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Identification of commonly regulated genes in HPV18- and HPV16-infected cervical cancer cells treated with the curcumin analogue 1,5-bis(2-hydroxyphenyl)-1,4-pentadiene-3-one

Objective: To identify commonly regulated genes in HPV-infected HeLa and CaSki cervical cancer cells treated with curcumin analogue 1,5-bis(2-hydroxyphenyl)-1,4-pentadiene-3-one (MS17) and to explore potential mechanisms that underlie its cytotoxic, anti-proliferative and apoptotic activity. Methods: HeLa and CaSki cells were treated with 2 × EC50 and 3 × EC50 doses of MS17 for 24 h and the RNA extracts were subjected to one-colour microarray-based gene expression profiling. Pair-wise significant genes (false discovery rate-corrected, P<0.05) were analysed for fold change (FC) compared to control samples. Differentially expressed genes with FC⩾2.0 (up-regulated; FC⩾2.0 and down-regulated; FC⩽-2.0) compared to the control samples were filtered through and analysed to create a global gene expression profile. Mutually regulated genes were ranked by FC and categorised by gene ontology. Results: Our data indicated dose-dependent regulation by MS17 and identified top 20 mutually up- and down-regulated genes each in HeLa and CaSki cells. Amongst these 17 were commonly regulated in both cell lines. These include the up-regulation of CCL26, DEFB103B, IL1RL1, LY96, GCNT3, MMP10, MMP3, GADD45G and HSPA6, and the down-regulation of TENM2, NEBL, KIFC1, CTDSP1, IGFBP5, LTBP1, NREP and MXD3. These genes were associated with key biological functions that were proposed to mediate the anticancer activity of MS17 in cervical cancer cells such as immune response, metabolic processes, proteolysis, programmed cell death, unfolded protein response, cell adhesion, cytoskeletal organisation, phosphatase activity, signal transduction and transcription regulator activity. Conclusions: Identification of seventeen common genes modulated by MS17 could be used as potential therapeutic targets in both cervical cancer cell lines and the findings of this study could be used to present an insight into the potential antitumor activity of MS17 in cervical cancer.

The treatment of cervical cancer cells with curcumin activates caspase-3-mediated apoptosis, restores p53 and pRb expression and inhibits AP-1 and NF-κB activity [2][3][4]. Notably, curcumin demonstrates potential antiviral activity due to its ability to inhibit the expression of E6 and E7 viral oncogenes [5,6] which significantly increases the cytotoxic and apoptotic effects of curcumin treatment on cervical cancer cells [7]. Synthetic 1,5-diaryl-3-oxo-1,4-pentadiene curcumin analogues known as diarylpentanoids reported greater growth suppressive effects in cancer cells over curcumin or other 7-carbon curcumin analogues [8]. Similarly with curcumin, these diarylpentanoids mediated programmed cell death, mitotic arrest and anti-proliferative effects in numerous cancer cell lines via a wide variety of molecular targets including p53, NF-κB, STAT3, c-Myc and PTEN [9][10][11]. EF24 is the most studied DAP to date due to its ability to collectively target molecules that induce, among others, anti-proliferative, apoptotic, anti-angiogenesis and anti-oxidative effects in cancer cells [12][13][14]. The treatment of HeLa cervical cancer cells by EF24 demonstrated the inhibition of cell viability via the suppression of NF-κB signaling [14], and studies by two other groups reported the potential anti-proliferative and apoptotic effects of treatment on cervical cancer cells [15,16]. Recently, a PGA-based curcumin nanoparticle formulation has been shown to effectively inhibit growth, induce apoptosis and cause cell cycle arrest in CaSki and SiHa cervical cancer cell lines [17]. Beyond these studies however, the anticancer effect of diarylpentanoids on cervical cancer cell lines have not been extensively studied.
We have previously established [18] that treatment of 1,5-bis(2hydroxyphenyl)-1,4-pentadiene-3-one, known as MS17, on CaSki and HeLa cervical cancer cells demonstrated significant cytotoxic and anti-proliferative activity compared to curcumin. MS17 also demonstrated significant down-regulation of HPV18and HPV16-associated E6 and E7 oncogene expression following treatment. Furthermore, MS17-exposed cells exhibited significant morphological changes consistent with apoptosis at their respective 2×EC 50 (HeLa; 6 µM, CaSki; 4 µM) and 3×EC 50 (HeLa; 9 µM, CaSki; 6 µM) dosages at 24 h of treatment. This suggested that an increase in treatment dose by 1.5-fold was able to effect apoptotic changes within the cells. To the best of our knowledge, this is the first report of its kind on HPV-positive cervical cancer cells. To investigate the mechanisms of action of the MS17 curcumin analogue on cervical cancer cells at a molecular level, microarraybased gene expression profiling of MS17-treated HPV-18 infected HeLa and HPV-16 infected CaSki cells was performed. Dosedependent changes in gene regulation that occurred in response to treatment were analysed and the regulation of 17 genes that were mutual to both cervical cancer cell lines were identified as potential common targets of MS17. The molecular changes in the regulation of these genes that potentially justifies the cytotoxic, antiproliferative and apoptotic activity of MS17 on cervical cancer cells have been presented here and discussed.

