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Cancer Biology and Translational Studies

Phosphodiesterase 3A Represents a Therapeutic Target that Drives Stem Cell–like Property and Metastasis in Breast Cancer

Na Hao, Wenzhi Shen, Renle Du, Shan Jiang, Junyong Zhu, Yanan Chen, Chongbiao Huang, Yi Shi, Rong Xiang and Yunping Luo
DOI: 10.1158/1535-7163.MCT-18-1233 Published March 2020

Abstract

Considerable evidence suggests that as breast cancer progresses, genetic and epigenetic mechanisms contribute to the emergence of self-renewing cells (CSC), which may also arise as a consequence of metastasis. Although the molecular pathways that trigger stemness and metastasis are known, key molecular and mechanistic gaps in our understanding of these processes remain unclear. Here, we first screened the inflammation-associated stemness gene phosphodiesterase 3A (PDE3A) using a medium-throughput siRNA library, which was overexpressed in breast tumors and significantly correlated with clinical progression. PDE3A induced the inflammatory nuclear factor NFκB signaling pathway by suppressing cAMP/PKA, which promotes the expression of the stem cell marker OCT4. In addition, PDE3A also promoted the translocation of CCDC88A from the cytoplasm to nuclei, thereby boosting the invasion–metastasis cascade in breast cancer. Most importantly, the PDE3A-selective inhibitor cilostazol dramatically suppressed breast tumor growth and reduced metastasis to the lungs in xenograft breast cancer models, with minimum toxicity. Taken together, we show that PDE3A could predispose patients with breast cancer to metastases by acting as a mediator of cancer stemness. PDE3A is a potential therapeutic target for advanced breast cancer.

Introduction

Among patients diagnosed with metastatic breast cancer, the median overall survival is approximately 18 months with standard treatments. Metastasis remains one of the most complex and challenging hurdles of contemporary oncology (1). Recent studies have demonstrated that the progression of tumor may result in the emergence of cancer stem cells (CSC; ref. 2), which also arise as a consequence of metastasis (3). While much progress has also been garnered as tumor-promoting (4), our current understanding of which factor(s) drive the stemness signaling pathway in the breast cancer is limited.

PDE3s are members of the phosphodiesterase superfamily (5) and the PDE3 family comprises two subfamilies that are encoded by highly related genes on chromosomes 12 (PDE3A) and 11 (PDE3B; ref. 6). In normal tissues, PDE3A is expressed in cardiac tissues, vascular smooth muscles, platelets, oocytes, the kidney, and the cervix (7, 8). However, recent research has shown that PDE3A is also expressed in lung cancer cell lines (9–11). Nevertheless, the expression and role of PDE3A in human breast cancer remain unclear.

The PDE3A-selective inhibitor, cilostazol, is a vasodilator and antithrombotic agent that can cause an increase in cAMP levels in platelets, smooth muscle cells, and endothelial cells (12, 13). However, an earlier study has shown that cilostazol can suppress colon cancer cell motility and may be effective as an antimetastatic drug for patients with cancer (14). Another study published as an AGA abstract reported that cilostazol is a potential anticancer agent that targets the stemness of colorectal cancer. More interestingly, it has been reported that cilostazol imparts protective effects against doxorubicin-induced cardiomyopathy in mice, which is particularly relevant to breast cancer as doxorubicin-based therapies are the standard of care for most patients with breast cancer (15). Whether cilostazol suppresses breast cancer and an antimetastatic drug for patients with breast cancer thus requires further investigation.

CCDC88A, also known as Ga-interacting vesicle-associated protein Girdin/GIV, is an actin-binding Akt substrate and is phosphorylated directly by Akt in response to EGFR signaling (16). It has been observed that its high expression is closely correlated with histologic grade and distant metastasis in breast cancer (17). In addition, CCDC88A is considered as a novel metastasis-related protein and an independent adverse prognosticator in breast carcinoma (18–20). The translocation of CCDC88A from the cytoplasm to the nuclei is crucial for its function promoting migration and metastasis (21). However, factors that mediate the nuclear translocation of CCDC88A in breast cancer remain unclear.

This study has determined that PDE3A is a novel breast cancer target that is upregulated in tumors of patients with breast cancer. The high expression level of PDE3A is an independent predictor of poor prognosis and correlates with clinical prognosis of metastasis in invasive breast cancer. Moreover, PDE3A activates inflammatory pathways that mediate cancer cell stemness by suppressing the cAMP/PKA pathway. In addition, the upregulation of PDE3A correlates with the expression of CCDC88A and promotes CCDC88A translocation to the nucleus, thus contributing to breast cancer metastasis. Furthermore, the PDE3A-selective inhibitor cilostazol reduces breast cancer cell stem cell–like properties and metastasis both in vitro and in mouse xenografts, with minimum toxicity. Thus, our findings have established that PDE3A is a novel therapeutic target in malignant breast cancer.

Materials and Methods

Cell culture and human sample collection

MDA-MB-231 breast cancer cells were cultured in L15 medium. T-47D, MCF-10A, and MCF-7 cells were cultured in DMEM. All culture media were supplemented with 10% FBS (Hyclone). All cells except MDA-MB-231 were grown at 37°C in 5% CO2 incubators and MDA-MB-231 were grown at 37°C in 0% CO2 incubators. All cells were passaged for less than 3 months before renewal from frozen, early-passage stocks. All cells were purchased from ATCC and all were tested to ensure that they were Mycoplasma negative.

A total of 108 breast cancer samples were collected from patients who had received surgery at PLA Hospital (China). Retrospective clinicopathologic data were obtained, including age, sex, tumor size, regional lymph node status, TNM stage, pathologic type, differentiation, PET-CT, and MRI scanning data. All patients provided written informed consent for the use of their specimens and disease information for future investigations as specified by the Ethics Committee of the PLA hospital (IRB SQ/01.01/01.3; approval no. #S2016-023-01).

Small-molecule inhibitors

Small-molecule inhibitors cilostazol and H89 (22) were purchased from Sigma-Aldrich (1134153) and Beyotime (S1643), respectively.

