Abstract
Background
Hepatocellular carcinoma (HCC) is the second-highest cause of
malignancy-related death worldwide, and many physiological and
pathological processes, including cancer, are regulated by microRNAs
(miRNAs). miR-193a-3p is an anti-oncogene that plays an important part
in health and disease biology by interacting with specific targets and
signals.
Methods
In vitro assays were performed to explore the influences of miR-193a-3p
on the propagation and apoptosis of HCC cells. The sequencing data for
HCC were obtained from The Cancer Genome Atlas (TCGA), and the
expression levels of miR-193a-3p in HCC and non-HCC tissues were
calculated. The differential expression of miR-193a-3p in HCC was
presented as standardized mean difference (SMD) with 95% confidence
intervals (CIs) in Stata SE. The impact of miR-193a-3p on the prognoses
of HCC patients was determined by survival analysis. The potential
targets of miR-193a-3p were then predicted using miRWalk 2.0 and
subjected to enrichment analyses, including Gene Ontology (GO)
annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway
analysis, and Protein-Protein Interaction (PPI) network analysis. The
interaction between miR-193a-3p and one predicted target, Cyclin D1
(CCND1), was verified by dual luciferase reporter assays and Pearson
correlation analysis.
Results
MiR-193a-3p inhibited the propagation and facilitated the apoptosis of
HCC cells in vitro. The pooled SMD indicated that miR-193a-3p had a low
level of expression in HCC (SMD: −0.88, 95% CI [−2.36 −0.59]). Also,
HCC patients with a higher level of miR-193a-3p expression tended to
have a favorable overall survival (OS: HR = 0.7, 95% CI [0.43–1.13],
P = 0.14). For the KEGG pathway analysis, the most related pathway was
“proteoglycans in cancer”, while the most enriched GO term was “protein
binding”. The dual luciferase reporter assays demonstrated the direct
interaction between miR-193a-3p and CCND1, and the Pearson correlation
analysis suggested that miR-193a-3p was negatively correlated with
CCND1 in HCC tissues (R = − 0.154, P = 0.002).
Conclusion
miR-193a-3p could suppress proliferation and promote apoptosis by
targeting CCND1 in HCC cells. Further, miR-193a-3p can be used as a
promising biomarker for the diagnosis and treatment of HCC in the
future.
Keywords: Mir-193a-3p, Hepatocellular Carcinoma, Cyclin D1, Cell
proliferation, Apoptosis, Bioinformatics
Introduction
Hepatocellular carcinoma (HCC) is the most prevalent type of primary
liver cancer, and it accounts for approximately 70 to 90% of liver
cancer cases. In terms of morbidity, it ranks fifth among males, ninth
among females, and second among factors for cancer death worldwide
([42]Schoenberg et al., 2018). Hepatocellular carcinoma occurs in the
environment of chronic hepatitis and is highly associated with
hepatitis viral infection (hepatitis B or C) or toxin exposure
(e.g., alcohol and aflatoxins). For patients with chronic hepatitis B
or C, even effective antiviral therapy cannot completely eliminate the
risk of HCC occurrence or relapse after effective treatment. However,
the molecular mechanism of HCC remains poorly understood, and it is
necessary to explore the effective biomarkers for HCC. MicroRNAs
(miRNAs) control a variety of physiological and pathological processes,
including cancer. MiRNAs have been shown to be directly involved in the
cell proliferation, apoptosis, and metastasis of HCC by targeting many
key protein-coding genes ([43]Huang & He, 2011). The aberrant
expression of miRNAs and their corresponding target genes may be
essential in the initiation and development of hepatic carcinoma.
MiRNAs are internal non-coding small RNAs regulating protein-coding
genes in a sequence-specific manner ([44]Shi, Han & Spivack, 2013), and
they adjust the expression of numerous genes by attaching to specific
sequences in the 3′-untranslated region (UTR). This results in mRNA
degradation or the suppression of mRNA translation ([45]Moura, Borsheim
& Carvalho, 2014). Multiple studies have shown that miRNAs participate
in the invasion and metastasis of HCC ([46]Di Leva, Briskin & Croce,
2012; [47]Sun et al., 2013). Some miRNAs could also function as
biomarkers for early diagnosis, stratification, and response evaluation
in HCC ([48]Braconi & Patel, 2008). [49]Chen et al. (2018) demonstrated
that miR-590-5p inhibited HCC chemoresistance by targeting
yes-associated protein 1 (YAP1). MiR-133b promotes cell proliferation
and metastasis in HCC by regulating splicing factor 3b subunit 4
(SF3B4) ([50]Liu et al., 2018b). MiR-3650 suppresses HCC migration and
epithelial-mesenchymal transition (EMT) by directly targeting
neurofascin ([51]Wu et al., 2019). Targeting miR-494-3p, miR-126-3p, or
miR-342-3p could inhibit HCC invasion and metastasis ([52]Liu et al.,
2018a; [53]Lou et al., 2018). [54]Gu et al. (2019) concluded that the
miR-144/CCNB1 (Cyclin B1) axis was important and that the inhibition of
miR-144 could improve the outcomes of human HCC. MiR-140-3p increases
the sensitivity of HCC cells to sorafenib ([55]Li et al., 2018). A
previous study showed that miR-193a-3p expression was regulated by DNA
promoter hypermethylation and miR-193a-3p facilitated HCC resistance to
5-fluorouracil (5-FU) via repressing serine/arginine-rich splicing
factor 2 (SRSF2) ([56]Ma et al., 2012). Our team found that miR-193a-3p
was downregulated in HCC by means of in-house quantitative reverse
transcription polymerase chain reactions (qRT-PCR) in 2015, and it
could also serve as a prognostic indicator ([57]Liu et al., 2015).
