Abstract
Background
Emerging evidence has shown that circular RNAs (circRNAs) play
essential roles in cancer biology and are potential biomarkers and
targets for cancer therapy. However, the expression and function of
circRNAs in ovarian carcinogenesis and its progression remain elusive.
Methods
RNA sequencing was performed to reveal circRNA expression profiles in
ovarian cancerous and normal tissues. Single-molecule RNA in-situ
hybridization was used to quantify circPLEKHM3 expression in tumor
tissues. Cell-based in-vitro and in-vivo assays were subsequently
conducted to support the clinical findings.
Results
CircPLEKHM3 was identified as one of the most significantly
down-regulated circRNAs in ovarian cancer tissues compared with normal
tissues. Its expression was further decreased in peritoneal metastatic
ovarian carcinomas compared to primary ovarian carcinomas. Patients
with lower circPLEKHM3 tend to have a worse prognosis. Functionally,
circPLEKHM3 overexpression inhibited cell growth, migration and
epithelial–mesenchymal transition, whereas its knockdown exerted an
opposite role. Further analyses showed that circPLEKHM3 sponged miR-9
to regulate the endogenous expression of BRCA1, DNAJB6 and KLF4, and
consequently inactivate AKT1 signaling. In addition, AKT inhibitor
MK-2206 could block the tumor-promoting effect of circPLEKHM3
depletion, and potentiate Taxol-induced growth inhibition of ovarian
cancer cells.
Conclusions
Our findings demonstrated that circPLEKHM3 functions as a tumor
suppressor in ovarian cancer cells by targeting the
miR-9/BRCA1/DNAJB6/KLF4/AKT1 axis and may be used as a prognostic
indicator and therapeutic target in ovarian cancer patients. The new
strategy for treating ovarian cancer by a combination therapy of Taxol
with MK-2206 is worth further investigation, especially in ovarian
cancer patients with loss of circPLEKHM3 expression.
Keywords: CircPLEKHM3, Ovarian cancer, miR-9, BRCA1, DNAJB6, KLF4,
AKT1, Prognosis
Introduction
Circular RNAs (circRNAs) are a new class of regulatory non-coding RNA
(ncRNA) molecules that form a covalently closed continuous loop
structure without a 5′ cap and 3′ poly–A tail [[47]1]. CircRNAs are
mainly generated by lasso-driven circularization (exon skipping),
intron pairing-driven circularization (direct backsplicing) and
RNA-binding proteins [[48]2]. The majority of circRNAs originate from
exons of protein-coding genes, and a few are directly cyclized by
introns or exon–introns [[49]3]. The improvements in high-throughput
RNA sequencing (RNA-seq) and novel bioinformatics tools have led to
identifying thousands of circRNAs in various organisms. Because of the
covalent loop structure, circRNAs are more stable than linear RNAs and
are resistant to exonucleolytic RNA decay [[50]4]. CircRNAs are
evolutionarily conserved among organisms, and are abundant in blood
[[51]5], saliva [[52]6] and exosomes [[53]7], making them promising
diagnostic biomarkers for disease.
Emerging evidence shows that circRNAs may play essential roles in many
diseases, including cancer [[54]8]. One of the major functions of
circRNAs is to act as miRNA sponges. Several circRNAs were reported to
be able to competitively bind to the miRNA response elements with mRNA
and long ncRNA to regulate gene expression [[55]9–[56]11].
Dysregulation of the circRNA–miRNA–mRNA axis in signaling pathways is
involved in several cancer types. For instance, CDR1as acts as a sponge
for miR-7 and miR-671 in the brain, which is essential for maintaining
normal brain function [[57]9]. Dysregulation of circHIPK3 changes
retinal endothelial cell viability, proliferation, migration, and tube
formation by the activation or inhibition of miR-30a-3p [[58]10].
CircCCDC66 functions as a miRNA sponge to protect MYC mRNA from being
attacked by miR-33b and miR-93 in colon cancer [[59]11]. In addition,
exon–intron circRNAs can influence transcription via interaction with
U1 snRNP, Pol II, and the gene promoter [[60]12]. Some circRNAs can act
as ‘scaffolding’ for RNA-binding proteins influencing
post-transcriptional gene regulation [[61]13]. Although a large number
of circRNAs have been identified by RNA-seq, the functions of most
circRNAs remain elusive.
Ovarian cancer is the leading cause of death from gynecological
malignancy worldwide [[62]14]. More than 75% of affected women are
diagnosed at advanced stages with vague and non-specific symptoms. Less
than one-third of late-stage patients survive 5 years after diagnosis
[[63]15]. Most patients develop metastatic disease after surgery and
intensive platinum–taxane chemotherapy. Hence, a major barrier to the
treatment of ovarian cancer is identifying novel prognostic biomarkers
that can distinguish patients at high risk for relapse and whether any
of these biomarkers are potential therapeutic targets. Recent studies
have shown that circRNAs play vital roles in the development and
progression of many cancers and have promising prognostic and
therapeutic potential [[64]7, [65]16]. However, the expression profiles
and underlying molecular mechanisms of circRNAs in ovarian cancer
remain largely unknown. Elucidating the role of circRNAs will be
critical for understanding the pathogenesis and identifying potential
new biomarkers or therapeutic targets for ovarian cancer.
In this study, we compared the expression profiles of circRNAs in
ovarian cancer and normal ovarian tissues, and found that a circular
RNA derived from PLEKHM3 termed circPLEKHM3 is significantly
down-regulated in ovarian cancer. Further analyses indicated patients
with lower circPLEKHM3 expression tend to have worse prognosis.
Functional studies showed that circPLEKHM3 acts as a competing
endogenous RNA (ceRNA) for miR-9 to up-regulate BRCA1, DNAJB6 and KLF4,
which subsequently contribute to the activation of the
epithelial–mesenchymal transition (EMT), AKT1/P27kip1 and Wnt/β-catenin
signaling pathways, and consequently suppress tumorigenesis and
progression in ovarian cancer.
Materials and methods
Preparation of RNA-seq libraries for detecting circRNAs
This study was reviewed and approved by the Ethnics Committees of
Women’s Hospital of Zhejiang University School of Medicine (Hangzhou,
China). Five tumor tissues from ovarian cancer patients and five normal
ovarian tissues from patients with benign gynaecological diseases were
collected. Total RNA was extracted by the Trizol reagent (Invitrogen,
Carlsbad, CA, USA). RNA integrity was assessed by the Agilent 2100
Bioanalyzer System (Agilent Technologies, Palo Alto, CA, USA). Before
constructing the complementary DNA (cDNA) library, 1 μg total RNA was
treated with NEBNext rRNA Depletion Kit (NEB, Ipswich, MA, USA, Cat#
E6318) to remove ribosomal RNA (rRNA). Then, strand-specific RNA-seq
libraries were prepared using the NEBNext Ultra Directional RNA Library
Prep Kit (NEB, Cat# E7420) for Illumina according to the manufacturer’s
instructions. The libraries were sequenced with a HiSeq X10 sequencer
(Illumina, San Diego, CA, USA) with paired-end reads of length
2 × 150 bp. Approximately, 150 million reads were generated for each
sequencing library (Additional file [66]1: Table S1).
