The tumour microenvironment and metabolism in renal cell carcinoma targeted or immune therapy

CXCL3/TGF-β-mediated crosstalk between CAFs and tumor cells augments RCC progression and sunitinib resistance

Cancer-associated fibroblasts (CAFs) play a significant role in tumor development and treatment failure, yet the precise mechanisms underlying their contribution to renal cell carcinoma (RCC) remains underexplored. This study explored the interaction between CAFs and tumor cells, and related mechanisms. CAFs isolated from tumor tissues promoted the tumor progression and drugs resistance both in vivo and in vitro. Mechanistically, chemokine (C-X-C motif) ligand (CXCL) 3 secreted from CAFs mediated its effects. CXCL3 activated its receptor CXCR2 to active the downstream ERK1/2 signaling pathway, subsequently promoting epithelial-mesenchymal transition and cell stemness. Blocking the crosstalk between CAFs and tumor cells by CXCR2 inhibitor SB225002 attenuated the functions of CAFs. Furthermore, Renca cells facilitated the transformation of normal interstitial fibroblasts (NFs) into CAFs and the expression of CXCL3 through TGF-β-Smad2/3 signaling pathway. In turn, transformed NFs promoted the tumor progression and drug resistance of RCC. These findings may constitute potential therapeutic strategies for RCC treatment.

Exploring the role of CD8+ T cells in clear renal cell carcinoma metastasis

Clear cell renal cell carcinoma (ccRCC) accounts for approximately 75-80% of all patients with renal cell carcinoma. Despite its prevalence, little is known regarding the key components involved in ccRCC metastasis. In this study, scRNA-seq analysis was employed to classify CD8+ T cells into four sub-clusters based on their genetic profiles and immunofluorescence experiments were used to validate two key clusters. Through gene set enrichment analysis, these newly identified sub-clusters were found to exhibit distinct biological characteristics. Notably, TYMP, TOP2A, CHI3L2, CDKN3, CENPM, and RZH2 were highly expressed in these sub-clusters, indicating a correlation with poor prognosis. Among these sub-clusters, CD8+ T cells (MT-ND4) were identified as potentially playing a critical role in mediating ccRCC metastasis. These results contribute to our understanding of CD8+ T cell heterogeneity in ccRCC and shed light on the mechanisms underlying the loss of immune response against cancer.

The combination of immune checkpoint inhibitors and antibody-drug conjugates in the treatment of urogenital tumors: a review insights from phase 2 and 3 studies

With the high incidence of urogenital tumors worldwide, urinary system tumors are among the top 10 most common tumors in men, with prostate cancer ranking first and bladder cancer fourth. Patients with resistant urogenital tumors often have poor prognosis. In recent years, researchers have discovered numerous specific cancer antigens, which has led to the development of several new anti-cancer drugs. Using protein analysis techniques, researchers developed immune checkpoint inhibitors (ICIs) and antibody-conjugated drugs (ADCs) for the treatment of advanced urogenital tumors. However, tumor resistance often leads to the failure of monotherapy. Therefore, clinical trials of the combination of ICIs and ADCs have been carried out in numerous centers around the world. This article reviewed phase 2 and 3 clinical studies of ICIs, ADCs, and their combination in the treatment of urogenital tumors to highlight safe and effective methods for selecting individualized therapeutic strategies for patients. ICIs activate the immune system, whereas ADCs link monoclonal antibodies to toxins, which can achieve a synergistic effect when the two drugs are combined. This synergistic effect provides multiple advantages for the treatment of urogenital tumors.

AURKA promotes renal cell carcinoma progression via regulation of CCNB1 transcription

AURKA is a member of the serine/threonine kinase family and its kinase activity is crucial for the progression of mitosis. Recent studies have highlighted the therapeutic significance of AURKA inhibition in multiple cancer types. However, the specific mechanisms by which AURKA contributes to the progression of renal cell carcinoma (RCC) have not been fully elucidated. In this study, AURKA expression level was identified in human RCC tissues by immunohistochemical (IHC) staining. The function of AURKA on cell malignant phenotypes was evaluated in vitro after AURKA inhibition. The subcutaneous xenograft was conducted to confirm the in vivo effect of AURKA knockdown on growth of RCC cells. Finally, Co-IP, luciferase assay and ChIP experiments were performed to reveal the regulatory mechanism of AURKA on CCNB1. Our results showed a significant upregulation of AURKA in RCC tissues and cell lines, and a high AURKA expression was associated with poor prognosis. AURKA knockdown inhibited RCC cell proliferation and migration, induced cell apoptosis, and led to G1/G2 phase arrest. This effect was further confirmed by the use of an AURKA inhibitor. Mechanistically, AURKA interacted with E2F1, and subsequently recruited it to the promoter region of CCNB1. CCNB1 expression was essential for AURKA-induced RCC progression. Collectively, our results suggested that AURKA plays an important role in development of RCC via regulating CCNB1 transcription.

Rationale for immune checkpoint inhibitors plus targeted therapy for advanced renal cell carcinoma

Renal cell carcinoma (RCC) is a frequent urological malignancy characterized by a high rate of metastasis and lethality. The treatment strategy for advanced RCC has moved through multiple iterations over the past three decades. Initially, cytokine treatment was the only systemic treatment option for patients with RCC. With the development of medicine, antiangiogenic agents targeting vascular endothelial growth factor and mammalian target of rapamycin and immunotherapy, immune checkpoint inhibitors (ICIs) have emerged and received several achievements in the therapeutics of advanced RCC. However, ICIs have still not brought completely satisfactory results due to drug resistance and undesirable side effects. For the past years, the interests form researchers have been attracted by the combination of ICIs and targeted therapy for advanced RCC and the angiogenesis and immunogenic tumor microenvironmental variations in RCC. Therefore, we emphasize the potential principle and the clinical progress of ICIs combined with targeted treatment of advanced RCC, and summarize the future direction.

Molecular characteristics and prognostic significances of lysosomal-dependent cell death in kidney renal clear cell carcinoma

Lysosomal-dependent cell death (LDCD) has an excellent therapeutic effect on apoptosis-resistant and drug-resistant tumors; however, the important role of LDCD-related genes (LDCD-RGs) in kidney renal clear cell carcinoma (KIRC) has not been reported. Initially, single-cell atlas of LDCD signal in KIRC was comprehensively depicted. We also emphasized the molecular characteristics of LDCD-RGs in various human neoplasms. Predicated upon the expressive quotients of LDCD-RGs, we stratified KIRC patients into tripartite cohorts denoted as C1, C2, and C3. Those allocated to the ambit of C1 evinced the most sanguine prognosis within the KIRC cohort, underscored by the acme of LDCD-RGs scores. This further confirms the significant role that LDCD-RGs play in both the pathophysiological foundation and clinical implications of KIRC. In culmination, by virtue of employing the LASSO-Cox analytical modality, we have ushered in an innovative and avant-garde prognostic framework tailored for KIRC, predicated on the bedrock of LDCD-RGs. The assemblage of KIRC instances was arbitrarily apportioned into constituents inclusive of a didactic cohort, an internally wielded validation cadre, and an externally administered validation cohort. Concurrently, patients were dichotomized into strata connoting elevated jeopardy synonymous with adverse prognostic trajectories, and conversely, diminished risk tantamount to favorable prognoses, contingent on the calibrated expressions of LDCD-RGs. Succinctly, our investigative findings serve to underscore the cardinal capacity harbored by LDCD-RGs within the KIRC milieu, concurrently birthing a pioneering prognostic schema intrinsically linked to the trajectory of KIRC and its attendant prognoses.

Cellular senescence-driven transcriptional reprogramming of the MAFB/NOTCH3 axis activates the PI3K/AKT pathway and promotes osteosarcoma progression

Osteosarcoma is the most common primary malignancy of bones and primarily occurs in adolescents and young adults. However, a second smaller peak of osteosarcoma incidence was reported in the elderly aged more than 60. Elderly patients with osteosarcoma exhibit different characteristics compared to young patients, which usually results in a poor prognosis. The mechanism underlying osteosarcoma development in elderly patients is intriguing and of significant value in clinical applications. Senescent cells can accelerate tumor progression by metabolic reprogramming. Recent research has shown that methylmalonic acid (MMA) was significantly up-regulated in the serum of older individuals and played a central role in the development of aggressive characteristics. We found that the significant accumulation of MMA in elderly patients imparted proliferative potential to osteosarcoma cells. The expression of MAFB was excessively up-regulated in osteosarcoma specimens and was further enhanced in response to MMA accumulation as the patient aged. Specifically, we first confirmed a novel molecular mechanism between cellular senescence and cancer, in which the MMA-driven transcriptional reprogramming of the MAFB-NOTCH3 axis accelerated osteosarcoma progression via the activation of PI3K-AKT pathways. Moreover, the down-regulation of the MAFB-NOTCH3 axis increased the sensitivity and effect of AKT inhibitors in osteosarcoma through significant inhibition of AKT phosphorylation. In conclusion, we confirmed that MAFB is a novel age-dependent biomarker for osteosarcoma, and targeting the MAFB-NOTCH3 axis in combination with AKT inhibition can serve as a novel therapeutic strategy for elderly patients with osteosarcoma in experimental and clinical trials.

