Generation of PTEN‑knockout (‑/‑) murine prostate cancer cells using the CRISPR/Cas9 system and comprehensive gene expression profiling
- Authors:
- Published online on: September 5, 2018 https://doi.org/10.3892/or.2018.6683
- Pages: 2455-2466
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Copyright: © Takao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Phosphatase and tensin homolog (PTEN) is a tumor suppressor and a lipid phosphatase that catalyzes dephosphorylation of phosphatidylinositol 3,4,5-trisphosphate. PTEN has a high frequency of mutations in various cancers including prostate cancer and glioblastoma. PTEN alterations are observed in approximately half of all malignant tumors and correlate with increased RAC-alpha serine/threonine-protein (AKT) phosphorylation and initiation of downstream targets that modulate a wide range of cellular processes associated with the progression of tumor growth and survival (1–8).
To investigate the function of PTEN, various knockout mice have been prepared and the effect of PTEN deficiency examined (9). The authors also established a conditional PTEN-deficient mouse model of prostate cancer driven by the PSA-Cre promoter and demonstrated its utility in various experimental settings (10–13). To develop better treatment strategies requires a deeper understanding the cellular and molecular mechanisms of PTEN deficiency. However, autochthonous tumors are highly heterogeneous and are composed of a complex tumor microenvironment that consists of various cell types including epithelial cancer cells, stromal fibroblasts, immune endothelial and blood cells, in addition to other contaminants, all of which contribute to the molecular characterization of PTEN deficiency. Although small interfering RNA methodology enables us to induce PTEN-deficiency at the protein level (14), researchers often take into consideration the fact that gene expression still remains at a certain level even under conditions of gene knockdown.
Next-generation genome editing strategies have been developed and are currently considered some of the best technological tools to most efficiently characterize gene function (15). The present study generated an isogenic PTEN-deficient cell clone from a parental mouse prostate cancer cell line using the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) system and performed comprehensive gene expression profiling analyses to identify its impact on unique genes associated with crucial roles in cellular processes, including cancer development and immunity.
Materials and methods
Cell lines
The mouse prostate cancer cell line, 2924V, which expresses wild-type PTEN was used in the present study. This cell line was established from a prostate tumor originating from a 57 week-old PSACre;PtenloxP/loxP conditional knockout mouse (10). Cells were cultured at 37°C and 5% CO2 in RPMI-1640 medium (Sigma-Aldrich; Merck KGaA, Darmstadt, Germany) supplemented with 10% inactivated fetal bovine serum (HyClone; GE Healthcare Life Sciences, Logan, UT, USA), 100 IU/ml penicillin, and 100 µg/ml streptomycin.
PTEN-knockout using the CRISPR/Cas9 system
The CRISPR/Cas9 system was used to disrupt the expression of the PTEN gene as described previously (16). pSpCas9(BB)-2A-Puro (PX459) was a gift from Feng Zhang (Broad Institute of MIT, Harvard, MA, USA; Addgene plasmid #48139; 15). Briefly, a single guide RNA (sgRNA) sequence was selected using Optimized CRISPR Design (http://crispr.mit.edu/). The sgRNA sequence targeting PTEN was 5′-GCTAACGATCTCTTTGATGA-3′. The plasmid expressing human Cas9 and the PTEN sgRNA was prepared by ligating oligonucleotides into the BbsI site of PX459 (Pten/PX459). To establish a PTEN knockout clone with a one-nucleotide deletion, 2924V cells (1×106 cells/dish) were seeded in a 10-cm dish. Cells were then transfected with 10 µg of PTEN/PX459 using Lipofectamine® 3000 (Thermo Fisher Scientific, Inc., Waltham, MA, USA). Antibiotic selection (puromycin; 2 µg/ml) was begun 72 h after transfection and continued for at least 3 days. A single clone was selected, expanded, and then used for biological assays. For sequence analysis of the PTEN gene, the following primer set was used: 5′-CGCTAATCCAGTGTACAGTA-3′ and 5′-CTGCGAGGATTATCCGTCTT-3′.
Morphology
The cells were plated in a 12-well plate. After 24 h, the cell morphology was digitally photographed at ×100 magnification using an inverted microscope system (IX73: Olympus Corporation, Tokyo, Japan).
MTT assay
Briefly, parent cells, mock cells, and ΔPTEN were seeded (5×103 cells/well) into a 96-well plate. Subsequently, 10-µl MTT solution (5 µg/ml; Sigma-Aldrich; Merck KGaA, Darmstadt, Germany) was added to each well and cells were incubated at 37°C in 5% CO2 for 4 h. Next, cell lysis buffer [10% sodium dodecyl sulfate (SDS) in 0.01 M HCL] was added to the wells to dissolve the formazan crystals produced by MTT. The optical density (550 nm) at each time point (day 0, 1, 3, 5, and 7) is presented as the mean ± standard error of the mean (n=6).
