icb-1 Gene counteracts growth of ovarian cancer cell lines

Cancer Letters 335 (2013) 441–446

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icb-1 Gene counteracts growth of ovarian cancer cell lines Oliver Treeck a,⇑, Susanne Schüler a, Julia Häring a, Maciej Skrzypczak a,b, Claus Lattrich a, Olaf Ortmann a a b

Department of Obstetrics and Gynecology, University Medical Center Regensburg, Regensburg, Germany Second Department of Gynecology, Medical University of Lublin, Poland

a r t i c l e

i n f o

Article history: Received 24 October 2012 Received in revised form 7 February 2013 Accepted 27 February 2013

Keywords: Transcriptome analysis icb-1 Gene Gene knockdown Ovarian cancer Gene expression profiling

a b s t r a c t Human gene icb-1 has been originally identified to be involved in differentiation processes of cancer cells. To examine the function of icb-1 in ovarian cancer, we knocked down its expression in three ovarian cancer cell lines and performed microarray-based gene expression profiling with subsequent gene network modeling. Loss of icb-1 expression accelerated proliferation of SK-OV-3, OVCAR-3 and OAW-42 cells and led to upregulation of ovarian cancer biomarkers like KLK10 and CLDN16. Most of the upregulated genes were part of oncogenic pathways regulated by ERa or TNF. Our data suggest that icb-1 gene inhibits growth and progression of ovarian cancer cells. Ó 2013 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Human gene icb-1 (C1orf38, chromosome 1 open reading frame 38) has been originally cloned and described by our group to be involved in differentiation processes of gynecological cancer cells [1]. Recently, it has been proposed as member of a new metazoan gene family called THEMIS coding for cytosolic proteins binding to the Grb2 adaptor protein involved in receptor tyrosine kinase signaling [2]. Whereas macrophages and B-cells exhibit the highest expression levels of icb-1, this gene is also expressed in a variety of human tissues and cancer cell lines including ovarian cancer cells. We found icb-1 expression to be elevated after exposure of cancer cells to stimuli of cellular differentiation, like endometrial cancer cells to basement membrane or leukemia cells to retinoic acid [1,3]. Data of a recent study suggested icb-1 to be a component of signaling pathways mediating differentiating effects of vitamin D3 and ATRA [4]. These reports clearly suggested that icb-1 might be involved in such processes of cancer cells. Other studies demonstrating that icb-1 is an interferon-gamma responsive gene which in turn inhibited the effects of this cytokine on ovarian cancer cells showed that the view on icb-1 function had to be broadened [5]. This was confirmed by identification of an estrogen response element (ERE) in the promoter region of this gene regulating it in an ERa-dependent manner [6]. Recently we reported icb-1 gene to affect estrogen responsiveness of ovarian cancer cells [7]. The ⇑ Corresponding author. Address: Department of Obstetrics and Gynecology, Lab Molecular Oncology, University Medical Center Regensburg, Regensburg, Germany. Tel.: +49 941 7827520. E-mail address: [email protected] (O. Treeck). 0304-3835/$ - see front matter Ó 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.canlet.2013.02.049