Pharmacological functions of salidroside in renal diseases: facts and perspectives

Rhodiola rosea is a valuable functional medicinal plant widely utilized in China and other Asian countries for its anti-fatigue, anti-aging, and altitude sickness prevention properties. Salidroside, a most active constituent derived from Rhodiola rosea, exhibits potent antioxidative, hypoxia-resistant, anti-inflammatory, anticancer, and anti-aging effects that have garnered significant attention. The appreciation of the pharmacological role of salidroside has burgeoned over the last decade, making it a beneficial option for the prevention and treatment of multiple diseases, including atherosclerosis, Alzheimer's disease, Parkinson's disease, cardiovascular disease, and more. With its anti-aging and renoprotective effects, in parallel with the inhibition of oxidative stress and inflammation, salidroside holds promise as a potential therapeutic agent for kidney damage. This article provides an overview of the microinflammatory state in kidney disease and discuss the current therapeutic strategies, with a particular focus on highlighting the recent advancements in utilizing salidroside for renal disease. The potential mechanisms of action of salidroside are primarily associated with the regulation of gene and protein expression in glomerular endothelial cells, podocytes, renal tubule cells, renal mesangial cells and renal cell carcinoma cell, including TNF-α, TGF-β, IL-1β, IL-17A, IL-6, MCP-1, Bcl-2, VEGF, ECM protein, caspase-3, HIF-1α, BIM, as well as the modulation of AMPK/SIRT1, Nrf2/HO-1, Sirt1/PGC-1α, ROS/Src/Cav-1, Akt/GSK-3β, TXNIP-NLRP3, ERK1/2, TGF-β1/Smad2/3, PI3K/Akt, Wnt1/Wnt3a β-catenin, TLR4/NF-κB, MAPK, JAK2/STAT3, SIRT1/Nrf2 pathways. To the best of our knowledge, this review is the first to comprehensively cover the protective effects of salidroside on diverse renal diseases, and suggests that salidroside has great potential to be developed as a drug for the prevention and treatment of metabolic syndrome, cardiovascular and cerebrovascular diseases and renal complications.

PDGF-BB accelerates TSCC via fibroblast lactates limiting miR-26a-5p and boosting mitophagy

The tumor microenvironment and cancer-associated fibroblasts (CAFs) play crucial roles in tumor development, and their metabolic coupling remains unclear. Clinical data showed a positive correlation between PDGF-BB, CAFs, and glycolysis in the tumor microenvironment of oral tongue squamous cell carcinoma patients. In vitro, CAFs are derived from hOMF cells treated with PDGF-BB, which induces their formation and promotes aerobic glycolysis. Mitophagy increased the PDGF-BB-induced formation of CAF phenotypes and aerobic glycolysis, while autophagy inhibition blocked PDGF-BB-induced effects. Downregulation of miR-26a-5p was observed in CAFs; upregulation of miR-26a-5p inhibited the expression of mitophagy-related proteins ULKI, Parkin, PINK1, and LC3 and aerobic glycolysis in PDGF-BB-induced CAFs. PDGF-BB-induced CAFs promoted tumor cell proliferation, invasion, metastasis, NF-κB signaling pathway activation, and PDGF-BB secretion. Thus, PDGF-BB is associated with lactate-induced CAF formation and glucose metabolism reprogramming. These findings indicate potential therapeutic targets in oral tongue squamous cell carcinoma.

NEIL3 promotes cell proliferation of ccRCC via the cyclin D1-Rb-E2F1 feedback loop regulation

Nei endonuclease VIII-like 3 (NEIL3), a novel tumor-related gene, is differentially expressed and involved in pathophysiological processes in multiple tumors. However, the potential biological functions and molecular mechanisms of NEIL3 in human clear cell renal cell carcinoma (ccRCC) have not been identified. In this research, we demonstrated that NEIL3, transcriptionally activated by E2F1, served as an oncogene to facilitate cell proliferation and cell cycle progression and contribute to tumorigenesis via the cyclin D1-Rb-E2F1 feedback loop in ccRCC. First, we found that NEIL3 expression was upregulated in ccRCC tissues and cell lines compared with matched adjacent nontumor tissues and renal tubular epithelial cells and was also positively correlated with adverse clinicopathological characteristics, such as advanced cancer stages and higher tumor grades, and acted as an independent prognostic marker in ccRCC. Mechanistically, we demonstrated that NEIL3 promoted cell proliferation, DNA replication and cell cycle progression in vitro and tumor growth in vivo. Furthermore, we found that NEIL3 overexpression activated the cyclin D1-Rb-E2F1 pathway, and the E2F1 upregulation transcriptionally activated NEIL3 expression, thus forming a feedback loop. In addition, there was a positive correlation between NEIL3 and E2F1 expression in clinical specimens of ccRCC. Taken together, our results suggest that NEIL3 serves as a proto-oncogene in ccRCC and presents as a novel candidate for ccRCC diagnosis and treatment.

Long non-coding RNA HIF1A-AS2 promotes carcinogenesis by enhancing Gli1-mediated HIF1α expression in clear cell renal cell carcinoma

BACKGROUND

The most common urologic tumor in humans with the highest incidence rate is clear cell renal cell carcinoma (ccRCC). Long non-coding RNAs (lncRNAs) act as regulatory factors in several tumors. Here, we studied ccRCC regulated by hypoxia-inducible factor 1α (HIF1α)-antisense RNA 2 (AS2) or HIF1A-AS2.

METHODS

We performed wound-healing, transwell, and CCK-8 assays by decreasing or increasing the HIF1A-AS2 expression in RCC cell lines. Western blotting and qRT-PCR were used to identify the expression of downstream genes of the HIF1A-AS2 pathway. Gli1 and HIF1A-AS2 relationship was assessed using RIP and RNA pull-down assays. Lastly, transcriptome sequencing was performed on kidney cancer cells that had been knocked down to find possible regulatory mechanisms.

RESULTS

Our results suggest that high expression of HIF1A-AS2 may promote RCC cell proliferation and Gli1 expression as a downstream factor. Furthermore, they have physical binding sites and together regulate HIF1α to encourage the development of ccRCC. HIF1A-AS2 lncRNA may offer a new molecular target for ccRCC treatment.

CONCLUSION

lncRNA HIF1A-AS2 affects ccRCC development by regulating HIF1a expression through Gli1.

Potential value of mitochondrial regulatory pathways in the clinical application of clear cell renal cell carcinoma: a machine learning-based study

BACKGROUND

Renal clear cell carcinoma (RCC) is a common cancer in urinary system with increasing incidence. At present, targeted therapy and immunotherapy are the main therapeutic programs in clinical therapy. To develop novel drugs and provide new ideas for clinical therapy, the identification of potential ccRCC subtypes and potential target genes or pathways has become a current research focus.

AIM

The aim of this study was to explore the underlying mechanisms of mitochondrial function in ccRCC. This regulatory pathway is closely related to tumor development and metastasis in ccRCC patients, and their abnormal changes may affect the prognosis of cancer patients. Therefore, we decided to construct a prognostic model of ccRCC patients based on mitochondrial regulatory genes, aiming to provide new methods and ideas for clinical therapy.

RESULT

The 5-year survival prediction model based on iterative LASSO reached 0.746, and the cox model based on coxph reached C-index = 0.77, integrated c/D AUC = 0.61, and integrated brier score = 0.14. The rsf model based on randomForestSRC was built with C-index = 0.82, integrated c/D AUC = 0.69, and integrated brier score = 0.11. The results show that mitochondrial regulatory pathway is a potential target pathway for clinical therapy of ccRCC, which can provide guidelines for clinical targeted therapy, immunotherapy and other first-line therapy.

Recent progress in the development of nanomaterials targeting multiple cancer metabolic pathways: a review of mechanistic approaches for cancer treatment

Cancer is a very heterogeneous disease, and uncontrolled cell division is the main characteristic of cancer. Cancerous cells need a high nutrition intake to enable aberrant growth and survival. To do so, cancer cells modify metabolic pathways to produce energy and anabolic precursors and preserve redox balance. Due to the importance of metabolic pathways in tumor growth and malignant transformation, metabolic pathways have also been given promising perspectives for cancer treatment, providing more effective treatment strategies, and target-specific with minimum side effects. Metabolism-based therapeutic nanomaterials for targeted cancer treatment are a promising option. Numerous types of nanoparticles (NPs) are employed in the research and analysis of various cancer therapies. The current review focuses on cutting-edge strategies and current cancer therapy methods based on nanomaterials that target various cancer metabolisms. Additionally, it highlighted the primacy of NPs-based cancer therapies over traditional ones, the challenges, and the future potential.

Lipid metabolism-related gene expression in the immune microenvironment predicts prognostic outcomes in renal cell carcinoma

Background

Rates of renal cell carcinoma (RCC) occurrence and mortality are steadily rising. In an effort to address this issue, the present bioinformatics study was developed with the goal of identifying major lipid metabolism biomarkers and immune infiltration characteristics associated with RCC cases.

Methods

The Cancer Genome Atlas (TCGA) and E-MTAB-1980 were used to obtain matched clinical and RNA expression data from patients diagnosed with RCC. A LASSO algorithm and multivariate Cox regression analyses were employed to design a prognostic risk model for these patients. The tumor immune microenvironment (TIME) in RCC patients was further interrogated through ESTIMATE, TIMER, and single-cell gene set enrichment analysis (ssGSEA) analyses. Gene Ontology (GO), KEGG, and GSEA enrichment approaches were further employed to gauge the mechanistic basis for the observed results. Differences in gene expression and associated functional changes were then validated through appropriate molecular biology assays.