Colony formation assay
Colony formation assays were performed by seeding 500 cells of each line in 12-well plates. After 14 days, cells were fixed/stained with 3.7% formaldehyde (Wako Pure Chemical Industries, Ltd., Osaka, Japan) containing 0.2 % (wt/vol) crystal violet (Sigma-Aldrich; Merck KGaA) at room temperature and number of colonies were imaged and counted manually. Bar graphs represent the number of stained colonies. Data are presented as the mean ± standard error of the mean (n=3).
Western blotting
Cells were lysed in radioimmunoprecipitation assay buffer (Wako Pure Chemical Industries, Ltd.) supplemented with a protease inhibitor cocktail (Roche Applied Science, Mannheim, Germany) for 30 min at 4°C. Insoluble material was removed by centrifugation at 15,400 × g for 10 min at 4°C. Protein content was determined using a DC protein assay kit (5000112JA; Bio-Rad Laboratories, Inc., Hercules, CA, USA) according to the manufacturer's protocol. Protein lysates were mixed with loading buffer and boiled for 5 min. A total of 10 µg protein was separated by electrophoresis on 10% PAGE gels (TEFCO, Tokyo, Japan). Proteins were then transferred to Immobilon-P membranes (EMD Millipore, Billerica, MA, USA) and blocked in 5% skim milk in Tris-buffered saline with 0.01% Tween-20 (TBS-T) for 1 h at room temperature. All antibodies were purchased from Cell Signaling Technology, Inc. (Danvers, MA, USA). Membranes were incubated with primary antibodies [PTEN, 1:3,000, #9559; AKT1, 1:1,000, #9272; phosphorylated (p)-AKT, 1:1,000, #9271; phosphorylated (p)-Rb, 1:3,000, #9307; cyclin D1, 1:3,000, #2922; CDC2, 1:3,000, #9112; CDK2, 1:3,000, #2546; CDK4, 1:3,000, #2906; CDK6, 1:1,000, #3136; CDK7, 1:1,000, #2916 and GAPDH 1:5,000, #5174] overnight at 4°C. After three washes with TBS-T, membranes were incubated with anti-mouse, #7076/rabbit, #7074, horseradish peroxidase (HRP)-conjugated secondary antibody (1:5,000) for 1 h at room temperature followed by a final wash. Proteins were detected by applying ImmunoStar LD (Wako Pure Chemical Industries, Ltd.) to the membrane and signals were quantified using ImageQuant LAS-4000 (GE Healthcare Life Sciences, Little Chalfont, UK) according to the manufacturer's protocol.
RNA extraction
For microarray analysis, reverse transcription (RT)-polymerase chain reaction (PCR) and quantitative (q) PCR, total RNA was extracted from cell lines with the NucleoSpin RNA kit (Macherey-Nagel, Düren, Germany) according to the manufacturer's protocol. RNA extraction for miRNA analysis was performed with the MiRNeasy Mini Kit (Qiagen GmbH, Hilden, Germany) according to the manufacturer's protocol.
Microarray analysis
Expression profiling analysis of mRNA was performed using the Agilent Oligo Microarray Kit (8×60 K; G4852B; Agilent Technologies, Inc., Santa Clara, CA, USA). Nucleic acid labeling and hybridization were performed with the One-Color Microarray-Based Gene Expression Analysis kit (Agilent Technologies, Inc.) according to the manufacturer's protocol. Briefly, 100 ng of total RNA was amplified and labeled using the Low Input Quick Amp Labeling Kit. After labeling, RNA was purified with RNeasy Mini Kit (Qiagen GmbH). The RNA fragmentation reaction was performed at 60°C for 30 min, after which the samples were collected on ice for 1 min, and 2X Hi-RPM Hybridization Buffer was added to stop the reaction. Samples were further mixed, centrifuged at 13,000 × g for 1 min at room temperature, placed on ice, and then loaded onto the array. The arrays were hybridized at 65°C for 17 h. The microarray slides were then washed with Gene Expression Wash Buffers I and II and scanned with the Agilent Microarray Scanner-G2505C (Agilent Technologies, Inc.). Feature Extraction Software Version 11.0.1.1 (Agilent Technologies, Inc.) was used to extract and analyze the signals and signal intensities were normalized as previously described (17).
The background signals were normalized and microarray expression data were rank-ordered according to the expression levels of the ΔPTEN/mock cells. Differentially expressed genes between ΔPTEN and mock cells were considered relevant if there was ≥10-fold change.