proposed role of icb-1 in cancer cells was further corroborated by results suggesting that single nucleotide polymorphisms in this gene affect breast cancer susceptibility [8]. To further approach icb-1 function in ovarian cancer cells, in this study we knocked down icb-1 expression in three ovarian cancer cell lines and performed DNA microarray analyses to identify gene networks affected by this gene. 2. Materials and methods 2.1. Materials Phenol red-free DMEM culture medium was obtained from Invitrogen (Karlsruhe, Germany), FCS was purchased from PAA (Pasching, Austria). SK-OV-3, OVCAR-3 and OAW-42 ovarian cancer cells were obtained from American Type Culture Collection (Manassas, USA). RNeasy Mini Kit, RNase Free DNase Set and Quantitect SYBR Green PCR Kit were obtained from Qiagen (Hilden, Germany). PCR primers were synthesized at Metabion (Planegg–Martinsried, Germany). Transfectin reagent was obtained from BioRad (Hercules, USA). Platinum Pfx Polymerase and OptiMEM medium were purchased at Invitrogen (Karlsruhe, Germany). Sure Silencing shRNA plasmid for human icb-1 (C1orf38) gene was purchased from SABiosciences, Frederick, USA. 2.2. Cell culture and proliferation assays Ovarian cancer cell lines were maintained in DMEM/F12 medium supplemented with 10% FCS. Cells were cultured with 5% CO2 at 37 °C in a humidified incubator. Generation of cell lines with stable icb-1 knockdown (icb-1 KD) and control cell lines by transfection with icb-1 shRNA or negative control shRNA plasmids was described previously [7]. For cell proliferation assays, cells cultured in DMEM/ F12 supplemented with 10% FBS were seeded in 96-well plates in triplicates (1000 cell/well). On days 0, 3, 5 and 7 relative numbers of viable cells were measured using the fluorimetrical, resazurin-based Cell Titer Blue assay (Promega) according to the manufacturer’s instructions at 560Ex/590Em nm in a Victor3 multilabel

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counter (PerkinElmer, Germany). Cell growth was expressed as percentage of day 0. Growth data were statistically analyzed by the Kruskal–Wallis one-way analysis of variance.

2.3. Reverse transcription and qPCR Three total RNA preparations from each tumor cell line were performed by means of the SV Total RNA Isolation System (Promega) according to the manufacturer’s instructions. From 0,6 lg total RNA, two independent cDNAs were synthesized using 100 U M-MLV-P reverse transcriptase (Promega), 2,5 mM dNTP mixture and 50 pM random primers (Invitrogen). For real time PCR detection of gene expression in an intron-spanning manner (primer sequences in Table 1), 2 ll cDNA were amplified using Light CyclerÒFastStart DNA master mix SYBR Green I and the LightCyler 2.0 PCR device (Roche Diagnostics, Mannheim, Germany). The PCR program was 95 °C for 15 min, followed by 45 PCR cycles (95 °C for 10 s, 56 °C for 30 s, 72 °C for 30 s) and a final extension for 5 min at 72 °C, followed by a standard melting curve analysis. In all RT-PCR experiments, a 190 bp b-actin fragment was amplified as reference gene using intron-spanning primers actin-2573 and actin-2876. Data were analyzed using the comparative DDCT method [9] calculating the difference between the threshold cycle (CT) values of the target and reference gene of each sample and then comparing the resulting DCT values between different samples. In these experiments, mRNA not subjected to reverse transcription was used as a negative control to distinguish cDNA and vector or genomic DNA amplification.

2.4. Western blot analysis SK-OV-3 (icb-1 KD) and SK-OV-3 (control) cells were lysed in RIPA buffer (1% (v/ v) Igepal CA-630, 0.5% (w/v) sodium deoxycholate, 0.1% (w/v) sodium dodecyl sulfate (SDS) in phosphate-buffered solution (PBS) containing aprotonin and sodium orthovanadate. Aliquots containing 10 lg of protein were resolved by 10% (w/v) SDS–polyacrylamide gel electrophoresis, followed by electrotransfer to a PVDF hybond (Amersham, UK) membrane. Immunodetection was carried out using CLDN16 antibody (ab42482, Abcam, Germany) in a dilution of 1:2000 or b-actin antibody (8226, Abcam, Germany) diluted 1:5000 in PBS containing 5% skim milk (w/v) followed by horseradish peroxidase conjugated secondary antibody (1:20,000) which was detected using chemiluminescence (ECL) system (Amersham, Buckinghamshire, UK). The Western blot results from three independent protein isolations were densitometrically analyzed and expressed in percentage of cell transfected with negative control shRNA.

