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 evaluate the implications of the prognostic nutrition index (PNI) in non-metastatic renal cell carcinoma (RCC) patients treated with surgery and to compare it with other hematological biomarkers, including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and systemic immune inflammation index (SII). METHODS: A cohort of 328 non-metastatic RCC patients who received surgical treatment between 2010 and 2012 at Peking University First Hospital was analyzed retrospectively. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff values of the hematological biomarkers. The Youden index was maximum for PNI was value of 47.3. So we divided the patients into two groups (PNI≤ 47. 3 and >47. 3) for further analysis. Categorical variables [age, gender, body mass index (BMI), surgery type, histological subtype, necrosis, pathological T stage and tumor grade] were compared using the Chi-square test and Student' s t test. The association of the biomarkers with overall survival (OS) and disease-free survival (DFS) was analyzed using Kaplan-Meier methods with log-rank test, followed by multivariate Cox proportional hazards model. RESULTS: According to the maximum Youden index of ROC curve, the best cut-off value of PNI is 47. 3. Low level of PNI was significantly associated with older age, lower BMI and higher tumor pathological T stage (P < 0.05). Kaplan-Meier univariate analysis showed that lower PNI was significantly correlated with poor OS and DFS (P < 0.05). In addition, older age, lower BMI, tumor necrosis, higher tumor pathological T stage and Fuhrman grade were significantly correlated with poor OS (P < 0.05). Cox multivariate analysis showed that among the four hematological indexes, only PNI was an independent factor significantly associated with OS, whether as a continuous variable (HR=0.9, 95%CI=0.828-0.978, P=0.013) or a classified variable (HR=2.397, 95%CI=1.061-5.418, P=0.036). CONCLUSION Low PNI was a significant predictor for advanced pathological T stage, decreased OS, or DFS in non-metastatic RCC patients treated with surgery. In addition, PNI was superior to the other hematological biomar-kers as a useful tool for predicting prognosis of RCC in our study. It should be externally validated in future research before the PNI can be used widely as a predictor of RCC patients undergoing nephrectomy.
Humans ; Prognosis ; Nutrition Assessment ; Carcinoma, Renal Cell/surgery* ; Retrospective Studies ; Biomarkers ; Kidney Neoplasms/pathology*

Humans ; Carcinoma, Renal Cell/pathology* ; Kidney Neoplasms/pathology* ; Thinking ; World Health Organization

Objective: To investigate the expression of glycoprotein non metastatic melanoma protein B (GPNMB) in renal eosinophilic tumors and to compare the value of GPNMB with CK20, CK7 and CD117 in the differential diagnosis of renal eosinophilic tumors. Methods: Traditional renal tumor eosinophil subtypes, including 22 cases of renal clear cell carcinoma eosinophil subtype (e-ccRCC), 19 cases of renal papillary cell carcinoma eosinophil subtype (e-papRCC), 17 cases of renal chromophobe cell carcinoma eosinophil subtype (e-chRCC), 12 cases of renal oncocytoma (RO) and emerging renal tumor types with eosinophil characteristics [3 cases of eosinophilic solid cystic renal cell carcinoma (ESC RCC), 3 cases of renal low-grade eosinophil tumor (LOT), 4 cases of fumarate hydratase-deficient renal cell carcinoma (FH-dRCC) and 5 cases of renal epithelioid angiomyolipoma (E-AML)], were collected at the Affiliated Drum Tower Hospital of Nanjing University Medical School from January 2017 to March 2022. The expression of GPNMB, CK20, CK7 and CD117 was detected by immunohistochemistry and statistically analyzed. Results: GPNMB was expressed in all emerging renal tumor types with eosinophil characteristics (ESC RCC, LOT, FH-dRCC) and E-AML, while the expression rates in traditional renal eosinophil subtypes e-papRCC, e-chRCC, e-ccRCC and RO were very low or zero (1/19, 1/17, 0/22 and 0/12, respectively); the expression rate of CK7 in LOT (3/3), e-chRCC (15/17), e-ccRCC (4/22), e-papRCC (2/19), ESC RCC (0/3), RO (4/12), E-AML(1/5), and FH-dRCC (2/4) variedly; the expression of CK20 was different in ESC RCC (3/3), LOT(3/3), e-chRCC(1/17), RO(9/12), e-papRCC(4/19), FH-dRCC(1/4), e-ccRCC(0/22) and E-AML(0/5), and so did that of CD117 in e-ccRCC(2/22), e-papRCC(1/19), e-chRCC(16/17), RO(10/12), ESC RCC(0/3), LOT(1/3), E-AML(2/5) and FH-dRCC(1/4). GPNMB had 100% sensitivity and 97.1% specificity in distinguishing E-AML and emerging renal tumor types (such as ESC RCC, LOT, FH-dRCC) from traditional renal tumor types (such as e-ccRCC, e-papRCC, e-chRCC, RO),respectively. Compared with CK7, CK20 and CD117 antibodies, GPNMB was more effective in the differential diagnosis (P<0.05). Conclusion: As a new renal tumor marker, GPNMB can effectively distinguish E-AML and emerging renal tumor types with eosinophil characteristics such as ESC RCC, LOT, FH-dRCC from traditional renal tumor eosinophil subtypes such as e-ccRCC, e-papRCC, e-chRCC and RO, which is helpful for the differential diagnosis of renal eosinophilic tumors.
Humans ; Kidney Neoplasms/pathology* ; Carcinoma, Renal Cell/pathology* ; Diagnosis, Differential ; Angiomyolipoma/diagnosis* ; Biomarkers, Tumor/metabolism* ; Leukemia, Myeloid, Acute/diagnosis* ; Membrane Glycoproteins