Results

Through the approach detailed above, a risk model based on 8 genes associated with RCC patient overall survival and lipid metabolism was ultimately identified that was capable of aiding in the diagnosis of this cancer type. Poorer prognostic outcomes in the analyzed RCC patients were associated with higher immune scores, lower levels of tumor purity, greater immune cell infiltration, and higher relative immune status. In GO and KEGG enrichment analyses, genes that were differentially expressed between risk groups were primarily related to the immune response and substance metabolism. GSEA analyses additionally revealed that the most enriched factors in the high-risk group included the stable internal environment, peroxisomes, and fatty acid metabolism. Subsequent experimental validation in vitro and in vivo revealed that the most significantly differentially expressed gene identified herein, ALOX5, was capable of suppressing RCC tumor cell proliferation, invasivity, and migration.

Conclusion

In summary, a risk model was successfully established that was significantly related to RCC patient prognosis and TIME composition, offering a robust foundation for the development of novel targeted therapeutic agents and individualized treatment regimens. In both immunoassays and functional analyses, dysregulated lipid metabolism was associated with aberrant immunological activity and the reprogramming of fatty acid metabolic activity, contributing to poorer outcomes.

Downregulation of RNA binding protein 47 predicts low survival in patients and promotes the development of renal cell malignancies through RNA stability modification

RNA binding proteins (RBPs) are crucial for cell function, tissue growth, and disease development in disease or normal physiological processes. RNA binding motif protein 47 (RBM47) has been proven to have anti-tumor effects on many cancers, but its effect is not yet clear in renal cancer. Here, we demonstrated the expression and the prognostic role of RBM47 in public databases and clinical samples of clear cell renal carcinoma (ccRCC) with bioinformatics analysis. The possible mechanism of RBM47 in renal cancer was verified by gene function prediction and in vitro experiments. The results showed that RBM47 was downregulated in renal cancers when compared with control groups. Low RBM47 expression indicated poor prognosis in ccRCC. RBM47 expression in renal cancer cell lines was reduced significantly when compared to normal renal tubular epithelial cells. Epithelial-mesenchymal transition (EMT) and transforming growth factor-β signaling pathway was associated with RBM47 in ccRCC by Gene set enrichment analysis. RBM47 expression had a positive correlation with e-cadherin, but a negative correlation with snail and vimentin. RBM47 overexpression could repress the migration, invasion activity, and proliferation capacity of renal cancer cells, while RBM47 inhibition could promote the development of the malignant features through EMT signaling by RNA stability modification. Therefore, our results suggest that RBM47, as a new molecular biomarker, may play a key role in the cancer development of ccRCC.

Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment

Clear cell renal cell carcinoma (ccRCC) is one of the most common primary malignancies of the urinary tract, highly heterogeneous, and increasing in incidence worldwide. Anoikis is a specific type of programmed cell death in which solid tumor cells or normal epithelial cells that do not have metastatic properties lose adhesion to the extracellular matrix or undergo inappropriate cell adhesion-induced apoptosis. Anoikis is thought to play a critical role in tumorigenesis, maintenance, and treatment, according to an increasing amount of research. However, there is still some uncertainty regarding the general impact of anoikis-related genes (ARGs) on the prognostic importance, tumor microenvironment characteristics, and treatment reaction of ccRCC patients. For this study, we used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus datasets to access the RNA sequencing results and clinical information from ccRCC patients. 29 ARGs related to survival were found using differential analysis and univariate Cox regression analysis. The samples were then divided into two clusters that had different immune traits via unsupervised cluster analysis using 29 prognosis-associated differently expressed ARGs. Then, to build an ARGs signature, 7 genes (PLAU, EDA2R, AFP, PLG, TUBB3, APOBEC3G, and MALAT1) were found using Least Absolute Shrinkage and Selection Operator regression analysis. The new ARGs signature demonstrated outstanding prognostic capability for ccRCC patients' overall survival. In conclusion, for ccRCC patients, we created an ARGs signature that strongly connects to immunological traits and therapy response. Clinicians may find this ARGs signature helpful in developing more individualized and detailed treatment strategies for ccRCC patients.

Unraveling the prognostic significance and molecular characteristics of tumor-infiltrating B lymphocytes in clear cell renal cell carcinoma through a comprehensive bioinformatics analysis

Introduction

Clear cell renal cell carcinoma (ccRCC) is a prevalent subtype of kidney cancer that exhibits a complex tumor microenvironment, which significantly influences tumor progression and immunotherapy response. In recent years, emerging evidence has underscored the involvement of tumor-infiltrating B lymphocytes (TIL-Bs), a crucial component of adaptive immunity, and their roles in ccRCC as compared to other tumors. Therefore, the present study endeavors to systematically explore the prognostic and molecular features of TIL-Bs in ccRCC.

Methods

Initially, xCell algorithm was used to predict TIL-Bs in TCGA-KIRC and other ccRCC transcriptomic datasets. The Log-Rank test and Cox regression were applied to explore the relationship of B-cells with ccRCC survival. Then, we used WGCNA method to identify important modules related to TIL-Bs combining Consensus subcluster and scRNA-seq data analysis. To narrow down the prospective biomarkers, a prognostic signature was proposed. Next, we explored the feature of the signature individual genes and the risk-score. Finally, the potential associations of signature with clinical phenotypes and drugs were investigated.

Results

Preliminary, we found ccRCC survival was negatively associated with TIL-Bs, which was confirmed by other datasets. Afterwards, ten co-expression modules were identified and a distinct ccRCC cluster was subsequently detected. Moreover, we assessed the transcriptomic alteration of B-cell in ccRCC and a relevant B-cell subtype was also pinpointed. Based on two core modules (brown, red), a 10-gene signature (TNFSF13B, SHARPIN, B3GAT3, IL2RG, TBC1D10C, STAC3, MICB, LAG3, SMIM29, CTLA4) was developed in train set and validated in test sets. These biomarkers were further investigated with regards to their differential expression and correlation with immune characteristics, along with risk-score related mutations and pathways. Lastly, we established a nomogram combined tumor grade and discovered underlying drugs according to their sensitivity response.

Discussion

In our research, we elucidated the remarkable association between ccRCC and B-cells. Then, we detected several key gene modules, together with close patient subcluster and B-cell subtype,which could be responsible for the TIL-Bs in ccRCC. Moreover, we proposed a 10-gene signature and investigated its molecular features from multiple perspectives. Overall, understanding the roles of TIL-Bs could aid in the immunotherapeutic approaches for ccRCC, which deserve further research to clarify the implications for patient prognosis and treatment.

Integrated analysis of the roles of oxidative stress related genes and prognostic value in clear cell renal cell carcinoma

BACKGROUND

Patients with clear cell renal cell carcinoma (ccRCC), which is the most commonly diagnosed subtype of renal cell carcinoma, are at risk of tumor metastasis and recrudescence. Previous research has shown that oxidative stress can induce tumorigenesis in many cancers and can be a target of cancer treatment. Despite these findings, little progress has been made understanding in the association of oxidative stress-related genes (OSRGs) with ccRCC.

METHODS

In vitro experiments were conducted with MTT survival assays, qRT‒PCR, apoptosis assays, cell cycle assays, ROS assays, and IHC staining.

RESULTS

In our study, 12 differentially expressed oxidative stress-related genes (DEOSGs) and related transcription factors (TFs) that are relevant to overall survival (OS) were screened, and their mutual regulatory networks were constructed with data from the TCGA database. Moreover, we constructed a risk model of these OSRGs and performed clinical prognostic analysis and validation. Next, we performed protein-protein interaction (PPI) network analysis and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of MELK, PYCR1, and PML. A tissue microarray also verified the high expression of MELK and PYCR1 in ccRCC. Finally, in vitro cellular experiments demonstrated that knockdown of MELK or PYCR1 significantly inhibited ccRCC cell proliferation by causing cell apoptosis and inducing cell cycle arrest in the G1 phase. Intracellular ROS levels were elevated after these two genes were knocked down.

CONCLUSION

Our results revealed the potential DEORGs to be used in ccRCC prognostic prediction and identified two biomarkers, named PYCR1 and MELK, which regulated the proliferation of ccRCC cells by affecting ROS levels. Furthermore, PYCR1 and MELK could be promising targets for predicting the progression and prognosis of ccRCC, thereby serving as new targets for medical treatments.

Identification of microRNA editing sites in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor originating from the renal tubular epithelium. Although the microRNAs (miRNAs) transcriptome of ccRCC has been extensively studied, the role of miRNAs editing in ccRCC is largely unknown. By analyzing small RNA sequencing profiles of renal tissues of 154 ccRCC patients and 22 normal controls, we identified 1025 miRNA editing sites from 246 pre-miRNAs. There were 122 editing events with significantly different editing levels in ccRCC compared to normal samples, which include two A-to-I editing events in the seed regions of hsa-mir-376a-3p and hsa-mir-376c-3p, respectively, and one C-to-U editing event in the seed region of hsa-mir-29c-3p. After comparing the targets of the original and edited miRNAs, we found that hsa-mir-376a-1_49g, hsa-mir-376c_48g and hsa-mir-29c_59u had many new targets, respectively. Many of these new targets were deregulated in ccRCC, which might be related to the different editing levels of hsa-mir-376a-3p, hsa-mir-376c-3p, hsa-mir-29c-3p in ccRCC compared to normal controls. Our study sheds new light on miRNA editing events and their potential biological functions in ccRCC.

