CPA4 as a biomarker promotes the proliferation, migration and metastasis of clear cell renal cell carcinoma cells

Clear cell renal cell carcinoma (ccRCC) is a commonly occurring and highly aggressive urological malignancy characterized by a significant mortality rate. Current therapeutic options for advanced ccRCC are limited, necessitating the discovery of novel biomarkers and therapeutic targets. Carboxypeptidase A4 (CPA4) is a zinc-containing metallocarboxypeptidase with implications in various cancer types, but its role in ccRCC remains unexplored. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized in order to investigate the differential expression patterns of CPA4. The expression of CPA4 in ccRCC patients was further verified using immunohistochemical (IHC) examination of 24 clinical specimens. A network of protein-protein interactions (PPI) was established, incorporating CPA4 and its genes that were expressed differentially. Functional enrichment analyses were conducted to anticipate the contribution of CPA4 in the development of ccRCC. To validate our earlier study, we conducted real-time PCR and cell functional tests on ccRCC cell lines. Our findings revealed that CPA4 is overexpressed in ccRCC, and the higher the expression of CPA4, the worse the clinical outcomes such as TNM stage, pathological stage, histological grade, etc. Moreover, patients with high CPA4 expression had worse overall survival, disease-specific survival and progress-free interval than patients with low expression. The PPI network analysis highlighted potential interactions contributing to ccRCC progression. Functional enrichment analysis indicated the involvement of CPA4 in the regulation of key pathways associated with ccRCC development. Additionally, immune infiltration analysis suggested a potential link between CPA4 expression and immune response in the tumour microenvironment. Finally, cell functional studies in ccRCC cell lines shed light on the molecular mechanisms underlying the role of CPA4 in promoting ccRCC formation. Overall, our study unveils CPA4 as a promising biomarker with prognostic potential in ccRCC. The identified interactions and pathways provide valuable insights into its implications in ccRCC development and offer a foundation for future research on targeted therapies. Further investigation of CPA4's involvement in immune responses may contribute to the development of immunotherapeutic strategies for ccRCC treatment.

Neurogenesis-Associated Protein, a Potential Prognostic Biomarker in Anti-PD-1 Based Kidney Renal Clear Cell Carcinoma Patient Therapeutics

The transketolase 1 gene (TKTL1) is an essential factor that contributes to brain development. Some studies have shown the influence of TKTL1 in cancers, but it has been rarely reported in kidney cancer. Furthermore, the role of TKTL1 in the prognosis and tumor infiltration of immune cells in various cancers, particularly kidney cancer, remains unknown. In this study, TKTL1 expression and its clinical characteristics were investigated using a variety of databases. TIMER was used to investigate the relationship between TKTL1 and immune infiltrates in various types of cancer. We also studied the relationship between TKTL1 expression and response to PD-1 blocker immunotherapy in renal cancer. We conducted TKTL1 agonists virtual screening from 13,633 natural compounds (L6020), implemented secondary library construction according to the types of top results, and then conducted secondary virtual screening for 367 alkaloids. Finally, in vitro assays of cell viability assays and colony formation assays were performed to demonstrate the pharmacological potency of the screening of TKTL1 agonists. Using these methods, we determined that TKTL1 significantly affects the prognostic potential in different types of kidney cancer patients. The underlying mechanism might be that the TKTL1 expression level was positively associated with devious immunocytes in kidney renal clear cell carcinoma (KIRC) rather than in kidney renal papillary cell carcinoma (KIRP) and kidney chromophobe (KICH). This recruitment may result from the up-regulation of the mTOR signaling pathway affecting T cell metabolism. We also found that TKTL1 may act as an immunomodulator in KIRC patients' response to anti-PD-1 therapy. Moreover, we also found that piperine and glibenclamide are potent agonists of TKTL1. We have demonstrated, in vitro, that piperine and glibenclamide can inhibit the proliferation and clone formation of Caki-2 cell lines by agonizing the expression of TKTL1. In summary, our discovery implies that TKTL1 may be a promising prognostic biomarker for KIRC patients who respond to anti-PD-1 therapy. Piperine and glibenclamide may be effective therapeutic TKTL1 agonists, providing a theoretical basis for the clinical treatment of kidney cancer.

