Abstract

Introduction

   Ovarian cancer is one of the most common gynecological cancers
   worldwide. While, therapies against ovarian cancer have not been
   completely effective, sinomenine has been proved to have anti-tumor
   activity in various cancer cells. However, study of its anti-ovarian
   cancer effect is still rare, and the underlying mechanism has not been
   elucidated. Therefore, we aim to explore the mechanism of sinomenine
   anti-ovarian cancer.

Materials and Methods

   The effect of anti-ovarian cancer HeyA8 cells was analyzed by CCK8 and
   colony formation assay. The mechanism of sinomenine anti-ovarian cancer
   was explored via high throughput RNA-seq, and then the target mRNA and
   protein expression were verified by real-time PCR and Western blot,
   respectively.

Results

   We found that the proliferation and clone formation ability of ovarian
   cancer HeyA8 cells were markedly reduced by 1.56 mM sinomenine. The
   transcriptome analysis showed that 2679 genes were differentially
   expressed after sinomenine treatment in HeyA8 cells, including 1323
   down-regulated genes and 1356 up-regulated genes. Gene ontology and
   KEGG pathway enrichment indicated that differential expression genes
   (DEGs) between the groups of sinomenine and DMSO-treated HeyA8 cells
   were mainly involved in the process of the cell cycle, such as
   kinetochore organization, chromosome segregation, and DNA replication.
   Strikingly, the top 18 ranked degree genes in the protein–protein
   interaction (PPI) network were mainly involved in the process of
   mitosis, such as sister chromatid segregation, condensed chromosome,
   and microtubule cytoskeleton organization. Moreover, real-time PCR
   results showed consistent expression trends of DEGs with transcriptome
   analysis. The results of Western blot showed the expression level of
   CDK1, which was the highest degree gene in PPI and the main regulator
   controlling the process of mitosis, and the levels of phosphorylated
   P-CDK (Thr161) and P-Histone H3 (Ser10) were decreased after being
   treated with sinomenine.

Conclusion

   Our results demonstrated that sinomenine inhibited the proliferation of
   HeyA8 cells through suppressing mitosis by down-regulating the
   expression and the activity of CDK1. The study may provide a
   preliminary research basis for the application of sinomenine in
   anti-ovarian cancer.

   Keywords: ovarian cancer, sinomenine, high throughput RNA-seq, CDK1,
   cell proliferation

Introduction

   Ovarian cancer (OC) is the seventh most common cancer among women in
   the world and the second leading cause of gynecological cancer
   death.[40]^1 Most OC is often diagnosed at the advanced stage.[41]^2 In
   the past few decades, many treatment methods, such as active surgery,
   targeted therapy, intraperitoneal hyperthermia chemotherapy, small
   molecular inhibitors, neoadjuvant chemotherapy, and intraperitoneal
   chemotherapy, were hired to cure OC.[42]^3^,[43]^4 However, most
   patients with ovarian cancer will suffer from tumor recurrence after
   first-line therapy. Although OC is sensitive to chemotherapy with
   platinum and taxane following debulking surgery, resistance to
   chemotherapy will eventually develop in almost all patients. Once the
   disease recurs, the interval between subsequent treatments steadily
   decreases due to rapid development and chemoresistance.[44]^5
   Therefore, it is urgent to explore more effective reagents for the
   treatment of OC.