Identification of circRNAs
The output RNA-Seq sequence reads were pre-processed with Trim Galore
([67]http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/)
(Additional file [68]1: Table S1). Adapters and sequences with low
quality (base quality < 20) were removed before the analysis. The
trimmed reads were first mapped to human reference genome (hg19) and
gene annotation database (Ensembl genes v75 — [69]www.ensembl.org)
using TopHat2 (v2.0.13) [[70]17]. Then, all the unmapped reads were
used to identify circRNAs by CIRCexplorer2 [[71]18]. The expression
level of circRNA was estimated as the ratio of the number of
back-spliced junction reads to the maximum number of reads spanning the
linear-spliced junction of the same exon(s) in each library. To
identify circRNAs expressed independently of their parental genes, only
circRNAs whose correlations with their parental genes were not
significant (P-value > 0.05) were used for subsequent analysis. The
expression difference in circRNAs between tumor and normal samples was
examined using Students’ t-test.
Real-time quantitative RT-PCR
Total RNA was extracted with Trizol, and 1 μg total RNA was reverse
transcribed into cDNA in a reaction volume of 20 μl using PrimeScript™
RT reagent Kit with gDNA Eraser (TAKARA, Shiga, Japan). Primers for
real-time quantitative RT-PCR (qRT-PCR) analysis of human circPLEKHM3,
linear PLEKHM3, and GAPDH are provided in Additional file [72]2: Table
S2. Before the analysis, total RNA was incubated at 37 °C for 10 min
with or without RNase R exonuclease (NEB).
Western blot analysis and immunohistochemistry
Western blot analysis was performed following the standard protocol as
previously described [[73]19]. For immunohistochemistry analysis, the
formalin-fixed and paraffin-embedded (FFPE) samples were first
deparaffinized and rehydrated, followed by PBS washing. Antigen
retrieval was performed in 0.01 M sodium citrate buffer (pH 6.0) at
100 °C for 15 min. The positive cells were scored as: 0 for < 5%, 1 for
6–25%, 2 for 26–50%, 3 for 51–75% and 4 for 76–100%. Staining intensity
was scored as: 0 for no staining, 1 for weak, 2 for moderate, and 3 for
strong. Immunoreactive scores were calculated by multiplying these two
grading scores, which ranged from 0 to 12. The antibodies used are
listed in Additional file [74]2: Table S2.
Single-molecule RNA in-situ hybridization
The expression of circPLEKHM3 in ovarian cancer tissues was evaluated
by BaseScope Assay (Advanced Cell Diagnostics (ACD), Newark, CA, USA).
A 1ZZ BaseScope probe targeting the junction sequences of circPLEKHM3
(903-11 nt) was designed, termed as BA-Hs-PLEKHM3-E3-circRNA-Junc (ACD,
Cat# 700001). FFPE tissue samples were prepared following the
manufacturer’s protocol. BaseScope assays were performed using
BaseScope Detection Reagent Kit-RED (ACD, Cat# 322900) in accord with
the manufacturer’s protocol. Chromogenic detection was performed using
BaseScope Fast RED followed by counterstaining with hematoxylin
(American MasterTech Scientific, Lodi, CA). At 20X magnification, the
number of visible red dots in 20 randomly scanned regions of each image
is used to measure the CircPLEKHM3 expression.
Cell culture
A2780 cells were cultured in RPMI-1640 media (GIBCO, Australia)
supplemented with 10% FBS (GIBCO), penicillin (100 U/ml) and
streptomycin (100 ng/ml). OV90 cells were grown in a 1:1 mixture of
MCDB 105 medium and medium 199 (GIBCO) supplemented with 15% FBS,
penicillin (100 U/ml) and streptomycin (100 ng/ml). MDAH2274 cells were
grown in DMEM media (GIBCO) supplemented with 10% FBS, penicillin
(100 U/ml) and streptomycin (100 ng/ml). All cells were grown at 37 °C
in 5% CO[2].
Knockdown of circPLEKHM3
Small interference RNAs (siRNAs) that target the junction sequence of
circPLEKHM3 were designed and synthesized by GenePharma (Shanghai,
China) (Additional file [75]2: Table S2). Cells were transfected with
these siRNAs with GeneMute™ reagent (SignaGen Laboratories, Rockville,
MD, USA). All transfection assays were carried out in triplicate.
Identification of genes altered by knockdown of circPLEKHM3
mRNA sequencing libraries were prepared for OV90 circPLEKHM3 knockdown
and scrambled control cells using the TruSeq RNA Sample Preparation Kit
from Illumina as described previously [[76]20]. Sequencing data were
preprocessed and mapped as described above. Briefly, the trimmed reads
were mapped to human reference genome (hg19) and gene annotation
database (Ensembl genes v75) using TopHat2 (v2.0.13) [[77]17]
(Additional file [78]3: Table S3). Transcripts were then constructed
and identified using Cufflinks [[79]21]. Differentially expressed genes
(DEGs) (adjusted P-values < 0.05) were determined by Cuffdiff [[80]21].
Overexpression of circPLEKHM3
Primers for constructing the pLO–ciR–circPLEKHM3 vector were designed
(Additional file [81]2: Table S2). PLO–ciR vector was purchased from
GENESEED (Guangzhou, China). Lentivirus particles were generated in the
293T packaging cells by transfection with the pMD2.G pseudotyping
plasmid (Addgene, Teddington, UK, Cat# 12259), the psPAX2 packing
plasmid (Addgene, Cat# 12260), and either the PLO–ciR–PLEKHM3, or
PLO–ciR viral vector plasmids. Transfections were performed with
liptofectamine 3000 in a 6–cm dish.
CCK8 assay
Cell proliferation was tested with the CCK8 kit (DOJINDO, Kumamoto,
Japan, Cat# CK04). Cells were seeded in 96-well plates with approximate
2000 cells/well in 100 μl medium in quintuplicate. CCK8 was added into
wells at 0, 24, 48, 72, 96, and 120 h respectively, and incubated for
2.5 h. The absorbance was measured at a wavelength of 450 nm.
Cell migration assay
The starved cells (10^5 cells for A2780, 3 × 10^4 cells for OV90 and
MDAH2274) were plated with 300 μL serum-free media into the prepared
invasion transwells, and placed above media containing 10% FBS. Plates
were incubated in 5% CO[2] at 37 °C overnight. Images were captured
from each membrane and the number of migratory cells was counted under
a microscope.
Preparation of nuclear and cytoplasmic extracts
The nuclear and cytoplasmic fraction of cells was isolated using the
PARIS™ kit (Ambion, Austin, TX, USA, Cat# AM1921). About 10^7 cells
were washed with PBS on ice followed by centrifugation at 500×g for
5 min. Cell pellets were resuspended in 500 μl cell fraction buffer,
incubated on ice for 10 min, and then centrifuged at 500×g and 4 °C for
5 min to separate the nuclear and cytoplasmic cell fractions. Nuclear
pellets were homogenized with the cell disruption buffer.
Luciferase report assays
The psiCHECK™-2 Vector (Promega, Madison, WI, USA, Cat# C8021), which
contains Renilla and firefly luciferase reporter genes, was prepared
for luciferase report assays with the full-length circPLEKHM3 or the 3′
UTR of KLF4 and DNAJB6. In the mutant vectors, the miR-9 binding sites
in circPLEKHM3 or the 3’UTR of KLF4 and DNAJB6 variant 1 were mutated
on psiCHECK™-2 Vectors. The constructed psiCHECK™-2 Vectors were
transfected into cancer cells with miRNA mimic and negative control
miRNA in 24-well plates. Twenty-four hours after transfection, the
cells were lysed with passive lysis buffer (Promega, Cat# E1910), and
reporter gene expression was assessed using the Dual Luciferase
reporter assay system (Promega, Cat# E1910). The fold change of the
relative luciferase activities between miRNA mimic and negative control
was calculated.