PDE3A mRNA expression, genetic alterations, and TCGA data analysis

Publicly available breast cancer expression datasets GDS4091/7954293 were downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/). The datasets contained gene expression profiles of CSC populations in highly metastatic variants of the MDA-MB-231 breast cancer cells and the parental MDA-MB-231 cells. The normalized expression of PDE3A was compared between different cells and metastatic groups with a two-tailed t test. For genetic alterations of PDE3A genes, data from a recent genomics study at the cBioPortal for Cancer Genomics (http://www.cbioportal.org) was interrogated (23, 24) and OncoPrint displays of gene alterations were presented. The TCGA data of 1,095 patients with breast cancer were downloaded from the TCGA database (http://cancergenome.nih.gov/). Normalized mRNA expression of PDE3A, clinicopathologic parameters, and follow-up data were extracted and analyzed.

Production of lentiviruses expressing PDE3A short hairpin RNA and cDNA and transfection of PDE3A siRNA

Short hairpin RNA (shRNA) targeting PDE3A and CCDC88A were designed by the BLOCK-iT RNAi Designer provided by Thermo Fisher Scientific (https://rnaidesigner.invitrogen.com/rnaiexpress/index.jsp). shRNA targeting human PDE3A, CCDC88A, and a scrambled control sequence were chemically synthesized and cloned into lentiviral vectors pLV-H1-EF1α-puro. PDE3A-shNC, 5′-AAAAGCTACACTATCGAGCAATTTTGGATCCAAAATTGCTCGATAGTGTAGC-3′; shRNA1-PDE3A, 5′-AAAAGGAATAATCCAGTGATGATGATTGGATCCAATCATCATCACTGGATTATTCC-3′; shRNA2-PDE3A, 5′-AAAAGGTTCTCACAGGGCCTTAACTTTGGATCCAATAAGTTAAGGCCCTGTGAGAACC-3′; shCCDC88A, 5′-AAAACCGGCTTCATTAGTTCTGCGGGAAACTCGAGTTTCCCGCAGAACTAATGAAGTTTTTTGTTGGATCCAACAAAAAACTTCATTAGTTCTGCGGGAAACTCGAGTTTCCCGCAGAACTAATGAAGCCGG-3′; complementary DNA of human PDE3A and CCDC88A was cloned by reverse transcription PCR using total RNA from L02 cells and a specific primer pair for PDE3A, 5′-GCTCTAGAGCCACCATGGCAGTGCCCGGCGACGCTG-3′ (forward) and 5′-GGAATTCCATATGACTGGTCTGGCTTTTGGGTTGGTAT-3 (reverse); CCDC88A, 5′-ATGGAGAACGAAATTTTTACT-3′ (forward), and 5′-AATTTCTGCTTTCTTGTACTTT-3 (reverse). The amplified fragments were ligated into the pLV-EF1α-MCS-IRES-Puro (catalog no. cDNA- pLV03, Biosettia Inc.) expression vector. Lentiviral vectors encoding PDE3A and CCDC88A shRNA or cDNA were transiently transfected into 293T cells (ATCC) using Lipofectamine RNAiMAX (Invitrogen) according to the manufacturer's instructions to generate lentiviral particles. The recombinant lentiviruses were then transduced into MDA-MB-231, T-47D, or MCF-7 cells, and the transduced cells were selected with puromycin (2 μg/mL) for a week after which the cells are pooled and expanded.

qRT-PCR

Total RNAs were purified with the RNeasy Mini Kit (Qiagen) and cDNA were synthesized with the SuperScript III First-Strand Synthesis SuperMix for qRT-PCR (Thermo Fisher Scientific). The expression levels of PDE3A, CCDC88A, SOX2, OCT4, Nanog, and GAPDH mRNA were quantified with the LightCycler 480 Real-Time PCR System with Universal ProbeLibrary Probe #36 (Roche). The primers were as follows: PDE3A, 5′-GGGCGATGAAAGAGGTGAA-3′ (forward) and 5′-TGGCTTGTTGAGACGAGTT-3′ (reverse); CCDC88A, 5′-CAGACCGAAGGATAAAGAC-3′ (forward) and 5′-ATGGCTGTAGTAGAGAAGG-3′ (reverse); SOX2, 5′-CGCAGACCTACATGAACG-3′ (forward) and 5′-GGACTTGACCACCGAACC-3′ (reverse); OCT4, 5′-CGATCAAGCAGCGACTATG-3′ (forward) and 5′-GAGTGGTGACGGAGACAG-3′ (reverse); Nanog, 5′-AAGAACTCTCCAACATCCTGAAC-3′ (forward) and 5′-CCTGCGTCACACCATTGC -3′ (reverse); and GAPDH, 5′-TCATCCCTGCCTCTACTG-3′ (forward) and 5′-TGCTTCACCACCTTCTTG-3′ (reverse).

Western blotting analysis

IHC was performed as described previously (25) with the following modifications. The primary antibodies were as follows: PDE3A (ab169534, Abcam); SOX2 (sc-20088, Santa Cruz Biotechnology); Nanog (ab80892, Abcam); PKAα (sc-48412, Santa Cruz Biotechnology); N-cadherin (ab18203, Abcam), and Vimentin (ab8978, Abcam) at a 1:1,000 dilution; OCT4 (ab19857, Abcam); IkappaB-α (1130-1, EPIT MICS) and E-cadherin (ab40772, Abcam) at a 1:800 dilution; CCDC88A (ab179481, Abcam); NFκB (p105/p50; 1559-1, EPIT MICS); p-NFκB (sc-101744, Santa Cruz Biotechnology), and β-catenin (ab32572, Abcam) at a 1:500 dilution; Lamin A/C (4777S, Cell Signaling Technology) and β-actin (sc-47778, Santa Cruz Biotechnology) at a 1:1,200 dilution. Images were acquired using the Bio-Rad Chemi Doc MP Imaging System (Bio-Rad). All Western blots were a representative image of three separate experiments. The results were analyzed using ImageJ software (NIH, Baltimore, MD).

