Survival Of ccRCC Patients Research Articles

Tumor Suppressor Properties of Small C-Terminal Domain Phosphatases in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) accounts for 80-90% of kidney cancers worldwide. Small C-terminal domain phosphatases CTDSP1, CTDSP2, and CTDSPL (also known as SCP1, 2, 3) are involved in the regulation of several important pathways associated with carcinogenesis. In various cancer types, these phosphatases may demonstrate either antitumor or oncogenic activity. Tumor-suppressive activity of these phosphatases in kidney cancer has been shown previously, but in general case, the antitumor activity may be dependent on the choice of cell line. In the present work, transfection of the Caki-1 cell line (ccRCC morphologic phenotype) with expression constructs containing the coding regions of these genes resulted in inhibition of cell growth in vitro in the case of CTDSP1 (p < 0.001) and CTDSPL (p < 0.05) but not CTDSP2. The analysis of The Cancer Genome Atlas (TCGA) data showed differential expression of some of CTDSP genes and of their target, RB1. These results were confirmed by quantitative RT-PCR using an independent sample of primary ccRCC tumors (n = 52). We observed CTDSPL downregulation and found a positive correlation of expression for two gene pairs: CTDSP1 and CTDSP2 (rs = 0.76; p < 0.001) and CTDSPL and RB1 (rs = 0.38; p < 0.05). Survival analysis based on TCGA data demonstrated a strong association of lower expression of CTDSP1, CTDSP2, CTDSPL, and RB1 with poor survival of ccRCC patients (p < 0.001). In addition, according to TCGA, CTDSP1, CTDSP2, and RB1 were differently expressed in two subtypes of ccRCC-ccA and ccB, characterized by different survival rates. These results confirm that CTDSP1 and CTDSPL have tumor suppressor properties in ccRCC and reflect their association with the more aggressive ccRCC phenotype.

Abstract A011: Single-cell RNA sequencing reveals a potential renal tumor progenitor in conditional Vhlh knockout mouse model and ccRCC clinical samples

Abstract Introduction: The study aims to identify the progenitor of clear-cell renal cell carcinoma (ccRCC). Background: Inactivation of tumor suppressor gene VHL is the driver for the pathogenesis of ccRCC, the majority subtype of kidney tumors. However, it has also been observed that not all VHL-deficient cells develop into tumors. It is therefore likely that additional characteristics are required for ccRCC formation. Accumulating evidence suggests that tumor formation is initiated by a small pool of cells with tumor-initiating capacity, which are termed tumor progenitor cells (TPCs). Yet, the concept of TPCs in ccRCC has not been fully validated. Methods: LSL-tdTomato reporter was used to trace Vhlh mutant cells in the prior pre-malignant ccRCC mouse model, in which Vhlh was conditionally knocked out (VhlhKO) in renal epithelial cells under the control of Hoxb7-Cre. We also utilized single-cell RNA sequencing (scRNA-seq) to investigate the diversity of Vhlh-deficient renal tubule cells. Results: We show that the tubule phenotypes (traced by the tdTomato reporter) are associated with Vhlh inactivation; the abnormal tdTomato+ cells in Vhlh KO mice exhibit clear-cell phenotype, hyperplasia and multi-layered epithelial cell clusters. scRNA-seq was then used to analyze isolated tdTomato+ cells from Vhlh KO and wild-type (WT) kidneys. The results reveal that inactivation of Vhlh generates an expanded population of principal collecting duct cells characterized by the expression of keratin 19 (Krt19). These Krt19+ cells highly express stem cell-related genes (Wnt4, Sox4, Klf4, Ly6a). They also express multiple tubule segment-specific markers, suggesting the process of dedifferentiation. The expression of Krt19 is strikingly increased and colocalized with a subpopulation of tdTomato+ cells in Vhlh KO kidney, compared with WT where Krt19+ cells are a rare population scattered in tubule epithelia. Colocalization of KRT19 and CAIX in ccRCC samples confirms the ccRCC identity of these KRT19+ cells. High expression of KRT19 is significantly associated with poor overall survival of ccRCC patients. On kidney tissue microarray, KRT19 is strongly expressed in the early-stage peri-tumor tissue with the presence of immune cell infiltration and lipid droplets in the vicinity. In the high-grade ccRCC, KRT19 is expressed in the typical ccRCC cells and in multi-layered adenomas. Notably, Krt19+ progenitor-like cells are found in the fibrotic region with immune cell infiltration in Vhlh mutant kidney. The direct contact between macrophages and Krt19+ cells in mutant kidney, but not in WT, implies that macrophages may be a component in the progenitor-cell niche when Vhlh is conditionally knocked out. Conclusion: We suspect that VHL loss-of-function in the rare tissue progenitor cells may generate a tumor progenitor subset. Elucidation of the role of KRT19 in the context of VHL inactivation and characterization of the stem/progenitor cell niche are of importance as they will shed new lights on early diagnosis and therapeutic intervention. Citation Format: Dinh-Xuan Pham, Chen-Yun Chen, Hieu-Huy Nguyen-Tran, Tien Hsu. Single-cell RNA sequencing reveals a potential renal tumor progenitor in conditional Vhlh knockout mouse model and ccRCC clinical samples [abstract]. In: Proceedings of the AACR Special Conference: Advances in Kidney Cancer Research; 2023 Jun 24-27; Austin, Texas. Philadelphia (PA): AACR; Cancer Res 2023;83(16 Suppl):Abstract nr A011.

