Abstract
Clear cell renal cell carcinoma (ccRCC) remains a common cause of cancer mortality. Better understanding of ccRCC molecular drivers resulted in the development of antiangiogenic therapies that block the blood vessels that supply tumors with nutrients for growth and metastasis. Unfortunately, most ccRCC patients eventually become resistant to initial treatments, creating a need for alternative treatment options. We investigated the role of the small GTPase Rac1 in ccRCC. Analysis of ccRCC clinical samples indicates that Rac signaling drives disease progression and predicts patients with poorer outcomes. Investigation of Rac1 identifies multiple roles for Rac1 in the pathogenesis of ccRCC. Rac1 is overexpressed in RCC cell lines and drives proliferation and migratory/metastatic potential. Rac1 is also critical for endothelial cells to grow and form endothelial tubular networks potentiated by angiogenic factors. Importantly, Rac1 controls paracrine signaling of angiogenic factors including VEGF from renal carcinoma cells to surrounding blood vessels. A novel Rac1 inhibitor impaired the growth and migratory potential of both renal carcinoma cells and endothelial cells and reduced VEGF production by RCC cells, thereby limiting paracrine signaling both in vitro and in vivo. Lastly, Rac1 was shown to be downstream of VEGF receptor (VEGFR) signaling and required for activation of MAPK signaling. In combination with VEGFR2 inhibitors, Rac inhibition provides enhanced suppression of angiogenesis. Therefore, targeting Rac in ccRCC has the potential to block the growth of tumor cells, endothelial cell recruitment, and paracrine signaling from tumor cells to other cells in the tumor microenvironment.
Introduction
The incidence and mortality of renal cell carcinoma (RCC) increased worldwide to 403,000 new cases and 175,000 deaths estimated in 2018 (1). Clear cell renal cell carcinoma (ccRCC) accounts for 80% of all RCC (2). Studies of hereditary and sporadic ccRCCs identify loss of the von Hippel–Lindau (VHL) tumor-suppressor gene as critical through a mechanism involving hypoxia-inducible factor (HIF)(3). VEGF, a HIF-regulated gene, is a potent stimulator of new blood vessel formation (4).
Angiogenesis is required for tumors to obtain oxygen and nutrients for growth (5). Proangiogenic growth factors such as VEGF and basic fibroblast growth factor (bFGF) bind to receptors on endothelial cells and entice vessel branching and growth toward concentration gradients within tumors (6).
This led to the use of small-molecule inhibitors such as sunitinib that target the VEGF receptor family (VEGFR1–3; ref. 7). Unfortunately, up to 20% of ccRCC patients show de novo resistance to VEGFR inhibitors, and patients who do respond become resistant (8). Mechanisms of resistance have yet to be elucidated (9). Next-generation sequencing has provided insight into the genetic complexity of ccRCCs. Only 56% of ccRCC harbor VHL alterations, which may explain why antiangiogenic treatment fails (10). Elucidation of alternative drivers of ccRCC may allow novel therapeutic options for patient treatment.
Rac1, a Rho family GTPase that act as a molecular switch, cycles between the active, GTP-bound, and inactive, GDP-bound state (11). Levels of activated Rac1 are tightly regulated by guanine nucleotide exchange factors (GEF), GTPase-activating proteins, and protein stability through proteasomal degradation. In fact, HECT domain and ankyrin repeat containing E3 ubiquitin ligase 1 (HACE1), the E3 ubiquitin ligase for Rac1, was first discovered in Wilms' tumor, an RCC of childhood (12). HACE1 is lost in multiple cancers resulting in the accumulation of activated Rac1 (13, 14).
Rac1 is involved in numerous cellular functions such as migration and invasion, adhesion, proliferation, cellular metabolism, evasion of apoptosis, and reactive oxygen species (ROS) production (15). Hyperactivation of the Rac signaling pathway is common in human cancers and drives tumor initiation, progression, and metastatic dissemination. Overexpression/amplification of Rac1 has been observed in breast cancer, prostate cancer, ovarian cancer, lung cancer, nasopharyngeal carcinoma, leukemia, and gastric cancer (16–20). Hyperactivation of Rac signaling has been implicated in resistance to chemotherapy, radiotherapy, and therapies targeting the EGFR/HER2 family of receptors and BRAF (21–25). Lastly, Rac has been shown to play a role in resistance to bevacizumab, an anti-VEGF therapy (26), suggesting the combinational approach of combining VEGF/VEGFR-targeted therapies with a Rac inhibitor may improve the effectiveness of antiangiogenic therapies.
We investigated Rac signaling in ccRCC and found multiple aberrations of the signaling pathway leading to hyperactivation potentiating aggressive disease and poor patient outcomes. Using molecular and pharmaceutical based approaches, we show that ccRCC is highly susceptible to Rac1 blockade both in vitro and in vivo. We also show that Rac targeting attenuates angiogenesis by directly affecting endothelial cells. Lastly, we show that Rac1 plays a role in the production of angiogenic growth factors in ccRCC and that systemic treatment with a Rac inhibitor can indirectly attenuate the angiogenic response.
