d-Galactose induces the senescence and phenotype switch of corpus cavernosum smooth muscle cells.

Studies regarding age-related erectile dysfunction (ED) based on naturally aging models are limited by their high costs, especially for the acquisition of primary cells from the corpus cavernosum. Herein, d-galactose ( d-gal) was employed to accelerate cell senescence, and the underlying mechanism was explored. As predominant functional cells involved in the erectile response, corpus cavernosum smooth muscle cells (CCSMCs) were isolated from 2-month-old rats. Following this, d-gal was introduced to induce cell senescence, which was verified via ß-galactosidase staining. The effects of d-gal on CCSMCs were evaluated by terminal deoxynucleoitidyl transferase dUTP nick-end labeling (TUNEL), immunofluorescence staining, flow cytometry, western blot, and quantitative real-time polymerase chain reaction (qRT-PCR). Furthermore, RNA interference (RNAi) was carried out for rescue experiments. Subsequently, the influence of senescence on the corpus cavernosum was determined via scanning electron microscopy, qRT-PCR, immunohistochemistry, TUNEL, and Masson stainings. The results revealed that the accelerated senescence of CCSMCs was promoted by d-gal. Simultaneously, smooth muscle alpha-actin (alpha-SMA) expression was inhibited, while that of osteopontin (OPN) and Krüppel-like factor 4 (KLF4), as well as fibrotic and apoptotic levels, were elevated. After knocking down KLF4 expression in d-gal-induced CCSMCs by RNAi, the expression level of cellular alpha-SMA increased. Contrastingly, the OPN expression, apoptotic and fibrotic levels declined. In addition, cellular senescence acquired partial remission. Accordingly, in the aged corpus cavernosum, the fibrotic and apoptotic rates were increased, followed by downregulation in the expression of alpha-SMA and the concurrent upregulation in the expression of OPN and KLF4. Overall, our results signaled that d-gal-induced accelerated senescence of CCSMCs could trigger fibrosis, apoptosis and phenotypic switch to the synthetic state, potentially attributed to the upregulation of KLF4 expression, which may be a multipotential therapeutic target of age-related ED.

Identification of tumor antigens and immune landscapes for bladder urothelial carcinoma mRNA vaccine.

Background: Bladder urothelial carcinoma (BLCA) is associated with high mortality and recurrence. Although mRNA-based vaccines are promising treatment strategies for combating multiple solid cancers, their efficacy against BLCA remains unclear. We aimed to identify potential effective antigens of BLCA for the development of mRNA-based vaccines and screen for immune clusters to select appropriate candidates for vaccination. Methods: Gene expression microarray data and clinical information were retrieved from The Cancer Genome Atlas and GSE32894, respectively. The mRNA splicing patterns were obtained from the SpliceSeq portal. The cBioPortal for Cancer Genomics was used to visualize genetic alteration profiles. Furthermore, nonsense-mediated mRNA decay (NMD) analysis, correlation analysis, consensus clustering analysis, immune cell infiltration analysis, and weighted co-expression network analysis were conducted. Results: Six upregulated and mutated tumor antigens related to NMD, and infiltration of APCs were identified in patients with BLCA, including HP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2. The patients were subdivided into two immune clusters (IC1 and IC2) with distinct clinical, cellular and molecular features. Patients in IC1 represented immunologically 'hot' phenotypes, whereas those in IC2 represented immunologically 'cold' phenotypes. Moreover, the survival rate was better in IC2 than in IC1, and the immune landscape of BLCA indicated significant inter-patient heterogeneity. Finally, CALD1, TGFB3, and ANXA6 were identified as key genes of BLCA through WGCNA analysis, and their mRNA expression levels were measured using qRT-PCR. Conclusion: HP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2 were identified as potential antigens for developing mRNA-based vaccines against BLCA, and patients in IC2 might benefit more from vaccination.