   Natural plant products have been widely used in the treatment of
   various diseases. Sinomenine
   (7,8-didehydro-4-hydroxy-3,7-dimethoxy-17-methylmorphinan-6-one), an
   alkaloid monomer extracted from Sinomenium acutum plants, contains four
   rings, A, B, C and D.[45]^6 Many studies have proved that sinomenine
   has anti-inflammatory, anti-rheumatic, anti-oxidant, analgesic,
   immunosuppressive, and anti-angiogenic effects.[46]^7–11 Although the
   shorter biological half-life of sinomenine and the side-effects, such
   as increasing histamine release, restrained its clinical
   applications,[47]^6^,[48]^12 sinomenine has also been developed into
   Zhengqingfengtongning (ZQFTN), a Chinese proprietary medicine approved
   by the Chinese government for treating RA and other autoimmune diseases
   in China. The anti-tumor effect of sinomenine has been preliminarily
   addressed in many kinds of tumors, such as liver cancer,[49]^13 breast
   cancer,[50]^14 lung cancer,[51]^15 renal cell carcinoma,[52]^16 and
   glioblastoma.[53]^17 Recently, the inhibitory effect of sinomenine on
   growth and metastasis of ovarian cancer cells has drawn considerable
   attention.[54]^18^,[55]^19 Li et al showed that sinomenine inhibits
   ovarian cancer cell growth and metastasis by inhibiting the
   Wnt/β-catenin pathway via targeting MCM2.[56]^18 Xu et al identified
   that sinomenine exerted the antitumor effect in ovarian cancer cells by
   hindering the expression of long non-coding RNA HOST2.[57]^19 However,
   these studies and findings are basic and preliminary for the effect of
   sinomenine on ovarian cancer. The mechanism of sinomenine inhibiting
   ovarian cancer remains to be further elucidated.

   High-throughput sequencing, especially RNA sequencing (RNA-seq) has
   become an effective way to explore functional genes and mechanisms in
   anti-tumor research because of its low cost and ultra-high data
   output.[58]^20 Recently, RNA-seq has been successfully applied in
   ovarian cancer research for earlier detection, identification of
   pathological origin, defining the aberrant genes and dysregulated
   molecular pathways across patient groups, and identification of novel
   genes and molecular pathways in the development of multidrug
   resistance.[59]^21 Here, we hired high-throughput RNA-seq to explore
   the potential mechanism of the sinomenine mediated growth inhibition of
   ovarian cancer HeyA8 cells. Then, the results of the high-throughput
   mRNA sequence were validated by real-time PCR. Furthermore, we also
   preliminarily clarified that sinomenine inhibited the growth of ovarian
   cancer cells through the suppression of mitosis by down-regulating the
   expression and the activity of CDK1. This study was expected to lay a
   theoretical foundation for the future application of sinomenine in the
   treatment of ovarian cancers.

Materials and Methods

Tumor Cells and Cell Culture Condition

   The human ovarian cancer cell line HeyA8-MDR was obtained from Stem
   Cell Bank, Chinese Academy of Sciences and was maintained in RPMI-1640
   (Hyclone) supplemented with 10% fetal bovine serum (Gibcol) and 1%
   penicillin/streptomycin (Gibcol) at 37 °C in a humidified atmosphere
   with 5% CO[2].

Cell Survival Rate Assay and Cell Proliferation Assay

   For cell survival rate assay, HeyA8-MDR cells were seeded at a density
   of 5000 cells per well into 96-well plates. After incubation for 24
   hours, sinomenine (0, 0.25, 0.5, 1, 2, 4 and 8 mM) was added to each
   well. The control cells (0 µM) were only treated with an equivalent
   volume of DMSO. Each concentration of sinomenine was tested with six
   replicates. After incubation for 48 hours, the culture medium was
   supplemented with 10 ul CCK8 solution for 2 hours at 37 °C. Then the
   absorbance was measured at 450 nm. Cell survival rates were shown as a
   percentage of the absorbance reading of the control cells. IC50 was
   calculated with the IC50 Calculator
   ([60]https://www.aatbio.com/tools/ic50-calculator).

   Cell proliferation assay was detected by CCK8 as described in our
   previous study.[61]^22 Briefly, 1 × 10^3 HeyA8-MDR cells per well were
   plated on 96-well plates. After being incubated for 24 hours, the cells
   were treated with 1.56 mM sinomenine and DMSO separately. Then, 10 µL
   CCK8 reagent was added to each well and incubated for 2 hours at 37 °C.
   The optical density value was measured at 450 nm every day for 7 days.

Clone Formation Assay

   HeyA8-MDR cells were seeded at a density of 200 cells per well into
   6-well plates. HeyA8-MDR cells, treated with 1.56 mM sinomenine and
   DMSO separately, were incubated for 10 days in a cell incubator at 37
   °C. Then, the cells were fixed with 4% PFA and stained with crystal
   violet staining solution (#Y1232, Yuxiu Biotech, China). The number of
   colonies, containing more than 50 cells observed under a microscope,
   were counted.