Functional enrichment analyses of differentially expressed genes were carried out using the Panther web-based tool (18).
To confirm gene expression, RT-qPCR was performed using the ABI 7900 HT Fast Real-Time PCR System (Applied Biosystems; Thermo Fisher Scientific, Inc.) and calculated using the 2−ΔΔCq method (19). Total RNA from the three cell lines were converted to cDNA with the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems; Thermo Fisher Scientific, Inc.) according to the manufacturer's protocol. The Tet methylcytosine dioxygenase 1 (Tet1), twist family BHLH transcription factor 2 (Twist2), arginase 1 (Arg1), C-fos induced growth factor (Figf), Wingless-Type MMTV Integration Site Family, Member 3 (Wnt3), prostaglandin reductase 1 (Ptgr1), polypeptide N-acetylgalactosaminyltransferase 14 (Galnt14), and GAPDH (reference) genes were amplified and detected using SYBR-Green (Applied Biosystems; Thermo Fisher Scientific, Inc.). PCR reactions were prepared in a final volume of 20 µl, with 17.6 µl of SYBR-Green PCR Master Mix (Applied Biosystems; Thermo Fisher Scientific, Inc.), 2.0 µl of DNA, and 0.2 µl each of the 10 pmol/µl forward and reverse primers. Thermal cycler settings included DNA polymerase activation at 95°C for 2 min followed by 55 cycles of denaturation at 95°C for 15 sec, annealing at 60°C for 15 sec, and extension at 70°C for 20 sec. Each measurement was performed in triplicate. The quality of the PCR products was monitored by using the post-PCR melt-curve analysis.
In order to visualize PCR Products, PCR was carried out changing the number of cycles to 30 cycles. The PCR products were electrophoresed in 1.5% agarose gel, and stained with GelRed Nucleic Acid Stain (41003-T; Biotium, Inc., Fremont, CA, USA) and photographed. Primer sequences are listed in Table I.
miRNA array analysis
miRNA profiling analysis was performed using the Agilent Mouse miRNA kit (8×60 K; G4872A-070155). miRNA labeling, hybridization, and washing were carried out according to the manufacturer's protocol (Agilent Technologies, Inc.). Hybridized microarrays were scanned with a DNA microarray scanner (Agilent Microarray Scanner; G2505C) and features were extracted using the Agilent Feature Extraction image analysis tool (version 11.0.1.1). Briefly, average values of the spots of each miRNA were background-subtracted and subjected to further analysis. miRNA array expression data were rank-ordered according to the expression levels of the ΔPTEN/mock cells. To confirm miRNA expression level, RT-qPCR was performed. Total RNA from the three cell lines were converted to cDNA with the Taqman MicroRNA Reverse Transcription Kit (Applied Biosystems) according to the manufacturer's protocol. Realtime PCR was performed using Taqman MicroRNA Assays (has-miR-210, RT:000512 and snoRNA234; RT:001234 as control; Applied Biosystems) according to the manufacturer's protocol.
Statistical analysis
At least three replications per experiment and three independent experiments were performed. The results are expressed as the mean ± standard error of the mean. Independent-samples Student's t-test and one-way analysis of variance, followed by the least significant difference post-hoc test were performed to analyze data using JMP Ver.13.2.1 (SAS Institute Inc; Tokyo, Japan). P<0.05 was considered to indicate a statistically significant difference (*P<0.05; **P<0.01; ***P<0.001).
Results
Establishment of PTEN-knockout cells using the CRISPR/Cas9 System
The present study performed genome editing (targeting sequence presented in Fig. 1A) using the CRISPR/Cas9 system and obtained multiple clones (ΔPTEN). Fig. 1B and C reveal DNA sequencing of target sites in the resultant clones. These results demonstrated that targeting PTEN with the CRISPR/Cas9 system effectively generated mutant-PTEN clones. Next, the present study assessed the effects of PTEN inactivation in the resulting clones. Overall, the general appearance was similar between parental, mock, and ΔPTEN cells; however, marginal differences were observed in the morphological appearance of ΔPTEN cells such as heterogeneity of the cell shape (Fig. 2).