RNA fluorescence in-situ hybridization (FISH)
About 6 × 10^4 cells per well were seeded on cell slides at the bottom
of a 24-well plate and incubated. The degree of cell fusion was 80–90%
before the experiment. The specific probe to circPLEKHM3 back-splice
sequence and miR-9-5p was synthesized by RiboBio (Guangzhou, China) and
GeneBio (Shanghai, China), respectively. After cell fixation and
permeabilization, cells were treated with prehybridization buffer at
37 °C for 30 min and then hybridized overnight in the hybridization
buffer containing 50 μM circPLEKHM3 probe and 250 nM miR-9-5p probe at
37 °C. Subsequently, following the manufacturer’s protocol of RNA FISH
(GeneBio), the coverslips were washed with wash buffer I three times,
and wash bufferII, wash buffer III and PBS once at 42 °C. After dyeing
with DAPI for 10 min, the coverslips were washed with PBS three times.
Representative confocal microscopy images of RNA FISH were presented.
RNA immunoprecipitation
RNA immunoprecipitation (RIP) assay was performed using the Magna RIP™
RNA-Binding Protein Immunoprecipitation Kit (EMD Millipore, Darmstadt,
Germany, Cat# 17–700). Briefly, 2 × 10^7 cells were lysed in 100 μl RIP
lysis buffer with the addition of 0.5 μL of protease inhibitor cocktail
and 0.25 μL of RNase inhibitor and kept on ice. Then, the lysates were
incubated with AGO2 and IgG antibody with protein A/G magnetic beads at
4 °C overnight. The beads were washed three times with wash buffer
containing RNase inhibitor and then the RNA was extracted. The
abundance of circPLEKHM3 and linear PLEKHM3 was measured by qRT-PCR.
Animal experiments
Four-week-old female athymic nude mice (BALB/c Nude) were used. Control
cells and circPLEKHM3 knockdown cells with pLKO.1 vector (1.2 × 10^6
cells) were suspended in 0.1 ml RPMI-1640 media without FBS and were
subcutaneously inoculated into the flanks of the mice. Six mice were
used in each group. Mice were monitored every 5 days for tumor growth,
and tumor size was measured using a caliper. Three weeks after
inoculation, mice were sacrificed and tumor weight was measured. All
experiments were performed in accordance with the Guide for the Care
and Use of Laboratory Animals (NIH publication 80–23, revised 1996),
with the approval of the Zhejiang University, Hangzhou, China.
Drug treatment
Cells were seeded in 96-well plates at 5000 cells/well in 100 μl
medium, and treated with Taxol (Selleck, Houston, TX, USA, Cat# s1150),
MK-2206 (TargetMol, Shanghai, China) or a combination of them for 48 h.
The half-life of MK-2206 is about 60 h [[82]22]. Cell viability was
determined using a CCK8 assay. All drug treatment assays were carried
out in quintuplicate. The index of synergy between MK-2206 and Taxol
was evaluated by the Q-value in Jin’s formula [[83]23]:
[MATH: Q=EMK+Taxol/EMK+ETaxol−EMK×ETaxol :MATH]
where E[MK + Taxol] is the efficacy of the combination treatment; and
E[MK] and E[taxol] are the efficacies of MK-2206 and Taxol,
respectively. In this method, an index > 1.15 indicates synergistic
effects between the two treatments; values of the index between 0.85
and 1.15 indicate additive effects of the two treatments; values < 0.85
indicate antagonistic effects of the two treatments. The IC50 values
for the treatment of MK-2206 and Taxol were also determined in A2780
scramble and circPLEKHM3 knockdown cells.
Bioinformatics analysis
Three algorithms (miRanda, Pita and RNAhybrid) were used to predict
miR-9 targets [[84]24–[85]26]. The intersection of the three algorithms
was considered as the predicted miRNA targets. DEGs with a q-value of
Student’s t-test < 0.01 were subjected to pathway enrichment analysis,
using a hypergeometric test based on the KEGG PATHWAY database. To
determine if β-catenin signaling is activated upon the knockdown of
circPLEKHM3, we used the log2-transformed expression data of CTNNB1
downstream target genes [[86]27] from RNA-seq data of OV90 circPLEKHM3
knockdown cells. The activation of β-catenin signaling was estimated by
the PLAGE [[87]28] method, implemented in the R package ‘GSVA’
[[88]29].
Statistical analysis
The differences between two groups were examined using Student’s t-test
and a one-way analysis of variance for normally distributed data, and
using the Mann–Whitney U test for non-normally distributed data.
P-values < 0.05 were set as the significant threshold. Before the
survival analysis, the mean of expression was used to classify patient
samples into two groups. The events of overall survival were defined as
death, while recurrence-free survival was ended by any disease
recurrence or death. A Kaplan–Meier survival analysis was performed to
assess the association of circRNA/gene expression with clinical outcome
and the P-value was calculated with a log-rank test. All statistical
analyses were implemented in R statistical packages
([89]https://www.r-project.org/).
Results
Down-regulation of circPLEKHM3 is associated with poor prognosis in ovarian
cancer
To illustrate the role of circRNAs in ovarian cancer, the expression
profiles of circRNAs and mRNAs were explored in five ovarian tumor
tissues and five normal ovarian tissues using rRNA-depleted RNA
sequencing. Volcano plots displayed the log2-fold changes in circRNA
expression between ovarian tumor and normal tissues versus its
associated -log10 of the P-values (Fig. [90]1a and Additional file
[91]4: Figure S1). CircPLEKHM3 was identified as one of the most
significantly down-regulated circRNAs in ovarian tumor tissues.
CircPLEKHM3 is spliced from exons of PLEKHM3 on the reverse strand of
chromosome 2 (from 208,841,375-208,842,310 bp, hg19 genome build).
CircPLEKHM3 was chosen for further investigation because its parental
gene PLEKHM3 has not yet been studied in cancer and the PLEKHM3 was not
significantly differentially expressed between ovarian tumor and normal
tissues. To validate the existence of circPLEKHM3, junction primers
were designed (Fig. [92]1b) to amplify the circPLEKHM3 junction
expression in cDNA from A2780 and OV90, followed by Sanger sequencing
(Fig. [93]1b). The sequencing result confirmed the existence of
circPLEKHM3, which had an identical junction to that observed in the
circBase database (Additional file [94]5: Figure S2). The circPLEKHM3
junction was only detected in cDNA, whereas its parental gene was
detected in both cDNA and genomic DNA from ovarian cancer cell lines
(Additional file [95]6: Figure S3). Furthermore, the expression of
circPLEKHM3 was resistant to digestion with RNase R exonuclease,
suggesting that the studied RNA species is most likely to be circular
in form (Fig. [96]1c). Finally, three pairs of primers were
specifically designed to amplify the full length of circPLEKHM3. Among
the three pairs of primers, the forward and reverse primers were next
to each other but in the opposite direction (Fig. [97]1b), so that only
circular RNAs could be amplified. PCR results further confirmed the
existence of circPLEKHM3 (Fig. [98]1d). CircPLEKHM3 contained 936 nt
and its full-length sequences are given in Additional file [99]5:
Figure S2. Taken together, these experiments validated the existence of
circPLEKHM3 that was detected by rRNA-depleted RNA-seq in ovarian tumor
tissues.
Fig. 1.
[100]Fig. 1
[101]Open in a new tab
CircPLEKHM3 is down-regulated in ovarian cancer and associated with
prognosis. a Scatterplot showing the relative expression of circRNA in
ovarian tumor and normal tissues. CircPLEKHM3 is marked as a dark
circle. b Schematic diagram of the generation of circPLEKHM3.