Treatment of cervical cancer cells and total RNA extraction
Cancer cells were plated at 4×10 5 cells per mL in 1 mL culture medium per well as described earlier [18], exposed to MS17 at their respective doses for 24 h and prepared for RNA extraction. Experiments were performed in triplicate and included a set of untreated control cells (media with DMSO alone). Total RNA was extracted using the Qiagen RNeasy® Mini Kit (Qiagen, Valencia, CA., USA) according to the manufacturer's instructions. RNA samples with an A 260 /A 280 and A 260 /A 230 ratio of ≥1.9 and with a RNA integrity number score of approximately ≥8 were selected for gene expression profiling.

Microarray analysis
Agilent oligonucleotide microarrays were used for one-colour gene expression analysis and samples were prepared according to the protocols provided by One-Color Low Input Quick Amp labeling kit (Agilent, Valencia, CA, USA). Information from features on the array was extracted using Agilent's Feature Extraction Software 11.5.1 (Agilent Technologies, 2004, USA) and analysed (GeneSpring GX version 13.0 software, Agilent, USA). Normalisation was performed using Agilent Single Color 28004 Technology. Raw signals were log transformed, normalized and baseline transformed to the median of all samples. Values were normalised by shifting to the 75th percentile. Probes were subjected to additional steps of filtering on detected flags and expression value. Filtering on expression removes probes with low raw signal intensities (<20) and entities where at least 100 percent of samples in any 1 out of 4 conditions have values exceeding 20 qualified to proceed to the next filtering criteria.

Statistical analysis
Statistical analysis was performed using analysis of variance with Benjamini-Hochberg false discovery rate multiple testing correction, followed by a post hoc testing using Tukey's Honestly Significance Difference to identify pair-wise significant genes. Genes that passed the significance threshold with a false discovery rate-corrected adjusted P-value of P<0.05 was analysed for its fold change (FC) compared to control samples. FC measures the relative change in expression between treatment (MS17-treated samples) and control (DMSO-treated) conditions for a particular gene. Differentially expressed genes (DEGs) with FC≥2.0 (up-regulated; FC≥2.0 and down-regulated; FC≤-2.0) compared to the control samples were filtered through and analysed to create a global gene expression profile. Hierarchical cluster analysis was performed on this DEG list using software-recommended parameters.

Data analysis
For an analysis on the dose-dependent regulation of genes by MS17, downstream analysis focused on selected mutually regulated DEGs in MS17-treated HeLa (6 µM and 9 µM) and CaSki (4 µM and 6 µM) cells. The top twenty DEGs that were mutually upregulated and down-regulated each in both cell lines were selected to obtain a list of top ranked genes. Ontological analysis of mutually regulated genes was performed using the Database for Annotation, Visualisation and Integrated Discovery (DAVID) [19] which is freely accessed at http://david.abcc.ncifcrf.gov. Gene symbols of mutually expressed genes from each cell line were submitted to DAVID. Annotations were limited to 'Homo sapiens' and gene ontological (GO) analysis was performed using the functional annotation tool and further analysed using the GO functional categories which provide a description of associated biological processes and molecular functions for the selected genes. Genes were grouped into functional categories based on the exported GO terms from DAVID.

