Challenges and opportunities in the proteomic characterization of clear cell renal cell carcinoma (ccRCC): A critical step towards the personalized care of renal cancers

Arginine methylation modulates tumor fate and prognosis in clear cell renal cell carcinoma

BACKGROUND

Arginine methylation, a key post-translational modification, plays a pivotal role in regulating various cellular processes and has been implicated in cancer progression. However, the potential of arginine methylation-related genes as prognostic markers in clear cell renal cell carcinoma (ccRCC) remains underexplored.

METHODS

We utilized public transcriptomic datasets from TCGA, E-MTAB-1980 and ICGC, for model construction and validation. Single-cell RNA sequencing datasets were employed to evaluate gene expression patterns at the cellular level. Consensus clustering, KM survival analysis, and GSVA were applied to identify molecular subtypes and related pathways. Univariate and multivariate Cox regression analyses were applied to develop an arginine methylation-related signature (AMS). Immune profiling, mutation landscape, and drug sensitivity prediction were also employed to explore the model's association with clinical features, immune infiltration, mutation burden, and therapeutic responses.

RESULTS

The AMS demonstrated robust prognostic performance, with consistent validation across external cohorts. High-risk patients exhibited significantly worse survival, elevated TMB, and an immunosuppressive tumor microenvironment characterized by increased infiltration of regulatory immune cells. Single-cell RNA sequencing revealed key prognostic genes expressed predominantly in cancer and immune cells, supporting their role in tumor progression and immune interactions.

CONCLUSION

The arginine methylation-based prognostic model provides a reliable framework for survival risk stratification in ccRCC and holds promise for guiding personalized therapeutic strategies. Future research should emphasize clinical validation of this model and explore its potential role in optimizing immunotherapy and targeted treatment strategies for ccRCC.

Preoperative prediction of WHO/ISUP grade of ccRCC using intratumoral and peritumoral habitat imaging: multicenter study

OBJECTIVES

The World Health Organization/International Society of Urological Pathology (WHO/ISUP) grading of clear cell renal cell carcinoma (ccRCC) is crucial for prognosis and treatment planning. This study aims to predict the grade using intratumoral and peritumoral subregional CT radiomics analysis for better clinical interventions.

METHODS

Data from two hospitals included 513 ccRCC patients, who were divided into training (70%), validation (30%), and an external validation set (testing) of 67 patients. Using ITK-SNAP, two radiologists annotated tumor regions of interest (ROI) and extended surrounding areas by 1 mm, 3 mm, and 5 mm. The K-means clustering algorithm divided the tumor region into three sub-regions, and the Least Absolute Shrinkage and Selection Operator (LASSO) regression identified the most predictive features. Various machine learning models were established, including radiomics models, peritumoral radiomics models, models based on intratumoral heterogeneity (ITH) score, clinical models, and comprehensive models. Predictive ability was evaluated using receiver operating characteristic (ROC) curves, area under the curve (AUC) values, DeLong tests, calibration curves, and decision curves.

RESULTS

The combined model showed strong predictive power with an AUC of 0.852 (95% CI: 0.725-0.979) on the test data, outperforming individual models. The ITH score model was highly precise, with AUCs of 0.891 (95% CI: 0.854-0.927) in training, 0.877 (95% CI: 0.814-0.941) in validation, and 0.847 (95% CI: 0.725-0.969) in testing, proving its superior predictive ability across datasets.

CONCLUSION

A comprehensive model combining Habitat, Peri1mm, and salient clinical features was significantly more accurate in predicting ccRCC pathologic grading.

KEY POINTS

Question: Characterize tumor heterogeneity to non-invasively predict WHO/ISUP pathological grading preoperatively.

FINDINGS

An integrated model combining subregion characterization, peritumoral characteristics, and clinical features can predict ccRCC grade preoperatively.

CLINICAL RELEVANCE

Subregion tumor characterization outperforms the single-entity approach. The integrated model, compared with the radiomics model, boosts grading and prognostic accuracy for more targeted clinical actions.

High expression of ARPC1B promotes the proliferation and apoptosis of clear cell renal cell carcinoma cells, leading to a poor prognosis

BACKGROUND

ARPC1B has been identified as a key regulator of malignant biological behavior in various tumors. However, its specific role in clear cell renal cell carcinoma (ccRCC) remains poorly understood. This study aims to evaluate the influence of ARPC1B on the prognosis and disease progression in ccRCC patients.

METHODS

Multi-omics data and clinical information from public databases were analyzed to determine the associations between ARPC1B and prognosis, clinical features, immune microenvironment, and drug sensitivity in ccRCC. Co-expression and gene set enrichment analyses were conducted to elucidate the potential role of ARPC1B in ccRCC pathogenesis. Functional assays, including RT-qPCR, CCK8 assays, colony formation assays, immunofluorescence, immunohistochemistry, and xenograft tumor formation in nude mice, were performed to assess ARPC1B's impact on cell proliferation and apoptosis. Flow cytometry and Western blotting were further employed to investigate the underlying molecular mechanisms of ARPC1B in ccRCC.

RESULTS

ARPC1B expression was significantly elevated in ccRCC and associated with an unfavorable prognosis. Both independent and meta-analyses confirmed that ARPC1B is an independent prognostic risk factor in ccRCC. Furthermore, ARPC1B expression significantly correlated with the immune microenvironment and drug sensitivity. In vitro, experiments demonstrated that ARPC1B knockdown suppressed ccRCC cell proliferation and induced apoptosis through the BAX-Bcl-2/c-caspase3/c-PARP axis, which was further validated by in vivo studies.

CONCLUSION

ARPC1B overexpression is associated with poor prognosis, altered immune status, and drug sensitivity in ccRCC. Furthermore, ARPC1B promotes the malignant behavior of ccRCC cells and holds potential as a prognostic biomarker and therapeutic target for ccRCC.

FOXP3 as a prognostic marker and therapeutic target in immunogenic cell death modulation for clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) remains a challenging cancer type due to its resistance to standard treatments. Immunogenic cell death (ICD) has the potential to activate anti-tumor immunity, presenting a promising avenue for ccRCC therapies.

METHODS

We analyzed data from GSE29609, TCGA-KIRC, and GSE159115 to identify ICD-related prognostic genes in ccRCC. By applying consensus clustering, patients were categorized based on ICD modification patterns, and an ICD signature (ICDS) model was developed using a PCA approach. Functional studies were conducted with FOXP3 knockdown in ccRCC cell lines to explore its impact on cell behavior.

RESULTS

Eleven ICD-related genes were identified as key prognostic indicators in ccRCC, with high ICDS linked to worse survival outcomes. High ICDS also correlated with increased levels of immune-suppressive cells within the tumor microenvironment. FOXP3 was highlighted as a critical gene influencing ICD, where its knockdown significantly reduced ccRCC cell proliferation and migration, underscoring its role in tumor progression.

CONCLUSIONS

This study establishes FOXP3 as a pivotal factor in ICD regulation and ccRCC progression. Targeting FOXP3 and other ICD pathways could enhance treatment efficacy in ccRCC, providing a foundation for ICD-based therapeutic strategies. Evaluating ICD patterns in ccRCC may guide patient-specific interventions, paving the way for improved management of this aggressive cancer.

Identifying ADME-related gene signature for immune landscape and prognosis in KIRC by single-cell and spatial transcriptome analysis

Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of kidney cancer. Although multiple therapeutic agents have been proven effective in KIRC, their clinical application has been hindered by a lack of reliable biomarkers. This study focused on the prognostic value and function of drug absorption, distribution, metabolism, and excretion- (ADME-) related genes (ARGs) in KIRC to enhance personalized therapy. The critical role of ARGs in KIRC microenvironment was confirmed by single cell RNA-seq analysis and spatial transcriptome sequencing analysis for the first time. Then, an ADME-related prognostic signature (ARPS) was developed by the bulk RNA-seq analysis. The ARPS, created through Cox regression, LASSO, and stepAIC analyses, identified eight ARGs that stratified patients into high-risk and low-risk groups. High-risk patients had significantly poorer overall survival. Multivariate analysis confirmed the independent predictive ability of ARPS, and an ARPS-based nomogram was constructed for clinical application. Gene ontology and KEGG pathway analyses revealed immune-related functions and pathways enriched in these groups, with low-risk patients showing better responses to immunotherapy. Finally, the expression of ARGs was validated by qRT-PCR and Western blotting experiments. These findings underscore the prognostic significance of ARPS in KIRC and its potential application in guiding personalized treatment strategies.