Materials and Methods
Cell lines and cell culture
Caki-1 and 786-O cells were purchased from ATCC and cultured in McCoy's 5A, and 769-P cells were purchased from ATCC and cultured in RPMI media. HEK293T cells were cultured in DMEM. Caki-1, 786-O, 769-P, and HEK293T cell media were supplemented with 5% (v/v) fetal bovine serum (Invitrogen). HUVECs were purchased from Lonza and grown in Endothelial Cell Growth Media 2. Cells were cultured at 37°C in a humidified atmosphere of 5% CO2. Mycoplasma testing (Lonza) was conducted every 5 cell passages. GYS32661(21) was manufactured by Patheon. Sunitinib was purchased from Selleckchem.
Transfection
For the transient knockdown of Rac1, SilencerValidated Human RAC1 siRNA oligos (cat. # AM51334) along with negative control siRNA (cat. # AM4611) were purchased from Ambion. siRNAs were transfected using RNAiMax (Invitrogen). HACE1 was cloned in pLv105 lentiviral vector (Genecopoeia), and pLv105 Empty Vector was used to generate stable cell lines. The vectors were cotransfected with plasmid psPAX and pMD2G plasmids into 293T cells using Lipofectamine 2000 (Invitrogen). Viral supernatant was collected 48 hours after transfection, filtered (0.45-μm pore size), and added to cells in the presence of 8 μg/mL polybrene (Sigma-Aldrich). Puromycin (2 μg/mL) was used for selection. Viral supernatant was added to the cells, and stable clones were selected for puromycin resistance.
The Cancer Genome Atlas data mining
The clear cell renal carcinoma data set (KIRC) was accessed and mined through the Cancer Genome Atlas (TCGA) Research Network (Provisional 2017; http://cancergenome.nih.gov/). Kaplan–Meier curves from TCGA-KIRC data sets were generated using KMPLOT (27).
Immunoblot assays
Cell lysates were prepared in RIPA lysis buffer. Blots were probed with Rac1 (1:1,000 Millipore, clone 23A8), HACE1 (1:1,000 abcam, EPR7962), p44/42 MAPK (Erk1/2; 1:5,000 Cell Signaling Technology, #4695), phospho-p44/42 MAPK (Erk1/2; 1:1,000 Cell Signaling Technology, #4370), phospho-VEGF receptor 2 (Tyr1175; 1:1,000 Cell Signaling Technology, #2478), and Cyclin D1 (1:5,000 Abcam, EPR2241) antibodies. Fluorescent tag anti-rabbit (LI-COR) and anti-mouse (LI-COR) secondary antibodies were used. Signal was detected using LI-COR. Blots were reprobed with an anti-actin (Abcam) antibody.
Rac pulldown experiments
GTP-bound Rac1 levels were determined using a Rac1 activation assay kit according to the manufacturer's protocol (Pierce Biotechnology). Cells were washed in cold PBS and lysed on ice in 600 μL lysis buffer. Total lysates were cleared by centrifugation. An equal amount of lysate was incubated for 30 minutes at 4°C with PAK binding domain agarose beads. Precipitated complexes were washed thrice with lysis buffer. After the final wash, the supernatant was discarded, and 40 μL of 2× Laemmli buffer were added to the beads. Total lysates and precipitates were then analyzed by Western blot.
Proliferation assay
Cells (1 × 103) were cultured in 6-well cell culture plates in triplicate. The cells were trypsinized and counted with hemocytometer for 3 to 6 consecutive days.
Migration assays
Cells were seeded in the upper compartment of a 24-well Boyden-Chamber (8-μm pore size; Costar) and allowed to migrate for 16 hours in response to complete media in the lower compartment. The cells that migrated to the underside of the filter were stained with crystal violet and counted under bright-field microscopy.
Soft-agar assay
The soft-agar colony-forming assay was performed in 6-well plates with a base of 2 mL of medium containing 5% FBS with 0.6% agar (Amresco). Cells were seeded in 2 mL of medium containing 5% FBS with 0.35% agar at 1 × 103 cells/well and layered onto the base. Two milliliters of media with 5% FBS was covered on the top of agar gel. The photographs of colonies growing in the plates were taken and scored using ImageJ.
Cytotoxicity assays
Cells were plated in 96-well plates (5,000 cells per well), and 24 hours later, various concentrations of GYS32661 were added and incubated for 3 days. Cytotoxicity was measured using a standard PrestoBlue dye (Invitrogen).
Tube formation assays
Tube formation assays were done as previously described (28). Briefly, HUVECs were seeded on growth factor–reduced Matrigel (Corning) in 48-well plates and supplemented with 10 ng/mL VEGF165 (PeproTech) or EGM-2. Cells were incubated for 4 to 6 hours, after which wells were photographed at 40× magnification with a Nikon TS100 microscope. Tube formation was quantified by counting the number of branching points.