RNA Extraction, RNA-Seq Transcriptome Library Construction, and Illumina
HiSeq 4000 Sequencing

   RNA extraction, library construction and sequencing were performed at
   Shanghai Majorbio Bio-pharm Biotechnology Co., Ltd. (Shanghai, China).
   Total RNA was extracted using TRIzol^® Reagent (Thermo Scientific) and
   genomic DNA was removed by digestion with DNase I (Takara). Then RNA
   quality was determined by 2100 Bioanalyser (Agilent) and quantified
   using the ND-2000 (NanoDrop Technologies). Only high-quality RNA
   samples (OD260/280 = 1.8~2.2, OD260/230≥2.0, RIN≥6.5, 28S:18S≥1.0, >2
   μg) were used to construct the sequencing library.

   RNA-seq transcriptome library was constructed with the TruSeqTM RNA
   sample preparation Kit from Illumina (San Diego, CA) using 1 μg of
   total RNA. Shortly, messenger RNA was purified using oligo (dT)
   magnetic beads and then fragmented by fragmentation buffer.
   Double-stranded cDNA was synthesized using a SuperScript
   double-stranded cDNA synthesis kit (Invitrogen) with random hexamer
   primers (Illumina). Then the synthesized cDNA was subjected to
   end-repair, phosphorylation and “A” base addition according to
   Illumina’s library construction protocol. Libraries were size selected
   for cDNA target fragments of 200–300 bp on 2% Low Range Ultra Agarose
   followed by PCR amplified using Phusion DNA polymerase (NEB) for 15 PCR
   cycles. After being quantified by TBS380, the paired-end RNA-seq
   sequencing library was sequenced with the Illumina HiSeq 4000 (2×150 bp
   read length). The RNA-seq data were deposited at NCBI (BioProject id:
   PRJNA641485).

Read Mapping

   The raw paired end reads were trimmed and quality controlled by SeqPrep
   ([62]https://github.com/jstjohn/SeqPrep) and Sickle
   ([63]https://github.com/najoshi/sickle) with default parameters. Then
   clean reads were separately aligned to reference the genome with
   orientation mode using TopHat ([64]http://tophat.cbcb.umd.edu/,
   version2.1.1) software.[65]^23 The mapping criteria of bowtie were as
   follows: sequencing reads should be uniquely matched to the genome
   allowing up to 2 mismatches, without insertions or deletions. Then the
   region of the gene was expanded following depths of sites and the
   operon was obtained. In addition, the whole genome was split into
   multiple 15 kb windows that share 5 kb. New transcribed regions were
   defined as more than 2 consecutive windows without an overlapped region
   of gene, where at least 2 reads were mapped per window in the same
   orientation.

Differential Expression Analysis and Functional Enrichment

   The expression level of each transcript was calculated according to the
   Transcripts Per Kilobase of exon model per Million mapped reads (TPM)
   using RSEM ([66]http://deweylab.biostat.wisc.edu/rsem/).[67]^24 The
   differentially expressed genes (DEGs) (fold changes ≥ 2 and corrected
   P-value ≤0.05) between control and sinomenine-treated HeyA8 cell line
   were identified by R statistical package software EdgeR (Empirical
   analysis of Digital Gene Expression in R,
   [68]http://www.bioconductor.org/packages/2.12/bioc/html/edgeR.html).[69
   ]^25 GO functional enrichment and KEGG pathway analysis were carried
   out by Goatools ([70]https://github.com/tanghaibao/Goatools) and KOBAS
   2.1.1 ([71]http://kobas.cbi.pku.edu.cn/download.php).[72]^26 The GO
   terms and the KEGG pathways were considered statistically significant
   when Bonferroni-corrected P-value ≤0.05.