ALKBH5 promotes malignant proliferation of renal clear cell carcinoma by activating the MAPK pathway through binding to HNRNPDL

It is well established that ALKBH5 plays a crucial role in the malignant progression of various types of tumors. However, its role in clear cell renal cell carcinoma (ccRCC) and the underlying regulatory mechanisms remain unclear. In this study, we employed a range of techniques, including protein blotting, real-time quantitative PCR, silver staining, mass spectrometry, co-immunoprecipitation (Co-IP), GST-pull down, and immunofluorescence, to investigate the functions of ALKBH5 in ccRCC and elucidate the specific mechanisms involved. Our results demonstrated that ALKBH5 expression was significantly upregulated in ccRCC. In vitro experiments revealed that ALKBH5 promoted tumor proliferation, invasion, migration, and stemness. In vivo, ALKBH5 was shown to enhance tumor growth and lung metastasis. Mechanistically, our studies suggest that ALKBH5 accelerates the malignant progression of ccRCC by binding to heterogeneous nuclear ribonucleoprotein D-like (HNRNPDL), facilitating the nuclear translocation of MEK, ERK, and p38, and activating downstream targets such as c-Myc and PCNA.

Circ_0061140 Potentiates Clear Cell Renal Cell Carcinoma Progression Via the MicroRNA-126-5p/ADAM9 Axis

Circular RNAs (circRNAs) function as new cancer biomarkers, but the role of circ_0061140 remains unknown in clear cell renal cell carcinoma (ccRCC). Therefore, we aimed to validate the functions of circ_0061140 in ccRCC and its potential as a prognostic biomarker. At first, circ_0061140 expression in ccRCC tissues and cells was detected, and circ_0061140 was upregulated in ccRCC tissues (p < 0.0001) and cells (p < 0.0001). Patients with high expression of circ_0061140 had a worse prognosis (p < 0.05). Then, siRNA against circ_0061140 was transfected into Caki-1 and UT14 cells to explore its roles in the biological functions of ccRCC cells, and suppressing roles of downregulated circ_0061140 were observed in the cell growth of Caki-1 and UT14 cells (p < 0.01). Next, circ_0061140 was found to be a sponge of miR-126-5p, and ADAM9 was determined to be a target of miR-126-5p. Finally, functional rescue experiments were conducted to observe their roles in ccRCC cell growth. It was suggested that suppressed miR-126-5p or overexpressed ADAM9 induced cell proliferation and restricted cell apoptosis in ccRCC cells based on si-circ_0061140 (p < 0.01). Altogether, this study highlights that circ_0061140 plays an oncogenic role in ccRCC through modulation of the miR-126-5p/ADAM9 axis.

Multi-omics analysis of Prolyl 3-hydroxylase 1 as a prognostic biomarker for immune infiltration in ccRCC

The formation of human collagen requires the presence of Prolyl 3-hydroxylase 1 (P3H1), but the regulatory mechanism of P3H1 remained insufficiently understood. Our study aimed to identify the role of P3H1 in clear cell renal cell carcinoma (ccRCC). P3H1 expression in ccRCC was validated using multiple databases and in vitro experiments. We performed a correlation analysis of P3H1 with drug sensitivity, immune checkpoints, and immune cell infiltration using transcriptome and single-cell sequencing. Drawing upon the Encyclopedia of RNA Interactomes database, we selected P3H1 as the focal point of our investigation, meticulously uncovering the intricate network of microRNAs and lncRNAs that potentially orchestrate ceRNA mechanisms. This study employs a multidimensional approach integrating vitro assays and multi-omics bioinformatics analyses to investigate P3H1's impact on ccRCC prognosis, immune modulation, immune checkpoints, ceRNA regulatory network, drug sensitivity, and therapeutic responses, aiming to uncover new insights into its therapeutic potential and inform future clinical strategies.

Comparative Proteomics of ccRCC Cell Lines to Identify Kidney Cancer Progression Factors

BACKGROUND/AIM

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer, accounting for approximately 75% of kidney cancers. The objective of this study was to identify novel progression markers for ccRCC based on proteomics, with the goal of stage determination and early diagnosis of kidney cancer patients.

MATERIALS AND METHODS

We performed quantitative global proteomics coupled with Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and high-resolution tandem mass spectrometry on kidney-derived cells, including HEK-293, 786-O (primary ccRCC), and Caki-1 (metastatic ccRCC) cells, to investigate the novel progression factors of ccRCC.

RESULTS

In this study, a total of 1,106 proteins were quantified. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted for differentially expressed proteins (DEPs) that were increased in ccRCC cells compared to HEK-293 cells. Ultimately, 99 DEPs including 75 up-regulated and 24 down-regulated proteins, that were significantly altered in both ccRCC cells, were identified. Among DEPs, vimentin was identified as the most significantly changed protein. Its increased expression in ccRCC was verified through immunoblotting in ccRCC cell lines and immunohistochemistry in kidney tumors.

CONCLUSION

From the global proteomics data detected in ccRCC, we propose 99 DEPs including vimentin as progression factors.

Exosomal microRNA as a key regulator of PI3K/AKT pathways in human tumors

MicroRNAs (miRNAs) are conserved non-protein-coding RNAs that are naturally present in organisms and can control gene expression by suppressing the translation of mRNA or causing the degradation of mRNA. MicroRNAs are highly concentrated in the PI3K/AKT pathway, and abnormal activation of the PI3K/AKT pathway plays a role in cancer progression. The AKT/PI3K pathway is critical for cellular functions and can be stimulated by cytokines and in normal situations. It is involved in regulating various intracellular signal transduction, including development, differentiation, transcriptional regulation, protein, and synthesis. There is a growing body of evidence indicating that miRNAs, which are abundant in exosomes released by different cells, can control cellular biological activities via modulating the PI3K/AKT pathway, hence influencing cancer progression and drug resistance. This article provides an overview of the latest research progress regarding the function and medical use of the PI3K/AKT pathway and exosomal miRNA/AKT/PI3K axis in the behaviors of cancer cells.

CircSP3 encodes SP3-461aa to promote ccRCC progression via stabilizing MYH9 and activating the PI3K-Akt signaling pathway

Clear cell renal cell carcinoma (ccRCC) is a primary kidney cancer with high aggressive phenotype and extremely poor prognosis. Accumulating evidence suggests that circular RNAs (circRNAs) play pivotal roles in the occurrence and development of various human cancers. However, the expression, clinical significance and regulatory role of circRNAs in ccRCC remain largely unclear. Here we report that circSP3 to be increased in tissues from ccRCC patients and ccRCC cells, and to positively correlate with ccRCC malignant features. Knockdown of circSP3 inhibits proliferation, triggers apoptosis, and reduces migration and invasion in different ccRCC cells in vitro. Correspondingly, circSP3 overexpression Promote ccRCC tumorigenicity in a mouse xenograft model. Mechanistically, circSP3 could bind with the ribosome to initiate the translation process to encodes a novel 461-amino acid peptide referred to as SP3-461aa, which protects the MYH9 protein from proteasomal degradation. SP3-461aa played a pivotal role in mediating the oncogenic effects of circSP3 by interacting with the MYH9 protein and activating the PI3K-Akt signaling pathway. These findings suggested that circSP3 plays an important role in ccRCC development and could be a potential biomarker for the treatment and prognosis of ccRCC.

Niraparib for the treatment of metastatic ccRCC in a patient with CDK12 and RAD51C mutations: a case report

Background

Niraparib, a poly ADP-ribose polymerase inhibitors (PARPi), has been widely applied in the intervention of epithelial ovarian, fallopian tube, or primary peritoneal cancer. Nevertheless, as of the present moment, there are limited instances demonstrating favorable outcomes stemming from niraparib therapy in patients with clear cell renal cell carcinoma (ccRCC).

Case presentation

Here, we report a case of a 50-year-old patient with ccRCC who subsequently developed distant metastasis. The patient received monotherapy with pazopanib and combination therapy with axitinib and tislelizumab, demonstrating limited efficacy. Liquid biopsy revealed missense mutations in the CDK12 and RAD51C of the homologous recombination repair (HRR) pathway, suggesting potential sensitivity to PARPi. Following niraparib treatment, the patient's condition improved, with no significant side effects.

Conclusion

In summary, patients with ccRCC harboring HRR pathway gene mutation may potentially benefit from niraparib. This will present more options for ccRCC patients with limited response to conventional treatments.

Diagnostic, predictive and prognostic molecular biomarkers in clear cell renal cell carcinoma: A retrospective study

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive subtype of kidney cancer. Many patients are diagnosed at advanced stages, making early detection crucial. Unfortunately, there are currently no noninvasive tests for ccRCC, emphasizing the need for new biomarkers. Additionally, ccRCC often develops resistance to treatments like radiotherapy and chemotherapy. Identifying biomarkers that predict treatment outcomes is vital for personalized care. The integration of artificial intelligence (AI), multi-omics analysis, and computational biology holds promise in bolstering detection precision and resilience, opening avenues for future investigations. The amalgamation of radiogenomics and biomaterial-basedimmunomodulation signifies a revolutionary breakthrough in diagnostic medicine. This review summarizes existing literature and highlights emerging biomarkers that enhance diagnostic, predictive, and prognostic capabilities for ccRCC, setting the stage for future clinical research.

