Background
Prostate cancer affects 1 in 6 males in their lifetime, and is the second leading cause of cancer death in men in the U.S. [
1]. Almost 2.8 million men are currently living with a diagnosis of prostate cancer [
2], yet the ability to discern whose cancer will progress to metastatic disease remains a challenge. A better understanding of the metastatic process could lead to enhanced prognostic ability and subsequent improvements in patient care and outcome. Cancer cells can escape the primary tumor via blood vessels or lymphatic vessels and travel to distant organs. The presence of tumor cell-positive lymph nodes from biopsy indicates the tumor has already spread from the primary site. Lymph node metastasis is an important prognostic indicator in many cancers, such as breast, melanoma and prostate [
3‐
6]. Lymph node metastasis correlates with poor prognosis in prostate cancer, as compared to those without lymph node involvement [
7]. Even before evidence of lymph node metastasis, lymphovascular invasion (LVI), defined as the unequivocal presence of tumor cells within an endothelium-lined space, can act as an independent risk factor in prostate cancer [
5]. Since all lymphatic drainage eventually empties into the venous system, tumor extravasation into lymphatic vessels may lead to more widespread metastasis via the vascular circulatory system to distant organs like bone [
8,
9].
As many patients now opt for an active surveillance or ‘watchful waiting’ period during the management of organ-confined disease [
10,
11], the development of new biomarkers and therapeutic options is greatly needed. The identification of genes important in the metastatic cascade may facilitate our development of such therapies.
Animal models of metastasis are important tools that allow us to interrogate steps in this process. Spontaneous and experimental models of metastasis in mice have allowed us to discover and analyze new genes and biomarkers and to test anti-cancer drugs within complex microenvironments. Studies have shown that when human cancer cell xenografts are implanted into the orthotopic site, as compared to an ectopic (usually subcutaneous) site, enhanced tumorigenicity and metastasis followed [
12‐
14]. The microenvironment is well documented to influence tumor cell behavior and is capable of stimulating or repressing cell plasticity, proliferation, migration and invasion [
15‐
17]. Orthotopically implanted tumor cells and their spontaneously metastasizing counterparts are exposed to many of the same environmental influences and selective pressures that human prostate cancer cells undergo in the prostate and lymph nodes. In addition, human xenografts allow one to interrogate the efficacy of human-specific drugs such as proteins (eg, interferons) or antibodies (eg, bevacizumab). Xenograft models provide a complement to genetically engineered mouse models which develop over a longer time and reside in an immunocompetent host but do not always capture all aspects of human cancer.
In vivo cycling of cancer cells has been demonstrated to be a useful method to select for highly aggressive cell lines. The human prostate cancer cell lines, PC-3 and LNCaP, were previously cycled
in vivo to select for highly metastatic variants from sentinel lymph node metastasis [
12,
18]. These human cancer models have proven highly beneficial to the prostate cancer research community [
19]. Herein, we describe a similar method to create a novel prostate cancer model developed in our laboratory using the DU145 human prostate cancer cell line. Originally isolated by Stone, et. al., from a human brain metastasis, DU145 is a “classical” and widely-used prostate cancer cell line [
20]. DU145 cells do not express detectable levels of prostate specific antigen and are not hormone sensitive.
This report describes the development and characterization of this model and our studies investigating molecular changes that correlate with metastatic potential.
Methods
Cell culture and transfection
DU145 human prostate cancer cells were obtained from ATCC (HTB-81) and maintained in high glucose DMEM with 10% fetal bovine serum (FBS), 1% glutamine, penicillin and streptomycin (GPS), and 1% sodium pyruvate (Invitrogen, Carlsbad, CA). Phase contrast microscopy was performed using a TE2000 microscope (Nikon) and RT SPOT camera with SPOT Advanced v4.0.9. software (Diagnostic Instruments, Inc., Sterling Heights, MI). Cells were transfected with siRNA using SilentFect (Biorad) in Opti-MEM I Reduced Serum Medium (Invitrogen), incubated for 4 hours, media changed, and cells used for assays at 48-72 hr. siRNAs were obtained from Thermo Scientific: ON-TARGETplus non-targeting control siRNA pool (D-001818-10-05), ON-TARGETplus human EPCAM siRNA pool (L-004568-01-0005), ON-TARGETplus human PLAU siRNA (L-006000-00-0005), ON-TARGETplus human ITGB4 siRNA pool (L-008011-00-0005). EPCAM and ITGB4 siRNAs were used at 30nM and PLAU siRNA used at 90nM for effective knockdown without toxicity.