However, in terms of expression, there are no research papers on HCC
concerning the correlation between miR-193a-3p and its target genes.
Therefore, we forecasted the target genes of miR-193a-3p in the present
study.
Previous studies have demonstrated that miR-193a-3p inhibits the
expression of some carcinogenic factors, such as CDK 6, c-kit, E2F6,
and E-cadherin, which could enhance tumor invasion and angiogenesis
([58]Gao et al., 2011; [59]Iliopoulos, Rotem & Struhl, 2011; [60]Liu et
al., 2015; [61]Ma et al., 2012). Cyclin, a group of regulatory subunits
of the holoenzyme, are able to regulate cellular processes through the
cell cycle ([62]Liu et al., 2017). As a proto-oncogene
([63]Karimkhanloo et al., 2017), CCND1 can promote DNA synthesis, cell
proliferation, cell colonization, and hepatoma formation ([64]Wu, Lan &
Liu, 2019). Several studies have confirmed that miR-193a-3p inhibits
the growth of gastric and prostate cancer cells by targeting CCND1
([65]Chou et al., 2018; [66]Liu et al., 2017), but its role in HCC
remains unclear. Therefore, we studied the relationship between
miR-193a-3p and its target genes in HCC, as well as the potential
mechanism involved.
We performed in vitro assays to explore the effect of miR-193a-3p on
the propagation and apoptosis of HCC cells. We then used the sequencing
data of HCC to determine the expression of miR-193a-3p and CCND1. The
impact of miR-193a-3p on the prognoses of patients with HCC was
evaluated by survival analysis. Finally, it was determined that
miR-193a-3p suppressed the proliferation and promoted the apoptosis of
HCC cells, and miR-193a-3p has a negative correlation with CCND1 in
HCC. For the first time, the interconnection between their expression
levels in HCC was mined in depth, and the underlying molecular
mechanism of miR-193a-3p in HCC was studied.
Materials & Methods
Re-expression and suppression of miR-193a-3p in HCC cells
The HCC cell line Hep3B was cultured at 37 °C in Dulbecco’s Modified
Eagle Medium (Thermo Fisher Scientific, Waltham, MA, USA) supplemented
with 10% fetal bovine serum, 100 units/ml penicillin, and 100 ug/ml
streptomycin in a humid incubator with 5% CO2. In accordance with the
manufacturer’s procedure, we used CombiMag Magnetofection (OZ
Biosciences, Marseille Cedex 9, France) to transfect Hep3B cells with
the miR-193a-3p inhibitor (sequence: 5′-ACUGGGACUUUGUAGGCCAGUU-3′), the
miRNA inhibitor’s negative control (sequence:
5′-ACGUGACACGUUCGGAGAATT-3′), the simulated miR-193a-3p (sequence:
5′-AACUGGCCUACAAAGUCCCAGU-3′), and the negative control for the miRNA
simulation (sequence: 5′-UUCUCCGAACGUGUCACGUTT-3′) (GenePharma,
Shanghai, China) at an equal concentration of 20 µM (20 pmol/µl). Hep3B
cells were seeded into a 96-well plate at a density of 3 × 10^4/well.
After being transfected with miRNA simulations or miRNA inhibitors,
cells were cultivated for ten days. Among them, zero-day samples and
intermediate samples at the fifth day were gathered and analyzed via
diverse experiments. A cell proliferation assay was performed using a
Promega MTS kit (cat. no. G3580; Promega Corporation, Beijing, China).