Objective: To investigate the clinicopathologic and molecular characteristics of fumarate hydratase (FH) deficient uterine leiomyoma. Methods: Eighty cases of FH deficient uterine leiomyoma were diagnosed from April 2018 to September 2022 in Department of Pathology, Peking University Third Hospital. Sanger sequencing of FH gene exons (exon 1-10) were performed on tumor tissues and matched non-tumor tissues/peripheral blood for all cases. FH immunohistochemistry were performed in 74 cases; S-(2-succino)-cysteine (2SC) were also detected by immunohistochemistry in five cases. Results: Patients' age ranged from 18 to 54 (36.0±7.5) years, with more than 60% exhibiting clinical symptoms of multiple and large leiomyomas (the median diameter was 70 mm). More than four histologic features, including staghorn vasculature, alveolar-pattern edema, bizarre nuclei, oval nuclei arranged in chains, prominent eosinophilic nucleoli with perinucleolar haloes and eosinophilic intracytoplasmic globules were observed in 98.5% (67/68) patients. The immunohistochemical sensitivity of FH and 2SC were 97.3% and 100%, respectively. Based on the Sanger sequencing results, the cases were divided into germline variant group (31 cases), somatic variant group (29 cases) and no variant group (20 cases). Sixty-nine percent (20/29) of the patients with FH germline variation had clear family history. Conclusions: Clinical features, histological morphology, FH and 2SC immunohistochemistry and Sanger sequencing have their own significance and limitations in differential diagnosis of FH deficient uterine leiomyoma. In clinical practice, the above information should be fully integrated and studied for accurate pathologic diagnosis and selection of patients with FH germline variation.
Female ; Humans ; Adolescent ; Young Adult ; Adult ; Middle Aged ; Fumarate Hydratase/genetics* ; Uterine Neoplasms/pathology* ; Leiomyoma/pathology* ; Germ-Line Mutation ; Diagnosis, Differential ; Leiomyomatosis/pathology* ; Carcinoma, Renal Cell/diagnosis*

In recent years, the incidence of renal cancer has been increasing continuously. Surgical resection is the "gold standard" for the treatment of small renal cancer. However, local ablation therapy of renal cancer is undoubtedly the best choice for patients with short life expectancy, other complications, and impaired renal function who are not suitable for surgery. In recent years, with the development of ablation techniques and long-term follow-up, local ablation has shown good therapeutic effects. As many domestic hospitals are performing or planning to perform renal tumor cryoablation to improve the clinical cure rate and surgical safety of renal tumor cryoablation, it is necessary to standardize the surgical indications, contraindications, perioperative management, efficacy evaluation, and other common problems. Currently, there is no expert consensus regarding perioperative renal tumor cryoablation in China. To standardize the perioperative management of renal tumor cryoablation and related technical operations in clinical practice, and improve the effectiveness and safety of cryoablation, the expert committee of Tumor Interventional and Minimally Invasive Diagnosis and Treatment Continuing Education Base of the Chinese Anti-Cancer Association convened experts in related fields to discuss and formulate this consensus, which is hereby published, for clinical reference and application.
Humans ; Carcinoma, Renal Cell/surgery* ; Consensus ; Cryosurgery/methods* ; Kidney Neoplasms/pathology* ; Treatment Outcome ; China

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