IHC and immunofluorescence analysis

IHC was performed as described previously (26) with the following modifications. Antigen retrieval for sections of tissue microarrays (TMA PR803b, US Biomax, Inc.) was performed in a pressure cooker. The antibodies used for these studies were anti-PDE3A and anti-CCDC88A mAb (ab179481, Abcam). The intensity of the staining was evaluated by the following criteria: 0: negative; 1, low; 2, medium; 3, high. The percentage of positive nuclear staining was scored as follows: score 0, 0%–<5%; score 1, 5%–<10%; score 2, 10%–50%; score 3; 50%–80%; score 4,80%–100%. Five randomly chosen fields (20× magnification) were evaluated under a light microscope. The final scores were calculated by multiplying the scores of the intensity with the extent and dividing into four grades: 0, negative (−); 1–2, low staining (+); 4–8, medium staining (++), and 9–12, high staining (+++).

Immunofluorescence (IF) staining was performed as described previously (26). The antibodies used for these studies were anti-PDE3A (ab169534, Abcam) and anti-CCDC88A (ab179481, Abcam).

Cancer stemness assays

Procedures of flow cytometry, tumor sphere assay, Transwell, and wound-healing assay were performed as described previously (25).

Chromatin immunoprecipitation-qPCR assay

The procedure of chromatin immunoprecipitation (ChIP)-qPCR was described in a previously published article (27). The antibodies used for the ChIP assays were anti-RNA Pol-II (Millipore; lot: 2825646) and anti-NFκB (MICS; 1559-1) antibodies and IgG (Millipore; lot: 2861373). The primers were as follows: OCT4 promoter site 1, 5′-AGGACAGTGAGAAGGAAG-3′ (forward) and 5′-CTTGTGGCTGGATATGAG-3′ (reverse); OCT4 promoter site 2, 5′-GCCAGAAATACACCACCTACAG-3′ (forward) and 5′-CAAGCCAGTCCAGAGAGTCC-3′ (reverse); OCT4 promoter site 3, 5′-CCACTGCCTTGTAGACCTTCC-3′ (forward) and 5′-CACTCTTATGTTGCCTCTGTTCG-3′ (reverse); OCT4 promoter site 4, 5′-AGGTCAGCGTGCCCAGTC-3′ (forward) and 5′-CAAGAGAATAGCCAACGGAATGC-3′ (reverse); OCT4 promoter site 5, 5′-CTCCTCTGCGTCTTTCTG-3′ (forward) and 5′-TAGTTCCTCCTTCCTCTGG-3′ (reverse); OCT4 promoter site 6, 5′-TCCCAGGCTTCTTTGAAC-3′ (forward) and 5′-AACTCAGACATCTAATACCAC-3′ (reverse); OCT4 promoter site 7, 5′-GGGAAGTAGGGACCAACC-3′ (forward) and 5′-AGTAGACTGCCAGACAAGG-3′ (reverse); OCT4 promoter site 8, 5′-GAGGTGTGGGAGTGATTC-3′ (forward) and 5′-ATGATTAAAGGCGTGAGC-3′ (reverse); OCT4 promoter site 9, 5′-CTGGGCAACAAAGTGAGAC-3′ (forward) and5′-CTAATGGTGGTGGCAATGG-3′ (reverse); OCT4 promoter site 10, 5′-ATTGCCACCACCATTAGG-3′ (forward) and 5′-CGAAGGGACTACTCAACC-3′ (reverse).

Co-immunoprecipitation

MDA-MB-231 cells were lysed in lysis buffer (pH 7.4) containing protease inhibitor cocktail and a phosphatase inhibitor cocktail. Lysates were immunoprecipitated with Dynabeads Protein G coupled to an anti-PDE3A antibody (ab169534, Abcam) or mouse IgG isotype as a control for 2 hours at 4°C. Beads were pelleted by a magnetic rack and subsequently analyzed via Western blot analysis.

RNA-sequencing data analysis

RNA-sequencing (RNA-seq) libraries were prepared from 1 μg of total RNA using Illumina TruSeq RNA Sample. Libraries were validated with an Agilent Bioanalyzer (Agilent Technologies). Sequencing was performed on an Illumina HiSeq 2000 sequencer at BGI Tech. FASTQ-formatted sequence data were analyzed using a standard BWA-Bowtie-Cufflinks workflow. In brief, sequence reads were mapped to the reference human-genome assembly (February 2009, GRCh37/hg19) with BWA and Bowtie software. Subsequently, the Cufflinks package was applied for transcript assembly, quantification of normalized gene and isoform expression in RPKM (reads per kilobase per million mapped reads), or FPKM (fragments per kilobase of exon model per million mapped reads) and testing for differentially expression genes (DEG). Signaling pathways were analyzed on KEGG database by FUNRICH software.

Gene-set enrichment analysis

GSEA was performed using the Java Desktop software (http://software.broadinstitute.org/gsea/index.jsp; ref. 27). Genes were ranked according to the shrunken limma log2 fold changes, and the GSEA tool was used in “pre-ranked” mode with all default parameters.

Xenograft tumor models and small inhibitor treatments

For establishing tumors, 2 × 106 MDA-MB-231 cells were suspended in total of 100 μL PBS and implanted subcutaneously between fourth and fifth pairs of breasts of female NOD/SCID mice at 6–8 weeks of age. When the tumor volume was approximately 80 mm3, the mice were separated randomly into four groups, and treated intraperitoneally (i.p.) with 100 μL of either vehicle or cilostazol (at a dose of, 25, 50, or 75 mg/kg) every 2 days. Tumor growth was measured by calipers, and volume was calculated with the equation volume = 1/2 (length × width2). At the end of the study, mice were sacrificed and the tumors were excised and weighed. In addition, the kidney, heart, lung, liver, and spleen were harvested and weighed.

The animal protocol was approved by The Institutional Laboratory Animal Care and Use Committee (IACUC) at Nankai University (Tianjin, China).