For the apoptosis assay, cells were double-stained with Hoechst
33,342/propidium iodide (PI) kit (Sigma-Aldrich Co., St Louis, MO, USA)
according to the manufacturer’s instructions. The viable and apoptotic
cells were observed and counted under a fluorescence microscope (100×,
ZEISS Axiovert 25, Zaventem, Belgium).
qRT-PCR
The expression of miR-193a-3p was then confirmed via qRT-PCR. Total RNA
Kit I (Promega, Beijing, China) was used to extract total RNA from the
above-mentioned cells. The tailing reaction miRNA First Strand cDNA
Synthesis (Sangon Biotech, Shanghai, China) was used to inversely
transcribe cDNA. The primer sequence for miR-193a-3p was 5′-
AACUGGCCUACAAAGUCCCAGU-3′. The primer sequence for U6 (internal
control) was 5′-ACACTCCAGCTGGGAACTGGCCTACAAAGTCC-3′. The PCR was
performed using an SYBR Green MicroRNAs qPCR Kit (SYBR Green Method)
(Sangon Biotech) on an ABI Prism 7500 (Applied Biosystems, Foster City,
CA, USA). The expression of miR-193a-3p in each group was initially
calculated via the 2
[MATH:
ˆ :MATH]
^(−ΔΔCq) method and normalized to the mock group (cells that were
transfected solely with CombiMag Magnetofection). Subsequently, the
change in miR-193a-3p level upon transfection was calculated with the
formula (2
[MATH:
ˆ :MATH]
^ΔΔCq-1) ([67]Chen et al., 2012).
Differential expression of miR-193a-3p in HCC in miRNA-sequencing data
We downloaded sequencing data for miR-193a-3p’s expression profile in
HCC from The Cancer Genome Atlas (TCGA) on May 1, 2019, including 369
HCC tissues and 49 non-HCC tissues. We also used the in-house qRT-PCR
results of our team’s work in 2015, which contained 95 HCC tissues and
95 non-HCC tissues. The Medical Ethics Committee of First Affliated
Hospital of Guangxi Medical University approved this study (approval
no. 2015 KY-E-041). Each participant signed an informed consent. We
computed the number, mean, and standard deviation of miR-193a-3p
expression levels in cancer and non-cancer groups. Next, we used
StataSE (StataCorp, College Station, TX, USA), SPSS 25.0 (IBM, Armonk,
New York) and GraphPad Prism 8 software (GraphPad Software Inc., San
Diego, CA, US) for the statistical analyses. By comparing the
expression in HCC and non-HCC tissues with standardized mean difference
(SMD) and a violin plot, the differential expression of miR-193a-3p in
HCC and non-HCC tissues was confirmed, and its diagnostic significance
was evaluated. We also retrieved the expression data for CCND1 in HCC
from 371 HCC and 50 non-HCC samples in the form of RNA sequencing data.
The association between miR-193a-3p and CCND1 was analyzed using these
downloaded data in SPSS 25.0, and P < 0.05 was defined as statistically
significant.
Relationship between miR-193a-3p and progression of HCC
We retrieved the Kaplan–Meier plots from the Kaplan–Meier Plotter
website ([68]http://kmplot.com/) to analyze the survival discrepancies
between patients with high and low expression levels of miR-193a-3p and
further evaluate its prognostic value in HCC.
Enrichment analyses and a protein-protein interaction (PPI) network
construction
To further explore the potential molecular mechanism of miR-193a-3p in
HCC, we conducted a bioinformatics analysis. First, the potential
targets of miR-193a-3p were predicted using miRWalk 2.0
([69]http://zmf.umm.uni-heidelberg.de/mirwalk2), a comprehensive
database comprised of twelve predictive online tools:
microT-CDSmiRWalk, MicroT4microT4, miRanda, miRBridge, miRDB, miRMap,
miRNAMap, PICTAR2, PITA, RNA22, RNAhybrid, and TargetScan. Genes that
appeared in more than five platforms were subjected to subsequent
analysis. The Kyoto Encyclopedia Genes and Genomes (KEGG) pathway terms
and Gene Ontology (GO) biological processes, cellular components, and
molecular functions were analyzed using the Database for Annotation,
Visualization, and Integrated Discovery (DAVID 6.7)
([70]https://david.ncifcrf.gov/). We defined the significant GO and
KEGG pathways with the criterion of P < 0.05.
To reveal the link between the target genes, we constructed a PPI
network using STRING software v10.0 ([71]https://string-db.org/). Based
on the number of nodes and edges, the genes most related to miR-193a-3p
were identified. Hub genes were identified by the numerical digits of
the degrees of every node and edge. P < 0.05 was considered
statistically significant. Among the hub genes, we selected CCND1 as
the target gene for miR-193a-3p in this study, and the relationship
between them was explored in depth.
