Renal cell carcinoma (RCC) is notorious for its propensity to metastasize even after a prolonged period of remission following nephrectomy. The metastatic spread can occur months or even years after initial treatment, which necessitates a heightened level of clinical awareness and vigilance in patients with a history of renal malignancy, particularly who present with new or unexplained nasal symptoms. Although RCC most commonly metastasize to the lungs, bones and liver, its involvement in the nasal cavity is exceedingly rare, posing significant diagnostic challenges due to the non-specific nature of symptoms. We describe a case of metastatic renal cell clear cell carcinoma presenting with recurrent epistaxis and unilateral nasal obstruction. Immunohistochemistry studies play a crucial role in confirming the diagnosis and ruling out potential differential diagnoses, along with a comprehensive clinical history of the patient.

Nuclear receptor co-activator 4 (NCOA4) acts as a selective cargo receptor that binds to ferritin, a cytoplasmic iron storage complex. By mediating ferritinophagy, NCOA4 regulates iron metabolism and releases free iron in the body, thus playing a crucial role in a variety of biological processes, including growth, development, and metabolism. Recent studies have shown that NCOA4-mediated ferritinophagy is closely associated with the occurrence and development of iron metabolism-related diseases, such as liver fibrosis, renal cell carcinoma, and neurodegenerative diseases. In addition, a number of clinical drugs have been identified to modulate NCOA4-mediated ferritinophagy, significantly affecting disease progression and treatment efficacy. This paper aims to review the current research progress on the role of NCOA4-mediated ferritinophagy in related diseases, in order to provide new ideas for targeted clinical therapy.
Humans ; Nuclear Receptor Coactivators/physiology* ; Ferritins/metabolism* ; Animals ; Neurodegenerative Diseases/metabolism* ; Iron/metabolism* ; Autophagy/physiology* ; Liver Cirrhosis/metabolism* ; Carcinoma, Renal Cell/metabolism* ; Kidney Neoplasms/physiopathology*

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 analyze the association of CHMP2B expression level of with clinicopathological characteristics and prognosis of clear cell renal cell carcinoma (CRCC) and the possible role of CHMP2B in tumorigenesis and progression of CRCC. METHODS: RNAseq data of CRCC were downloaded from the TCGA database for analysis of CHMP2B expression levels in tumor and adjacent tissues and their correlation with clinicopathological characteristics of the patients. Survival outcomes of the patients with high and low CHMP2B expressions were analyzed using the Kaplan-Meier model, and the COX risk regression model was used for identifying the prognostic factors of the patients. The correlation between CHMP2B expression and immune infiltration, its co-expressed genes, and the effect of CHMP2B gene mutations on immunotherapy responses, and its immunohistochemical expression in CRCC and normal tissues were analyzed. Clinical samples of CRCC were collected to examine CHMP2B expressions using RT-PCR, and cell experiment was carried out to test the effect of CHMP2B overexpression on biological behaviors of CRCC cells. RESULTS: CHMP2B was significantly under-expressed in renal cancer tissues, and its overexpression obviously inhibited the proliferation of CRCC cells in vitro. CHMP2B expression level was significantly correlated with age, gender, lymph node metastasis, and tumor stage, and the patients with low CHMP2B expression had poor survival outcomes. Enrichment and co-expression gene analyses suggested that CHMP2B was mainly involved in viral outgrowth, necrotic apoptosis, endocytosis, and immune-regulatory processes in kidney cancer. CONCLUSIONS CHMP2B is lowly expressed in renal cancer tissues to affect tumor progression and tumor immune processes, and may serve as a prognostic biomarker and therapeutic target for CRCC.
Humans ; Carcinoma, Renal Cell/metabolism* ; Kidney Neoplasms/metabolism* ; Cell Proliferation ; Prognosis ; Cell Line, Tumor ; Male ; Female ; Gene Expression Regulation, Neoplastic

OBJECTIVES: To identify potential molecular targets of quercetin in the treatment of clear cell renal carcinoma (ccRCC). METHODS: The therapeutic targets of quercetin were screened from multiple databases by network pharmacology analysis, and the targets significantly correlated with ccRCC were screened from 4907 plasma proteins using a Mendelian randomization method. The drug-disease network model was constructed to screen the potential key targets. The functions of these targets were evaluated via bioinformatics analysis, and the screened targets were verified in cultured ccRCC cells. RESULTS: Network pharmacology analysis combined with Mendelian randomization identified TP53 (OR=3.325, 95% CI: 1.805-6.124, P=0.0001), ARF4 (OR=0.173, 95% CI: 0.065-0.456, P=0.0003), and DPP4 (OR=0.463, 95% CI: 0.302-0.711, P=0.0004) as the core targets in quercetin treatment of ccRCC. Bioinformatics analysis showed that TP53 was highly expressed in ccRCC, and patients with high TP53 expressions had worse survival outcomes. Molecular docking studies showed that the binding energy between quercetin and TP53 was -5.83 kcal/mol. In cultured 786-O cells, CCK-8 assay and wound healing assay showed that treatment with quercetin significantly inhibited cell proliferation and migration. Quercetin treatment also strongly suppressed the expression of TP53 at both the mRNA and protein levels in 786-O cells as shown by RT-qPCR and Western blotting. CONCLUSIONS TP53 may be the key target of quercetin in the treatment of ccRCC, which sheds light on potential molecular mechanism that mediate the therapeutic effect of quercetin.
Humans ; Quercetin/pharmacology* ; Carcinoma, Renal Cell/genetics* ; Cell Proliferation/drug effects* ; Kidney Neoplasms/genetics* ; Cell Movement/drug effects* ; Tumor Suppressor Protein p53/metabolism* ; Cell Line, Tumor ; Computational Biology

