p53β: a new prognostic marker for patients with clear-cell renal cell carcinoma from 5.3 years of median follow-up

p53β: a new prognostic marker for patients with clear-cell renal cell carcinoma from 5.3 years... Abstract We previously reported six different p53 isoforms in renal cell carcinoma (RCC). In the present study, influences of p53β on recurrence-free survival (RFS) and overall survival (OS) were evaluated. Patients diagnosed with RCC in our center were into this study. mRNA expressions of p53 isoforms (p53α, p53β, p53γ) in tumors were determined by RT-PCR and real-time PCR. Functional yeast-based assay was performed to analyze p53 mutational status. p53β transfected 786-O and CAKi-1 cells were cultured to examine expressions of B-cell lymphoma 2-associated X protein (bax) and caspase-3, and ratios of apoptosis. After surgeries, all patients were followed up at programmed intervals. 266 patients were analyzed in this study. Median follow-up time was 5.3 years. RT-PCR (r = −0.72, P = 0.016) and real-time PCR (r = −0.65, P = 0.033) both showed only p53β expressed higher level in lower tumor stage versus higher stage. p53 wild-type and p53 mutation had comparable RFS (P = 0.361) and OS (P = 0.218), respectively. Kaplan–Meier analysis showed high p53β expression was associated with significantly improved RFS and OS, regardless of p53 mutational status. High p53β expression indicated better RFS [hazard ratio (HR) 2.599, 95% confidence interval (CI) 1.472–4.551, P = 0.038] and OS (HR 2.604, 95% CI 1.453–4.824, P = 0.031). p53β transfected 786-O and CAKi-1 cells expressed significantly higher level of bax and caspase-3, and had higher ratios of apoptosis than untransfected cells. Taken together, higher level of p53β predict better prognosis in patients with RCC through enhancing apoptosis in tumors. Introduction p53 mutations can be detected in many cancers, and they are associated with tumor progression, resistance to chemotherapy and poor prognosis (1,2). However, this is not the case for renal cell carcinoma (RCC), whose high intrinsic resistance to treatments is accompanied by a very low frequency of mutations in p53 (3). Hence, there are some other mechanisms affecting transcription activity of p53 gene. Several years ago, inhibitory or activating functions of p53 isoforms on p53 dependent gene induction were identified. We previously detected six isoforms (p53α, p53β, p53γ, Δ133p53, Δ133p53β, Δ133p53γ) in clear-cell RCC (4). To date, at least 12 different p53 isoforms have been identified (5). p53 protein isoforms all share a common part of the deoxy ribonucleic acid-binding domain, and contain distinct transactivation and C-terminal regulatory domains, enabling them differentially to regulate gene expression (6). Besides their different subcellular localizations, the isoforms exert different effects on p53 mediated gene expressions. Some p53 isoforms can influence the transactivation activity of p53, whereas others exhibit a function that is independent on p53 (7). p53 isoforms related to clinical features and outcomes in various cancers. Δ133p53 expression was associated with prognosis in the vast majority of ovarian cancer cases (8). Δ40p53 was significantly upregulated in breast cancer tissue compared with normal breast and was significantly associated with aggressive breast cancer subtype (9). p53β expression was negatively associated with tumor size and positively associated with disease-free survival, where high levels of p53β were protective, particularly in patients with p53 mutation, suggesting p53β can counteract the damage inflicted by mutant p53 (9). Moreover, high expression of p53β was found to correlate with increased response to camptothecin and doxorubicin chemotherapy in lung cancer, implying a role of p53β in enhancing chemosensitivity (10). We previously reported p53β was significantly overexpressed in RCC tissue and associated with tumor stage (4). We hypothesized p53β could be a potential prognostic marker in RCC. To prove our idea, patients with clear-cell RCC were for the first time collected in the present study to evaluate clinical significance of p53β. p53α and p53γ were served as control. Materials and methods Patients and tissue samples The Ethics Committee of Shandong Provincial Hospital approved the study protocol. Between June 2006 and May 2013, tumor samples were taken after informed consent from patients with clear-cell RCC, who underwent (1) nephron sparing surgery or (2) radical nephrectomy or (3) radical nephrectomy and postoperative targeted therapy. None of the patients were undergone preoperative chemotherapy and/or radiation therapy. The patients with bilateral renal tumors and/or local/distant metastasis were excluded from this study. All patients were staged according to 2010 TNM classification system and nuclear grade of tumors was determined using Fuhrman grading scheme. After surgeries, all patients were followed up at three monthly intervals in the first 2 years, then at six monthly intervals, and assessed for recurrence-free survival (RFS) and overall survival (OS). Disease recurrence was determined by ultrasound and computed tomography. All tumor tissues were confirmed by two pathologists according to WHO (2004) classification. Tumor tissue samples were divided into three parts, one-third were fixed in formalin and embedded in paraffin, and the other two-third were frozen in liquid nitrogen and then stored at −80°C until used. RT-PCR and real-time PCR Total RNA of tumor tissue in cryopreservation was isolated using TRIzol reagent (15596018, Applied Biosystems, New York, NY). Total RNA was reverse transcribed into a complementary DNA library. Then RT-PCR and real-time PCR were performed to examine expressions of p53α, p53β and p53γ in tumor samples according to previous protocols (11). All reagents for RT-PCR, real-time PCR, including the primers for human p53α, p53β, p53γ, β-actin and glyceraldehydes-3- phosphate dehydrogenase (GAPDH), were purchased from Applied Biosystems. Primer sequences are presented as follows: p53α (Forward:5′-GTCACTGCCATGGA GGAGCCGCA-3′; Reverse:5′-GACGCACACCTATTGCAAGCAAGGGTT-3′); p53β (Forward:5′-GCGAGCAC TGCCCAACA-3′; Reverse:5′-GAAAGCTGGTCT GGTCCTGAA-3′); p53γ (Forward:5′-ACTAAGCGAGCACTGCCCAA-3′; Reverse:5′-GTAAGTCAAGTA GCATCTGAAGGGTG-3′); GAPDH (Forward:5′- CCATGTTCGTCATGGGTG TGAACCA-3′; Reverse:5′-GCCAGTAGAGGCAGG GATGATGTTC-3′); β-actin (Forward:5′-CAGGGCGTGATGGTGGGCA-3′; Reverse:5′-CAAACATCATCTGGGTCATCTTCTC-3′). RT-PCR products were electrophoresed in 1.5% agarose gels in the presence of ethidium bromide, visualized by UV fluorescence and recorded by a digital camera connected to a computer. Reactions of real-time PCR were run in Applied Biosystems’ PRISM 7300HT sequence detection system. Real-time PCR results were analyzed by Applied Biosystems’ SDS 7000 software to determine expressions of p53α, p53β and p53γ, respectively. Each experiment was repeated three times. Then the cases enrolled in the present study were divided into two groups (a high-expressing group and a low-expressing group) according to median p53β expression level based upon real-time PCR results. Analysis of p53 mutational status p53 mRNA species from tumors were reverse transcribed, amplified by PCR, and cotransformed into Saccharomyces cerevisiae together with a linearized yeast homologous recombination expression vector carrying the 5′ and 3′ ends of the p53 open-reading frame. Then the functional yeast-based assay was used as described previously (12) to analyze p53 mutational status. Wild-type p53, which activates transcription of the yeast ADE2 gene that encodes the phosphoribosylaminoimidazole carboxylase results in white colonies, whereas mutant alleles lack transcriptional activity and result in smaller, red colonies. For each tumor sample, the test was performed in triple. The percentages of red colonies and white colonies in each examination were recorded. The tumor with higher percentage of red colonies than white colonies was defined as p53 mutation, conversely, p53 wild-type. Experiments of exploring protection mechanisms of p53β RNA isolation and real-time PCR Ten tumor samples were randomly selected from p53β high-expressing group and p53β low-expressing group, respectively. RNA isolation and real-time PCR were then performed according to the protocol described above. Primers for human B-cell lymphoma 2-associated X protein (bax), caspase-3 and GAPDH were purchased (Sangon Biotech, Shanghai, China). Primer sequences are: bax (Forward: 5′-TCCA CCAAGAAGCTGAGCGAG-3′; Reverse: 5′-GTCCAGCCCATGATGGTTCT-3′); caspase-3 (Forward: 