Identification of PLAUR-related ceRNA and immune prognostic signature for kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC) represents one of the most fatal cancers, usually showing malignant progression and a high tumor recurrence rate. The urokinase-type plasminogen activator receptor (PLAUR) plays a critical role in the initiation and progression of several cancers, including KIRC. However, the function and mechanism of PLAUR in patients with KIRC are still unclear and require further investigation. In the present study, we first explored the expression profile and prognostic values of PLAUR in pan-cancer based on The Cancer Genome Atlas and Genotype-Tissue Expression databases. PLAUR was upregulated in multiple cancers and was significantly associated with poor overall survival and disease-free survival only in patients with KIRC. Subsequently, the PVT1/SNHG15-hsa-miR-532-3p axis was identified as the most potential upstream regulatory network of PLAUR in KIRC. In addition, PLAUR expression was closely associated with tumor-infiltrating immune cells, tumor immunity biomarkers, and immunomodulator expression. Furthermore, we constructed a multiple-gene risk prediction signature according to the PLAUR-related immunomodulators (PRIs). A prognostic nomogram was then developed to predict the 1-, 3-, and 5-year survival probabilities of individuals. In conclusion, our study identified the PVT1/SNHG15-hsa-miR-532-3p-PLAUR axis and a prognostic signature of PRIs, which could be a reference for future clinical research.

The Prognostic Significance of RIMKLB and Related Immune Infiltrates in Colorectal Cancers.

RimK-like family member B (RIMKLB) is an enzyme that post-translationally modulates ribosomal protein S6, which can affect the development of immune cells. Some studies have suggested its role in tumor progression. However, the relationships among RIMKLB expression, survival outcomes, and tumor-infiltrating immune cells (TIICs) in colorectal cancer (CRC) are still unknown. Therefore, we analyzed RIMKLB expression levels in CRC and normal tissues and investigated the correlations between RIMKLB and TIICs as well as the impact of RIMKLB expression on clinical prognosis in CRC using multiple databases, including the Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), PrognoScan, and UALCAN databases. Enrichment analysis was conducted with the cluster Profiler package in R software to explore the RIMKLB-related biological processes involved in CRC. The RIMKLB expression was significantly decreased in CRC compared to normal tissues, and correlated with histology, stage, lymphatic metastasis, and tumor status (p < 0.05). Patients with CRC with high expression of RIMKLB showed poorer overall survival (OS) (HR = 2.5,p = 0.00,042), and inferior disease-free survival (DFS) (HR = 1.9,p = 0.19) than those with low expression of RIMKLB. TIMER analysis indicated that RIMKLB transcription was closely related with several TIICs, including CD4+ and CD8+ T cells, B cells, tumor-associated macrophages (TAMs), monocytes, neutrophils, natural killer cells, dendritic cells, and subsets of T cells. Moreover, the expression of RIMKLB showed significant positive correlations with infiltrating levels of PD1 (r = 0.223, p = 1.31e-06; r = 0.249, p = 1.25e-03), PDL1 (r = 0.223, p = 6.03e-07; r = 0.41, p = 5.45e-08), and CTLA4 (r = 0.325, p = 9.68e-13; r = 0.41, p = 5.45e-08) in colon and rectum cancer, respectively. Enrichment analysis showed that the RIMKLB expression was positively related to extracellular matrix and immune inflammation-related pathways. In conclusion, RIMKLB expression is associated with survival outcomes and TIICs levels in patients with CRC, and therefore, might be a potential novel prognostic biomarker that reflects the immune infiltration status.

Prediction of overall survival based upon a new ferroptosis-related gene signature in patients with clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common and lethal renal cell carcinoma (RCC) histological subtype. Ferroptosis is a newly discovered programmed cell death and serves an essential role in tumor occurrence and development. The purpose of this study is to analyze ferroptosis-related gene (FRG) expression profiles and to construct a multi-gene signature for predicting the prognosis of ccRCC patients. METHODS: RNA-sequencing data and clinicopathological data of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed FRGs between ccRCC and normal tissues were identified using 'limma' package in R. GO and KEGG enrichment analyses were conducted to elucidate the biological functions and pathways of differentially expressed FRGs. Consensus clustering was used to investigate the relationship between the expression of FRGs and clinical phenotypes. Univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to screen genes related to prognosis and construct the optimal signature. Then, a nomogram was established to predict individual survival probability by combining clinical features and prognostic signature. RESULTS: A total of 19 differentially expressed FRGs were identified. Consensus clustering identified two clusters of ccRCC patients with distinguished prognostic. Functional analysis revealed that metabolism-related pathways were enriched, especially lipid metabolism. A 7-gene ferroptosis-related prognostic signature was constructed to stratify the TCGA training cohort into high- and low-risk groups where the prognosis was significantly worse in the high-risk group. The signature was identified as an independent prognostic indicator for ccRCC. These findings were validated in the testing cohort, the entire cohort, and the International Cancer Genome Consortium (ICGC) cohort. We further demonstrated that the signature-based risk score was highly associated with the ccRCC progression. Further stratified survival analysis showed that the high-risk group had a significantly lower overall survival (OS) rate than those in the low-risk group. Moreover, we constructed a nomogram that had a strong ability to forecast the OS of the ccRCC patients. CONCLUSIONS: We constructed a ferroptosis-related prognostic signature, which might provide a reliable prognosis assessment tool for the clinician to guide clinical decision-making and outcomes research.