Identification and validation of a novel signature based on macrophage marker genes for predicting prognosis and drug response in kidney renal clear cell carcinoma by integrated analysis of single cell and bulk RNA sequencing

Macrophages are found in a variety of tumors and play a critical role in shaping the tumor microenvironment, affecting tumor progression, metastasis, and drug resistance. However, the clinical relevance of marker genes associated with macrophage in kidney renal clear cell carcinoma (KIRC) has yet to be documented. In this study, we initiated a thorough examination of single-cell RNA sequencing (scRNA-seq) data for KIRC retrieved from the Gene Expression Omnibus (GEO) database and determined 244 macrophage marker genes (MMGs). Univariate analysis, LASSO regression, and multivariate regression analysis were performed to develop a five-gene prognostic signature in The Cancer Genome Atlas (TCGA) database, which could divide KIRC patients into low-risk (L-R) and high-risk (H-R) groups. Then, a nomogram was constructed to predict the survival rate of KIRC patients at 1, 3, and 5 years, which was well assessed by receiver operating characteristic curve (ROC), calibration curve, and decision curve analyses (DCA). Functional enrichment analysis showed that immune-related pathways (such as immunoglobulin complex, immunoglobulin receptor binding, and cytokine-cytokine receptor interaction) were mainly enriched in the H-R group. Additionally, in comparison to the L-R cohort, patients belonging to the H-R cohort exhibited increased immune cell infiltration, elevated expression of immune checkpoint genes (ICGs), and a higher tumor immune dysfunction and exclusion (TIDE) score. This means that patients in the H-R group may be less sensitive to immunotherapy than those in the L-R group. Finally, IFI30 was validated to increase the ability of KIRC cells to proliferate, invade and migrate in vitro. In summary, our team has for the first time developed and validated a predictive model based on macrophage marker genes to accurately predict overall survival (OS), immune characteristics, and treatment benefit in KIRC patients.

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

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

Comprehensive analysis of pain genes in prognosis of kidney renal clear cell carcinoma and tumor immunotherapy: A comprehensive bioinformatic study

Background

The effect of pain genes (NAV1, EHMT2, SP1, SLC6A4, COMT, OPRM1, OPRD1, CYP2D6, and CYP3A4) have not been reported previously in kidney renal clear cell carcinoma (KIRC) patients and thus we made a comprehensive analysis of pain genes in the prognosis of KIRC and tumor immunotherapy.

Methods

In this study, TCGA, Kaplan-Meier plotter, Metascape, STRING, Human Protein Atlas, Single Cell Expression Atlas database, LinkedOmics, cBioPortal, MethSurv, CancerSEA, COSMIC database and R package (ggplot2, version 3.3.3) were used for comprehensive analysis of pain genes in KIRC. Pearson and Spearman correlation coefficients were for co-expression analysis. Immunotherapy and TISIDB database were used for tumor Immunotherapy.

Results

Representative pain genes (SP1, SLC6A4, COMT, OPRD1, CYP2D6, and CYP3A4) were statistically significant (p < 0.0001) in the prognosis of KIRC. Immunotherapy (anti-PD-1 therapy, anti-PD-L1 therapy, and anti-CTLA4 therapy) and immunomodulator (immunoinhibitor, immunostimulator, and MHC molecule) in KIRC were significant associated with pain genes (SP1, SLC6A4, COMT, OPRD1, CYP2D6, and CYP3A4), which were the important addition to clinical decision making for patients.

Conclusions

Our study uncovered a mechanism for the effect of pain genes on KIRC outcome via the modulation of associated co-expression gene networks, gene variation, and tumor Immunotherapy.