Statistical analysis

Cell culture–based experiments were performed at least three times. The data are presented as mean ± SD from three independent experiments. Statistical analyses were performed using two-tailed Student t tests to compare the means. Differences and correlations in immunostaining were analyzed with the χ2 test. Expression correlation between PDE3A and CCDC88A in 33 breast cancer patients' tissues are assessed by Pearson correlation coefficient (r) and a two-tailed t test for significance. P < 0.05 was considered to be significant.

Results

PDE3A is upregulated in human breast cancer tissues

Previous study determined 10 candidate inflammatory genes (NFκB1, IL1α, IL1β, p50, p130, TRAF6, PRTN3, PDE3A, ICAM3 and CCL16) associated with cancer stemness, which suggests their role in CSC maintenance (25). On the basis of our preliminary data that PDE3A is associated with CSC characteristics, we focused on PDE3A.

To investigate the expression pattern of PDE3A in human cancers, we detected the expression levels of PDE3A in multiple types of cancer tissues (breast cancer, lung cancer, stomach cancer, and colon cancer) using microarrays consisting of 63 biopsies by IHC staining. The results shown that PDE3A was expressed at abnormally high levels in these tumor biopsies, particularly in higher pathologic grade tissues (Supplementary Fig. S1A). Furthermore, we performed IHC staining in a total of 58 pairs of breast tumor tissues and adjacent nontumor tissues. The left panel in Fig. 1B shown that PDE3A was overexpressed in breast cancer tissues and rarely in the adjacent nontumor tissues. Wilcoxon rank sum test confirmed that PDE3A staining was more intense in the breast cancer tissues than the corresponding normal tissues (Z = −6.208, P < 0.001, Wilcoxon signed ranks test; Fig. 1B, right). In addition, we confirmed the overexpression of PDE3A in 8 pairs of fresh breast cancer and the adjacent nontumor tissues by Western blot (WB; Fig. 1C) and qRT-PCR (Fig. 1D) assays and in six human breast cancer cell lines (Supplementary Fig. S1B). IF assays localized endogenous PDE3A to the cytoplasm (Supplementary Fig. S1C). Furthermore, an oncoprint display from the cBioPortal database shows altered PDE3A expression in 122 (5%) of 2,509 cases/patients (Supplementary Fig. S2A).

Figure 1.
Figure 1.

The expression and clinical significance of PDE3A in patients with breast cancer. A, Left, Representative images for absent, weak, moderate, and strong expression of PDE3A by IHC staining on 59 pairs of breast tumor tissues (Ca) and adjacent nontumor (NT) tissues. Right, A heatmap and statistically analyzed by Wilcoxon signed ranks test. B and C, Eight pairs of fresh breast cancer tissues and NT tissues were subjected to WB assays (B) and RT-qPCR analysis (C). D, Kaplan–Meier analysis of recurrence survival of the 1,050 patients with breast cancer (the minimum follow-up time is 168.1 months; the cut-off line for PDE3A low and high group is 43 RPKM; log-rank tests. E, Left, One patient's PET-CT, MRI, and IHC images of primary breast tumor and supraclavicular mass with distant metastasis. Right, The statistics of IHC score between nonmetastasis patients and metastasis patients.

To determine whether the high expression of PDE3A is associated with breast cancer patient outcomes, we performed survival analysis using recurrent or metastatic cases or deaths as endpoints that reflect a low cumulative survival probability and poor prognosis. A cohort of 1,002 patients with breast cancer who had a median follow-up of 102 months (range 14–145 months) from the TCGA database was further studied. The recurrence-free survival time for patients with low PDE3A expression (≤43 RPKM) was significantly longer than those with high PDE3A level (>43 RPKM; P = 0.020, log-rank test; Fig. 1E). In addition, as shown in Table 1, high PDE3A expression levels were strongly correlated with T staging (P = 0.0019, χ2 tests) and nodal staging (P = 0.0089, χ2 tests). Furthermore, we assessed 7 patients with metastatic breast cancer who were subjected to PET-CT scanning. Among of these, the MRI, PET-CT, and IHC staining results of primary tumor tissues of two patients are shown in Fig. 1F and Supplementary Fig. S2B, respectively. For the patient in Fig. 1F, the MRI results indicated a tumor grade of BI-RADS IV (American College of Radiology's Breast Imaging Reporting and Data System lexicon and categorize); the time-intensity curve (TIC) was type III washout; the PET-CT imaging shown cervical vertebra metastasis and the corresponding IHC staining showed that PDE3A was highly expressed in the primary tumor tissues. IHC staining of the rest of the 5 patients with metastasis to the lung, liver, axillary lymph nodes, retroperitoneal, centrum, and supraclavicular lymph nodes indicated that PDE3A was highly expressed in all these patients (Supplementary Fig. S2C). The IHC score for PDE3A in the metastatic patients was higher than in the nonmetastatic patients (Fig. 1F). Thus, high PDE3A expression levels are associated with breast cancer metastasis.

View this table:
Table 1.

Association between PDE3A expression and clinicopathologic features of breast cancer tissues from patients.

In addition, we used a Cox proportional hazard model to determine the prognostic value of PDE3A. PDE3A immunoreactivity, patients' age, tumor size, lymph node, TNM stage, histologic grade, and molecular subtypes were selected as risk variables because all of them are potential factors influencing a low cumulative survival probability for breast cancer. HRs are presented in Table 2. In the multivariate analyses of disease-free survival models, the HR values of PDE3A immunoreactivity and TNM stage were 2.624 (P = 0.043) and 6.014 (P = 0.016), respectively. These indicated that PDE3A expression and TNM stage are two independent factors that are related to a poor outcome in patients with invasive breast cancer. Therefore, high PDE3A expression levels are associated with poor prognosis and are an independent predictor of poor recurrent/metastasis prognosis in breast cancer.

View this table:
Table 2.

Cox proportional hazard model analysis of prognostic factors in patients with breast carcinoma.

All of these data indicate that PDE3A is upregulated in breast cancer is closely correlated with clinical prognosis of metastasis, and is an independent predictor of poor prognosis.