Cell migration, invasion and proliferation assays
Cell migration was measured using Corning transwell inserts (BD Biosciences) with 8.0 μm pore polycarbonate membrane. Membranes were coated with Collagen I (BD Biosciences) at 100 μg/ml. 1% FBS in DMEM was used in the lower wells as chemoattractant. Cells were trypsinized, trypsin inactivated with soybean trypsin inhibitor and washed in DMEM. 6×104 cells were added to the top transwell chamber and allowed to migrate for 4 hours. Cells were fixed and stained with Diff-Quik (Fisher Scientific) and a cotton swab used to remove non-migrated cells from the upper chamber. Migrated cells were counted in 3–5 fields/well with 2–3 wells/condition. Cells were used for experiments 48 hours after transfection. For invasion assays, BD BioCoat Matrigel Invasion Chambers, with 8.0 μm pore PET membrane in 24-well cell culture inserts (BD Biosciences) were used with 5% FBS as the chemoattractant. Cells were allowed to invade for 12 hours and were fixed, stained and counted as described above. For uPA inhibitor experiments, cells were treated with 0.1% DMSO vehicle, 10 μM amiloride or UK122 (EMD Millipore, Billerica, MA). In vitro cell number was measured using CyQUANT Cell Proliferation Assay kit (Life Technologies). Cells were plated in a 96 well plate at 2.5×103 cells per well and incubated for 1–4 days. Plates were frozen and processed together at the end of the experiment. Fluorescent signal correlated with cell number and was measured with 450 nm excitation and 520 nm emission filters.
Western blot analysis
Whole cell lysates were collected in modified RIPA buffer with EGTA and EDTA (Boston Bioproducts, Ashland, MA) with protease inhibitor cocktail (P8340, Sigma-Aldrich). Conditioned media was collected from serum-free cell cultures, cells removed by centrifugation at 200 × g and protein concentrated using Amicon Ultra-15 3 kDa Centrifugal Filter Units (Millipore) at 3000 × g. Protein concentration was measured using a BCA (bicinchoninic acid) assay kit (Pierce/Thermo Scientific). Reduced protein in Laemmli sample buffer was resolved using SDS-PAGE and transferred to Immobilon-P 0.45 μm PVDF membrane (EMD Millipore, Billerica, MA). Membranes were blocked with 5% non-fat dry milk in PBS, incubated with primary antibody, followed by the appropriate secondary IgG antibody; sheep anti-mouse IgG HRP or donkey anti-rabbit IgG HRP linked (GE Healthcare). Membranes were washed thoroughly between steps using PBS containing 0.05% Tween-20, and developed using ECL Plus western blotting detection kit (GE Healthcare). Primary antibodies used for western blot analysis were as follows: EpCAM (C10, sc-25308), Integrin β4 (H-101, sc-9090), uPA (H-140, sc-14019) from Santa Cruz Biotechnology; AKT (#9272), p-AKT (#9271), S6K (#9202), p-S6K (#9205) from Cell Signaling. GAPDH (6C5) antibody was obtained from Abcam. Membranes were stripped using ReBlot Plus Strong Antibody stripping solution (EMD Millipore) before reprobing.
Immunohistochemistry
Paraffin-embedded tumor tissue and lymph nodes were dewaxed, rehydrated, and stained with hematoxylin and eosin (H&E) or immunostained to detect human cytokeratin-18 (K18, Epitomics), EpCAM (Santa Cruz), E-Cadherin (BD Bioscience), mouse blood vessels (CD31, Pharmingen), or mouse lymphatic vessels (podoplanin, Reliatech). Antigen retrieval was performed with boiling citrate buffer (pH 6) for K18, EpCAM and E-cadherin or with proteinase K for podoplanin and CD31. Endogenous peroxidases were blocked with 3% peroxide in methanol. Tissues were blocked using normal serum and incubated with primary antibodies overnight at 4°C, biotinylated secondary antibodies (Vector Laboratories, Burlingame, CA) for one hour, and Vectastain Elite (avidin-HRP; Vector) for 30 min, and finally developed with diaminobenzidine chromogen (DAB, Vector). To detect human epithelial cell metastases, sentinel lymph node sections were stained with K18, counterstained with hematoxylin, examined by microscopy and K18-positive cells in small foci were scored as metastases. Single K18-positive cells in the lymph node were not scored as metastases. Three different tissue levels from each of two lymph nodes (when available) were examined per mouse.