Spatial heterogeneity of tumor microenvironment influences the prognosis of clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is an immunologically and histologically diverse tumor. However, how the structural heterogeneity of tumor microenvironment (TME) affects cancer progression and treatment response remains unclear. Hence, we characterized the TME architectures of ccRCC tissues using imaging mass cytometry (IMC) and explored their associations with clinical outcome and therapeutic response.MethodsUsing IMC, we profiled the TME landscape of ccRCC and paracancerous tissue by measuring 17 markers involved in tissue architecture, immune cell and immune activation. In the ccRCC tissue, we identified distinct immune architectures of ccRCC tissue based on the mix score and performed cellular neighborhood (CN) analysis to subdivide TME phenotypes. Moreover, we assessed the relationship between the different TME phenotypes and ccRCC patient survival, clinical features and treatment response.ResultsWe found that ccRCC tissues had higher levels of CD8+ T cells, CD163− macrophages, Treg cells, endothelial cells, and fibroblasts than paracancerous tissues. Immune infiltrates in ccRCC tissues distinctly showed clustered and scattered patterns. Within the clustered pattern, we identified two subtypes with different clinical outcomes based on CN analysis. The TLS-like phenotype had cell communities resembling tertiary lymphoid structures, characterized by cell–cell interactions of CD8+ T cells-B cells and GZMB+CD8+ T cells-B cells, which exhibited anti-tumor features and favorable outcomes, while the Macrophage/T-clustered phenotype with macrophage- or T cell-dominated cell communities had a poor prognosis. Patients with scattered immune architecture could be further divided into scattered-CN-hot and scattered-CN-cold phenotypes based on the presence or absence of immune CNs, but both had a better prognosis than the macrophage/T-clustered phenotype. We further analyzed the relationship between the TME phenotypes and treatment response in five metastatic ccRCC patients treated with sunitinib, and found that all three responders were scattered-CN-hot phenotype while both non-responders were macrophage/T-clustered phenotype.ConclusionOur study revealed the structural heterogeneity of TME in ccRCC and its impact on clinical outcome and personalized treatment. These findings highlight the potential of IMC and CN analysis for characterizing TME structural units in cancer research.

LINC01480 as a Prognostic Biomarker Associated With Proliferation, Migration, and Invasion of Clear Cell Renal Cell Carcinoma.

The present study aimed to identify key long noncoding RNAs (lncRNAs) involved in survival and metastasis of clear cell renal cell carcinoma (ccRCC). A systemic screening for genes with differential expression in ccRCC was performed using publicly available databases. Cox regression analysis was used to identify lncRNAs associated with survival. A competing endogenous RNAs (ceRNA) regulation network of metastasis-related lncRNAs was constructed and hub lncRNAs were identified. Functional and pathway enrichment analyses were performed to investigate the role of lncRNA in ccRCC. Cell Counting Kit-8 and Transwell assays were used to determine the levels of cell proliferation, migration, and invasion. A total of 732 lncRNAs were found to be differentially expressed between ccRCC tumors and healthy samples. Among them, 139 lncRNAs were differentially expressed between metastasis and non-metastasis ccRCC samples and 75 lncRNAs were associated with overall survival and curated metastasis-related genes. Notably, LINC01480 was identified as the hub lncRNA involved in regulation of ccRCC metastasis. Clinically, LINC01480 may act as an independent factor for poor overall survival of ccRCC patients (log-rank p<0.05). Reverse transcription-quantitative PCR analysis validated that LINC01480 was significantly up-regulated in ccRCC compared to paired normal samples (n=20). Moreover, LINC01480 silencing inhibited the proliferation, migration, and invasion of ccRCC cells in vitro. Gene set enrichment analysis showed that high LINC01480 expression may promote ccRCC metastasis through enhancing immunodeficiency and amino acid metabolism. LINC01480 may act as a novel biomarker for overall prognosis in ccRCC and exhibit potential as a therapeutic target for the treatment of metastatic ccRCC.

Establishing a prognostic model based on five starvation-related long non-coding RNAs for clear cell renal cell carcinoma.