Endothelial cell–fibroblast coculture assays
Coculture assays were performed as previously described (29). Briefly, human dermal fibroblasts (Lonza) were seeded in 24-well plates. Once confluent, HUVECs were seeded in serum-free media. Cells were incubated for 12 days, after which cells were fixed with methanol. After blocking, wells were incubated with rabbit anti-CD31/PECAM-1 antibody (Abcam, diluted 1:200) overnight at 4°C. After incubation with secondary antibody (Vector Labs) the cells were developed with diaminobenzidine tetrahydrochloride (DAB, Vector Labs). Cells were counterstained with hematoxylin, and photographed at 20× magnification with a Nikon TS100 microscope. Tube formation was quantified by counting the number of branching points.
Ex vivo angiogenesis assay
Aortic ring assays were performed as previously described (30). Briefly, the abdominal aortas were isolated and cut into 1-mm sections that were embedded in growth factor–reduced Matrigel and cultured in EGM-2 containing assay conditions. Images were acquired with a Nikon TS100 microscope. The sprouting area was determined using the SWIFT-Choroid method to quantify the area of the sprouts (31).
Matrigel plug assays
Matrigel Plug assays were performed as previously described (30). In brief, mice were injected subcutaneously on the flank with 400 μL growth factor–reduced Matrigel containing 400 ng of human recombinant bFGF (Millipore). After 5 days, mice were injected intravenously with 20 ng FITC-conjugated lectin that binds selectively to mouse ECs (GSL I-BSL I; Vector Laboratories). The Matrigel plugs were removed, photographed, and homogenized, and the fluorescent content was read at 620 nmol/L (Tecan M1000).
Reverse phase protein assays
Media were collected from cells after 48-hour incubation at 37°C and centrifuged for 5 minutes at 10,000 × g to remove cellular debris. Human Angiogenesis Antibody Array (R&D Systems; ARY007) was probed according to the manufacturer's instructions. Heat map of data was generated using Displayr.
VEGF ELISA assays
Media were collected from cells after 48-hour incubation at 37°C and centrifuged for 5 minutes at 10,000 × g to remove cellular debris. A human VEGF ELISA kit was purchased from Thermo Fisher (cat. # KHG0111). Conditioned media were analyzed according to the manufacturer's instructions.
ccRCC xenograft assays
Adult (8–10 weeks of age) SCID mice were used for xenograft studies. Caki-1 and 786-O (1 × 106 cells) were injected subcutaneously into the left flank of the mice. When the tumors reached approximately 100–150 mm3, mice were divided into treatment groups (N = 5). Saline was used as the vehicle control. The sunitinib treatment group was dosed orally with 30 mg/kg 5 days per week. The GYS32661 treatment group was injected intraperitoneally 30 mg/kg for 5 days per week. The combination treatment groups received sunitinib (30 mg/kg, 5 days per week) and GYS32661 (30 mg/kg, 5 days per week). The control group received saline intraperitoneally. Tumor volume and body weight were measured every 3 days. Tumor volume was calculated using the formula V = (AB2)/2, where A is the largest diameter and B is the smallest diameter. Animal work was conducted under an approved IACUC protocol from the University of Miami Miller School of Medicine.
Immunohistochemistry
Immunohistochemical staining for HACE1 was performed on kidney clear cell carcinoma tissue microarrays (US Biomax). Slides were deparaffinized with xylene and then hydrated in an ethanol series. Antigen retrieval was done by using citrate buffer solution (pH 6.0) for 30 minutes at 95°C. The endogenous peroxidase activity was blocked using hydrogen peroxide. The tissues were blocked with an avidin–biotin blocking system (Vector Laboratories). After blocking, slides were incubated with rabbit anti-HACE1 antibody (Ventana, diluted 1:1,000) overnight at 4°C. After incubation with secondary antibody (Vector Labs), the slides were developed with diaminobenzidine tetrahydrochloride (DAB, Vector Labs). Slides were counterstained with hematoxylin. The immunohistochemical slides were scanned into high-resolution images using the Olympus VS120. All digital images obtained in .svs format were visualized with Olympus software. Each TMA spot was examined by two independent reviewers who assigned a score of 0 (no staining), 1 (<10% of malignant cells staining), 2 (10%–50% of malignant cells staining), or 3 (>50% of malignant cells staining) within carcinomatous areas. Immunohistochemistry staining of FFPE from tumors collected at experimental endpoint for CD31 (Abcam, 1:100), VEGFA (Cell Signaling Technology, 1:100), and phospho-VEGFR2 (Cell Signaling Technology, 1:100) were conducted as described above. CD31+ blood vessels were counted, and microvessel density (MVD) was scored. For VEGFA and phosphor-VEGFR2 staining was assigned a score of 0 (<10% of field stained), 1 (10%–25% of field stained), 2 (25%–50% of field stained), 3 (50%–75% of field stained), or 4 (>50% of field stained).
Statistical analysis
Data are expressed as mean ± SEM of n = 3 unless otherwise stated. Differences between 2 groups and multiple groups were analyzed by two-tailed Student t test and one-way ANOVA, respectively. P value of less than 0.05 was considered statistically significant. *, P < 0.05; **, P < 0.005; ***, P <0.0005.
