Heart Metastases of Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) is a common genitourinary cancer. Of the several histologic types of RCC, clear cell renal cell carcinoma (ccRCC) is the most frequent. Due to the development of imaging methods such as computed tomography (CT) or magnetic resonance imaging (MRI), the incidence of ccRCC diagnosis has increased rapidly. However, up to one third of patients at prime diagnosis of ccRCC are at metastatic stadium of the disease. Metastases of ccRCC are found mostly in the lungs, bones and liver. Metastasis of ccRCC to the heart is an uncommon clinical situation. We present a rare case of metastatic stadium of ccRCC with metastases to heart tissue visualized in transthoracic echocardiography.

The Tumor Immune Microenvironment in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a type of kidney cancer that arises from the cells lining the tubes of the kidney. The tumor immune microenvironment (TIME) of ccRCC is a complex interplay of various immune cells, cytokines, and signaling pathways. One of the critical features of the ccRCC TIME is the presence of infiltrating immune cells, including T cells, B cells, natural killer cells, dendritic cells, and myeloid-derived suppressor cells. Among these cells, CD8+ T cells are particularly important in controlling tumor growth by recognizing and killing cancer cells. However, the TIME of ccRCC is also characterized by an immunosuppressive environment that hinders the function of immune cells. Several mechanisms contribute to the immunosuppressive nature of the ccRCC TIME. For instance, ccRCC cells produce cytokines such as interleukin-10 (IL-10) and transforming growth factor-beta (TGF-β), which suppress immune cell activation and promote the differentiation of regulatory T cells (Tregs). Tregs, in turn, dampen the activity of effector T cells and promote tumor growth. In addition, ccRCC cells can express programmed death-ligand 1 (PD-L1), which interacts with the programmed cell death protein 1 (PD-1) receptor on T cells to inhibit their function. In addition, other immune checkpoint proteins, such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and lymphocyte activation gene 3 (LAG-3), also contribute to the immunosuppressive milieu of the ccRCC TIME. Finally, the hypoxic and nutrient-poor microenvironment of ccRCC can stimulate the production of immunosuppressive metabolites, such as adenosine and kynurenine, which further impair the function of immune cells. Understanding the complex interplay between tumor cells and the immune system in the ccRCC TIME is crucial for developing effective immunotherapies to treat this disease.

Significance of PBRM1 mutation in disease progress and drug selection in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the predominant type of kidney cancer, and the mutation of PBRM1 (Polybromo 1) gene is a commonly observed genetic alteration. The high frequency of PBRM1 mutation in ccRCC suggests its potential use as a biomarker for personalized therapy. In this study, we aimed to investigate the significance of PBRM1 mutation in disease progression and drug sensitivity in ccRCC. Additionally, we analyzed the critical pathways and genes associated with PBRM1 mutation to understand its potential mechanisms. Our findings show that PBRM1 mutation was observed in 38% of ccRCC patients and correlated with advanced disease stages. We also identified selective inhibitors for ccRCC with PBRM1 mutation using online databases such as PD173074 and AGI-6780. Furthermore, we identified 1253 genes as differentially expressed genes (DEGs) that were significantly enriched in categories such as metabolic progression, cell proliferation, and development. Although PBRM1 mutation did not show an association with ccRCC prognosis, a lower PBRM1 expression level correlated with worsened prognosis. Our study provides insights into the association of PBRM1 mutation with disease progression in ccRCC and suggests potential gene and signaling pathways for personalized treatment in ccRCC with PBRM1 mutation.

Integrated glycoproteomic characterization of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC), a common form of RCC, is responsible for the high mortality rate of kidney cancer. Dysregulations of glycoproteins have been shown to associate with ccRCC. However, the molecular mechanism has not been well characterized. Here, a comprehensive glycoproteomic analysis is conducted using 103 tumors and 80 paired normal adjacent tissues. Altered glycosylation enzymes and corresponding protein glycosylation are observed, while two of the major ccRCC mutations, BAP1 and PBRM1, show distinct glycosylation profiles. Additionally, inter-tumor heterogeneity and cross-correlation between glycosylation and phosphorylation are observed. The relation of glycoproteomic features to genomic, transcriptomic, proteomic, and phosphoproteomic changes shows the role of glycosylation in ccRCC development with potential for therapeutic interventions. This study reports a large-scale tandem mass tag (TMT)-based quantitative glycoproteomic analysis of ccRCC that can serve as a valuable resource for the community.

Clear cell renal cell carcinoma with focal psammomatous calcifications: a rare occurrence mimicking translocation carcinoma

AIMS

Renal cell carcinoma (RCC) with clear cells and psammoma-like calcifications would often raise suspicion for MITF family translocation RCC. However, we have rarely encountered tumours consistent with clear cell RCC that contain focal psammomatous calcifications.

METHODS AND RESULTS

We identified clear cell RCCs with psammomatous calcifications from multiple institutions and performed immunohistochemistry and fluorescence and RNA in-situ hybridisation (FISH and RNA ISH). Twenty-one tumours were identified: 12 men, nine women, aged 45-83 years. Tumour size was 2.3-14.0 cm (median = 6.75 cm). Nucleolar grade was 3 (n = 14), 2 (n = 4) or 4 (n = 3). In addition to clear cell pattern, morphology included eosinophilic (n = 12), syncytial giant cell (n = 4), rhabdoid (n = 2), branched glandular (n = 1), early spindle cell (n = 1) and poorly differentiated components (n = 1). Labelling for CA9 was usually 80-100% of the tumour cells (n = 17 of 21), but was sometimes decreased in areas of eosinophilic cells (n = 4). All (19 of 19) were positive for CD10. Most (19 of 20) were positive for AMACR (variable staining = 20-100%). Staining was negative for keratin 7, although four showed rare positive cells (four of 20). Results were negative for cathepsin K (none of 19), melan A (none of 17), HMB45 (none of 17), TFE3 (none of 5), TRIM63 RNA ISH (none of 13), and TFE3 (none of 19) and TFEB rearrangements (none of 12). Seven of 19 (37%) showed chromosome 3p deletion. One (one of 19) showed trisomy 7 and 17 without papillary features.

CONCLUSIONS

Psammomatous calcifications in RCC with a clear cell pattern suggests a diagnosis of MITF family translocation RCC; however, psammomatous calcifications can rarely be found in true clear cell RCC.

Diagnostic Accuracy of MRI for Solid Renal Masses: A Systematic Review and Meta-analysis

BACKGROUND

Biparametric (bp)-MRI and multiparametric (mp)-MRI may improve the diagnostic accuracy of renal mass histology.

PURPOSE

To evaluate the available evidence on the diagnostic accuracy of bp-MRI and mp-MRI for solid renal masses in differentiating malignant from benign, aggressive from indolent, and clear cell renal cell carcinoma (ccRCC) from other histology.

STUDY TYPE

Systematic review.

POPULATION

MEDLINE, EMBASE, and CENTRAL up to January 11, 2022 were searched.

FIELD STRENGTH/SEQUENCE

1.5 or 3 Tesla.

ASSESSMENT

Eligible studies evaluated the accuracy of MRI (with at least two sequences: T2, T1, dynamic contrast and diffusion-weighted imaging) for diagnosis of solid renal masses in adult patients, using histology as reference standard. Risk of bias and applicability were assessed using QUADAS-2.

STATISTICAL TESTS

Meta-analysis using a bivariate logitnormal random effects model.

RESULTS

We included 10 studies (1239 masses from approximately 1200 patients). The risk of bias was high in three studies, unclear in five studies and low in two studies. The diagnostic accuracy of malignant (vs. benign) masses was assessed in five studies (64% [179/281] malignant). The summary estimate of sensitivity was 95% (95% confidence interval [CI]: 77%-99%), and specificity was 63% (95% CI: 46%-77%). No study assessed aggressive (vs. indolent) masses. The diagnostic accuracy of ccRCC (vs. other subtypes) was evaluated in six studies (47% [455/971] ccRCC): the summary estimate of sensitivity was 85% (95% CI: 77%-90%) and specificity was 77% (95% CI: 73%-81%).

DATA CONCLUSION

Our study reveals deficits in the available evidence on MRI for diagnosis of renal mass histology. The number of studies was limited, at unclear/high risk of bias, with heterogeneous definitions of solid masses, imaging techniques, diagnostic criteria, and outcome measures.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

RBM4 inhibits the growth of clear cell renal cell carcinoma by enhancing the stability of p53 mRNA

RBM4 has been reported as a tumor suppressor gene in cancers, including lung cancer, colon cancer and gastric cancer. However, the role of RBM4 in clear cell renal cell carcinoma (ccRCC) remains unclear. Therefore, the present study investigated the expression and biological function of RBM4 in ccRCC. Analysis of the differential expression of RBM4 and its relationship with clinicopathological features using ccRCC samples data from TCGA database deminstrated that RBM4 expression in tumor samples of ccRCC was lower than that in normal samples, and RBM4 expression was closely related to the survival time of patients. RBM4 overexpression (RBM4-oe) cell lines were constructed to investigate the effect of RBM4 on biological function using CCK-8, EdU, flow cytometry and wound-healing assays. In addition, the regulatory effect of RBM4 on signaling pathways was investigated by GSEA and WB assays. RBM4-oe significantly reduced the proliferation of ccRCC cells by controlling the p53 signaling pathway, inhibited cell cycle progression and promoted apoptosis. In addition, RBM4-oe suppressed the migration and invasion of cells by EMT. Mechanistically, RBM4-oe facilitated the activity of the p53 signaling pathway by enhancing the stability of p53 mRNA. Finally, RBM4-oe markedly inhibited the growth of tumors formed with 786-O cells in vivo. In summary, there findings suggeated that RBM4 inhibits the progression of ccRCC by promoting p53 signaling pathway activity by enhancing the stability of p53 mRNA, suggesting that RBM4 may be a potential target for the treatment of patients.