Elevated CDC45 Expression Predicts Poorer Overall Survival Prognoses and Worse Immune Responses for Kidney Renal Clear Cell Carcinoma via Single-Cell and Bulk RNA-Sequencing

The main objective of this paper is to analyze the prognostic and immunological value of CDC45 in kidney renal clear cell carcinoma (KIRC) using single-cell and bulk RNA-sequencing approaches. The expression of CDC45 in KIRC was evaluated by the HPA database, the TCGA-KIRC dataset and verified by PCR analysis and single-cell RNA-sequencing. The ability of CDC45 to independently predict prognosis in KIRC was confirmed by univariate/multivariate regression analysis. Gene set enrichment analysis (GSEA) was employed to explore CDC45-related pathways in KIRC. In addition, Relationships between CDC45 and immunity were also examined. Elevated CDC45 expression in KIRC was demonstrated at mRNA and protein levels. The results of the correlation analysis showed that as CDC45 expression increased, so did the histological grade, clinical stage, and TNM stage of the patients (p < 0.05). Univariate/multivariate regression analysis suggested CDC45 as an independent prognostic factor for KIRC. Seven pathways related to CDC45 were screened through GSEA. Meanwhile, we found that CDC45 was correlated with tumor mutational burden (TMB) and microsatellite instability (MSI) but not tumor neoantigen burden (TNB). Regarding immunity, CDC45 exhibited correlations with the tumor microenvironment, immune cell infiltration, and immune checkpoints. Besides, low CDC45 expression was shown to be associated with a better response to immunotherapy. Single-cell RNA-sequencing revealed that CDC45 was differently expressed in T cells (p < 0.05). CDC45 showed potential as a prognostic biomarker and therapeutic target for KIRC. Meanwhile, the CDC45 low expression group was more sensitive to immunotherapy.

Integration of bioinformatics analysis to identify possible hub genes and important pathways associated with clear cell renal cell carcinoma

INTRODUCTION

One of the most fatal urological malignancies is clear cell renal cell carcinoma (ccRCC), yet little is known about its pathophysiology or prognosis. This study is aimed at obtaining some novel biomarkers with diagnostic and prognostic meaning and may find out potential therapeutic targets for ccRCC.

MATERIAL AND METHODS

Using three publically accessible ccRCC gene expression profiles acquired from the Gene Expression Omnibus database, differentially expressed genes (DEG) were discovered and function enrichment analyses were carried out. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted by using the DAVID tool and a protein-protein interaction (PPI) network was constructed and visualized by Cytoscape. Then we identified 10 hub genes using the cytohubba plugin of Cytoscape based on degree score. The mRNA and protein expression of hub genes was analyzed by GEPIA and Human Protein Atlas (HPA) database. Then, prognosis analysis of hub genes was conducted using GEPIA 3.0 which consists of data from The Cancer Genome Atlas (TCGA).

RESULTS

We discovered 293 DEG which is highly enriched in several biological processes connected to immune-regulation and pathways linked to tumors, including HIF-1, PI3K-AKT, and metabolic pathways. In particular, C1QA, C1QB, FCER1G, and TYROBP were related to advanced clinical stage, high pathological grade, and poor survival in patients with ccRCC.

CONCLUSIONS

Further molecular biological studies are required to confirm the role of the putative biomarkers in human ccRCC. Our work highlighted the hub genes and pathways involved in the progression of ccRCC.

The relationship between the network of non-coding RNAs-molecular targets and N6-methyladenosine modification in tumors of urinary system

N6-methyladenosine (m6A) methylation, a prevalent eukaryotic post-transcriptional modification, is involved in multiple biological functions, including mediating variable splicing, RNA maturation, transcription, and nuclear export, and also is vital for regulating RNA translation, stability, and cytoplasmic degradation. For example, m6A methylation can regulate pre-miRNA expression by affecting both splicing and maturation. Non-coding RNA (ncRNA), which includes microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), does not encode proteins but has powerful impacts on transcription and translation. Conversely, ncRNAs may impact m6A methylation by affecting the expression of m6A regulators, including miRNAs targeting mRNA of m6A regulators, or lncRNAs, and circRNAs, acting as scaffolds to regulate transcription of m6A regulatory factors. Dysregulation of m6A methylation is common in urinary tumors, and the regulatory role of ncRNAs is also important for these malignancies. This article provides a systematic review of the role and mechanisms of action of m6A methylation and ncRNAs in urinary tumors.

A novel prognostic predictor of immune microenvironment and therapeutic response in clear cell renal cell carcinoma based on angiogenesis-immune-related gene signature

Background

Clear cell renal cell carcinoma (ccRCC), the most common type of RCC, typically produces no symptoms initially. Patients with ccRCC are at increased risk of developing advanced metastatic disease due to the absence of dependable and effective prognostic biomarkers. Therefore, it is particularly urgent to find optimal stratification of patients with ccRCC to distinguish the clinical benefits of different malignant degrees. Angiogenesis has a profound impact on the malignant behavior of renal cancer cells, and anti-angiogenic drugs have been applied to metastatic renal cancer patients. Moreover, immune function dysregulation is also a significant factor in tumorigenesis. We aim to construct a predictive model that combines angiogenesis and immune-related genes (AIRGs) to aid clinicians in predicting ccRCC prognosis.

Methods

We gathered transcriptome and clinicopathology data from two datasets, the E-MTAB-1980 dataset and the Cancer Genome Atlas (TCGA). We utilized consensus clustering to find new molecular subgroups. A predictive model for the prognosis of angiogenesis-immune-associated genes (AIRGs) was conducted by the lasso and multivariate Cox regression analysis. The signature's predictive ability was then tested in different datasets. Meticulous scrutiny and comprehensive assessment were undertaken, both internally and externally, to establish the prognostic model. Analyses of immunogenomics were carried out to examine the relationship between risk scores and clinical/immune features, including immune cell infiltration, genomic alterations, and response to targeted and immunotherapy therapy.

Results

Our prognostic signature, comprising 4 AIRGs, stood as an independent prognostic factor for ccRCC, while risk scores emerged as a novel indicator for forecasting overall survival. Risk scores exhibited significant associations with various immunophenotypic factors, such as oncogenic pathways, antitumor response, different immune cell infiltration, antitumor immunity, and response to targeted and immunotherapy therapy.

Conclusions

AIRGs-based prognostic prediction model could effectively predict immunotherapy responses and survival outcomes of ccRCC.

Identification of key genes and signalling pathways in clear cell renal cell carcinoma: An integrated bioinformatics approach

BACKGROUND

Clear cell Renal Cell Carcinoma (ccRCC) is one of the most prevalent types of kidney cancer. Unravelling the genes responsible for driving cellular changes and the transformation of cells in ccRCC pathogenesis is a complex process.

OBJECTIVE

In this study, twelve microarray ccRCC datasets were chosen from the gene expression omnibus (GEO) database and subjected to integrated analysis.

METHODS

Through GEO2R analysis, 179 common differentially expressed genes (DEGs) were identified among the datasets. The common DEGs were subjected to functional enrichment analysis using ToppFun followed by construction of protein-protein interaction network (PPIN) using Cytoscape. Clusters within the DEGs PPIN were identified using the Molecular Complex Detection (MCODE) Cytoscape plugin. To identify the hub genes, the centrality parameters degree, betweenness, and closeness scores were calculated for each DEGs in the PPIN. Additionally, Gene Expression Profiling Interactive Analysis (GEPIA) was utilized to validate the relative expression levels of hub genes in the normal and ccRCC tissues.

RESULTS

The common DEGs were highly enriched in Hypoxia-inducible factor (HIF) signalling and metabolic reprogramming pathways. VEGFA, CAV1, LOX, CCND1, PLG, EGF, SLC2A1, and ENO2 were identified as hub genes.

CONCLUSION

Among 8 hub genes, only the expression levels of VEGFA, LOX, CCND1, and EGF showed a unique expression pattern exclusively in ccRCC on compared to other type of cancers.

Network Analysis and Basic Experiments on the Inhibition of Renal Cancer Proliferation and Migration by Alpinetin through PI3K/AKT/ mTOR Pathway

BACKGROUND

Alpinetin, a natural flavonoid, has been shown to have anticancer effects on many tumors. This study investigated the antitumor effect of alpinetin on renal clear cell carcinoma (ccRCC).

METHODS

Network Pharmacology analysis was carried out on the targets and molecular mechanisms of alpinetin treating ccRCC. The Annexin V PE/7-AAD kit was used to detect apoptosis. Flow cytometry and Cell Counting Kit-8 (CCK-8) were used to detect cell proliferation and cycle. A 24-well transwell chamber and the ibidi scratch insertion performed cell migration analysis. The protein expression of the target molecule was detected by Western blotting. Nude mouse tumorigenesis assays were used to determine the in vivo antitumor effects of alpinetin.