2.5. GeneChip™ microarray assay Processing of four RNA samples (two biological replicates from control-shRNA or icb-1-shRNA transfected SK-OV-3 cells) was performed at the local Affymetrix Service Provider and Genomics Core Facility, ‘‘KFB – Center of Excellence for Fluorescent Bioanalytics’’ (Regensburg, Germany; http://www.kfb-regensburg.de). Sample preparation for microarray hybridization was carried out as described in the Affymetrix GeneChipÒ Whole Transcript (WT) Sense Target Labeling Assay manual. 300 ng of total RNA were used to generate double-stranded cDNA, omitting the initial ribosomal RNA (rRNA) reduction procedure. Subsequently synthesized cRNA (WT cDNA Synthesis and Amplification Kit, Affymetrix) was purified and reverse transcribed into single-stranded (ss) DNA. After purification, the ssDNA was fragmented using a combination of uracil DNA glycosylase (UDG) and apurinic/apyrimidinic endonuclease 1 (APE 1). Fragmented DNA was labeled with biotin (WT Terminal Labeling Kit, Affymetrix), and 2.3 lg DNA were hybridized to the GeneChip Human Gene 1.0 ST Array (Affymetrix) for 16 h at 45 °C in a rotating chamber. Hybridized arrays were washed and stained in an Affymetrix Washing Station FS450 using preformulated solutions (Hyb, Wash & Stain Kit, Affymetrix), and the fluorescent signals were measured with an Affymetrix GeneChipÒ Scanner 3000-7G.

Table 1 Sequences of PCR primers used for validation of selected microarray data. Gene name

Sequence (50 –30 )

CLDN16

GGCCTCTGGTGGGAATGCGT CAGCTTCAAGGGATGCTCCGCA AAAAGGGGGCGTTTCGGGCA ATGGCCAGGATCTGCGTGGG GACTGGTCGGCAGTCAAGCCAT ACCCCGGGTCTCATCTCGGG CTCCAGCCCAGCACCTGCG ATCAGGGGCAGTGGGCTGCT GCACCCTGCTCGTCACTTGGG ACTCCACGGGCTGCTGCTGGAA

KLK10 MAGEB2 SLC34A2 CCNA1

Amplicon size (bp) 93 108 95 124 145

2.6. Microarray data analysis Summarized probe signals were created by using the RMA algorithm in the Affymetrix GeneChip Expression Console Software and exported into Microsoft Excel. Data was then analyzed using Ingenuity IPA Software (Ingenuity Systems, Stanford, USA) and the GeneMANIA prediction server [10]. Genes with more than 2-fold changed mRNA levels after icb-1 knockdown in both biological replicates were considered to be differentially expressed and were included in the analyses.