Identification and validation of DLX4 as a prognostic and diagnostic biomarker for clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a lethal cancer, and biomarkers for exact diagnosis and predicting prognosis are urgently needed. The present study aimed to determine the roles of distal-less homeobox (DLX) family genes in ccRCC. The clinicopathological and mRNA expression data of patients with ccRCC were derived from The Cancer Genome Atlas database. Kaplan-Meier curves, univariate and multivariate Cox hazard analyses, in addition to receiver operator characteristic curves were used to evaluate the prognostic and diagnostic values. A single-sample gene set enrichment analysis was used to quantify the infiltration levels of immune cells. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry were conducted to examine the expression levels of DLX4 in tumor and adjacent tissue; the results demonstrated that DLX4 was highly expressed in ccRCC tissues compared with normal renal tissues. Furthermore, DLX4 expression was associated with tumor stage and grade. High proportions of males, advanced pathological stage, higher tumor grade and T, N and M stage were also observed in the high DLX4 expression group. Patients with the high DLX4 expression levels tended to have lower overall survival and disease-free survival rates compared with those with low DLX4 expression. DLX4 expression also showed favorable diagnostic efficiency in ccRCC patients. Based on functional enrichment analysis, cell cycle related pathways, epithelial-mesenchymal transition, glycolysis and inflammatory response were associated with the expression levels of DLX4. Furthermore, DLX4 expression was revealed to be associated with tumor immunosuppressive microenvironment. Overall, the expression level of DLX4 may be considered a novel prognostic indicator in ccRCC and a specific diagnostic biomarker for patients with ccRCC.

Comprehensive analyses of A 12-metabolism-associated gene signature and its connection with tumor metastases in clear cell renal cell carcinoma

BACKGROUND

The outcomes of patients with clear cell renal cell carcinoma (ccRCC) were dreadful due to lethal local recurrence and distant metastases. Accumulating evidence suggested that ccRCC was considered a metabolic disease and metabolism-associated genes (MAGs) exerted essential functions in tumor metastases. Thus, this study intends to seek whether the dysregulated metabolism promotes ccRCC metastases and explores underlying mechanisms.

METHOD

Weighted gene co-expression network analysis (WGCNA) was employed based on 2131 MAGs to select genes mostly associated with ccRCC metastases for subsequent univariate Cox regression. On this basis, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression were employed to create a prognostic signature based on the cancer genome atlas kidney renal clear cell carcinoma (TCGA-KIRC) cohort. The prognostic signature was confirmed using E-MTAB-1980 and GSE22541 cohorts. Kaplan-Meier, receiver operating characteristic (ROC) curve, and univariate and multivariate Cox regression were applied to detect the predictability and independence of the signature in ccRCC patients. Functional enrichment analyses, immune cell infiltration examinations, and somatic variant investigations were employed to detect the biological roles of the signature.

RESULT

A 12-gene-metabolism-associated prognostic signature, termed the MAPS by our team, was constructed. According to the MAPS, patients were divided into low- and high-risk subgroups and high-risk patients displayed inferior outcomes. The MAPS was validated as an independent and reliable biomarker in ccRCC patients for forecasting the prognosis and progression of ccRCC patients. Functionally, the MAPS was closely associated with metabolism dysregulation, tumor metastases, and immune responses in which the high-risk tumors were in an immunosuppressive status. Besides, high-risk patients benefited more from immunotherapy and held a higher tumor mutation burden (TMB) than low-risk patients.

CONCLUSION

The 12-gene MAPS with prominent biological roles could independently and reliably forecast the outcomes of ccRCC patients, and provide clues to uncover the latent mechanism in which dysregulated metabolism controlled ccRCC metastases.

FCGR2A as one novel potential target for poor survival prognosis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma. Immunoglobulin FcγRIIa receptor (FCGR2A) has been implicated in various cancers, however, its role on ccRCC is not well studied. A total of 151 patients with ccRCC were recruited for the study. Cox proportional hazards regression analysis was performed to calculate the hazard radios of FCGR2A expression and tumor characteristics. Pathological changes associated with ccRCC in tumor tissue sections were analyzed by hematoxylin-eosin staining. Immunohistochemical and immunofluorescence staining were used to detect the protein expression of FCGR2A in the tissue sections. Correlation between the expression of FCGR2A and the overall survival (OS) of ccRCC patients was analyzed by biological process neural network and support vector machine. The expression of FCGR2A was significantly correlated with the TNM of tumor, family history of ccRCC and Fuhrman stage of ccRCC. Patients with high FCGR2A expression in the tumor tissue, had poorer OS than the patients with low and moderate FCGR2A expression. The Receiver operating characteristic curve showed that FCGR2A can be used as a sensitive and specific biomarker for the diagnosis of ccRCC. Western blotting revealed that the FCGR2A was expressed at higher levels in the ccRCC tissues. Biological process neural network and support vector machine fitting showed that the R2 between FCGR2A and survival time of ccRCC patients was 0.8429 and 0.7669, respectively. FCGR2A is highly expressed in ccRCC, higher expression of FCGR2A is associated with poorer OS of ccRCC.

N6-methyladenosine-modified DBT alleviates lipid accumulation and inhibits tumor progression in clear cell renal cell carcinoma through the ANXA2/YAP axis-regulated Hippo pathway

BACKGROUND

The mechanism of metabolism reprogramming is an unsolved problem in clear cell renal cell carcinoma (ccRCC). Recently, it was discovered that the Hippo pathway altered tumor metabolism and promoted tumor progression. Thus, this study aimed at identifying key regulators of metabolism reprogramming and the Hippo pathway in ccRCC and pinpointing potential therapeutic targets for ccRCC patients.

METHODS

Hippo-related gene sets and metabolic gene sets were used to screen potential regulators of the Hippo pathway in ccRCC. Public databases and samples from patients were applied to investigate the association of dihydrolipoamide branched chain transacylase E2 (DBT) with ccRCC and Hippo signaling. The role of DBT was confirmed by gain or loss of function assays in vitro and in vivo. Mechanistic results were yielded by luciferase reporter assay, immunoprecipitation, mass spectroscopy, and mutational studies.

RESULTS

DBT was confirmed as a Hippo-related marker with significant prognostic predictive value, and its downregulation was caused by methyltransferase-like-3 (METTL3)-mediated N6-methyladenosine (m⁶ A) modification in ccRCC. Functional studies specified DBT as a tumor suppressor for inhibiting tumor progression and correcting the lipid metabolism disorder in ccRCC. Mechanistic findings revealed that annexin A2 (ANXA2) interacted with the lipoyl-binding domain of DBT to activate Hippo signaling which led to decreased nuclear localization of yes1-associated transcriptional regulator (YAP) and transcriptional repression of lipogenic genes.

CONCLUSIONS

This study demonstrated a tumor-suppressive role for the DBT/ANXA2/YAP axis-regulated Hippo signaling and suggested DBT as a potential target for pharmaceutical intervention in ccRCC.

RUNX2 interacts with SCD1 and activates Wnt/β-catenin signaling pathway to promote the progression of clear cell renal cell carcinoma

BACKGROUND

Previous studies have demonstrated that Runt-associated transcription factor 2 (RUNX2) serves as the main transcription factor for osteoblast differentiation and chondrocyte maturation. RUNX2 is related to a variety of tumors, particularly tumor invasion and metastasis, while the expression and molecular mechanisms of RUNX2 in clear cell renal cell carcinoma (ccRCC) keep to be determined. Stearyl CoA desaturase 1 (SCD1), an endoplasmic reticulum fatty acid desaturase, transfers saturated fatty acids to monounsaturated fatty acids, is expressed highly in numerous malignancies.

METHODS

The Cancer Genome Atlas (TCGA) datebase and Western blot was used to analyzed the mRNA and protein levels of the target gene in ccRCC tissues and adjacent tissues. The proliferation ability of ccRCC cells was tested by colony forming and EdU assay. The migration ability of cells was detected by transwell assay. Immunoprecipitation was utilized to detect protein-protein interaction. Cycloheximide chase assay was used to measure the half-life of SCD1 protein.

RESULTS

In this study, the expressions of RUNX2 and SCD1 are increased in ccRCC tissues as well as ccRCC cell lines. Both RUNX2 and SCD1 could promote proliferation and migration in ccRCC cells. Furthermore, RUNX2 could physically interact with SCD1. In addition, the functional degradation and the inactivation of Wnt/β-catenin signaling pathway triggered by the downregulation of RUNX2 could be partly offset by the overexpression of SCD1.

CONCLUSION

The findings indicate that the RUNX2/SCD1 axis may act as a potential therapeutic target via the Wnt/β-catenin signaling pathway of ccRCC.