Dual-Luciferase reporter experiments
We used the Dual-Luciferase® Reporter Assay System (Promega, WI, USA)
to identify the activity of luciferase and the target gene’s 3′UTR
plasmids (CCND1 3′UTR + miR-193a-3p) or no-load plasmids (CCND1
3′UTR-NC + miR-193a-3p) in transfecting HEK293T cells. To make the
experimental results more reliable, we set up a positive reference
miRNA group (has-miR-146b vector plasmid) and a positive reference
miRNA NC (negative control) group (TRAF6 3′UTR plasmids).
Statistical analysis
We performed an independent samples t-test and a Pearson correlation
analysis (two-tailed) using SPSS 25.0 to analyze the data we extracted
from the miRNA-sequencing data and the previous in-house qRT-PCR data.
We considered P < 0.05 to indicate statistical significance. We also
used StataSE to perform the meta-analysis, and the combined SMD with
95% confidence intervals (CIs) were computed to estimate the continuous
outcomes. Violin plots and bar charts were generated using GraphPad
Prism 8. One-way analysis of variance (ANOVA) and the post-hoc
Bonferroni test were applied in the in vitro experiments to draw
comparisons between groups in GraphPad Prism8. We performed GO and KEGG
pathway analyses through DAVID and the R package, using ‘GOplot’ and
‘ggplot2’ to visualize the results. In the meantime, based on
bioinformatics predictions, two binding sites of miR-193a-3p on CCND1
and the negative correlation between the two genes in various cancers
were found on starBase v3.0
([72]http://starbase.sysu.edu.cn/index.php).
Results
miR-193a-3p inhibited cell propagation and promoted apoptosis in vitro
Compared with the blank control and the negative simulated control
group, the miR-193a-3p level in Hep3B cells that treated with
miR-193a-3p inhibitor was significantly decreased at five days after
transfection (P < 0.001). In contrast, the transfection of the
miR-193a-3p simulation led to a sharp increase in miR-193a-3p level
within five and ten days (P < 0.01) ([73]Fig. 1A). To determine the
effect of miR-193a-3p on cell proliferation, viable (Hoechst 33342
positive/PI negative) cells were counted after transfection under a
microscope. We observed that upon miR-193a-3p’s simulation, the amount
of cell proliferation significantly decreased at five and ten days
(P < 0.01) ([74]Fig. 1B). Apoptotic assays showed that upon the
upregulation of miR-193a-3p, the apoptotic cells increased 1.4 folds.
However, under inhibitor action, the quantity of apoptotic cells
decreased slightly in the Hep3B cells, though this change was not
significant ([75]Fig. 1C).
Figure 1. Results of in vitro experiments of miR-193a-3p in HCC.
Figure 1
[76]Open in a new tab
(A) Expression level of miR-193a-3p in HCC cell line Hep3B. Hep3B cells
were treated with inhibitor or mimic of miR-193-3p or negative control
and the alteration of miR-193-3p expression was confirmed by qRT-PCR.
(B) Effect of miR-193a-3p on proliferation of Hep3B cells as determined
by Hoechst 33342/propidium iodide (PI) dual-luciferase chromatin
staining. (C) Effect of miR-193a-3p on apoptosis in Hep3B cells as
determined by Hoechst 33342/propidium iodide (PI) dual-luciferase
chromatin staining. Hep3B cells were cultured with miR-193a-3p
inhibitor, mimic or different controls for 0, 5, and 10 days, and using
the CellTiter-Blue cell viability assay. *P < 0.05, **P < 0.01,
***P < 0.0001, compared to blank control or negative control at the
same day.
miRNA expression level and its clinical significance in HCC
Four hundred and sixty-four HCC and 144 non-tumor tissue samples were
collected from miRNA-sequencing data (online) and the in-house qRT-PCR.
We used violin plots to visualized the differential expression of
miR-193a-3p. Based on the data for miRNA sequencing, no statistical
difference in miR-193a-3p level was observed between HCC and non-tumor
tissues (P = 0.3796) ([77]Fig. 2A). In contrast, miR-193-3p was
downregulated in HCC tissues based on the results of in-house qRT-PCR
(P < 0.0001) ([78]Fig. 2B). The pooled result from a random-effects
model (I^2 = 97.7%; P = 0.000) indicated that miR-193a-3p was expressed
at a low level in HCC (SMD: -0.88; 95% CI: -2.36–0.59) ([79]Fig. 2C).
The Kaplan–Meier plot indicated that HCC patients with a higher level
of miR-193a-3p expression tended to have a more favorable overall
survival rate than those with a low level of expression, though the
difference was not significant (OS: HR=0.7, 95% CI [0.43–1.13],
P = 0.14) ([80]Fig. 2D).