Single-cell disulfidptosis regulator patterns guide intercellular communication of tumor microenvironment that contribute to kidney renal clear cell carcinoma progression and immunotherapy

Background

Disulfidptosis, an emerging type of programmed cell death, plays a pivotal role in various cancer types, notably impacting the progression of kidney renal clear cell carcinoma (KIRC) through the tumor microenvironment (TME). However, the specific involvement of disulfidptosis within the TME remains elusive.

Methods

Analyzing 41,784 single cells obtained from seven samples of KIRC through single-cell RNA sequencing (scRNA-seq), this study employed nonnegative matrix factorization (NMF) to assess 24 disulfidptosis regulators. Pseudotime analysis, intercellular communication mapping, determination of transcription factor activities (TFs), and metabolic profiling of the TME subgroup in KIRC were conducted using Monocle, CellChat, SCENIC, and scMetabolism. Additionally, public cohorts were utilized to predict prognosis and immune responses within the TME subgroup of KIRC.

Results

Through NMF clustering and differential expression marker genes, fibroblasts, macrophages, monocytes, T cells, and B cells were categorized into four to six distinct subgroups. Furthermore, this investigation revealed the correlation between disulfidptosis regulatory factors and the biological traits, as well as the pseudotime trajectories of TME subgroups. Notably, disulfidptosis-mediated TME subgroups (DSTN+CD4T-C1 and FLNA+CD4T-C2) demonstrated significant prognostic value and immune responses in patients with KIRC. Multiple immunohistochemistry (mIHC) assays identified marker expression within both cell clusters. Moreover, CellChat analysis unveiled diverse and extensive interactions between disulfidptosis-mediated TME subgroups and tumor epithelial cells, highlighting the TNFSF12-TNFRSF12A ligand-receptor pair as mediators between DSTN+CD4T-C1, FLNA+CD4T-C2, and epithelial cells.

Conclusion

Our study sheds light on the role of disulfidptosis-mediated intercellular communication in regulating the biological characteristics of the TME. These findings offer valuable insights for patients with KIRC, potentially guiding personalized immunotherapy approaches.

Combination of bulk RNA sequencing and scRNA sequencing uncover the molecular characteristics of MAPK signaling in kidney renal clear cell carcinoma

The MAPK signaling pathway significantly impacts cancer progression and resistance; however, its functions remain incompletely assessed across various cancers, particularly in kidney renal clear cell carcinoma (KIRC). Therefore, there is an urgent need for comprehensive pan-cancer investigations of MAPK signaling, particularly within the context of KIRC. In this research, we obtained TCGA pan-cancer multi-omics data and conducted a comprehensive analysis of the genomic and transcriptomic characteristics of the MAPK signaling pathway. For in-depth investigation in KIRC, status of MAPK pathway was quantitatively estimated by ssGSEA and Ward algorithm was utilized for cluster analysis. Molecular characteristics and clinical prognoses of KIRC patients with distinct MAPK activities were comprehensively explored using a series of bioinformatics algorithms. Subsequently, a combination of LASSO and COX regression analyses were utilized sequentially to construct a MAPK-related signature to help identify the risk level of each sample. Patients in the C1 subtype exhibited relatively higher levels of MAPK signaling activity, which were associated with abundant immune cell infiltration and favorable clinical outcomes. Single-cell RNA sequencing (scRNA-seq) analysis of KIRC samples identified seven distinct cell types, and endothelial cells in tumor tissues had obviously higher MAPK scores than normal tissues. The immunohistochemistry results indicated the reduced expression levels of PAPSS1, MAP3K11, and SPRED1 in KIRC samples. In conclusion, our study represents the first integration of bulk RNA sequencing and single-cell RNA sequencing to elucidate the molecular characteristics of MAPK signaling in KIRC, providing a solid foundation for precision oncology.

Effects of Purine Metabolism-Related LINC01671 on Tumor Heterogeneity in Kidney Renal Clear Cell Carcinoma

BACKGROUND

Renal cell carcinoma has several subtypes, with kidney renal clear cell carcinoma (KIRC) being the most common and heterogeneous. Purine metabolism is associated with cancer progression. However, the role of purine metabolism-related long non-coding RNAs (lncRNAs) in KIRC remains unknown.