CircPLEKHM3 was back-spliced from exon 3 of PLEKHM3. Primers were
designed on exon 2 to examine the expression of linear transcripts of
PLEKHM3. To validate the existence of circPLEKHM3, primers were
designed on the spliced junction, followed by Sanger sequencing. To
obtain the full-length sequences of circPLEKHM3, three pairs of primers
in opposite directions were designed on exon 3, and their PCR products
were sequenced. c qRT-PCR analysis of the relative abundance of
circPLEKHM3 and PLEKHM3 mRNA in A2780 and OV90 treated with RNase R. d
PCR product of full-length circPLEKHM3. Primers used to clone
full-length circPLEKHM3 are indicated in Fig. 1b and their sequences
can be found in Additional file [102]2: Table S2. e, f qRT-PCR analysis
of the expression of circPLEKHM3 and PLEKHM3 in a new independent
cohort including 12 tumor tissues from ovarian cancer patients and 12
normal ovarian tissues from patients with benign gynaecologic diseases
(e), and 26 primary ovarian carcinoma and matched peritoneal metastatic
ovarian carcinomas (f). g Kaplan–Meier survival analysis of circPLEKHM3
expression in ovarian cancer patients. The expression of circPLEKHM3
was evaluated using a BaseScope assay in 86 FFPE tissues from ovarian
cancer patients. h Representative images (20× magnification) of the
BaseScope assay for circPLEKHM3 in patients with better prognosis
(upper) and worse prognosis (lower). CircPLEKHM3 transcript appears as
a distinct red dot, with each dot representing a single RNA transcript.
Data are presented as mean ± SD; n = 3; ** P < 0.01, *** P < 0.001
qRT-PCR assays were performed in independent 12 tumor tissues from
ovarian cancer patients and 12 normal ovarian tissues from patients
with benign gynaecological diseases. BaseScope assays were also
performed in these tissues and additional normal oviduct tissues. Both
qRT-PCR and BaseScope assays confirmed that circPLEKHM3 expression was
significantly down-regulated in tumor tissues, while PLEKHM3 expression
did not differ between tumor and normal tissues (Fig. [103]1e and
Additional file [104]7: Figure S4). Interestingly, circPLEKHM3
expression was further decreased in peritoneal metastatic ovarian
carcinomas as compared with the primary ovarian carcinomas they were
derived from, whereas PLEKHM3 expression did not differ between
metastatic and primary carcinomas (Fig. [105]1f and Additional file
[106]8: Figure S5). Furthermore, BaseScope assays were used to assess
circPLEKHM3 expression in FFPE tissues from ovarian cancer patients
with clinical outcome. Kaplan–Meier survival analysis revealed that
down-regulated circPLEKHM3 was associated with short overall survival
and recurrence-free survival in cancer patients (Fig. [107]1g, h).
However, the expression of linear PLEKHM3 was not associated with
patient outcomes (Additional file [108]9: Figure S6). These results
suggest that circPLEKHM3 is a potential diagnostic and prognostic
biomarker and its expression is highly predictive for the clinical
outcome in ovarian cancer patients.
CircPLEKHM3 plays a tumor-suppressive role in ovarian cancer
As described above, circPLEKHM3 expression is significantly
down-regulated in cancer tissues and its down-regulation is associated
with a poor prognosis in ovarian cancer. These observations suggest
that circPLEKHM3 may play a tumor-suppressive role in ovarian cancer.
To test this hypothesis, we amplified the full-length cDNA of
circPLEKHM3 from A2780 (Additional file [109]5: Figure S2), and cloned
it into the expression vector. CircPLEKHM3 was significantly
up-regulated after transfecting the circPLEKHM3 expression vector in
A2780 and MDAH2274 cells (Fig. [110]2a, Additional file [111]10: Figure
S7), whereas the transfection did not affect linear PLEKHM3 mRNA levels
(Additional file [112]11: Figure S8). As a result, the up-regulation of
circPLEKHM3 dramatically inhibited cell proliferation (Fig. [113]2b)
and migration (Fig. [114]2c). Further analysis revealed that the stable
overexpression of circPLEKHM3 increased the expression of E-cadherin
and zonula occludens (ZO)-1, but decreased the expression of SNAIL1 and
Slug (Fig. [115]2d), indicating that EMT was repressed upon
up-regulation of circPLEKHM3. On the contrary, two siRNAs were also
designed to target the backsplice junction of circPLEKHM3, which did
not affect the expression of its parental gene (Additional file
[116]11: Figure S8). Depletion of circPLEKHM3 (Fig. [117]2e) promoted
ovarian cancer cell proliferation (Fig. [118]2f), migration (Fig.
[119]2g), and EMT (Fig. [120]2h). These assays collectively suggested
that circPLEKHM3 may act as a tumor suppressor in ovarian cancer. To
further confirm the role of circPLEKHM3 in vivo, we established a nude
mice xenograft model by subcutaneous inoculation of A2780 cells stably
transfected with sh-circPLEKHM3 and scrambled control. We observed that
tumor volumes and weights were significantly larger in the
sh-circPLEKHM3 than those in the control group (Fig. [121]2i, j),
suggesting that circPLEKHM3 could suppress the tumorigenicity of
ovarian cancer cells in vivo. Immunohistochemistry analysis of
E-cadherin and SNAIL further indicated that EMT was promoted in
immunodeficient mice upon knockdown of circPLEKHM3 (Additional file
[122]12: Figure S9). Taken together, these results suggest that
circPLEKHM3 plays a tumor-suppressive role in ovarian cancer in vitro
and in vivo.
Fig. 2.
[123]Fig. 2
[124]Open in a new tab
CircPLEKHM3 exerts tumor-suppressive effects in ovarian cancer cells. a
The relative abundance of circPLEKHM3 in ovarian cancer cells
transfected with circPLEKHM3 and mock plasmids determined by qRT-PCR. b
Proliferation of A2780 and MDAH2274 cells transfected with circPLEKHM3
overexpression and mock vectors assessed with the CCK8 kit. c Migration
of A2780 and MDAH2274 cells transfected with circPLEKHM3 overexpression
and mock vectors measured in a transwell assay at 24 h. d
Immunoblotting of E-cadherin, ZO-1, Slug and SNAIL1 in A2780 and
MDAH2274 cells transfected with circPLEKHM3 overexpression and mock
vectors. e qRT-PCR analysis of the relative abundance of circPLEKHM3 in
OV90 and A2780 cells transfected with two siRNAs and scrambled control.
f Proliferation of A2780 and MDAH2274 cells transfected with two siRNAs
targeting circPLEKHM3 and scrambled control assessed with the CCK8 kit.