Results
Rac1 is overexpressed in ccRCC and predicts poor patient survival
Rac1 is overexpressed in many cancers and contributes to disease progression and metastatic dissemination (32). TCGA has allowed investigations of clinical associations for gene alterations in ccRCC (TCGA-KIRC; ref. 10).
We queried Rac1 levels in TCGA-KIRC data set consisting of 534 ccRCC patients and 72 normal kidney samples (Fig. 1A). Compared with normal kidney, Rac1 was significantly upregulated in ccRCC. This was confirmed in an additional clinical data set (Supplementary Fig. S1A). Rac1 DNA copy-number analysis indicated that overexpression was mainly due to Rac1 amplifications (Supplementary Fig. S1B). Interestingly, although expressed at lower levels, Rac2, which has been implicated in hematopoietic cells, was also upregulated (Supplementary Fig. S1C). Among the Rac family members, Rac1 had the highest expression in ccRCC. Elevated expression of numerous Rac GEFs such as TIAM1, TRIO, VAV1, and PREX1 was also observed (Supplementary Fig. S1D). These data support the role of activated Rac1 contributing to disease progression in ccRCC. Elevated Rac1 levels are also associated with poorer overall survival outcomes (Fig. 1B). Rac1 levels were found to be highest in patients with stage IV disease (Supplementary Fig. S1E).
To confirm Rac1 drives aggressiveness in ccRCC, Rac1 was knocked down in Caki-1, human ccRCC cells, using siRNA targeting Rac1. Transfection of Rac1 siRNA (siRac1) at 25 nmol/L effectively knocked down Rac1 compared with nonsilencing control (siNSC; Fig. 1C). As Rac1 is canonically involved in motility, we tested the effects of Rac1 knockdown in cells transfected with siNSC or siRac1 in a Boyden-Chamber migration assay. Knockdown of Rac1 reduced the migratory potential of Caki-1 cells by more than half (Fig. 1D). Rac1 knockdown in another ccRCC cell line, 786-O, also significantly reduced migration (Supplementary Fig. S1F).
Rac1 also plays a role in enhanced cellular proliferation (33). The knockdown of Rac1 in Caki-1 cells (Fig. 1E) and 786-O cells (Supplementary Fig. S1G) showed significant growth reduction. Rac1 contributes to enhanced proliferation by regulating levels of CyclinD1, an important regulator of cell-cycle progression (34). Cyclin D1 levels were reduced upon Rac1 knockdown (Fig. 1F). These data suggest Rac1 is upregulated during transformation of normal kidney to ccRCC and contributes to migration and disease progression.
Loss of HACE1 in ccRCC results in hyperactivation of Rac signaling
HACE1 loss in breast cancer resulted in accumulation of activated Rac1 (14). To determine if HACE1 was reduced in ccRCC, we investigated TCGA-KIRC data set. HACE1 expression was significantly reduced in ccRCC tumors compared with normal kidney (Fig. 2A). Interestingly, a statistically significant relationship between Rac1 and HACE1 expression in TCGA-KIRC data set was observed (Supplementary Fig. S2A). Normal adjacent kidney tissue showed strong HACE1 immunohistochemistry staining (Fig. 2B), which was concordant with the TCGA-KIRC data, whereas ccRCC samples showed a marked reduction in HACE1 (Fig. 2C). Survival rates were investigated in patients from TCGA-KIRC data set. Patients were dichotomized into high and low HACE1 expression (Fig. 2D). Patients with low HACE1 expression in tumors had poor survival with a hazard ratio of 0.6 (log-rank P = 0.0013). Therefore, HACE1 is commonly lost during the progression from normal kidney to ccRCC, and HACE1 loss correlates with poor patient survival.
To study the effects of HACE1 loss, a panel of RCC cells along with normal human embryonic kidney (HEK293T) cells was probed for HACE1 protein levels (Fig. 2E). RCC cells have lower HACE1 levels compared with the normal control cell line. Knockdown of HACE1 in normal kidney cells leads to tumors in mice (13). To investigate HACE1 overexpression in ccRCC, HACE1 or empty-vector (EV) controls were stably overexpressed in Caki-1 and 786-O cells. Active Rac1 was detected by Rac1-GTP pulldown assays. HACE1 overexpression dramatically reduced levels of active Rac1 in Caki-1 cells (Fig. 2F) and 786-O cells (Supplementary Fig. S2B). Therefore, HACE1 attenuates active levels of Rac1 in ccRCC.
To determine whether HACE1 overexpression inhibits cellular motility, we performed Boyden-Chamber migration assays. Caki-1 EV cells easily migrated, whereas Caki-1 cells overexpressing HACE1 showed a greater than 75% reduction in migratory (Fig. 2G). Similar findings were observed in 786-O cells (Supplementary Fig. S2C).
Overexpression of HACE1 has also been shown to reduce cellular proliferation in 2D and 3D growth assays (14). HACE1 overexpression in Caki-1 cells significantly impaired cellular proliferation (Fig. 2H) as well as in 786-O cells (Supplementary Fig. S2D). To observe the effects of HACE1 overexpression on RCC anchorage-independent growth, control Caki-1 and HACE1-overexpressing cells were seeded in soft agar. Overexpression of HACE1 decreased anchorage-independent growth by 97% (Fig. 2I). Similar results were observed in 786-O cells (Supplementary Fig. S2E). Taken together, HACE1 levels are decreased during transformation from normal kidney to ccRCC, resulting in the accumulation of activated Rac1 leading to enhanced proliferation and migration.