Protein–Protein Interaction (PPI) Network Analysis

   The PPI for DEGs (fold changes≥4 and corrected P-value ≤0.05) were
   calculated on the web of the Retrieval of Interacting Genes (STRING)
   database ([73]https://string-db.org/)[74]^27 and the cut-off criterion
   of the combined score was set as >0.4. Then, PPI networks for DEGs were
   visualized by Cytoscape (Version: 3.8.0).[75]^28

Real-Time PCR

   Total RNAs were reverse transcribed by the MMLV Reverse Transcriptase
   (Promega) according to the manufacture’s protocol. Real-time PCR
   analysis was performed on the LightCycler^® 96 System (Roche) with
   ChamQ SYBR qPCR Master Mix (Q321-02, Vazyme, China). All samples were
   examined in triplicate. The fold changes of each target gene were
   calculated using the 2^−ΔΔCt method relative to GAPDH.

Flow Cytometry Assay

   Cells, which were treated with sinomenine and DMSO separately, were
   harvested and washed twice with PBS. Then the cells were fixed with 4%
   paraformaldehyde for 10 min at 4 °C, and permeabilized for 10 minutes
   with 0.3% Triton X-100. The cells were incubated with anti-P-Histone H3
   (53348, CST) antibodies for 30 minutes. After staining, the cells were
   washed twice and then incubated with FITC-conjugated Affinipure Goat
   Anti-Rabbit IgG (H+L) (SA00003-2, Proteintech) for 30 minutes. After
   being washed twice, the stained cells were stained with 50 ug/mL
   propidium iodide (PI) and analyzed with Beckman Coulter CytoFLEX flow
   cytometry system.

Western Blot

   Western blots were performed as described previously.[76]^29 The
   primary antibodies were listed as follows: Geminin (52508), CDT1
   (8064), Thymidine Kinase 1 (28755), P-Histone H3 (53348), Cyclin A2
   (91500), Cyclin B1 (12231), Cyclin E1 (20808) and P-cdc2 (Tyr15) (4539)
   from Cell Signaling Technology, P-Cdk1/2 (Thr14) (DF2944) and P-CDK1
   (Thr161) (AF8001) from Affinity, CDK1 (67575-1-Ig) from Protein Tech
   Group.

Statistical Analysis

   The data were shown as means ± standard deviation (SD). The difference
   between means was analyzed using SPSS 16.0 software (SPSS Inc.,
   Chicago, IL, USA). The methods of statistical analysis were indicated
   in figure legends. p < 0.05 was considered as statistically
   significant.

Results

Sinomenine Inhibits the Growth of Ovarian Cancer Cell Line HeyA8

   To explore the inhibitory effect of sinomenine on the cell growth of
   ovarian cancer HeyA8 cells, the cell viability of HeyA8 were measured
   by CCK8 assay. As shown in [77]Figure 1A, the inhibitory effect of
   sinomenine on HeyA8 cells was dose-dependent. The IC50 of sinomenine
   was 1.56 mM in HeyA8 cells ([78]Figure 1B). The result of the CCK8
   assay showed that sinomenine significantly suppressed the proliferation
   of HeyA8 at the concentration of 1.56 mM ([79]Figure 1C). In addition,
   the result of the clone formation assay also indicated that sinomenine
   significantly inhibit the ability of the clone formation of HeyA8 cells
   ([80]Figure 1D and [81]E). Taken together, these results indicated that
   sinomenine inhibited the growth of ovarian cancer HeyA8 cells, which is
   consistent with results in previous reports.[82]^18^,[83]^19

Figure 1.

   [84]Figure 1
   [85]Open in a new tab

   Sinomenine inhibits proliferation of ovarian cancer cell line HeyA8.
   (A) The survival rate of HeyA8 cells treated with different
   concentrations of sinomenine (0, 0.25, 0.5, 1.0, 2.0, 4.0, and 8.0 mM)
   for 48 hours were measured by CCK8 assay. (B) The IC50 of sinomenine
   was 1.56 mM in HeyA8 cells, which was calculated with the IC50
   Calculator on the website
   ([86]https://www.aatbio.com/tools/ic50-calculator). (C) The growth
   curves of HeyA8 treated with DMSO as control and sinomenine (1.56 mM)
   were measured by CCK8 assay. (D) HeyA8 treated with sinomenine formed
   fewer and smaller colonies than those treated with DMSO. (E) The number
   of colonies of HeyA8 cells treated with sinomenine and DMSO separately
   in (D), the value represents the mean ± SD for triplicate samples,
   **P<0.01, Student’s t-test.