RESULTS

The network pharmacology revealed that GAPDH, HRAS, SRC, EGFR, and AKT1 are the main targets of alpinetin in treating ccRCC, with the PI3K/AKT signaling pathway being the main pathway of action. We found that alpinetin could significantly inhibit the proliferation and migration of ccRCC cells by inducing apoptosis. In addition, alpinetin also inhibited the cycle progression of ccRCC cells by blocking them in the G1 phase. Furthermore, in vivo and in vitro, alpinetin could inhibit the activation of an important pathway involved in the proliferation and migration of ccRCC cells, namely the PI3K/Akt pathway.

CONCLUSION

Alpinetin can inhibit the growth of ccRCC cells by inhibiting the activation of the PI3K/Akt pathway and can be a potential anti-cancer drug for ccRCC.

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.

OSM May Serve as a Biomarker of Poor Prognosis in Clear Cell Renal Cell Carcinoma and Promote Tumor Cell Invasion and Migration

Background

Currently, the role of oncostatin M (OSM) in clear cell renal cell carcinoma (ccRCC) has not been investigated. This study will explore the impact of OSM on ccRCC expression, prognosis, and cell function.

Materials and Methods

In this study, we used The Cancer Genome Atlas (TCGA) database to evaluate OSM expression characteristics, pathogenic factor distribution, and prognostic aspects in ccRCC. We also combined this analysis with qRT-PCR to verify OSM mRNA expression levels at the tissue level. Then, the effects of OSM on the proliferation, invasion, and migration abilities of ccRCC cells were explored through CCK8, Transwell, Western blotting, and immunofluorescence experiments. Finally, the oncogenic mechanisms associated with OSM in ccRCC were explored through signaling pathway enrichment and single-cell analysis.

Results

The results demonstrated that OSM was significantly more expressed in ccRCC than in normal tissues. According to the survival analysis, OSM in ccRCC was considerably worse in the group with high expression than in the group with low expression. Also, the univariate and multivariate Cox analyses of clinical characteristics show that OSM in ccRCC may be able to predict a poor prognosis on its own as a biomarker. In vitro cellular experiments demonstrated that high OSM expression had no discernible impact on ccRCC cell proliferation compared to the control group, but it did promote tumor cell invasion and migration. Signaling pathways and single-cell analysis revealed that OSM might promote ccRCC invasion and migration through M2 macrophages.

Conclusion

In conclusion, OSM may serve as an independent poor prognostic biomarker in ccRCC and promote tumor cell invasion and migration. This discovery is expected to provide a new therapeutic target for patients with recurrent and metastatic ccRCC.

Unveiling the multi-target compounds of Rhazya stricta: Discovery and inhibition of novel target genes for the treatment of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a prevalent kidney malignancy with a pressing need for innovative therapeutic strategies. In this context, emerging research has focused on exploring the medicinal potential of plants such as Rhazya stricta. Nevertheless, the complex molecular mechanisms underlying its potential therapeutic efficacy remain largely elusive. Our study employed an integrative approach comprising data mining,network pharmacology,tissue cell type analysis, and molecular modelling approaches to identify potent phytochemicals from R. stricta, with potential relevance for ccRCC treatments. Initially, we collected data on R. stricta's phytochemical from public databases. Subsequently, we integrated this information with differentially expressed genes (DEGs) in ccRCC, which were derived from microarray datasets(GSE16441,GSE66270, and GSE76351). We identified potential intersections between R. stricta and ccRCC targets, which enabled us to construct a compound-genes-pathway network using Cytoscape software. This helped illuminate R. stricta's multi-target pharmacological effects on ccRCC. Moreover, tissue cell type analysis added another layer of insight into the cellular specificity of potential therapeutic targets in the kidney. Through further Kaplan-Meier survival analysis, we pinpointed MMP9,ACE,ERBB2, and HSP90AA1 as prospective diagnostic and prognostic biomarkers for ccRCC. Notably, our study underscores the potential of R. stricta derived compounds-namely quebrachamine,corynan-17-ol, stemmadenine,strictanol,rhazinilam, and rhazimolare-to impede ccRCC progression by modulating the activity of MMP9,ACE,ERBB2, and HSP90AA1 genes. Further, molecular docking and dynamic simulations confirmed the plausible binding affinities of these compounds. Despite these promising findings, we recognize the need for comprehensive in vivo and in vitro studies to further investigate the pharmacokinetics and biosafety profiles of these compounds.

Construction of the metabolic reprogramming-associated gene signature for clear cell renal cell carcinoma prognosis prediction

BACKGROUND

Metabolism reprogramming is a hallmark that associates tumor growth, metastasis, progressive, and poor prognosis. However, the metabolism-related molecular patterns and mechanism in clear cell renal cell carcinoma (ccRCC) remain unclear. Herein, the purpose of this study was to identify metabolism-related molecular pattern and to investigate the characteristics and prognostic values of the metabolism-related clustering.

METHODS

We comprehensively analyzed the differentially expressed genes (DEGs), and metabolism-related genes (MAGs) in ccRCC based on the TCGA database. Consensus clustering was used to construct a metabolism-related molecular pattern. Then, the biological function, molecular characteristics, Estimate/immune/stomal scores, immune cell infiltration, response to immunotherapy, and chemotherapy were analyzed. We also identified the DEGs between subclusters and constructed a poor signature and risk model based on LASSO regression cox analysis and univariable and multivariable cox regression analyses. Then, a predictive nomogram was constructed and validated by calibration curves.

RESULTS

A total of 1942 DEGs (1004 upregulated and 838 downregulated) between ccRCC tumor and normal samples were identified, and 254 MRGs were screened out from those DEGs. Then, 526 ccRCC patients were divided into two subclusters. The 7 metabolism-related pathways enriched in cluster 2. And cluster 2 with high Estimate/immune/stomal scores and poor survival. While, cluster 1 with higher immune cell infiltrating, expression of the immune checkpoint, IFN, HLA, immune activation-related genes, response to anti-CTLA4 treatment, and chemotherapy. Moreover, we identified 295 DEGs between two metabolism-related subclusters and constructed a 15-gene signature and 9 risk factors. Then, a risk score was calculated and the patients into high- and low-risk groups in TCGA-KIRC and E-MTAB-1980 datasets. And the prediction viability of the risk score was validated by ROC curves. Finally, the clinicopathological characteristics (age and stage), risk score, and molecular clustering, were identified as independent prognostic variables, and were used to construct a nomogram for 1-, 3-, 5-year overall survival predicting. The calibration curves were used to verify the performance of the predicted ability of the nomogram.

CONCLUSION

Our finding identified two metabolism-related molecular subclusters for ccRCC, which facilitates the estimation of response to immunotherapy and chemotherapy, and prognosis after treatment.

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

BACKGROUND

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).

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

HOOK1 Inhibits the Progression of Renal Cell Carcinoma via TGF-β and TNFSF13B/VEGF-A Axis

Accumulating evidence shows HOOK1 disordered in human malignancies. However, the clinicopathological and biological significance of HOOK1 in renal cell carcinoma (RCC) remains rarely studied. In this study, the authors demonstrate that HOOK1 is downregulated in RCC samples with predicted poorer clinical prognosis. Mechanistically, HOOK1 inhibits tumor growth and metastasis via canonical TGF-β/ALK5/p-Smad3 and non-canonical TGF-β/MEK/ERK/c-Myc pathway. At the same time, HOOK1 inhibits RCC angiogenesis and sunitinib resistance by promoting degradation of TNFSF13B through the ubiquitin-proteasome pathway. In addition, HOOK1 is transcriptionally regulated by nuclear factor E2F3 in VHL dependent manner. Notably, an agonist of HOOK1, meletin, is screened and it shows antitumor activity more effectively when combined with sunitinib or nivolumab than it is used alone. The findings reveal a pivotal role of HOOK1 in anti-cancer treatment, and identify a novel therapeutic strategy for renal cell carcinoma.