(G) Migration of A2780 and OV90 cells transfected with two siRNAs
targeting circPLEKHM3 and scrambled control measured in a transwell
assay. h Immunoblotting for E-cadherin, ZO-1, Slug and SNAIL1 in A2780
and OV90 cells transfected with siRNA1. i Representative images in
immunodeficient mice. A2780 scramble and sh-circPLEKHM3 cells were
injected subcutaneously in the left and right flank of mice,
respectively. j The growth curves for tumors and tumor weights of
immunodeficient mice injected with A2780 scramble cells and A2780
sh-circPLEKHM3 cells. Tumor volumes were normalized by the first
measurement at day 7 after injection. Absolute tumor weights were
measured after mice were sacrificed 3 weeks after injection. Six mice
per group were used in the nude mouse assay
CircPLEKHM3 directly binds to miR-9 and suppresses miR-9 activity
CircRNAs have been shown to act as a miRNA sponge to regulate gene
expression. CircPLEKHM3 is abundant and stable in the cytoplasm, while
PLEKHM3 is abundant in the nucleus (Fig. [125]3a). We thus investigated
the potential miRNAs associated with circPLEKHM3. The full-length
sequence of circPLEKHM3 was first blasted in the miRBase database v20
([126]http://www.mirbase.org/). It was found that circPLEKHM3 possessed
a complementary sequence to the miR-9 seed region (Fig. [127]3b). We
then cloned the circPLEKHM3 sequence and the sequence with mutated
binding sites of miR-9, and inserted them immediately downstream of the
luciferase reporter gene (Additional file [128]13: Figure S10). To
examine whether miR-9 can bind to circPLEKHM3, we co-transfected the
miR-9 mimic and luciferase reporters into OV90 cells. Overexpression of
miR-9 mimic remarkably reduced luciferase activity to almost 50% when
compared with the negative control RNA (Fig. [129]3c). These results
suggest that miR-9 can interact with circPLEKHM3 via the complementary
seed region. To further support this finding, we conducted an anti-Ago2
immunoprecipitation assay in OV90, which showed that, compared with
IgG, endogenous circPLEKHM3 but not PLEKHM3 was specifically enriched
in the immunoprecipitation fraction pulled down by Ago2 (Fig. [130]3d).
Additionally, the co-localization results from FISH analysis confirmed
that circPLEKHM3 directly binds to miR-9 (Fig. [131]3e).
Fig. 3.
[132]Fig. 3
[133]Open in a new tab
CircPLEKHM3 targets miR-9. a qRT-PCR analysis of circPLEKHM3 and
PLEKHM3 expression in nuclear and cytosolic fractions of OV90 cells.
U6, GAPDH, and β-actin were used for quality control. b Luciferase
report vector of wild-type (WT) and mutant (Mut) circPLEKHM3. The
highlighted sequences represent miR-9 seed sequences or sequences that
are complementary to miR-9 seed sequences. In the Mut vector, the miR-9
binding sites in circPLEKHM3 were mutated on psiCHECK™-2 Vectors. c
Luciferase activity of LUC-circPLEKHM3 wild types and mutants in OV90
cells transfected with miR-9 mimic and negative control mimic. d RNA
immunoprecipitation assay to measure the amount of circPLEKHM3 and
PLEKHM3 pull downed by AGO2 and IgG antibodies in OV90 cells. e RNA
fluorescence in-situ hybridization for circPLEKHM3 and miR-9 in A2780
and OV90 cells. f Cell growth and (g) migration assays were performed
in circPLEKHM3 knockdown A2780 and OV90 cells transfected with miR-9
inhibitor and negative control (NC). Migration assays were measured
24 h after transfection
To investigate whether the circPLEKHM3–miR-9 interaction regulates the
function of cancer cells, we transfected A2780 and OV90 cells with
miR-9 inhibitor after knockdown of circPLEKHM3. Compared with the
control, transfection of miR-9 inhibitor significantly rescued cell
phenotypes by decreasing cell proliferation and migration (Fig.
[134]3f, g). This suggested that circPLEKHM3 may play a
tumor-suppressive role in ovarian cancer cells by suppressing miR-9
activity. Collectively, these results strongly support that circPLEKHM3
binds directly to miR-9 and suppresses miR-9 activity in ovarian cancer
cells.
CircPLEKHM3 suppresses the proliferation and migration of ovarian cancer
cells by sponging miR-9 to regulate BRCA1, DNAJB6, and KLF4
Next, three algorithms (miRanda, Pita and RNAhybrid) were used to
predict potential targets of miR-9 [[135]24–[136]26]. DNAJB6 and KLF4
were the common targets predicted by all three algorithms. Their
expressions were significantly decreased when depleting circPLEKHM3
based on the RNA-seq data from OV90 circPLEKHM3 knockdown cells
(Additional file [137]14: Figure S11). BRCA1 was an experimentally
verified target and its gene expression can be regulated by miR-9
[[138]30]. Thus, we only focused on DNAJB6 and KLF4 in subsequent
experiments.
There are two transcript variants of DNAJB6: variant 1 and 2, according
to the UniProtKB database ([139]www.uniprot.org/uniprot/O75190).
Variant 1 encodes DNAJB6 protein isoform a (DNAJB6a, 36 kDa), and
variant 2 encodes DNAJB6 protein isoform b (DNAJB6b, 26.9 kDa). These
two transcript variants have distinct 3′ untranslated regions (UTRs) of
DNAJB6 mRNA. Interestingly, the 3′ UTR of variant 1 has a specific
sequence complementary to the miR-9 seed region, whereas the 3′ UTR of
variant 2 lacks the specific complementary sequence to miR-9
(Fig. [140]4a). Luciferase reporter assays demonstrated that miR-9
mimic significantly decreased the luciferase activity of DNAJB6 variant
1, while the luciferase activity of variant 2 remained unchanged (Fig.
[141]4b). This verified the interaction between miR-9 and DNAJB6
variant 1 but not variant 2. As expected, knockdown or overexpression
of circPLEKHM3 and miR-9 only affected the expression of DNAJB6a, but
not of DNAJB6b (Fig. [142]4d, Additional file [143]15: Figure S12). The
expression of DNAJB6a was analyzed in RNA-seq data from ovarian cancer
in The Cancer Genome Atlas (TCGA). Patients with lower DNAJB6a
expression tend to have worse prognosis (Additional file [144]16:
Figure S13).
Fig. 4.
[145]Fig. 4
[146]Open in a new tab
CircPLEKHM3 controls cell proliferation and migration through binding
miR-9 to regulate BRCA1, DNAJB6 and KLF4 expression. a A schematic
illustration of two variants of DNAJB6. The 3’UTR of DNAJB6 variant 2
lacks the miR-9 binding sites. b A schematic illustration of the
luciferase report vector of DNAJB6 variant 1 3’UTR wild type (WT) and
mutant (Mut) (upper panel), and the relative luciferase activity of
LUC–DNAJB6 variant 1 WT and Mut, and LUC–DNAJB6 variant 2 WT in A2780
cells transfected with miR-9 and control mimics (lower panel). The
highlighted sequences represent miR-9 seed sequences or sequences that
are complementary to miR-9 seed sequences. In the Mut vector, the miR-9
binding sites in the 3’UTR of DNAJB6 variant 1 were mutated on
psiCHECK™-2 Vectors. c A schematic illustration of the luciferase
report vector of KLF4 3’UTR WT and Mut types (upper panel), and the
relative luciferase activity of LUC–KLF4 WT and Mut in A2780 cells
transfected with miR-9 and control mimics (lower panel). In the Mut
vector, the miR-9 binding sites in the 3’UTR of KLF4 were mutated on
psiCHECK™-2 Vectors. d Immunoblotting analyses of DNAJB6a, DNAJB6b,
KLF4 and BRCA1 in ovarian cancer cells transfected with circPLEKHM3
overexpression, mock vectors, circPLEKHM3 siRNAs and negative control
(NC). e Kaplan–Meier survival analysis of KLF4 protein expression in
ovarian cancer patients. KLF4 protein expression was measured by
immunohistochemistry analysis. Patient samples were divided into two
groups according to their KLF4 immunohistochemistry scores. f
Representative images (20× magnification) of immunohistochemical
staining for KLF4 in patients with a better prognosis (upper panel) and
a worse progno (lower panel). g Representative images (20×
magnification) of immunohistochemical staining for KLF4 and BRCA1 in
immunodeficient mice injected with A2780 scramble and sh-circPLEKHM3
cells
Similar to DNAJB6a, our experiments also confirmed that KLF4 was the
target of miR-9 and can be regulated by circPLEKHM3 (Fig. [147]4c, d,
and Additional file [148]15: Figure S12). KLF4 was reported to play a
role in EMT and act as a tumor suppressor in ovarian cancer [[149]31].