Starvation-induced tumor microenvironment significantly alters genetic profiles including long non-coding RNAs (lncRNAs), further regulating the malignant biological characteristics (invasion and migration) of clear cell renal cell carcinoma (ccRCC). Transcriptome RNA-sequencing data of 539 ccRCC tumors and 72 normal tissues were acquired from the TCGA and paired clinical samples of 50 ccRCC patients. In vitro experiments, such as qPCR, migration and invasion assays were applied to reveal the clinical relevance of LINC-PINT, AC108449.2 and AC007637.1. 170 lncRNAs were verified as starvation-related lncRNAs (SR-LncRs), of which 25 lncRNAs were associated with overall survival in ccRCC patients. Furthermore, a starvation-related risk score model (SRSM) was built based on the expression levels of LINC-PINT, AC108449.2, AC009120.2, AC008702.2 and AC007637.1. ccRCC patients with high level of LINC-PINT expression were divided into high-risk group and led to higher mortality, but AC108449.2 and AC007637.1 were contrary. Analogously, LINC-PINT was highly expressed in ccRCC cell lines and tumor tissues, especially in patients with advanced stage, T-stage and M-stage, while AC108449.2 and AC007637.1 showed the opposite results. In addition, the increased levels of AC108449.2 and AC007637.1 were significantly correlated with grade. Silencing LINC-PINT reduced the invasion and migration characteristics of ccRCC cells. SiR-AC108449.2 and siR-AC007637.1 enhanced the ability of invasion and migration in ccRCC cells. In this study, we find the clinical significance of LINC-PINT, AC108449.2 and AC007637.1 in predicting the prognosis of ccRCC patients and verify their correlation with various clinical parameters. These findings provide an advisable risk score model for ccRCC clinical decision-making.

Recent Advances in the Management of Clear Cell Renal Cell Carcinoma: Novel Biomarkers and Targeted Therapies.

Renal cell carcinoma (RCC) belongs to a heterogenous cancer group arising from renal tubular epithelial cells. Among RCC subtypes, clear cell renal cell carcinoma (ccRCC) is the most common variant, characterized by high aggressiveness, invasiveness and metastatic potential, features that lead to poor prognosis and high mortality rate. In addition, diagnosis of kidney cancer is incidental in the majority of cases, and this results in a late diagnosis, when the stage of the disease is advanced and the tumor has already metastasized. Furthermore, ccRCC treatment is complicated by its strong resistance to chemo- and radiotherapy. Therefore, there is active ongoing research focused on identifying novel biomarkers which could be useful for assessing a better prognosis, as well as new molecules which could be used for targeted therapy. In this light, several novel targeted therapies have been shown to be effective in prolonging the overall survival of ccRCC patients. Thus, the aim of this review is to analyze the actual state-of-the-art on ccRCC diagnosis, prognosis and therapeutic options, while also reporting the recent advances in novel biomarker discoveries, which could be exploited for a better prognosis or for targeted therapy.

Integrative transcriptome and proteome analyses of clear cell renal cell carcinoma develop a prognostic classifier associated with thrombus

Clear cell renal cell carcinoma (ccRCC) with venous tumor thrombus (VTT) is associated with poor prognosis. Our integrative analyses of transcriptome and proteome reveal distinctive molecular features of ccRCC with VTT, and yield the development of a prognostic classifier to facilitate ccRCC molecular subtyping and treatment. The RNA sequencing and mass spectrometry were performed in normal-tumor-thrombus tissue triples of five ccRCC patients. Statistical analysis, GO and KEGG enrichment analysis, and protein–protein interaction network construction were used to interpret the transcriptomic and proteomic data. A six-gene-based classifier was developed to predict patients’ survival using Cox regression, which was validated in an independent cohort. Transcriptomic analysis identified 1131 tumorigenesis-associated differentially expressed genes (DEGs) and 856 invasion-associated DEGs. Overexpression of transcription factor EGR2 in VTT indicated its important role in tumor invasion. Furthermore, proteomic analysis showed 597 tumorigenesis-associated differentially expressed proteins (DEPs) and 452 invasion-associated DEPs. The invasion-associated DEPs showed unique enrichment in DNA replication, lysine degradation, and PPAR signaling pathway. Integration of transcriptome and proteome reveals 142 tumorigenesis-associated proteins and 84 invasion-associated proteins displaying changes consistent with corresponding genes in transcriptomic profiling. Based on their different expression patterns among normal-tumor-thrombus triples, RAB25 and GGT5 were supposed to play a consistent role in both tumorigenesis and invasion processes, while SHMT2 and CADM4 might play the opposite roles in tumorigenesis and thrombus invasion. A prognostic classifier consisting of six DEGs (DEPTOR, DPEP1, NAT8, PLOD2, SLC7A5, SUSD2) performed satisfactorily in predicting survival of ccRCC patients (HR = 4.41, P < 0.001), which was further validated in an independent cohort of 40 cases (HR = 5.52, P = 0.026). Our study revealed the transcriptomic and proteomic profiles of ccRCC patients with VTT, and identified the distinctive molecular features associated with VTT. The six-gene-based prognostic classifier developed by integrative analyses may facilitate ccRCC molecular subtyping and treatment.