3. Results 3.1. Growth of ovarian cancer cell lines after knockdown of icb-1 gene Stable knockdown of icb-1 expression in ovarian cancer cells by transfection with icb-1 shRNA plasmids was performed as described previously [7]. The selected clones retained between 7% and 12% of icb-1 mRNA expression (Fig. 1a). First we analyzed the effect of icb-1 knockdown on growth of the ovarian cancer cell lines SK-OV-3, OVCAR-3 and OAW-42 [11–13]. Compared to cells transfected with negative control shRNA, all cell lines expressing icb-1 shRNA exhibited an increased cell proliferation (Fig. 1b). This effect was most pronounced after 5 and 7 days of culture of the cell lines OAW-42 and SK-OV-3 (p < 0.01). With regard to OVCAR-3 cells, a statistically significant growth increase was observed only after 7 days of culture (p < 0.01). 3.2. Transcriptome analysis Analyzing the effect of icb-1 knockdown on the transcriptome of SK-OV-3 cells by means of GeneChip Human Gene 1.0 ST DNA microarrays (Affymetrix), besides icb-1 (C1ORF38) we found 94 differentially expressed genes exhibiting more than 2-fold changes, 72 of which were up- and 22 downregulated (Suppl. 1). 18 genes were more than 2.5-fold induced, transcript levels of five genes, besides icb-1 itself, were decreased at least 2.5-fold (Table 2). To verify the DNA microarray results, we performed qPCR analyses of five selected genes (Fig. 2a). We chose the genes MAGEB2, CLDN16 and SLC34A2 due to their status as top regulated genes. Additionally, we chose the 3.55-fold upregulated gene KLK10 due to its known role in ovarian cancer and CCNA1 gene due to its function as cell cycle regulator. Upregulation of mRNA levels of MAGEB2, KLK10, CCNA1 and CLDN16 gene and decrease of SLC34A2 transcript levels in SK-OV-3 (icb-1 KD) cells was confirmed in these experiments. CLDN16 and KLK10 transcript levels were about 6fold elevated after knockdown of icb-1 gene, whereas the induction factor of CCNA1 was 2.6-fold and MAGEB2 even was upregulated 22-fold. To verify the observed gene expression changes on the protein level, we additionally performed Western blot analysis of one representative gene. In these experiments, we observed CLDN16 protein levels to be significantly increased in SK-OV-3 (icb-1 KD) cells (Fig. 2b). 3.3. Network analysis Using Ingenuity Pathway Analysis Software (IPA, Ingenuity Systems, Stanford, USA), we analyzed the obtained microarray data. IPA Software allowed identification of gene networks affected by knockdown of icb-1 gene in SK-OV-3 cells. We observed various ovarian cancer biomarkers or other cancer-related genes to be overexpressed in SK-OV-3 (icb-1 KD cells). The gene exhibiting the strongest induction after icb-1 knockdown, melanoma antigen family B2 (MAGEB2, 8.34-fold) as well as kallikrein-related peptidase 10 (KLK10, 3.55-fold) and 6 further genes being induced more than 2-fold including cyclin A1 (CCNA1), have been previously

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On the other hand, we identified a second set of upregulated genes primarily as targets of tumor necrosis factor alpha (TNF), partially by interaction with a network of p38 MAP kinase, caspase 1 (CASP1) and thrombin (F2) (Fig. 4). Prominent genes of this second network were claudin 16 (CLDN16, 5.89-fold), carbohydrate sulfotransferase 9 (CHST9, 4.91-fold), pregnancy specific beta-1glycoprotein 3 (PSG3, 3.10-fold) or cadherin 13 (CDH13, 2.57-fold) [19–22].

4. Discussion

Fig. 1. Effect of an icb-1 knockdown on growth of ovarian cancer cell lines. (a) Icb-1 mRNA expression after transfection with icb-1 shRNA (icb-1 KD) or with negative control shRNA (con) [7]. (b) Indicated cell lines were seeded in DMEM/F12 containing 10% FCS in triplicates in 96-well plates (1000 cells/well) and were cultured for 7 days. Shown are the relative cell numbers in percent of day 0, measured by means of the resazurin-based CTB assay as described in the materials and methods section (n = 4).  p < 0.01 vs. control cells.

reported as estrogen responsive genes, mainly in studies on breast cancer cells (Fig. 3), (Suppl. 1) [14–18].

