OBJECTIVES: Renal cell carcinoma (RCC) is a malignant renal tumor that poses a significant threat to patient health. Accurate preoperative pathological grading plays a crucial role in determining the appropriate treatment for this disease. Currently, deep learning technology has become an important method for pathological grading of RCC. However, existing methods primarily rely on single-phase computed tomography (CT) imaging for analysis and prediction, which has limitations such as missing small lesions, one-sided evaluation, and local focusing issues. Therefore, this study proposes a multi-modal deep learning algorithm that integrates multi-phase enhanced CT images with clinical variable data, aiming to provide a basis for predicting the pathological grading of RCC. METHODS: First, the algorithm took four-phase enhanced CT images from the plain scan, arterial phase, venous phase, and delayed phase, along with clinical variables, as inputs. Then, an embedding encoding module was used to extract heterogeneous information from the clinical variables, and a 3-dimensional (3D) ResNet50 model was employed to capture spatial information from the multi-phase enhanced CT image data. Finally, a Fusion module deeply integrated the feature information from clinical variables and each phase's CT image features, further utilizing a cross-self-attention mechanism to achieve multi-phase feature fusion. This approach comprehensively captures the deep semantic information from the patient data, fully leveraging the complementary advantages of multi-modal and multi-phase data. To validate the effectiveness of the proposed method, a total of 1 229 RCC patients were approved by ethics review were included to train the model. RESULTS: Experimental results demonstrated superior performance compared to traditional radiomics and state-of-the-art deep learning methods, achieving an accuracy of 83.87%, a recall rate of 95.04%, and an F1-score of 82.23%. CONCLUSIONS The proposed algorithm exhibits strong stability and sensitivity, significantly enhancing the predictive performance of RCC pathological grading. It offers a novel approach for accurate RCC diagnosis and personalized treatment planning.
Humans ; Carcinoma, Renal Cell/pathology* ; Deep Learning ; Kidney Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed/methods* ; Algorithms ; Neoplasm Grading ; Male ; Female ; Middle Aged

OBJECTIVES: To investigate the characteristics of immune cell infiltration in tumor samples from Chinese patients with clear cell renal cell carcinoma (ccRCC) and the correlation of immune cell infiltration with tumor stage and response to immunotherapy. METHODS: Tumor samples and clinicopathological data were collected from 154 ccRCC patients treated in Nanfang Hospital, Southern Medical University from October, 2020 to October, 2023. The immune cell types infiltrating the tumor tissues were identified using immunohistochemistry and immunofluorescence staining, and their correlations with the patients' clinicopathological characteristics were analyzed. Patient-derived tumor tissue fragment models (PDTF) models, constructed using tumor tissues from 22 patients, were treated with PD-1 monoclonal antibody, and T cell activation was detected using flow cytometry to assess the patients' responses to immunotherapy. RESULTS: In Chinese ccRCC patients included in this study, CD8⁺ T cells, CD4⁺ T cells, and CD3⁺ T cells were the most abundant in the tumor tissues. Higher infiltration levels of CD3⁺ T cells (P=0.004), PD-1⁺ T cells (P=0.020), CD68⁺ T cells (P=0.049), CD79⁺ T cells (P=0.049), and Tryptase⁺ cells (P=0.049) were all positively correlated with a larger tumor size (≥5 cm). A higher infiltration level of CD4⁺ T cells was associated with a lower tumor stage. Patients with higher International Society of Urological Pathology (ISUP) grades had higher infiltration levels of CD3⁺ T cells (P=0.023), CD8⁺ T cells (P=0.045), PD-1⁺ T cells (P=0.014), CD20⁺ B cells (P=0.020) and CD79⁺ B cells (P=0.049), and lower levels of Tryptase⁺ cells (P=0.001). Patients with abundant infiltrating immune cells tended to have better responses to immunotherapy. CONCLUSIONS The infiltrating immune cells are heterogeneous in Chinese ccRCC patients, and immune cell infiltration characteristics are closely correlated with clinicopathological parameters of the patients.
Humans ; Carcinoma, Renal Cell/pathology* ; Kidney Neoplasms/pathology* ; Immunotherapy ; Male ; Lymphocytes, Tumor-Infiltrating/immunology* ; Female ; Middle Aged ; CD8-Positive T-Lymphocytes/immunology* ; Aged ; T-Lymphocytes/immunology* ; Programmed Cell Death 1 Receptor/immunology* ; Adult ; CD4-Positive T-Lymphocytes/immunology* ; Neoplasm Staging