5′-ATGGACAACAACGAAACCTCCGTG-3′; Reverse: 5′-CC ACTCCCAGTCATTCCTTTAGTG-3′); GAPDH (Forward: 5′-CGGAGTCAACGGA TTTGGTCGTAT-3′; Reverse: 5′-AGCCTTCTCCATGGTGGTGAAGAC-3′). Western blot Ten tumor samples were randomly selected from p53β high-expressing group and p53β low-expressing group, respectively. They were lysed on ice in double distilled water containing 10 mM Tris (T5912, Sigma-Aldrich, Shanghai, China) and 1 mM EDTA (798681, Sigma-Aldrich, Shanghai, China). The homogenate was spun at 12000 rpm for 10 min, and the supernatant was recovered as a protein sample, which was measured for protein concentration by means of the Bicinchoninic acid assay method (Pierce Chemical Co, Rockford, IL). Tissue lysates containing 20 μg of protein were electrophoresed in sodium dodecyl sulfate-polyacrylamide gel (s0179, HaiGene, Haerbin, Heilongjiang, China) electrophoresis and were then transferred onto polyvinylidene difluoride membranes (Bio-Rad Laboratories, Hercules, CA). Detection of protein on the membrane was performed with the ECL kit (Amersham Life Sciences Inc, Arlington Heights, IL) using primary antibodies: rabbit anti-bax (ab32503, Abcam, Cambridge, MA) and rabbit anti-active caspase-3 (ab32042, Abcam, Cambridge), followed by exposure to X-ray films. All membranes were re-probed with anti-GAPDH (sc-365062, Santa Cruz Biotechnology, Santa Cruz, CA) for internal control. The resulting images were analyzed by means of Image Pro Plus software (Media Cybernetics, Rockville, MD) to determine the integrated density value of each protein band. Each sample was examined in triplicate. Cell experiments RCC cell lines, 786-O (p53 mutant) and CAKi-1 (p53 wild-type), were obtained from Cell Bank, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. 786-O cells were maintained in RPMI-1640 Medium supplemented with 100 μg/ml streptomycin, 100 U/ml penicillin and 10% fetal bovine serum at 37°C in a humidified atmosphere with 5% CO2. CAKi-1 cells were cultured in McCoy’s 5A Medium supplemented with 1.5 mmol/l glutamine, 2.2 g/l sodium bicarbonate and 10% fetal bovine serum. pCMV-HA and pCMV-HA-p53β plasmids were generated by Shanghai Bioleaf Biotech Co., Ltd, China. 1 × 105 786-O cells were seeded in six-well cell culture plate and cultured for 12 h. After washing three times by phosphate buffer saline, the medium was replaced by Opti-MEM medium without fetal bovine serum or antibiotics. 4 μg plasmids and 10 μl Lipofectamine 2000 (11668027, Invitrogen, Shanghai, China) were diluted gently in 200 μl Opti-MEM medium without fetal bovine serum or antibiotics, incubated in room temperature for 20 min, and added in to each well. The six-well cell culture plate was returned to cell culture incubator for 6 h. Then the Opti-MEM medium was discarded, and replaced by RPMI-1640 Medium. The cells were incubated for 48 h prior to testing for transgene expression. CAKi-1 cells were transfected using the same protocol. The cells transfected with pCMV-HA plasmids were termed as 786-O-pCMV-HA and CAKi-1-pCMV-HA, and 786-O-pCMV-HA-p53β and CAKi-1-pCMV-HA-p53β for transfecting with pCMV-HA-p53β plasmids. In order to examine p53β expressions in these cells, RNA isolation and real-time PCR were then performed according to the protocol described above. To examine expressions of bax and active caspase-3 in cultured cells, Western blot was performed. 786-O, 786-O-pCMV-HA, 786-O-pCMV-HA-p53β, CAKi-1, CAKi-1-pCMV-HA and CAKi-1-pCMV-HA-p53β were lysed in phosphate buffer saline containing 1% IGEPAL, 0.5% sodium deoxycholate, 0.1% sodium dodecyl sulfate, aprotinin (10 μg/ml) and leupeptin (10 μg/ml). Then western blot analyses were performed according to the protocol narrated above. Primary antibodies included rabbit anti-bax (ab32503, Abcam, Cambridge, MA), rabbit anti-active caspase-3 (ab32042, Abcam, Cambridge) and mouse anti-GAPDH (sc-365062, Santa Cruz Biotechnology, Santa Cruz). Each cell was subjected to three independent experiments. Flow cytometry was carried on to determine apoptosis in cells. 786-O, 786-O-pCMV-HA-p53β, CAKi-1 and CAKi-1-pCMV-HA-p53β were harvested to detect apoptotic ratios by using Apoptosis Detection Kit (556570, BD Biosciences, San Diego, CA). The cells were stained with propidium iodide according to the supplier’s instructions. Apoptotic cells were detected using FACSCalibur flow cytometer, Beckman Coulter, Brea. Data were analyzed using FlowJo software (Tree Star Inc, Ashland, OR). Statistical analysis Data were analyzed with SPSS 17.0 statistical software (SPSS Inc., IL) and expressed as mean ± standard error of the mean for continuous variables. Continuous data were compared among groups by using Student’s t test or one-way analysis of variance. Chi-square test and Fisher’s exact test were performed to examine relationship between p53 mutational status and categorical clinicopathological parameters. For correlations between tumor stage from T1 to T4 and expression levels of p53 isoforms, Spearman’s correlation coefficients were calculated. Time-to-event data were analyzed using a Cox proportional hazards regression model, and Kaplan–Meier plots were generated to assess survival probabilities. Comparison of survival curves was performed using log-rank test. Results are presented as HR, with 95% CI and P values. P < 0.05 was considered statistically significant. Results Demographic characteristics of patients Two hundred and sixty eight patients (161 male, 107 female) diagnosed with clear-cell RCC met the inclusion criteria were enrolled into this study. After operations, one male patient died of severe bleeding and one female patient died of hepatic failure. These two cases were excluded from final analysis. Median age was 55 years (31–76 years). Median follow-up was 5.3 years (19–85 months). Table 1 provides the demographic characteristics of patients. Table 1. Demographic characteristics of patients   No. (%)  P value  Gender    0.033   Male  160 (60.2)     Female  106 (39.8)    Age (years)    0.087   ≥55  122 (45.9)     <55  144 (54.1)    Symptoms    0.018   Absent  184 (69.2)     Present  82 (30.8)    Side    0.044   Left  115 (43.2)     Right  151 (56.8)    Tumor grade    0.007   G1+G2  157 (59.0)     G3+G4  109 (41.0)    Tumor stage    0.704   T1  83 (31.2)     T2  60 (22.6)     T3  72 (27.1)     T4  51 (19.1)    NM status    < 0.001   N0M0  170 (63.9)     Others  96 (36.1)    Treatment    0.068   NSS  101 (38.0)     RN  98 (36.8)     RN with TT  67 (25.2)      No. (%)  P value  Gender    0.033   Male  160 (60.2)     Female  106 (39.8)    Age (years)    0.087   ≥55  122 (45.9)     <55  144 (54.1)    Symptoms    0.018   Absent  184 (69.2)     Present  82 (30.8)    Side    0.044   Left  115 (43.2)     Right  151 (56.8)    Tumor grade    0.007   G1+G2  157 (59.0)     G3+G4  109 (41.0)    Tumor stage    0.704   T1  83 (31.2)     T2  60 (22.6)     T3  72 (27.1)     T4  51 (19.1)    NM status    < 0.001   N0M0  170 (63.9)     Others  96 (36.1)    Treatment    0.068   NSS  101 (38.0)     RN  98 (36.8)     RN with TT  67 (25.2)    NSS, nephron sparing surgery; RN, radical nephrectomy; TT, targeted therapy. View Large Expressions of p53 isoforms in tumor tissue Expressions of p53α, p53β and p53γ in tumor samples subgrouped by tumor stage were analyzed by RT-PCR (Figure 1A). Spearman’s correlation analysis showed that no significant differences were detected in different tumor stages regarding to p53α (P = 0.104) or p53γ (P = 0.075), respectively. While, the expressions of p53β were significantly (r = −0.72, P = 0.016) decreased from T1 stage to T4 stage (Figure 1B). Real-time PCR analysis also demonstrated that there were no significant differences of p53α expression (P = 0.271) or p53γ expression (P = 0.114) from T1 to T4 stage, respectively. However, result demonstrated significantly higher level of p53β expression in lower stage versus higher stage (r = −0.65, P = 0.033) (Figure 1C). Figure 1. View largeDownload slide Expressions of p53 isoforms in tumor tissue. (A) Expressions of p53α, p53β and p53γ in tumor samples were analyzed by RT-PCR. (B) The results of RT-PCR were presented in the bar chart. (C) Expression levels of p53 isoforms were analyzed with real-time PCR. Figure 1. View largeDownload slide Expressions of p53 isoforms in tumor tissue. (A) Expressions of p53α, p53β and p53γ in tumor samples were analyzed by RT-PCR. (B) The results of RT-PCR were presented in the bar chart. (C) Expression levels of p53 isoforms were analyzed with real-time PCR. Clinical relevance of p53 mutational status Of the included cases, 197 of 266 (74.1%) patients were wild-type p53, and 69 of 266 (25.9%) harboured p53 mutations. The relevances of