Knockdown of icb-1 gene accelerated growth of three ovarian cancer cell lines and elevated expression of various cancer-related genes. Two of these genes previously have been reported as biomarkers for ovarian cancer. The one exhibiting the highest induction factor was claudin 16 gene (CLDN16, 5.89-fold upregulated), coding for a tight junction protein. Demonstration of elevated CLDN16 protein levels after icb-1 knockdown validated our mRNA data gained by microarray and qRT-PCR analysis. CLDN16 has previously been described to be a human ovarian cancer specific transcript (HOST), being only rarely expressed in normal ovary or in nonovarian cancers [23]. A recent study comparing gene expression profiles of primary and recurrent ovarian cancer found CLDN16 to be the top elevated gene in recurrent serous tumors [24]. The tight junction protein encoded by CLDN16 gene plays important roles in paracellular cation transport and ionic permeability of various epithelia [25]. However, its role in ovarian carcinogenesis remains unclear. Other members of the family, CLDN3 and CLDN4, are frequently overexpressed in ovarian cancer and have been shown to increase the metastatic potential of ovarian cancer cells [26]. The second upregulated ovarian cancer-related gene, kallikreinrelated peptidase 10 (previous name kallikrein 10) (KLK10, 3.55fold), is known to be overexpressed in ovarian cancer and to be a predictor of poor disease outcome in women with late-stage ovarian cancer [27–33]. Thus, upregulation of CLDN16 and KLK10 gene clearly suggests that icb-1 knockdown led to further progression of the oncogenic transformation of this ovarian cancer cell line. The top upregulated gene, melanoma antigen family B, 2 (MAGEB2, 8.34-fold), has previously been reported to be exclusively expressed in tumor cells of different origin, including ovarian cancer cells, and thus is a highly specific cancer marker [34]. The genes of the MAGE families code for tumor specific antigens recognized by autologous cytolytic T lymphocytes [35]. Thus, the strong upregulation of MAGEB2 after icb-1 knockdown can be considered as another evidence for the tumor suppressor function of this gene in ovarian cancer. With regard to the downregulated genes, the solute carrier family 34 member 2 (SLC34A2) gene previously was reported to be higher expressed in well-differentiated endometrioid and papillary serous ovarian carcinomas compared to low-differentiated endometrioid carcinomas [36]. Thus, its strong downregulation observed in SK-OV-3 (icb-1 KD) cells might be another example for oncogenic actions triggered by knockdown of icb-1 gene in ovarian cancer cells. The observed induction of many cancer-related genes including cell cycle regulator cyclin A1 is in line with our previous study reporting that knockdown of icb-1 in SK-OV-3 cells accelerated growth of this cell line cultured in serum-free medium both in an estrogen-dependent and independent manner [7]. Microarray analysis now allowed identification of estrogen-inducible genes like KLK10, MAGEB2 or cyclin A1 in SK-OV-3 (icb KD) cells, corroborating previous data demonstrating transformation of this cell line from an hormone-independent to an estrogen-responsive phenotype [7].

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Table 2 Gene expression after knockdown of icb-1 expression in SK-OV-3 ovarian cancer cells as assessed on the mRNA level by means of DNA Microarray analysis (Affymetrix chip). Shown are all more than 2.5-fold up- and downregulated genes and additional genes exhibiting more than 2-fold regulation being mentioned in the text. Gene symbol

Gene name

Regulation (-fold)

Upregulated genes MAGEB2 CLDN16 SNORD25 CHST9 APBB1IP SRGN KLK10 TMTC1 MYEF2 PSG3 APOBEC3B ZNF257 GPAM SMR3B CD200 TNNT2 NUF2 CDH13 CCNA1

Melanoma antigen family B, 2 Claudin 16 Small nucleolar RNA, C/D box 25 Carbohydrate (N-acetylgalactosamine 4–0) sulfotransferase 9 Amyloid beta (A4) precursor protein-binding, family B, member 1 interact. protein Serglycin Kallikrein-related peptidase 10 Transmembrane and tetratricopeptide repeat containing 1 Myelin expression factor 2 Pregnancy specific beta-1-glycoprotein 3 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3B Zinc finger protein 257 Glycerol-3-phosphate acyltransferase, mitochondrial Submaxillary gland androgen regulated protein 3B CD200 molecule Troponin T type 2 NUF2, NDC80 kinetochore complex component, homolog (S. cerevisiae) Cadherin 13, H-cadherin Cyclin A1

8.34 5.89 5.52 4.91 4.29 3.86 3.55 3.51 3.37 3.10 3.04 3.03 2.92 2.85 2.78 2.70 2.57 2.57 2.19