Rac inhibition as an alternative treatment option for ccRCC
We recently characterized a novel Rac inhibitor (GYS32661) as highly effective in treating colorectal cancer (21). A panel of RCC cells was treated with the Rac inhibitor, and cellular viability assays were performed (Fig. 3A). All cell lines were sensitive to Rac inhibition, with Caki-1 cells being most sensitive (IC50 of 5.8 μmol/L). To confirm Rac1 was inhibited, Rac activation assays were performed on 769-P, 786-O, and Caki-1 cells in the presence of GYS32661 (Fig. 3B–D). GYS32661 showed strong inhibition of Rac1 as determined by Rac1-GTP pulldown. Next, to confirm the treatment with GYS32661 pheno-copied the effects of knockdown of Rac1, cellular proliferation assays were conducted on Caki-1 cells (Fig. 3E) and 786-O cells (Supplementary Fig. S3A) treated with GYS32661 or vehicle. GYS32661 inhibited both cell lines in a dose-dependent manner. Boyden-Chamber migration assays on Caki-1 cells (Fig. 3F) and 786-O cells (Fig. 3G) treated with GYS32661 or vehicle indicated Rac inhibition significantly impairs motility compared with vehicle treated cells. Next, we confirmed the Rac inhibitor attenuated anchorage-independent growth in soft agar. A dose-dependent inhibition of soft-agar growth was observed in 786-O cells (Fig. 3H) and Caki-1 cells (Fig. 3I) with activity observed at concentrations as low as 2.5 μmol/L. Taken together, GYS32661 shows strong inhibition of Rac1 and reduces migratory ability, soft-agar growth, and cellular viability of ccRCC cells in vitro.
786-O cells were inoculated into mice and randomized into treatment groups once tumors were palpable. The Rac inhibitor treatment arm was compared with a vehicle control arm along with a VEGFR2 inhibitor, sunitinib (Sutent; Fig. 3J). Animals treated with sunitinib showed a significant reduction of tumor growth. GYS32661 treated animals also showed significant reduction in tumor growth comparable with the sunitinib arm with intratumoral concentrations reaching 10 μmol/L (Supplementary Fig. S3B). Thus, Rac inhibition is an effective therapeutic option in the treatment of ccRCC.
Rac inhibition blocks in vitro and in vivo angiogenesis
ccRCCs secrete numerous angiogenic growth factors such as VEGFA (35). Antiangiogenic therapies are successful in treating ccRCC. Angiogenic factors such as VEGFA induce the sprouting of new blood vessels off of preexisting ones (36). After sprouting, endothelial cells migrate outward, proliferate, and form new tubular structures (37). Rac1 has been suggested to play a role in angiogenesis (28). To determine the dependency of angiogenesis on Rac1, HUVECs were transfected with siNSC or siRac1 (Fig. 4A). siRac1 transfection resulted in significant reduction of Rac1 protein levels. A 3-day cellular proliferation assay was conducted on HUVECs transfected with siRac1 and siNSC (Fig. 4B). Similar to previous studies (28), the knockdown of Rac1 with siRNA significantly reduced HUVEC proliferation. Rac1 knockdown in HUVECs also resulted in a greater than 3-fold reduction in migration as compared with control cells (Fig. 4C). Lastly, we examined the effects of Rac1 knockdown on HUVEC tubule formation. HUVECs transfected with siNSC and siRac1 were seeded on Matrigel and the number of branch points. HUVECs that had Rac1 silenced exhibited a 68% decrease in the number of branch points as compared with control cells (Fig. 4D).
We next tested whether Rac inhibition will phenocopy the Rac knockdown effects on HUVEC cells. HUVECs treated with GYS32661 reduced Rac1 activity in a dose-dependent manner (Fig. 4E). Treatment with the Rac inhibitor at 2.5 and 5 μmol/L resulted in 38% and 68% reduction in cellular migration (Fig. 4F), respectively. The same concentrations of GYS32661 also led to a significant reduction in the number of branch points in a tube formation assay (Fig. 4G). To further investigate Rac inhibition on angiogenesis, aortas were isolated from mice and grown ex vivo in an aortic ring assay. Aortas were grown in either vehicle (DMSO) or 2.5 μmol/L and 5 μmol/L GYS32661, and the area of newly sprouted vessels was measured (Fig. 4H). Vehicle-treated rings formed numerous sprouts after 5 days, whereas aortas that were treated with 2.5 μmol/L resulted in a greater than 75% reduction in a newly sprouted vessel area and 5 μmol/L almost completely eliminated sprouting altogether. The reduction in area suggests both the number of branches off the aorta and total length of sprouts are reduced upon treatment with the Rac inhibitor. To investigate tubule formation involving processes more reflective of those occurring in vivo, we performed fibroblast and endothelial cell coculture experiments (Fig. 4I). HUVECs seeded in serum-free media containing vehicle on the fibroblast layer formed robust vascular networks as determined by the number of branch points. When the HUVECs were incubated with the Rac inhibitor, endothelial cell networks were disrobed in a dose-dependent manner. These results further indicate the role of Rac signaling in the vascularization process. The in vitro data generated with siRNA (Fig. 4A–D) along with the Rac inhibitor confirm that Rac1 plays an important role in angiogenesis.