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

Tumor aerobic glycolysis is one of the main features of tumor metabolic reprogramming. This abnormal glycolytic metabolism provides bioenergy and biomaterials for tumor growth and proliferation. It is worth noting that aerobic glycolysis will not only provide biological materials and energy for tumor cells, but also help tumor cells to escape immune surveillance through regulation of immune microenvironment, thereby resisting tumor immunotherapy and promoting tumor progression. Based on the pathogenesis of renal cell carcinoma, this paper describes the characteristics of aerobic glycolysis, the effect of glycolytic metabolism on the immune microenvironment of renal cell carcinoma, the effect of glycolysis inhibitors on the immune microenvironment of renal cell carcinoma, and the prospect of glycolysis inhibitors combined with immune checkpoint inhibitors in the treatment of renal cell carcinoma.
Humans ; Carcinoma, Renal Cell/therapy* ; Immunotherapy ; Glycolysis ; Metabolic Reprogramming ; Kidney Neoplasms/therapy* ; Tumor Microenvironment

Introduction: Clear Cell Renal Cell Carcinoma, a renal cortical tumor characterized by malignant epithelial cells with clear cytoplasm and compact alveolar or acinar growth pattern interspersed with intricate arborizing vasculature.1 This is rare in people less than 45 years old. Though it has varied clinical manifestations, its classical triad: abdominal mass, hematuria, and groin pain only present in four to 17% of cases.2 We therefore present a case of renal cell carcinoma occurring in an unusual age group who presented with vague gastrointestinal symptoms and polycythemia which accounts only less than 5% of cases.3 Case Presentation: This is a case of a 28-year-old Filipino male who presented with epigastric pain with abdominal fullness and anorexia who later complained of frequent vomiting after solid and liquid intake. CBC revealed polycythemia. Gastroscopy with biopsy showed esophagitis Los Angeles classification Grade A and duodenal mass obstructing 95% of the lumen. Computed tomographic scan of whole abdomen revealed large renal mass, right of 15.9x9.35x11.34cm extending superiorly at the antropyloric region causing gastric luminal narrowing down to first and second segments of duodenum with a 4.2cm enlarged lymph node in aortocaval area. Magnetic resonance imaging revealed a huge complex right renal mass of 12x12x10cm in size extending beyond Gerota’s fascia with 8x5.2x6.2cm lymph node compressing the vena cava. Right radical nephrectomy was done for both supportive management to relieve the obstruction and for histologic diagnosis which revealed clear cell renal cell carcinoma. JAK2 gene mutation test was done to determine the cause of polycythemia and phlebotomy was performed to address the problem. Conclusion This case presents with vague gastrointestinal symptoms which is atypical of renal cell carcinoma, hence highlights the importance of properly investigating its cause. Furthermore, a multidisciplinary approach involving different subspecialties plays a significant role in the diagnosis and management in this patient.
Carcinoma, Renal Cell ; Polycythemia

OBJECTIVES: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC), and developing personalized treatment strategies is crucial for improving patient prognosis. This study aims to develop and validate a preoperative computer tomography (CT) radiomics-based predictive model to estimate Ki-67 expression in ccRCC patients, thereby assisting in clinical treatment decisions and prognosis prediction. METHODS: A retrospective analysis was conducted on 214 ccRCC patients who underwent surgical treatment at Gansu Provincial Hospital between January 2018 and November 2023. Patients were classified into high Ki-67 expression (n=123) and low Ki-67 expression (n=91) groups based on postoperative immunohistochemical staining results. The dataset was randomly divided in a 7꞉3 ratio into a training set (n=149) and a validation set (n=65). Preoperative contrast-enhanced urinary CT images and clinical data were collected. After preprocessing, 5 mm arterial-phase CT images were manually segmented layer by layer to delineate the region of interest (ROI) using ITK-SNAP 3.8 software. Radiomic features were then extracted using the FeAture Explorer (FAE) package. Dimensionality reduction and feature selection were performed using the least absolute shrinkage and selection operator (LASSO) algorithm, yielding the optimal feature set. Three classification models were constructed using logistic regression (LR), multilayer perceptron (MLP), and support vector machine (SVM). The receiver operating characteristic (ROC) curve, area under the curve (AUC), decision curve analysis (DCA), and calibration curves were used for model evaluation. RESULTS: A total of 107 radiomic features were extracted from 5 mm arterial-phase CT images, and twenty-one features significantly associated with Ki-67 expression were selected using the LASSO algorithm. Predictive models were developed using LR, MLP, and SVM classifiers. In the training and validation sets, the AUC values for each model were 0.904 (95% CI 0.852 to 0.956) and 0.818 (95% CI 0.710 to 0.926) for the LR model, 0.859 (95% CI 0.794 to 0.923) and 0.823 (95% CI 0.716 to 0.929) for the MLP model, and 0.917 (95% CI 0.865 to 0.969) and 0.857 (95% CI 0.760 to 0.953) for the SVM model. DCA demonstrated that all models had good clinical net benefit, while calibration curves indicated high accuracy of the predictions, supporting the robustness and reliability of the models. CONCLUSIONS A CT radiomics-based model for predicting Ki-67 expression in ccRCC was successfully developed. This model provides valuable guidance for treatment planning and prognostic assessment in ccRCC patients.
Humans ; Carcinoma, Renal Cell/surgery* ; Kidney Neoplasms/surgery* ; Tomography, X-Ray Computed/methods* ; Ki-67 Antigen/metabolism* ; Retrospective Studies ; Female ; Male ; Middle Aged ; Aged ; Prognosis ; Adult ; Preoperative Period ; Radiomics