Integrated glycoproteomic characterization of clear cell renal cell carcinoma

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

Integrated Metabolomic and Transcriptomic Analysis of Modified Nucleosides for Biomarker Discovery in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for ~75% of kidney cancers. The biallelic inactivation of the von Hippel-Lindau tumor suppressor gene (VHL) is the truncal driver mutation of most cases of ccRCC. Cancer cells are metabolically reprogrammed and excrete modified nucleosides in larger amounts due to their increased RNA turnover. Modified nucleosides occur in RNAs and cannot be recycled by salvage pathways. Their potential as biomarkers has been demonstrated for breast or pancreatic cancer. To assess their suitability as biomarkers in ccRCC, we used an established murine ccRCC model, harboring Vhl, Trp53 and Rb1 (VPR) knockouts. Cell culture media of this ccRCC model and primary murine proximal tubular epithelial cells (PECs) were investigated by HPLC coupled to triple-quadrupole mass spectrometry using multiple-reaction monitoring. VPR cell lines were significantly distinguishable from PEC cell lines and excreted higher amounts of modified nucleosides such as pseudouridine, 5-methylcytidine or 2'-O-methylcytidine. The method's reliability was confirmed in serum-starved VPR cells. RNA-sequencing revealed the upregulation of specific enzymes responsible for the formation of those modified nucleosides in the ccRCC model. These enzymes included Nsun2, Nsun5, Pus1, Pus7, Naf1 and Fbl. In this study, we identified potential biomarkers for ccRCC for validation in clinical trials.

Micall2 Is Responsible for the Malignancy of Clear Cell Renal Cell Carcinoma

Background

There lacks a sufficient research on the tumorigenesis of clear cell renal cell carcinoma (ccRCC), causing that the prognosis of ccRCC was not effectively improved. Micall2 contributes to the malignancy of cancer. Moreover, Micall2 is considered a typical cell mobility-promoting factor. However, the relationship between Micall2 and ccRCC malignancy is unknown.

Methods

In this study, we first investigated the expression patterns of Micall2 in ccRCC tissues and cell lines. Next, we explored the in vitro and in vivo roles of Micall2 in ccRCC tumorigenesis based on ccRCC cell lines with different Micall2 expression and gene manipulation assays.

Results

Our study showed that ccRCC tissues and cell lines expressed higher level of Micall2 than paracancerous tissues and normal renal tubular epithelial cell, and Micall2 expression was overexpressed on cancerous tissue with significant metastasis and enlargement. Among three ccRCC cell lines, the expression of Micall2 was the highest in 786-O cells and the lowest in CAKI-1 cells. Moreover, 786-O cells showed the highest malignancy in vitro and in vivo (including proliferation, migration, invasion, reduced E-cadherin expression and tumorigenicity of nude mice in vivo), while CAKI-1 cells showed the contrary results. Furthermore, the upregulated Micall2 by Gene overexpression promoted the proliferation, migration and invasion of ccRCC cells while the downregulated Micall2 by Gene silencing showed the opposite effect.

Conclusion

Micall2, as a pro-tumorigenic gene marker of ccRCC, contributes the malignancy of ccRCC.

DNA methylation-mediated low expression of ZNF582 promotes the proliferation, migration, and invasion of clear cell renal cell carcinoma

OBJECTIVE

The methylation of DNA promoter region mediates the low expression of many tumor suppressor genes and plays an essential part in cancer progression. We investigated methylation and expression of ZNF582 in clear cell renal cell carcinoma (ccRCC), and to study the function of ZNF582 in ccRCC cells.

METHODS

Methylation data and mRNA expression data of TCGA-KIRC were obtained from TCGA database to screen methylation-driven genes. Survival analysis and gene set enrichment analysis (GSEA) were done for the target gene. The methylation degree and mRNA level of ZNF582 in ccRCC cell line were detected by methylation-specific PCR (MSP) and qRT-PCR, respectively. Effects of overexpression of ZNF582 on ccRCC cells were assessed via CCK-8, flow cytometry, wound healing, Transwell, and cell adhesion assays.

RESULTS

Eighteen methylation-driven genes were identified via bioinformatics methods. Among them, ZNF582 was noticeably hypermethylated and lowly expressed in tumor tissue, and ZNF582 methylation and expression levels were pronouncedly associated with prognosis and clinical stage. MSP also displayed that the ZNF582 DNA promoter region was hypermethylated in ccRCC cells, and the mRNA expression of ZNF582 was dramatically elevated after demethylation. In vitro cell experiments disclosed that overexpression of ZNF582 markedly hindered cell proliferation, invasion, migration, and fostered cell apoptosis and adhesion of ccRCC.

CONCLUSION

ZNF582 was hypermethylated in ccRCC, which mediated its low level. Overexpression of ZNF582 inhibited tumor cell proliferation, migration and invasion. This study generates novel ideas for ccRCC diagnosis and treatment.

A novel risk model of three SUMOylation genes based on RNA expression for potential prognosis and treatment sensitivity prediction in kidney cancer

Introduction: Kidney cancer is one of the most common and lethal urological malignancies. Discovering a biomarker that can predict prognosis and potential drug treatment sensitivity is necessary for managing patients with kidney cancer. SUMOylation is a type of posttranslational modification that could impact many tumor-related pathways through the mediation of SUMOylation substrates. In addition, enzymes that participate in the process of SUMOylation can also influence tumorigenesis and development. Methods: We analyzed the clinical and molecular data which were obtanied from three databases, The Cancer Genome Atlas (TCGA), the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC), and ArrayExpress. Results: Through analysis of differentially expressed RNA based on the total TCGA-KIRC cohort, it was found that 29 SUMOylation genes were abnormally expressed, of which 17 genes were upregulated and 12 genes were downregulated in kidney cancer tissues. A SUMOylation risk model was built based on the discovery TCGA cohort and then validated successfully in the validation TCGA cohort, total TCGA cohort, CPTAC cohort, and E-TMAB-1980 cohort. Furthermore, the SUMOylation risk score was analyzed as an independent risk factor in all five cohorts, and a nomogram was constructed. Tumor tissues in different SUMOylation risk groups showed different immune statuses and varying sensitivity to the targeted drug treatment. Discussion: In conclusion, we examined the RNA expression status of SUMOylation genes in kidney cancer tissues and developed and validated a prognostic model for predicting kidney cancer outcomes using three databases and five cohorts. Furthermore, the SUMOylation model can serve as a biomarker for selecting appropriate therapeutic drugs for kidney cancer patients based on their RNA expression.

The Underestimated Role of the p53 Pathway in Renal Cancer

The TP53 tumor suppressor gene is known as the guardian of the genome, playing a pivotal role in controlling genome integrity, and its functions are lost in more than 50% of human tumors due to somatic mutations. This percentage rises to 90% if mutations and alterations in the genes that code for regulators of p53 stability and activity are taken into account. Renal cell carcinoma (RCC) is a clear example of cancer that despite having a wild-type p53 shows poor prognosis because of the high rate of resistance to radiotherapy or chemotherapy, which leads to recurrence, metastasis and death. Remarkably, the fact that p53 is poorly mutated does not mean that it is functionally active, and increasing experimental evidences have demonstrated this. Therefore, RCC represents an extraordinary example of the importance of p53 pathway alterations in therapy resistance. The search for novel molecular biomarkers involved in the pathways that regulate altered p53 in RCC is mandatory for improving early diagnosis, evaluating the prognosis and developing novel potential therapeutic targets for better RCC treatment.

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

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.

Comprehensive Evaluation of the m6A Regulator Prognostic Risk Score in the Prediction of Immunotherapy Response in Clear Cell Renal Cell Carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is known for its high drug resistance. The tumor-immune crosstalk mediated by the epigenetic regulation of N6-methyladenosine (m6A) modification has been demonstrated in recent studies. Therefore, m6A modification-mediated immune cell infiltration characteristics may be helpful to guide immunotherapy for ccRCC.

METHODS

This study comprehensively analyzed m6A modifications using the clinical parameters, single-cell RNA sequencing data, and bulk RNA sequencing data from the TCGA-ccRC cohort and 13 external validation cohorts. A series of bioinformatic approaches were applied to construct an m6A regulator prognostic risk score (MRPRS) to predict survival and immunotherapy response in ccRCC patients. Immunological characteristics, enriched pathways, and mutation were evaluated in high- and low-MRPRS groups.

RESULTS

The expressional alteration landscape of m6A regulators was profiled in ccRCC cell clusters and tissue. The 8 regulator genes with minimal lambda were integrated to build an MRPRS, and it was positively correlated with immunotherapeutic response in extent validation cohorts. The clinicopathological features and immune infiltration characteristics could be distinguished by the high- and low-MRPRS. Moreover, the MRPRS-mediated mutation pattern has an enhanced response to immune checkpoint blockade in the ccRCC and pan-cancer cohorts.

CONCLUSIONS

The proposed MRPRS is a promising biomarker to predict clinical outcomes and therapeutic responses in ccRCC patients.

The clinical significance of epigenetic and RNAPII variabilities occurring in clear cell renal cell carcinoma as a potential prognostic marker

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30 ccRCC patients were used, to follow the epigenetic changes (γH2A.X, H3K4me3 and H3K9me3) and the alterations in the level of RNA polymerase II (RNAPII).

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The variabilities between the tumorous and non-tumorous parts of the tissue were measured by image analysis in which we monitored 30 cells from different positions of either the tumorous or the non-tumorous part of the tissue sections.