Construction of a Lactate-Related Prognostic Signature for Predicting Prognosis, Tumor Microenvironment, and Immune Response in Kidney Renal Clear Cell Carcinoma.

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent primary malignancies with high heterogeneity in the urological system. Growing evidence implies that lactate is a significant carbon source for cell metabolism and plays a vital role in tumor development, maintenance, and therapeutic response. However, the global influence of lactate-related genes (LRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response has not been comprehensively elucidated in patients with KIRC. In the present study, we collected RNA sequencing and clinical data of KIRC from The Cancer Genome Atlas (TCGA), E-MTAB-1980, and GSE22541 cohorts. Unsupervised clustering of 17 differentially expressed LRG profiles divided the samples into three clusters with distinct immune characteristics. Three genes (FBP1, HADH, and TYMP) were then identified to construct a lactate-related prognostic signature (LRPS) using the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. The novel signature exhibited excellent robustness and predictive ability for the overall survival of patients. In addition, the constructed nomogram based on the LRPS-based risk scores and clinical factors (age, gender, tumor grade, and stage) showed a robust predictive performance. Furthermore, patients classified by risk scores had distinguishable immune status, tumor mutation burden, response to immunotherapy, and sensitivity to drugs. In conclusion, we developed an LRPS for KIRC that was closely related to the immune landscape and therapeutic response. This LRPS may guide clinicians to make more precise and personalized treatment decisions for KIRC patients.

Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study.

Liver metastasis in colorectal cancer (CRC) is common and has an unfavorable prognosis. This study aimed to establish a functional nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer liver metastasis (CRCLM). A total of 9,736 patients with CRCLM from 2010 to 2016 were randomly assigned to training, internal validation, and external validation cohorts. Univariate and multivariate Cox analyses were performed to identify independent clinicopathologic predictive factors, and a nomogram was constructed to predict CSS and OS. Multivariate analysis demonstrated age, tumor location, differentiation, gender, TNM stage, chemotherapy, number of sampled lymph nodes, number of positive lymph nodes, tumor size, and metastatic surgery as independent predictors for CRCLM. A nomogram incorporating the 10 predictors was constructed. The nomogram showed favorable sensitivity at predicting 1-, 3-, and 5-year OS, with area under the receiver operating characteristic curve (AUROC) values of 0.816, 0.782, and 0.787 in the training cohort; 0.827, 0.769, and 0.774 in the internal validation cohort; and 0.819, 0.745, and 0.767 in the external validation cohort, respectively. For CSS, the values were 0.825, 0.771, and 0.772 in the training cohort; 0.828, 0.753, and 0.758 in the internal validation cohort; and 0.828, 0.737, and 0.772 in the external validation cohort, respectively. Calibration curves and ROC curves revealed that using our models to predict the OS and CSS would add more benefit than other single methods. In summary, the novel nomogram based on significant clinicopathological characteristics can be conveniently used to facilitate the postoperative individualized prediction of OS and CSS in CRCLM patients.

Identification of ARHGEF38, NETO2, GOLM1, and SAPCD2 Associated With Prostate Cancer Progression by Bioinformatic Analysis and Experimental Validation.