clinicopathological features and p53 mutational status were summarized in Table 2. Gender (P = 0.474), age (P = 0.062), symptoms (P = 0.600), side of tumors (P = 0.239), tumor stage (P = 0.087), and NM status (P = 0.065) did not differ with respect to p53 mutational status. p53 mutational status was significantly associated with tumor grade (G1+G2 versus G3+G4, P < 0.001). Table 2. Association of p53 mutational status with clinicopathological features   p53 wild-type  p53 mutation  P value  No. (%)  No. (%)  Gender      0.474   Male  121 (75.6)  39 (24.4)     Female  76 (71.7)  30 (28.3)    Age (years)      0.062   ≥55  97 (79.5)  25 (20.5)     <55  100 (69.4)  44 (30.6)    Symptoms      0.600   Absent  138 (75.0)  46 (25.0)     Present  59 (72.0)  23 (28.0)    Side      0.239   Left  81 (70.4)  34 (29.6)     Right  116 (76.8)  35 (23.2)    Tumor grade      < 0.001   G1+G2  141 (89.8)  16 (10.2)     G3+G4  56 (51.4)  53 (48.6)    Tumor stage      0.087   T1  59 (71.1)  24 (28.9)     T2  41 (68.3)  19 (31.7)     T3  55 (76.4)  17 (23.6)     T4  42 (82.4)  9 (17.6)    NM status      0.065   N0M0  113 (66.5)  57 (33.5)     Others  65 (67.7)  31 (32.3)      p53 wild-type  p53 mutation  P value  No. (%)  No. (%)  Gender      0.474   Male  121 (75.6)  39 (24.4)     Female  76 (71.7)  30 (28.3)    Age (years)      0.062   ≥55  97 (79.5)  25 (20.5)     <55  100 (69.4)  44 (30.6)    Symptoms      0.600   Absent  138 (75.0)  46 (25.0)     Present  59 (72.0)  23 (28.0)    Side      0.239   Left  81 (70.4)  34 (29.6)     Right  116 (76.8)  35 (23.2)    Tumor grade      < 0.001   G1+G2  141 (89.8)  16 (10.2)     G3+G4  56 (51.4)  53 (48.6)    Tumor stage      0.087   T1  59 (71.1)  24 (28.9)     T2  41 (68.3)  19 (31.7)     T3  55 (76.4)  17 (23.6)     T4  42 (82.4)  9 (17.6)    NM status      0.065   N0M0  113 (66.5)  57 (33.5)     Others  65 (67.7)  31 (32.3)    View Large Patients with p53 wild-type carcinoma demonstrated comparable RFS (P = 0.361) and OS (P = 0.218) with patients with p53 mutant carcinoma, respectively (Table 3). Table 3. Associations between p53 mutational status and survival   p53 wild-type  p53 mutation  P value  Median RFS (months)  52.2  46.3  0.361  Median OS (months)  61.3  57.5  0.218    p53 wild-type  p53 mutation  P value  Median RFS (months)  52.2  46.3  0.361  Median OS (months)  61.3  57.5  0.218  View Large Influences of p53β expression on RFS and OS Influences of p53β expression on RFS and OS were examined based upon follow-up data. Result showed that in patients with p53 mutant tumor, high p53β expression group was associated with significantly improved RFS (median 58.2 months versus median 46.0 months; P = 0.039) and OS (median 65.1 months versus median 49.9 months; P = 0.042) compared with low p53β expression group, respectively. In patients with p53 wild-type clear-cell RCC, result was consistent. The RFS time and OS time of p53β high expression group were median 67.1 months and median 69.9 months, respectively, both significantly (P < 0.001 and P = 0.001) higher than p53β low expression group (median 52.7 months and median 58.7 months, respectively) (Figure 2). Figure 2. View largeDownload slide Influences of p53β expression on RFS and OS. Censored cases are represented by a ‘+’. The median survival time (95% CI) and log-rank test P value are shown. (A, B) show the influences of p53β expression on RFS and OS in patients with p53 mutant tumors. (C, D) show the influences of p53β expression on RFS and OS in patients with p53 wild-type tumors. Figure 2. View largeDownload slide Influences of p53β expression on RFS and OS. Censored cases are represented by a ‘+’. The median survival time (95% CI) and log-rank test P value are shown. (A, B) show the influences of p53β expression on RFS and OS in patients with p53 mutant tumors. (C, D) show the influences of p53β expression on RFS and OS in patients with p53 wild-type tumors. A multivariate model comprising p53β expression and selected clinicopathological parameters (symptoms, tumor grade, tumor stage, NM status, treatment methods) was generated (Table 4). High expression of p53β was indicated better RFS (HR 2.599, 95% CI 1.472–4.551, P = 0.038) and OS (HR 2.604, 95% CI 1.453–4.824, P = 0.031) of clear-cell RCC patients (Table 4). Table 4. Multivariate analysis of p53β in patients with clear-cell renal cell carcinoma   RFS  OS  HR (95% CI)  P value  HR (95% CI)  P value  Symptoms   Absent  Reference    Reference     Present  1.644 (0.991–1.972)  0.033  3.536 (1.467–4.713)  0.010  Tumor grade   G1+G2  Reference    Reference     G3+G4  1.252 (0.958–1.471)  0.042  1.833 (0.968–2.012)  0.069  Tumor stage   T1  Reference    Reference     T2  1.175 (0.730–1.664)  0.573  0.988 (0.768–1.631)  0.420   T3  1.280 (0.993–2.016)  0.027  1.605 (1.001–2.384)  0.066   T4  2.867 (1.368–3.593)  0.008  1.594 (0.986–1.727)  0.041  NM status   N0M0  Reference    Reference     Others  1.079 (0.912–1.633)  0.042  2.501 (1.393–3.632)  0.044  Treatment   NSS  Reference    Reference     RN  0.907 (0.669–1.434)  0.106  2.113 (1.766–4.450)  0.491   RN with TT  1.101 (0.977–1.142)  0.057  1.143 (0.961–1.385)  0.035  p53β   High expression  Reference    Reference     Low expression  2.599 (1.472–4.551)  0.038  2.604 (1.453–4.824)  0.031    RFS  OS  HR (95% CI)  P value  HR (95% CI)  P value  Symptoms   Absent  Reference    Reference     Present  1.644 (0.991–1.972)  0.033  3.536 (1.467–4.713)  0.010  Tumor grade   G1+G2  Reference    Reference     G3+G4  1.252 (0.958–1.471)  0.042  1.833 (0.968–2.012)  0.069  Tumor stage   T1  Reference    Reference     T2  1.175 (0.730–1.664)  0.573  0.988 (0.768–1.631)  0.420   T3  1.280 (0.993–2.016)  0.027  1.605 (1.001–2.384)  0.066   T4  2.867 (1.368–3.593)  0.008  1.594 (0.986–1.727)  0.041  NM status   N0M0  Reference    Reference     Others  1.079 (0.912–1.633)  0.042  2.501 (1.393–3.632)  0.044  Treatment   NSS  Reference    Reference     RN  0.907 (0.669–1.434)  0.106  2.113 (1.766–4.450)  0.491   RN with TT  1.101 (0.977–1.142)  0.057  1.143 (0.961–1.385)  0.035  p53β   High expression  Reference    Reference     Low expression  2.599 (1.472–4.551)  0.038  2.604 (1.453–4.824)  0.031  NSS, nephron sparing surgery; RN, radical nephrectomy; TT, targeted therapy. View Large Experiments of exploring protection mechanisms of p53β For tumor samples, real-time PCR showed messenger RNA expressions of bax (P = 0.023) and caspase-3 (P = 0.007) were both significantly higher in p53β high-expressing group compared with p53β low-expressing group (Figure 3A). Moreover, western blot analysis demonstrated significantly higher levels of bax (P = 0.039) and active caspase-3 (P = 0.020) expressions in p53β high-expressing group versus p53β low-expressing group, respectively (Figure 3B and C). Figure 3. View largeDownload slide Experiments of exploring protection mechanisms of p53β. (A) Expressions of bax and caspase-3 in tumor samples (p53β high-expressing group, n = 10; p53β low-expressing group, n = 10) were analyzed with real-time PCR. Each sample was examined in triplicate. (B, C) Western blot analysis of expressions of bax and active caspase-3 in tumor samples (p53β high-expressing group, n = 10; p53β low-expressing group, n = 10). GAPDH served as an internal control. The ratios (in percentile) of bax/GAPDH and active caspase-3/GAPDH were determined by dividing the densitometric values of these protein bands obtained from the western blot. Each sample was examined in triplicate. (D) 786-O (p53 mutant) and CAKi-1 (p53 wild-type) cells were transfected with pCMV-HA plasmids or pCMV-HA-p53β plasmids. Expressions of p53β were analyzed by real-time PCR. Each cell was subjected to three independent experiments. (E, F) Western blot analysis of expressions of bax and active caspase-3 in cells. Each cell was subjected to three independent experiments. (G) Quantifications of apoptosis in786-O cells, CAKi-1 cells and p53β-transfected cells were analyzed by flow cytometry. The apoptotic peaks were indicated by black arrows. Each experiment was performed in triplicate. (H) The percentages of apoptotic cells were evaluated. All data were analyzed by SPSS 17.0 statistical software with Student’s t test or one-way analysis of variance. P < 0.05 was considered statistically significant. Figure 3. View largeDownload slide Experiments of exploring protection mechanisms of p53β. (A) Expressions of bax and caspase-3 in tumor samples (p53β high-expressing group, n = 10; p53β low-expressing group, n = 10) were analyzed with real-time PCR. Each sample was examined in triplicate. (B, C) Western blot analysis of expressions of bax and active caspase-3 in tumor samples (p53β high-expressing group, n = 10; p53β low-expressing group, n = 10). GAPDH served as an internal control. The ratios (in percentile) of bax/GAPDH and active caspase-3/GAPDH were determined by dividing the densitometric values of these protein bands obtained from the western blot. Each sample was examined in triplicate. (D) 786-O (p53 mutant) and CAKi-1 (p53 wild-type) cells were transfected with pCMV-HA plasmids or pCMV-HA-p53β plasmids. Expressions of p53β were analyzed by real-time PCR. Each cell was subjected to three independent experiments. (E, F) Western blot analysis of expressions of bax and active caspase-3 in cells. Each cell was subjected to three independent experiments. (G) Quantifications of apoptosis in786-O cells, CAKi-1 cells and p53β-transfected cells were analyzed by flow cytometry. The apoptotic peaks were indicated by black arrows. Each experiment was performed in triplicate. (H) The percentages of apoptotic cells were evaluated. All data were analyzed by SPSS 17.0 statistical software with Student’s t test or one-way analysis of variance. P < 0.05 was considered statistically significant. To examine the effects of p53β on RCC cells, p53β gene transfected 786-O cells and CAKi-1 cells were generated. Results of real-time PCR showed expressions of p53β were both significantly upregulated in p53β gene transfected 786-O cells (P < 0.001) and CAKi-1 cells (P < 0.001) (Figure 3D). Western blot analysis showed higher expressions of bax (P = 0.033) and active caspase-3 (P < 0.001) in 786-O-pCMV-HA-p53β cells than in 786-O cells, and higher in CAKi-1-pCMV-HA-p53β cells (P = 0.020, P = 0.041) than in CAKi-1 cells, respectively (Figure 3E and F). For quantification of apoptosis, flow cytometry analysis was performed (Figure 3G). Results showed that the cells transfected with p53β harboured higher ratios of apoptosis, irrespective of p53 mutational status (Figure 3H). Discussion To date, a large number of studies have reported that p53 appears to be mutated in about 50% of human cancers (13,14). While in RCC, p53 itself is rarely mutated, only existing in 3–33% of patients (15). Moreover, the expression of p53 did not reveal any prognostic significance in RCC (16). In the present study, 25.9% of patients carried mutant gene of p53. In breast cancer, mutation frequency of p53 is less than would be expected for a protein that plays such a pivotal role in maintaining genomic integrity (17), and many studies have shown a lack of association of breast cancer risk with polymorphisms in p53, indicating that wild-type p53 becomes inactivated by mechanisms other than mutation (9). In the present study, p53 mutant patients had similar RFS and OS with p53 wild-type patients, indicating p53 mutation status had no effect on prognosis of RCC patients. However, the role of p53 mutational status in predicting the prognosis of RCC is still a controversial issue. Girgin C’s report showed survival rates of mutant p53 and wild-type p53 cases with RCC were 33.3% and 84.2%, respectively (P = 0.0027) (18), with a conclusion that p53 mutation status was one of the most important prognostic factors. While, there was no evidence to support the conclusion that p53 mutation was associated with poorer survival of RCC in another study (14). In other types of cancers such as squamous-cell carcinoma of the head/neck and esophageal carcinoma, p53 mutation is increasingly identified as a poor prognostic marker (19–21). Further studies are needed to explain these discrepancies. In recent years, the role of p53 isoforms in carcinogenesis has emerged (22). However, their functions remain unclear, which were concluded primarily from some studies using several cell lines (23,24). Nevertheless, previous data indicated that p53 isoforms could enhance or inhibit ability of p53 to activate certain target promoters and to induce apoptosis (23,24). Therefore, regulated expression of p53 isoform is crucial for biological outcome of p53. In 2009, we firstly confirmed six p53 isoforms in clear-cell RCC (4). Of the six isoforms, only p53β mRNA was significantly overexpressed in tumor samples and was correlated with tumor stage, indicating p53β a good predictor of cancer progression for RCC. In previous reports, DO-1 was commonly used as an indicator of p53β (25). However, DO-1 can also recognize p53α and p53γ. Jean–Christophe Bourdon’s group firstly raised an antibody KJC8, specific to the p53β isoforms (that is, p53β, Δ40p53β and Δ133p53β), which was still unable to detect p53β specifically (23,26). Moreover, it was uncertain to work in staining paraffin-embedded sections with KJC8 (26). Hence, in the present study, RT-PCR and real-time PCR were performed instead of immumohistochemical staining. Our result showed only p53β expression level was correlated with tumor stage, which was consistent with our previous data. Moreover, expression of p53β decreased accompanied by increasement of tumor stage and lower RFS and OS, implying p53β a beneficial factor for the patients with clear-cell RCC. To our knowledge, p53β has already been investigated as a protective factor against damage inflicted by tumors such as breast cancer and colon cancer (9,27). Breast cancer patients expressing low levels of p53β had worse prognosis, whereas patients expressing high levels of p53β had better prognosis (9). In addition, p53β expression was positively associated with long-term survival in acute myeloid leukaemia (28). However, p53β was also found to correlate with worse RFS in ovarian cancer patients with functionally active p53 (29). Avery–Kiejda and colleagues attributed the reason to the different sites of cancers (9). Hereby we firstly confirmed high expression of p53β as a predictor for good prognosis in patients with clear-cell RCC, regardless of p53 mutational status. High p53β expression resulted in a significant reduction of risk for recurrence and a significant increase of survival compared with low p53β expression. It is unclear how p53β exerts a beneficial function for the patients with RCC. Bax is a key mediator of cell growth and apoptosis. Overexpression of bax results in cell death through promotion of cytosolic accumulation of cytochrome C released from mitochondria (30). p53β was found to activate the promoter of bax, thus promoting apoptosis and senescence, and retaining tumor suppressive functions (31). Most importantly, Marcel and co-authors added additional layer of understanding into the mechanism of p53β function that p53β can bind to p53 in a DNA-mediated manner to create p53β/p53 complex, then enhancing p53 transcriptional activity on target gene bax that regulate cell cycle progression and apoptosis (31,32). In the present study, transfection of p53β was able to upregulate expression of bax and activate final apoptotic effector caspase-3, indicating a role of apoptosis in the protection mechanism of p53β. In conclusion, p53β expressed significantly more in lower tumor stage than in higher stage in RCC. For the first time, high p53β expression was proved to provide prolonged RFS and OS in clear-cell RCC patients, regardless of p53 mutational status, indicating p53β a good predictor of prognosis in patients with clear-cell RCC. Activations of bax and downstream effector caspase-3 followed by apoptosis of tumor cells were considered as possible protection mechanisms of p53β in RCC. Further knowledge regarding the details of mechanisms of protection provided by p53β is required to potentially provide p53-based gene diagnosis and individual biological therapy. Funding This study was funded by Foundation for Outstanding Young Scientist in Shandong Province (BS2011SW039) and National Natural Science Foundation of China (81572534, 81300629). Conflict of Interest Statement: None declared. Abbreviations CI confidence interval HR hazard ratio OS overall survival RCC renal cell carcinoma RFS recurrence-free survival References 1. 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Fujita, K.et al.  ( 2009) p53 isoforms Delta133p53 and p53beta are endogenous regulators of replicative cellular senescence. Nat. Cell Biol ., 11, 1135– 1142. Google Scholar CrossRef Search ADS PubMed  28. Anensen, N.et al.  ( 2006) A distinct p53 protein isoform signature reflects the onset of induction chemotherapy for acute myeloid leukemia. Clin. Cancer Res ., 12, 3985– 3992. Google Scholar CrossRef Search ADS PubMed  29. Hofstetter, G.et al.  ( 2010) Alternative splicing of p53 and p73: the novel p53 splice variant p53delta is an independent prognostic marker in ovarian cancer. Oncogene , 29, 1997– 2004. Google Scholar CrossRef Search ADS PubMed  30. Li, M.X.et al.  ( 2015) Mitochondria and apoptosis: emerging concepts. F1000Prime Rep ., 7, 42. Google Scholar PubMed  31. Solomon, H.et al.  ( 2014) Modulation of alternative splicing contributes to cancer development: focusing on p53 isoforms, p53β and p53γ. Cell Death Differ ., 21, 1347– 1349. Google Scholar CrossRef Search ADS PubMed  32. Marcel, V.et al.  ( 2014) Modulation of p53β and p53γ expression by regulating the alternative splicing of TP53 gene modifies cellular response. Cell Death Differ ., 21, 1377– 1387. Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Carcinogenesis Oxford University Press