Downregulated genes SLC4A4 CDH6 NELL2 ZNF716 SLC34A2

Solute carrier family 4, sodium bicarbonate cotransporter, member 4 Cadherin 6, type 2, K-cadherin (fetal kidney) NEL-like 2 (chicken) Zinc finger protein 716 Solute carrier family 34 (sodium phosphate), member 2

2.54 2.54 3.02 3.49 5.40

Fig. 2. Validation of microarray data by means of RT-qPCR and Western blot analysis. (a) Transcript levels of the indicated genes in SK-OV-3 (icb-1 KD) cells are compared to expression in control-transfected cells, here defined as 100%. Black bars: SK-OV-3 (icb-1 KD); white bars: SK-OV-3 (control) cells. Three independent mRNAs, each represented by two cDNAs, have been analyzed.  vs. negative control shRNA. (b) Western blot analysis detecting CLDN16 protein in SK-OV-3 cells before and after knockdown of icb-1 gene. 10 lg protein were resolved by 10% SDS–PAGE and gele was processed as described in the materials and methods section. Lower panel: densitometric quantification of three independent experiments, values are expressed as percent of the CLDN16/b-actin ratio in cells expressing negative control shRNA.  vs. negative control (con).

Software-based pathway analysis predicted tumor necrosis factor (TNF) and NFkB to be key molecules of the second network of induced cancer-related genes including CLDN16 and CHST9 [19– 22]. The pleiotropic cytokine TNF is able to exert antitumoral or cancer-promoting effects by inducing growth, invasion and metastasis of tumor cells [37]. Activation of TNF signaling in SK-OV-3 (icb-1 KD) cells, as predicted from upregulation of genes directly or indirectly responsive to TNF, is in line with a previous study we performed on breast cancer cells demonstrating mutual regulation of icb-1 and TNF gene expression [38]. The question remains, why no decrease of icb-1 expression in ovarian cancer tissue was observed in previous large-scale expression profiling studies on ovarian cancer samples. Icb-1 expression levels in leukocytes are known to be more than 100-fold higher

than in cancer cells of epithelial origin [1]. Thus, icb-1 gene expression alterations in ovarian cancer tissue samples, as examined previously on total RNA by DNA microarray technology, probably have been masked by predominant leukocyte expression. Actually, recent data from our lab (unpublished results) demonstrated that icb-1 expression in breast cancer tissue samples most significantly correlated with macrophage marker CD68 (Spearman’s rho 0.734, p < 0.0001). Thus, as long as no reliable antibodies for detection of icb-1 protein in ovarian cancer tissue exist, which will allow discrimination between leukocyte and cancer cell expression, studies on the cell line level are the best alternative. In conclusion, the results of this study clearly suggest icb-1 gene to inhibit growth of ovarian cancer cell lines. Whether the same is true in ovarian cancer tissue, has to be elucidated in further studies.

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Fig. 3. Estrogen-responsive genes upregulated in SK-OV-3 (icb-1 KD) cells. Arrows indicate a known stimulatory effect of 17-b estradiol (E2) on gene expression, primarily from breast cancer cell studies [14–18].

Fig. 4. Network of upregulated genes in SK-OV-3 (icb-1 KD) cells known to be directly or indirectly regulated by tumor necrosis factor (TNF). Arrows indicate a known stimulatory effect on gene expression. Black symbols: upregulated genes; grey symbols: predicted intermediate genes; white boxes: predicted regulatory key molecules. Prediction by IPA Software (Ingenuity Pathway Analysis, Ingenuity Systems, Stanford, USA).

Conflict of interest All authors state that they have nothing to declare. Acknowledgement We would like to thank Helena Lowack for expert technical assistance. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.canlet.2013.02. 049. References [1] O. Treeck, E. Strunck, G. Vollmer, A novel basement membrane-induced gene identified in the human endometrial adenocarcinoma cell line HEC1B, FEBS Letters 425 (1998) 426–430.

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