PDE3A is upregulated in the population of CSCs in highly metastatic variants of MDA-MB-231 and T-47D cancer cells

To explore the roles of PDE3A in tumor progression, we analyzed the expression of PDE3A in the metastatic variants of breast cancer cells with a population of cancer stem cells in the raw data of GDS4091/7953293 from the GEO database. Figure 2A shown that the heatmap identified some of the most upregulated genes in metastatic variants compared with the parental of MDA-MB-231 breast cancer cells. Interestingly, we found that the level of PDE3A expression was significantly upregulated in the stem cell population in highly metastatic variants of breast cancer cells (Fig. 2B; Supplementary Fig. S3A).

Figure 2.
Figure 2.

PDE3A is increased in the population of CSC and facilitates breast cancer metastasis. A, Heatmap of 47 upregulated genes in the parental MDA-MB-231 cells (the first two columns), bone metastatic variants of 231-BoM-183 cells (the middle two columns), and brain metastatic variants of 231-BrM-2a cells (the last two columns). Gray, upregulation; black, downregulation. B, Volcano plot of differentially expressed genes. C, The expression of PDE3A, SOX2, OCT4, and Nanog in MDA-MB-231 and T-47D cells that were transfected with shPDE3A were detected by WB assay. D, Primary mammosphere frequency of shPDE3A-infected MDA-MB-231 and T-47D cells were calculated, and representative single spheres imaged were visualized by microscope. E, Percentage of ALDH1+ cells of shPDE3A-infected MDA-MB-231 and T-47D cells were detected by flow cytometry. F, GSEA of the PDE3A enrichment, which was defined by RNA-seq transcriptomes of MDA-MB-231 cells treated with the two siRNAs of PDE3A. G and H, Transwell and wound healing assay for shPDE3A-infected MDA-MB-231 and T-47D cells by microscope. I, The primary tumor was monitored in NOD/SCID mice after injected with shNC and shPDE3A of MDA-MB-231 cells. The tumor growth curve of each group (n = 5). J, The pulmonary metastases foci were evaluated by hematoxylin and eosin (H&E) staining (n = 5; **, P < 0.01; ***, P < 0.001).

We further established the stable MDA-MB-231 and T-47D cell lines in which PDE3A expression levels were knocked down with shRNA (shPDE3A_1 and shPDE3A_2). As expected, knocking down PDE3A reduced the expression of stemness-related genes, including SOX2, OCT4, and Nanog in MDA-MB-231 and T-47D cells (Fig. 2C). We also observed that reduction in the expression of PDE3A inhibits the tumorsphere-forming ability of MDA-MB-231 and T-47D cells (Fig. 2D; Supplementary Fig. S3B) and decreases the proportion of ALDH1+ cells (Fig. 2E; Supplementary Fig. S3C).

PDE3A facilitates breast cancer metastasis by triggering cancer cell invasion metastasis in a breast cancer model

To further investigate whether the overexpression of PDE3A contributes to metastasis in breast cancer, we analyzed the transcriptome of MDA-MB-231 cells treated with the two shRNAs of PDE3A by RNA-seq. Examination by GSEA software revealed genes that strongly hallmarked the epithelial-to-mesenchymal transition pathway (Fig. 2F). Consistent with this observation, the invasion and migration ability of MDA-MB-231 and T-47D cells significantly decreased when PDE3A was knocked down (Fig. 2G and H; Supplementary Fig. S3D and S3E). To address these effects in vivo, NOD/SCID mice were injected with wild-type MDA-MB-231 cells or MDA-MB-231 cells transfected with shRNAs of PDE3A. Tumor growth was significantly slower in the shPDE3A-MDA-MB-231 groups than the control group (Fig. 2I; Supplementary Fig. S3F). Pulmonary metastasis in the shPDE3A-infected MDA-MB-231 groups was clearly reduced compared with the control group (Fig. 2J).

Together, these results suggest that PDE3A plays a critical role in facilitating tumor invasion and metastatic phenotypes both in vitro and in vivo.

The NFκB signaling pathway activated by cAMP/PKA promotes OCT4 expression to sustain cancer stem-like property

To investigate which signaling pathway is involved in the CSC-like property, we performed Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis, which was embedded in FUNRICH software. The top KEGG pathways that were significantly enriched contained the upregulated and downregulated DEGs between the control and shPDE3A_1 group (Fig. 3A), the upregulated DEGs enriched in the JAK-STAT, IL17, TNF, NFκB, PPAR, and T-cell receptor signaling pathways, and the downregulated DEGs enriched in the IL17, TNF, NOD-like receptor, and NFκB signaling pathways. A preliminary research report indicated NFκB signaling is markedly activated by immune inflammatory cells in the tumor microenvironment and the activation of cAMP/PKA in cells mediates the suppression of inflammatory pathways such as the NFκB signaling pathway (28). We thus performed experiments to further explore the role of these inflammatory signals that are induced by the NFκB signaling pathway.

Figure 3.
Figure 3.

NF-κB enhances the transcriptional expression of OCT4, which was activated by cAMP/PKA signaling pathway. A, KEGG pathway enrichment analysis, which was embedded in FUNRICH software. The number of the most enriched pathway of differently expressed genes (DEG) between shNC and shPDE3A_1 was evaluated. Blue, downregulated DEGs; red, upregulated DEGs. B, Intracellular cAMP levels in culture lysates were measured using the cAMP Biotrak Enzyme immunoassay system. C–E, Protein expression of cAMP, PKA, IkBα, NF-κB, and phosphorylation-NF-κB (p-NF-κB) in shNC and shPDE3A-infected MDA-MB-231 cells or treated with cAMP/PKA–selective inhibitor H89 by WB assay. F, The expression and localization of NF-κB and p-NF-κB in cytoplasm and nucleus shPDE3A-infected MDA-MB-231 and T-47D cells by IF assay. G, Schematics of PDE3A gene promoter with ChIP primer–pair locations indicated by horizontal short lines and their distance in kb relative to the TSS. H and I, ChIP-qPCR and qRT-PCR analysis with primers P1–P10 of PDE3A mRNA in MDA-MB-231 cells.