RP11-367G18.1 V2 enhances clear cell renal cell carcinoma progression via induction of epithelial-mesenchymal transition

PURPOSE

Metastasis is the end stage of renal cell carcinoma (RCC), and clear cell renal cell carcinoma (ccRCC) is the most common malignant subtype. The hypoxic microenvironment is a common feature in ccRCC and plays an essential role in the regulation of epithelial-mesenchymal transition (EMT). Accumulating evidence manifests that long non-coding RNAs (lncRNAs) participate in RCC tumorigenesis and regulate hypoxia-induced EMT. Here, we identified a lncRNA RP11-367G18.1 induced by hypoxia, that was overexpressed in ccRCC tissues.

METHODS

A total of 216 specimens, including 149 ccRCC tumor samples and 67 related normal kidney parenchyma tissue samples, were collected. To investigate the biological fucntions of RP11.367G18.1 in ccRCC, migration, invasion, soft agar colony formation, xenograft tumorigenicity assays, and tail vein and orthotopic metastatic mouse models were performed. The relationship between RP11-367G18.1 and downstream signaling was analyzed utilizing reporter assay, RNA pull-down, chromatin immunopreciptation, and chromatin isolation by RNA purification assays.

RESULTS

Hypoxic conditions and overexpression of HIF-1α increased the level of RP11-367G18.1. RP11-367G18.1 induced EMT and enhanced cell migration and invasion through variant 2. Inhibition of RP11-367G18.1 variant 2 reversed hypoxia-induced EMT phenotypes. An in vivo study revealed that RP11-367G18.1 variant 2 was required for hypoxia-induced tumor growth and metastasis in ccRCC. Mechanistically, RP11-367G18.1 variant 2 interacted with p300 histone acetyltransferase to regulate lysine 16 acetylation on histone 4 (H4K16Ac), thus contributing to hypoxia-regulated gene expression. Clinically, RP11-367G18.1 variant 2 was upregulated in ccRCC tissues, particularly metastatic ccRCC tissues, and it is linked to poor overall survival.

CONCLUSION

These findings demonstrate the prognostic value and EMT-promoting role of RP11-367G18.1 and indicate that this lncRNA may provide a therapeutic target for ccRCC.

Tumor-to-Tumor Metastases Involving Clear Cell Renal Cell Carcinomas: A Diagnostic Challenge for Pathologists Needing Clinical Correlation

Tumor-to-tumor metastasis is a rare event which it is specifically up to pathologists to bring to light correctly. The histological identification of such tumor-to-tumor cases is simple when the respective histologies are different but can be problematic if the case includes two carcinomas with similar cytoarchitecture viewed one inside the other under the microscope. We report four cases of this condition in which clear cell renal cell carcinoma is involved, either as a receptor or as a donor, and remark on the difficulties in recognizing some of them. Appropriate clinical-pathological correlation, including a review of the patient's antecedents and radiological exams, would be a great help in routinely identifying tumor-to-tumor metastases.

FBXO30 functions as a tumor suppressor and an E3 ubiquitin ligase for hZIP1‑mediated HIF‑1α degradation in renal cell carcinoma

Studies on clear cell renal cell carcinoma (ccRCC) are gaining momentum due to its high malignancy and potential to metastasize. F‑box protein 30 (FBXO30) is a member of the F‑box protein family; however, its role and mechanism in cancer remains to be fully elucidated. Western blotting, reverse transcription‑quantitative PCR and immunohistochemsitry were performed to detect the expression levels of FBXO30 in ccRCC tissues and adjacent normal tissues. Tumor biological function assays and animal experiments were conducted to clarify the inhibitory effect of FBXO30 on the progression and metastasis of ccRCC. Protein half‑life assay, MG132 inhibition assay, immunofluorescence assay and co‑immunoprecipitation assay were performed to explore the ubiquitination mechanism of FBXO30 and HIF‑1α. Zinc supplementation assay was used to verify the regulatory relationship between human ZRT, IRT‑like protein 1 (hZIP1), FBXO30 and HIF‑1α. The present study revealed that the expression levels of FBXO30 were lower in ccRCC tissues compared with those in normal adjacent tissues. In addition, FBXO30 inhibited the tumorigenesis and metastatic capacity of ccRCC cells in vivo and in vitro. FBXO30 mediated the ubiquitination and degradation of hypoxia‑inducible factor‑1α (HIF‑1α) in ccRCC cells under normoxia, thereby inhibiting the oncogenic effect of HIF‑1α. Notably, hZIP1 served as an upstream regulator of FBXO30, regulating the expression of FBXO30 and HIF‑1α by recruiting Zn²⁺. In conclusion, the present data suggested that FBXO30 is a novel E3 ubiquitination ligase that can function as a tumor suppressor in ccRCC, and the hZIP1/Zn²⁺/FBXO30/HIF‑1α axis may provide potential biomarkers or therapeutic targets for ccRCC.

A novel lipid metabolism gene signature for clear cell renal cell carcinoma using integrated bioinformatics analysis

Background: Clear cell renal cell carcinoma (ccRCC), which is the most prevalent type of renal cell carcinoma, has a high mortality rate. Lipid metabolism reprogramming is a hallmark of ccRCC progression, but its specific mechanism remains unclear. Here, the relationship between dysregulated lipid metabolism genes (LMGs) and ccRCC progression was investigated. Methods: The ccRCC transcriptome data and patients' clinical traits were obtained from several databases. A list of LMGs was selected, differentially expressed gene screening performed to detect differential LMGs, survival analysis performed, a prognostic model established, and immune landscape evaluated using the CIBERSORT algorithm. Gene Set Variation Analysis and Gene set enrichment analysis were conducted to explore the mechanism by which LMGs affect ccRCC progression. Single-cell RNA-sequencing data were obtained from relevant datasets. Immunohistochemistry and RT-PCR were used to validate the expression of prognostic LMGs. Results: Seventy-one differential LMGs were identified between ccRCC and control samples, and a novel risk score model established comprising 11 LMGs (ABCB4, DPEP1, IL4I1, ENO2, PLD4, CEL, HSD11B2, ACADSB, ELOVL2, LPA, and PIK3R6); this risk model could predict ccRCC survival. The high-risk group had worse prognoses and higher immune pathway activation and cancer development. Conclusion: Our results showed that this prognostic model can affect ccRCC progression.

Research Progress of Tumor Microenvironment Targeted Therapy for Clear Cell Renal Cell Carcinoma

Renal clear cell carcinoma (ccRCC) and the tumor microenvironment (TME) influence each other, leading to the tumor microenvironment that can guide the corresponding treatment. With the deepening of research, some treatment options have achieved good results, such as tyrosine kinase inhibitors, immune checkpoint inhibitors, and so on. As the link between TME and malignancy is constantly discovered, more targeted studies on different components of TME are increasing, and this targeted therapy is a new method for treating ccRCC, and also a current research hotspot. This review summarizes the characteristics of the ccRCC tumor microenvironment, the outcomes of different treatments, and some potential targets.

ANO4 Expression Is a Potential Prognostic Biomarker in Non-Metastasized Clear Cell Renal Cell Carcinoma

Background: Over the past decade, transcriptome profiling has elucidated many pivotal pathways involved in oncogenesis. However, a detailed comprehensive map of tumorigenesis remains an enigma to solve. Propelled research has been devoted to investigating the molecular drivers of clear cell renal cell carcinoma (ccRCC). To add another piece to the puzzle, we evaluated the role of anoctamin 4 (ANO4) expression as a potential prognostic biomarker in non-metastasized ccRCC. Methods: A total of 422 ccRCC patients with the corresponding ANO4 expression and clinicopathological data were obtained from The Cancer Genome Atlas Program (TCGA). Differential expression across several clinicopathological variables was performed. The Kaplan-Meier method was used to assess the impact of ANO4 expression on the overall survival (OS), progression-free interval (PFI), disease-free interval (DFI), and disease-specific survival (DSS). Univariate and multivariate Cox logistic regression analyses were conducted to identify independent factors modulating the aforementioned outcomes. Gene set enrichment analysis (GSEA) was used to discern a set of molecular mechanisms involved in the prognostic signature. Tumor immune microenvironment was estimated using xCell. Results: ANO4 expression was upregulated in tumor samples compared to normal kidney tissue. Albeit the latter finding, low ANO4 expression is associated with advanced clinicopathological variables such as tumor grade, stage, and pT. In addition, low ANO4 expression is linked to shorter OS, PFI, and DSS. Multivariate Cox logistic regression analysis identified ANO4 expression as an independent prognostic variable in OS (HR: 1.686, 95% CI: 1.120-2.540, p = 0.012), PFI (HR: 1.727, 95% CI: 1.103-2.704, p = 0.017), and DSS (HR: 2.688, 95% CI: 1.465-4.934, p = 0.001). GSEA identified the following pathways to be enriched within the low ANO4 expression group: epithelial-mesenchymal transition, G2-M checkpoint, E2F targets, estrogen response, apical junction, glycolysis, hypoxia, coagulation, KRAS, complement, p53, myogenesis, and TNF-α signaling via NF-κB pathways. ANO4 expression correlates significantly with monocyte (ρ = -0.1429, p = 0.0033) and mast cell (ρ = 0.1598, p = 0.001) infiltration. Conclusions: In the presented work, low ANO4 expression is portrayed as a potential poor prognostic factor in non-metastasized ccRCC. Further experimental studies should be directed to shed new light on the exact molecular mechanisms involved.