Ovarian cancer patients with higher KLF4 expression had consistently
better prognoses (Additional file [150]16: Figure S13).
Immunohistochemistry analyses showed that KLF4 was presented in the
cytoplasm and nuclear of tumor cells and exhibited stronger staining in
tumor tissues from patients with a better prognosis (Fig. [151]4e, f).
KLF4 and BRCA1 exhibited stronger staining in tumor tissues of
immunodeficient mice injected with A2780 scramble cells than the mice
injected with A2780 sh-circPLEKHM3 cells (Fig. [152]4g). These results
collectively suggest that circPLEKHM3 could act as a ceRNA for miR-9 to
regulate the expression of BRCA1, DNAJB6 and KLF4, and suppress the
proliferation and migration of ovarian cancer cells.
CircPLEKHM3 inactivates AKT1 and Wnt/β-catenin signaling pathways
DNAJB6a and BRCA1 were previously reported to directly negatively
regulate the activation of AKT1 [[153]32, [154]33]. RNA-seq analysis
was performed on circPLEKHM3 knockdown and scrambled control cells.
DEGs between circPLEKHM3 knockdown and scrambled control cells were
detected from these RNA-seq data. Strikingly, AKT1 activation was
involved in all the top significant pathways that were enriched for
DEGs upon knockdown of circPLEKHM3 (Fig. [155]5a). Additionally,
overexpression of circPLEKHM3 inactivated AKT1, while depletion of
circPLEKHM3 increased moderately phosphorylation of AKT1 but had a
negligible effect on total AKT1 level in ovarian cancer cells (Fig.
[156]5b, d, e). Involvement of DNAJB6a, KLF4 and AKT1 in Wnt/β-catenin
signaling has been reported previously [[157]34–[158]36]. We thus
investigated the potential regulatory role of circPLEKHM3 in
Wnt/β-catenin signaling. We demonstrated that overexpression of
circPLEKHM3 could dephosphorylate GSK3β and decrease β-catenin
expression, whereas depletion of circPLEKHM3 showed the opposite
effects on GSK3β and β-catenin (Fig. [159]5b). This is in line with our
RNA-seq result that the Wnt/β-catenin signaling pathway was
significantly activated upon knockdown of circPLEKHM3 (Fig. [160]5c).
Furthermore, we designed two siRNAs to knock down AKT1 in ovarian
cancer cells with depletion of circPLEKHM3. As a result, the
upregulation of Wnt/β-catenin that resulted from downregulation of
circPLEKHM3 was dramatically attenuated (Fig. [161]5f); the cell
phenotypes were also rescued by decreasing cell proliferation and
migration (Fig. [162]5f, g). Taken together, our data revealed that
circPLEKHM3 inactivates the AKT1 and canonical Wnt/β-catenin signaling
pathways by regulating the expression of BRCA1, DNAJB6 and KLF4 in
ovarian cancer cells.
Fig. 5.
[163]Fig. 5
[164]Open in a new tab
CircPLEKHM3 acts as a tumor suppressor in AKT1 and β-catenin signaling
pathways. a Top five KEGG pathways enriched for differentially
expressed genes upon knockdown of circPLEKHM3 in ovarian cancer cells.
Differentially expressed genes were identified by RNA-seq data of
circPLEKHM3 knockdown and scrambled control cells, and the 10 most
significant genes are shown. b Immunoblotting analyses of P-AKT1,
β-catenin, P-GSK3β, P21, and P27 in ovarian cancer cells with depletion
of circPLEKHM3 or transfected with circPLEKHM3 overexpression and
control vectors. c β-catenin signaling was activated in OV90 upon
knockdown of circPLEKHM3. The pathway activation score was used to
estimate the degree to which β-catenin signaling was activated in
circPLEKHM3 knockdown and negative control (NC) OV90 cells. d
Representative images (20× magnification) of immunohistochemical
staining for P-AKT1 in immunodeficient mice injected with A2780
scramble and sh-circPLEKHM3 cells. e Immunoblotting analyses of AKT1
and P-AKT1 in circPLEKHM3 knockdown A2780 cells transfected with AKT1
siRNAs and negative controls (NC). f Cell growth and (g) migration
assays were performed in circPLEKHM3 knockdown A2780 cells transfected
with AKT1 siRNAs and negative controls. Migration assays were measured
24 h after transfection
AKT inhibitor MK-2206 and Taxol combination therapy exerts synergetic effects
on the treatment of ovarian cancer with loss of circPLEKHM3 expression
Activation of AKT1 and its related signaling pathways is frequently
observed in ovarian cancer [[165]37, [166]38]. Evidence is accumulating
that the acquisition of resistance to chemotherapeutic drugs involves
the AKT activation pathway [[167]39, [168]40]. As described above, the
down-regulation of circPLEKHM3 could activate AKT1, and thus promote
cell proliferation and migration in ovarian cancer. Most patients
develop resistance to platinum–taxane chemotherapy in advanced ovarian
cancer. MK-2206 is an oral AKT inhibitor that can prevent AKT
phosphorylation and enhance antitumor efficacy in combined treatment
with standard chemotherapeutic agents or molecular targeted drugs
[[169]41]. In this study, we observed that, depending on the
concentration, MK-2206 treatment could repress AKT1 phosphorylation in
ovarian cancer cells (Fig. [170]6a). Although the differences in IC50
values of MK2206 between circPLEKHM3 knockdown and scrambled control
cells are statistically significant, the effect of circPLEKHM3
knockdown on the MK2206 sensitivity is perceivably small (Fig. [171]6b
and Additional file [172]3: Table S3). Currently, Taxol is the
first-line chemotherapeutic drug for treating ovarian cancer. In
contrast to MK-2206, sh-circPLEKHM3 cells were slightly less sensitive
to Taxol (Fig. [173]6c and Additional file [174]3: Table S3). This is
perhaps due to the reduced expression of BRCA1 in circPLEKHM3 knockdown
cells that increases the resistance of Taxol for treating ovarian
cancer [[175]42]. Overall, MK-2206 enhanced antitumor efficacy in
combined treatment with Taxol in both circPLEKHM3 knockdown and
scrambled control cells (Fig. [176]6c). Under MK-2206/Taxol combination
therapy, the mean synergetic indexes were 1.1 and 1.3 in scramble and
sh-circPLEKHM3cells, respectively (Fig. [177]6d). This suggests that
MK-2206 and Taxol have a synergetic effect on the apoptosis of ovarian
cancer cells, and that such synergetic effects are more prominent in
ovarian cancer cells with a lower circPLEKHM3 expression. Additionally,
the apoptosis analysis further supported these findings (Additional
file [178]17: Figure S14). These results collectively demonstrate that
although the effect of circPLEKHM3 knockdown on the MK2206 and Taxol
sensitivity is small, the MK-2206/Taxol combination therapy exerts a
synergetic effect in the treatment of ovarian cancer, and this
synergetic effect is increased in ovarian cancer cells with a loss of
circPLEKHM3 expression.
Fig. 6.