Identification of ATP6V0A4 as a potential biomarker in renal cell carcinoma using integrated bioinformatics analysis

Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of renal cancer, and is associated with a high mortality rate, which is related to high rates of tumor recurrence and metastasis. The aim of the present study was to identify reliable molecular biomarkers with high specificity and sensitivity for ccRCC. A total of eight ccRCC-related expression profiles were downloaded from Gene Expression Omnibus for integrated bioinformatics analysis to screen for significantly differentially expressed genes (DEGs). Reverse transcription-quantitative (RT-q)PCR, western blotting and immunohistochemistry staining assays were performed to evaluate the expression levels of candidate biomarkers in ccRCC tissues and cell lines. In total, 255 ccRCC specimens and 165 adjacent normal kidney specimens were analyzed, and 344 significant DEGs, consisting of 115 upregulated DEGs and 229 downregulated DEGs, were identified. The results of Gene Ontology analysis suggested a significant enrichment of DEGs in 'organic anion transport' and 'small molecule catabolic process' in biological processes, in 'apical plasma membrane' and 'apical part of the cell' in cell components, and in 'anion transmembrane transporter activity' and 'active transmembrane transporter activity' in molecular functions. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that the DEGs were significantly enriched in the 'phagosome', the 'PPAR signaling pathway', 'complement and coagulation cascades', the 'HIF-1 signaling pathway' and 'carbon metabolism'. Next, 7 hub genes (SUCNR1, CXCR4, VCAN, CASR, ATP6V0A4, VEGFA and SERPINE1) were identified and validated using The Cancer Genome Atlas database. Survival analysis showed that low expression of ATP6V0A4 was associated with a poor prognosis in patients with ccRCC. Additionally, received operating characteristic curves indicated that ATP6V0A4 could distinguish ccRCC samples from normal kidney samples. Furthermore, RT-qPCR, western blotting and immunohistochemistry staining results showed that ATP6V0A4 was significantly downregulated in ccRCC tissues and cell lines. In conclusion, ATP6V0A4 may be involved in tumor progression and regarded as a potential therapeutic target for the recurrence and metastasis of ccRCC.

Advanced in vitro models for renal cell carcinoma therapy design

Renal cell carcinoma (RCC) and its principal subtype, clear cell RCC, are the most diagnosed kidney cancer. Despite substantial improvement over the last decades, current pharmacological intervention still fails to achieve long-term therapeutic success. RCC is characterized by a high intra- and inter-tumoral heterogeneity and is heavily influenced by the crosstalk of the cells composing the tumor microenvironment, such as cancer-associated fibroblasts, endothelial cells and immune cells. Moreover, multiple physicochemical properties such as pH, interstitial pressure or oxygenation may also play an important role. These elements are often poorly recapitulated in in vitro models used for drug development. This inadequate recapitulation of the tumor is partially responsible for the current lack of an effective and curative treatment. Therefore, there are needs for more complex in vitro or ex vivo drug screening models. In this review, we discuss the current state-of-the-art of RCC models and suggest strategies for their further development.

Cuproptosis related gene PDHB is identified as a biomarker inversely associated with the progression of clear cell renal cell carcinoma

BACKGROUND

Cuproptosis is a newly discovered programmed cell death dependent on mitochondrial respiratory disorder induced by copper overload. Pyruvate dehydrogenase E1 subunit beta (PDHB) is one of the cuproptosis genesand is a nuclear-encoded pyruvate dehydrogenase, which catalyzes the conversion of pyruvate to acetyl coenzyme A. However, the mechanism of PDHB in clear cell renal cell carcinoma (ccRCC) remains unclear.

METHODS

We used data from TCGA and GEO to assess the expression of PDHB in normal and tumor tissues. We further analyzed the relationship between PDHB and somatic mutations and immune infiltration. Finally, we preliminarily explored the impact of PDHB on ccRCC.

RESULTS

The expression level of PDHB was lower in tumor tissue compared with normal tissue. Meanwhile, the expression level of PDHB was also lower in high-grade tumors than low-grade tumors. PDHB is positively correlated with prognosis in ccRCC. Furthermore, PDHB may be associated with decreased risk of VHL, PBRM1 and KDM5C mutations. In 786-O cells, copper chloride could promote the expression of cuproptosis genes (DLAT, PDHB and FDX1) and inhibit cell growth. Last but not least, we found that PDHB could inhibit the proliferation and migration of ccRCC cells.

CONCLUSION

Our results demonstrated that PDHB could inhibit the proliferation, migration and invasion in ccRCC cells, which might be a prognostic predictor of ccRCC. Targeting this molecular might provide a new therapeutic strategy for patients with advanced ccRCC.

Predicting response of immunotherapy and targeted therapy and prognosis characteristics for renal clear cell carcinoma based on m1A methylation regulators

In recent years, RNA methylation modification has been found to be related to a variety of tumor mechanisms, such as rectal cancer. Clear cell renal cell carcinoma (ccRCC) is most common in renal cell carcinoma. In this study, we get the RNA profiles of ccRCC patients from ArrayExpress and TCGA databases. The prognosis model of ccRCC was developed by the least absolute shrinkage and selection operator (LASSO) regression analysis, and the samples were stratified into low-high risk groups. In addition, our prognostic model was validated through the receiver operating characteristic curve (ROC). "pRRophetic" package screened five potential small molecule drugs. Protein interaction networks explore tumor driving factors and drug targeting factors. Finally, polymerase chain reaction (PCR) was used to verify the expression of the model in the ccRCC cell line. The mRNA matrix in ArrayExpress and TCGA databases was used to establish a prognostic model for ccRCC through LASSO regression analysis. Kaplan Meier analysis showed that the overall survival rate (OS) of the high-risk group was poor. ROC verifies the reliability of our model. Functional enrichment analysis showed that there was a obviously difference in immune status between the high-low risk groups. "pRRophetic" package screened five potential small molecule drugs (A.443654, A.770041, ABT.888, AG.014699, AMG.706). Protein interaction network shows that epidermal growth factor receptor [EGRF] and estrogen receptor 1 [ESR1] are tumor drivers and drug targeting factors. To further analyze the differential expression and pathway correlation of the prognosis risk model species. Finally, polymerase chain reaction (PCR) showed the expression of YTHN6-Methyladenosine RNA Binding Protein 1[YTHDF1], TRNA Methyltransferase 61B [TRMT61B], TRNA Methyltransferase 10C [TRMT10C] and AlkB Homolog 1[ALKBH1] in ccRCC cell lines. To sum up, the prognosis risk model we created not only has good predictive value, but also can provide guidance for accurately predicting the prognosis of ccRCC.

Sphingosine kinase 1 regulates lipid metabolism to promote progression of kidney renal clear cell carcinoma

PURPOSE

To detect the expression of sphingosine kinase 1 (SPHK1) in clear cell renal cell carcinoma (ccRCC) and explore its biological role in the occurrence and development of ccRCC through regulation of fatty acid metabolism.

METHODS

Using the Cancer Genome Atlas database, SPHK1 expression and its clinical significance were detected in clear cell renal cell carcinoma. Immunohistochemistry was performed to detect SPHK1 expression in RCC samples in our hospital. The connection between the SPHK1 levels and clinicopathological features of patients was assessed. Nile Red was used to detect fatty acids in cells. Cell Counting Kit-8 and 5-ethynyl-2'-deoxyuridine assays were performed to determine the effect of SPHK1 on renal cell viability and proliferation, respectively. Additionally, the effects of SPHK1 on the proliferation and metastasis of ccRCC were studied using wound healing and Transwell assays. Fatty acids were added exogenously in recovery experiments and western blotting was performed to determine the effect of SPHK1 on fatty acid metabolism in ccRCC. Finally, the effects of SPHK1 on tumor growth were investigated in a xenograft model.

RESULTS

Bioinformatics analysis revealed that SPHK1 expression was upregulated in kidney RCC. OverSPHK1 expression was associated with poor prognosis for ccRCC patients. High SPHK1 expression was detected in human ccRCC. SPHK1 expression was related to clinicopathological features, such as tumor size and Furman grade. Additionally, cell proliferation, migration, and invasion were inhibited in ccRCC cells with low SPHK1 expression. In rescue experiments, proliferation, migration, and invasion were restored. In vivo, reduced SPHK1 levels correlated with lower expression of fatty acid synthase, stearoyl-CoA desaturase 1, and acetyl CoA carboxylase, and slowed tumor growth.

CONCLUSIONS

SPHK1 is abnormally overexpressed in human ccRCC. Patients with ccRCC may benefit from treatments that target SPHK1, which may also serve as a prognostic indicator.

Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature

It has been reported that metabolic disorders participate in the formation and progression of clear cell renal cell carcinoma (ccRCC). However, the predictive value of metabolism-related genes (MRGs) in clinical outcome of ccRCC is still largely unknown. Herein, a novel metabolism-related signature was generated to assess the effect of MRGs on the prognosis of ccRCC patients. Important module MRGs were selected by differentially expressed analysis and WGCNA. Subsequently, the hub MRGs were screened via univariate cox regression as well as LASSO regression. A new metabolism-related signature of 6 hub MRGs (PAFAH2, ACADSB, ACADM, HADH, PYCR1 and ITPKA) was constructed, with a good prognostic prediction ability in the TCGA cohort. The prediction accuracy of this signature was further confirmed in both GSE22541 and FAHWMU cohort. Interestingly, this MRG risk signature was highly correlated with tumor mutation burden and immune infiltration in ccRCC. Notably, lower PAFAH2, a member of 6 MRGs, was found in ccRCC. Knockdown of PAFAH2 contributed to renal cancer cell proliferation and migration. Collectively, a 6-MRG prognostic risk signature is generated to estimate the prognostic status of ccRCC patients, providing a novel insight in the prognosis prediction and treatment of ccRCC.