Differentially Expressed Genes (DEGs) in HeyA8 Cells Caused by the Treatment
of Sinomenine

   To investigate the DEGs caused by the treatment of sinomenine, the gene
   expression of HeyA8 cells, which were treated with 1.56 mM sinomenine
   and an equal volume DMSO for 48 hours separately, were analyzed by
   high-throughput RNA sequencing. After gene mapping and the expression
   level of each transcript was converted to the value of TPM, the
   comparison at corrected P-value p ≤ 0.05 and log2FC fold change ≥ 1
   (for up-regulation) or ≤ −1 (for down-regulation) was made to identify
   the DEGs for two groups ([87]Figure 2A). The list of DEGs, along with
   their TPM and annotations, are presented in [88]Supplementary Table S1.
   A total of 2679 genes were identified as DEGs, including 1323
   down-regulated genes and 1356 up-regulated genes ([89]Figure 2B), and
   were displayed by cluster heatmaps ([90]Figure 2C).

Figure 2.

   [91]Figure 2
   [92]Open in a new tab

   Differentially expressed genes (DEGs) between different treatment
   groups. (A) Volcano map of DEGs. The horizontal axis represents
   expression changes (log) of the genes in sinomenine and DMSO treated
   groups, while the vertical axis showed the statistical significance of
   the changes in gene expression. The discrepancy was more significant
   with smaller p values and bigger −log10 (corrected p-value). Each dot
   in the image represents one gene, the grey dots represent genes with no
   significant discrepancy, red dots were significantly up-regulated genes
   and green dots were significantly down-regulated genes. (B) The numbers
   of DEGs. There were 1323 down-regulated genes and 1356 up-regulated
   genes. (C) Heatmap of DEGs. Red represents high relative gene
   expression level and blue represents low relative gene expression
   level. Con: groups of HeyA8 cells treated with DMSO, SIN: groups of
   HeyA8 cells treated with sinomenine.

Gene Ontology and KEGG Pathway Enrichment Analysis of DEGs

   To study the characteristics of the 2679 DEGs, gene ontology (GO)
   enrichment analysis was performed. The top 20 ranked GO terms of DEGs
   were shown in [93]Figure 3A. Kinetochore organization occupied the
   strongest enrichment degree as it possessed the highest rich factor
   (0.65), followed by strand displacement, meiotic chromosome
   segregation, attachment of spindle microtubules to kinetochore and DNA
   strand elongation. These enriched GO terms were obviously involved in
   the regulation of cell cycle, especially involved in the DNA
   replication in S phase, Kinetochore organization in G2 phase and
   chromosome segregation in M phase. These indicated that sinomenine
   inhibits the HeyA8 cell growth by regulating the process of the cell
   cycle.

Figure 3.

   [94]Figure 3
   [95]Open in a new tab

   GO and KEGG enrichment analysis of DEGs. (A) Bubble diagram of top 20
   ranked GO terms of DEGs. The vertical axis indicates GO terms and the
   horizontal axis represents the rich factor. The enrichment degree was
   stronger with a bigger rich factor. The size of dots indicates the
   number of genes in the GO term. (B) KEGG pathway enrichment analysis of
   DEGs. The vertical axis represents KEGG pathways. The upper horizontal
   axis represents the number of genes enriched in the indicated pathway
   (dots on the yellow line). The lower horizontal axis represents the
   significant level of enrichment (green bar).

   To further investigate the biological functions of DEGs, KEGG pathway
   enrichment analysis was performed. The results also showed the top 20
   statistically significant pathways ([96]Figure 3B). The top 5
   significant pathways are DNA replication, cell cycle, homologous
   recombination, Fanconi anemia pathway, and microRNAs in cancer. In
   addition to the above pathways, these pathways including purine
   metabolism, pyrimidine metabolism, mismatch repair and nucleotide
   excision repair are also closely related to the cell cycle. Taken
   together, these results of GO and KEGG pathway enrichment could provide
   essential information on the investigation of sinomenine in ovarian
   cancer HeyA8 cells.

