary ROC (sROC) was conducted to combine the effect of single datasets. Diagnostic odds ratio, as well as negative and positive likelihood ratios, were also analyzed. In addition, the present study performed sROC analysis to further appraise the distinguishing ability of miR-132-3p (
The TCGA gene expression profile data of CCA and non-tumor samples were downloaded from UCSC Xena, and differentially expressed genes [defined as those with a log (fold change) equal to 1 and P<0.05] were analyzed using the edgeR package (
Predicted target genes of miR-132-3p were obtained from miRWalk 2.0 (
Gene Ontology (GO) annotation of the aforementioned overlapped genes was performed in WebGestalt 2017 (
TCGA mRNA expression profiles were used to validate the expression levels of hub genes at the mRNA level. The Human Protein Atlas (
The GEO datasets (GSE32957, GSE47764 and GSE53992) indicated that miR-132-3p was upregulated in CCA (
The results also indicated that miR-132-3p may have potential as a biomarker to distinguish CCA tissues from non-cancer tissues based on ROC curves of RT-qPCR, miRNA-microarray and RNA-sequencing data (
No significant association between miR-132-3p levels and survival was observed either in the miRNA-sequencing data from TCGA or GEO GSE53870 data (
In total, 3,309 differentially expressed genes in CCA were identified, including 1,619 upregulated and 1,690 downregulated genes. Since miR-132-3p is highly expressed in CCA, downregulated genes are more likely to be direct targets of miR-132-3p. Due to the absence of data on the protein levels of the predicted genes, the current study focused on genes influenced by miR-132-3p at the mRNA level. In total, 555 overlapped genes were obtained, including downregulated and predicted genes (
The PPI network constructed in the present study is shown in
To the best of our knowledge, the expression levels and potential target genes of miR-132-3p in CCA have not been investigated to date. The present study, by combining RT-qPCR, miRNA-microarray and RNA-sequencing data, demonstrated that miR-132-3p was significantly upregulated in 321 CCA tissues compared with in 253 non-tumor controls. Furthermore, higher levels of miR-132-3p were significantly associated with CCA initiation and progression, which may be in part due to multiple target genes and signaling pathways.
miR-132-3p has been reported to be differentially expressed in numerous diseases. Notably, it is highly expressed in sural nerve biopsies from patients with neuropathy exhibiting neuropathic pain compared with those without pain (
The clinical role of a miRNA depends on its specific targets. Regarding the target candidates of miR-132-3p, only a few genes have been identified thus far. In breast cancer, miR-132-3p contributes to the post-transcriptional regulation of BCRP/ABCG2 (
According to previously published studies, the six hub target genes identified in the current study are closely associated with numerous types of cancer. GHR has been verified to be involved in triple-negative breast cancer (
The present study has several limitations. Firstly, the sample size used for RT-qPCR testing was relatively small, which may decrease the accuracy of the conclusions. Secondly, the role of miR-132-3p in progression and survival requires further study. Thirdly, the potential target genes of miRNA-132-3p were only initially verified by their expression levels; therefore, further
In conclusion, upregulation of miR-132-3p may serve a pivotal role in the tumorigenesis and progression of CCA by targeting different pathways. Further studies are required to support the current findings.
Not applicable.
The study was supported by the Promoting Project of Basic Capacity for Young and Middle-aged University Teachers in Guangxi (grant no. 2017KY0111), Innovation Project of Guangxi Graduate Education (grant no. YCBZ2017045) and the National Natural Science Foundation of China (grant no. 31760319).
The datasets generated and/or analyzed during the current study are available in the TCGA (
HYW performed RT-qPCR, analyzed and interpreted data, and drafted the manuscript. SX, AGL, MDW, ZBC, YXL, YH, MJL, QPH and SLP analyzed data from microarrays and miRNA RNA-sequencing, and participated in all data processing, RT-qPCR and paper draft writing. All authors read and approved the final manuscript.
This study was approved by the Ethics Committee of First Affiliated Hospital, Guangxi Medical University, China. Informed written consent was obtained from all patients participating in the study.
Not applicable.
The authors declare that they have no competing interests.