EFHD1, a novel mitochondrial regulator of tumor metastasis in clear cell renal cell carcinoma

The biological function of many mitochondrial proteins in mechanistic detail has not been well investigated in clear cell renal cell carcinoma (ccRCC). A seven-mitochondrial-gene signature was generated by Lasso regression analysis to improve the prediction of prognosis of patients with ccRCC, using The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium cohort. Among those seven genes, EFHD1 is less studied and its role in the progression of ccRCC remains unknown. The decreased expression of EFHD1 was validated in clinical samples and was correlated with unfavorable outcome. Overexpression of EFHD1 in ccRCC cells resulted in the reduction of mitochondrial Ca²⁺ , and the inhibition of cell migration and invasion in vitro and tumor metastasis in vivo. Mechanistically, EFHD1 physically bound to the core mitochondrial calcium transporter (mitochondrial calcium uniporter, MCU) through its N-terminal domain. The interaction between EFHD1 and MCU suppressed the uptake of Ca²⁺ into mitochondria, and deactivated the Hippo/YAP signaling pathway. Further data revealed that the ectopic expression of EFHD1 upregulated STARD13 to enhance the phosphorylation of YAP protein at Ser-127. The knockdown of STARD13 or the overexpression of MCU partly abrogated the EFHD1-mediated induction of phosphorylation of YAP at Ser-127 and suppression of cell migration. Taken together, the newly identified EFHD1-MCU-STARD13 axis participates in the modulation of the Hippo/YAP pathway and serves as a novel regulator in the progression of ccRCC.

Elevated THBS3 predicts poor overall survival for clear cell renal cell carcinoma and identifies LncRNA/RBP/THBS3 mRNA networks

This study was used to assess THBS3's overall survival (OS) prognostic values in clear cell renal cell carcinoma (ccRCC) as well as to determine the LncRNA/RNA binding protein (RBP)/THBS3 interactions. Clinical data and RNA sequencing data were gathered from the TCGA dataset. Significant pathways associated with THBS3 were identified by gene set enrichment analysis (GSEA). Cox regression analyses, both univariate and multivariate, were applied to assess factors with independent prognostic abilities. We also discussed THBS3's relationship to immunity. We discovered that THBS3 expression was increased in ccRCC samples, as well as shorter OS in the TCGA dataset (P<0.05). External verification results in GSE6344, ICGC, ArrayExpress, UALCAN datasets, and qRT-PCR remained consistent (all P<0.05). Cox regression analyses, both univariate and multivariate, identified THBS3 as a factor with independent prognostic ability (both P<0.001). THBS3 expression as well as several clinicopathological variables were included in the nomogram OS prognosis prediction method as well. GSEA identified four THBS3-related signal pathways and THBS3 was revealed to be significantly associated with MSI, TMB, neoantigen, and immunity (all P<0.05). We also identified several LncRNA/RBP/THBS3 mRNA networks as potentially THBS3-related mechanisms. For THBS3-related drug sensitivities, THBS3 was negatively associated with Actinomycin D, Cobimetinib, Eribulin mesilate, Geldanamycin analog, and Vinblastine, while it was positively related to Erlotinib drug sensitivity. In addition to being an independent prognostic factor for ccRCC, THBS3 had a close connection to immunity, with identifying LncRNA/RBPs/THBS3 mRNA networks. Verifications of our findings in vivo and in vitro should be done in the future.

Development of a TGF-β signaling-related genes signature to predict clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma

Background

Transforming growth factor (TGF)-β signaling is strongly related to the development and progression of tumor. We aimed to construct a prognostic gene signature based on TGF-β signaling-related genes for predicting clinical prognosis and immunotherapy responses of patients with clear cell renal cell carcinoma (ccRCC).

Methods

The gene expression profiles and corresponding clinical information of ccRCC were collected from the TCGA and the ArrayExpress (E-MTAB-1980) databases. LASSO, univariate and multivariate Cox regression analyses were conducted to construct a prognostic signature in the TCGA cohort. The E-MTAB-1980 cohort were used for validation. Kaplan-Meier (K-M) survival and time-dependent receiver operating characteristic (ROC) were conducted to assess effectiveness and reliability of the signature. The differences in gene enrichments, immune cell infiltration, and expression of immune checkpoints in ccRCC patients showing different risks were investigated.

Results

We constructed a seven gene (PML, CDKN2B, COL1A2, CHRDL1, HPGD, CGN and TGFBR3) signature, which divided the ccRCC patients into high risk group and low risk group. The K-M analysis indicated that patients in the high risk group had a significantly shorter overall survival (OS) time than that in the low risk group in the TCGA (p < 0.001) and E-MTAB-1980 (p = 0.012). The AUC of the signature reached 0.77 at 1 year, 0.7 at 3 years, and 0.71 at 5 years in the TCGA, respectively, and reached 0.69 at 1 year, 0.72 at 3 years, and 0.75 at 5 years in the E-MTAB-1980, respectively. Further analyses confirmed the risk score as an independent prognostic factor for ccRCC (p < 0.001). The results of ssGSEA that immune cell infiltration degree and the scores of immune-related functions were significantly increased in the high risk group. The CIBERSORT analysis indicated that the abundance of immune cell were significantly different between two risk groups. Furthermore, The risk score was positively related to the expression of PD-1, CTLA4 and LAG3.These results indicated that patients in the high risk group benefit more from immunotherapy.

Conclusion

We constructed a novel TGF-β signaling-related genes signature that could serve as an promising independent factor for predicting clinical prognosis and immunotherapy responses in ccRCC patients.

PIMREG is a prognostic biomarker involved in immune microenvironment of clear cell renal cell carcinoma and associated with the transition from G1 phase to S phase

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the world and affects human health seriously. PIMREG is a mitotic regulator which is essential to the metaphase-to-anaphase transition in cell cycle. Although PIMREG plays a crucial role in the malignant progression of tumors, there are few reports on its role in ccRCC.

Methods

The transcriptional expression profile and clinical data of PIMREG were downloaded from TCGA database and verified by qRT-PCR. Kaplan-Meier plotter was used to analyze the effect of PIMREG on overall survival (OS), disease specific survival (DSS) and progression-free interval (PFI) of patients with ccRCC. Univariable and multivariable Cox regression analysis were used to determine the independent prognostic factors of ccRCC. The effects of PIMREG on cell migration and invasion were detected by wound healing assay and transwell invasion assay, and CCK-8 assay, colony formation assay and cell cycle assay were used to detect the effect of PIMREG on cell proliferation. In addition, the changes in cell cycle related proteins were detected by western blot.

Results

PIMREG was highly expressed in human ccRCC and was positively correlated with pathologic stage, TNM stage and histologic grade. In addition, patients with high expression of PIMREG had a poor prognosis. Univariable and multivariable Cox regression analysis identified that PIMREG was an independent prognostic factor of ccRCC. Additionally, PIMREG was also closely related to immune cell infiltration. Experiments in vitro identified that the knockdown of PIMREG could significantly inhibit the proliferation, migration and invasion abilities of ccRCC. The expression of cyclin D1, CDK4 and CDK6 was also significantly reduced after PIMREG knockdown.

Conclusions

PIMREG plays a vital role in the development of ccRCC and may become a potential therapeutic target in the future.

Low Expression of MATR3 Is Associated with Poor Survival in Clear Cell Renal Cell Carcinoma

Matrin 3 (MATR3) is one of the most abundant inner nuclear matrix proteins involved in multiple nuclear processes. However, to date, the biological role and prognostic relevance of MATR3 in human cancers still need to be explored. Therefore, the present study aimed to examine the expression levels and prognostic significance of MATR3 in clear cell renal cell carcinoma (ccRCC) patients. We assessed MATR3 immunohistochemical staining and RNA-seq data from publicly available data sets, and the results were analyzed with reference to clinicopathological characteristics and the overall survival of patients. Furthermore, the protein-protein interaction (PPI) network for MATR3 and its neighbors was constructed, functionally annotated, and screened for survival-related genes. MATR3 protein and mRNA levels were lower in tumor tissues compared to control tissues. Lower MATR3 protein (HR 2.36, 95%CI 1.41-3.97; p = 0.001) and mRNA (HR 2.01, 95%CI 1.46-2.75; p < 0.0001) expression levels were found to be a significant independent adverse prognostic factor for the patient's overall survival (OS). Moreover, of the candidate genes, the MRPL23 gene was identified as being the most predictive of OS, and combined MRPL23/MATR3 expression status predicted patient survival better than looking at each marker individually (HR 3.15, 95%CI 2.05-4.83; p < 0.0001). In conclusion, the results from the present investigation warrant further research into the biological and prognostic value of MATR3 and MRPL23 in ccRCC patients.