Protein–Protein Interaction (PPI) Network Analysis of DEGs

   In order to systemically analyze the functions of DEGs in
   sinomenine-treated ovarian cancer HeyA8 cells, a total of 856 DEGs
   (foldchange ≥ 4, corrected P-value ≤ 0.05) were mapped to the PPI
   database to obtain the PPI networks. As shown in [97]Figure 4A, a total
   of 600 relationships between 104 genes (nodes) were identified.
   [98]Table 1 shows the node genes with the top 18 ranked degree (number
   of interactions). The DEGs of CDK1 (degree = 62), PLK1 (degree = 50),
   BUB1 (degree = 48), NDC80 (degree = 48) and BUB1B (degree = 44) formed
   networks with high degrees. The top 3 ranked degree genes (CDK1, PLK1,
   and BUB1) play important roles in the progression of G2/M phase in the
   cell cycle.[99]^30^,[100]^31 Furthermore, real-time PCR analysis was
   used to verify the results of transcriptome sequencing and the results
   indicated that the expression trends of the top 18 ranked degree genes
   were consistent with those obtained by RNA-seq, suggesting that the
   RNA-seq data reliably reflected the gene expression alterations
   ([101]Figure 4B). According to the RNA-seq and real-time PCR results,
   the expressions of cell cycle regulated genes, such as CDK1, PLK1, and
   BUB1, were significantly decreased after sinomenine treatment. These
   results were also in accord with the cell phenotype experiments.

Figure 4.

   [102]Figure 4
   [103]Open in a new tab

   The network of protein-protein interactions (PPI) of DEGs. (A) The
   network of PPI. The size of the circles (nodes) represents the degrees
   of the gene in the PPI network. A greater size indicates a greater
   degree. (B) Real-time PCR validation of the expressions of top18 degree
   DEGs. Yellow lines were from the results of the transcriptome data (TPM
   Value); Black lines were from the results of real-time PCR (Relative
   Expression). Con: HeyA8 cells treated with DMSO; SIN: HeyA8 cells
   treated with sinomenine for 48 hours. Three replicates were carried out
   in the real-time PCR analysis. Bars represent means ± SD (n = 3). (C)
   Histogram of top 20 ranked GO terms of the real-time PCR validated 18
   genes in the PPI network.

Table 1.

   Node Genes with Top 18 Ranked Degree in the PPI Network
   Tanscript/Gene ID    String ID    Degree
   CDK1              ENSG00000170312 62
   PLK1              ENSG00000166851 50
   BUB1              ENSG00000169679 48
   NDC80             ENSG00000080986 48
   BUB1B             ENSG00000156970 44
   MAD2L1            ENSG00000164109 34
   CCNB1             ENSG00000134057 34
   CCNB2             ENSG00000157456 32
   CENPE             ENSG00000138778 30
   KIF11             ENSG00000138160 30
   AURKA             ENSG00000087586 26
   KIF2C             ENSG00000142945 22
   NUF2              ENSG00000143228 22
   CCNA2             ENSG00000145386 22
   MCM2              ENSG00000073111 20
   MCM7              ENSG00000166508 18
   CENPA             ENSG00000115163 18
   UBE2C             ENSG00000270804 18
   [104]Open in a new tab

   In addition, GO enrichment analysis indicated that the validated 18
   genes were enriched in regulation of sister chromatid segregation,
   chromosome, condensed chromosome, microtubule cytoskeleton organization
   involved in mitosis, condensed nuclear chromosome, mitotic cell cycle
   process, and mitotic nuclear division, etc. ([105]Figure 4C). These
   results suggested that sinomenine may affect the proliferation of
   ovarian cancer HeyA8 cells by regulating the progression of M phase in
   cell cycle through these target genes and their classical pathways.