Identification of novel and potent dual-targeting HDAC1/SPOP inhibitors using structure-based virtual screening, molecular dynamics simulation and evaluation of in vitro and in vivo antitumor activity

Cancer is one of the important factors threatening human health. Hence, it is essential to create novel potent drugs to treat it. Due to the strong correlation among histone deacetylase1 (HDAC1), speckle-type POZ protein (SPOP) and cancers, dual inhibition of HDAC1 and SPOP may be a promising strategy for cancer treatment. In this study, we successfully identified four potential dual-targeting HDAC1/SPOP candidate compounds with structure-based virtual screening. In vitro inhibition experiments confirmed that the four compounds had dual inhibitory effects on HDAC1 and SPOP. Among them, compound HS-2 had a stronger inhibitory effect on HDAC1 and SPOP than the positive controls. Further molecular dynamics simulations indicated that HS-2 could stably bind to HDAC1 and SPOP. In addition, MTT assay indicated that HS-2 inhibited the growth of tumor cells in the micromolar range. In vivo evaluation showed that HS-2 could obviously inhibit the growth of tumor in nude mice without obvious toxicity. These findings suggest that HS-2 is a novel and potent dual-targeting HDAC1/SPOP inhibitor for cancer treatment.

Connexin43 is associated with the progression of clear cell renal carcinoma and is regulated by tangeretin to sygergize with tyrosine kinase inhibitors

BACKGROUND

The roles of Connexin43 (Cx43) in clear cell renal cell carcinoma (ccRCC) microenviroment remains to be poorly defined.

METHODS

The expression profile, prognosis and immune analysis of Cx43 in various cancers, particularly in ccRCC were performed using TCGA database, and various biological function assays were applied to explore the physiological role of Cx43 and tangeretin in ccRCC. Western blot were applied to examine the protein expression and Kunming mice were used to evaluate preliminary safety or anti-tumor activity of tangeretin and sunitinib.

RESULTS

Compared with the normal group, higher expression levels of Cx43 in ccRCC, and distinct associations between Cx43 expression and ccRCC prognosis or immune infiltration, were found. Notably, the expression of Cx43 was found to be highly correlated with that of receptor tyrosine kinases (RTKs), particularly with VEGFR1, VEGFR2 and VEGFR3. The expression of Cx43 and EGFR was also found to be higher in ccRCC than that in the para-cancerous specimens. Knocking down Cx43 expression decreased RCC cell viability, cell migration, p-EGFR, MMP-9 and survivin expression. Using 14 Chinese medicine monomers, tangeretin was screened and found to inhibit tumor cell viability and Cx43 expression. Tangeretin also enhanced the sensitivity of RCC cells to tyrosine kinase inhibitors (TKIs) sunitinib and sorafenib. However, the same concentration of tangeretin exerted a less prominent effect on normal renal cell viability.

CONCLUSIONS

Cx43 is strongly associated with RTK expression and ccRCC progression, while tangeretin can inhibit RCC cell malignancy by inhibiting Cx43 expression and enhance the sensitivity of RCC cells to TKIs.

Cellular and Molecular Players in the Tumor Microenvironment of Renal Cell Carcinoma

Globally, clear-cell renal cell carcinoma (ccRCC) represents the most prevalent type of kidney cancer. Surgery plays a key role in the treatment of this cancer, although one third of patients are diagnosed with metastatic ccRCC and about 25% of patients will develop a recurrence after nephrectomy with curative intent. Molecular-target-based agents, such as tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), are recommended for advanced cancers. In addition to cancer cells, the tumor microenvironment (TME) includes non-malignant cell types embedded in an altered extracellular matrix (ECM). The evidence confirms that interactions among cancer cells and TME elements exist and are thought to play crucial roles in the development of cancer, making them promising therapeutic targets. In the TME, an unfavorable pH, waste product accumulation, and competition for nutrients between cancer and immune cells may be regarded as further possible mechanisms of immune escape. To enhance immunotherapies and reduce resistance, it is crucial first to understand how the immune cells work and interact with cancer and other cancer-associated cells in such a complex tumor microenvironment.

PI3K/AKT/mTOR Dysregulation and Reprogramming Metabolic Pathways in Renal Cancer: Crosstalk with the VHL/HIF Axis

Renal cell carcinoma (RCC) represents 85-95% of kidney cancers and is the most frequent type of renal cancer in adult patients. It accounts for 3% of all cancer cases and is in 7th place among the most frequent histological types of cancer. Clear cell renal cell carcinoma (ccRCC), accounts for 75% of RCCs and has the most kidney cancer-related deaths. One-third of the patients with ccRCC develop metastases. Renal cancer presents cellular alterations in sugars, lipids, amino acids, and nucleic acid metabolism. RCC is characterized by several metabolic dysregulations including oxygen sensing (VHL/HIF pathway), glucose transporters (GLUT 1 and GLUT 4) energy sensing, and energy nutrient sensing cascade. Metabolic reprogramming represents an important characteristic of the cancer cells to survive in nutrient and oxygen-deprived environments, to proliferate and metastasize in different body sites. The phosphoinositide 3-kinase-AKT-mammalian target of the rapamycin (PI3K/AKT/mTOR) signaling pathway is usually dysregulated in various cancer types including renal cancer. This molecular pathway is frequently correlated with tumor growth and survival. The main aim of this review is to present renal cancer types, dysregulation of PI3K/AKT/mTOR signaling pathway members, crosstalk with VHL/HIF axis, and carbohydrates, lipids, and amino acid alterations.

Immunotherapy and Immune Infiltration in Patients with Clear Cell Renal Cell Carcinoma: A Comprehensive Analysis

On a global scale, renal cell carcinoma (RCC) is the second most common form of cancer and the 10th leading cause of cancer-related deaths. There are about 70% of cases of RCC that are clear cell renal cell carcinomas (ccRCCs). This study explores possible targets for immune therapy in patients with RCC. In the recent years, immunotherapy has been applied to RCC patients. In order to identify genes that are closely associated with immune cells, a weighted gene coexpression network analysis (WGCNA) was conducted. A close association was found between genes involved in MEred and M0 macrophages, M1 macrophages, and M2 macrophages. A prognostic prediction model is subsequently developed by incorporating the OS and the expression level of key genes from the RCC cohort into a univariate COX regression analysis, a multivariate COX regression analysis, and a combined COX regression analysis. We finally discovered that 6 genes are closely associated with the prognosis of RCC patients, including SLC16A12, SLC2A9, IGF2BP2, EMX2, ANK3, and METTL7A. The survival analysis proved the prognostic prediction value of the model. The 1-year, 3-year, and 5-year AUC of ROC curves are 0.759, 0.723, and 0.733, respectively. For clinical ROC curves, the AUC score for risk score, stage, grade, and T stage is 0.759, 0.824, 0722, and 0.736, respectively. The nomogram was constructed for better prognosis prediction of RCC patients. In addition, GSVA and GO enrichment analysis was performed to explore the potential pathways that are closely associated with genes involved in the prognostic prediction model. Accordingly, our study demonstrates that immune cells play a crucial role in RCC infiltration. The development of a prognostic prediction model is a potential new prognostic biomarker and potential immunotherapy target for tumors.

Prognostic and predictive biomarkers for immunotherapy in advanced renal cell carcinoma

The therapeutic algorithm of renal cell carcinoma has been revolutionized by the approval of immunotherapy agents by regulatory agencies. However, objective and durable responses are still not observed in a large number of patients, and prognostic and predictive biomarkers for immunotherapy response are urgently needed. Prognostic models used in clinical practice are based on clinical and laboratory factors (such as hypercalcaemia, neutrophil count or Karnofsky Performance Status), but, with progress in molecular biology and genome sequencing techniques, new renal cell carcinoma molecular features that might improve disease course and outcomes prediction have been highlighted. An implementation of current models is needed to improve the accuracy of prognosis in the immuno-oncology era. Moreover, several potential biomarkers are currently under evaluation, but effective markers to select patients who might benefit from immunotherapy and to guide therapeutic strategies are still far from validation.

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.

Non-SMC condensin I complex subunit H participates in anti-programmed cell death-1 resistance of clear cell renal cell carcinomas

Non-SMC condensin I complex subunit H (NCAPH) is reported to play an important role and be a poor prognostic factor in various cancers. However, the function and regulatory mechanism of NCAPH in clear cell renal cell carcinoma (ccRCC) remain unknown. The roles of NCAPH on ccRCC growth were detected in vitro and in vivo assays. The regulatory mechanism of NCAPH was explored by immunoprecipitation assay, ubiquitination assay, ChIP assay, RIP assay, luciferase reporter assay and RNA pull-down assay. The role of NCAPH in immunoregulation also was explored by flow cytometry, T cell-mediated tumour cell killing assay and immune-competent mouse model. In this research, we displayed that NCAPH was upregulated in ccRCC and patients with elevated NCAPH expression had an undesirable prognosis. Functionally, NCAPH depletion restrained ccRCC growth in vitro and in vivo. The elevated NCAPH was attributed to FOXP3-mediated transcription, FUS-mediated transcription splicing and METTL3-mediated m6A modification. Moreover, YTHDC1 promoted NCAPH mRNA nuclear export, and IGF2BP3 enhanced NCAPH mRNA stability in an m6A-dependent manner. NCAPH increased PD-L1 expression by inhibiting the degradation of β-catenin in ccRCC cells, which further facilitated aerobic glycolysis and immune tolerance of ccRCC. Collectively, our findings display the vital function of NCAPH in ccRCC and uncover that NCAPH may be regarded as a potential therapeutic target to reverse the immune tolerance of ccRCC.