ARC-20: A phase 1 dose-escalation and dose-expansion study to investigate the safety, tolerability, and pharmacology of HIF-2α inhibitor AB521 monotherapy in patients with clear cell renal cell carcinoma and other solid tumors.

TPS4602 Background: Renal cell carcinoma (RCC) is one of the 10 most common neoplasms in the United States. Patients with clear cell RCC (ccRCC) commonly have inactivation of the von Hippel-Lindau tumor suppressor protein, resulting in accumulation of hypoxia-inducible factor alpha (HIFα) subunits (especially HIF-2α) and leading to tumor growth. AB521, an orally bioavailable small molecule inhibitor of HIF-2α, potently inhibits transcription of HIF-2α-dependent genes in cell lines and preclinical species. Single doses of AB521 (3 mg, 10 mg, 30 mg, and 100 mg) and multiple ascending doses of AB521 (15 mg, 30 mg, and 50 mg) have been previously studied in healthy volunteers. ARC-20 is a first-in-patient study to investigate the safety, tolerability, and pharmacology of AB521 monotherapy in patients with solid tumors and evaluate the clinical activity of AB521 in previously treated patients with ccRCC. Methods: ARC-20 (NCT05536141) is a phase 1, multicenter, open-label study. Eligible patients are adults with solid tumors with ≥1 measurable lesion(s) per Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 and an Eastern Cooperative Oncology Group performance status of 0 or 1. ARC-20 has 2 stages, dose escalation and dose expansion. The dose escalation stage uses a standard 3+3 design and includes patients with pathologically confirmed solid tumors and no other available treatment options. Patients will be sequentially assigned to 1 of 4 cohorts evaluating doses of AB521 ranging from 20 to 200 mg/day. Intermediate dose cohorts may be evaluated based on emergent safety or pharmacologic data. The dose expansion stage will evaluate approximately 30 patients with histologically confirmed ccRCC who have received previous treatment for metastasis with an anti-programmed cell death protein 1 (anti-PD-1) therapy and a vascular endothelial growth factor (VEGF)-targeting tyrosine kinase inhibitor (TKI). Patients previously treated with a HIF-2α-targeting therapy are not eligible for dose expansion. Results from the dose-escalation stage will inform the dose and schedule used during dose expansion. Primary endpoints are the incidence of dose-limiting toxicity and adverse events. Secondary endpoints include objective response rate, AB521 plasma concentration, and AB521 pharmacokinetics. Exploratory endpoints include changes in expression of erythropoietin and other HIF-2α driven biomarkers in blood and tumor tissues, along with progression-free survival for ccRCC patients during dose expansion. Clinical trial information: NCT05536141 .

Single-Cell RNA-Seq Analysis Reveals Ferroptosis in the Tumor Microenvironment of Clear Cell Renal Cell Carcinoma.

In this study, we investigated the role of ferroptosis in the tumor microenvironment (TME) of clear cell renal cell carcinoma (ccRCC), the leading cause of renal cancer-related death. We analyzed single-cell data from seven ccRCC cases to determine cell types most correlated with ferroptosis and performed pseudotime analysis on three myeloid subtypes. We identified 16 immune-related ferroptosis genes (IRFGs) by analyzing differentially expressed genes between cell subgroups and between high and low immune infiltration groups in the TCGA-KIRC dataset and the FerrDb V2 database. Using univariate and multivariate Cox regression, we identified two independent prognostic genes, AMN and PDK4, and constructed an IRFG score model immune-related ferroptosis genes risk score (IRFGRs) to evaluate its prognostic value in ccRCC. The IRFGRs demonstrated excellent and stable performance for predicting ccRCC patient survival in both the TCGA training set and the ArrayExpress validation set, with an AUC range of 0.690-0.754, outperforming other commonly used clinicopathological indicators. Our findings enhance the understanding of TME infiltration with ferroptosis and identify immune-mediated ferroptosis genes associated with prognosis in ccRCC.

Development of an Immune Prognostic Model for Clear Cell Renal Cell Carcinoma Based on Tumor Microenvironment.