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These markers were classified to predict patient outcomes based on their individual cellular background. These results also support that detection of any alteration in the level of H3K4me3, H3K9me3, and γH2AX can account valuable information for presuming the progression of ccRCC and the clinical benefits to select the most efficient personalized therapy.

Patients diagnosed with clear cell renal cell carcinoma (ccRCC) have poor prognosis for recurrence and approximately 30–40% of them will later develop metastases. For this reason, the appropriate diagnosis and the more detailed molecular characterisation of the primary tumour, including its susceptibility to metastasis, are crucial to select the proper adjuvant therapy by which the most prosperous outcome can be achieved. Nowadays, clinicopathological variables are used for classification of the tumours. Apart from these, molecular biomarkers are also necessary to improve risk classification, which would be the most beneficial amongst modern adjuvant therapies. As a potential molecular biomarker, to follow the transcriptional kinetics in ccRCC patients (n=30), we analysed epigenetic changes (γH2A.X, H3K4me³, and H3K9me³) and the alterations in the level of RNA polymerase II (RNAPII) by immunohistochemical staining on dissected tissue sections. The variabilities between the tumorous and non-tumorous parts of the tissue were detected using quantitative image analysis by monitoring 30 cells from different positions of either the tumorous or the non-tumorous part of the tissue sections. Data obtained from the analyses were used to identify potential prognostic features and to associate them with the progression. These markers might have a value to predict patient outcomes based on their individual cellular background. These results also support that detection of any alteration in the level of H3K4me³, H3K9me³, and γH2A.X can account for valuable information for presuming the progression of ccRCC and the clinical benefits to select the most efficient personalised therapy.

Multi-Omics Analysis of the Prognosis and Biological Function for TRPV Channel Family in Clear Cell Renal Cell Carcinoma

Background

The transient receptor potential vanilloid (TRPV) channels family, TRPV1-6, has been identified to profoundly affect a wide spectrum of pathological processes in various cancers. However, the biological function and prognostic value of TRPVs in clear cell renal cell carcinoma (ccRCC) are still largely unknown.

Methods

We obtained the gene expression data and clinical information of 539 ccRCC patients from The Cancer Genome Atlas (TCGA) database. A series of databases were used for data processing and visualization, including GEPIA, GeneMANIA, MethSurv, GSCA, TIMER, and starBase databases.

Results

The mRNA expression of TRPV2/3 was upregulated while the expression of TRPV5/6 was downregulated in ccRCC tumor tissues. TRPV family members in ccRCC were rarely mutated (nearly 7 frequencies). The ROC curve showed that TRPV2/5/6 had a high diagnostic ability in discriminating ccRCC from the control samples (AUC>0.9). Higher levels of TRPV3 expression were associated with poor prognosis of ccRCC patients, while higher expression of TRPV4 was associated with favorable prognosis. The expression of TRPV3 in normal and ccRCC tissues was validated by Immunohistochemistry, and its expression was remarkably related to high histologic grade and advanced stage. Besides, TRPV3 exhibit a reduction of DNA methylation level with tumor progression, and 12 CpGs of TRPV3 were associated with a significant prognosis. In addition, TRPV3 expression was significantly associated with the accumulation of several tumor-infiltrating immune cells, especially regulatory T cells. Furthermore, high levels of TRPV3 induced the expression of immune checkpoints such as LAG3, CTLA4, PDCD1, and TIGIT. Finally, we predicted a key SNHG3/AL513497.1-miR-10b-5p-TRPV3 axis linking to carcinogenesis and progression of ccRCC.

Conclusion

Our study may uncover TRPV channels–associated molecular mechanisms involved in the tumorigenesis and progression of ccRCC. TRPV family members might be diagnosed and prognostic markers and potential therapeutic targets for ccRCC patients.

Circ_0003146 upregulates SCARB1 expression by acting as a miR-1272 sponge to promote malignant behaviors of clear cell renal cell carcinoma

Circular RNAs (circRNAs) exhibit essential regulation in the malignant development of clear cell renal cell carcinoma (ccRCC). The aims of this study were to investigate the role and mechanism of circ_0003146 in the biologic behaviors of ccRCC. RNA level analysis was performed through reverse transcription-quantitative PCR assay. Cell proliferation was measured by EdU assay and cell counting kit-8 assay. The protein expression was analyzed using a western blot. Flow cytometry and caspase 3 activity assay were used to assess cell apoptosis. Cell migration and invasion were evaluated via wound healing assay and transwell assay. Circ_0003146 function in vivo was determined by xenograft tumor assay. Dual-luciferase reporter assay was applied for target relation analysis. Circ_0003146 upregulation was detected in ccRCC tissues and cells. Downregulation of circ_0003146 induced inhibition of proliferation, migration, invasion and EMT but the promotion of apoptosis in ccRCC cells. Tumor growth in vivo was inhibited after knockdown of circ_0003146. Circ_0003146 directly interacted with miR-1272, and the miR-1272 sponging effect was responsible for the function of circ_0003146. Scavenger receptor class B type 1 (SCARB1) was a target of miR-1272, and circ_0003146 regulated SCARB1 level by absorbing miR-1272. The regulation of circ_0003146 in ccRCC progression was achieved by upregulating SCARB1 in part. The current findings demonstrated that circ_0003146 contributed to the malignant progression of ccRCC via inducing SCARB1 upregulation by targeting miR-1272.

RoDiCE: robust differential protein co-expression analysis for cancer complexome

MOTIVATION

The full spectrum of abnormalities in cancer-associated protein complexes remains largely unknown. Comparing the co-expression structure of each protein complex between tumor and healthy cells may provide insights regarding cancer-specific protein dysfunction. However, the technical limitations of mass spectrometry-based proteomics, including contamination with biological protein variants, causes noise that leads to non-negligible over- (or under-) estimating co-expression.

RESULTS

We propose a robust algorithm for identifying protein complex aberrations in cancer based on differential protein co-expression testing. Our method based on a copula is sufficient for improving identification accuracy with noisy data compared to conventional linear correlation-based approaches. As an application, we use large-scale proteomic data from renal cancer to show that important protein complexes, regulatory signaling pathways and drug targets can be identified. The proposed approach surpasses traditional linear correlations to provide insights into higher-order differential co-expression structures.

AVAILABILITY AND IMPLEMENTATION

https://github.com/ymatts/RoDiCE.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Quaking I-5 protein inhibits invasion and migration of kidney renal clear cell carcinoma via inhibiting epithelial-mesenchymal transition suppression through the regulation of microRNA 200c

Background

It has been demonstrated that quaking I-5 protein (QKI-5) plays crucial roles in the metastasis of various kinds of cancers. However, the function and mechanism of QKI-5 in kidney renal clear cell carcinoma (KIRC) metastasis remains unclear. Therefore, this study aimed to explore the mechanism of QKI-5 in the metastasis of KIRC.

Methods

The expression of QKI-5 was detected using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blot in KIRC tissues and different cell lines. Immunohistochemical staining was used to detect the quantity of QKI-5 in primary and metastases of KIRC. Cell migration and invasion were measured using wound healing and transwell assays respectively. The quantity of epithelial mesenchymal transition marker proteins was detected using western blot and immunofluorescence staining. The interaction of QKI-5 via microRNA 200c (miR-200c) was confirmed using dual luciferase reporter assay.

Results

Although QKI-5 was significantly more likely to be downregulated in KIRC tissues than that in normal Kidney tissues, it was dramatically elevated in metastatic KIRC tumors. Upregulation of QKI-5 promoted cell migration and invasion and elevated the expression of epithelial-mesenchymal transition (EMT) marker proteins, including vimentin, snail and slug, while it was downregulated for E-cadherin. Furthermore, a dual luciferase reporter assay demonstrated that QKI-5 was a direct target of miR-200c, and that miR-200c could reverse the effect of QKI-5 on cell migration, invasion, and expression of EMT marker proteins.

Conclusions

Our results revealed that downregulation of QKI-5 by miR-200c attenuated KIRC migration and invasion via the EMT process, indicating that QKI-5 may be a potential therapeutic target and a key indicator of KIRC progression.

Quantitative proteomic analysis reveals sophisticated metabolic alteration and identifies FMNL1 as a prognostic marker in clear cell renal cell carcinoma

Purpose: In this study, we have undertaken the whole proteomic analysis and got a better understanding of biological processes involved in the development and progression of ccRCC. We hope promising biomarkers can be uncovered to facilitate early diagnosis, predict the prognosis and progression, more importantly, to be applied as potential therapeutic targets.

Experimental design: Fresh frozen tissue samples were surgically resected from patients with local or locally advanced ccRCC. Trypsin digested proteins were analyzed using TMT-based LC-MS/MS proteomic approach, followed by bioinformatic analysis. A potential prognostic marker FMNL1 was chosen to be validated in TCGA_KIRC datasets (n=525 and 72), further validation sets (n=10 and 10) and expanded validation sets (n=81 and 16). The effects of FMNL1 on proliferation, migration and invasion were determined by colony formation, wound healing, and transwell assays in 786-O and Caki-1 cells in vitro study.