Flowchart representing the main design of the present study. miR-132-3p, microRNA-132-3p.
Scatterplots based on Gene Expression Omnibus datasets and in-house RT-qPCR analysis. (A) GSE32957, (B) GSE47764, (C) GSE53870, (D) GSE53992, (E) GSE57555, (F) GSE59856, (G) GSE60978 and (H) GSE85589 data. (I) In-house RT-qPCR analysis data. miR-132-3p, microRNA-132-3p; RT-qPCR, reverse transcription-quantitative PCR.
Continuous variable meta-analysis based on RT-qPCR, TGCA and Gene Expression Omnibus data. Forest plots based on the (A) fixed and (B) random effect models. (C) Sensitivity analysis. (D) Forest plot following exclusion of GSE53870. (E) Funnel plot. RT-qPCR, reverse transcription-quantitative PCR; TCGA, The Cancer Genome Atlas.
Receiver operating characteristic curves based on Gene Expression Omnibus datasets and in-house RT-qPCR data. (A) GSE32957, (B) GSE47764, (C) GSE53870, (D) GSE53992, (E) GSE57555, (F) GSE59856, (G) GSE60978 and (H) GSE85589 data. (I) In-house RT-qPCR analysis data. AUC, area under the curve; RT-qPCR, reverse transcription-quantitative PCR.
Validation of the ability of microRNA-132-3p to distinguish cholangiocarcinoma tissues from non-cancerous tissues. (A) sROC. (B) Pooled sensitivity and specificity. (C) Positive and negative likelihood ratios. (D) Negative likelihood ratios. (E) Forest plot of diagnostic odds ratio. sROC, summary receiver operating characteristic; RT-qPCR, reverse transcription-quantitative PCR; TCGA, The Cancer Genome Atlas.
Survival analysis of miR-132-3p in CCA based on TCGA data and Gene Expression Omnibus GSE53870 datasets. Survival curves based on the (A) median and (B) mean expression levels of miR-132-3p in TCGA dataset. Survival curves based on the (C) median and (D) mean expression levels of miR-132-3p in the GSE53870 dataset. CCA, cholangiocarcinoma; miR-132-3p, microRNA-132-3p; TCGA, The Cancer Genome Atlas.
Association between miR-132-3p expression and pathological stage in CCA, and diagnostic value of miR-132-3p expression based on miRNA-sequencing data from TCGA. (A) Scatterplots of CCA and non-tumor tissues. (B) ROC curve analysis of CCA and non-tumor tissues. (C) Scatterplots of pathological stage. (D) ROC curve analysis of pathological stage. (E) Scatterplots of grade. (F) ROC curve analysis of grade. CCA, cholangiocarcinoma; miR-132-3p, microRNA-132-3p; ROC, receiver operating characteristic.
Venn diagram based on the results of 12 online prediction databases and differentially expressed genes in TCGA. A total of 555 overlapped genes were subjected to further analysis. DEGS, differentially expressed genes; TCGA, The Cancer Genome Atlas.
Protein-protein interaction network based on 14 genes involved in the ‘Focal Adhesion-PI3K-Akt-mTOR-signaling pathway’.
Bar charts of GO annotation and WikiPathway analysis of target genes of microRNA-132-3p. (A) WikiPathway analysis. (B) GO annotation analysis. GO, Gene Ontology.
(A) Biological processes, (B) cellular components and (C) molecular functions were visualized using the BiNGO plugin in Cytoscape.
Protein-protein interaction of target genes. The network was performed with a medium confidence (combined score >0.4) and disconnected nodes were deleted.
Validation of 14 hub genes at the mRNA level based on The Cancer Genome Atlas data. (A) CHRM2, (B) FOXO1, (C) GHR, (D) HGF, (E) IFNAR1, (F) IGF1, (G) IL6R, (H) IRS1, (I) ITGA9, (J) PIK3R1, (K) PPP2R1B, (L) RAF1, (M) TNN and (N) SLC2A2.
Validation of 10 hub genes at the protein level based on The Human Protein Atlas data. (A) CHRM2, available from:
ROC curves of six selected genes based on The Cancer Genome Atlas. (A) GHR, (B) HGF, (C) IGF1, (D) IRS1, (E) ITGA9 and (F) PIK3R1. AUC, area under the curve; ROC, receiver operating characteristic.