[179]Fig. 6
[180]Open in a new tab
MK-2206 enhances Taxol-induced growth inhibition of ovarian cancer
cells, especially in circPLEKHM3 knockdown cells. a Immunoblotting
analyses of P-AKT1 in A2780 scramble and circPLEKHM3 knockdown cells
treated with different concentrations of the AKT1 inhibitor MK-2206 or
DMSO for 1 h. b Cell viability of A2780 scramble and circPLEKHM3
knockdown cells treated with different concentrations of MK-2206 for
48 h. c Cell viability of A2780 scramble and circPLEKHM3 knockdown
cells treated with different concentrations of Taxol combined with
0.3 μM MK-2206 for 48 h. d The synergistic index of combination
treatment of Taxol and MK-2206 in A2780 scramble and circPLEKHM3
knockdown cells. Different concentrations of Taxol (0.3 nM, 0.6 nM,
1.2 nM, 2.4 nM and 4.8 nM) were combined with 0.3 μM MK-2206 in the
treatment. e Potential molecular mechanisms of circPLEKHM3 in ovarian
cancer. CircPLEKHM3 functions as a tumor suppressor in ovarian cancer
cells by sponging miR-9 to enhance the endogenous suppressive effect of
BRCA1, DNAJB6 and KLF4, and consequently inactivate AKT1 and Wnt-β
catenin signaling pathways
Discussion
Dysregulation of circRNAs plays critical roles in neoplastic initiation
and progression. However, the expression and function of circRNAs in
ovarian carcinogenesis and progression remains elusive. In this study,
we thus performed deep rRNA-depleted RNA sequencing in ovarian
cancerous and normal tissues. RNA-seq analysis detected circPLEKHM3 as
one of the most significantly down-regulated circular RNAs in ovarian
cancer. Interestingly, circPLEKHM3 expression was further decreased in
peritoneal metastatic ovarian carcinomas as compared with the primary
ovarian carcinomas they were derived from, implying its potential role
in ovarian cancer metastasis. CircPLEKHM3 is a novel circRNA and its
expression and functional role in cancers has not yet been explored. To
evaluate its clinical value, we quantified the expression of
circPLEKHM3 in FFPE tissues from ovarian cancer using a BaseScope
assay. The BaseScope assay is a new RNA in-situ hybridization technique
and has the advantage of effectively preventing non-specific binding of
the probe while reducing background interference [[181]43]. The
BaseScope assay revealed that ovarian cancer patients with a lower
circPLEKHM3 expression tend to have a worse prognosis.
Functionally, the down-regulation of circPLEKHM3 could promote the
proliferation and migration of ovarian cancer cells, and induce EMT to
facilitate tumor metastasis, whereas the up-regulation of circPLEKHM3
could exert an opposite role. Recent studies have revealed that
circRNAs have an important function in gene regulation. For example,
circRNAs can function as a miRNA sponge [[182]10, [183]11],
transcription regulator [[184]12], and protein decoy [[185]44], and
regulate gene expression at transcriptional or post-transcriptional
level. Our results demonstrated that circPLEKHM3 can directly bind to
miR-9, and function as a ceRNA to enhance the suppressive effect of
miR-9 target genes such as BRCA1, DNAJB6 and KLF4, and consequently
inactivate AKT1. The direct interaction between circPLEKHM3 and miR-9
was very evident under the confocal microscope at 60× magnification.
Consistently, luciferase and RIP assays further supported that
circPLEKHM3 and miR-9 physically bind to each other (Fig. [186]3e).
RNA-seq analysis of circPLEKHM3 knockdown cells revealed that AKT1
activation is one of the top targeted pathways upon deletion of
circPLEKHM3 in ovarian cancer cells. Previous studies have reported
that wild-type BRCA1 can negatively regulate AKT1 activation [[187]32,
[188]45]. DNAJB6a can bind to the phosphorylation sites threonine 308
(T308) and serine 473 (S473) of AKT1, inhibiting AKT1 activation
[[189]33], although this signaling pathway may need further
investigation in ovarian cancer cells. These data are in good agreement
with our observations in ovarian cancer. Additionally, KLF4 directly
interacts with the C-terminal transactivation domain of β-catenin and
inhibits p300/cbp recruitment by β-catenin [[190]35, [191]46].
β-Catenin also contributes to the transcriptional regulation of AKT1
[[192]47]. Importantly, cell phenotypes were rescued when inhibiting
the miR-9 in circPLEKHM3 knockdown cells, implying miR-9 as an
essential regulator in this model. Furthermore, when AKT1 was knocked
down in ovarian cancer cells with depletion of circPLEKHM3, the
upregulation of Wnt/β-catenin that resulted from downregulation of
circPLEKHM3 was dramatically attenuated; the cell phenotypes were also
rescued by decreasing cell proliferation and migration. Taken together,
these data suggested the circPLEKHM3-miR-9 axis is an important
regulator in mediating the crosstalk between Wnt/β-catenin and AKT1
signaling pathways that promote the progression of ovarian cancer.
As described above, circPLEKHM3 could hypoactivate AKT1. Our study
found that circPLEKHM3 is commonly down-regulated in ovarian cancer.
This is consistent with the abnormal activation of AKT1 frequently
observed in ovarian cancer [[193]37, [194]38]. These results provide a
rationale for the combination therapy of cisplatin-based chemotherapy
drugs with an AKT inhibitor in ovarian cancer. As expected, circPLEKHM3
knockdown cells were more sensitive to AKT inhibitor MK-2206. Moreover,
the chemotherapy drug Taxol synergistically improved the effect of
MK-2206 in ovarian cancer cells with a loss of circPLEKHM3 expression.
Summarizing, circPLEKHM3 has strong potential as a therapeutic target
for ovarian cancer. MK2206 is now in phase II clinical trials
[[195]48]. Therefore, our results have the potential to translate into
effective therapies for ovarian cancer.
Lastly, one caveat should be acknowledged in the study. CircPLEKHM3 was
significantly down-regulated in ovarian cancer tissues compared with
normal tissues. Its expression was further decreased in peritoneal
metastatic ovarian carcinomas compared to primary ovarian carcinomas.
To evaluate its potential clinical value, we measured the expression of
circPLEKHM3 in FFPE tissues from ovarian cancer using the BaseScope
assay. Interestingly, we observed that tumor tissues from patients with
short-term survival tend to have fewer positive staining cells than
those with long-term survival. This implied that the reduction of
circPLEKHM3 expression at tumor tissue level is likely attributed to
the reduced number of cells expressing circPLEKHM3. However, the
BaseScope assay is a semi-quantitative approach to detect RNA
expression using in situ hybridization. There is a detection limit in
the BaseScope assay. Some regions without visible dots could be due to
extremely low expression of circPLEKHM3. Additionally, we performed
single cell cloning of an ovarian cancer cell line (A2780) and found
that circPLEKHM3 has a considerable variability in expression among
these clones (Additional file [196]10: Figure S7B). Therefore, due to
the technical limitation and large variability in circPLEKHM3
expression, at the current stage we could not completely exclude
another potential mechanism that the reduction of circPLEKHM3
expression at tumor tissue level is perhaps attributed to the decreased
expression level per cell of circPLEKHM3. Whether the expression level
per cell of circPLEKHM3 is reduced or the number of cells expressing
circPLEKHM3 is reduced? It is an important question that could be also
asked about most studies with qRT-PCR and RNA-seq. Further
investigations are required to answer this question. It is worth noting
that the reduction in the expression of circPLEKHM3 within tumor
tissues that is caused by either of the above two mechanisms (reduction
in per cell or number of cells) will likely have the same effect on the
expression level of free miR-9 in general in tumor cell populations
(also saying, at tumor tissue level). That is, either of the two
mechanisms will lead to release more sponged miR-9 into tumor tissues,
which subsequently reduces the endogenous suppressive effect of BRCA1,
DNAJB6 and KLF4.