Results: A total of 657 differentially expressed proteins were identified and quantified between ccRCC and adjacent normal tissues (p-value<0.05, FC>2 or<1/2), of which 186 proteins were up-regulated and 471 proteins were down-regulated. Bioinformatic analysis showed enriched metabolic biological processes and pathways. Univariate and multivariate analysis defined FMNL1 as an independent negative prognostic marker in the TCGA datasets. High expression of FMNL1 correlated significantly with tumor stage and distant metastasis (P<0.05) both in the TCGA-KIRC datasets and expanded validation sets. Kaplan-Meier survival curve illustrated that the patients with high FMNL1 protein level had shorter OS time in the expanded validation sets (p=0.0273). In vitro experiments presented the functional effects of FMNL1 knockdown on the inhibition of proliferation, migration and invasion in cancer cell lines.

Conclusion and clinical relevance: The proteomic results uncovered sophisticated metabolic reprogramming of ccRCC and indicated that the upregulation of rate-limiting enzymes in glycolysis and mitochondrial impairment may be the cause of metabolic reprogramming in ccRCC. Moreover, FMNL1 has been identified as a promising prognostic marker, and knockdown of FMNL1 could inhibit ccRCC cell proliferation, migration and invasion, which might be used as a new effective therapeutic strategy to inhibit the progression of ccRCC.

Computational study of effective matrix metalloproteinase 9 (MMP9) targeting natural inhibitors

Object: The present study screened ideal lead natural compounds that could target and inhibit matrix metalloproteinase 9 (MMP9) protein from the ZINC database to develop drugs for clear cell renal cell carcinoma (CCRCC)-targeted treatment.

Methods: Discovery Studio 4.5 was used to compare and screen the ligands with the reference drug, solasodine, to identify ideal candidate compounds that could inhibit MMP9. The LibDock module was used to analyze compounds that could strongly bind to MMP9, and the top 20 compounds determined by the LibDock score were selected for further research. ADME and TOPKAT modules were used to choose the safe compounds from these 20 compounds. The selected compounds were analyzed using the CDOCKER module for molecular docking and feature mapping for pharmacophore prediction. The stability of these compound–MMP9 complexes was analyzed by molecular dynamic simulation. Cell counting kit-8, colony-forming, and scratch assays were used to analyze the anti-CCRCC effects of these ligands.

Results: Strong binding to MMP9 was exhibited by 6,762 ligands. Among the top 20 compounds, sappanol and sventenin exhibited nearly undefined blood–brain barrier level and lower aqueous solubility, carcinogenicity, and hepatotoxicity than the positive control drug, solasodine. Additionally, these compounds exhibited lower potential energies with MMP9, and the ligand–MMP9 complexes were stable in the natural environment. Furthermore, sappanol inhibited CCRCC cell migration and proliferation.

Conclusion: Sappanol and sventenin are safe and reliable compounds to target and inhibit MMP9. Sappanol can CCRCC cell migration and proliferation. These two compounds may give new thought to the targeted therapy for patients with CCRCC.

Circ_RPL23A acts as a miR-1233 sponge to suppress the progression of clear cell renal cell carcinoma by promoting ACAT2

Clear cell renal cell carcinoma (ccRCC) is a prevalent urological carcinoma with high metastatic risk. Circular RNAs (circRNAs) have been identified as effective diagnostic and therapeutic biomarkers for ccRCC. This research aims to disclose the effect and regulatory mechanism of circRNA ribosomal protein L23a (circ_RPL23A) in ccRCC. We performed quantitative real-time polymerase chain reaction (qRT-PCR) to examine circ_RPL23A, microRNA-1233 (miR-1233) and acetyl-coenzyme A acetyltransferase 2 (ACAT2). Cell cycle progression, apoptosis, cell viability, invasion and migration, which were respectively conducted by using flow cytometry, 3-(4, 5-dimethylthiazol-2-y1)-2, 5-diphenyl tetrazolium bromide (MTT), transwell assays. The levels of ACAT2 protein and cell cycle proteins, proliferation-associated protein, and epithelial-mesenchymal transition (EMT) associated proteins were measured by western blot. Target relationship was analyzed via dual-luciferase reporter assay and RNA pull down assay. The animal model was used to study how circ_RPL23A affects in vivo. Circ_RPL23A was lower expressed in ccRCC tissues and cells. The elevated circ_RPL23A suppressed cell cycle progression, proliferation, migration and invasion but promoted apoptosis in ccRCC cells. MiR-1233 was a target of circ_RPL23A and direct targeted to ACAT2. Besides, circ_RPL23A exerted its anti-tumor effect by sponging miR-1233, and then relieved the inhibition effect of miR-1233 on ACAT2. Overexpression of circ_RPL23A also curbed ccRCC tumor growth in vivo. Circ_RPL23A inhibited ccRCC progression by upregulating ACAT2 expression by competitively binding miR-1233, which might provide an in-depth cognition for ccRCC pathogenesis and circ_RPL23A might be a promising biomarker in ccRCC diagnosis and treatment.

Delivery of miR-224-5p by Exosomes from Cancer-Associated Fibroblasts Potentiates Progression of Clear Cell Renal Cell Carcinoma

Objectives

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma. Cancer-associated fibroblasts (CAFs) as the primary components of cancer stroma can affect tumor progression by secreting exosomes, while exosomes are carriers for proteins, nucleic acids, and other agents that responsible for delivery of biological information. Given this, exosomes derived from CAFs are emerging as promising biomarkers in clinical cancer diagnosis. Nevertheless, their role in clear cell renal cell carcinoma (ccRCC) remains poorly understood.

Methods

Here, we separated fibroblasts from ccRCC tissue, extracted exosomes, observed their morphology, and detected the expression of exosome marker proteins including Hsp70, CD9, and CD63. In the meantime, we labeled exosomes and performed coculture experiment to verify the delivery of miR-224-5p from CAFs to 769-P cells with exosomes as a carrier, so as to clarify the effect of CAF-derived exosomes on ccRCC cell malignant behaviors, as well as to discuss how miR-224-5p involves in above regulation.

Results

Transmission electron microscopy was firstly applied, and it was noted that the exosomes we isolated were in normal range. Besides, Western blot also confirmed the presence of exosome marker proteins Hsp70, CD9, and CD63. Furthermore, coculture experiments were performed and the CAF-derived exosomes were observed to be able to facilitate the malignant behaviors of ccRCC cells, and the exosomal miR-224-5p could be internalized by ccRCC cells to participate in regulation of cell proliferation, migration, invasion, and apoptosis.

Conclusion

To sum up, miR-224-5p can enter ccRCC cells via CAF-derived exosomes, in turn, promoting the malignant behaviors of ccRCC cells, which indicates that miR-224-5p has the potential severing as a therapeutic target for ccRCC.

Prediction and analysis of novel key genes ITGAX, LAPTM5, SERPINE1 in clear cell renal cell carcinoma through bioinformatics analysis

Background

Clear Cell Renal Cell Carcinoma (CCRCC) is the most aggressive subtype of Renal Cell Carcinoma (RCC) with high metastasis and recurrence rates. This study aims to find new potential key genes of CCRCC.

Methods

Four gene expression profiles (GSE12606, GSE53000, GSE68417, and GSE66272) were downloaded from the Gene Expression Omnibus (GEO) database. The TCGA KIRC data was downloaded from The Cancer Genome Atlas (TCGA). Using GEO2R, the differentially expressed genes (DEG) in CCRCC tissues and normal samples were analyzed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed in DAVID database. A protein-protein interaction (PPI) network was constructed and the hub gene was predicted by STRING and Cytoscape. GEPIA and Kaplan-Meier plotter databases were used for further screening of Key genes. Expression verification and survival analysis of key genes were performed using TCGA database, GEPIA database, and Kaplan-Meier plotter. Receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of key genes in CCRCC, which is plotted by R software based on TCGA database. UALCAN database was used to analyze the relationship between key genes and clinical pathology in CCRCC and the methylation level of the promoter of key genes in CCRCC.

Results

A total of 289 up-regulated and 449 down-regulated genes were identified based on GSE12606, GSE53000, GSE68417, and GSE66272 profiles in CCRCC. The upregulated DEGs were mainly enriched with protein binding and PI3K-Akt signaling pathway, whereas down-regulated genes were enriched with the integral component of the membrane and metabolic pathways. Next, the top 35 genes were screened out from the PPI network according to Degree, and three new key genes ITGAX, LAPTM5 and SERPINE1 were further screened out through survival and prognosis analysis. Further results showed that the ITGAX, LAPTM5, and SERPINE1 levels in CCRCC tumor tissues were significantly higher than those in normal tissues and were associated with poor prognosis. ROC curve shows that ITGAX, LAPTM5, and SERPINE1 have good diagnostic value with good specificity and sensitivity. The promoter methylation levels of ITGAX, LAPTM5 and SERPINE1 in CCRCC tumor tissues were significantly lower than those in normal tissues. We also found that key genes were associated with clinical pathology in CCRCC.