Survival curve analysis of six selected genes based on The Cancer Genome Atlas. (A) GHR, (B) HGF, (C) IGF1, (D) IRS1, (E) ITGA9 and (F) PIK3R1.
Information of all studies with miR-132-3p expression data.
Patients | Control | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Study | Year | Country | Platform | n | Mean | SD | n | Mean | SD | t | P-value | (Refs.) |
GSE85589 | 2016 | South Korea | GPL19117 | 101 | 0.7245 | 0.29268 | 19 | 0.7639 | 0.22898 | 0.555 | 0.58 | – |
GSE60978 | 2015 | Norway | GPL15159 | 8 | 8.1602 | 0.36503 | 6 | 7.3325 | 1.2594 | −1.783 | 0.1 | ( |
GSE59856 | 2015 | Japan | GPL18941 | 98 | 2.6523 | 0.22236 | 150 | 2.6411 | 0.17843 | −0.436 | 0.663 | ( |
GSE57555 | 2015 | Japan | GPL18044 | 11 | −0.0022 | 0.07204 | 11 | −0.0143 | 0.07242 | −0.393 | 0.698 | ( |
GSE53992 | 2014 | USA | GPL18159 | 16 | −3.6742 | 0.8184 | 28 | −5.214 | 2.1984 | −2.686 | 0.01 | ( |
GSE53870 | 2015 | China | GPL18118 | 63 | 9.2162 | 0.20197 | 9 | 10.2856 | 0.93524 | 3.419 | 0.009 | – |
GSE47764 | 2013 | China | GPL11487 | 3 | 5.9577 | 0.27337 | 3 | 4.7176 | 0.13126 | −7.083 | 0.002 | ( |
GSE32957 | 2012 | USA | GPL14732 | 23 | 5.7495 | 0.90686 | 5 | 3.9843 | 0.7151 | −4.065 | <0.001 | ( |
TCGA | – | – | – | 36 | 6.9586 | 0.52035 | 9 | 6.3613 | 0.51683 | −3.084 | 0.004 | – |
RT-qPCR | 2019 | China | – | 25 | 2.4634 | 1.59019 | 22 | 1.0190 | 0.83004 | −3.969 | <0.001 | – |
RT-qPCR, reverse transcription-quantitative PCR; TCGA, The Cancer Genome Atlas.
Relationship between miR-132-3p expression and clinicopathological features in patients with CCA based on The Cancer Genome Atlas data.
Clinicopathological feature | n | miR-132-3p expression log2 (total_TPM +1), mean ± standard deviation | t | P-value |
---|---|---|---|---|
Tissue | −3.084 | 0.004 | ||
CCA | 36 | 6.9586±0.5204 | ||
Non-tumor | 9 | 6.3613±0.5168 | ||
Sex | −0.356 | 0.724 | ||
Male | 16 | 6.9236±0.5276 | ||
Female | 20 | 6.9866±0.1177 | ||
Age, years | −1.504 | 0.142 | ||
<60 | 12 | 7.1398±0.4039 | ||
≥60 | 24 | 6.8680±0.5553 | ||
Smoking status | −0.054 | 0.958 | ||
No | 22 | 6.9617±0.6113 | ||
Yes | 12 | 6.9719±0.3962 | ||
T stage | −1.462 | 0.153 | ||
T1 | 19 | 6.8406±0.3793 | ||
T2-T3 | 17 | 7.0905±0.6289 | ||
N stage | −1.411 | 0.167 | ||
N0 | 26 | 6.8838±0.5470 | ||
N1-NX | 10 | 7.1532±0.4042 | ||
M stage | −0.738 | 0.465 | ||
M0 | 28 | 6.9242±0.5332 | ||
M1-MX | 8 | 7.0792±0.4856 | ||
Pathological stage | −2.039 | 0.003 | ||
I–II | 29 | 6.8754±0.5279 | ||
III–IVB | 7 | 7.3034±0.3267 | ||
Grade | −2.176 | 0.037 | ||
G1-G2 | 16 | 6.7581±0.5297 | ||
G3-G4 | 20 | 7.1191±0.4651 |
CCA, cholangiocarcinoma; miR-132-3p, microRNA-132-3p.