Validation of microarray results by quantitative realtime PCR
To assess the robustness of the microarray analysis, quantitative real-time PCR analysis was performed to validate a selected panel of DEGs (CCL26, MMP10, MMP3, CTDSP1, IGFBP and MXD3) and normalised against the endogenous gene, human glyceraldehyde 3-phosphate dehydrogenase (GAPDH). Complementary DNA was generated from the RNA isolated from MS17-treated HeLa and CaSki cells that were used for microarray profiling following the previously described protocol [18]. Transcript levels of the selected DEGs and GAPDH were measured by TaqMan® Gene Expression Assays specific to each gene. The primers and TaqMan probe sequences used for the selected genes corresponded to assay IDs (CCL26, Hs00171146_m1; MMP10, Hs00233987_ m1, MMP3, Hs00968308_m1; CTDSP1, Hs01105503_m1; IGFBP5, Hs01052295_m1; MXD3, Hs00361007_m1; GAPDH, Hs99999905_m1) acquired from the TaqMan Gene Expression Assay database (Applied Biosystems, USA). Samples were prepared according to manufacturer's instructions and loaded into the StepOnePlus™ real-time PCR system (Applied Biosystems), cycled using the Fast run method and relative mRNA expression levels of the target genes were calculated using the comparative Ct method. Each reaction was run in duplicates and fold change expression of mRNA results from quantitative real-time PCR was converted to log2 fold change and represented in bar graphs alongside log2 fold change data from microarray analyses. The bar graph representing the results was constructed using GraphPad Prism version 6.00 for Windows, GraphPad Software (San Diego, CA., USA).

Results
Based on dosages that were previously established to induce apoptosis, HeLa was exposed to 6 µM and 9 µM, while CaSki was exposed to 4 µM and 6 µM of MS17 for 24 h. Only significant entities that demonstrated a P-value of P<0.05 and were differentially expressed compared to the control by a fold change greater than or equal to 2.0 (FC≥2.0) were considered for analysis. Amongst these genes, 1 167 and 1 836 genes in HeLa were differentially expressed by 6 µM and 9 µM treatment respectively while in CaSki, 1 069 and 1 091 genes were differentially expressed by 4 µM and 6 µM treatment. DEGs were subjected to a hierarchical cluster analysis from which a dose-dependent effect of MS17 treatment on both HeLa and CaSki gene regulation was suggested as 826 genes in HeLa and 491 genes in CaSki composed DEGs that were mutually expressed by both treatment doses. Of these DEGs, we have identified top 20 mutually up-and down-regulated genes each in HeLa and CaSki cells.
Ontological classification was performed on the top 20 ranking genes that were differentially regulated by MS17 treatment and mutually expressed by both treatment doses in HeLa (Table 1) and CaSki ( Table 2) cells. These genes were subsequently grouped according to their respective biological functions. Amongst the top 20 genes, 17 genes were commonly regulated by MS17 in both cell lines (denoted as asterisks in Table 1 and Table 2). These included the up-regulation of CCL26, DEFB103B, IL1RL1, LY96, GCNT3, MMP10, MMP3, GADD45G and HSPA6 which were associated with immune response, metabolic processes, proteolysis, programmed cell death and unfolded protein response, and the down-regulation of TENM2, NEBL, KIFC1, CTDSP1, IGFBP5, LTBP1, NREP and MXD3 which were associated with cell adhesion, cytoskeletal organisation, phosphatase activity, signal transduction and transcription regulator activity. Of these 17 genes, 3 up-and 3 down-regulated genes were selected and validated, and the expression patterns determined from real-time PCR were consistent with the microarray results ( Figure  1).   HPV subtypes may suggest that targeting these genes could have therapeutic implications.