OBJECTIVES: To investigate the expression levels of marginal zone B and B1-cell-specific protein (MZB1) in pan-cancer and its association with patient prognosis and tumor microenvironment (TME). METHODS: MZB1 expression data, clinicopathological parameters, and survival data from 33 cancer types were extracted from the UCSC database for analyzing the correlations of MZB1 with clinical stage, patient prognosis, immunomodulatory genes, immune checkpoint genes, tumor stemness, immune cell infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI). MZB1 gene mutations in pan-cancer were assessed using cBioPortal online database, and the value of MZB1 for cancer diagnosis was evaluated using ROC curve analysis. MZB1 expression levels in myeloid leukemia and renal carcinoma cells were detected using RT-qPCR and Western blotting, and the effect of MZB1 knockdown on cell proliferation was examined using EdU assay. RESULTS: MZB1 was significantly overexpressed in 20 cancer types, including kidney renal clear cell carcinoma (KIRC), breast invasive carcinoma, and acute myeloid leukemia. Its expression was associated with TNM stage, clinical stage, overall survival, and progression-free survival in multiple cancers. In most tumors, MZB1 expression was correlated significantly with immunomodulatory genes, immune checkpoint genes, tumor stemness, immune cell infiltration, TMB, and microsatellite instability. Gene amplification was the predominant mutation type of MZB1 in pan-cancer, and MZB1 showed high diagnostic value for skin cutaneous melanoma, KIRC, and head and neck squamous cell carcinoma. MZB1 was highly expressed in different myeloid leukemia cell lines and renal carcinoma cell lines, and MZB1 knockdown significantly suppressed the proliferation of HL60 and 769-P cells. CONCLUSIONS MZB1 is highly expressed in a variety of tumors, and its aberrant expression affects the occurrence and prognosis of many tumors, suggesting its potential as a novel tumor biomarker and immunomodulatory target.
Humans ; Prognosis ; Tumor Microenvironment ; Neoplasms/pathology* ; Cell Line, Tumor ; Mutation ; Kidney Neoplasms ; Microsatellite Instability ; Cell Proliferation ; Carcinoma, Renal Cell

OBJECTIVES: To investigate the role of Holliday cross-recognition protein (HJURP) in tumorigenesis, progression, and immunotherapy responses. METHODS: Bioinformatics approaches were used to analyze the expression level of HJURP in various cancers and its association with prognosis, clinical stage, and immune cell infiltration using TCGA, GTEx, SangerBox and TIMER 2.0 databases. LinkedOmics database was employed to investigate HJURP-related genes and their potential functions in kidney renal clear cell carcinoma (KIRC). The expression of HJURP in KIRC samples was examined with immunohistochemistry, Western blotting and qRT-PCR, and the effect of HJURP silencing on cell proliferation and migration was tested in cultured KIRC cells. RESULTS: HJURP was highly expressed in 26 cancers with negative correlations with the patients' survival outcomes in 5 cancers including KIRC (P<0.05). HJURP expression levels was strongly correlated with clinical stages and immune cell infiltration in the tumors. In KIRC, HJURP expression was significantly elevated (P<0.0001) and showed a positive correlation with TNM stage (P<0.05), overall stage (P<0.01) and immune cell infiltration. Gene Ontology (GO) functional analysis showed that HJURP is predominantly enriched in biological processes such as biological regulation and metabolic processes. Concerning cellular components, HJURP is primarily localized to the cell membrane and nucleus. In terms of molecular functions, it is chiefly enriched in activities related to protein binding and ion binding. HJURP was highly expressed in both clinical KIRC tissues and KIRC cell lines (P<0.001). In cultured KIRC cells, silencing of HJURP significantly inhibited cell proliferation and migration abilities. CONCLUSIONS HJURP may serves as an indicator of prognosis and immunotherapy response of KIRC, and its high expression enhances malignant behaviors of KIRC cells.
Humans ; Prognosis ; Kidney Neoplasms/pathology* ; Biomarkers, Tumor/metabolism* ; Carcinoma, Renal Cell/pathology* ; DNA-Binding Proteins/genetics* ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement

Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
Humans ; Nomograms ; Retrospective Studies ; Carcinoma, Renal Cell/pathology* ; Prognosis ; Risk Factors ; Nephrectomy ; Kidney Neoplasms/pathology* ; Necrosis