Immune infiltration remains at a high level in clear cell renal cell carcinoma (ccRCC). It has been confirmed that immune cell infiltration in tumor microenvironment (TME) is intimately bound up with the progression and the clinical outcome of ccRCC. The prognostic model, developed based on different immune subtypes of ccRCC, has a predictive value in patients' prognosis. RNA sequencing data, somatic mutation data of ccRCC and clinical information were acquired from the cancer genome atlas (TCGA) database. The key immune-related genes (IRGs) were selected and by univariate Cox, LASSO, and multivariate Cox regression analyses. Then the ccRCC prognostic model was developed. The applicability of this model was verified in the independent dataset GSE29609. Thirteen IRGs including CCL7, ATP6V1C2, ATP2B3, ELAVL2, SLC22A8, DPP6, EREG, SERPINA7, PAGE2B, ADCYAP1, ZNF560, MUC20, and ANKRD30A were finally selected and a 13-IRGs prognostic model was developed. Survival analysis demonstrated that when compared with the low-risk group, patients in the high-risk group had a lower overall survival (p<0.05). AUC values based on the 13-IRGs prognostic model used to predict 3- and 5-year survival of ccRCC patients were greater than 0.70. And risk score was an independent prognostic factor (p<0.001). In addition, nomogram could accurately predict ccRCC patient's prognosis. This 13-IRGs model can effectively evaluate the prognosis of ccRCC patients, and also provide guidance for the treatment and prognosis of ccRCC patients.

A novel prognostic signature for clear cell renal cell carcinoma constructed using necroptosis-related miRNAs

BackgroundThis work aims to analyze the relationship between necroptosis-related microRNAs (miRNAs) and the prognosis of clear cell renal cell carcinoma (ccRCC).MethodsThe miRNAs expression profiles of ccRCC and normal renal tissues from The Cancer Genome Atlas (TCGA) database were used to construct a matrix of the 13 necroptosis-related miRNAs. Cox regression analysis was used to construct a signature to predict the overall survival of ccRCC patients. The genes targeted by the necroptosis-related miRNAs in the prognostic signature were predicted using miRNA databases. Gene Ontology (Go) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to investigate the genes targeted by the necroptosis-related miRNAs. The expression levels of selected miRNAs in 15 paired samples (of ccRCC tissues and adjacent normal renal tissues) were investigated using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR).ResultsSix necroptosis-related miRNAs were found to differentially expressed between ccRCC and normal renal tissues. A prognostic signature consisting of miR-223-3p, miR-200a-5p, and miR-500a-3p was constructed using Cox regression analysis and risk scores were calculated. Multivariate Cox regression analysis showed that the hazard ratio was 2.0315 (1.2627–3.2685, P = 0.0035), indicating that the risk score of the signature was an independent risk factor. The receiver operating characteristic (ROC) curve showed that the signature has a favorable predictive capacity and the Kaplan-Meier survival analysis indicated that ccRCC patients with higher risk scores had worse prognoses (P < 0.001). The results of the RT-qPCR verified that all three miRNAs used in the signature were differentially expressed between ccRCC and normal tissues (P < 0.05).ConclusionThe three necroptosis-related-miRNAs used in this study could be a valuable signature for the prognosis of ccRCC patients. Necroptosis-related miRNAs should be further explored as prognostic indicators for ccRCC.

SERPINE1 and its co-expressed genes are associated with the progression of clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma(ccRCC) is a frequently occurring malignant tumor of the urinary system. Despite extensive research, the regulatory mechanisms underlying the pathogenesis and progression of ccRCC remain largely unknown.MethodsWe downloaded 5 ccRCC expression profiles from the Gene Expression Omnibus (GEO) database and obtained the list of differentially expressed genes (DEGs). Using String and Cytoscape tools, we determined the hub genes of ccRCC, and then analyzed their relationship with ccRCC patient survival. Ultimately, we identified SERPINE1 as a prognostic factor in ccRCC. Meanwhile, we confirmed the role of SERPINE1 in 786-O cells by cell transfection and in vitro experiments.ResultsOur analysis yielded a total of 258 differentially expressed genes, comprising 105 down-regulated genes and 153 up-regulated genes. Survival analysis of SERPINE1 expression in The Cancer Genome Atlas (TCGA) confirmed its association with the increase of tumor grade, lymph node metastasis, and tumor stage, as well as with shorter survival. Furthermore, we found that SERPINE1 expression levels were associated with CD8 + T cells, CD4 + T cells, B cells, macrophages, neutrophils, and dendritic cells. Cell experiments showed that knockdown SERPINE1 expression could inhibit the proliferation, migration and invasion of ccRCC cells. Among the co-expressed genes with the highest correlation, ITGA5, SLC2A3, SLC2A14, SHC1, CEBPB, and ADA were overexpressed and associated with shorter overall survival (OS) in ccRCC.ConclusionsIn this study, we identified hub genes that are strongly related to ccRCC, and highlights the potential utility of overexpressed SERPINE1 and its co-expressed genes could be used as prognostic and diagnostic biomarkers in ccRCC.