Sinomenine Suppressed Mitosis by Inhibiting the Expression and the Activity
of CDK1

   The results of RNA-seq and real-time PCR indicated that sinomenine
   inhibited the mRNA expression level of CDK1 in ovarian cancer HeyA8
   cells. While, the cyclin B1/Cdk1 complex was reported to play an
   important role in regulating the entry into mitosis.[106]^32^,[107]^33
   In order to clarify the effect of sinomenine on cell cycle
   distribution, firstly, we analyzed the cell cycle distribution of HeyA8
   cells by flow cytometry assay and the results showed the population of
   G2/M were decreased from 55.6% ± 2.85% to 44.08% ± 3.22% in HeyA8 cells
   treated with sinomenine for 48 hours ([108]Figure 5A and [109]B).
   Meanwhile, the percentage of M phase was decreased from 14.46 ± 1.10%
   to 6.35% ± 0.61% ([110]Figure 5C and [111]D). Then, the expression
   levels of some cell cycle related proteins including cyclin E1, cyclin
   A2, cyclin B1, Geminin, CDT1, Thymidine kinase 1 and P-Histone H3
   (Ser10), which presented in cells at various phases of the cell cycle,
   were analyzed by Western blot ([112]Figure 5E). The results showed that
   the expression level of P-Histone H3 (Ser10), which is present only in
   the M phase, was significantly decreased in sinomenine treated HeyA8
   cells when compared with DMSO treated negative control HeyA8 cells and
   blank control HeyA8 cells. However, there were no significant changes
   in the expression levels of other cell cycle related proteins
   ([113]Figure 5F). These results indicated that sinomenine decreased the
   number of M-phase cells, suggesting the suppression of mitosis in
   ovarian cancer HeyA8 cells.

Figure 5.

   [114]Figure 5
   [115]Open in a new tab

   Sinomenine suppressed G2/M transition in HeyA8 cells by inhibiting the
   expression and the activity of CDK1. (A and B) The cell cycle
   transition of HeyA8 cells was examined by flow cytometry assay (A). The
   results showed that the percentage of cells in the G2/M phase was
   decreased significantly after treatment with sinomenine for 48 hours
   (B). Each value represents the mean ± SD for triplicate samples.
   ***P<0.001, Student’s t-test. (C and D) The percentage of M phase cells
   were analyzed by flow cytometry assay staining with P-Histone H3
   (Ser10) and PI (C). The results showed that the percentage of M phase
   in HeyA8 cells treated with sinomenine for 48 hours were obviously
   decreased (D). Each value represents the mean ± SD for triplicate
   samples. ***P<0.001, Student’s t-test. (E) The expression of specific
   proteins in different cell cycle phase were determined by Western blot.
   (F) The expression level of P-Histone H3 (ser10), which only expressed
   in the M phase, were clearly decreased in sinomenine treated HeyA8
   cells. Each value represents the mean ± SD for triplicate samples.
   ***P<0.001, one-way ANOVA analysis. (G) The expression of CDK1 and the
   phosphorylation of CDK1 were detected by Western blot. (H) The
   expression level CDK1 and P-CDK1 (Thr161) were clearly decreased in
   sinomenine treated HeyA8 cells. Each value represents the mean ± SD for
   triplicate samples. **P<0.01, ***P<0.001, one-way ANOVA analysis.

   Meanwhile, the activity of CDK1 depends on its phosphorylation
   state.[116]^34 Phosphorylation of the Thr161 residue of Cdk1 can
   stabilize its interaction with cyclins and lead to further activation
   of the kinase.[117]^35 On the other hand, the cyclin B1/Cdk1 complex
   can be inactivated via inhibitory phosphorylation of Thr14 and Tyr15
   residues of the CDK1.[118]^36 Therefore, we detected the protein
   expression level and phosphorylation levels of CDK1 by Western blot
   ([119]Figure 5G). The results showed that the expression level of CDK1
   and the phosphorylation level of CDK1 on Thr161 in sinomenine treated
   HeyA8 cells were significantly lower than those in DMSO treated HeyA8
   cells and control HeyA8 cells. While, the phosphorylation levels of
   CDK1 on Thr14 and Tyr15 did not change significantly ([120]Figure 5H).
   These results indicated that sinomenine suppressed the expression of
   CDK1 and the activity of CDK1 by inhibiting the phosphorylation of CDK1
   on Thr161.

