Background
Kidney cancers are common in developed countries and are notoriously difficult to be treated. Ninety percent of kidney cancers are renal cell carcinomas (RCCs) which originate from tubular structures of the kidney. They are subdivided into clear cell carcinoma (ccRCC), papillary carcinoma, chromophobe, and oncocytoma. The remaining 10% are transitional cell carcinomas, which are derived from cells lining the renal pelvis and ureter [
1,
2]. Standard treatments for RCCs are surgery (partial or total nephrectomy) for localized kidney cancer, targeted therapies and immunotherapies for metastasized cancer. Seventy-five percent of the RCCs are ccRCCs which are poorly sensitive to traditional chemotherapy. Targeted therapies are also limited by the lack of knowledge of genetic mutations in the ccRCC cells.
The receptor tyrosine kinases (RTKs) are a large family of transmembrane receptors with 58 members in human [
3]. The ligand-induced dimerization of the RTKs lead to phosphorylation/activation of the receptors as well as the downstream signaling molecules [
4,
5]. RTKs play critical roles in the development of many diseases, especially cancer. Dysregulations of the RTK signaling through point mutation, gene amplification, overexpression, chromosomal alterations, and/or constitutive activation are key factors in oncogenesis [
4,
6‐
11]. However, the activation and function of the RTKs in ccRCC have not been fully investigated.
Previous studies in ccRCCs have mainly focused on RTKs gene expressions [
12,
13]. No genetic mutations of RTKs have been reported in the ccRCCs. The only molecular mechanism related to RTKs in ccRCCs is dysregulation of the pVHL/HIF axis [
14,
15], which drives expression of VEGF and PDGFβ and, hence, activation of their receptors VEGFR2 and PDGFRβ [
16‐
20]. Therefore, current treatments for ccRCCs are mostly anti-angiogenic tyrosine-kinase inhibitors (TKIs) targeting VEGFR, which include pazopanib, sunitinib, axitinib, sorafenib, and bevacizumab [
21,
22].
In the present study, we analyzed the phosphorylation/activation/ patterns of RTKs in 10 ccRCC patient samples, 4 RCC cell lines, and 4 other kidney tumor samples. Our data revealed that multiple RTKs were activated in the ccRCCs and the phosphorylation patterns of the RTKs in the ccRCC patients were similar to each other but different from adjacent normal tissues and the other kidney tumors. Treatments with a combination of RTK inhibitors based on their phosphorylation patterns in the ccRCC-derived xenografts effectively inhibited the cancer cell growth. These data suggest an effective therapeutic strategy to treat ccRCC patients.
Methods
Collection of primary kidney tumors
The renal tissue specimens were collected in compliance with local ethics regulations at the Department of Urology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, China. The 10 ccRCC patients were five males and five females (Table
1). The mean age at diagnosis was 65 ± 9. The patient information of 3 other kidney cancer samples and 1 benign renal tumor sample are in Table
2. After surgical resection, tissue samples were lysed in lysis buffer (R&D Sytems, AYR001B) for protein lysates on the ice or fixed in neutral buffered formalin (10%) for histology staining, or immediately processed to establish ccRCC patient-derived xenograft models in nude mice.
Table 1
Patient information of renal cell carcinoma (RCC)
RE0370 | 72 | Clear cell RCC | II |
RE0380 | 56 | Clear cell RCC | I~II |
RE0390 | 73 | Clear cell RCC | II |
RE0400 | 77 | Clear cell RCC | II |
RE0410 | 67 | Clear cell RCC | II~III |
RE0440 | 66 | Clear cell RCC | II |
RE0450 | 53 | Clear cell RCC | I |
RE0480 | 54 | Clear cell RCC | II |
RE0490 | 56 | Clear cell RCC | II |
RE0510 | 77 | Clear cell RCC | II |
Table 2
Patient information of the other kidney cancers and a benign renal tumor
RE0020 | 59 | Papillary RCC |
RE0150 | 55 | Oncocytoma |
RE0210 | 52 | Renal pelvic carcinoma |
RE0500 | 52 | Cystic nephroma |
Cell lines
786–0(CRL-1932), A-498(HTB-44), ACHN(CRL-1611), and Caki-1(HTB-46) cell lines were obtained from ATCC. 786–0 and Caki-1 cell lines were derived from human primary ccRCC. A-498 and ACHN cell lines were derived from human primary papillary RCCs. 786–0 and ACHN cells were cultured in RPMI 1640 Medium (Gibco) with 10% FBS (Gibco). A498 cells were cultured in Dulbecco’s Modification of Eagle’s Medium (Gibco) with 10% FBS. Caki-1 cells were cultured in McCoy’s 5A Medium (Sigma) with 10% FBS.