To observe the effects of Rac inhibition in vivo, Matrigel plugs containing angiogenic growth factors were inoculated in mice. Mice were treated with either vehicle or 30 mg/kg GYS32661 for 5 days while blood vessels formed. On day 5, mice were injected systemically with FITC-lectin, which binds and labels endothelial cells (38), plugs were excised, visually examined and endothelial cells were quantitated by FITC measurements (Fig. 4J). Control Matrigel plugs appeared colorless and yielded background levels of FITC fluorescence. Matrigel plugs from vehicle-treated mice were red in appearance and had fluorescence readings over 2,500 RFUs, indicating robust angiogenic growth. Matrigel plugs from Rac inhibitor–treated mice were clear or yellowish in color and had greater than 60% reduction in fluorescence, confirming reduced angiogenesis (Fig. 4J). To further investigate Rac inhibitor treatment in vivo, we measured the number of blood vessels from the 786-O xenograft experiment by CD31 (PECAM-1) immunohistochemistry (IHC; Fig. 4K). CD31+ vessels were quantitated, and tumor microvessel density (MVD) measurements were calculated (Fig. 4L). Sunitinib and Rac inhibitor treatment resulted in significant reduction in CD31+ vessels compared with control tumors. Together, these data suggest that Rac inhibition is an effective antiangiogenic therapy.
Rac inhibition enhances the antiangiogenic effects of VEGFR2 targeted therapy
We next tested whether GYS32661 could improve antiangiogenic therapies such as sunitinib. Cellular proliferation assays were performed using HUVECs grown in VEGF containing media. Control HUVECs easily proliferated (Fig. 5A). Sunitinib or GYS32661 treatment significantly decreased proliferation. However, when GYS32661 was in combination with sunitinib, proliferation was completely halted. HUVECs were also seeded on Matrigel in VEGF containing media and allowed to form tubular structures. Although control-treated HUVECs formed numerous tubular structures, sunitinib treatment reduced tube formation to 53% of control (Fig. 5B). GYS32661 also disrupted angiogenic tube formation, lowering branch points to 51% of control. In combination, the two drugs almost complexly ablated tubular formation as indicated by significant decreases in branch points compared with either agent alone.
The majority of angiogenesis inhibitors target VEGF or its receptor, VEGFR (39). VEGF binds to VEGFR2, initiating downstream MAPK signaling (40). Sunitinib blocks activation of VEGFR2 and subsequently blocks downstream MAPK signaling (41). HUVECs stimulated with VEGF showed potent activation of VEGFR2 and MAPK signaling as indicated by an increase in phosphorylated proteins (Fig. 5C). In the presence of sunitinib, levels of phosphorylated VEGFR2 and MAPK were significantly decreased. Rac1 and its downstream effector, p21-activated kinase (PAK), integrate signaling from growth factor receptors to ERK activation (42, 43). To determine the dependency of Rac1 on MAPK signaling, HUVECs were stimulated with VEGF in the presence of GYS32661. Phosphorylation of VEGFR2 was observed, but downstream signaling through MAPK was blocked, suggesting Rac lies downstream of VEGFR2 and is required for MAPK activation. When HUVECs were treated with both sunitinib and GYS32661, a decrease in MAPK signaling was even lower than the single agents alone as determined (Fig. 5C).
To observe the effects of combinational therapy in vivo, Caki-1 tumors were randomized into four treatment groups: vehicle, sunitinib, GYS32661, and sunitinib plus GYS32661 (Fig. 5D). Sunitinib treatment (30 mg/kg) showed significant reduction of tumor growth. GYS32661 treatment resulted in significantly reduced growth, suggesting that Rac inhibitors are viable treatment options. Although sunitinib and GYS32661 treatments reduced growth of the tumors in vivo, the combination resulted in even greater growth inhibition than either drug alone. To observe tumor angiogenesis, immunohistochemical analysis of tumors for CD31 was performed (Fig. 5E). Sunitinib showed significant reduction of CD31+ MVD compared with vehicle controls. Similar to the 786-O xenograft experiment, mice treated with GYS32661 had significantly fewer blood vessels than the control tumors. When quantitating CD31+ blood vessels in the combination group, the average MVD was found to be significantly lower than the sunitinib treatment group alone. Therefore, the addition of GYS32661 significantly improved the antiangiogenic response.