We detected the level of cAMP and the protein expression of PKA, IkBα, NFκB, and p-NFκB in shPDE3A-infected MDA-MB-231 and T-47D cells compared with the respective control cells (Fig. 3B and C). The results show that the levels of cAMP and PKA protein expression increased, whereas that of p-NFκB decreased when PDE3A expression was knocked down. Simultaneously, the expression and localization of p-NFκB in the nucleus were reduced in the shPDE3A groups, as detected by Western blot assays (Fig. 3D). As expected, when the MDA-MB-231 and T-47D cells were treated with H89, which is a selective inhibitor of cAMP/PKA, the activation of p-NFκB and its translocation to the nucleus was rescued (Fig. 3E). IF showed the same results that NFκB is translocated to the nucleus when cells were cultured with inflammatory medium of THP1 cells (Fig. 3F). These results suggest that PDE3A activates the NFκB signaling pathway by inhibiting cAMP/PKA.

Then, we explored whether NFκB could regulate the stem cell–like property using a ChIP-qPCR assay. Ten peaks of NFκB binding within the OCT4 promoter on chr6_ssto_hap7:2,465000–2,467,051 were designed as sites 1 to 10 (Fig. 3G). We were able to detect a strong binding of NFκB to site 5 in the OCT4 promoter (Fig. 3H and I). The binding affinity of NFκB to the site 5 regions was stronger than the other sites. These results suggested that NFκB could bind to the promoter of the stemness marker OCT4 (29, 30). These findings indicate that the NFκB signaling pathway plays a critical role in sustaining the CSC-like property in breast cancer.

The correlation between PDE3A and CCDC88A expression in breast cancer

To gain more insights into the molecular mechanism underlying the role of PDE3A in breast cancer cell metastasis, we evaluated and predicted the candidate proteins that are associated with PDE3A in four databases [bioGRID database (https://thebiogrid.org/), APID interactiomes, IMEx and IntAct database] using the Cytoscape software (Fig. 4B; Supplementary Fig. S4A–S4C). Then, we constructed a Venn diagram to identify the optimal five genes (HSPA5, TUBA1C, CCDC88A, Pcdh1, and Cep44) shared among all four databases to further increasing the reliability of our prediction (Fig. 4A). We next evaluated the degree and the relationship between the nodes and the hub genes in each network, particularly the bioGRID network (Fig. 4B). On the basis of the interactor node distribution (the shortest distance far from PDE3A was CCDC88A), organism node (CCDC88A screened from biological experiments), and betweenness centrality values (CCDC88A has the highest betweenness centrality value), one node (CCDC88A gene) was selected.

Figure 4.
Figure 4.

The correlation between PDE3A and CCDC88A expression in breast cancer. A, Venn diagram overlaps four different sets of protein–protein interaction (PPI) with PDE3A from bioGRID, APID interactomes, IMEx, and IntAct database. B, PPI network analysis from bioGRID (https://thebiogrid.org/). Interactor node distribution: light gray, same organism nodes (20); gray, chemical nodes (12); black, different organism nodes (7). Interaction edge distribution: light gray, chemical edges (0); gray, genetic edge (0); black, physical edges (29). C, Representative IHC staining images of high and low levels for PDE3A and CCDC88A in consecutive sections. D, Real distribution of IHC results between PDE3A and CCDC88A expression. E, The correlation matrix between PDE3A and CCDC88A expression in breast cancer tissues. F, Spearman correlation analysis of the mRNA expression profiles of PDE3A and CCDC88A in 1,040 patients with breast cancer from TCGA database. G, Immunoprecipitation assay in MDA-MB-231 cells.

We also investigated the relationship between PDE3A and CCDC88A in vitro. First, we examined the correlation between the protein expression levels of PDE3A and CCDC88A by IHC staining in a cohort of 33 breast cancer specimens. Figure 4C shows that the PDE3A protein colocalized with the CCDC88A protein in consecutive sections of breast cancer tissues, and the expression level of them was significantly associated breast cancer tissues (χ2 = 3.997, P < 0.0001, Spearman correlation analysis; Fig. 4D). In addition, matrix correlation analysis showed that PDE3A and CCDC88A expression are closely correlated (Fig. 4E). Next, the data from the TCGA database were analyzed and the correlation between the mRNA expression levels of PDE3A and CCDC88A reached 0.4338 (P < 0.0001, Spearman correlation analysis; Fig. 4F). A co-IP assay revealed that immunoprecipitation of PDE3A from MDA-MB-231 brought down with CCDC88A (Fig. 4G; Supplementary Fig. S4D). Finally, we detected the correlation between the protein and mRNA levels of PDE3A and CCDC88A in shPDE3A cell lines (Supplementary Figs. S4E and S4F). The results suggest that CCDC88A is downregulated due to the reduction in PDE3A expression.

These results indicated that PDE3A is closely related to CCDC88A, which is associated with poor prognosis in patients with invasive breast cancer.

PDE3A promotes the translocation of CCDC88A from the cytoplasm to the nucleus in breast cancer

To further address how the interaction with PDE3A modulates CCDC88A expression, we localized the CCDC88A protein in MCF-10A, MDA-MB-231, and T-47D breast cancer cells using WB and IF assays (Fig. 5A and B). CCDC88A was highly expressed in breast cancer cells and was mainly localized to the cytoplasm in the MDA-MB-231 and T-47D cells (Fig. 5C and D). These observations coincided with the results of IHC and IF, which indicated that CCDC88A is mainly localized in the cytoplasm of breast cancer tissues, with no significant staining in the nuclei.

Figure 5.
Figure 5.