A New Signature That Predicts Progression-Free Survival of Clear Cell Renal Cell Carcinoma with Anti-PD-1 Therapy.

Immunotherapy has greatly improved the survival time and quality of life of patients with renal cell carcinoma, but the benefits are limited to a small portion of patients. There are too few new biomarkers that can be used to identify molecular subtypes of renal clear cell carcinoma and predict survival time with anti-PD-1 treatment. Single-cell RNA data of clear cell renal cell carcinoma (ccRCC) treated with anti-PD-1 were obtained from public databases, then 27,707 high-quality CD4 + T and CD8 + T cells were obtained for subsequent analysis. Firstly, genes set variation analysis and CellChat algorithm were used to explore potential molecular pathway differences and intercellular communication between the responder and non-responder groups. Additionally, differentially expressed genes (DEGs) between the responder and non-responder groups were obtained using the "edgeR" package, and ccRCC samples from TCGA-KIRC (n = 533) and ICGA-KIRC (n = 91) were analyzed by the unsupervised clustering algorithm to recognize molecular subtypes with different immune characteristics. Finally, using univariate Cox analysis, least absolute shrinkage and selection operator (Lasso) regression, and multivariate Cox regression, the prognosis model of immunotherapy was established and verified to predict the progression-free survival of ccRCC patients treated with anti-PD-1. At the single cell level, there are different signal pathways and cell communication between the immunotherapy responder and non-responder groups. In addition, our research also confirms that the expression level of PDCD1/PD-1 is not an effective marker for predicting the response to immune checkpoint inhibitors (ICIs). The new prognostic immune signature (PIS) enabled the classification of ccRCC patients with anti-PD-1 therapy into high- and low-risk groups, and the progression-free survival times (PFS) and immunotherapy responses were significantly different between these two groups. In the training group, the area under the ROC curve (AUC) for predicting 1-, 2- and 3-year progression-free survival was 0.940 (95% CI: 0.894-0.985), 0.981 (95% CI: 0.960-1.000), and 0.969 (95% CI: 0.937-1.000), respectively. Validation sets confirm the robustness of the signature. This study revealed the heterogeneity between the anti-PD-1 responder and non-responder groups from different angles and established a robust PIS to predict the progression-free survival of ccRCC patients receiving immune checkpoint inhibitors.

FAK-mediated phosphorylation at Y464 regulates p85β nuclear translocation to promote tumorigenesis of ccRCC by repressing RB1 expression

PI3K regulatory subunit p85s normally stabilizes and regulates catalytic subunit p110s in the cytoplasm. Recent studies show that p110-free p85s in the nucleus plays important roles in biological processes. However, the mechanisms by which p85s translocate into the nucleus remain elusive. Here, we describe the mechanism by which p85β translocates into the nucleus to promote ccRCC tumorigenesis. Phosphorylation of p85β at the Y464 by FAK facilitates its nuclear translocation in the kidney through enhancing the binding of p85β to KPNA1. PIK3R2/p85β is highly expressed in ccRCC samples and associated with overall survival of ccRCC patients. Nuclear but not cytoplasmic p85β performs oncogenic functions by repressing RB1 expression and regulating the G1/S cell cycle transition. Nuclear p85β represses RB1 expression by stabilizing histone methyltransferase EZH1/EZH2 proteins. Last, the FAK inhibitor defactinib significantly suppresses the tumor growth of ccRCC with high p85β Y464 levels.

Deciphering the Role of Melatonin-Related Signatures in Tumor Immunity and the Prognosis of Clear Cell Renal Cell Carcinoma.

Adopting multiomics data from TCGA and other public datasets, we analysed the expression, mutation, and prognostic evaluation in multiple cancers. ccRCC patients were categorized into two subgroups by an unsupervised cluster algorithm: melatonin-pattern cancer subtype 1 (MPCS1) and subtype 2 (MPCS2). We then explored the immune microenvironment, immune therapy response, and tumor metabolic pathways between the two subtypes. The clinical characteristics, genomic mutation landscape, and molecular inhibitor response were further investigated. Finally, a melatonin regulator-related prognostic model was constructed to predict patient prognosis in ccRCC. We found that melatonin regulators were dysregulated depending on distinct cancer types, which were associated with genomic variation. The two subtypes indicated different clinical characteristics and biological processes in ccRCC. MPCS2, an aggressive subtype, led an advanced clinical stage and poorer survival of ccRCC patients. The activated oncogenic signaling pathway and metabolic signatures were responsible for cancer progression in the MPCS2 subtype. The MPCS2 subgroup suggested a higher tumor mutational burden and immune dysfunction state, resulting in a lower response to immunotherapy. The copy number variations of MPCS2 were significantly more frequent than those of MPCS1. In addition, the two subgroups exhibited distinct drug responsiveness, with MPCS2 being less responsive to multiple drugs. Finally, we established a subtype biomarker-based prognostic risk model that exhibited satisfactory performance in ccRCC patients. Melatonin regulator-related features could remodel functional pathways and the tumor immune microenvironment through genomic mutations and pathway regulation. Melatonin regulator-associated molecular subtypes enhance the understanding of the molecular characteristics of renal cancer and can guide clinical treatment. Activating the melatonergic system axis may improve the effect of immunotherapy for ccRCC.