Using western blot analysis, the present study verified the effective knockout of PTEN in ΔPTEN cells. Fig. 3 shows that the expression of PTEN was present in the parental strain and mock-transfected cells but was effectively downregulated in ΔPTEN cells. Accordingly, Akt phosphorylation levels increased in the absence of PTEN. Activation of the PI3K/Akt pathway promotes the cellular proliferation of transformed cells; thus, the expression of molecules involved in proliferation was then assessed. In ΔPTEN cells, the upregulation of Akt phosphorylation was associated with the elevated expression of cyclin D1, cyclin dependent kinase (CDK)4, and decreased expression of CDK7. In addition, increased phosphorylation of the retinoblastoma tumor-suppressor protein (RB) was observed, a known regulator of cellular proliferation, in ΔPTEN cells. As the expression of molecules involved in the cell cycle was demonstrated to be enhanced in ΔPTEN cells, the present study then assessed the effects of PTEN inactivation on cell viability. Fig. 4 shows that the inactivation of the PTEN function in ΔPTEN cells results in increased cell growth and enhanced colony formation.
Microarray and miRNA array analysis of PTEN-knockout cells
Using gene microarrays, the present study assessed changes in gene expression following the loss of the PTEN function and focused on genes that were differentially expressed in ΔPTEN cells relative to mock-transfected cells and the parental strain (Fig. 5). Overall, 111 genes were upregulated by at least 10-fold, including one with a 74-fold increase in ΔPTEN cells (Table II). In addition, 23 genes were identified to be substantially downregulated by ≥10-fold, one with a 139-fold decrease (Table III).
Table II.Genes that are upregulated 10-fold or more in phosphatase and tensin homolog knockout cells. |
Table III.Genes that are downregulated 10-fold or more in phosphatase and tensin homolog knockout cells. |
The mRNA expression levels of Tet1, Twist2, Arg1, Figf, Wnt3, Ptgr1, and Galnt14 were measured by RT-qPCR to confirm the results of the microarray analysis (Fig. 6A). The expression patterns of the RT-PCR analysis were parallel to those in the microarray, thereby verifying the results (Fig. 6B).
Next, the present study performed gene enrichment profiling to gain better insight into the genes differentially expressed after PTEN-knockout in the model. The analysis using the Panther annotation database revealed that 64 of the 111 upregulated genes corresponded to 15 pathways (Fig. 7).
Furthermore, the expression of non-coding RNAs, in particular miRNAs, were assessed to further delve into the impact of PTEN inactivation and altered gene expression. Notably, the miRNA expression analysis in this study revealed that only the mmu-miR-210-3p expression increased (≥10-fold) due to PTEN-knockout. Corroborating our initial observation, the RT-qPCR analysis presented an evident increase of mmu-miR-210-3p in ΔPTEN cells compared with the parental strain and mock-transfected cells (Fig. 8).
Discussion
The present study investigated the changes in carcinogenesis-associated genes caused by PTEN deficiency in a mouse prostate cancer model. A PTEN-deficient mouse prostate cancer isogenic cell line was established using the CRISPR/Cas9 system. The phosphorylation of Akt and the expression of cyclin D1 were elevated in PTEN-deficient cells. Although the expression of CDK7 wa srevealed to be decreased, the reason remains unknown. The expression levels of cyclinD1 and CDK4 that increased as demonstrated by western blotting, were not recognized as much different from that of parental cell or mock cell in microarray analysis. The reason for this increase in the expression currently remains unclear. Furthermore, microarray and miRNA arrays were used to assess the changes in gene expression. These results suggested that the PTEN expression is essential for normal gene expression.
The present study observed alterations in the expression levels of various genes due to the loss of the PTEN gene, which may be attributed to an increase in the expression of TET1. Demethylation is increased in several genes due to the enhanced expression of TET1, a dioxygenase that catalyzes the conversion of the modified genomic base 5-methylcytosine (5 mc) into 5-hydroxymethylcytosine (5hmc). Reportedly, Nanog is an example of a gene induced by Tet1 expression. Not only does Nanog have a role in the maintenance of mouse ES cells (20), but also in the maintenance of cancer stem cells, suppression of apoptosis, promotion of cancer progression and metastasis, and angiogenesis (21). These findings suggest that PTEN deficiency drives TET1 and TET1-gene regulation during carcinogenesis; however, the underlying reasons for an increase in the TET1 expression in PTEN deficiency remain unclear.
In this model, we established the upregulation of Twist2, Figf, Wnt3, and Arg1 in response to Pten-knockout; these genes play vital roles in the development and progression of cancer and promote the immune suppression in the surrounding tumor microenvironment.
Twist2, a member of the basic helix-loop-helix (BHLH) transcription factors, is overexpressed in several cancer types. Previously, studies have reported the correlation of Twist expression with head and neck squamous cell carcinomas, cervical carcinomas, and ovarian cancer (22–24). Yang et al reported that hypoxia inducible factor-1 (HIF-1) promotes EMT through direct regulation of Twist expression (25). Twist is a master regulator of gastrulation and mesoderm specification and is implicated to be essential in the mediation of cancer metastasis (25). In this study, the expression of Twist was enhanced by the absence of functional PTEN, suggesting transcriptional regulation by mechanisms mediated by proteins other than HIF-1.