The LncRNA signature associated with cuproptosis as a novel biomarker of prognosis in immunotherapy and drug screening for clear cell renal cell carcinoma

Cuproptosis is a new form of cell death, the second form of metal ion-induced cell death defined after ferroptosis. Recently, cuproptosis has been suggested to be associated with tumorigenesis. However, the relationship between cuproptosis and patient prognosis in clear cell renal cell carcinoma (ccRCC) in the context of immunotherapy remains unknown. The aim of this study was to investigate the correlation between cuproptosis-related long non-coding RNA (lncRNA) and ccRCC in terms of immunity as well as prognosis. Clinical information on lncRNAs associated with differences in cuproptosis genes in ccRCC and normal tissues was collected from The Cancer Genome Atlas (TCGA) dataset. Univariate Cox regression was used to screen lncRNAs. A total of 11 lncRNAs closely associated with cuproptosis were further screened and established using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression, and the samples were randomly divided into training and test groups. A risk prognostic model was constructed using the training group, and the model was validated using the test group. We investigated the predictive ability of the prognostic risk model in terms of clinical prognosis, tumor mutation, immune escape, immunotherapy, tumor microenvironment, immune infiltration levels, and tumor drug treatment of ccRCC. Using the median risk score, patients were divided into low and high-risk groups. Kaplan-Meier curves showed that the overall survival (OS) of patients in the high-risk group was significantly worse than low-risk group (p < 0.001). Receiver operating characteristic (ROC) curves further validated the reliability of our model. The model consistently and accurately predicted prognosis at 1, 3, and 5 years, with an AUC above 0.7. Tumor cell genes generally precede morphological abnormalities; therefore, the model we constructed can effectively compensate for the traditional method of evaluating the prognosis of patients with renal cancer, and our model was also clinically meaningful in predicting ccRCC staging. In addition, lower model risk scores determined by mutational load indicated a good chance of survival. The high-risk group had greater recruitment of immune cells, while the anti-immune checkpoint immunotherapy was less efficacious overall than that of the low-risk group. Tumor and immune-related pathways were enriched, and anti-tumor agents were selected to improve the survival of ccRCC. This prognostic risk model is based on the levels of cuproptosis-associated lncRNAs and provides a new perspective in the clinical assessment and precise treatment of ccRCC.

Clear Cell Renal Cell Carcinoma: From Biology to Treatment

The majority of kidney cancers are detected incidentally and typically diagnosed at a localized stage, however, the development of regional or distant disease occurs in one-third of patients. Over 90% of kidney tumors are renal cell carcinomas, of which, clear cell is the most predominate histologic subtype. Von Hippel Lindau (VHL) gene alterations result in the overexpression of growth factors that are central to the pathogenesis of clear cell carcinoma. The therapeutic strategies have revolved around this tumor suppressor gene and have led to the approval of tyrosine kinase inhibitors (TKI) targeting the vascular endothelial growth factor (VEGF) axis. The treatment paradigm shifted with the introduction of immune checkpoint inhibitors (ICI) and programed death-1 (PD-1) inhibition, leading to durable response rates and improved survival. Combinations of TKI and/or ICIs have become the standard of care for advanced clear cell renal cell carcinoma (ccRCC), changing the outlook for patients, with several new and promising therapeutic targets under development.

GBP2 promotes clear cell renal cell carcinoma progression through immune infiltration and regulation of PD‑L1 expression via STAT1 signaling

Guanylate‑binding protein 2 (GBP2) has been widely studied in cancer, however, its potential role in clear cell renal cell carcinoma (ccRCC) is not fully elucidated. The present study aimed to explore the effect of GBP2 on tumor progression and its possible underlying molecular mechanisms in ccRCC. The Cancer Genome Atlas, Gene Expression Omnibus, Cancer Cell Line Encyclopedia databases, and several bioinformatics analysis tools, such as Gene Expression Profiling Interactive Analysis 2, Kaplan‑Meier plotter, UALCAN, LinkedOmics, Metascape, GeneMANIA and Tumor Immune Estimation Resource, were used to characterize the functional relationship between GBP2 and ccRCC. Focusing on the association between GBP2 and programmed death ligand 1 (PD‑L1) in vitro, the regulatory mechanism was investigated by knockdown and overexpression of GBP2 in Caki‑1 and 786‑O cells using reverse transcription‑quantitative PCR, western blotting and co‑immunoprecipitation techniques. The results indicated that GBP2 was commonly upregulated in ccRCC, correlating with worse prognosis. In addition, GBP2 expression levels were positively associated with different patterns of immune cell infiltration, suggesting that the GBP2 gene regulates PD‑L1 expression via the signal transducer and activator of transcription 1 (STAT1) pathway. The present study suggested that GBP2 regulates tumor immune infiltration and promotes tumor immune escape through PD‑L1 expression, revealing a potential immunotherapeutic target for ccRCC.

Proteoglycan SPOCK1 as a Poor Prognostic Marker Promotes Malignant Progression of Clear Cell Renal Cell Carcinoma via Triggering the Snail/Slug-MMP-2 Axis-Mediated Epithelial-to-Mesenchymal Transition

Sparc/osteonectin, cwcv, and kazal-like domains proteoglycan 1 (SPOCK1) has been reported to play an oncogenic role in certain cancer types; however, the role of SPOCK1 in the progression of clear cell renal cell carcinoma (ccRCC) remains elusive. Here, higher SPOCK1 transcript and protein levels were observed in ccRCC tissues compared to normal tissues and correlated with advanced clinical stages, larger tumor sizes, and lymph node and distal metastases. Knockdown and overexpression of SPOCK1 in ccRCC cells led to decreased and increased cell clonogenic and migratory/invasive abilities in vitro as well as lower and higher tumor growth and invasion in vivo, respectively. Mechanistically, the gene set enrichment analysis (GSEA) database was used to identify the gene set of epithelial-to-mesenchymal transition (EMT) pathways enriched in ccRCC samples with high SPOCK1 expression. Further mechanistic investigations revealed that SPOCK1 triggered the Snail/Slug-matrix metalloproteinase (MMP)-2 axis to promote EMT and cell motility. Clinical ccRCC samples revealed SPOCK1 to be an independent prognostic factor for overall survival (OS), and positive correlations of SPOCK1 with MMP-2 and mesenchymal-related gene expression levels were found. We observed that patients with SPOCK1^high/MMP2^high tumors had the shortest OS times compared to others. In conclusion, our findings reveal that SPOCK1 can serve as a useful biomarker for predicting ccRCC progression and prognosis, and as a promising target for treating ccRCC.

LGALS1 was related to the prognosis of clear cell renal cell carcinoma identified by weighted correlation gene network analysis combined with differential gene expression analysis

Understanding the molecular mechanism of clear cell renal cell carcinoma (ccRCC) is essential for predicting the prognosis and developing new targeted therapies. Our study is to identify hub genes related to ccRCC and to further analyze its prognostic significance. The ccRCC gene expression profiles of GSE46699 from the Gene Expression Omnibus (GEO) database and datasets from the Cancer Genome Atlas Database The Cancer Genome Atlas were used for the Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. We screened out 397 overlapping genes from the four sets of results, and then performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genome (KEGG) pathways. In addition, the protein-protein interaction (PPI) network of 397 overlapping genes was mapped using the STRING database. We identified ten hub genes (KNG1, TIMP1, ALB, C3, GPC3, VCAN, P4HB, CHGB, LGALS1, EGF) using the CytoHubba plugin of Cytoscape based on the Maximal Clique Centrality (MCC) score. According to Kaplan-Meier survival analysis, higher expression of LGALS1 and TIMP1 was related to poorer overall survival (OS) in patients with ccRCC. Univariate and multivariate Cox proportional hazard analysis showed that the expression of LGALS1 was an independent risk factor for poor prognosis. Moreover, the higher the clinical grade and stage of ccRCC, the higher the expression of LGALS1. LGALS1 may play an important role in developing ccRCC and may be potential a biomarker for prognosis and treatment targets.

Metastatic Renal Cell Carcinoma to the Soft Tissue 27 Years after Radical Nephrectomy: A Case Report

Background and Objectives: Approximately 20-40% of patients affected with renal cell carcinoma (RCC) develop either distant metastatic or locally recurring disease following radical nephrectomy. Soft tissue, skin, and the central nervous system are less common metastatic sites. We present the case of a patient who has received a diagnosis of RCC; it was found that she had no metastases at the time of nephrectomy but had metastases in the soft tissue and subcutaneous tissue of the scalp 27 years later. As far as we can tell, this is the longest period elapsed between primary renal tumor and subcutaneous/soft tissue metastasis; moreover, this case is the first report of a combined soft tissue/subcutaneous metastasis from RCC. Case presentation: A 73-year-old woman underwent right radical nephrectomy 27 years earlier for clear cell renal cell carcinoma (CCRCC). She presented at our unit because she noticed swelling in the left temporal region; after radiological exams, a benign lesion was suspected. The patient underwent surgical eradication, but the massive bleeding did not allow the removal of the lesion. A biopsy of the mass was performed and the histological examination was consistent with RCC metastases. Conclusions: Metastases from renal cell carcinoma to the subcutaneous and soft tissues are rare. It is essential to take into account RCC metastases in the differential diagnostic of the new starting mass of the head and neck, and the necessity for close and continuous surveillance of patients diagnosed with renal cancer even after a long disease-free period should be emphasized.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Postoperative Metabolic Phenoreversion in Clear Cell Renal Cell Carcinoma

The ultimate goal of surgical treatment in cancer is to remove the tumor mass for restoring a healthy state. A 16-lipid panel that discriminated healthy controls from clear cell renal cell carcinoma (ccRCC) patients in a prior study was evaluated in the present work in paired-serum samples collected from patients (n = 41) before and after nephrectomy. Changes in the lipid and metabolite fingerprints from ccRCC patients were investigated and compared with fingerprints from healthy individuals obtained by means of ultra-performance liquid chromatography-high-resolution mass spectrometry. The lipid panel differentiated phenotypes associated with metabolic restoration after surgery, representing a serum signature of phenoreversion to a healthy metabolic state. In particular, PC 16:0/0:0, PC 18:2/18:2, and linoleic acid allowed discriminating serum samples from ccRCC patients with poor prognosis from those with an improved outcome during the follow-up period. Ratios of PC 16:0/0:0 and PC 18:2/18:2 with linoleic acid levels may contribute as prognostic tools to support decision-making during the patient follow-up care. The preliminary character of these results should be validated with larger cohorts, including subjects with different ethnicities, life style, and diets. MetaboLights study references: MTBLS1839, MTBLS3838, and MTBLS4629.