Identification of Differentially Methylated Genes Associated with Clear Cell Renal Cell Carcinoma and Their Prognostic Values.

Renal cell carcinoma (RCC) is a heterogeneous disease comprising histologically defined subtypes among which clear cell RCC (ccRCC) accounts for 70% of all RCC cases. DNA methylation constitutes a main part of the molecular mechanism of cancer evolution and prognosis. In this study, we aim to identify differentially methylated genes related to ccRCC and their prognostic values. The GSE168845 dataset was downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between ccRCC tissues and paired tumor-free kidney tissues. DEGs were submitted to public databases for functional and pathway enrichment analysis, protein-protein interaction (PPI) analysis, promoter methylation analysis, and survival correlation analysis. In the setting of |log2FC| ≥ 2 and adjusted p value <0.05 during differential expression analysis of the GSE168845 dataset, 1659 DEGs between ccRCC tissues and paired tumor-free kidney tissues were sorted out. The most enriched pathways were "T cell activation" and "cytokine-cytokine receptor interaction." After PPI analysis, 22 hub genes related to ccRCC stood out, among which CD4, PTPRC, ITGB2, TYROBP, BIRC5, and ITGAM exhibited higher methylation levels, and BUB1B, CENPF, KIF2C, and MELK exhibited lower methylation levels in ccRCC tissues compared with paired tumor-free kidney tissues. Among these differentially methylated genes, TYROBP, BIRC5, BUB1B, CENPF, and MELK were significantly correlated with the survival of ccRCC patients (p < 0.001). Our study indicates the DNA methylation of TYROBP, BIRC5, BUB1B, CENPF, and MELK may be promising results for the prognosis of ccRCC.

Development of a Novel KCNN4-Related ceRNA Network and Prognostic Model for Renal Clear Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) accounts for more than 80% of renal cell carcinomas. Yet, it has not been fully understood about the derivation and progression of the tumor, as well as the long-term benefits from multimodality therapy. Therefore, reliable and applicable molecular markers are urgently needed for the prediction of diagnosis and prognosis of ccRCC patients. Genetic and clinical information of 533 ccRCC patients from The Cancer Genome Atlas database was collected for comprehensive bioinformatic analyses. UALCAN was used to detect gene expression in paired tumor samples. Two data sets from Gene Expression Omnibus database were analyzed to identify differentially expressed genes (DEGs), and Gene Set Enrichment Analysis was applied for the functional enrichment of DEGs. Tumor Immune Single Cell Hub and Tumor IMmune Estimation Resource databases were separately used for analyses of single-immune cell and immune cell infiltration. Encyclopedia of RNA Interactomes database was explored to predict targeted microRNAs (miRNAs) and corresponding long non-coding RNAs (lncRNAs). Cox regression analysis was performed for the construction of risk signature and prognosis model. Finally, quantitative real-time polymerase chain reaction and western blot were conducted for KCNN4 expression detection in cell lines and clinical samples. Small interfering RNA was employed to knock down KCNN4, and corresponding functional experiments were conducted on ccRCC cells as well. KCNN4 showed elevated expression in tumors and prominent clinical correlation in ccRCC. In total, 41 KCNN4-related genes were enriched, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed they were intimately related to immune-related signaling pathways. Spearman's analysis revealed the significantly positive correlation of KCNN4 with immune cell infiltration. By integrating hub miRNA-let-7e-5p and four critical lncRNA, a competitive endogenous RNA network-based risk signature was constructed. The prognosis model derived from it showed considerable predictive value for survival of ccRCC patients. Finally, in vitro experiments confirmed the remarkable tumor-promoting role of KCNN4 in ccRCC cells. KCNN4 significantly affected the immune status of tumor microenvironment and immunotherapy elements, through which it promoted tumor progression in ccRCC, and it could be a potential biomarker for prognosis and immunotherapy effects of ccRCC patients.