p53β: a new prognostic marker for patients with clear-cell renal cell carcinoma from 5.3 years of median follow-up

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Abstract

Abstract We previously reported six different p53 isoforms in renal cell carcinoma (RCC). In the present study, influences of p53β on recurrence-free survival (RFS) and overall survival (OS) were evaluated. Patients diagnosed with RCC in our center were into this study. mRNA expressions of p53 isoforms (p53α, p53β, p53γ) in tumors were determined by RT-PCR and real-time PCR. Functional yeast-based assay was performed to analyze p53 mutational status. p53β transfected 786-O and CAKi-1 cells were cultured to examine expressions of B-cell lymphoma 2-associated X protein (bax) and caspase-3, and ratios of apoptosis. After surgeries, all patients were followed up at programmed intervals. 266 patients were analyzed in this study. Median follow-up time was 5.3 years. RT-PCR (r = −0.72, P = 0.016) and real-time PCR (r = −0.65, P = 0.033) both showed only p53β expressed higher level in lower tumor stage versus higher stage. p53 wild-type and p53 mutation had comparable RFS (P = 0.361) and OS (P = 0.218), respectively. Kaplan–Meier analysis showed high p53β expression was associated with significantly improved RFS and OS, regardless of p53 mutational status. High p53β expression indicated better RFS [hazard ratio (HR) 2.599, 95% confidence interval (CI) 1.472–4.551, P = 0.038] and OS (HR 2.604, 95% CI 1.453–4.824, P = 0.031). p53β transfected 786-O and CAKi-1 cells expressed significantly higher level of bax and caspase-3, and had higher ratios of apoptosis than untransfected cells. Taken together, higher level of p53β predict better prognosis in patients with RCC through enhancing apoptosis in tumors. Introduction p53 mutations can be detected in many cancers, and they are associated with tumor progression, resistance to chemotherapy and poor prognosis (1,2). However, this is not the case for renal cell carcinoma (RCC), whose high intrinsic resistance to treatments is accompanied by a very low frequency of mutations in p53 (3). Hence, there are some other mechanisms affecting transcription activity of p53 gene. Several years ago, inhibitory or activating functions of p53 isoforms on p53 dependent gene induction were identified. We previously detected six isoforms (p53α, p53β, p53γ, Δ133p53, Δ133p53β, Δ133p53γ) in clear-cell RCC (4). To date, at least 12 different p53 isoforms have been identified (5). p53 protein isoforms all share a common part of the deoxy ribonucleic acid-binding domain, and contain distinct transactivation and C-terminal regulatory domains, enabling them differentially to regulate gene expression (6). Besides their different subcellular localizations, the isoforms exert different effects on p53 mediated gene expressions. Some p53 isoforms can influence the transactivation activity of p53, whereas others exhibit a function that is independent on p53 (7). p53 isoforms related to clinical features and outcomes in various cancers. Δ133p53 expression was associated with prognosis in the vast majority of ovarian cancer cases (8). Δ40p53 was significantly upregulated in breast cancer tissue compared with normal breast and was significantly associated with aggressive breast cancer subtype (9). p53β expression was negatively associated with tumor size and positively associated with disease-free survival, where high levels of p53β were protective, particularly in patients with p53 mutation, suggesting p53β can counteract the damage inflicted by mutant p53 (9). Moreover, high expression of p53β was found to correlate with increased response to camptothecin and doxorubicin chemotherapy in lung cancer, implying a role of p53β in enhancing chemosensitivity (10). We previously reported p53β was significantly overexpressed in RCC tissue and associated with tumor stage (4). We hypothesized p53β could be a potential prognostic marker in RCC. To prove our idea, patients with clear-cell RCC were for the first time collected in the present study to evaluate clinical significance of p53β. p53α and p53γ were served as control. Materials and methods Patients and tissue samples The Ethics Committee of Shandong Provincial Hospital approved the study protocol. Between June 2006 and May 2013, tumor samples were taken after informed consent from patients with clear-cell RCC, who underwent (1) nephron sparing surgery or (2) radical nephrectomy or (3) radical nephrectomy and postoperative targeted therapy. None of the patients were undergone preoperative chemotherapy and/or radiation therapy. The patients with bilateral renal tumors and/or local/distant metastasis were excluded from this study. All patients were staged according to 2010 TNM classification system and nuclear grade of tumors was determined using Fuhrman grading scheme. After surgeries, all patients were followed up at three monthly intervals in the first 2 years, then at six monthly intervals, and assessed for recurrence-free survival (RFS) and overall survival (OS). Disease recurrence was determined by ultrasound and computed tomography. All tumor tissues were confirmed by two pathologists according to WHO (2004) classification. Tumor tissue samples were divided into three parts, one-third were fixed in formalin and embedded in paraffin, and the other two-third were frozen in liquid nitrogen and then stored at −80°C until used. RT-PCR and real-time PCR Total RNA of tumor tissue in cryopreservation was isolated using TRIzol reagent (15596018, Applied Biosystems, New York, NY). Total RNA was reverse transcribed into a complementary DNA library. Then RT-PCR and real-time PCR were performed to examine expressions of p53α, p53β and p53γ in tumor samples according to previous protocols (11). All reagents for RT-PCR, real-time PCR, including the primers for human p53α, p53β, p53γ, β-actin and glyceraldehydes-3- phosphate dehydrogenase (GAPDH), were purchased from Applied Biosystems. Primer sequences are presented as follows: p53α (Forward:5′-GTCACTGCCATGGA GGAGCCGCA-3′; Reverse:5′-GACGCACACCTATTGCAAGCAAGGGTT-3′); p53β (Forward:5′-GCGAGCAC TGCCCAACA-3′; Reverse:5′-GAAAGCTGGTCT GGTCCTGAA-3′); p53γ (Forward:5′-ACTAAGCGAGCACTGCCCAA-3′; Reverse:5′-GTAAGTCAAGTA GCATCTGAAGGGTG-3′); GAPDH (Forward:5′- CCATGTTCGTCATGGGTG TGAACCA-3′; Reverse:5′-GCCAGTAGAGGCAGG GATGATGTTC-3′); β-actin (Forward:5′-CAGGGCGTGATGGTGGGCA-3′; Reverse:5′-CAAACATCATCTGGGTCATCTTCTC-3′). RT-PCR products were electrophoresed in 1.5% agarose gels in the presence of ethidium bromide, visualized by UV fluorescence and recorded by a digital camera connected to a computer. Reactions of real-time PCR were run in Applied Biosystems’ PRISM 7300HT sequence detection system. Real-time PCR results were analyzed by Applied Biosystems’ SDS 7000 software to determine expressions of p53α, p53β and p53γ, respectively. Each experiment was repeated three times. Then the cases enrolled in the present study were divided into two groups (a high-expressing group and a low-expressing group) according to median p53β expression level based upon real-time PCR results. Analysis of p53 mutational status p53 mRNA species from tumors were reverse transcribed, amplified by PCR, and cotransformed into Saccharomyces cerevisiae together with a linearized yeast homologous recombination expression vector carrying the 5′ and 3′ ends of the p53 open-reading frame. Then the functional yeast-based assay was used as described previously (12) to analyze p53 mutational status. Wild-type p53, which activates transcription of the yeast ADE2 gene that encodes the phosphoribosylaminoimidazole carboxylase results in white colonies, whereas mutant alleles lack transcriptional activity and result in smaller, red colonies. For each tumor sample, the test was performed in triple. The percentages of red colonies and white colonies in each examination were recorded. The tumor with higher percentage of red colonies than white colonies was defined as p53 mutation, conversely, p53 wild-type. Experiments