Objective: To report the long-term survival of renal cell carcinoma (RCC) patients treated with radical nephrectomy in Sun Yat-sen University Cancer Center. Methods: We retrospectively analyzed the clinical, pathological and follow-up records of 1 367 non-metastatic RCC patients treated with radical nephrectomy from 1999 to 2020 in this center. The primary endpoint of this study was overall survival rate. Survival curves were estimated using the Kaplan-Meier method, and group differences were compared through Log-rank test. Univariate and multivariate Cox analysis were fit to determine the clinical and pathological features associated with overall survival rate. Results: A total of 1 367 patients treated with radical nephrectomy with complete follow-up data were included in the study. The median follow-up time was 52.6 months, and 1 100 patients survived and 267 died, with the median time to overall survival not yet reached. The 5-year and 10-year overall survival rates were 82.8% and 74.9%, respectively. The 5-year and 10-year overall survival rates of Leibovich low-risk patients were 93.3% and 88.2%, respectively; of Leibovich intermediate-risk patients were 82.2% and 72.3%, respectively; and of Leibovich high-risk patients were 50.5% and 30.2%, respectively. There were significant differences in the long-term survival among the three groups (P<0.001). The 10-year overall survival rates for patients with pT1, pT2, pT3 and pT4 RCC were 83.2%, 73.6%, 55.0% and 31.4%, respectively. There were significant differences among pT1, pT2, pT3 and pT4 patients(P<0.001). The 5-year and 10-year overall survival rates of patients with lymph node metastasis were 48.5% and 35.6%, respectively, and those of patients without lymph node metastasis were 85.1% and 77.5%, respectively. There was significant difference in the long-term survival between patients with lymph node metastasis and without lymph node metastasis. The 10-year overall survival rate was 96.2% for nuclear Grade 1, 81.6% for nuclear Grade 2, 60.5% for nuclear Grade 3, and 43.4% for nuclear Grade 4 patients. The difference was statistically significant. There was no significant difference in the long-term survival between patients with localized renal cancer (pT1-2N0M0) who underwent open surgery and minimally invasive surgery (10-year overall survival rate 80.5% vs 85.6%, P=0.160). Multivariate Cox analysis showed that age≥55 years (HR=2.11, 95% CI: 1.50-2.96, P<0.001), T stage(T3+ T4 vs T1a: HR=2.37, 95% CI: 1.26-4.46, P=0.008), local lymph node metastasis (HR=3.04, 95%CI: 1.81-5.09, P<0.001), nuclear grade (G3-G4 vs G1: HR=4.21, 95%CI: 1.51-11.75, P=0.006), tumor necrosis (HR=1.66, 95% CI: 1.17-2.37, P=0.005), sarcomatoid differentiation (HR=2.39, 95% CI: 1.31-4.35, P=0.005) and BMI≥24kg/m(2) (HR=0.56, 95%CI: 0.39-0.80, P=0.001) were independent factors affecting long-term survival after radical nephrectomy. Conclusions: The long-term survival of radical nephrectomy in patients with renal cell carcinoma is satisfactory. Advanced age, higher pathological stage and grade, tumor necrosis and sarcomatoid differentiation were the main adverse factors affecting the prognosis of patients. Higher body mass index was a protective factor for the prognosis of patients.
Humans ; Middle Aged ; Carcinoma, Renal Cell/secondary* ; Lymphatic Metastasis ; Retrospective Studies ; Neoplasm Staging ; Kidney Neoplasms/pathology* ; Prognosis ; Nephrectomy ; Survival Analysis ; Necrosis/surgery* ; Survival Rate

Humans ; Carcinoma, Renal Cell/pathology* ; Kidney Neoplasms/pathology* ; Biomarkers, Tumor

Objective: To investigate the clinicopathological features, molecular genetic features, differential diagnosis and prognosis of ELOC mutated renal cell carcinoma. Methods: From January 2015 to June 2022, 11 cases of renal cell carcinoma with clear-cell morphology, expression of CAⅨ and CK7 and no 3p deletion were collected. Two cases of ELOC mutant renal cell carcinoma were diagnosed using whole exome sequencing (WES). The clinical features, morphology, immunophenotype, FISH and WES results were analyzed. The relevant literature was reviewed. Results: The two patients were both male, aged 29 and 51 years, respectively. They were both found to have a renal mass by physical examination. The maximum diameters of the tumors were 3.5 cm and 2.0 cm, respectively. At the low magnification, the tumors were well-defined. The tumor cells showed a pushing border and were separated by thick fibrous bands, forming nodules. The tumor cells were arranged in a variety of patterns, including tubular, papillary, solid nest or alveolar. At high magnification, the tumor cells were large, with well-defined cell borders and clear cytoplasm or fine eosinophilic granules. CAⅨ was diffusely box-like positive in both cases. Case 1 was partially and moderately positive for CK7, strongly positive for CD10, diffusely and moderately positive for P504S, and weakly positive for 34βE12. In case 2, CK7 and CD10 were both partially, moderately positive and P504s were diffusely positive, but 34βE12 was negative. FISH results showed that both cases had no 3p deletion. ELOC c.235T>A (p.Y79N) mutation was identified using WES in case 1, while ELOC c.236_237inv (p.Y79C) mutation was identified in case 2. Conclusions: As a new clinical entity, ELOC mutated renal cell carcinoma may be underdiagnosed due to its overlap with clear cell renal cell carcinoma in morphology and immunophenotype. The diagnosis of renal cell carcinoma with ELOC mutation should be confirmed by morphology, immunohistochemistry, FISH and gene mutation detection. However, more additional cases are needed to explain its biological behavior and prognosis.
Humans ; Male ; Biomarkers, Tumor/genetics* ; Carcinoma, Renal Cell/pathology* ; Chromosome Aberrations ; Kidney Neoplasms/pathology* ; Molecular Biology ; Mutation ; Prognosis