SF3B4 promotes Twist1 expression and clear cell renal cell carcinoma progression by facilitating the export of KLF 16 mRNA from the nucleus to the cytoplasm

Splicing factor 3B subunit 4 (SF3B4) plays important functional roles not only in pre-mRNA splicing, but also in the regulation of transcription, translation, and cell signaling, and its dysregulation contributes to various diseases including Nager syndrome and tumorigenesis. However, the role of SF3B4 and underlying mechanisms in clear cell renal cell carcinoma (ccRCC) remain obscure. In the present study, we found that the expression of SF3B4 was significantly elevated in ccRCC tissues and negatively correlated with the overall survival of ccRCC patients. Upregulation of SF3B4 promotes migration and invasion of ccRCC cells in vitro and in vivo. The promoting effect of SF3B4 on cell migration and invasion is mediated by Twist1, a key transcription factor to mediate EMT. Interestingly, SF3B4, a component of the pre-mRNA spliceosome, is able to promote KLF16 expression by facilitating the transport of KLF16 mRNA into the cytoplasm. Mechanistically, SF3B4 promotes the export of KLF16 mRNA from the nucleus to the cytoplasm and thus enhances KLF16 expression, and in turn elevated KLF16 directly binds to the Twist1 promoter to activate its transcription, leading to EMT and ccRCC progression. Our findings provide evidence that the SF3B4-KLF16-Twist1 axis plays important functional roles in the development and progression of ccRCC, and manipulating this pathway may be a novel therapeutic target for the treatment of ccRCC.

Analysis of the expression and clinical significance of PGM5 in clear cell renal cell carcinoma based on the TCGA database

To analyze the expression characteristics and clinical relevance of PGM5 in clear cell renal cell carcinoma based on the TCGA database. The differential expression of PGM5 and the association between PGM5 and clinical diagnosis and prognosis in clear cell renal cell carcinoma were analyzed based on the TCGA, GEIPIA, and Linkedomics databases. The R language was used to process and analyze data. The genes related to the expression of PGM5 were analyzed with the WebGestalt tool. The analysis based on the TCGA showed that the expression level of PGM5 mRNA in ccRCC tissues was lower than that in normal renal tissues. The Linkedomics database analysis showed that PGM5 mRNA is different expressed in the pathological Stage of the clear cell takes cell carcinoma (P < 0.05). The expression level tended to be downregulated with the happens of the pathological stage. PGM5 mRNA was differentially expressed in different T, N, and M stages (P<0.05). Survival analysis showed that PGM5 expression level was significantly associated with overall survival and disease-free survival in ccRCC patients. The diagnostic accuracy showed that the PGM5 expression had excellent diagnostic value by ROC curve analysis for distinguishing between ccRCC tissues and normal renal tissues. In addition, the expression level of PGM5 was positively correlated with that of PAPB, and PARM1, respectively, and negatively correlated with those of PMM2, NME1, and PDCD5. The enrichment analysis of genes associated with PGM5 expression was positively correlated with DNA replication and cell cycle and negatively correlated with those of cGMP-PKG and Rap1 signaling pathways. The expression level of PGM5 mRNA is associated with the pathological stage, T stage, N stage, M stage, and prognosis in patients with clear cell renal cell carcinoma. Therefore, PGM5 has the potential to become a diagnostic marker, as well as a therapeutic target of clear cell renal cell carcinoma.

Long Noncoding RNA MAGI2-AS3 Represses Cell Progression in Clear Cell Renal Cell Carcinoma by Modulating the miR-629-5p/PRDM16 Axis.

The objective of this study was to determine the regulatory mechanism of MAGI2-AS3 in clear cell renal cell carcinoma (ccRCC), thereby supplying a new insight for ccRCC treatment. Expression data in TCGA-KIRC were obtained. Target gene lncRNA for research was determined using expression analysis and clinical analysis. lncRNA's downstream regulatory miRNA and mRNA were predicted by bioinformatics databases. ccRCC cell malignant phenotypes were detected via CCK-8, colony formation, Transwell migration, and invasion assays. The targeting relationship between genes was assessed through dual-luciferase reporter gene analysis. Kaplan-Meier (K-M) analysis was carried out to verify the effect of MAGI2-AS3, miR-629-5p, and PRDM16 on the survival rate of ccRCC patients. MAGI2-AS3 expression in ccRCC tissue and cells was shown to be markedly decreased and its expression to continuously decline with tumor progression. MAGI2-AS3 suppresses ccRCC proliferation and migration. Dual-luciferase assay showed that MAGI2-AS3 binds miR-629-5p and that miR-629-5p binds PRDM16. In addition, functional experiments showed that MAGI2-AS3 facilitates PRDM16 expression by repressing miR-629-5p expression, thereby suppressing ccRCC cell aggression. K-M analysis showed that upregulation of either MAGI2-AS3 or PRDM16 significantly improves ccRCC patient survival, while upregulation of miR-629-5p has no significant impact. MAGI2-AS3 sponges miR-629-5p to modulate PRDM16 to mediate ccRCC development. Meanwhile, the MAGI2-AS3/miR-629-5p/PRDM16 axis, as a regulatory pathway of ccRCC progression, may be a possible therapeutic target and prognostic indicator of ccRCC.