The Emerging Role of PET/CT with PSMA-Targeting Radiopharmaceuticals in Clear Cell Renal Cancer: An Updated Systematic Review

BACKGROUND

Recent articles proposed the employment of positron emission tomography/computed tomography (PET/CT) with prostate-specific membrane antigen (PSMA)-targeting radiopharmaceuticals in clear cell renal cell carcinoma (ccRCC).

METHODS

The authors performed a comprehensive literature search of studies on the performance of PET/CT with PSMA-targeting radiopharmaceuticals in ccRCC. Original articles concerning this imaging examination were included in newly diagnosed ccRCC patients and ccRCC patients with disease recurrence.

RESULTS

A total of sixteen papers concerning the diagnostic performance of PSMA-targeted PET/CT in ccRCC (331 patients) were included in this systematic review. The included articles demonstrated an excellent detection rate of PSMA-targeting PET/CT in ccRCC.

CONCLUSIONS

PSMA-targeted PET/CT seems promising in detecting ccRCC lesions as well as in discriminating the presence of aggressive phenotypes. Prospective multicentric studies are warranted to strengthen the role of PSMA-targeting PET/CT in ccRCC.

Druggable Biomarkers Altered in Clear Cell Renal Cell Carcinoma: Strategy for the Development of Mechanism-Based Combination Therapy

Targeted therapeutics made significant advances in the treatment of patients with advanced clear cell renal cell carcinoma (ccRCC). Resistance and serious adverse events associated with standard therapy of patients with advanced ccRCC highlight the need to identify alternative 'druggable' targets to those currently under clinical development. Although the Von Hippel-Lindau (VHL) and Polybromo1 (PBRM1) tumor-suppressor genes are the two most frequently mutated genes and represent the hallmark of the ccRCC phenotype, stable expression of hypoxia-inducible factor-1α/2α (HIFs), microRNAs-210 and -155 (miR_S), transforming growth factor-beta (TGF-ß), nuclear factor erythroid 2-related factor 2 (Nrf2), and thymidine phosphorylase (TP) are targets overexpressed in the majority of ccRCC tumors. Collectively, these altered biomarkers are highly interactive and are considered master regulators of processes implicated in increased tumor angiogenesis, metastasis, drug resistance, and immune evasion. In recognition of the therapeutic potential of the indicated biomarkers, considerable efforts are underway to develop therapeutically effective and selective inhibitors of individual targets. It was demonstrated that HIF_S, miR_S, Nrf2, and TGF-ß are targeted by a defined dose and schedule of a specific type of selenium-containing molecules, seleno-L-methionine (SLM) and methylselenocystein (MSC). Collectively, the demonstrated pleiotropic effects of selenium were associated with the normalization of tumor vasculature, and enhanced drug delivery and distribution to tumor tissue, resulting in enhanced efficacy of multiple chemotherapeutic drugs and biologically targeted molecules. Higher selenium doses than those used in clinical prevention trials inhibit multiple targets altered in ccRCC tumors, which could offer the potential for the development of a new and novel therapeutic modality for cancer patients with similar selenium target expression. Better understanding of the underlying mechanisms of selenium modulation of specific targets altered in ccRCC could potentially have a significant impact on the development of a more efficacious and selective mechanism-based combination for the treatment of patients with cancer.

Development and validation of A CT-based radiomics nomogram for prediction of synchronous distant metastasis in clear cell renal cell carcinoma

Background

Early identification of synchronous distant metastasis (SDM) in patients with clear cell Renal cell carcinoma (ccRCC) can certify the reasonable diagnostic examinations.

Methods

This retrospective study recruited 463 ccRCC patients who were divided into two cohorts (training and internal validation) at a 7:3 ratio. Besides, 115 patients from other hospital were assigned external validation cohort. A radiomics signature was developed based on features by means of the least absolute shrinkage and selection operator method. Demographics, laboratory variables and CT findings were combined to develop clinical factors model. Integrating radiomics signature and clinical factors model, a radiomics nomogram was developed.

Results

Ten features were used to build radiomics signature, which yielded an area under the curve (AUC) 0.882 in the external validation cohort. By incorporating the clinical independent predictors, the clinical model was developed with AUC of 0.920 in the external validation cohort. Radiomics nomogram (external validation, 0.925) had better performance than clinical factors model or radiomics signature. Decision curve analysis demonstrated the superiority of the radiomics nomogram in terms of clinical usefulness.

Conclusions

The CT-based nomogram could help in predicting SDM status in patients with ccRCC, which might provide assistance for clinicians in making diagnostic examinations.

Prognostic prediction of clear cell renal cell carcinoma based on lipid metabolism-related lncRNA risk coefficient model

Objective: In order to predict the prognosis in patients with clear cell renal cell carcinoma (ccRCC) so as to understand cancer lipid metabolism and sensitivity to immune-targeting drugs, model algorithms were used to establish a risk coefficient model of long non-coding RNAs (lncRNAs) associated with lipid metabolism. Methods: The transcriptome data were retrieved from TCGA, and lncRNAs associated with lipid metabolism were obtained through Pearson correlation and differential expression analyses. Differentially expressed lipid metabolism-related lncRNAs and lipid metabolism-related lncRNA pairs were obtained using the R language software. The minimum absolute shrinkage method and the selector operation regression method were used to construct the model and draw the receiver operator characteristic curve. High-risk patients were differentiated from low-risk patients through the cut-off value, and the correlation analyses of the high-risk subgroup and low-risk subgroup were performed. Results: This research discovered that 25 pairs of lncRNAs were associated with the lipid metabolism of ccRCC, and 12 of these pairs were utilized to build the model. In combination with clinical data, the areas under the 1-, 3- and 5-year survival curves of ccRCC patients were 0.809, 0.764 and 0.792, separately. The cut-off value was used to perform subgroup analysis. The results showed that high-risk patients had poor prognosis. The results of Cox multivariate regressive analyses revealed that age and risk score were independent prediction factors of ccRCC prognosis. In addition, immune cell infiltration, the levels of gene expression at immune checkpoints, and high-risk patients more susceptible to sunitinib-targeted treatment were assessed by the risk model. Conclusion: Our team identified new prognostic markers of ccRCC and established risk models that could assess the prognosis of ccRCC patients and help determine which type of patients were more susceptible to sunitinib. These discoveries are vital for the optimization of risk stratification and personalized management.

Proteomics Characterization of Clear Cell Renal Cell Carcinoma

PURPOSE

To explore the tumor proteome of patients diagnosed with localized clear cell renal cancer (ccRCC) and treated with surgery.

MATERIAL AND METHODS

A total of 165 FFPE tumor samples from patients diagnosed with ccRCC were analyzed using DIA-proteomics. Proteomics ccRCC subtypes were defined using a consensus cluster algorithm (CCA) and characterized by a functional approach using probabilistic graphical models and survival analyses.

RESULTS

We identified and quantified 3091 proteins, including 2026 high-confidence proteins. Two proteomics subtypes of ccRCC (CC1 and CC2) were identified by CC using the high-confidence proteins only. Characterization of molecular differences between CC1 and CC2 was performed in two steps. First, we defined 514 proteins showing differential expression between the two subtypes using a significance analysis of microarrays analysis. Proteins overexpressed in CC1 were mainly related to translation and ribosome, while proteins overexpressed in CC2 were mainly related to focal adhesion and membrane. Second, a functional analysis using probabilistic graphical models was performed. CC1 subtype is characterized by an increased expression of proteins related to glycolysis, mitochondria, translation, adhesion proteins related to cytoskeleton and actin, nucleosome, and spliceosome, while CC2 subtype showed higher expression of proteins involved in focal adhesion, extracellular matrix, and collagen organization.

CONCLUSIONS

ccRCC tumors can be classified in two different proteomics subtypes. CC1 and CC2 present specific proteomics profiles, reflecting alterations of different molecular pathways in each subtype. The knowledge generated in this type of studies could help in the development of new drugs targeting subtype-specific deregulated pathways.

A novel NSUN5/ENO3 pathway promotes the Warburg effect and cell growth in clear cell renal cell carcinoma by 5-methylcytosine-stabilized ENO3 mRNA

OBJECTIVES

Clear cell renal cell carcinoma (ccRCC) cells often reprogram their metabolisms. Enolase 3 (ENO3) is closely related to the Warburg effect observed in cells during tumor progression. However, the expression and function of ENO3 in ccRCC cells remain unclear. Therefore, this study investigated the expression and functional significance of ENO3 in the Warburg effect observed in ccRCC cells.

METHODS

In this study, B-mode and microflow imaging ultrasound examinations were performed to evaluate patients with ccRCC. The extracellular acidification rate test and glucose uptake and lactate production assays were used to examine the Warburg effect in ccRCC cells. Western blotting, quantitative reverse transcription polymerase chain reaction, and immunochemistry were used to detect the expression of ENO3 and NOP2/Sun RNA methyltransferase 5 (NSUN5).