of exploring protection mechanisms of p53β RNA isolation and real-time PCR Ten tumor samples were randomly selected from p53β high-expressing group and p53β low-expressing group, respectively. RNA isolation and real-time PCR were then performed according to the protocol described above. Primers for human B-cell lymphoma 2-associated X protein (bax), caspase-3 and GAPDH were purchased (Sangon Biotech, Shanghai, China). Primer sequences are: bax (Forward: 5′-TCCA CCAAGAAGCTGAGCGAG-3′; Reverse: 5′-GTCCAGCCCATGATGGTTCT-3′); caspase-3 (Forward: 5′-ATGGACAACAACGAAACCTCCGTG-3′; Reverse: 5′-CC ACTCCCAGTCATTCCTTTAGTG-3′); GAPDH (Forward: 5′-CGGAGTCAACGGA TTTGGTCGTAT-3′; Reverse: 5′-AGCCTTCTCCATGGTGGTGAAGAC-3′). Western blot Ten tumor samples were randomly selected from p53β high-expressing group and p53β low-expressing group, respectively. They were lysed on ice in double distilled water containing 10 mM Tris (T5912, Sigma-Aldrich, Shanghai, China) and 1 mM EDTA (798681, Sigma-Aldrich, Shanghai, China). The homogenate was spun at 12000 rpm for 10 min, and the supernatant was recovered as a protein sample, which was measured for protein concentration by means of the Bicinchoninic acid assay method (Pierce Chemical Co, Rockford, IL). Tissue lysates containing 20 μg of protein were electrophoresed in sodium dodecyl sulfate-polyacrylamide gel (s0179, HaiGene, Haerbin, Heilongjiang, China) electrophoresis and were then transferred onto polyvinylidene difluoride membranes (Bio-Rad Laboratories, Hercules, CA). Detection of protein on the membrane was performed with the ECL kit (Amersham Life Sciences Inc, Arlington Heights, IL) using primary antibodies: rabbit anti-bax (ab32503, Abcam, Cambridge, MA) and rabbit anti-active caspase-3 (ab32042, Abcam, Cambridge), followed by exposure to X-ray films. All membranes were re-probed with anti-GAPDH (sc-365062, Santa Cruz Biotechnology, Santa Cruz, CA) for internal control. The resulting images were analyzed by means of Image Pro Plus software (Media Cybernetics, Rockville, MD) to determine the integrated density value of each protein band. Each sample was examined in triplicate. Cell experiments RCC cell lines, 786-O (p53 mutant) and CAKi-1 (p53 wild-type), were obtained from Cell Bank, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. 786-O cells were maintained in RPMI-1640 Medium supplemented with 100 μg/ml streptomycin, 100 U/ml penicillin and 10% fetal bovine serum at 37°C in a humidified atmosphere with 5% CO2. CAKi-1 cells were cultured in McCoy’s 5A Medium supplemented with 1.5 mmol/l glutamine, 2.2 g/l sodium bicarbonate and 10% fetal bovine serum. pCMV-HA and pCMV-HA-p53β plasmids were generated by Shanghai Bioleaf Biotech Co., Ltd, China. 1 × 105 786-O cells were seeded in six-well cell culture plate and cultured for 12 h. After washing three times by phosphate buffer saline, the medium was replaced by Opti-MEM medium without fetal bovine serum or antibiotics. 4 μg plasmids and 10 μl Lipofectamine 2000 (11668027, Invitrogen, Shanghai, China) were diluted gently in 200 μl Opti-MEM medium without fetal bovine serum or antibiotics, incubated in room temperature for 20 min, and added in to each well. The six-well cell culture plate was returned to cell culture incubator for 6 h. Then the Opti-MEM medium was discarded, and replaced by RPMI-1640 Medium. The cells were incubated for 48 h prior to testing for transgene expression. CAKi-1 cells were transfected using the same protocol. The cells transfected with pCMV-HA plasmids were termed as 786-O-pCMV-HA and CAKi-1-pCMV-HA, and 786-O-pCMV-HA-p53β and CAKi-1-pCMV-HA-p53β for transfecting with pCMV-HA-p53β plasmids. In order to examine p53β expressions in these cells, RNA isolation and real-time PCR were then performed according to the protocol described above. To examine expressions of bax and active caspase-3 in cultured cells, Western blot was performed. 786-O, 786-O-pCMV-HA, 786-O-pCMV-HA-p53β, CAKi-1, CAKi-1-pCMV-HA and CAKi-1-pCMV-HA-p53β were lysed in phosphate buffer saline containing 1% IGEPAL, 0.5% sodium deoxycholate, 0.1% sodium dodecyl sulfate, aprotinin (10 μg/ml) and leupeptin (10 μg/ml). Then western blot analyses were performed according to the protocol narrated above. Primary antibodies included rabbit anti-bax (ab32503, Abcam, Cambridge, MA), rabbit anti-active caspase-3 (ab32042, Abcam, Cambridge) and mouse anti-GAPDH (sc-365062, Santa Cruz Biotechnology, Santa Cruz). Each cell was subjected to three independent experiments. Flow cytometry was carried on to determine apoptosis in cells. 786-O, 786-O-pCMV-HA-p53β, CAKi-1 and CAKi-1-pCMV-HA-p53β were harvested to detect apoptotic ratios by using Apoptosis Detection Kit (556570, BD Biosciences, San Diego, CA). The cells were stained with propidium iodide according to the supplier’s instructions. Apoptotic cells were detected using FACSCalibur flow cytometer, Beckman Coulter, Brea. Data were analyzed using FlowJo software (Tree Star Inc, Ashland, OR). Statistical analysis Data were analyzed with SPSS 17.0 statistical software (SPSS Inc., IL) and expressed as mean ± standard error of the mean for continuous variables. Continuous data were compared among groups by using Student’s t test or one-way analysis of variance. Chi-square test and Fisher’s exact test were performed to examine relationship between p53 mutational status and categorical clinicopathological parameters. For correlations between tumor stage from T1 to T4 and expression levels of p53 isoforms, Spearman’s correlation coefficients were calculated. Time-to-event data were analyzed using a Cox proportional hazards regression model, and Kaplan–Meier plots were generated to assess survival probabilities. Comparison of survival curves was performed using log-rank test. Results are presented as HR, with 95% CI and P values. P < 0.05 was considered statistically significant. Results Demographic characteristics of patients Two hundred and sixty eight patients (161 male, 107 female) diagnosed with clear-cell RCC met the inclusion criteria were enrolled into this study. After operations, one male patient died of severe bleeding and one female patient died of hepatic failure. These two cases were excluded from final analysis. Median age was 55 years (31–76 years). Median follow-up was 5.3 years (19–85 months). Table 1 provides the demographic characteristics of patients. Table 1. Demographic characteristics of patients   No. (%)  P value  Gender    0.033   Male  160 (60.2)     Female  106 (39.8)    Age (years)    0.087   ≥55  122 (45.9)     <55  144 (54.1)    Symptoms    0.018   Absent  184 (69.2)     Present  82 (30.8)    Side    0.044   Left  115 (43.2)     Right  151 (56.8)    Tumor grade    0.007   G1+G2  157 (59.0)     G3+G4  109 (41.0)    Tumor stage    0.704   T1  83 (31.2)     T2  60 (22.6)     T3  72 (27.1)     T4  51 (19.1)    NM status    < 0.001   N0M0  170 (63.9)     Others  96 (36.1)    Treatment    0.068   NSS  101 (38.0)     RN  98 (36.8)     RN with TT  67 (25.2)      No. (%)  P value  Gender    0.033   Male  160 (60.2)     Female  106 (39.8)    Age (years)    0.087   ≥55  122 (45.9)     <55  144 (54.1)    Symptoms    0.018   Absent  184 (69.2)     Present  82 (30.8)    Side    0.044   Left  115 (43.2)     Right  151 (56.8)    Tumor grade    0.007   G1+G2  157 (59.0)     G3+G4  109 (41.0)    Tumor stage    0.704   T1  83 (31.2)     T2  60 (22.6)     T3  72 (27.1)     T4  51 (19.1)    NM status    < 0.001   N0M0  170 (63.9)     Others  96 (36.1)    Treatment    0.068   NSS  101 (38.0)     RN  98 (36.8)     RN with TT  67 (25.2)    NSS, nephron sparing surgery; RN, radical nephrectomy; TT, targeted therapy. View Large Expressions of p53 isoforms in tumor tissue Expressions of p53α, p53β and p53γ in tumor samples subgrouped by tumor stage were analyzed by RT-PCR (Figure 1A). Spearman’s correlation analysis showed that no significant differences were detected in different tumor stages regarding to p53α (P = 0.104) or p53γ (P = 0.075), respectively. While, the expressions of p53β were significantly (r = −0.72, P = 0.016) decreased from T1 stage to T4 stage (Figure 1B). Real-time PCR analysis also demonstrated that there were no significant differences of p53α expression (P = 0.271) or p53γ expression (P = 0.114) from T1 to T4 stage, respectively. However, result demonstrated significantly higher level of p53β expression in lower stage versus higher stage (r = −0.65, P = 0.033) (Figure 1C). Figure 1. View largeDownload slide Expressions of p53 isoforms in tumor tissue. (A) Expressions of p53α, p53β and p53γ in tumor samples were analyzed by RT-PCR. (B) The results of RT-PCR were presented in