PDE3A promotes the translocation of CCDC88A from cytoplasm to nuclei in breast cancer. A, The patterns exhibit the colocalization of PDE3A and CCDC88A in T-47D cells by IF staining. Green, CCDC88A; red, PDE3A; blue, DAPI. B, CCDC88A protein expression in MCF-10A, T-47D, and MDA-MB-231 cells by WB assay. C, The overall expression level of PDE3A and CCDC88A in MCF-7_PDE3A cells by WB analysis. D and E, The cytoplasm and nucleus of CCDC88A in MCF-7, T-47D, MDA-MB-231, and MCF-7-PDE3A cells by WB analysis. F, Cytoplasmic and nucleus expression of CCDC88A and PDE3A in MCF-7-PDE3A and MCF-7-vector cells by IF staining. G, The metastasis-related markers were detected on shPDE3A-infected MDA-MB-231 and T-47D cells by WB assay. H and I, Statistical analysis for MCF-vector, MCF-7-PDE3A, and MCF-7-PDE3A-shCCDC88A cells by transwell (H) and wound-healing (I) assay. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

To determine whether the molecular mechanisms of PDE3A-induced migration involved the regulation of CCDC88A expression, we constructed a stable cell line with PDE3A overexpression in the weakly invasive MCF-7 breast cancer cell line. The overall CCDC88A protein expression levels in PDE3A-overexpressing cells were significantly higher compared to the cells transfected with empty vectors. However, the expression levels of CCDC88A protein were significantly higher in the cytoplasm than in the nuclei when PDE3A was overexpressed in breast cancer MCF-7 cells (Fig. 5E and F). Finally, we established the MCF-7-PDE3A-shCCDC88A cell lines for further experimentation. The expression of metastasis marker N-cadherin, vimentin, and β-catenin significantly increased and the migration and invasion ability was dramatically enhanced when PDE3A was overexpressed. However, these effects were suppressed in the shPDE3A and MCF-7-PDE3A-shCCDC88A cells (Fig. 5G–I; Supplementary Figs. S4G–S4H). These results revealed that the overexpression of PDE3A significantly reduced the CCDC88A levels in the cytoplasm but significantly promoted its expression in the nuclei and the effect of PDE3A expression on CCDC88A localization is necessary for the requirement for PDE3A expression in tumor metastasis.

The PDE3A-selective inhibitor cilostazol suppresses breast cancer metastasis both in vitro and in vivo

Given the crucial function of PDE3A in breast cancer cells, we examined the effect of selective inhibitors of PDE3A. Recently, cilostazol, a PDE3A inhibitor, has been shown to be a potential anticancer agent (31, 32). We thus investigated the effect of cilostazol on human breast cancer models. Treatment with cilostazol led to significant inhibition of cell viability in a dose-dependent manner (Fig. 6A). The IC50 values of 24, 48, 72 hours of cilostazol treatment were 4.203 μmol/L, 2.006 μmol/L, 1.565 μmol/L, and 3.717 μmol/L, 1.453 μmol/L, 1.453 μmol/L in MDA-MB-231 and T-47D cells, respectively (Supplementary Fig. S5A). The IC50s of liver cancer HepG2 cells, lung cancer A549 cells, cervical cancer HeLa cells, noncancer LO2 cells, and mouse myocardial H9c2 cells treated with cilostazol were similar to breast cancer cells (Supplementary Fig. S5B and S5C). In addition, comparison of the treatment of cilostazol with PDE3A knockdown showed the same inhibitory effect in MDA-MB-231 and T-47D cells (Supplementary Fig. S5D). Therefore, we selected 2 μmol/L and 4 μmol/L of cilostazol that encompassed the concentrations above and below the IC50 values for further investigation. The ability of the breast cancer cell lines to metastasize was examined with or without cilostazol treatment. Cilostazol markedly decreased the invasion and migration abilities (Fig. 6B and C; Supplementary Fig. S5E and S5F) and the level of protein and mRNA of stemness-related genes, including SOX2, OCT4, and Nanog in a dose-dependent manner (Supplementary Figs. S5G and S5H).

Figure 6.
Figure 6.

PDE3A-selective inhibitor cilostazol suppressed breast cancer metastasis both in vitro and in vivo. A, The cell viability of MDA-MB-231 and T-47 when treated by cilostazol. B and C, Transwell and wound-healing assay of MDA-MB-231 and T-47D cells with or without cilostazol treatment. D, Schedule of cilostazol treatment with NOD/SCID mice bearing breast cancer (MDA-ME-231 cells; n = 5). E and F, Progression of tumor volumes and weight monitoring in mice treated with cilostazol doses 0, 25, 50, 75 mg/kg, respectively. G, Bioluminescent imaging of primary tumor and tumor weight statistics for different doses of cilostazol treatment. H, MDA-MB-231 xenografts from each group were collected, and lung metastatic foci were evaluated by H&E staining (n = 5). *, P < 0.05; **, P < 0.01; ***, P < 0.001.

To further evaluate the therapeutic potential of cilostazol in vivo, we investigated the effects of cilostazol on tumor progression. We generated xenografts using MDA-MB-231 cells that were transplanted into the sixth mammary fat pads of NOD/SCID mice, and the tumor growth and lung metastasis were measured (Fig. 6D). The growth of primary tumor growth was significantly suppressed when the mice were intraperitoneally injected with cilostazol at doses of 0, 25, 50, and 75 mg/kg (Fig. 6E and F). The size of the primary tumors was smaller in the treated group compared with the 0 mg/kg group and the negative control of xenografted tumor cell line expressing low PDE3A levels (Fig. 6G; Supplementary Fig. S5I). The number of foci of pulmonary lung metastasis in mice treated with 0, 25, 50, and 75 mg/kg of cilostazol was significantly reduced compared with the untreated mice (Fig. 6H). Moreover, the expression of PDE3A, CCDC88A, and the stemness marker OCT4 were also suppressed after treatment with cilostazol (Supplementary Fig. S5J). In addition, cilostazol showed minimal toxicity in the mice (Supplementary Figs. S6A and S6B). Therefore, PDE3A-specific inhibitor cilostazol could significantly suppress breast cancer growth and metastasis both in vivo and in vitro, with minimum toxicity.