RESULTS

ENO3 upregulation in ccRCC tumor tissues was accompanied by an increase in tumor size. Importantly, ENO3 participated in the Warburg effect observed in ccRCC cells, and high levels of ENO3 indicated a poor prognosis for patients. Loss of ENO3 reduced glucose uptake, lactate production, and extracellular acidification rate as well as inhibited ccRCC cell proliferation. Furthermore, NSUN5 was involved in the ENO3-regulated Warburg effect and ccRCC cell progression. Mechanically, NSUN5 was upregulated in ccRCC tissues, and NSUN5 upregulation mediated 5-methylcytosine modification of messenger RNA (mRNA) in ccRCC cells to promote mRNA stability and ENO3 expression.

CONCLUSIONS

Collectively, the destruction of the NSUN5/ENO3 axis prevents ccRCC growth in vivo and in vitro, and targeting this pathway may be an effective strategy against ccRCC progression.

Corrigendum: Development and validation of A CT-based radiomics nomogram for prediction of synchronous distant metastasis in clear cell renal cell carcinoma

[This corrects the article DOI: 10.3389/fonc.2022.1016583.].

Identification and Validation of the Prognostic Panel in Clear Cell Renal Cell Carcinoma Based on Resting Mast Cells for Prediction of Distant Metastasis and Immunotherapy Response

Clear cell renal cell carcinoma (ccRCC) has a high metastatic rate, and its incidence and mortality are still rising. The aim of this study was to identify the key tumor-infiltrating immune cells (TIICs) affecting the distant metastasis and prognosis of patients with ccRCC and to construct a relevant prognostic panel to predict immunotherapy response. Based on ccRCC bulk RNA sequencing data, resting mast cells (RMCs) were screened and verified using the CIBERSORT algorithm, survival analysis, and expression analysis. Distant metastasis-associated genes were identified using single-cell RNA sequencing data. Subsequently, a three-gene (CFB, PPP1R18, and TOM1L1) panel with superior distant metastatic and prognostic performance was established and validated, which stratified patients into high- and low-risk groups. The high-risk group exhibited lower infiltration of RMCs, higher tumor mutation burden (TMB), and worse prognosis. Therapeutically, the high-risk group was more sensitive to anti-PD-1 and anti-CTLA-4 immunotherapy, whereas the low-risk group displayed a better response to anti-PD-L1 immunotherapy. Furthermore, two immune clusters revealing distinct immune, clinical, and prognosis heterogeneity were distinguished. Immunohistochemistry of ccRCC samples verified the expression patterns of the three key genes. Collectively, the prognostic panel based on RMCs is able to predict distant metastasis and immunotherapy response in patients with ccRCC, providing new insight for the treatment of advanced ccRCC.

Special issue "The advance of solid tumor research in China": Multi-omics analysis based on 1311 clear cell renal cell carcinoma samples identifies a glycolysis signature associated with prognosis and treatment response

In clear cell renal cell carcinoma (ccRCC), glycolysis is enhanced mainly because of the increased expression of key enzymes in glycolysis. Hence, the discovery of new molecular biomarkers for glycolysis may help guide and establish a precise system of diagnosis and treatment for ccRCC. Expression profiles of 1079 tumor samples of ccRCC patients (including 311 patients treated with everolimus or nivolumab) were downloaded from public databases. Proteomic profiles of 232 ccRCC samples were obtained from Fudan University Shanghai Cancer Center (FUSCC). Biological changes, tumor microenvironment and prognostic differences were explored between samples with various glycolysis characteristics. There were significant differences in CD8⁺ effector T cells, epithelial-to-mesenchymal transition and pan-fibroblast TGFb between the Low and High glyScore groups. The tumor mutation burden of the Low glyScore group was lower than that of the High glyScore group. And higher glyScore was significantly associated with worse overall survival (OS) in 768 ccRCC patients (P < .0001). External validation in FUSCC cohort also indicated that glyScore was of strong ability for predicting OS (P < .05). GlyScore may serve as a biomarker for predicting everolimus response in ccRCC patients due to its significant associations with progression-free survival (PFS). And glyScore may also predict overall survival in patients treated with nivolumab. We calculated the glyScore in ccRCC and the defined glyScore was of strong ability for predicting OS. In addition, glyScore may also serve as a biomarker for predicting PFS in patients treated with everolimus and could predict OS in patients treated with nivolumab.

Molecular subtypes based on metabolic genes are potential biomarkers for predicting prognosis and immune responses of clear cell renal cell carcinoma

Due to the existence of tumor molecular heterogeneity, even patients having similar clinicopathological features could have vastly different survival rates. Hence, we aimed to explore novel metabolism-associated genes (MAGs) related molecular subtypes for clear cell renal cell carcinoma (ccRCC) and their immune landscapes for predicting prognosis and immune responses. Gene matrices and clinical information were downloaded from TCGA and ICGC datasets. Consensus clustering was conducted by the R "ConsensusClusterPlus" package. ccRCC patients were successfully divided into three clusters (MC1, MC2, and MC3) based on MAGs in both TCGA and ICGC datasets. Our established three MAGs were significantly associated with chemokine/chemokine receptor, IFN, CYT, angiogenesis, immune checkpoint molecules, tumor-infiltrating immune cells, oncogenic pathways, pan-cancer immune subtypes, and tumor microenvironment (TME) scores or expressions. Moreover, these three metabolic ccRCC subtypes could predict immunotherapeutic responses. We further constructed a characteristic index (LDAscore) in three metabolic ccRCC subtypes and identified LDAscore-related modules by WGCNA. After deep data mining, 10 hub genes were obtained and seven genes (ATRX, BPTF, DHX9, EP300, POLR2B, SIN3A, UBE3A) were finally validated by qRT-PCR. Our results successfully established a novel ccRCC subtype based on MAGs, providing novel insights into metabolism-related ccRCC tumor heterogeneity and facilitating individualized therapy for future work.

The Construction and Validation of a new Predictive Model for Overall Survival of Clear Cell Renal Cell Carcinoma Patients with Bone Metastasis Based on Machine Learning Algorithm

BACKGROUND

This study aimed to develop and validate predictive models based on machine learning (ML) algorithms for patients with bone metastases (BM) from clear cell renal cell carcinoma (ccRCC) and to identify appropriate models for clinical decision-making.

METHODS

In this retrospective study, we obtained information on ccRCC patients diagnosed with bone metastasis (ccRCC-BM), from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015 (n = 1490), and collected clinicopathological information on ccRCC-BM patients at our hospital (n = 42). We then applied four ML algorithms: extreme gradient boosting (XGB), logistic regression (LR), random forest (RF), and Naive Bayes model (NB), to develop models for predicting the overall survival (OS) of patients with bone metastasis from ccRCC. In the SEER dataset, 70% of the patients were randomly divided into training cohorts and the remaining 30% were used as validation cohorts. Data from our center were used as an external validation cohort. Finally, we evaluated the model performance using receiver operating characteristic curves (ROC), area under the ROC curve (AUC), accuracy, specificity, and F1-scores.

RESULTS

The mean survival times of patients in the SEER and Chinese cohort were 21.8 months and 37.0 months, respectively. Age, marital status, grade, T stage, N stage, tumor size, brain metastasis, liver metastasis, lung metastasis, and surgery were included in the ML model. We observed that all four ML algorithms performed well in predicting the 1-year and 3-year OS of patients with ccRCC-BM.

CONCLUSION

ML is useful in predicting the survival of patients with ccRCC-BM, and ML models can play a positive role in clinical applications.

The mechanism of long-chain acyl-CoA synthetase 3 in inhibiting cell proliferation, migration, and invasion in clear cell renal cell carcinoma

Long-chain acyl-CoA synthases 3 (ACSL3) can activate long-chain fatty acids, which are often deregulated in tumors. However, the biological function of ACSL3 in clear cell renal cell carcinoma (ccRCC) is still unclear. In this research, the expression level, prognostic value, GO and KEGG functional enrichment analyses, genomic changes, clinical significance, immune infiltration of ACSL3 in ccRCC were comprehensively analysed. The expression levels of ACSL3 in ccRCC tissues were detected by quantitative reverse transcription-polymerase chain reaction (RT-qPCR), immunohistochemical staining (IHC), and Western blotting analysis. The proliferation, invasion, migration, apoptotic and lipid synthesis abilities of ccRCC cells were assessed using the cell counting kit (CCK-8), clone formation, scratch assay, Transwell assay, flow cytometry and Oil Red O assay, respectively. The results showed that ACSL3 was obviously downregulated in ccRCC and significantly associated with poor prognosis and clinicopathological factors of ccRCC patients. Additionally, the functional enrichment analysis indicated that ACSL3 was mainly involved in lipid synthesis and metabolism. The result of immune infiltration analysis proved that ACSL3 might regulate the tumor microenvironment of ccRCC. In addition, we demonstrated that overexpression of the ACSL3 could inhibit the proliferation, migration, and invasion of ccRCC cells, and promote apoptosis, reduce abnormal lipid accumulation. In conclusion, ACSL3 might be a novel ccRCC biomarker and the target for ccRCC tumor therapy.