Figf, also termed vascular endothelial growth factor (VEGF)-D is a member of the platelet-derived growth factor (PDGF)/VEGF family and is active in angiogenesis and endothelial cell growth. Reportedly, the normal VEGF-D expression is detected in the lung, heart, skeletal muscle, skin, adrenal gland, and gastrointestinal tract (26–28). In addition, VEGF-D is upregulated in glioblastoma (29), melanoma (30), colorectal carcinoma (31), breast carcinoma (32), and cervical intraepithelial neoplasia (33). Tian et al reported that PTEN suppresses VEGF expression in HCC through both phosphatase-dependent and -independent mechanisms (34). The present study also implicated that PTEN regulates VEGF expression through both phosphatase- and HIF-1a- -independent mechanisms. Kaushal et al (35) reported that VEGF-D expression is observed in all prostate cancer tissues and that it is increased in samples at advanced stages compared with those at the early stage; however, they did not report the correlation between VEGF-D expression and PTEN. In 20% of prostate cancers, PTEN is deleted (36). PTEN-deficient prostate cancers express VEGF-D at an early stage; therefore, it is imperative to compare the expression between tumors with and without PTEN.
The Wingless-type MMTV integration site family genes comprise structurally related genes that encode a secreted signaling protein implicated in oncogenesis and several developmental processes, including the regulation of cell fate and patterning during embryogenesis (37,38). In normal tissues, Wnt3 RNA is primarily detected in the testis, skin, and brain. Reportedly, Wnt3 is associated with cancer progression, invasion, and malignant conversion in cancer of the gastric (39), lungs (40,41), and hepatocellular carcinoma (42,43). In ΔPTEN cells, the cyclin D1 expression was upregulated. In addition, PTEN loss has been reported to augment cyclin D1 expression, although the underlying mechanism remains only partially understood. However, Zang et al reported that the Wnt/b-catenin pathway stimulates increased cyclin D1 levels in lymph node metastasis in papillary thyroid cancer (44). These results suggest an association between the PTEN-loss-induced Wnt3 expression and the subsequent upregulation of cyclin D1.
In mammals, two arginase isoforms (Arg1 and Arg2) have been identified. Arg1 is known as the liver type and is expressed in hepatocytes (45). In mice, Arg1 can also be expressed in myeloid cells under the stimulation of T helper 2 cytokines interleukin (IL)-4 and IL-13 (46), transforming growth factor-b (47), macrophage-stimulating protein (48), or GM-CSF (49). Although immune responses are controlled by amino acid metabolism, Rodriguez et al reported that arginase produced by tumor-infiltrating macrophages repressed the expression of the T-cell receptor CD3z, resulting in the suppression of antigen-specific T-cell responses (46). In this study, it was observed that Arg1 expression increased following Pten deficiency; however, to the best of the author's knowledge, there are no reports demonstrating that Arg1 is highly expressed in any cancer other than liver cancer. Recent cancer treatment strategies have targeted arginine metabolism (50,51), thereby making Arg1 an attractive therapeutic approach for PTEN-deficient tumors.
The present study also analyzed differential expression of miRNA and observed an increased expression of mmu-miR-210-3p in the PTEN-deficient cell line. Reportedly, the expression of miR-210 is induced by HIF-1, which is known to be upregulated in PTEN-deficient cells (52). The expression levels of the target genes of miR-210 were not observed to be altered in the present study. Studies have suggested that miR-210 is involved in multiple processes, including angiogenesis, metastasis, oncogenesis, decreased cell division, and tumor suppression (53,54). However, the exact function remains unclear and requires further investigation.
In conclusion, the present study established a mouse prostate cancer cell model of PTEN deficiency and provided evidence of altered expression of genes associated with the deregulation of signaling processes implicated in human cancers. Gene expression profiling suggested enhanced regulation cancer hallmarks, including cell proliferation, angiogenesis, metastasis, and immunosuppression. However, further studies are warranted to dissect and elucidate molecular mechanisms involved in promoting PTEN-deficient cancer progression.
Acknowledgements
Not applicable.
Funding
No funding was received.
Availability of data and materials
The datasets used during the present study are available from the corresponding author upon reasonable request.
Authors' contributions
AT, KY, SK, AO, HU, MADV, YK, SS, RU, TN and YH equally took part in the conception and design of the study, acquisition and interpretation of data, drafting the article and final approval of the version to be published.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors state that they have no competing interests.
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