In vivotumor experiments
Eight week old male Balb/c Nu/Nu mice were purchased from Massachusetts General Hospital and housed in the Animal Resource at Children’s Hospital (ARCH) facility accredited by the American Association for Accreditation of Laboratory Animal Care (AAALAC). All experiments were conducted in accordance with the principles and procedures outlined in the NIH Guide for the Care and Use of Laboratory Animals and approved by an Institutional Animal Care and Use Committee (IACUC) at Boston Children’s Hospital. For orthotopic prostate injections, mice were anesthetized and an abdominal incision was made to expose the prostate. 2×106 cells ( suspended in 40 μl HBSS) were injected into the prostate using a Hamilton mini-injector, and the incision was closed with 9 mm wound clips. Tumor growth was monitored by palpation. After 4–12 weeks (5 weeks for direct comparison experiment), mice were sacrificed and necropsied. Tumors (and lymph nodes in 5 wk experiment) were removed, weighed and measured with calipers, fixed in formalin and processed for paraffin blocks. Orthotopic tumor volumes were calculated as widthSuperscript> × /Superscript> × length × 0.5. Sentinel paraaortic lymph nodes were washed with PBS, filtered through a 100 μm cell strainer (BD Biosciences), and plated in complete media on tissue culture dishes. The following day, cells were washed thoroughly with PBS, replaced with fresh complete media and re-named DU145-LN1 (from lymph node). After expansion in culture, in vivo orthotopic prostate injection was repeated for additional rounds of selection with subsequent cells named DU145-LN2, then DU145-LN3, and finally DU145-LN4.
For skin tumors, 5×106 cells were injected subcutaneously into the right dorsal flank of 8 week old male Balb/c Nu/Nu mice. Tumor size was measured externally with calipers, and tumor volume was calculated as V = widthSuperscript> × /Superscript> × length × 0.5.
Gene expression analysis
RNA for cDNA microarray analysis was purified using RNeasy mini kits (Qiagen). Purity and integrity was confirmed by spectrophotometer and agarose gel. Total RNA was labeled and amplified according to manufacturer’s instructions by the Microarray Core Facility of the Molecular Genetics Core Facility at Boston Children’s Hospital supported by NIH-P50-NS40828 and NIH-P30-HD18655. DU145, DU145-LN1, DU145-LN2 and DU145-LN4 RNA samples were run on Illumina HumanRef-8 BeadChips (Illumina, San Diego, CA). Raw data were analyzed in BRB-ArrayTools (Biometric Research Branch, National Cancer Institute, Bethesda, MD, USA,
http://linus.nci.nih.gov/BRB-ArrayTools.html).
Signal intensity data was subject to rank invariant normalization. Duplicated probes on the array were treated independently during normalization and statistical analyses. Negative or low intensity signals <10 were corrected to 10 to prevent extreme fold change artifacts.
Samples were subject to Hierarchical cluster analysis using Euclidian distance. Differentially expressed genes were identified using a time course analysis (DU145 as time = 0, and DU145LN1, LN2 and LN4 as time = 1, 2 and 3 respectively), with a cut-off minimum of 1.5-fold change in DU145-LN4 relative to DU145. For functional gene analysis, the entire dataset was imported into Ingenuity IPA Network Analysis software (Ingenuity Systems, Redwood City, CA), and we selected Cancer and Cellular Movement categories for further analysis. Cluster analysis of the relationship between cell types within these categories or of the entire gene probe population using one minus Pearson correlation, produced essentially indistinguishable dendrograms. We cross-referenced back to probe intensity values and genes were removed if all data points had low intensities of <100 Arbitrary Intensity Units. Selected genes were represented by heat map using GENE-E software (
http://www.broadinstitute.org/cancer/software/GENE-E). For analysis of Cell Signaling, data were excluded if Illumina probe values were negative, <10, or less than the probe signal in the control group (DU145).
Statistical analyses
Data from cell proliferation, migration and invasion assays were analyzed using unpaired two-sample student’s t-test. Statistical significance was considered at p ≤ 0.05. Specific p-values for each experiment are indicated in Figure Legends.