Figure 2. The expression of miR-193-3p and its clinical significance in HCC.
Figure 2
[81]Open in a new tab
(A) Violin plot of miR-193a-3p expression in HCC based on TCGA
database. (B) Violin plot of miR-193a-3p expression in HCC based on
in-house qRT-PCR. (C) Forest plot of miR-193a-3p expression in HCC
(random-effects model). SMD < 0 indicates that miR-193-3p was
downregulated in HCC tissues as compared with non-tumor tissues. (D)
Overall survival (OS) analysis in Kaplan-Meier Plotter online website.
Enrichment analyses of candidate target genes and PPI network construction
We conducted GO and KEGG pathway analyses to study the functional
connections between the genes related to miR-193a-3p. [82]Table 1 shows
the top four significant gene annotations in GO and the top five
pathways in KEGG regarding the potential target of miR-193a-3p. As can
be seen in [83]Figs. 3 and [84]4, the KEGG pathway analysis showed that
“Proteoglycans in cancer” is the most closely related pathway, while
the “ErbB signaling pathway” is the second most closely related
pathway. Among all the miR-193a-3p-related genes, the most enriched GO
term is “protein binding”. The PPI network in [85]Fig. 5 showed the
nine genes most related to miR-193-3p, including KRAS, IGF1R, TNS1,
YWHAZ, MAPK8, MDM2, BCL2L1, MAPK1, and CCND1. Based on the enrichment
analyses and the constructed PPI network, CCND1 was selected as the
target of miR-193a-3p for the subsequent research.
Table 1. Significant gene annotations or pathways of GO and KEGG of potential
target of miR-193a-3p by DAVID.
Category ID Term Count P-Value
GOTERM_BP_DIRECT GO:0042147 Retrograde transport, endosome to Golgi 9
1.60E-04
GOTERM_BP_DIRECT GO:0061025 Membrane fusion 6 3.00E-03
GOTERM_BP_DIRECT GO:0030968 Rndoplasmic reticulum unfolded protein
response 6 3.40E-03
GOTERM_BP_DIRECT GO:0086002 Cardiac muscle cell action potential
involved in contraction 4 5.20E-03
GOTERM_CC_DIRECT GO:0016020 Membrane 78 1.70E-05
GOTERM_CC_DIRECT GO:0000139 Golgi membrane 29 1.10E-04
GOTERM_CC_DIRECT GO:0005829 Cytosol 97 1.60E-03
GOTERM_CC_DIRECT GO:0005789 Endoplasmic reticulum membrane 32 4.60E-03
GOTERM_MF_DIRECT GO:0005484 SNAP receptor activity 6 1.70E-03
GOTERM_MF_DIRECT GO:0017137 Rab GTPase binding 10 3.30E-03
GOTERM_MF_DIRECT GO:0005515 Protein binding 225 3.70E-03
GOTERM_MF_DIRECT GO:0042803 Protein homodimerization activity 27
1.50E-02
KEGG_PATHWAY hsa05214 Glioma 8 9.30E-04
KEGG_PATHWAY hsa05212 Pancreatic cancer 8 9.30E-04
KEGG_PATHWAY hsa05205 Proteoglycans in cancer 14 1.10E-03
KEGG_PATHWAY hsa04012 ErbB signaling pathway 9 1.20E-03
KEGG_PATHWAY hsa05220 Chronic myeloid leukemia 8 1.70E-03
[86]Open in a new tab
Figure 3. Enrichment analysis of miR-193a-3p related genes in the KEGG and GO
pathways.
[87]Figure 3
[88]Open in a new tab
(A) The related genes in a Chord plot are linked to their enriched GO
annotations via ribbons. (B) A cluster plot shows a circular dendrogram
of the clustering analysis of expression profiles. The inner ring shows
the color-coded logFC, while the outer ring shows the GO annotations.
(C) Chord plot of KEGG pathways. (D) Cluster plot of KEGG pathways. Red
codes next to the selected genes indicate upregulation, and blue codes
indicate downregulation.
Figure 4. Concentric circle diagram of the GO analysis and KEGG pathways.
Figure 4
[89]Open in a new tab
(A) Concentric circle diagram of the GO analysis. The nodes in the
concentric circle represent the co-expression genes clustered in the GO
annotations. (B) Concentric circle graph of KEGG pathways. The larger
and darker areas in the inner circle are more abundant.
Figure 5. PPI network of nine representative target genes of miR-193a-3p in
HCC.
[90]Figure 5
[91]Open in a new tab
The proteins in the blue rectangular boxes are hub genes, while the
gray continuous lines represent interactions between individual
proteins.