HE staining
Fixed tissues were dehydrated using grades of ethanol (70, 80, 90, 95, and 100%). Dehydration was followed by clearing the samples in two changes of xylene. The samples were then impregnated with two changes of molten paraffin wax, embedded, and blocked out. The tissue sections (7 μm) were stained with hematoxylin-eosin by standard procedures. Stained sections were observed and photographs were taken using a Leica microscope.
RTK phosphorylation/activation profiling
Human phospho-RTK arrays (R&D Systems, AYR001B) were used according to the manufacturer’s instructions. Briefly, a total of 5 mg protein lysates of in vitro cultured cells, or 10 mg protein lysates of clinical samples and mouse xenografts were diluted in the kit-specific dilution buffer and incubated with blocked membranes overnight. The membranes were washed and incubated with anti-phospho-tyrosine-HRP antibody for 2 h. The membranes were washed and exposed to chemiluminescent reagent. The arrays were photographed using Image Station 4000MM PRO system (Carestream). The pixel densities of various spots were collected and quantified with its software. The average signal (pixel density) of the pair of duplicate spots was determined for each RTK. A signal from the PBS negative control spots was used as a background value. And signals of reference spots in the corners were used for normalization among different arrays. Phospho-RTK relative value was calculated according to the following formula: Phospho-RTKx relative value = (INTx-INTnc)/(INTref-INTnc). INTx is the pixel density of RTKx, INTnc is the pixel density of background,and INTref is the density of reference spots.
Western blotting
Proteins were separated by SDS-PAGE and transferred to a nitrocellulose membrane. The membrane was blocked in TBS containing 0.1% Tween 20 (TBST) and 5% nonfat milk for 1 h at room temperature and then incubated overnight in TBST containing 5% bovine serum albumin and primary antibodies. Membranes were then washed with TBST and incubated with horseradish peroxidase-conjugated secondary antibody for 1 h, and immune complexes were detected by immobilon Western chemiluminescent HRP substrate (WBKLS0500, Millipore). Primary antibodies are anti-phospho-EGFR (#3777), anti-EGFR (#4267), anti-phospho-PDGFRβ (#3161), anti-PDGFRβ (#3169), anti-phospho-InsulinRβ (#3024), anti-InsulinRβ (#3025), anti-phospho-VEGFR2 (#2474), anti-VEGFR2 (#9698), anti-phospho-Met (#3077), anti-Met (#3148), anti-phospho-Akt (#4060), anti-phospho-Erk1/2 (#4370). All antibodies were purchased from Cell Signaling Technology. The membranes were photographed using Azure Biosystems (c300) and were quantified using its software (Analysis Toolbox). The density ratio of interest proteins to GAPDH or β-Actin were calculated.
Xenograft models and treatment
The female BALB/c nude (nu/nu) mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. and used for implantation at the age of 6–8 weeks. They were maintained under specific pathogen-free conditions, and food and water were supplied ad libitum. Housing and all procedures were performed according to protocols approved by the Ethics Committee of Shanghai institute of materia medica. Subcutaneous xenografts were established by injection of 5× 106 cells or one piece (2mm3) tumor per mouse to right flank. Tumor formation was monitored each week. Each subcutaneous tumor was measured using a caliper, and tumor volumes were calculated as follows: 0.5× length× width2. Nude mice with ccRCC patient-derived xenografts of approximately 100 mm3 were allocated randomly into 4 experimental groups and orally treated with 3 mg/kg/d Crizotinib (n = 6), 30 mg/kg/d Lapatinib (n = 6), combination of Crizotinib and Lapatinib(n = 6), or vehicle (n = 6) for 21 days. Mice were euthanized in a CO2 chamber for 2 h after the last treatment. Crizotinib and Lapatinib were purchased from Selleck Chemicals.
Immunofluorescence staining
Cryosections were blocked in PBS containing 5% normal donkey serum for 2 h at room temperature. Sections were incubated over night at 4 °C with the primary antibodies against PDGFRβ (ab32570, rabbit Anti-PDGF Receptor beta antibody, 1:50, Abcam), Pan-Keratin (#4545, mouse anti-pan-keratin antibody,1:50, CST), Vimentin (sc-7557, goat anti-vimentin antibody, 1:50, Santa Cruz). After washed with PBS three times, the sections were incubated for 1 h at room temperature with Alexa Fluor 594-labeled donkey anti-rabbit IgG (A21207,1:400, Invitrogen), Alexa Fluor 488-labeled donkey anti-mouse IgG (A21202,1:400, Invitrogen) and Alexa Fluor 555-labeled rabbit anti-goat IgG (A21431,1:400, Invitrogen). Sections were washed three times in PBS, followed by mounting tissue with Dako fluorescence mounting medium. Photographs were taken using a Leica DMi8.