Discussion
Our goal was to create a new reliable human prostate cancer model system that would use human prostate tumor cells and result in rapidly growing (non-necrotic) tumors in 100% of the mice injected and consistently recapitulate the invasive and metastatic properties seen in patients. Many prostate cancer research studies use one of three human cell lines: PC3, LNCaP or DU145. While each cell line has its benefits and drawbacks, we focused on the DU145 cell line since it did not have well-used metastatic sublines reported in the literature. In our search for metastasis-related pathways, we had also wanted to select an androgen independent cell line. These cells grow robustly
in vitro and express many prostate and epithelial markers, yet they grow poorly in mice even when injected into the mouse prostate gland. Therefore, many labs resort to injecting high numbers (>2×10
6) of cells and co-injecting ECM components or fibroblasts to enhance tumor-take and angiogenic potential. We chose to select for highly metastatic variants of DU145 using an
in vivo cycling strategy that was previously successful for PC-3 M and LNCaP [
12,
18].
Herein, we have presented the establishment and characterization of our new model of human prostate cancer, the DU145-LN metastatic series. The DU145-LN cells show enhanced
in vivo growth as well as migratory, invasive and metastatic abilities. These cell lines represent new tools to explore the process of metastasis. Our approach to developing the DU145-LN metastatic series via spontaneous metastasis from orthotopic organ sites provided the tumor with appropriate micro-environmental signals [
14]. Cells with the ability to spontaneously metastasize from the prostate tumor and survive in the lymph node were repeatedly selected. The role of lymphatic versus hematologic metastasis has been debated [
24,
25]. However, the presence of tumor-positive lymph nodes continues to be an important predictor of distant metastases and patient survival in many cancers [
9,
26]. Studies have shown that lymphovascular invasion is significantly associated with PSA biochemical recurrence and patient survival in prostate cancer [
5,
27], although LVI may not significantly improve predictive accuracy above standard clinicopathological features in prostate cancer [
11]. We clearly observed tumor foci in the enlarged lymphatics of the DU145-LN4 orthotopic tumors, indicating that our model recapitulates steps common in human prostate cancer progression.
After completing four rounds of cycling the DU145 cells in mice (prostate to lymph node), we compared all five cell lines in a head-to-head comparison for tumorigenicity and metastatic potential in a 5 week period (Figure
1 shows gross images of resulting tumors). DU145 was poorly angiogenic and had a low vascular density, therefore resulting in small tumors. Cycled tumors had higher microvessel densities, and vessel density has been shown to correlate with metastatic potential in human prostate cancer [
28]. In addition, the DU145-LN4 tumors had increased lymphangiogenesis surrounding the tumors and invasive leading edges. Lymphangiogenesis has been shown to be an important mechanism of prostate cancer metastasis [
26,
29], and has been our focus in this study.
Most human prostate cancer cells do not grow well subcutaneously; however, our new DU145-LN2 cell line represents a useful and rapid non-surgical xenograft model for tumor growth studies in the skin, e.g. drug screening. Metastatic cycling of DU145 prostate cancer cells also resulted in cells that were more motile and invasive. By examining the gene expression profiles of these cells we revealed many genes correlating with their metastatic ability. In this report we have demonstrated the involvement of EpCAM, integrin β4 and uPA in tumor cell migration and/or invasion--key steps in the metastatic cascade. Although each of these genes may not be individually competent to induce metastasis in parental cells, we propose that our model represents a valuable and relevant system, as the genes we have identified have been shown to be clinically important in prostate cancer.
EpCAM (also known as CD326) is well established as a tumor marker in many carcinomas, and is widely used to purify circulating tumor cells from blood [
30]. EpCAM is a transmembrane glycoprotein and has diverse functions in cell-cell adhesion, migration, proliferation and differentiation [
31]. In human prostate cancer, several tissue studies have shown upregulated EpCAM in the tumor epithelium and in metastatic lesions [
32‐
35]. EpCAM expression in prostate tumor tissue is also a significant predictor of shorter biochemical recurrence free-survival [
35]. The mechanism of EpCAM activity has not yet been well defined. EpCAM can be cleaved in its ectodomain to release an extracellular fragment, (EpEX) and this may affect E-cadherin mediated cell-cell adhesion [
36]. It is possible that this fragment may be involved in the increased migration and invasion observed in the DU145-LN4 cells. High expression of the epithelial marker E-cadherin has been associated with stronger cell-cell interaction and subsequent reduced cell motility [
36]. However, the presence of EpEX may modulate this role. Our Western blot analysis (Figure
5B) indicates that both full length EpCAM and EpEX is present at high levels in the DU145-LN4 (and DU145-LN2) cells. EpCAM also associates with the tight junction protein, claudin 7, to promote tumor cell migration rather than cell-cell adhesion that leads to lymphatic spread [
37]. Claudin 7 expression was also dramatically upregulated in the DU145-LN cell series in microarray data (relative to DU145, DU145-LN1 had 9.6X, DU145-LN2 had 21X and DU145-LN4 had 28X fold higher claudin-7 expression). Antisense knockdown of either EpCAM or claudin-7 reduces tumor growth and metastasis in mice, and knockdown of both is more effective [
38].