Objective: To explore the potential pathogenesis of clear cell renal cell carcinoma (ccRCC) based on the HIF-1α/ACLY signaling pathway, as well as to provide new ideas for the treatment of ccRCC. Methods: Seventy-eight ccRCC cases diagnosed at the First Affiliated Hospital of Soochow University, Suzhou, China were collected. The VHL mutation was examined using exon sequencing. The expression of HIF-1α/ACLY in VHL-mutated ccRCC was evaluated using immunohistochemical staining and further validated in VHL-mutated ccRCC cell lines (786-O, A498, UM-RC-2, SNU-333, and Caki-2) using Western blot. The mRNA and protein levels of ACLY were detected using real-time quantitative PCR and Western blot after overexpression or interference with HIF-1α in ccRCC cell lines. HeLa cells were treated with CoCl₂ and hypoxia (1%O₂) to activate HIF-1α and then subject to the detection of the ACLY mRNA and protein levels. The potential molecular mechanism of HIF-1α-induced ACLY activation was explored through JASPAR database combined with chromatin immunoprecipitation assay (ChIP) and luciferase reporter gene assay. The effect of HIF-1α/ACLY regulation axis on lipid accumulation was detected using BODIPY staining and other cell biological techniques. The expression of ACLY was compared between patients with ccRCC and those with benign lesions, and the feasibility of ACLY as a prognostic indicator for ccRCC was explored through survival analysis. Results: Exon sequencing revealed that 55 (70.5%) of the 78 ccRCC patients harbored a VHL inactivation mutation, and HIF-1α expression was associated with ACLY protein levels. The protein levels of ACLY and HIF-1α in ccRCC cell lines carrying VHL mutation were also correlated to various degrees. Overexpression of HIF-1α in A498 cells increased the mRNA and protein levels of ACLY, and knockdown of HIF-1α in Caki-2 cells inhibited the mRNA and protein levels of ACLY (P<0.001 for all). CoCl₂ and hypoxia treatment significantly increased the mRNA and protein levels of ACLY by activating HIF-1α (P<0.001 for all). The quantification of transcriptional activity of luciferase reporter gene and ChIP-qPCR results suggested that HIF-1α could directly bind to ACLY promoter region to transcriptionally activate ACLY expression and increase ACLY protein level (P<0.001 for all). The results of BODIPY staining suggested that the content of free fatty acids in cell lines was associated with the levels of HIF-1α and ACLY. The depletion of HIF-1α could effectively reduce the accumulation of lipid in cells, while the overexpression of ACLY could reverse this process. At the same time, cell function experiments showed that the proliferation rate of ccRCC cells with HIF-1α knockdown was significantly decreased, and overexpression of ACLY could restore proliferation of these tumor cells (P<0.001). Survival analysis further showed that compared with the ccRCC patients with low ACLY expression, the ccRCC patients with high ACLY expression had a poorer prognosis and a shorter median survival (P<0.001). Conclusions: VHL mutation-mediated HIF-1α overexpression in ccRCC promotes lipid synthesis and tumor progression by activating ACLY. Targeting the HIF-1α/ACLY signaling axis may provide a theoretical basis for the clinical diagnosis and treatment of ccRCC.
Humans ; Carcinoma, Renal Cell/pathology* ; Kidney Neoplasms/pathology* ; HeLa Cells ; Von Hippel-Lindau Tumor Suppressor Protein/genetics* ; Mutation ; Signal Transduction ; Luciferases/therapeutic use* ; Hypoxia/genetics* ; RNA, Messenger ; Lipids/therapeutic use* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Cell Line, Tumor ; Gene Expression Regulation, Neoplastic

Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
Humans ; Nomograms ; Retrospective Studies ; Carcinoma, Renal Cell/pathology* ; Prognosis ; Risk Factors ; Nephrectomy ; Kidney Neoplasms/pathology* ; Necrosis