the bar chart. (C) Expression levels of p53 isoforms were analyzed with real-time PCR. Figure 1. View largeDownload slide Expressions of p53 isoforms in tumor tissue. (A) Expressions of p53α, p53β and p53γ in tumor samples were analyzed by RT-PCR. (B) The results of RT-PCR were presented in the bar chart. (C) Expression levels of p53 isoforms were analyzed with real-time PCR. Clinical relevance of p53 mutational status Of the included cases, 197 of 266 (74.1%) patients were wild-type p53, and 69 of 266 (25.9%) harboured p53 mutations. The relevances of clinicopathological features and p53 mutational status were summarized in Table 2. Gender (P = 0.474), age (P = 0.062), symptoms (P = 0.600), side of tumors (P = 0.239), tumor stage (P = 0.087), and NM status (P = 0.065) did not differ with respect to p53 mutational status. p53 mutational status was significantly associated with tumor grade (G1+G2 versus G3+G4, P < 0.001). Table 2. Association of p53 mutational status with clinicopathological features   p53 wild-type  p53 mutation  P value  No. (%)  No. (%)  Gender      0.474   Male  121 (75.6)  39 (24.4)     Female  76 (71.7)  30 (28.3)    Age (years)      0.062   ≥55  97 (79.5)  25 (20.5)     <55  100 (69.4)  44 (30.6)    Symptoms      0.600   Absent  138 (75.0)  46 (25.0)     Present  59 (72.0)  23 (28.0)    Side      0.239   Left  81 (70.4)  34 (29.6)     Right  116 (76.8)  35 (23.2)    Tumor grade      < 0.001   G1+G2  141 (89.8)  16 (10.2)     G3+G4  56 (51.4)  53 (48.6)    Tumor stage      0.087   T1  59 (71.1)  24 (28.9)     T2  41 (68.3)  19 (31.7)     T3  55 (76.4)  17 (23.6)     T4  42 (82.4)  9 (17.6)    NM status      0.065   N0M0  113 (66.5)  57 (33.5)     Others  65 (67.7)  31 (32.3)      p53 wild-type  p53 mutation  P value  No. (%)  No. (%)  Gender      0.474   Male  121 (75.6)  39 (24.4)     Female  76 (71.7)  30 (28.3)    Age (years)      0.062   ≥55  97 (79.5)  25 (20.5)     <55  100 (69.4)  44 (30.6)    Symptoms      0.600   Absent  138 (75.0)  46 (25.0)     Present  59 (72.0)  23 (28.0)    Side      0.239   Left  81 (70.4)  34 (29.6)     Right  116 (76.8)  35 (23.2)    Tumor grade      < 0.001   G1+G2  141 (89.8)  16 (10.2)     G3+G4  56 (51.4)  53 (48.6)    Tumor stage      0.087   T1  59 (71.1)  24 (28.9)     T2  41 (68.3)  19 (31.7)     T3  55 (76.4)  17 (23.6)     T4  42 (82.4)  9 (17.6)    NM status      0.065   N0M0  113 (66.5)  57 (33.5)     Others  65 (67.7)  31 (32.3)    View Large Patients with p53 wild-type carcinoma demonstrated comparable RFS (P = 0.361) and OS (P = 0.218) with patients with p53 mutant carcinoma, respectively (Table 3). Table 3. Associations between p53 mutational status and survival   p53 wild-type  p53 mutation  P value  Median RFS (months)  52.2  46.3  0.361  Median OS (months)  61.3  57.5  0.218    p53 wild-type  p53 mutation  P value  Median RFS (months)  52.2  46.3  0.361  Median OS (months)  61.3  57.5  0.218  View Large Influences of p53β expression on RFS and OS Influences of p53β expression on RFS and OS were examined based upon follow-up data. Result showed that in patients with p53 mutant tumor, high p53β expression group was associated with significantly improved RFS (median 58.2 months versus median 46.0 months; P = 0.039) and OS (median 65.1 months versus median 49.9 months; P = 0.042) compared with low p53β expression group, respectively. In patients with p53 wild-type clear-cell RCC, result was consistent. The RFS time and OS time of p53β high expression group were median 67.1 months and median 69.9 months, respectively, both significantly (P < 0.001 and P = 0.001) higher than p53β low expression group (median 52.7 months and median 58.7 months, respectively) (Figure 2). Figure 2. View largeDownload slide Influences of p53β expression on RFS and OS. Censored cases are represented by a ‘+’. The median survival time (95% CI) and log-rank test P value are shown. (A, B) show the influences of p53β expression on RFS and OS in patients with p53 mutant tumors. (C, D) show the influences of p53β expression on RFS and OS in patients with p53 wild-type tumors. Figure 2. View largeDownload slide Influences of p53β expression on RFS and OS. Censored cases are represented by a ‘+’. The median survival time (95% CI) and log-rank test P value are shown. (A, B) show the influences of p53β expression on RFS and OS in patients with p53 mutant tumors. (C, D) show the influences of p53β expression on RFS and OS in patients with p53 wild-type tumors. A multivariate model comprising p53β expression and selected clinicopathological parameters (symptoms, tumor grade, tumor stage, NM status, treatment methods) was generated (Table 4). High expression of p53β was indicated better RFS (HR 2.599, 95% CI 1.472–4.551, P = 0.038) and OS (HR 2.604, 95% CI 1.453–4.824, P = 0.031) of clear-cell RCC patients (Table 4). Table 4. Multivariate analysis of p53β in patients with clear-cell renal cell carcinoma   RFS  OS  HR (95% CI)  P value  HR (95% CI)  P value  Symptoms   Absent  Reference    Reference     Present  1.644 (0.991–1.972)  0.033  3.536 (1.467–4.713)  0.010  Tumor grade   G1+G2  Reference    Reference     G3+G4  1.252 (0.958–1.471)  0.042  1.833 (0.968–2.012)  0.069  Tumor stage   T1  Reference    Reference     T2  1.175 (0.730–1.664)  0.573  0.988 (0.768–1.631)  0.420   T3  1.280 (0.993–2.016)  0.027  1.605 (1.001–2.384)  0.066   T4  2.867 (1.368–3.593)  0.008  1.594 (0.986–1.727)  0.041  NM status   N0M0  Reference    Reference     Others  1.079 (0.912–1.633)  0.042  2.501 (1.393–3.632)  0.044  Treatment   NSS  Reference    Reference     RN  0.907 (0.669–1.434)  0.106  2.113 (1.766–4.450)  0.491   RN with TT  1.101 (0.977–1.142)  0.057  1.143 (0.961–1.385)  0.035  p53β   High expression  Reference    Reference     Low expression  2.599 (1.472–4.551)  0.038  2.604 (1.453–4.824)  0.031    RFS  OS  HR (95% CI)  P value  HR (95% CI)  P value  Symptoms   Absent  Reference    Reference     Present  1.644 (0.991–1.972)  0.033  3.536 (1.467–4.713)  0.010  Tumor grade   G1+G2  Reference    Reference     G3+G4  1.252 (0.958–1.471)  0.042  1.833 (0.968–2.012)  0.069  Tumor stage   T1  Reference    Reference     T2  1.175 (0.730–1.664)  0.573  0.988 (0.768–1.631)  0.420   T3  1.280 (0.993–2.016)  0.027  1.605 (1.001–2.384)  0.066   T4  2.867 (1.368–3.593)  0.008  1.594 (0.986–1.727)  0.041  NM status   N0M0  Reference    Reference     Others  1.079 (0.912–1.633)  0.042  2.501 (1.393–3.632)  0.044  Treatment   NSS  Reference    Reference     RN  0.907 (0.669–1.434)  0.106  2.113 (1.766–4.450)  0.491   RN with TT  1.101 (0.977–1.142)  0.057  1.143 (0.961–1.385)  0.035  p53β   High expression  Reference    Reference     Low expression  2.599 (1.472–4.551)  0.038  2.604 (1.453–4.824)  0.031  NSS, nephron sparing surgery; RN, radical nephrectomy; TT, targeted therapy. View Large Experiments of exploring protection mechanisms of p53β For tumor samples, real-time PCR showed messenger RNA expressions of bax (P = 0.023) and caspase-3 (P = 0.007) were both significantly higher in p53β high-expressing group compared with p53β low-expressing group (Figure 3A). Moreover, western blot analysis demonstrated significantly higher levels of bax (P = 0.039) and active caspase-3 (P = 0.020) expressions in p53β high-expressing group versus p53β low-expressing group, respectively (Figure 3B and C). Figure 3. View largeDownload slide Experiments of exploring protection mechanisms of p53β. (A) Expressions of bax and caspase-3 in tumor samples (p53β high-expressing group, n = 10; p53β low-expressing group, n = 10) were analyzed with real-time PCR. Each sample was examined in triplicate. (B, C) Western blot analysis of expressions of bax and active caspase-3 in tumor samples (p53β high-expressing group, n = 10; p53β low-expressing group, n = 10). GAPDH served as an internal control. The ratios (in percentile) of bax/GAPDH and active caspase-3/GAPDH were determined by dividing the densitometric values of these protein bands obtained from the western blot. Each sample was examined in triplicate. (D) 786-O (p53 mutant) and CAKi-1 (p53 wild-type) cells were transfected with pCMV-HA plasmids or pCMV-HA-p53β plasmids. Expressions of p53β were analyzed by real-time PCR. Each cell was subjected to three independent experiments. (E, F) Western blot analysis of expressions of bax and active caspase-3 in cells. Each cell was subjected to three independent experiments. (G) Quantifications of apoptosis in786-O cells, CAKi-1 cells and p53β-transfected cells were analyzed by flow cytometry. The apoptotic peaks were indicated by black arrows. Each experiment was performed in triplicate. (H) The percentages of apoptotic