Stem Cells for Cancer Therapy: Translating the Uncertainties and Possibilities of Stem Cell Properties into Opportunities for Effective Cancer Therapy

Cancer recurrence and drug resistance following treatment, as well as metastatic forms of cancer, are trends that are commonly encountered in cancer management. Amidst the growing popularity of personalized medicine and targeted therapy as effective cancer treatment, studies involving the use of stem cells in cancer therapy are gaining ground as promising translational treatment options that are actively pursued by researchers due to their unique tumor-homing activities and anti-cancer properties. Therefore, this review will highlight cancer interactions with commonly studied stem cell types, namely, mesenchymal stroma/stem cells (MSC), induced pluripotent stem cells (iPSC), iPSC-derived MSC (iMSC), and cancer stem cells (CSC). A particular focus will be on the effects of paracrine signaling activities and exosomal miRNA interaction released by MSC and iMSCs within the tumor microenvironment (TME) along with their therapeutic potential as anti-cancer delivery agents. Similarly, the role of exosomal miRNA released by CSCs will be further discussed in the context of its role in cancer recurrence and metastatic spread, which leads to a better understanding of how such exosomal miRNA could be used as potential forms of non-cell-based cancer therapy.

The role of hyaluronan in renal cell carcinoma

Renal cell carcinoma (RCC) is associated with high mortality rates worldwide and survival among RCC patients has not improved significantly in the past few years. A better understanding of the pathogenesis of RCC can enable the development of more effective therapeutic strategies against RCC. Hyaluronan (HA) is a glycosaminoglycan located in the extracellular matrix (ECM) that has several roles in biology, medicine, and physiological processes, such as tissue homeostasis and angiogenesis. Dysregulated HA and its receptors play important roles in fundamental cellular and molecular biology processes such as cell signaling, immune modulation, tumor progression and angiogenesis. There is emerging evidence that alterations in the production of HA regulate RCC development, thereby acting as important biomarkers as well as specific therapeutic targets. Therefore, targeting HA or combining it with other therapies are promising therapeutic strategies. In this Review, we summarize the available data on the role of abnormal regulation of HA and speculate on its potential as a therapeutic target against RCC.

Ovarian cancer-associated immune exhaustion involves SPP1+ T cell and NKT cell, symbolizing more malignant progression

Background

Ovarian cancer (OC) is highly heterogeneous and has a poor prognosis. A better understanding of OC biology could provide more effective therapeutic paradigms for different OC subtypes.

Methods

To reveal the heterogeneity of T cell-associated subclusters in OC, we performed an in-depth analysis of single-cell transcriptional profiles and clinical information of patients with OC. Then, the above analysis results were verified by qPCR and flow cytometry examine.

Results

After screening by threshold, a total of 85,699 cells in 16 ovarian cancer tissue samples were clustered into 25 major cell groups. By performing further clustering of T cell-associated clusters, we annotated a total of 14 T cell subclusters. Then, four distinct single-cell landscapes of exhausted T (Tex) cells were screened, and SPP1 + Tex significantly correlated with NKT cell strength. A large amount of RNA sequencing expression data combining the CIBERSORTx tool were labeled with cell types from our single-cell data. Calculating the relative abundance of cell types revealed that a greater proportion of SPP1 + Tex cells was associated with poor prognosis in a cohort of 371 patients with OC. In addition, we showed that the poor prognosis of patients in the high SPP1 + Tex expression group might be related to the suppression of immune checkpoints. Finally, we verified in vitro that SPP1 expression was significantly higher in ovarian cancer cells than in normal ovarian cells. By flow cytometry, knockdown of SPP1 in ovarian cancer cells could promote tumorigenic apoptosis.

Conclusion

This is the first study to provide a more comprehensive understanding of the heterogeneity and clinical significance of Tex cells in OC, which will contribute to the development of more precise and effective therapies.

Mitochondrial metabolic reprogramming-mediated immunogenic cell death reveals immune and prognostic features of clear cell renal cell carcinoma

Background

Mitochondrial metabolic reprogramming (MMR)-mediated immunogenic cell death (ICD) is closely related to the tumor microenvironment (TME). Our purpose was to reveal the TME characteristics of clear cell renal cell carcinoma (ccRCC) by using them.

Methods

Target genes were obtained by intersecting ccRCC differentially expressed genes (DEGs, tumor VS normal) with MMR and ICD-related genes. For the risk model, univariate COX regression and K-M survival analysis were used to identify genes most associated with overall survival (OS). Differences in the TME, function, tumor mutational load (TMB), and microsatellite instability (MSI) between high and low-risk groups were subsequently compared. Using risk scores and clinical variables, a nomogram was constructed. Predictive performance was evaluated by calibration plots and receiver operating characteristics (ROC).

Results

We screened 140 DEGs, including 12 prognostic genes for the construction of risk models. We found that the immune score, immune cell infiltration abundance, and TMB and MSI scores were higher in the high-risk group. Thus, high-risk populations would benefit more from immunotherapy. We also identified the three genes (CENPA, TIMP1, and MYCN) as potential therapeutic targets, of which MYCN is a novel biomarker. Additionally, the nomogram performed well in both TCGA (1-year AUC=0.862) and E-MTAB-1980 cohorts (1-year AUC=0.909).

Conclusions

Our model and nomogram allow accurate prediction of patients' prognoses and immunotherapy responses.

NUDT1 Could Be a Prognostic Biomarker and Correlated with Immune Infiltration in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor with high morbidity and mortality. As a member of the Nudix hydrolase superfamily, Nudix (nucleoside diphosphate-linked moiety X)-type motif 1 (NUDT1) is closely related to the occurrence and development of cancer. Our study aims to explore the role of NUDT1 in ccRCC and its relationship with immune infiltration.

Methods

The NUDT1 expression matrix and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database. The expression difference of NUDT1 in ccRCC and its relationship with the clinical characteristics were investigated using R software. Kaplan-Meier (K-M) analysis, univariate Cox regression, multivariate Cox regression, receiver operating characteristic (ROC) curve, and nomogram were utilized to evaluate the survival and prognosis of patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to explore the function of differential genes in low- or high-expression group of NUDT1. TCGA dataset and Tumor IMmune Estimation Resource (TIMER) database were utilized to explore the relationship between NUDT1 and immune infiltration. Finally, TCGA dataset was utilized for gene set enrichment analysis (GSEA).

Results

NUDT1 was not only overexpressed in ccRCC but also significantly correlated with clinicopathological features (P < 0.05). K-M survival analysis showed that upregulated NUDT1 was closely related to the decrease of overall survival (OS) and progression-free survival (PFS) in ccRCC patients. Multivariate Cox regression revealed that NUDT1 was a independent prognostic indicator (HR = 1.437, 95% CI: 1.065-1.939, P=0.018). The ROC curve showed that NUDT1 had a certain accuracy in predicting the outcome of ccRCC patiens. Furthermore, a total of 150 coexpressed genes and 1,886 differentially expressed genes (DEGs) were identified. GO/KEGG and GSEA results suggested that NUDT1 and its DEGs were involved in the immune-related pathways. NUDT1 expression was positively correlated with infiltrating levels of regulatory T cells (Tregs), CD8⁺ T cells, follicular helper T cells, and M0 macrophages. In addition, NUDT1 was positively related to immune checkpoints, such as PD-1, LAG3, CTLA4, and CD70, in ccRCC.

Conclusion

NUDT1 plays a key role in the prognosis and immune cell infiltration of ccRCC patients, indicating its potential use as a prognostic biomarker and therapeutic target.

A Cuproptosis-Related lncRNAs Signature Could Accurately Predict Prognosis in Patients with Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancers. As cuproptosis, a new cell death mechanism proposed recently, differs from all other known mechanisms regulating cell death, we aimed to create prognostic markers using cuproptosis-related long non-coding ribonucleic acids (RNAs; lncRNAs) and elucidate the molecular mechanism.

Methods

Data from transcriptome RNA sequencing of ccRCC samples and the relevant clinical data were downloaded from The Cancer Genome Atlas, and Pearson's correlation analysis was implemented to obtain the cuproptosis-related lncRNAs. Then, univariate Cox, multivariate Cox, and Least Absolute Shrinkage and Selection Operator Cox analyses were performed to construct the risk signatures. The cuproptosis-related lncRNAs predictive signature was evaluated with receiver operating characteristic curves and subgroup analysis. Finally, Gene Set Enrichment Analysis (GSEA), single-sample GSEA (ssGSEA), tumor immune microenvironment (TIME), and immune checkpoints were performed to explore the relationship between immunity and patient prognosis.

Results

Five cuproptosis-related lncRNAs, including FOXD2-AS1, LINC00460, AC091212.1, AC007365.1, and AC026401.3, were used to construct the signature. In the training and test sets, low-risk groups (as identified by a risk score lower than the median) demonstrated a better prognosis with an area under the curve for 1-, 3-, and 5-year survival being 0.793, 0.716, and 0.719, respectively. GSEA analysis suggested significant enrichment of the tricarboxylic acid cycle and metabolism-related pathways in the low-risk group. Besides, both ssGSEA and TIME suggested that the high-risk group exhibited more active immune infiltration.