Statistical analysis
Data were represented as mean ± SEM. T test was used in human phospho-RTK studies. Two-way ANOVA with Tukey post hoc test was used in mouse xenograft treatment studies. Statistical significance was established for P < 0.05, P < 0.01, and P < 0.001.
Discussion
We identified 9 RTKs that were significantly phosphorylated in the primary ccRCC samples and 6 of which, Insulin R, HGFR, PDGFRβ, M-CSFR, VEGFR1, and VEGFR2, were specific to the ccRCCs samples comparing to their adjacent normal tissues. More importantly, the phosphorylation patterns of the RTKs in the ccRCC patient samples were similar among each other. It is therefore possible that the activation of the 6 ccRCCs-specific RTKs are important for the formation and growth of the ccRCCs. Our data are consistent with previous studies on the expressions and roles of RTKs in ccRCCs. There were several reports demonstrated VEGF/VEGFR activation and HGFR upregulation in patients with ccRCCs [
12,
17‐
20,
23,
24]. The M-CSFR activation we observed in the ccRCC samples may be due to increases and activations of the tumor-associated macrophages in ccRCCs [
25‐
27]. The role of Insulin R in ccRCCs is unclear [
28]. There was a report showing that the expressions of Insulin R were similar in ccRCCs and their adjacent normal tissues, but the phosphorylation of the Insulin R was not analyzed in this report [
29]. Our data demonstrated that the Insulin R was significantly phosphorylated in the ccRCC samples, but not in the adjacent normal tissues, suggesting that Insulin R may have a role in promoting ccRCC cell growth. However, it was also reported that Insulin R expression correlated with a lower Fuhrman nuclear grade and better patient prognosis [
29]. Further studies are needed to clarify the roles of Insulin R in ccRCCs. None the less, these data suggest that the 6 specifically activated RTKs in the ccRCCs may be important targets for the treatment of ccRCCs.
Among the 6 specifically activated RTKs, HGFR and Insulin R were reported to be mainly expressed in the ccRCC epithelial cells [
23,
24,
29]. The M-CSF R seems to be expressed in the tumor-associated macrophages [
25‐
27] while the VEGFRs were likely expressed in the blood vessel endothelial cells. The PDGFRβ was found to be mainly expressed within the periepithelial stroma in the ccRCC samples in our study. Similar expression patterns of PDGFRβ were found in breast, prostate, pancreatic, gastric, and oral squamous cell carcinoma cancer cells [
30‐
32]. More importantly, high PDGFRβ expression in fibroblast-rich stroma is commonly associated with poor prognosis [
33,
34]. These data suggest that the RTKs in the ccRCC stroma cells may also be abnormally activated to support the growth of the cancer cells. Thus, targeting the activated RTKs in both the cancer epithelial cells and the surrounding stroma cells that associated with poor prognosis may be a primary choice for treating the ccRCC patients.
It is unclear what caused the activation of the RTKs in the ccRCCs. The behavior of the ccRCCs in the xenograft mice, however, indicated that majority of the 9 RTKs might be activated by their corresponding growth factors in the tumor environments. When the cancer cells were implanted into a new environment in the xenograft mice, most of the cancer cells failed to grow, likely because of lack of necessary growth factors to activate the RTKs. The only ccRCC sample that did grow in the xenograft mouse had different RTK phosphorylation patterns from that of the original sample. In addition, the four cancer cell lines, when implanted into the xenograft mice, also showed similar RTK phosphorylation patterns as the primary cancer sample, but different from that of the in vitro growing cells. All these data suggest that the RTK phosphorylation patterns of the cancer cells are not cell autonomous, but rather are determined by their growing environments.
Although we could not reproduce the same RTK phosphorylation patterns of the ccRCC primary cancer samples in the xenograft models, the treatment of the tumor cells in the xenograft mice with a combination of the RTKIs, based on the RTK phosphorylation patterns, successfully inhibited the tumor cell growth, suggesting that the RTK phosphorylation pattern-guided treatment of cancers is an effective therapeutic strategy.
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