Discussions

   OC is the most lethal gynecologic malignancy and no significant
   treatment progress has been made in the past 30 years. It is easy to
   relapse and form drug resistance after the first comprehensive
   treatment. In order to improve the survival rate and prolong the
   survival period of patients, it is very important to find new effective
   chemotherapy drugs for the treatment of OC. Many studies showed that a
   large number of natural plant products possess the ability of
   anti-tumor. Up to now, many natural anti-tumor products, such as
   vinblastine, vincristine, podophyllotoxin, paclitaxel (Taxol) and
   camptothecin, have been tested clinically.[121]^37 In recent years,
   sinomenine, an alkaloid extracted from Sinomenium acutum plants, have
   been proved to have the ability of anti-tumor. However, the study of
   its anti-ovarian cancer effect is still rare and its mechanism is
   unclear. Here, we studied the anti-tumor effect of sinomenine on
   ovarian cancer cells and found that sinomenine inhibits the capacities
   of proliferation and colony formation of ovarian cancer HeyA8 cells,
   which was consistent with previous reports.[122]^18^,[123]^19
   Furthermore, we firstly preliminarily explored its mechanism by
   High-throughput RNA-seq. The results of GO and KEGG pathway enrichment
   and the Protein–Protein Interaction Analysis indicated that the DEGs
   were mainly involved in the cell cycle.

   Cell survival and proliferation mainly depend on the progression of the
   cell cycle, which is a series of tightly-regulated molecular events
   controlling DNA replication and mitosis.[124]^38^,[125]^39 The entry
   into mitosis is regulated by the activation of Cdc2/Cdk1 kinase, which
   was controlled by several steps including cyclin B1 nuclear
   accumulation and binding, dephosphorylation of Cdc2/Cdk1 at Thr14 and
   Tyr15, and phosphorylation of Cdc2/Cdk1 at Thr161.[126]^40^,[127]^41 In
   our experiment, sinomenine decreased the expression level of CDK1 and
   especially suppressed the activated phosphorylation Thr161 on CDK1. At
   the same time, sinomenine also decreased the phosphorylation of Histone
   H3 at Ser10, which is tightly correlated with chromosome condensation
   during mitosis.[128]^42 These results suggested that sinomenine
   inhibited the proliferation of ovarian cancer HeyA8 cells through
   suppressing the mitosis by down-regulating the expression and the
   activity of CDK1.

   While the process of the M phase is composed of many biological events,
   such as chromatin condenses, Spindle formation, chromosome separation,
   mitotic nuclear division, and mitotic DNA damage checkpoint.[129]^43
   The results of GO enrichment assay indicated that many of the top 18
   ranked DEGs in PPI were involved in multiple biological events in phase
   M. For instance, PLK1, serine/threonine-protein kinase 1, performs
   several important functions throughout M phase of the cell cycle,
   including the regulation of centrosome maturation and spindle assembly,
   the removal of cohesions from chromosome arms, the inactivation of
   anaphase-promoting complex/cyclosome (APC/C) inhibitors, and the
   regulation of mitotic exit and cytokinesis.[130]^44^,[131]^45 Mitotic
   checkpoint serine/threonine-protein kinase BUB1 performs two crucial
   functions, including spindle-assembly checkpoint signaling and correct
   chromosome alignment, during mitosis.[132]^46 NDC80, as a component of
   the essential kinetochore-associated NDC80 complex, is required for
   chromosome segregation and spindle checkpoint activity.[133]^47
   However, how sinomenine affects the process of M phase still needs to
   be further explored.

   In summary, our results indicated that sinomenine plays anti-tumor
   functions by inhibiting the growth of the ovarian cancer HeyA8 cells
   through the suppression of mitosis by down-regulating the expression
   and the activity of CDK1. These results may provide a preliminary
   research basis for the application of sinomenine in anti-ovarian
   cancer.

Acknowledgments