Conclusion

We proposed a cuproptosis-related lncRNAs signature, which had the potential for prognoses and prediction. Our findings might contribute to elucidating potential genomic biomarkers and targets for future therapies in the cuproptosis-related signaling pathways.

A tumor microenvironment preoperative nomogram for prediction of lymph node metastasis in bladder cancer

Background

Growing evidence suggests that tumor metastasis necessitates multi-step microenvironmental regulation. Lymph node metastasis (LNM) influences both pre- and post-operative bladder cancer (BLCA) treatment strategies. Given that current LNM diagnosis methods are still insufficient, we intend to investigate the microenvironmental changes in BLCA with and without LNM and develop a prediction model to confirm LNM status.

Method

"Estimation of Stromal and Immune cells in Malignant Tumors using Expression data" (ESTIMATE) algorithm was used to characterize the tumor microenvironment pattern of TCGA-BLCA cohort, and dimension reduction, feature selection, and StrLNM signature construction were accomplished using least absolute shrinkage and selection operator (LASSO) regression. StrLNM signature was combined with the genomic mutation to establish an LNM nomogram by using multivariable logistic regression. The performance of the nomogram was evaluated in terms of calibration, discrimination, and clinical utility. The testing set from the TCGA-BLCA cohort was used for internal validation. Moreover, three independent cohorts were used for external validation, and BLCA patients from our cohort were also used for further validation.

Results

The StrLNM signature, consisting of 22 selected features, could accurately predict LNM status in the TCGA-BLCA cohort and several independent cohorts. The nomogram performed well in discriminating LNM status, with the area under curve (AUC) of 75.1% and 65.4% in training and testing datasets from the TCGA-BLCA cohort. Furthermore, the StrLNM nomogram demonstrated good calibration with p >0.05 in the Hosmer-Lemeshow goodness of fit test. Decision curve analysis (DCA) revealed that the StrLNM nomogram had a high potential for clinical utility. Additionally, 14 of 22 stably expressed genes were identified by survival analysis and confirmed by qPCR in BLCA patient samples in our cohort.

Conclusion

In summary, we developed a nomogram that included an StrLNM signature and facilitated the preoperative prediction of LNM status in BLCA patients.

Fatty acid metabolism-related signature predicts survival in patients with clear cell renal carcinoma

OBJECTIVE

To explore fatty acid metabolism-related genes and signature, which could predict survival outcomes of clear cell renal carcinoma (ccRCC) patients.

MATERIALS AND METHODS

Transcriptional and survival data of fatty acid genes in ccRCC patients were retrieved from UCSC Xena and Geo DataSets. We first performed Lasso Cox regression analysis to identify survival-related genes. These genes were then used to construct metabolic-related gene signature and risk score. Enrichment analysis and immune component and chemotherapy response prediction were also performed.

RESULTS

In total, five survival-related genes were identified: AGR2, HAO2, IGF2BP1, MCCD1 and OLFM4 (p < 0.05). A series of survival value analyses revealed survival-related signature and risk score, including KM analysis (training set: p < 0.001; test set: p = 0.008). Four clinical indexes (T stage, N stage, M stage, and pathology) were positively correlated with risk score. Time-dependent ROC analysis yielded AUC value of 0.813. Immune landscape analysis revealed that risk score was strongly correlated with TAM score and cytotoxic score. Patients with high risk score and TAM score or cytotoxic score had the shortest survival time. Finally, inhibition of fatty acid metabolism in human ccRCC cell line produced corresponding changes in five genes, consistent with our preliminary results.

CONCLUSION

We identified five survival-related genes (AGR2, HAO2, IGF2BP1, MCCD1 and OLFM4) in ccRCC patients. Our results also indicated that survival-related signature based on these genes is a potential robust prognostic biomarker for ccRCC in patients.

Cell Differentiation Trajectory Predicts Prognosis and Immunotherapeutic Response in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the main type of malignancy in kidney related to glucose metabolism. Primary single cell culture and single cell sequencing are novel research technologies. In this study, we explored the differentiation status of ccRCC cells and its significance in prognosis and immunotherapeutic response through bioinformatics. We characterized distinct differentiation states and differentiation-related genes (DRGs) in ccRCC cells through single cell RNA sequencing (scRNA-seq) analysis. Combined with bulk RNA-seq data, we classified patients into two clusters and found that this classification was closely correlated with patient prognosis and immunotherapeutic responses. Based on machine learning, we identified a prognostic risk model composed of 14 DRGs, including BTG2, CDKN1A, COL6A1, CPM, CYB5D2, FOSB, ID2, ISG15, PLCG2, SECISBP2, SOCS3, TES, ZBTB16, and ZNF704, to predict the survival rate of patients and then constructed a nomogram model integrating clinicopathological characteristics and risk score for clinical practice. In the study of immune checkpoints, we found that patients in the high-risk group had a disposition to get worse prognosis and better effects of immune checkpoint blocking therapies. Finally, we found the expression level of model DRGs was associated with a tumor-immune microenvironment (TIME) pattern and the response of 83 compounds or inhibitors was significantly different in the two risk groups. In a word, our study highlights the potential contribution of cell differentiation in prognosis judgment and immunotherapy response and offers promising therapeutic options for ccRCC patients.

Prognosis Risk Model Based on Necroptosis-Related Signature for Bladder Cancer

Background: Bladder cancer(BLCA) is the ninth most common cancer. In recent years, necroptosis was found to be related to the occurrence and development of tumors. In this study, we aimed to construct a model based on a necroptosis-related signature to evaluate the potential prognostic application in BLCA. Methods: A total of 67 necroptosis-related genes were used to select the ideal cluster numbers, and it was found that there were four necroptosis-related patterns. Then, we compared the gene expression levels among all of the groups and established a necroptosis-related prognostic model. We made the following enrichment analysis of function and built a novel scoring system, the NEC score, to evaluate the state of necroptosis according to the expression level of necroptosis-related genes. Results: A total of 67 necroptosis-related genes were used to define four distinct necroptosis-related patterns: NEC cluster1–4. Each NEC cluster exhibited different patterns of survival and immune infiltration. Based on univariate Cox regression analyses and least absolute shrinkage and selection operator (Lasso) regression, 14 necroptosis-related genes were established to develop the NEC score. Patients were divided into two groups based on the NEC score. Patients in the high NEC score group had a significantly poorer overall survival than those in the low NEC score group. We further confirmed the correlation of clinical characteristics, as well as the immunotherapy outcome, with the NEC score, and confirmed the potential of the NEC score to be an independent prognostic factor. Furthermore, we compared the expression levels of eight potential biomarker genes between our own BLCA tissues and para-carcinoma tissue. Conclusion: We developed a novel NEC score that has a potential prognostic value in BLCA patients and may help personalized immunotherapy counselling.

Comprehensive analysis of a homeobox family gene signature in clear cell renal cell carcinoma with regard to prognosis and immune significance

The homeobox (HOX) family genes have been linked to multiple types of tumors, while their effect on malignant behaviors of clear cell renal cell carcinoma (ccRCC) and clinical significance remains largely unknown. Here, we comprehensively analyzed the expression profiles and prognostic value of HOX genes in ccRCC using datasets from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. We developed a prognostic signature comprising eight HOX genes (HOXB1, HOXA7, HOXB5, HOXD8, HOXD9, HOXB9, HOXA9, and HOXA11) for overall survival prediction in ccRCC and it allowed patients to be subdivided into high- and low-risk groups. Kaplan-Meier survival analysis in all the internal and external cohorts revealed significant difference in clinical outcome of patients in different risk groups, indicating the satisfactory predictive power of the signature. Additionally, we constructed a prognostic nomogram by integrating signature-derived risk score and clinical factors such as gender, age, T and M status, which might be helpful for clinical decision-making and designing tailored management schedules. Immunological analysis revealed that the regulatory T cells (Tregs) infiltrated differently between the two subgroups in both TCGA and ICGC cohorts. ssGSEA method showed that the enrichment scores for mast cells were significantly lower in high-risk group compared with the low-risk group, which was consistent in both TCGA and ICGC cohorts. As for the related immune function, the enrichment scores of APC co-inhibition, para-inflammation, and type II IFN response were consistently lower in high-risk group in both cohorts. Of the eight HOX genes, the mRNA and protein levels of HOXD8 were downregulated in ccRCC than that in normal tissues, and decreased expression of HOXD8 was associated with increased tumor grade and stage, and lymph node metastasis. Survival analysis revealed that lower expression of HOXD8 predicted worse overall survival in ccRCC. In conclusion, our HOX gene-based signature was a favorable indicator to predict the prognosis of ccRCC cases and associated with immune cell infiltration. HOXD8 might be a tumor suppressor gene in ccRCC and a potential predictor of tumor progression.

Expression of basement membrane genes and their prognostic significance in clear cell renal cell carcinoma patients

Background

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor with limited treatment options. A recent study confirmed the involvement of basement membrane (BM) genes in the progression of many cancers. Therefore, we studied the role and prognostic significance of BM genes in ccRCC.