Conclusion

ITGAX, LAPTM5, and SERPINE1 were identified as novel key candidate genes that could be used as prognostic biomarkers and potential therapeutic targets for CCRCC.

Determination of the key ccRCC-related molecules from monolayer network to three-layer network

Clear cell renal cell carcinoma (ccRCC), with an increasing incidence rate, is one of the ubiquitous cancers. Its pathogenic factors are complicated and the molecular mechanism is not clear. It is essential to analyze the potential key genes related to ccRCC carcinogenesis. In this study, the differentially expressed mRNAs, miRNAs and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) of ccRCC were screened from TCGA database. Then the miRNA-mRNA network, lncRNA-miRNA network and lncRNA-mRNA network were constructed by online database or WGCNA algorithm. Topology attributes of these monolayer networks showed that hsa-mir-155, hsa-mir-200c, hsa-mir-122, hsa-mir-506, hsa-mir-216b, hsa-mir-141, lncRNA AC137723.1 and AC021074.3 are the crucial genes related with the regulatory effects on the proliferation, metastasis and invasion of ccRCC cells. Subsequently, these three monolayer networks were integrated into a lncRNA-miRNA-mRNA multilayer network. Considering node degree, closeness centrality and betweenness centrality, we found hsa-mir-122 is screened out as the only crucial gene in three-layer network. In order to better illustrate the effect of hsa-mir-122 on ccRCC, the lncRNA-hsa-mir-122-mRNA network was constructed with hsa-mir-122 as the center. Pathway analysis of the unique target gene GALNT3 linked to hsa-mir-122 showed that GALNT3 influenced the metabolic process of mucin type O-Glycan biosynthesis. LncRNA AC090377.1 is the unique gene that has target genes among lncRNAs with clinical significance that linked to hsa-mir-122 in the lncRNA-hsa-mir-122-mRNA network. Pathway analysis of AC090377.1 suggested that GUCY2F enriched in phototransduction pathway associated with retina. From monolayer network to three-layer network, hsa-mir-122 is identified as an important molecule in the oncogenesis and progression of ccRCC, offering new strategies to further study of the carcinogenic mechanism of ccRCC.

The ER-mitochondria Ca2+ signaling in cancer progression: Fueling the monster

Cancer is a leading cause of death worldwide. All major tumor suppressors and oncogenes are now recognized to have fundamental connections with metabolic pathways. A hallmark feature of cancer cells is a reprogramming of their metabolism even when nutrients are available. Increasing evidence indicates that most cancer cells rely on mitochondrial metabolism to sustain their energetic and biosynthetic demands. Mitochondria are functionally and physically coupled to the endoplasmic reticulum (ER), the major calcium (Ca²⁺) storage organelle in mammalian cells, through special domains known as mitochondria-ER contact sites (MERCS). In this domain, the release of Ca²⁺ from the ER is mainly regulated by inositol 1,4,5-trisphosphate (IP3) receptors (IP3Rs), a family of Ca²⁺ release channels activated by the ligand IP3. IP3R mediated Ca²⁺ release is transferred to mitochondria through the mitochondrial Ca²⁺ uniporter (MCU). Once in the mitochondrial matrix, Ca²⁺ activates several proteins that stimulate mitochondrial performance. The role of IP3R and MCU in cancer, as well as the other proteins that enable the Ca²⁺ communication between these two organelles is just beginning to be understood. Here, we describe the function of the main players of the ER mitochondrial Ca²⁺ communication and discuss how this particular signal may contribute to the rise and development of cancer traits.

Succinylation Regulators Promote Clear Cell Renal Cell Carcinoma by Immune Regulation and RNA N6-Methyladenosine Methylation

Succinylation is a newly discovered and multienzyme-regulated post-translational modification (PTM) that is associated with the initiation and progression of cancer. Currently, no systematic analyses on the role of succinylation regulators in tumors have been reported. In this study, we performed a comprehensive pan-cancer analysis on four well-known succinylation regulators (CPT1A, KAT2A, SIRT5, and SIRT7). We found that these regulators played specific and critical roles in the prognosis of clear cell renal cell carcinoma (ccRCC). We constructed a risk score (RS) based on two independent prognostic prediction factors, CPT1A and KAT2A, and subsequently developed a nomogram model containing the RS, which showed good accuracy in the prediction of overall survival (OS) in ccRCC patients. Furthermore, we used the similar expression pattern of four succinylation regulators according to consensus clustering analysis to divide the patients into three clusters that exhibited prominently different OS as well as clinicopathological characteristics. Differently expressed genes (DEGs) and pathway enrichment analyses of three clusters indicated that succinylation regulators might promote malignant progression of ccRCC by regulating the infiltration of immune cells and RNA N6-methyladenosine (m6A) methylation. Importantly, our data suggest that CPT1A and SIRT5 might up-regulate and down-regulate the expression of LRPPRC and EIF3B, respectively. Our study systematically analyzed the prognostic predictive values of four succinylation regulators and revealed their potential mechanisms in ccRCC aggressiveness. These data provide new insight into the understanding of succinylation modification and present clinical evidence for its role in ccRCC treatments.

Identification of subtype specific biomarkers of clear cell renal cell carcinoma using random forest and greedy algorithm

Suitable biomarkers can be good indicator for cancer subtype. To find biomarkers that can accurately distinguish clear cell renal cell carcinoma (ccRCC) subtypes, we first determined ccRCC subtypes based on the expression of mRNA, miRNA and lncRNA, named clear cell type 1 (ccluster1) and 2 (ccluster2), using three unsupervised clustering algorithms. Besides being associated with the expression pattern derived from the single type of RNA, the differences between subtypes are relevant to the interactions between RNAs. Then, based on ceRNA network, the optimal combination features are selected using random forest and greedy algorithm. Further, in survival-related sub-ceRNA, competing gene pairs centering on miR-106a, miR-192, miR-193b, miR-454, miR-32, miR-98, miR-143, miR-145, miR-204, miR-424 and miR-1271 can also well identify ccluster1 and ccluster2 with prediction accuracy over 92%. These subtype-specific features potentially enhance the accuracy with which machine learning methods predict specific ccRCC subtypes. Simultaneously, the changes of miR-106 and OIP5-AS1 affect cell proliferation and the prognosis of ccluster1. The changes of miR-145 and FAM13A-AS1 in ccluster2 have an effect on cell invasion, apoptosis, migration and metabolism function. Here miR-192 displays a unique characteristic in both subtypes. Two subtypes also display notable differences in diverse pathways. Tumors belonging to ccluster1 are characterized by Fc gamma R-mediated phagocytosis pathway that affects tissue remodeling and repair, whereas those belonging to ccluster2 are characterized by EGFR tyrosine kinase inhibitor resistance pathway that participates in regulation of cell homeostasis. In conclusion, identifying these gene pairs can shed light on therapeutic mechanisms of ccRCC subtypes.

A novel prognostic model based on immunogenomics for clear cell renal cell carcinoma

BACKGROUND

Immune cell infiltration into tumor tissue is closely related to the clinical outcomes of patients with clear cell renal cell carcinoma (ccRCC). This study aimed to screen out potential immune genes associated with ccRCC, analyze their relationships with clinical outcomes, and construct a signature to predict ccRCC.

METHODS

The transcriptome RNA-sequencing data in 539 ccRCC and 72 adjacent normal tissues were obtained from TCGA database. Biomedical computational algorithms were conducted to identify immune-related differential expressed genes (IRDGs) and enriched pathways. Then, LASSO Cox and multivariate Cox analyses were performed to screen out genes that were then used to construct the prognostic model.

RESULTS

A total of 116 down-regulated and 565 up-regulated IRDGs were identified. Pathway enrichment analysis suggested that IRDGs was mainly enriched in the pathway of "cytokines and cytokine receptors". The entire data of ccRCC were randomly divided into the training set and the test set with a ratio of 1:1. A 4-gene signature was then constructed using LASSO Cox analysis and multivariate Cox analysis in the training set. This prognostic signature could stratify patients into high- and low-risk groups successfully, and serve as an independent predictor when adjusted with clinical factors by univariate and multivariate Cox regression analysis. These results were verified in the test set and the entire set. Besides, the abundance of CD4 + T cells and dendritic cells increased in the high-risk group. Finally, we built a nomogram incorporating risk score and clinical factors to predict the overall survival of ccRCC patients.

CONCLUSIONS

These findings may contribute to the research of ccRCC in immunization part.