Conclusions
CircPLEKHM3 is down-regulated in ovarian cancer. Patients with a lower
circPLEKHM3 expression have a worse prognosis. CircPLEKHM3 was found to
act as a tumor suppressor that inhibits cell proliferation. It’s
down-regulation promotes EMT to facilitate tumor progression, and
induces resistance to the chemotherapy drug Taxol in ovarian cancer.
Mechanistically, circPLEKHM3 binds to miR-9 to enhance the endogenous
suppressive effect of BRCA1, DNAJB6 and KLF4. The circPLEKHM3-miR-9
axis is an important regulator in mediating the crosstalk between
Wnt/β-catenin and AKT1 signaling pathways that promote the progression
of ovarian cancer. The combination of Taxol with MK-2206 displays a
synergistic effect in cells with circPLEKHM3 loss. These results
indicate that circPLEKHM3 is a valuable prognostic biomarker and a
promising target for anti-cancer therapy in ovarian cancer. The new
strategy of treating ovarian cancer with a combination therapy of Taxol
and MK-2206 is worth further consideration, especially in ovarian
cancer patients with a loss of the expression of circPLEKHM3.
Supplementary information
[197]12943_2019_1080_MOESM1_ESM.pdf^ (6.4KB, pdf)
Additional file 1: Table S1. Quality control metrics of rRNA-depleted
RNA sequencing libraries.
[198]12943_2019_1080_MOESM2_ESM.pdf^ (135.8KB, pdf)
Additional file 2: Table S2. Information on antibodies and primers used
in this study.
[199]12943_2019_1080_MOESM3_ESM.pdf^ (104.4KB, pdf)
Additional file 3: Table S3. IC50 values for the treatment of MK-2206
and Taxol in A2780 scramble and circPLEKHM3 knockdown cells.
[200]12943_2019_1080_MOESM4_ESM.pdf^ (55.6KB, pdf)
Additional file 4: Figure S1. qRT-PCR analysis of the relative
abundance of circPLEKHM3 and PLEKHM3 mRNA in RNA-seq samples. Five
tumor tissues from ovarian cancer patients and five normal ovarian
tissues from patients with benign gynaecological diseases were used in
RNA-seq experiments.
[201]12943_2019_1080_MOESM5_ESM.pdf^ (210.3KB, pdf)
Additional file 5: Figure S2. Genomic information on circPLEKHM3. (A)
CircBase annotation for circPLEKHM3 (ID: hsa_circ_0001095). (B)
Sequences of full-length circPLEKHM3 from Sanger sequencing.
[202]12943_2019_1080_MOESM6_ESM.pdf^ (20.5KB, pdf)
Additional file 6: Figure S3. PLEKHM3 and circPLEKHM3 detected by
agarose gel electrophoresis of A2780 and OV90 cells.
[203]12943_2019_1080_MOESM7_ESM.pdf^ (197KB, pdf)
Additional file 7: Figure S4. BaseScope assay for circPLEKHM3 in normal
oviduct, normal ovary and ovarian tumor tissues.
[204]12943_2019_1080_MOESM8_ESM.pdf^ (165.2KB, pdf)
Additional file 8: Figure S5. BaseScope assay for circPLEKHM3 in
primary ovarian carcinoma and matched peritoneal metastatic ovarian
carcinomas.
[205]12943_2019_1080_MOESM9_ESM.pdf^ (531.1KB, pdf)
Additional file 9: Figure S6. PLEKHM3 expression is not associated with
survivals of ovarian cancer patients. (A) The protein expression of
PLEKHM3 was measured by IHC analysis. Nine of eighty-six patients
either failed to have a good IHC staining or did not acquired
additional FFPE tissue blocks. (B) Kaplan–Meier survival analysis of
PLEKHM3 expression in ovarian cancer patients. Differences in the
survival risk between the two groups were assessed by the
Mantel–Haenszel log-rank test.
[206]12943_2019_1080_MOESM10_ESM.pdf^ (265.8KB, pdf)
Additional file 10: Figure S7. Expression of circPLEKHM3 in ovarian
cancer cells. (A) The relative expression of circPLEKHM3 in TOV112D,
OVCAR-3, HO8910, MDAH2774, OV90, A2780, and IOSE80 cell lines by real
time quantitative RT-PCR. (B) Expression of circPLEKHM3 in single cell
clones from A2780 cells.
[207]12943_2019_1080_MOESM11_ESM.pdf^ (41.6KB, pdf)
Additional file 11: Figure S8. The relative expression of PLEKHM3 after
knockdown or overexpression of circPLEKHM3 in ovarian cancer cells by
real time quantitative RT-PCR.
[208]12943_2019_1080_MOESM12_ESM.pdf^ (432.4KB, pdf)
Additional file 12: Figure S9. Representative images (20×
magnification) of immunohistochemical staining for E-cadherin and SNAIL
in immunodeficient mice injected with A2780 scramble and shcircPLEKHM3
cells.
[209]12943_2019_1080_MOESM13_ESM.pdf^ (194.8KB, pdf)
Additional file 13: Figure S10. Sanger sequencing of luciferase report
vectors of circPLEKHM3, DNAJB6 variant 1 and KLF4 3′ UTRs. The
highlighted sequences represent parts of miR-9 seed sequences that were
mutated on psiCHECK™-2 Vectors.
[210]12943_2019_1080_MOESM14_ESM.pdf^ (50.8KB, pdf)
Additional file 14: Figure S11. The relative expression of KLF4 and
DNAJB6 after knockdown of circPLEKHM3 in OV90 cells. The expression of
KLF4 and DNAJB6 was quantified by FPKM (fragments per kilobase of exon
model per million reads mapped) in the RNA-seq data from OV90
circPLEKHM3 knockdown and negative control (NC) cells.
[211]12943_2019_1080_MOESM15_ESM.pdf^ (114.3KB, pdf)
Additional file 15: Figure S12. The relative expressions of DNAJB6a
(DNAJB6 isoform a), DNAJB6b (DNAJB6 isoform b), KLF4 and BRCA1 in A2780
cells transfected with miR-9 mimic and inhibitor by immunoblotting
analysis.
[212]12943_2019_1080_MOESM16_ESM.pdf^ (281.8KB, pdf)
Additional file 16: Figure S13. Ovarian cancer patients with a higher
expression of DNAJB6 variant 1 and KLF4 are associated with better
prognoses. The expression of DNAJB6 variant 1 was retrieved from
RNA-seq data of ovarian cancer in TCGA. The expression of KLF4 was
downloaded from the Gene Expression Omnibus (GSE3149). Differences in
the survival risk between the two groups were assessed by the
Mantel–Haenszel log-rank test.
[213]12943_2019_1080_MOESM17_ESM.pdf^ (548.7KB, pdf)
Additional file 17: Figure S14. Apoptosis assays of cells with
treatment Taxol and/or MK2206. Cells were treated with Taxol (3 nM)
alone, MK2206 (3 μM) alone or Taxol in combination with MK-2206. Cells
were harvested and stained using the Annexin V-FITC apoptosis detection
kit after about 48 h of treatment. Cells with Annexin V+ staining
located in the right upper and lower quadrants were considered as
apoptotic cells (mean ± SEM, n = 3).
Acknowledgments