Discussion
The largest proportion of differentially up-regulated genes is associated with immune response. Many members in this cluster encode cytokines which are involved in immune system regulation and inflammation processes. Four highly up-regulated immune response-associated transcripts that were common to both cell lines included CCL26, followed by DEFB103B, IL1RL1 and LY96.
CCL26 encodes dendritic-cell specific chemokines that attract naive lymphocytes and neutrophils; DEFB103B codifies human β-defensin-3; IL1RL1 expresses the receptor for interleukin-1 and LY96 responds to toll-like receptor 4 on dendritic cells. They are respectively involved in the repression of cancer cell migration [20], growth [21,22] and the mediation of anticancer immunity [23]. The findings suggest that induction of an immune response, inhibition of cell migration and growth could be potential mechanisms by which MS17 exhibits anticancer activity on HeLa and CaSki cells. and MMP3 which degrade the extracellular matrix [25]. MMP10 is commonly implicated in inflammatory diseases and may be secreted by T-lymphocytes to assist in extracellular matrix degradation [26] during inflammation or an immune response. Cross-talk between matrix metalloproteinases suggests that they may possess proand anti-tumorigenic effects. Squamous cell carcinoma tumours in MMP3-null mice exhibited enhanced tumour progression and were inversely correlated with leukocyte infiltration [27]. Therefore abolished in approximately 50% of cervical cancer tumours [28,29].
Notably, its expression is up-regulated following exposure to curcumin treatment, DNA damage and genotoxic stress and induces cell cycle arrest, apoptosis and inhibits cell growth [30,31] and its induction could contribute to the apoptotic cell death mechanism of MS17 in treated HeLa and CaSki cells.
The heat shock gene HSPA6 which encodes the stress-inducible response, which also included HSPA6 as its top most up-regulated transcript [32]. Notably treatment of HeLa and leukaemia cells with curcumin and exposure of melanoma cells with curcumin analogue D6 induced the up-regulation of HSPA6, correlating strongly with cellular toxicity and was suggested to cause extreme endoplasmic reticulum stress resulting in apoptotic cell death [33][34][35]. This may thus reflect a similar mechanism by which MS17 up-regulates HSPA6 expression to modulate oxidative stress responses and trigger apoptosis induction in treated cells thus contributing to antitumorigenesis.
The expression of cell adhesion-associated TENM2 is downregulated in both cell lines following MS17 treatment. TENM2 encodes a transmembrane protein that enhances proliferation, promotes cell adhesion, facilitates microtubule organization [36] and is up-regulated by more than 250-fold in vincristine-resistant ovarian cancer cells [37]. The suppression of TENM2 by MS17 could disrupt adhesive contact between cells and mediate anti-proliferative activity in treated HeLa and CaSki cells.
Cytoskeleton organizing genes NEBL and KIFC1 are also downregulated by MS17 treatment in both cell lines. NEBL codifies nebulette, an actin protein involved in cytoskeletal organization.
The up-regulation of NEBL stimulates cell migration [38] while silencing of a related family member, Lasp1, in cell lines abrogates metastasis [39]. KIFC1 encodes microtubule motor proteins that function during spindle formation. The down-regulation of KIFC1 may destabilize spindle assembly, trigger cell cycle arrest and reduce cell viability [40]. Thus the repression of cytoskeletal organisation genes indicates the role of MS17 in modulating an anchorage network that is important for chromosome stability in mitosis.
The nuclear phosphatase expressed by CTDSP1 regulates gene expression by selective dephosphorylation of phosphoserine 5 within RNA polymerase Ⅱ and is commonly associated with the silencing of neuronal genes [41]. Its down-regulation by MS17 in cervical cancer cells suggests the potential modulation of transcriptional regulation to inhibit cell survival. IGFBP5, LTBP1 and NREP are grouped under signal transduction ontologies. IGFBP5 encodes IGF-binding proteins which are highly expressed in CIN tissues [42] and regulates the survival of cervical cancer cells by conferring it with antiapoptotic properties [43]. The down-regulation of IGFBP5 expression by MS17 suggests the reactivation of apoptosis in HeLa and CaSki cells which potentially contributes to cell death. LTBP1 encodes a latent TGFβ binding protein which contributes towards glioma cell malignancy while silencing is shown to reduce TGFβ activity [44] suggesting an important modulatory effect of LTBP1 over malignant tumour phenotypes. On the other hand, NREP encodes a neural regeneration protein but demonstrates RAC1-mediated involvement in glioma cell motility [45]. Hence the suppression of NREP by MS17 targets the disruption of actin cytoskeletal organization of HeLa and CaSki cells and impairs malignant cell proliferation and motility. Furthermore, MXD3 encodes a MAD family transcription factor which contributes to cell proliferation upon up-regulation but demonstrates anti-proliferative activity following MDX3-specific silencing [46] which may result in the suppression of cervical cancer proliferation following MS17 treatment.
In conclusion, the dose-dependent modulation of high ranking genes demonstrates the notable regulation of 17 genes that are common to both cell lines, suggesting the possibility that MS17

Conflict of interest statement
The authors declare no conflict of interest.