cells were evaluated. All data were analyzed by SPSS 17.0 statistical software with Student’s t test or one-way analysis of variance. P < 0.05 was considered statistically significant. Figure 3. View largeDownload slide Experiments of exploring protection mechanisms of p53β. (A) Expressions of bax and caspase-3 in tumor samples (p53β high-expressing group, n = 10; p53β low-expressing group, n = 10) were analyzed with real-time PCR. Each sample was examined in triplicate. (B, C) Western blot analysis of expressions of bax and active caspase-3 in tumor samples (p53β high-expressing group, n = 10; p53β low-expressing group, n = 10). GAPDH served as an internal control. The ratios (in percentile) of bax/GAPDH and active caspase-3/GAPDH were determined by dividing the densitometric values of these protein bands obtained from the western blot. Each sample was examined in triplicate. (D) 786-O (p53 mutant) and CAKi-1 (p53 wild-type) cells were transfected with pCMV-HA plasmids or pCMV-HA-p53β plasmids. Expressions of p53β were analyzed by real-time PCR. Each cell was subjected to three independent experiments. (E, F) Western blot analysis of expressions of bax and active caspase-3 in cells. Each cell was subjected to three independent experiments. (G) Quantifications of apoptosis in786-O cells, CAKi-1 cells and p53β-transfected cells were analyzed by flow cytometry. The apoptotic peaks were indicated by black arrows. Each experiment was performed in triplicate. (H) The percentages of apoptotic cells were evaluated. All data were analyzed by SPSS 17.0 statistical software with Student’s t test or one-way analysis of variance. P < 0.05 was considered statistically significant. To examine the effects of p53β on RCC cells, p53β gene transfected 786-O cells and CAKi-1 cells were generated. Results of real-time PCR showed expressions of p53β were both significantly upregulated in p53β gene transfected 786-O cells (P < 0.001) and CAKi-1 cells (P < 0.001) (Figure 3D). Western blot analysis showed higher expressions of bax (P = 0.033) and active caspase-3 (P < 0.001) in 786-O-pCMV-HA-p53β cells than in 786-O cells, and higher in CAKi-1-pCMV-HA-p53β cells (P = 0.020, P = 0.041) than in CAKi-1 cells, respectively (Figure 3E and F). For quantification of apoptosis, flow cytometry analysis was performed (Figure 3G). Results showed that the cells transfected with p53β harboured higher ratios of apoptosis, irrespective of p53 mutational status (Figure 3H). Discussion To date, a large number of studies have reported that p53 appears to be mutated in about 50% of human cancers (13,14). While in RCC, p53 itself is rarely mutated, only existing in 3–33% of patients (15). Moreover, the expression of p53 did not reveal any prognostic significance in RCC (16). In the present study, 25.9% of patients carried mutant gene of p53. In breast cancer, mutation frequency of p53 is less than would be expected for a protein that plays such a pivotal role in maintaining genomic integrity (17), and many studies have shown a lack of association of breast cancer risk with polymorphisms in p53, indicating that wild-type p53 becomes inactivated by mechanisms other than mutation (9). In the present study, p53 mutant patients had similar RFS and OS with p53 wild-type patients, indicating p53 mutation status had no effect on prognosis of RCC patients. However, the role of p53 mutational status in predicting the prognosis of RCC is still a controversial issue. Girgin C’s report showed survival rates of mutant p53 and wild-type p53 cases with RCC were 33.3% and 84.2%, respectively (P = 0.0027) (18), with a conclusion that p53 mutation status was one of the most important prognostic factors. While, there was no evidence to support the conclusion that p53 mutation was associated with poorer survival of RCC in another study (14). In other types of cancers such as squamous-cell carcinoma of the head/neck and esophageal carcinoma, p53 mutation is increasingly identified as a poor prognostic marker (19–21). Further studies are needed to explain these discrepancies. In recent years, the role of p53 isoforms in carcinogenesis has emerged (22). However, their functions remain unclear, which were concluded primarily from some studies using several cell lines (23,24). Nevertheless, previous data indicated that p53 isoforms could enhance or inhibit ability of p53 to activate certain target promoters and to induce apoptosis (23,24). Therefore, regulated expression of p53 isoform is crucial for biological outcome of p53. In 2009, we firstly confirmed six p53 isoforms in clear-cell RCC (4). Of the six isoforms, only p53β mRNA was significantly overexpressed in tumor samples and was correlated with tumor stage, indicating p53β a good predictor of cancer progression for RCC. In previous reports, DO-1 was commonly used as an indicator of p53β (25). However, DO-1 can also recognize p53α and p53γ. Jean–Christophe Bourdon’s group firstly raised an antibody KJC8, specific to the p53β isoforms (that is, p53β, Δ40p53β and Δ133p53β), which was still unable to detect p53β specifically (23,26). Moreover, it was uncertain to work in staining paraffin-embedded sections with KJC8 (26). Hence, in the present study, RT-PCR and real-time PCR were performed instead of immumohistochemical staining. Our result showed only p53β expression level was correlated with tumor stage, which was consistent with our previous data. Moreover, expression of p53β decreased accompanied by increasement of tumor stage and lower RFS and OS, implying p53β a beneficial factor for the patients with clear-cell RCC. To our knowledge, p53β has already been investigated as a protective factor against damage inflicted by tumors such as breast cancer and colon cancer (9,27). Breast cancer patients expressing low levels of p53β had worse prognosis, whereas patients expressing high levels of p53β had better prognosis (9). In addition, p53β expression was positively associated with long-term survival in acute myeloid leukaemia (28). However, p53β was also found to correlate with worse RFS in ovarian cancer patients with functionally active p53 (29). Avery–Kiejda and colleagues attributed the reason to the different sites of cancers (9). Hereby we firstly confirmed high expression of p53β as a predictor for good prognosis in patients with clear-cell RCC, regardless of p53 mutational status. High p53β expression resulted in a significant reduction of risk for recurrence and a significant increase of survival compared with low p53β expression. It is unclear how p53β exerts a beneficial function for the patients with RCC. Bax is a key mediator of cell growth and apoptosis. Overexpression of bax results in cell death through promotion of cytosolic accumulation of cytochrome C released from mitochondria (30). p53β was found to activate the promoter of bax, thus promoting apoptosis and senescence, and retaining tumor suppressive functions (31). Most importantly, Marcel and co-authors added additional layer of understanding into the mechanism of p53β function that p53β can bind to p53 in a DNA-mediated manner to create p53β/p53 complex, then enhancing p53 transcriptional activity on target gene bax that regulate cell cycle progression and apoptosis (31,32). In the present study, transfection of p53β was able to upregulate expression of bax and activate final apoptotic effector caspase-3, indicating a role of apoptosis in the protection mechanism of p53β. In conclusion, p53β expressed significantly more in lower tumor stage than in higher stage in RCC. For the first time, high p53β expression was proved to provide prolonged RFS and OS in clear-cell RCC patients, regardless of p53 mutational status, indicating p53β a good predictor of prognosis in patients with clear-cell RCC. Activations of bax and downstream effector caspase-3 followed by apoptosis of tumor cells were considered as possible protection mechanisms of p53β in RCC. Further knowledge regarding the details of mechanisms of protection provided by p53β is required to potentially provide p53-based gene diagnosis and individual biological therapy. Funding This study was funded by Foundation for Outstanding Young Scientist in Shandong Province (BS2011SW039) and National Natural Science Foundation of China (81572534, 81300629). Conflict of Interest Statement: None declared. Abbreviations CI confidence interval HR hazard ratio OS overall survival RCC renal cell carcinoma RFS recurrence-free survival References 1. 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CarcinogenesisOxford University Press

Published: Mar 1, 2018

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