Prostate cancer (PCa) represents one of the most prevalent types of cancers and is a large health burden for men. The pathogenic mechanisms of PCa still need further investigation. The aim of this study was to construct an effective signature to predict the prognosis of PCa patients and identify the biofunctions of signature-related genes. First, we screened differentially expressed genes (DEGs) between PCa and normal control tissues in The Cancer Genome Atlas (TCGA) and GSE46602 datasets, and we performed weighted gene co-expression network analysis (WGCNA) to determine gene modules correlated with tumors. In total, 124 differentially co-expressed genes were retained. Additionally, five genes (ARHGEF38, NETO2, PRSS21, GOLM1, and SAPCD2) were identified to develop the prognostic signature based on TCGA dataset. The five-gene risk score was verified as an independent prognostic indicator through multivariate Cox regression analyses. The expression of the five genes involved in the signature was detected in the Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), and Oncomine databases. In addition, we utilized DiseaseMeth 2.0 and MEXPRESS for further analysis and found that abnormal methylation patterns may be a potential mechanism for these five DEGs in PCa. Finally, we observed that these genes, except PRSS21, were highly expressed in tumor samples and PCa cells. Functional experiments revealed that silencing ARHGEF38, NETO2, GOLM1, and SAPCD2 suppressed the proliferation, migration, and invasiveness of PCa cells. In summary, this prognostic signature had significant clinical significance for treatment planning and prognostic evaluation of patients with PCa. Thus, ARHGEF38, NETO2, GOLM1, and SAPCD2 may serve as oncogenes in PCa.

Comprehensive Analysis of the Immune Infiltrates of Pyroptosis in Kidney Renal Clear Cell Carcinoma.

Kidney renal clear cell carcinoma (KIRC) has long been identified as a highly immune-infiltrated tumor. However, the underlying role of pyroptosis in the tumor microenvironment (TME) of KIRC remains poorly described. Herein, we systematically analyzed the prognostic value, role in the TME, response to ICIs, and drug sensitivity of pyroptosis-related genes (PRGs) in KIRC patients based on The Cancer Genome Atlas (TCGA) database. Cluster 2, by consensus clustering for 24 PRGs, presented a poor prognosis, likely because malignancy-related hallmarks were remarkably enriched. Additionally, we constructed a prognostic prediction model that discriminated well between high- and low-risk patients and was further confirmed in external E-MTAB-1980 cohort and HSP cohort. By further analyzing the TME based on the risk model, higher immune cell infiltration and lower tumor purity were found in the high-risk group, which presented a poor prognosis. Patients with high risk scores also exhibited higher ICI expression, indicating that these patients may be more prone to profit from ICIs. The sensitivity to anticancer drugs that correlated with model-related genes was also identified. Collectively, the pyroptosis-related prognosis risk model may improve prognostic information and provide directions for current research investigations on immunotherapeutic strategies for KIRC patients.

Identification and validation of a two-gene metabolic signature for survival prediction in patients with kidney renal clear cell carcinoma.

Metabolic reprogramming contributes to the high mortality of advanced stage kidney renal clear cell carcinoma (KIRC), the most common renal cancer subtype. This study aimed to identify a metabolism-related gene (MRG) signature to improve survival prediction in KIRC patients. We downloaded RNA sequencing data and corresponding clinical information for KIRC and control samples from The Cancer Genome Atlas database and identified, based on an MRG dataset in the Molecular Signatures Database, 123 MRGs with differential expression in KIRC. Following Cox regression analysis and least absolute shrinkage and selection operator selection, RRM2 and ALDH6A1 were identified as prognosis-related genes and used to construct a prognostic signature with independent prognostic significance. After risk score-based patient separation, stratified survival analysis indicated that high-risk patients showed poorer overall survival than low-risk patients. We then constructed a clinical nomogram that showed a concordance index of 0.774 and good performance based upon calibration curves. Gene set enrichment analysis revealed several metabolic pathways significantly enriched in the target genes. The two-gene metabolic signature identified herein may represent a highly valuable tool for KIRC prognosis prediction, and might also help identify new metabolism-related biomarkers and therapeutic targets for KIRC.

Prognostic risk signature based on the expression of three m6A RNA methylation regulatory genes in kidney renal papillary cell carcinoma.