Rac signaling contributes to the cross-talk between tumor and endothelial cells ccRCC
ccRCCs release angiogenic growth factors initiating the recruitment of nearby blood vessels (44). Rac1-dependent ROS promotes induction of HIF1α, a key angiogenic transcription factor (45). Additionally, Rac1 signaling upregulates VEGF production in prostate cancer, whereas Rac inhibition reduced VEGF expression (26). To determine if Rac1 plays a role in the secretion of angiogenic growth factors in ccRCC, conditioned media (CM) from Caki-1 cells transfected with siNSC or siRac1 were incubated on an angiogenic growth factor reverse phase protein array (RPPA; Fig. 6A). siNSC CM produced high quantities of VEGF, TSP-1, CXCL4, CXCL16, Amphiregulin, uPA, and GM-CSF. Caki-1 siRac1 cells showed a significant reduction in the production VEGF, TSP-1, CXCL16, CXCL4, and PDGF-AA. Interestingly, Rac1 knockdown resulted in elevated production of granulocyte–macrophage colony-stimulating factor (GM-CSF) in Caki-1 cells. GM-CSF has both stimulatory and suppressive effects in different types of cancer (46). A VEGF ELISA was performed on CM from siNSC and siRac1 Caki-1 cells to confirm RPPA results (Fig. 6B). CM from Caki-1 siNSC cells had high levels of VEGF as detected by ELISA. Confirming the RPPA, Rac1 knockdown resulted in significant reduction of VEGF secretion. A VEGF ELISA was also performed on CM from Caki-1 cells treated with increasing concentrations of GYS32661 (Fig. 6C). Vehicle-treated cells produced high levels of VEGF. Caki-1 cells treated with GYS32661 showed a dose-dependent reduction in VEGF secretion. To study whether VEGF secreted by Caki-1 cells affects VEGFR2-mediated signaling in HUVECs, CM from Caki-1 cells treated with vehicle or 10 μmol/L GYS32661 were added to starved HUVECs. HUVECs stimulated with 50 ng/mL VEGF were used as a positive control (Fig. 6D). Stimulation with VEGF resulted in potent activation of VEGFR2 determined by phosphorylation of the receptor and MAPK. HUVECs that were stimulated with CM from vehicle-treated Caki-1 cells also resulted in phosphorylation of VEGFR2 and activation of MAPK. Phosphorylation of VEGFR2 was not observed in HUVECs stimulated with conditioned media from cells treated with GYS32661, indicating less VEGF was present in the CM. Phosphorylation of MAPK was also attenuated compared with the vehicle control–treated conditioned medium. These data indicate that Rac1 blockade significantly impairs the ability of RCCs to secrete the angiogenic factor VEGF blocking the cross-talk with HUVECs by downregulating VEGFR-mediated signaling.
To confirm this phenomenon occurs in vivo, we performed immunohistochemical analysis of VEGFA and phosphorylated VEGFR2 on Caki-1 tumors treated with vehicle, sunitinib, GYS32661, and combination of sunitinib and GYS32661 (Fig. 6E). IHC analysis of vehicle tumors showed high intratumoral VEGFA levels (Fig. 6F) as well as high phosphorylated VEGFR2 (Fig. 6G). Sunitinib treatment reduced phospho-VEGFR2 staining. VEGFA staining intensity was also significantly reduced in sunitinib-treated tumors, consistent with reports that a positive feedback loop exists between VEGFR2 activation and VEGF production (47). Tumors treated with GYS32661 also showed a significant reduction in intratumoral VEGFA, confirming Rac1 plays a role in VEGF secretion. GYS32661 treatment reduced levels of pVEGFR2, suggesting that lower levels of VEGF secretion reduced activation of VEGFR2. Finally, although tumors treated with the combination of Rac inhibitor plus sunitinib resulted in comparable inhibition of pVEGFR2, levels of intratumoral VEGFA were significantly lower than tumors treated with either agent alone (Fig. 6E–G). Taken together, treatment of sunitinib reduces the angiogenic response of ccRCC in part by blocking VEGFR2 activation as well as reducing intratumoral VEGF levels by blocking the VEGF feed-forward loop. Rac inhibition of ccRCC also blocks the secretion of VEGF into the tumor microenvironment, resulting in diminished blood vessel recruitment. The combination of Rac inhibition and VEGFR2 blockade results in significantly lower intratumoral levels of VEGF resulting in even greater angiogenic blockade.
Discussion
In this study, we showed that Rac1 is highly expressed in ccRCC. Rac1 appears to play a role in initiation, progression, and metastatic dissemination of ccRCC. In addition to Rac1 overexpression, HACE1 was also found to be lost in ccRCC, resulting in the accumulation of activated Rac1 in tumors. HACE1 was first identified in Wilms' tumor patients, another type of RCC (12), suggesting that HACE1 loss may be common among all ccRCC. Together, ccRCC tumors that express high Rac1 levels and low levels of HACE1 may be prognostic of more aggressive disease, but may also identify patients susceptible to Rac-targeted therapies.