Methods

Co-expression analysis of ccRCC-related information deposited in The Cancer Genome Atlas database and a BM geneset from a recent study was conducted. The differentially expressed BM genes were validated using quantitative reverse-transcription polymerase chain reaction (qRT-PCR). Least absolute shrinkage and selection operator regression and univariate Cox regression analyses were performed to identify a BM gene signature with prognostic significance for ccRCC. Multivariate Cox regression, time-dependent receiver operating characteristic, Kaplan–Meier, and nomogram analyses were implemented to appraise the prognostic ability of the signature and the findings were further verified using a Gene Expression Omnibus dataset. Additionally, immune cell infiltration and and pathway enrichment analyses were performed using ImmuCellAI and Gene Set Enrichment Analysis (GSEA), respectively. Finally, the DSIGDB dataset was used to screen small-molecule therapeutic drugs that may be useful in treating ccRCC patients.

Results

We identified 108 BM genes exhibiting different expression levels compared to that in normal kidney tissues, among which 32 genes had prognostic values. The qRT-PCR analyses confirmed that the expression patterns of four of the ten selected genes were the same as the predicted ones. Additionally, we successfully established and validated a ccRCC patient prediction model based on 16 BM genes and observed that the model function is an independent predictor. GSEA revealed that differentially expressed BM genes mainly displayed significant enrichment of tumor and metabolic signaling cascades. The BM gene signature was also associated with immune cell infiltration and checkpoints. Eight small-molecule drugs may have therapeutic effects on ccRCC patients.

Conclusion

This study explored the function of BM genes in ccRCC for the first time. Reliable prognostic biomarkers that affect the survival of ccRCC patients were determined, and a BM gene-based prognostic model was established.

N6-methyladenosine long non-coding RNAs reveal novel tool to implicate overall survival and immune microenvironment in renal clear cell carcinoma

PURPOSE

This study aimed to investigate whether N6-methyladenosine (m6A)-related long non-coding RNAs (m6ARelncRNAs) could provide novel tools to predict overall survival of renal clear cell carcinoma.

METHODS

The transcriptomic data and clinical information of patients with renal clear cell carcinoma from The Cancer Genome Atlas (TCGA) were analysed. Distinct m6A modification patterns were systemically analysed via consensus clustering analysis. An m6ARelncRNA signature was constructed in the training cohort using the least absolute shrinkage and selection operator (LASSO) analysis and validated in the test cohort. Potential predictive accuracy of the signature was further assessed via Kaplan-Meier survival, univariate and multivariate Cox regression and subgroup analyses. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the role of m6ARelncRNAs in guiding immunotherapy for patients with renal carcinoma.

RESULTS

An m6ARelncRNA signature based on only six lncRNAs was successfully constructed. The high-risk group derived from this signature had significantly poorer overall survival in both training and test cohorts (p < 0.001). Independent prognostic analysis further revealed that m6ARelncRNA risk (p < 0.01) was an independent risk factor for survival outcomes of renal carcinoma. TIDE algorithm revealed that immunotherapy response was poorer in the high-risk group than in the low-risk group. Drug sensitivity analysis based on IC50 revealed that high-risk patients were potentially sensitive to various anti-tumour drugs, including bortezomib, cisplatin, docetaxel, etoposide and sunitinib.

CONCLUSION

m6ARelncRNAs provide novel tools that can be used to predict overall survival and examine the immune microenvironment of renal clear cell carcinoma.

Leucine zipper protein 2 serves as a prognostic biomarker for prostate cancer correlating with immune infiltration and epigenetic regulation

Background

We sought to determine whether leucine zipper protein 2 (LUZP2) could benefit men with prostate cancer (PCa) undergoing radical radiotherapy (RT) or prostatectomy (RP).

Methods

Analysis was done on differentiating expression, clinical prognosis, co-expressed genes, immune infiltration, and epigenetic changes. All of our analyses were done using the R software (version 3.6.3) and the appropriate packages.

Results

In terms of PCa, tumor samples expressed LUZP2 more than normal samples did. In the TCGA database and GSE116918, we found that LUZP2 was the only independent risk factor for PCa. The shared enriched pathways for patients undergoing RP or RT were cell-cell adhesion, regulation of filopodium assembly, and extracellular matrix containing collagen. With the exception of TNFRSF14, we discovered that LUZP2 was negatively correlated with 21 immune checkpoints in PCa patients receiving RT. We found a significant inverse relationship between LUZP2 expression and the tumor immune environment, which included B cells, CD4+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score, in patients receiving RP or RT. Additionally, tumor purity was positively correlated with LUZP2. We found that the drug bortezomib may be susceptible to the LUZP2. DNA methylation was significantly associated with the mRNA expression of LUZP2 in PCa patients from the TCGA database, and LUZP2 methylation was positively correlated with immune cells. The proliferative activity of various PCa cells, which correlated to different stages of this disease, was also found to be significantly reduced by LUZP2 reduction, according to the results of our experimental work.

Conclusions

We proposed a relatively comprehensive understanding of the roles of LUZP2 on PCa from the fresh perspective of senescence.

Potassium channel-related genes are a novel prognostic signature for the tumor microenvironment of renal clear cell carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for 80% of renal cell carcinomas (RCCs), and its morbidity and prognosis are unfavorable. Surgical resection is the first-line treatment for ccRCC, but the oncogenesis of ccRCC is very complex. With the development of high-throughput sequencing technology, it is necessary to analyze the transcriptome to determine more effective treatment methods. The tumor microenvironment (TME) is composed of tumor cells, various immune-infiltrating cells, fibroblasts, many cytokines, and catalysts. It is a complex system with a dynamic balance that plays an essential role in tumor growth, invasion, and metastasis. Previous studies have confirmed that potassium channels can affect the immune system, especially T lymphocytes that require potassium channel activation. However, the effect of potassium channels on the TME of ccRCC remains to be studied. Therefore, this study aims to construct a prognostic signature for ccRCC patients based on potassium ion channel-related genes (PCRGs), assess patient risk scores, and divide patients into high- and low-risk groups based on the cutoff value. In addition, we investigated whether there were differences in immune cell infiltration, immune activator expression, somatic mutations, and chemotherapeutic responses between the high- and low-risk groups. Our results demonstrate that the PCRG signature can accurately assess patient prognosis and the tumor microenvironment and predict chemotherapeutic responses. In summary, the PCRG signature could serve as an auxiliary tool for the precision treatment of ccRCC.

CDCA3 Predicts Poor Prognosis and Affects CD8+ T Cell Infiltration in Renal Cell Carcinoma

Background

Cell division cycle associated 3 (CDCA3) mediates the ubiquitination WEE1 kinase at G2/M phase. However, its contribution to cancer immunity remains uncertain.

Methods

We first evaluated the effect of CDCA3 on the prognosis of patients with renal cell carcinoma (RCC). The results of bioinformatics analysis were verified by the tissue microarray, immunofluorescence (IF) staining, CCK-8 assay, colony formation, cell cycle, and Western blot.

Results

Bioinformatics analysis predicated CDCA3 was an independent predictor of poor prognosis in RCC and was associated with poor TNM stage and grade. CDCA3 was related to the infiltration of CD8⁺ T cells and Tregs. Tissue microarray demonstrated that CDCA3 was strongly associated with poor prognosis and positively relevant to CD8⁺ T infiltration. In vitro experiments showed that exgenomic interference of CDCA3 could attenuate cellular proliferation, arrest cell cycle, and blockade accumulation of CDK4, Bub3, and Cdc20 in mitosis process.

Conclusion

CDCA3 presents as a good biomarker candidate to predict the prognosis of RCC patients and potentiates the immune tumor microenvironment (TME) of RCC.

Upregulation of Metallothionein 1 G (MT1G) Negatively Regulates Ferroptosis in Clear Cell Renal Cell Carcinoma by Reducing Glutathione Consumption

Ferroptosis is characterized by lipid peroxidation and iron accumulation, closely associated with clear cell renal cell carcinoma (ccRCC). It is of great significance for prognostic prediction and treatment of ccRCC to find biomarkers related to ferroptosis. We conducted several bioinformatic analyses using the transcriptome data and clinical information derived from online databases. Firstly, we identified the differentially expressed target genes in ccRCC. Then, t test and COX analysis were used to determine whether it was an independent prognostic factor combined with clinical information. String and gene set enrichment analysis (GSEA) were used to predict its function. Finally, we used ccRCC cells: 769-P and KAKI-1 in vitro to verify the regulation of target genes on cell proliferation apoptosis, iron metabolism, and GSH metabolism, which were used to judge the effect of target genes on ferroptosis. The study showed that MT1G is downregulated in ccRCC tissues compared with normal renal tissues. However, the ccRCC patients with higher expression relatively had higher malignancy and advanced stages. MT1G is an independent adverse factor for the prognosis of ccRCC. The protein interaction network analysis and GSEA showed that MT1G was closely related to GSH metabolism-related proteins (GSR) and lipid oxidation-related proteins (PLA2G2A). Samples with high expression of MT1G were enriched in “glutathione metabolism,” “oxidative phosphorylation,” and “proteasome,” whose function was involved in GSH metabolism and lipid peroxidation. The term associated with the occurrence and development of tumors included “P53 signaling pathway.” Furthermore, in vitro experiments showed that MT1G partially blocked ferroptosis induced by erastin and sorafenib-induced ccRCC cell lines (769-P and CAKI-1). The mechanism may be that MT1G affects ferroptosis by regulating GSH consumption in ccRCC cells. MT1G may be a negative regulator of ferroptosis in ccRCC cells and a biomarker of poor prognosis.