In this study, we investigated the prognostic significance of the expression of N6-methyladenosine (m6A) RNA methylation regulatory genes in kidney renal papillary cell carcinoma (KIRP). RNA-sequencing data analysis showed that 14 of 20 major m6A RNA methylation regulatory genes were differentially expressed in the KIRP tissues from The Cancer Genome Atlas (TCGA) database. We constructed a prognostic risk signature with three m6A RNA methylation regulatory genes, IGF2BP3, KIAA1429 and HNRNPC, based on the results from univariate and LASSO Cox regression analyses. Multivariate Cox regression analysis confirmed that the risk score based on the three-gene prognostic risk signature was an independent predictive factor in KIRP. The overall survival of high-risk KIRP patients was significantly shorter than the low-risk KIRP patients. Expression of the three prognostic risk-related genes correlated with the AJCC and TNM stages of KIRP patients from TCGA and GEPIA datasets. ROC curve analysis showed that the three-gene prognostic risk signature precisely predicted the 1-year, 3-year and 5-year survival of KIRP patients. These findings demonstrate that expression of three prognostic risk-related m6A RNA methylation regulatory genes accurately predicts survival outcomes in KIRP patients.

Development and validation of a prognostic model for kidney renal clear cell carcinoma based on RNA binding protein expression.

Dysregulated expression of RNA-binding proteins (RBPs) is strongly associated with the development and progression of multiple tumors. However, little is known about the role of RBPs in kidney renal clear cell carcinoma (KIRC). In this study, we examined RBP expression profiles using The Cancer Genome Atlas database and identified 133 RBPs that were differentially expressed in KIRC and non-tumor tissues. We then systematically analyzed the potential biological functions of these RBPs and established PPIs. Based on Lasso regression and Cox survival analyses, we constructed a risk model that could independently and accurately predict prognosis based on seven RBPs (NOL12, PABPC1L, RNASE2, RPL22L1, RBM47, OASL, and YBX3). Survival times were shorter in patients with high risk scores for cohorts stratified by different characteristics. Gene set enrichment analysis was also performed to further understand functional differences between high- and low-risk groups. Finally, we developed a clinical nomogram with a concordance index of 0.792 for estimating 3- and 5-year survival probabilities. Our results demonstrate that this risk model could potentially improve individualized diagnostic and therapeutic strategies.

Long Non-Coding RNA Profile Study Identifies an Immune-Related lncRNA Prognostic Signature for Kidney Renal Clear Cell Carcinoma.

Kidney renal clear cell carcinoma (KIRC) is the predominant pathological subtype of renal cell carcinoma (RCC) in adults. Long non-coding RNAs (lncRNAs) are an important class of gene expression regulators and serve fundamental roles in immune regulation. The intent of this study is to develop a novel immune-related lncRNA signature to accurately predict the prognosis for KIRC patients. Here, we performed genome-wide comparative analysis of lncRNA expression profiles in 537 KIRC patients from The Cancer Genome Atlas (TCGA) database. Cox regression model-identified immune-related lncRNAs were extracted for constructing a novel five immune-related lncRNA signature (AC008105.3, LINC02084, AC243960.1, AC093278.2, and AC108449.2) with the ability to predict the prognosis of KIRC patients. Univariate and multivariate Cox regression analyses demonstrated that the signature could act as an independent prognostic predictor for overall survival (OS). With the further investigation on different clinicopathological parameters, we found that the signature could divide KIRC samples into high-risk groups with shorter OS and low-risk groups with longer OS in different subgroups. Principal component analysis suggested that the five immune-related lncRNA signature drew a clear distinction between high- and low-risk groups based on the immune-related lncRNAs. The different immune status between the two groups was observed in gene set enrichment analysis and the ESTIMATE algorithm. Except for AC093278.2, the expressions of the other four lncRNAs expression were significantly upregulated in tumor tissues. In summary, the identified immune-lncRNA signature had important clinical implications in prognosis prediction and could be exploited as underlying immune therapeutic targets for KIRC patients.

An autophagy-related long non-coding RNA prognostic signature accurately predicts survival outcomes in bladder urothelial carcinoma patients.