Discussion

There is a currently insufficient therapeutically actionable means to effectively suppress metastasis, which may be mediated by stemness, genetic heterogeneity, dormancy, and immune tolerance (33, 34). In this study, we report that PDE3A expression is inversely correlated with prognosis and promotes breast cancer invasion by regulating the nuclear localization of CCDC88A. Conversely, breast cancer growth and metastasis could be effectively inhibited by PDE3A-specific inhibitor cilostazol in vitro and in vivo. At the same time, PDE3A could activate NFκB inflammatory signaling and promote the transcription of the OCT4 gene, which is a crucial regulator of stemness (Supplementary Fig. S7). These findings support our conclusion that PDE3A has pleiotropic effects on the breast CSC-like property and metastasis and is potentially a novel therapeutic target.

Several recent studies have demonstrated that the dysregulation of microenvironmental signaling, especially the inflammatory environment is crucial in determining tumor stemness properties and EMT (35, 36). In our study, the key and most compelling finding is that the upregulation PDE3A not only contributes to the activation of the NFκB inflammatory signaling and promotes the OCT4 stemness gene transcription, but also promotes nuclear translocation of CCDC88A, thereby leading to invasion and metastasis. In addition, our results indicate that PDE3A is a cascade molecule that weaves the inflammatory environment into stemness.

Our results agree with the finding of previous reports that elevated localization of CCDC88A in the nucleus indicates a worse prognosis for patients with breast cancer (37, 38). In these previous studies, CCDC88A translocation to the nuclei was mediated by necrosis factor receptor-associated factor 4 (TRAF4; ref. 21). It is possible that PDE3A acts in concert with TRAF4 to promote the nuclear translocation of CCDC88A. Moreover, several other cancer-related pathways, such as transcriptional dysregulation, cytokine–cytokine receptor interaction, and Jak–STAT signaling pathways, were enriched (Fig. 3A). These pathways will be further investigated by our research team. A recent study indicated that KIT receptor activity modulates PDE3A expression through the MAPK/ERK pathway at the transcriptional and protein levels in human gastrointestinal tumors (39). Another study found that PDE3A is hypermethylated in cisplatin-resistant non–small cell lung cancer and is a modulator of chemotherapy responses (40). Thus, PDE3A could possibly activate multiple pathways, including the inflammatory signaling pathway or CCDC88A, which need to be explored further.

In the orthotopic xenograft model in mice, we found that PDE3A promoted breast cancer cells metastases, which were potentially mediated by the PDE3A–CCDC88A–EMT axis and PDE3A-inflammatory–stemness–metastisis microenvironment. Metastasis is a complex multistep process that involves early invasion and cancer stem cells (41, 42). Therefore, the support of metastasis by tumor inflammation, stemness, and the immune environment is rather inefficient, but these factors critically influence the ultimate outcome of metastasis (43). While our xenograft model has clearly demonstrated that PDE3A could promote breast cancer cell metastasis, future studies using the PDE3A transgenic mice model may further reveal the importance of PDE3A in breast cancer development.

Breast tumors are sensitive to the PDE3A inhibitor cilostazol, which suggests that targeting PDE3A may have broad clinical utility in breast cancer. The tumor-specific inhibitory effect of cilostazol is likely attributable to the dependence of tumor cells to high levels of PDE3A. The effect of cilostazol may also offer other therapeutic advantages over other anticancer therapies (44–47). Moreover, it has been demonstrated that liposomes containing cilostazol can prevent tumor cell–platelet interactions, which may provide a useful tool for the route of administration (48). In addition, cilostazol may protect the heart from being damaged by the chemotherapeutic drug doxorubicin.

In summary, our studies have demonstrated that the high level of PDE3A expression is associated with tumor stem cell–like properties and metastasis in breast cancer and thus provides insights on the therapeutic effect of the PDE3A inhibitor cilostazol on breast cancer. The PDE3A–CCDC88A–EMT axis and PDE3A–inflammatory–stemness–metastasis environment are thought to promote breast cancer metastasis and targeting PDE3A using the selective inhibitor cilostazol can suppress tumor growth and metastasis. Therefore, PDE3A plays an important role in tumor progression and is potentially a novel, effective, and specific target for breast cancer therapy. Thus, the findings of this study may have immediate implications on the development of novel breast cancer therapeutics.

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Authors' Contributions

Conception and design: N. Hao, R. Xiang, Y. Luo

Development of methodology: N. Hao, W. Shen, R. Du, Y. Chen, Y. Shi, Y. Luo

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): N. Hao, S. Jiang, J. Zhu

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): N. Hao, J. Zhu, Y. Shi, R. Xiang

Writing, review, and/or revision of the manuscript: N. Hao, R. Xiang

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): N. Hao, W. Shen, R. Du, C. Huang, Y. Shi, R. Xiang, Y. Luo

Study supervision: N. Hao, Y. Chen, R. Xiang, Y. Luo

Other (secured funding for the study): Y. Luo

Acknowledgments

We thank Dr. Xioayan Yuan, Department of Galactophore, People's Liberation Army General Hospital, Beijing, China, for the collection of breast cancer tissues and clinicopathologic data from patients with breast cancer. We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this article. We also thank the financial support from National Basic Research Program (973) of China (no. 2013CB967202; to Y. Luo); The National Natural Science Foundation of China (NSFC; no. 81472654, to Y. Luo; no.81502562, to C. Chen; no. 81372386, to X. Li; and no. 81273331, to R. Xiang); and The International Science and Technology Cooperation Program of China (KY201501006; to R. Xiang).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Footnotes

  • Note: Supplementary data for this article are available at Molecular Cancer Therapeutics Online (http://mct.aacrjournals.org/).

  • Mol Cancer Ther 2020;19:868–81

  • Received October 29, 2018.
  • Revision received February 19, 2019.
  • Accepted December 3, 2019.
  • Published first December 23, 2019.

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Phosphodiesterase 3A Represents a Therapeutic Target that Drives Stem Cell–like Property and Metastasis in Breast Cancer
Na Hao, Wenzhi Shen, Renle Du, Shan Jiang, Junyong Zhu, Yanan Chen, Chongbiao Huang, Yi Shi, Rong Xiang and Yunping Luo
Mol Cancer Ther March 1 2020 (19) (3) 868-881; DOI: 10.1158/1535-7163.MCT-18-1233
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