Dual-luciferase reporter assays verified the interaction between miR-193a-3p
and CCND1
Through a search on miRwalk 2.0, we found the base-complementary
pairing between miR-193a-3p and CCND1 ([92]Fig. 6A). Subsequently,
double luciferase reporter assays verified the direct interaction
between miR-193a-3p and CCND1. The relative luciferase activity of the
CCND1 3′UTR+miR-193a-3p group decreased as compared with CCND1 3′UTR-NC
+miR-193a-3p cells (P = 0.006) ([93]Fig. 6B). The relative luciferase
activity of the positive-control miRNA group was lower than that of the
positive-control miRNA NC group (P < 0.001) ([94]Fig. 6B).
Figure 6. Relationship between miR-193a-3p and CCND1.
[95]Figure 6
[96]Open in a new tab
(A) Complementary base sequences of miR-193a-3p and CCND1. (B) The
relative luciferase activity of CCND1 3′UTR+miR-193a-3p decreased as
compared with CCND1 3′UTR-NC + miR-193a-3p cells. The relative
luciferase activity of the positive control miRNA group was lower than
that of the positive control miRNA NC group. (C) Negative correlation
between miR-193a-3p and CCND1 in TCGA database-Pearson correlation
analysis (double-tailed). Positive reference miRNA group: hsa-miR-146b
vector plasmid; positive reference miRNA NC (negative control) group:
TRAF6 3′UTR plasmids.
Expression of miR-193a-3p was negatively correlated with that of CCND1
The result of the Pearson correlation analysis (two-tailed) showed a
trend of negative correlation between miR-193a-3p and CCND1 in the
RNA-sequencing database (P = 0.002, R = −0.154) ([97]Fig. 6C). To
validate this correlation, we acquired the expression of miR-193a-3p
and CCND1 in twenty types of cancer from starBase V3.0. There were two
binding sites between miR-193-3p and CCND1, namely “chr11:
69467239-69467244[+]” and “chr11: 69467498-69467504[+]”. A negative
correlation was observed at both sites in adrenocortical carcinoma,
bladder urothelial sarcoma, liver hepatocellular cancer, lung
adenocarcinoma, mesothelioma, rectum adenocarcinoma, thyroid tumors,
and uterine corpus endometrial cancer ([98]Figs. 7 and [99]8).
Figure 7. Correlation between miR-193a-3p and CCND1 on the basis of starBase
v3.0 pan-cancer analysis project (binding site: chr11: 69467239-69467244[+]).
[100]Figure 7
[101]Open in a new tab
(A) Adrenocortical carcinoma. (B) Bladder urothelial carcinoma. (C)
Liver hepatocellular carcinoma. (D) Lung adenocarcinoma. (E)
Mesothelioma. (F) Rectum adenocarcinoma. (G) Thyroid carcinoma. (H)
Uterine corpus endometrial carcinoma.
Figure 8. Correlation between miR-193a-3p and CCND1 on the basis of starBase
v3.0 pan-cancer analysis project (binding site: chr11: 69467498-69467504[+]).
[102]Figure 8
[103]Open in a new tab
(A) Adrenocortical carcinoma. (B) Bladder urothelial carcinoma. (C)
Liver hepatocellular carcinoma. (D) Lung adenocarcinoma. (E)
Mesothelioma. (F) Rectum adenocarcinoma. (G) Thyroid carcinoma. (H)
Uterine corpus endometrial carcinoma.
Discussion
In this study, we first identified that miR-193a-3p can inhibit the
proliferation and promote the apoptosis of HCC through in vitro
experiments. We then collated and analyzed the expression profile of
the HCC sequencing data and found that miR-193a-3p had a low level of
expression in HCC. A survival analysis using online databases indicated
that HCC patients with higher miR-193a-3p levels tended to have
favorable prognoses. We used KEGG, GO pathway enrichment analysis, and
PPI network construction to explore the underlying mechanism of the
target genes. CCND1 was then defined as the key target gene of
miR-193a-3p, which was verified via the dual-luciferase reporter
assays. MiRNA-sequencing data for various tumors, including HCC,
confirmed that there was a negative correlation between the expression
of miR-193a-3p and CCND1. In this paper, it was first discovered that
miR-193a-3p played an anti-cancer role in HCC by targeting CCND1, and
the relationship between miR-193a-3p and CCND1 expression levels in HCC
was explored in depth for the first time.