Treatment strategies for clear cell renal cell carcinoma: Past, present and future

Clear cell renal cell carcinoma (ccRCC) is the most prevalent histological subtype of kidney cancer, which is prone to metastasis, recurrence, and resistance to radiotherapy and chemotherapy. The burden it places on human health due to its refractory nature and rising incidence rate is substantial. Researchers have recently determined the ccRCC risk factors and optimized the clinical therapy based on the disease's underlying molecular mechanisms. In this paper, we review the established clinical therapies and novel potential therapeutic approaches for ccRCC, and we support the importance of investigating novel therapeutic options in the context of combining established therapies as a research hotspot, with the goal of providing diversified therapeutic options that promise to address the issue of drug resistance, with a view to the early realization of precision medicine and individualized treatment.

Construction of an interferon regulatory factors-related risk model for predicting prognosis, immune microenvironment and immunotherapy in clear cell renal cell carcinoma

Background

Interferon regulatory factors (IRFs) played complex and essential roles in progression, prognosis, and immune microenvironment in clear cell renal cell carcinoma (ccRCC). The purpose of this study was to construct a novel IRFs-related risk model to predict prognosis, tumor microenvironment (TME) and immunotherapy response in ccRCC.

Methods

Multi-omics analysis of IRFs in ccRCC was performed based on bulk RNA sequencing and single cell RNA sequencing data. According to the expression profiles of IRFs, the ccRCC samples were clustered by non-negative matrix factorization (NMF) algorithm. Then, least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were applied to construct a risk model to predict prognosis, immune cells infiltration, immunotherapy response and targeted drug sensitivity in ccRCC. Furthermore, a nomogram comprising the risk model and clinical characteristics was established.

Results

Two molecular subtypes with different prognosis, clinical characteristics and infiltration levels of immune cells were identified in ccRCC. The IRFs-related risk model was developed as an independent prognostic indicator in the TCGA-KIRC cohort and validated in the E-MTAB-1980 cohort. The overall survival of patients in the low-risk group was better than that in the high-risk group. The risk model was superior to clinical characteristics and the ClearCode34 model in predicting the prognosis. In addition, a nomogram was developed to improve the clinical utility of the risk model. Moreover, the high-risk group had higher infiltration levels of CD8⁺ T cell, macrophages, T follicular helper cells and T helper (Th1) cells and activity score of type I IFN response but lower infiltration levels of mast cells and activity score of type II IFN response. Cancer immunity cycle showed that the immune activity score of most steps was remarkably higher in the high-risk group. TIDE scores indicated that patients in the low-risk group were more likely responsive to immunotherapy. Patients in different risk groups showed diverse drug sensitivity to axitinib, sorafenib, gefitinib, erlotinib, dasatinib and rapamycin.

Conclusions

In brief, a robust and effective risk model was developed to predict prognosis, TME characteristics and responses to immunotherapy and targeted drugs in ccRCC, which might provide new insights into personalized and precise therapeutic strategies.

Integrative analysis of transcriptomic landscape and urinary signature reveals prognostic biomarkers for clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) patients with venous tumor thrombus (VTT) have poor prognosis. We aimed to reveal features of ccRCC with VTT and develop a urine-based prognostic classifier to predict ccRCC prognosis through integrative analyses of transcriptomic landscape and urinary signature.

Methods

RNA sequencing was performed in five patients with ccRCC thrombus-tumor-normal tissue triples, while mass spectrometry was performed for urine samples from 12 ccRCC and 11 healthy controls. A urine-based classifier consisting of three proteins was developed to predict patients' survival and validated in an independent cohort.

Results

Transcriptomic analysis identified 856 invasion-associated differentially expressed genes (DEGs). Furthermore, proteomic analysis showed 133 differentially expressed proteins (DEPs). Integration of transcriptomic landscape and urinary signature reveals 6 urinary detectable proteins (VSIG4, C3, GAL3ST1, TGFBI, AKR1C3, P4HB) displaying abundance changes consistent with corresponding genes in transcriptomic profiling. According to TCGA database, VSIG4, TGFBI, and P4HB were significantly overexpressed in patients with shorter survival and might be independent prognostic factors for ccRCC (all p<0.05). A prognostic classifier consisting of the three DEPs highly associated with survival performed satisfactorily in predicting overall survival (HR=2.0, p<0.01) and disease-free survival (HR=1.6, p<0.001) of ccRCC patients. The ELISA analysis of urine samples from an independent cohort confirmed the satisfied predictive power of the classifier for pathological grade (AUC=0.795, p<0.001) and stage (AUC=0.894, p<0.001).

Conclusion

Based on integrative analyses of transcriptomic landscape and urinary signature, the urine-based prognostic classifier consisting of VSIG4, TGFBI, and P4HB has satisfied predictive power of ccRCC prognosis and may facilitate ccRCC molecular subtyping and treatment.

LITESPARK-011: belzutifan plus lenvatinib vs cabozantinib in advanced renal cell carcinoma after anti-PD-1/PD-L1 therapy

The first-in-class, small molecule HIF-2α inhibitor, belzutifan, has demonstrated promising antitumor activity in previously treated patients with clear cell renal cell carcinoma (RCC). HIF-2α also regulates VEGF expression and is involved in resistance to anti-VEGF therapy. This study describes the rationale and design for a randomized, phase III study evaluating efficacy and safety of belzutifan plus the tyrosine kinase inhibitor (TKI) lenvatinib versus the TKI cabozantinib in patients with advanced RCC progressing after anti-PD-1/PD-L1 therapy in the first- or second-line setting or as adjuvant therapy. Considering the unmet need for effective and tolerable treatment of advanced RCC following immune checkpoint inhibitors, belzutifan plus lenvatinib may have a positive benefit/risk profile. Clinical Trial Registration: NCT04586231 (ClinicalTrials.gov).

Wiskott-Aldrich syndrome gene as a prognostic biomarker correlated with immune infiltrates in clear cell renal cell carcinoma

Introduction

The abnormal expression of the Wiskott-Aldrich syndrome protein (WASP) encoded by the Wiskott-Aldrich syndrome (WAS) gene has been implicated in tumor invasion and immune regulation. However, prognostic implications of WAS and its correlation tumor infiltrating in renal clear cell carcinoma (ccRCC) is not clear cut.

Methods

The correlation between WAS expression, clinicopathological variables and clinical outcomes were evaluated using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Tumor Immune Estimation Resource (TIMER), UALCAN, Gene Expression Profiling Interaction Analysis (GEPIA), Kaplan-Meier (KM) plotter and other databases. Furthermore, we assessed the transcription expression of WAS in renal cancer tissues, various renal carcinoma cell lines and human renal tubular cells (HK2) using quantitative polymerase chain reaction (qPCR). A comprehensive analysis of multiple databases including TIMER, GEPIA, TISIDB, ESTIMATE algorithm, and CIBERSORT algorithm were performed to determine the correlation between WAS and tumor infiltrating immune cells in ccRCC.

Results

The results displayed an increase in WAS mRNA level in ccRCC compared to normal tissue. WAS protein level was found highly expressed in cancer tissues, particularly within renal tumor cells via the human protein atlas (HPA). Interestingly, we found that elevated WAS expression was significantly positively correlated with the infiltration of CD8+ T cells, B cells, Monocytes, Neutrophils, Macrophages, T cell regulation, NK cells, and Dendritic cells in ccRCC. Bioinformatics demonstrated a strong correlation between WAS expression and 42 immune checkpoints, including the T cell exhaustion gene PD-1, which is critical for exploring immunotherapy for ccRCC. We revealed that patients with high WAS expression were less sensitive to immunotherapy medications.

Conclusion

In conclusion, our study identified that WAS was a prognostic biomarker and correlated with immune infiltrates in ccRCC.

Identification of a basement membrane-based risk scoring system for prognosis prediction and individualized therapy in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) belongs to one of the 10 most frequently diagnosed cancers worldwide and has a poor prognosis at the advanced stage. Although multiple therapeutic agents have been proven to be curative in ccRCC, their clinical application was limited due to the lack of reliable biomarkers. Considering the important role of basement membrane (BM) in tumor metastasis and TME regulation, we investigated the expression of BM-related genes in ccRCC and identified prognostic BM genes through differentially expression analysis and univariate cox regression analysis. Then, BM-related ccRCC subtypes were recognized through consensus non-negative matrix factorization based on the prognostic BM genes and evaluated with regard to clinical and TME features. Next, utilizing the differentially expressed genes between the BM-related subtypes, a risk scoring system BMRS was established after serial analysis of univariate cox regression analysis, lasso regression analysis, and multivariate cox regression analysis. Time-dependent ROC curve revealed the satisfactory prognosis predictive capacity of BMRS with internal, and external validation. Multivariate analysis proved the independent predictive ability of BMRS and a BMRS-based nomogram was constructed for clinical application. Some featured mutants were discovered through genomic analysis of the BMRS risk groups. Meanwhile, the BMRS groups were found to have distinct immune scores, immune cell infiltration levels, and immune-related functions. Moreover, with the help of data from The Cancer Immunome Atlas (TCIA) and Genomics of Drug Sensitivity in Cancer (GDSC), the potential of BMRS in predicting therapeutic response was evaluated and some possible therapeutic compounds were proposed through ConnectivityMap (CMap). For the practicability of BMRS, we validated the expression of BMRS-related genes in clinical samples. After all, we identified BM-related ccRCC subtypes with distinct clinical and TME features and constructed a risk scoring system for the prediction of prognosis, therapeutic responses, and potential therapeutic agents of ccRCC. As ccRCC systemic therapy continues to evolve, the risk scoring system BMRS we reported may assist in individualized medication administration.