In this study, we analyzed the prediction accuracy of an autophagy-related long non-coding RNA (lncRNA) prognostic signature using bladder urothelial carcinoma (BLCA) patient data from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses showed significant correlations between five autophagy-related lncRNAs, LINC02178, AC108449.2, Z83843.1, FAM13A-AS1 and USP30-AS1, and overall survival (OS) among BCLA patients. The risk scores based on the autophagy-related lncRNA prognostic signature accurately distinguished high- and low-risk BCLA patients that were stratified according to age; gender; grade; and AJCC, T, and N stages. The autophagy-related lncRNA signature was an independent prognostic predictor with an AUC value of 0.710. The clinical nomogram with the autophagy-related lncRNA prognostic signature showed a high concordance index of 0.73 and accurately predicted 1-, 3-, and 5-year survival times among BCLA patients in the high- and low-risk groups. The lncRNA-mRNA co-expression network contained 77 lncRNA-mRNA links among 5 lncRNAs and 49 related mRNAs. Gene set enrichment analysis showed that cancer- and autophagy-related pathways were significantly enriched in the high-risk group, and immunoregulatory pathways were enriched in the low-risk group. These findings demonstrate that an autophagy-related lncRNA signature accurately predicts the prognosis of BCLA patients.

Network pharmacology-based identification of the key mechanism of Qinghuo Rougan Formula acting on uveitis.

BACKGROUND: Qinghuo Rougan Formula (QHRGF) is a traditional Chinese medicine (TCM) that has been widely apllied to treat uveitis for several decades. However, the inhibitory mechanism of QHRGF in uveitis has remained to be an enigma. METHODS: The Chinese herbal medicine pharmacology data and analysis platform wereused to search and screen for the effective components of the QHRGF compound injection and to analyse possible therapeutic targets based on network topology. In addition, various known disease target databases were enraolled, the therapeutic target proteins in uveitis were screened, and a protein-protein interaction (PPI) network was constructed. Enrichment analysis was performed on key nodes. Finally, the inhibitory effect of QHRGF on uveitis was verified by experiments. RESULTS: We identified 259 major candidate targets of QHRGF and successfully constructed a 'QHRGF-compound-target-uveitis' network. Above-mentioned targets revealed by Gene enrichment analysis have played an significant role in the cell cycle, autoimmune disease, apoptosis and related signal pathways. We demonstrated that QHRGF attenuates local inflammation in experimental autoimmune uveoretinitis (EAU) rats by regulating natural killer T (NKT) cells and inhibiting MAPK signal pathways. CONCLUSION: QHRGF may regulate the local immune response and inflammatory factors mainly through the MAPK signal pathway. For autoimmune uveitis, QHRGF may be a promising, long-lasting treatment strategy.

Inflammatory myofibroblastic tumor of kidney together with ipsilateral perinephric and periureteric fibrosis: A case report and literature review.

RATIONALE: Both inflammatory myofibroblastic tumor (IMT) and retroperitoneal fibrosis are rare lesions, but kidney involvement is more rare. It is the first study about IMT of the kidney in a patient with perinephric and periureteric fibrosis and we hold that fibroblast proliferation may be an intermediate status in oncogenesis of IMT. But further investigation is necessary in order to better clarify the relationship between fibroblast proliferation and IMT. PATIENT CONCERNS: A 54-year-old female presented no positive signs except dull back pain after overwork. DIAGNOSES: On the basis of the urinary ultrasonography and computed tomography (CT) scan, we strongly suspected a renal cell carcinoma. INTERVENTIONS: Considering the little remaining function of the right kidney and the possibility of malignancy, we performed a laparoscopic right radical nephrectomy. OUTCOMES: According to the analysis of the postoperative paraffin section and immunohistochemistry assay, a final diagnosis of IMT and retroperitoneal fibrosis nodules was made. LESSONS: Both IMTs are rare lesions and its etiology and pathogeny are unclear. It is the first study about IMT of the kidney in a patient with perinephric and periureteric fibrosis. This report suggested that fibroblast proliferation may be an intermediate status in oncogenesis of IMT, but further investigation is necessary in order to better clarify the relationship between fibroblast proliferation and IMT. The preoperative diagnosis of renal IMT remains difficult. Preoperative fine-needle aspiration or percutaneous biopsy and intraoperative frozen section were applied to confirm the diagnosis to avoid unnecessary nephrectomy, especially in patients with renal insufficiency, bilateral masses, or a solitary kidney.