Pathways related to microRNA-132-3p in cholangiocarcinoma.
Geneset | Description | Count | P-value |
---|---|---|---|
WikiPathway | |||
WP143 | Fatty Acid β Oxidation | 5 | 0.002 |
WP3932 | Focal Adhesion-PI3K-Akt-mTOR-signaling pathway | 14 | 0.043 |
WP3972 | PDGFR-β pathway | 3 | 0.046 |
Biological process | |||
GO:0006082 | Organic acid metabolic process | 96 | <0.001 |
GO:0016054 | Organic acid catabolic process | 41 | <0.001 |
GO:0019752 | Carboxylic acid metabolic process | 92 | <0.001 |
GO:0032787 | Monocarboxylic acid metabolic process | 62 | <0.001 |
GO:0043436 | Oxoacid metabolic process | 95 | <0.001 |
GO:0044282 | Small molecule catabolic process | 48 | <0.001 |
GO:0046395 | Carboxylic acid catabolic process | 41 | <0.001 |
GO:0055114 | Oxidation-reduction process | 79 | <0.001 |
GO:0044712 | Single-organism catabolic process | 72 | <0.001 |
GO:0006629 | Lipid metabolic process | 89 | <0.001 |
Cellular component | |||
GO:0005739 | Mitochondrion | 105 | <0.001 |
GO:0044429 | Mitochondrial part | 70 | <0.001 |
GO:0005777 | Peroxisome | 25 | <0.001 |
GO:0042579 | Microbody | 25 | <0.001 |
GO:0005759 | Mitochondrial matrix | 37 | <0.001 |
GO:0044438 | Microbody part | 17 | <0.001 |
GO:0044439 | Peroxisomal part | 17 | <0.001 |
GO:0005782 | Peroxisomal matrix | 10 | <0.001 |
GO:0031907 | Microbody lumen | 10 | <0.001 |
GO:0031966 | Mitochondrial membrane | 38 | <0.001 |
Molecular function | |||
GO:0048037 | Cofactor binding | 42 | <0.001 |
GO:0050662 | Coenzyme binding | 33 | <0.001 |
GO:0016491 | Oxidoreductase activity | 59 | <0.001 |
GO:0016903 | Oxidoreductase activity, acting on the aldehyde or oxo group of donors | 13 | <0.001 |
GO:0000062 | Fatty-acyl-CoA binding | 10 | <0.001 |
GO:0004879 | RNA polymerase II transcription factor activity, ligand-activated sequence-specific DNA binding | 11 | <0.001 |
GO:0098531 | Transcription factor activity, directligand regulated sequence-specific DNA binding | 11 | <0.001 |
GO:0016614 | Oxidoreductase activity, acting on CH-OH group of donors | 17 | <0.001 |
GO:0016620 | Oxidoreductase activity, acting on the aldehyde or oxo group of donors, NAD or NADP as acceptor | 9 | <0.001 |
GO:0008514 | Organic anion transmembrane transporter activity | 19 | <0.001 |
GO, Gene Ontology.
Binding sites for miR-132-3p of six target genes.
Target | miR-132-3p target region (3′-untranslated region) | Seed match | Context score percentile | Conserved branch length | Pct |
---|---|---|---|---|---|
GHR | 234–240 | 7mer-m8 | 95 | 5.527 | 0.54 |
HGF | 3,387-3,393 | 7mer-m8 | 92 | 1.625 | <0.1 |
IGF1 | 6,684-6,690 | 7mer-1A | 44 | 0.775 | <0.1 |
IRS1 | 1,875-1,881 | 7mer-m8 | 65 | 2.010 | <0.1 |
ITGA9 | 292–298 | 7mer-1A | 44 | 5.855 | 0.29 |
PIK3R1 | 1,083-1,089 | 7mer-m8 | 82 | 0.154 | <0.1 |
miR-132-3p, microRNA-132-2p; Pct, probability of conserved targeting.