The cell surface EpCAM complexes can also involve an additional partner identified in our gene expression analysis, β4 integrin. In normal epithelial cells α
6β
4 resides in hemidesmosomes. In tumor cells, integrin β4 can relocate from hemiodesmosomes to the leading edge of migrating cells where it is involved in the signaling of many receptor tyrosine kinases, including ErbB2, ErbB3, EGFR and Met [
39‐
41]. β4 integrin therefore impacts cell signaling, migration and invasion through multiple pathways. β4 expression also influences multiple miRNAs impacting cell motility [
42]. High levels of β4-integrin have been found across many prostate cancer tissue expression studies, and in metastatic and castrate-resistant prostate cancer metastases [
41]. Transgenic mice with a β4-integrin signaling domain
mutation showed reduced prostate tumor formation and progression, thus supporting our data that ITGB4 is involved in tumor cell migration and metastasis [
41].
We also showed that uPA expression positively correlated with metastatic potential in the DU145-LN cell series. uPA silencing significantly inhibited both tumor cell migration and invasion. Serine proteases, such as uPA play an important role in tumor progression. By degrading the extracellular matrix and basement membrane they can promote cell invasion, angiogenesis and metastasis [
43]. Circulating levels of uPA, and its receptor uPAR (urokinase-type plasminogen activator receptor), are significantly elevated in prostate cancer patients, and are higher in patients with lymph node and bone metastases, compared to those with non-metastatic disease [
44,
45]. uPA and uPAR levels correlate with Gleason score, extracapsular extension, LVI, seminal vesicle and lymph node invasion and are also associated with biochemical progression and poor prognosis [
45,
46]. Both uPA and uPAR are involved in Matrigel invasion in PC-3 cells [
47,
48], and RNAi or shRNA knockdown of uPA and uPAR reduced orthotopic prostate tumor size via apoptosis. In DU145 cells, uPAR over-expression increased Matrigel invasion
in vitro which was inhibited by uPA antibody or inhibitor. In addition, stable overexpression of uPAR was accompanied by uPA upregulation [
49], providing additional evidence for the interdependence of the protease and receptor activities.
The uPA protease axis appears to play an important role in the invasive and metastatic behavior of our metastatic model. The uPA receptor, uPAR (gene name PLAUR) also showed increased gene expression as DU145 cells become more metastatic; with 1.3X fold increased expression in LN1, 2.0X fold in LN2, and 2.7X fold in LN4, relative to parental DU145 cells. Furthermore, one of the key activators of uPA activity is the protease Matriptase (gene name ST14). Matriptase was also highly upregulated in our model of prostate cancer metastasis; 4.5X fold in DU145-LN1, 11X fold in DU145-LN2 and 16X fold increased in DU145-LN4, relative to DU145 (Figure
5A). Antagonists of the uPA/uPAR axis have been suggested for use as anti-tumor agents with targeted monoclonal antibodies and nanoparticles currently under development [
50].
Our model has identified a network of gene and pathway changes spontaneously arising as cells became more metastatic. These include EpCAM, β4-integrin and uPA. Clearly many of these pathways may interact and feedback upon each other. There may be master regulators in this system, such as transcription factors and/or microRNAs that influence expression of these and many other genes. Indeed, ZEB1 has been reported to regulate EpCAM, β4-integrin and uPA [
51‐
53]. In turn, the miR-200 family regulates the epithelial phenotype and ZEB1 [
54‐
56]. In addition, there are other transcription factors related to cancer and cell movement that are significantly upregulated in this model, including ELF3 (8.7X higher in DU145-LN4) and ETV4 (7.5X fold higher level in DU145-LN4 compared to DU145 cells). These and other genes may present new targets for intervention in metastatic cell behavior.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
JB conceived of the study, developed the animal model and cell lines, performed microarray analyses and wrote the manuscript; IC participated in in vivo experiments and edited the manuscript; MM performed immunohistochemistry; DTP carried out the migration, invasion and western blotting; AMW performed the proliferation assay, immunohistochemistry and participated in subcutaneous tumor experiments. BRZ participated in study design and edited the manuscript. DRB conceived of the study, developed the animal model and cell lines, performed immunohistochemistry and western blotting, and edited the manuscript. All authors read and approved the final manuscript.