Antiangiogenic therapies are effective in ccRCC and other types of cancers that are highly angiogenic. However, other angiogenic growth factors are also capable of initiating an angiogenic response such as bFGF. Therefore, alternative strategies to thwart angiogenesis, vessel stability, and maturation alone or in combination with conventional VEGF/VEGFR-targeted approaches may be better alternatives. Rac1 has been reported to be essential for normal angiogenesis and vascular development (48). Interestingly, although endothelial-specific Rac1 knockout mice are embryonic lethal due to their inability to sprout smaller vessel branches, animals were fully capable of forming a completely functional dorsal aorta, suggesting that new vessels may be more susceptible to Rac inhibition (49). Newly formed have been shown to be sensitive to Rac1 knockdown (28, 49). In the context of ccRCC, we confirmed the dependency of endothelial cell migration, tube formation, and growth both in vitro and in vivo on Rac1 and propose the use of a Rac inhibitor as an alternative strategy to block angiogenesis. Because the Rac inhibitor reduces VEGF secretion as well as blocks transduction signaling downstream of VEGFR, we showed that the combinatorial approach of a Rac inhibitor plus a VEGFR inhibitor was significantly better at blocking angiogenesis than the VEGFR inhibitor alone. Patients treated with therapeutic agents that target the VEGF:VEGFR can have significant toxicities (50–52). The addition of a Rac inhibitor to traditional antiangiogenic therapies may provide an opportunity to lower doses and reduce toxicities.
VEGF is an endothelial cell-specific mitogen (53) and is secreted by many different cell types including tumor cells, osteoblasts, macrophages, platelets, and renal mesangial cells (53–59). Although VEGF secretion is often thought of as a response to hypoxia, VEGF upregulation has been shown to be stimulated by high glucose levels, growth factor signaling, Stat3, TGFβ, and others (60–63). Investigation of placental VEGF expression identified Rac1 through its ability to activate NADPH oxidase (64). In cancers, immunohistochemical analyses of gastric cancer identified a positive correlation between Rac1, HIF1α, VEGF expression, and MVD (65). Additionally, a recent report indicated that negative regulation of Rac1 led to decreased VEGF expression in non–small cell lung cancer (66). In the present study, we show Rac1 silencing or inhibition suppresses VEGF production in ccRCC cells impairing endothelial cell expansion and new vessel formation. Therefore, treatment of tumors with a Rac inhibitor has the potential to target the tumor cells themselves as well as cutoff proangiogenic paracrine signaling to nearby blood vessels.
This work raises an interesting question as to how Rac1 regulates VEGF expression. As previously discussed, VHL aberrations in ccRCC resulting in HIF1α-mediated VEGF transcription is commonly observed. Although positive associations between Rac1, HIF1α, and VEGF suggest Rac1 may play a role in HIF1α-mediated VEGF expression, the limited number of RCC cell lines investigated in this study is a limitation. Therefore, further studies using a broader cell line panel need to be conducted. Suppression of Rac1 in ccRCC cells resulted in the suppression of angiogenic factors other than VEGF such as platelet-derived growth factor (PDGF), which is known to play a role in the blood vessel maturation and stabilization, recruitment of cancer-associated fibroblasts (CAF), autocrine stimulation of cancer cells, and epithelial-to-mesenchymal transition (EMT; ref. 67). This work suggests that further investigation of Rac signaling in CAFs and other components of the tumor microenvironment may provide important understanding of tumor progression.
Another recently reported study identified the Rac signaling pathway as a resistance mechanism to bevacizumab in prostate cancer (26), whereas Rac inhibition was capable of sensitizing tumors to bevacizumab. Our study suggests that the addition of a Rac inhibitor may revitalize antiangiogenic agents in indications otherwise thought to be resistant.
Analysis of clinical data sets indicates Rac signaling is aberrantly activated upon transition from normal kidney to ccRCC and that tumors with the highest Rac activation have the poorest prognosis. Furthermore, these findings suggest high Rac1 and/or low HACE1 levels may predict the aggressiveness of the disease and also indicate tumors that may be susceptible to Rac inhibition. In this study, we showed that targeting Rac in ccRCC tumors attenuates tumor growth in multiple ways. Rac inhibition reduces growth of cancer cells themselves as well as blocks the production of proangiogenic signaling molecules. Furthermore, Rac inhibition also targets the vasculature and prevents vessels expansion by directly affecting the endothelial cells (Fig. 7).
In summary, Rac plays a significant role in the ccRCC and the therapeutic targeting of Rac has the ability to target multiple components in the tumor microenvironment, making Rac inhibitors an interesting treatment option either as a single agent or in combination with antiangiogenic therapies.
Disclosure of Potential Conflicts of Interest
E.T. Goka is Director at Geneyus LLC and has ownership interest (including patents) in an entity. M.E. Lippman has ownership interest (including patents) in Seattle Genetics and Geneyus. No potential conflicts of interest were disclosed by the other authors.
Authors' Contributions
Conception and design: E.T. Goka, P. Chaturvedi, M.E. Lippman
Development of methodology: E.T. Goka, M.E. Lippman
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): E.T. Goka, D.T.M. Lopez
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): E.T. Goka, D.T.M. Lopez, M.E. Lippman
Writing, review, and/or revision of the manuscript: E.T. Goka, P. Chaturvedi, D.T.M. Lopez, M.E. Lippman
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): E.T. Goka, D.T.M. Lopez, M.E. Lippman
Study supervision: M.E. Lippman
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