MiR-193a-3p is a member of the miR-193 family. Recently research has
reported the inhibitory effect of miR-193-3p in a variety of tumors. In
2019, [104]Liu et al. (2019) found that a low level of miR-193a-3p
expression was related to the increased expression of p21-activated
kinase 4 (PAK4), p-Slug, and L1 cell adhesion molecule (L1CAM) in
non-small cell lung cancer (NSCLC) and that miR-193a-3p inhibited the
metastasis of NSCLC by repressing PAK4, p-Slug, and L1CAM. Through MTT
assay and cell colony formation experiments, [105]Yu et al. (2019)
showed that miR-193a-3p was downregulated in colorectal cancer cells,
while miR-193a-3p’s inhibitors promoted the proliferation and invasion
of rectal cells. Recently, many researchers have verified that
miR-193a-3p acts as an inhibitor in colon, gastric, and breast cancer
because it suppressed the proliferation, migration, and invasion of
these cancer cells ([106]Chou et al., 2018; [107]Pekow et al., 2017;
[108]Tsai et al., 2016). In addition, miR-193a-3p is involved in the
tumorigenicity of nasopharyngeal carcinoma and HCC ([109]Kong et al.,
2019; [110]Tsai et al., 2016). In 2015, our team also confirmed the low
expression levels of miR-193a-3p in HCC tissues by means of qRT-PCR
([111]Liu et al., 2015). Assuming that miR-193a-3p may exert its
biological functions by directly regulating the target genes, we thus
predicted the targets using miRwalk 2.0 and constructed a PPI network,
in which CCND1 was among the nine most related genes. In this case, we
conducted the dual-luciferase reporter assays to verify the direct
interaction between miR-193-3p and CCND1. This is the first study to
analyze the relationship between the expression levels of miR-193a-3p
and CCND1 in HCC. It is ultimately confirmed that miR-193a-3p has an
anti-cancer effect in HCC by affecting cell growth and apoptosis in
vitro.
There are numerous targets of miR-193a-3p, among which serine- and
arginine-rich splicing factor 2 (SRSF2), E2F transcription factor 1
(E2F1), and Mcl-1 have been proven to inhibit the development and
progression of HCC ([112]Khordadmehr & Shahbazi, 2019; [113]Kwon et
al., 2013; [114]Ma et al., 2012; [115]Salvi et al., 2013). In 2012,
[116]Ma et al. (2012) found that miR-193a-3p regulated the resistance
of HCC to 5-FU via interacting with SRSF2 and E2F1, with SRSF2 being
closely related to tumorigenicity of HCC cells and 5-FU resistance.
[117]Kong et al. (2019) found that SRSF2 was negatively related to the
expression level of miR-193a-3p in nasopharyngeal carcinoma via
qRT-PCR. Mcl-1 ectopic expression reversed miR-193a-3p’s promotion of
apoptosis, and a reporter assay with a luciferase construct embracing a
3′-untranslated region of Mcl-1 verified that Mcl-1 is a direct target
gene of miR-193a-3p ([118]Kwon et al., 2013). All in all, as one of the
most effective targets of miR-193a-3p, Mcl-1 is involved in the process
of programmed cell death, while miR-193a-3p regulates Mcl-1 and
promotes cell apoptosis via inducing the rearrangement of reactive
oxygen species and DNA damage ([119]Khordadmehr & Shahbazi, 2019).
However, the role of miR-193a-3p with CCND1 in HCC has not been
reported.
CCND1, located on chromosome 11q13, encodes the key cell cycle G1
regulation protein Cyclin D1 ([120]Kenny et al., 1999). It is also a
proto-oncogene and one of the main regulators of the Wnt signaling
pathway ([121]Karimkhanloo et al., 2017). Through combining with cyclin
dependent kinase 4 (CDK4) and cyclin dependent kinase 6 (CDK6), CCND1
enables rapid cell proliferation to promote the phosphorylation of
retinoblastoma proteins and other substrate ([122]Kenny et al., 1999).
In fact, CCND1 plays a role not only in cell cycle but also other
carcinogenic effects. Solid tumor models have shown that CCND1 can
regulate gene transcription by interacting with specific transcription
factors, pigmentation remodeling, and tissue modifying enzymes
([123]Aggarwal et al., 2010; [124]Bienvenu et al., 2010; [125]Fu et
al., 2004). CCND1 is overexpressed in epithelial ovarian cancer,
colorectal cancer, liver cancer, gastric cancer, nasopharyngeal cancer,
and lung cancer, leading to changes in the cell cycle, which, in turn,
give rise to the occurrence of tumors ([126]Huang et al., 2014). A
study by [127]Tian et al. (2013) demonstrated in 2013 that miR-19b,
miR-23b, miR-26a, and miR-92a may promote the proliferation of prostate
cancer cells by synergistically regulating the expression of
phosphatase and tensin homology, phosphoinositol 3-kinase/Akt, and
CCND1 in vitro. There is an article showing that through inhibition of
CCND1 expression, miR-193a-3p increases the proportion of G1 prostate
cancer cells, thus inhibits the cellular survival and proliferation
([128]Liu et al., 2017). Meanwhile, in breast cancer, the heterotopic
expression of miR-193a-3p in cancer cells directly targets
mitogen-activated protein kinase 8 (MAPK8), resulting in low CCND1
expression levels ([129]Khordadmehr & Shahbazi, 2019; [130]Uhlmann et
al., 2012). [131]Tsai et al. (2016) also reported that the role of
miR-193a-3p in inhibiting breast cancer cell migration and invasion was
directly related to CCND1. Furthermore, miR-193a-3p can restrain the
growth and invasion of gastric cancer cells by targeting CCND1
([132]Chou et al., 2018). In 2013, [133]Li et al. (2013) found that
miR-193a-3p impeded the progression of the myelocyte cycle in acute
myeloid leukemia (AML) by targeting CCND1, confirming that high
miR-193a-3p expression levels are capable of inhibiting the
proliferation of AML cells. Research projects discussing CCND1 in HCC
are relatively scarce. Thus, we are the first to study the relationship
between miR-193-3p and CCND1 in HCC. At the same time, we also analyzed
the miRNA and RNA-sequencing data, determined the base-complementary
pairing between miR-193a-3p and CCND1 in miRWalk 2.0, and obtained
their correlation in various neoplasms from starBase, confirming that
miR-193a-3p and CCND1 were negatively correlated in HCC. Considering
the role of miR-193a-3p in inhibiting HCC and the fact that CCND1
inhibits DNA synthesis, cell proliferation, cell colony formation, and
hepatoma formation by arresting the G1 phase in the cell cycle
([134]Wu, Lan & Liu, 2019), using miR-193a-3p to inhibit the expression
of CCND1 and thus suppress cell proliferation may be a novel strategy
for the treatment of HCC. For functional enrichment analyses, the most
related pathway was “proteoglycans in cancer”, while the “ErbB
signaling pathway” was the second most related pathway. Actually, the
ErbB pathway has been shown to participate in the
epithelial-mesenchymal transition (EMT) of HCC, and miR-296-5p is able
to inhibit EMT in HCC by attenuating ErbB signaling ([135]Shi et al.,
2018). In contrast, as a likely target of CCND1 ([136]Karimkhanloo et
al., 2017), the Wnt pathway is well-known to be involved in the
progression of HCC ([137]Zhu et al., 2019b; [138]Hu et al., 2019;
[139]Guan et al., 2019; [140]Zhu et al., 2019a.). However, it was not
among the most enriched pathways according to the findings of the KEGG
pathway analysis. One explanation for this contradictory phenomenon is
that the KEGG pathway was a in silico method, which remains to be
experimentally verified. Thus, it is interesting to study whether the
ErbB signaling pathway is disordered in HCC and whether it surpasses
the Wnt pathway in regulating the progression of HCC.
Of course, certain limitations of this research should be noted.
Regarding data analysis, because of the insufficient number of chips in
the Gene Expression Omnibus (GEO) database, we only analyzed the
expression profile of RNA-sequencing data from TCGA. The lack of
samples limited the verification of the heterogeneity between clinical
parameters and miR-193a-3p or CCND1. Therefore, more samples must be
further collated and analyzed to determine the clinical significance of
the interaction between CCND1 and miR-193a-3p in HCC. Second, both the
qRT-PCR data and the miRNA-sequencing data obtained from TCGA were from
tissues; the expression of miR-193a-3p in serum samples has not been
determined, which limits its value in diagnosis. Third, because miRNAs
have been well-recognized as participating in multiple biological
processes by regulating the expression of downstream target genes in a
complementary base-pairing manner, the enrichment of the functions and
signaling pathways of the target genes did indirectly provide insights
into the mechanism of miR-193-3p in HCC. However, the molecular
mechanism of the study is relatively lacking. Exactly which signal
pathways were involved and how miR-193-3p and CCND1 interacted with
these signal pathways remains to be investigated. Finally, regarding in
vitro experiments, although we carried out in-house qRT-PCR,
dual-luciferase reporter assays, and transfection experiments, only one
HCC cell line was used. More sophisticated in vivo and in vitro
experiments and more cell lines with multilevel validation are needed
for further supplementation.
Conclusions
Through data mining and in vitro experiments, we determined that
miR-193a-3p and CCND1 were negatively correlated in HCC and that
miR-193a-3p could inhibit the proliferation and promote the apoptosis
of HCC cells by targeting CCND1. This article provided clues for future
research concerning the pathogenesis of HCC. We hope this research
project can attract more attention to the reliable correlation between
CCND1 and miR-193a-3p and thus provide more perspectives on the
treatment of HCC.
Acknowledgments