METHODS

KIRC were grouped into Cluster-1 and Cluster-2 based on purine genes. Limma package was used to identify differentially expressed lncRNAs between two classes of purine genes. Single-factor screening was used followed by random forest dimensionality reduction and Lasso method to screen lncRNAs. A risk score model (Purine Score) containing the 3 lncRNAs was developed using the Lasso method.

RESULTS

A total of 22 differentially expressed lncRNAs were identified. These were reduced to a final set of three (LINC01671, ARAP1-AS1 and LINC02747). Age and metastasis (M) were identified as independent prognostic factors for KIRC using univariate and multivariate Cox analysis. An abnormal immune cell response was also associated with patient survival. The Purine Score correlated with abnormal expression of immune checkpoint genes. Genetic analysis of KIRC found somatic mutations in TP53, TRIOBP, PBRM1, PKHD1, VHL, NPHP3, TLN2, CABIN1, ABCC6, XIRP2, and CHD4. In vitro cell experiments showed that knockdown of LINC01671 promoted the proliferation and migration of 786-O cells, while inhibiting apoptosis. Overexpression of LINC01671 inhibited the proliferation and migration of CAKI-1 cells, while promoting apoptosis. Gene Set Enrichment Analysis (GSEA) analysis revealed that LINC01671 was significantly enriched in the MAPK, NF-kappa B, mTOR, PI3K-Akt, and Wnt signaling pathways.

CONCLUSIONS

LINC01671 may be a novel prognostic marker with important therapeutic value for KIRC.

Multi-omics Analysis of Prognostic Significance and Immune Infiltration of FASTK Family Members in Kidney Renal Clear Cell Carcinoma

Objective

The Fas-activated serine/threonine kinase (FASTK) family of proteins has been recently found to be able to regulate mitochondrial gene expression post-transcriptionally. Nonetheless, there is a paucity of study about the role of the FASTK family in kidney renal clear cell carcinoma (KIRC). This study was conducted to explore the correlation of FASTK family genes with expression, prognosis, and immune infiltration in KIRC.

Methods

We collected the data from the UALCAN, GeneMANIA, STRING, CancerSEA, cBioPortal, Kaplan-Meier plotter, GEPIA, TISIDB and TIMER databases to evaluate the genetic alterations, differential expression, prognostic significance, and immune cell infiltration of FASTKs in patients with KIRC.

Results

In tumor tissues of KIRC, the mRNA expression level of FASTK and TBRG4 was elevated, whereas that of FASTKD1, FASTKD2, and FASTKD5 was lowered compared with normal tissues (P < .05). Patients with KIRC and high FASTK and Transforming growth factor β regulator 4 (TBRG4) expression had worse overall survival (OS) and disease specific survival (DFS), while those with lower expression of FASTKD2/3/5 had worse outcomes. FASTK was positively correlated with DNA damage. FASTKD1 was positively related to differentiation. FASTKD2 was inversely related to proliferation and FASTKD5 was inversely related to invasion and EMT in KIRC cells. FASTK expression in KIRC was inversely linked to the presence of several immune cells including Tgd, macrophages, Tcm, and Mast cells (P < .05).

Conclusions

Our research provided fresh insight and in-depth analysis to the selection of prognostic biological markers of FASTK family members in KIRC.

Construction of EMT related prognostic signature for kidney renal clear cell carcinoma, through integrating bulk and single-cell gene expression profiles

Introduction: Kidney renal clear cell carcinoma (KIRC), as a main type of malignant kidney cancers, has a poor prognosis. Epithelial-mesenchymal transformation (EMT) exerts indispensable role in tumor progression and metastasis, including in KIRC. This study aimed to mine more EMT related details and build prognostic signature for KIRC. Methods: The KIRC scRNA-seq data and bulk data were downloaded from GEO and TCGA databases, respectively. The cell composition in KIRC was calculated using CIBERSORT. Univariate Cox regression analysis and LASSO Cox regression analysis were combined to determine the prognostic genes. Gene set variation analysis and cell-cell communication analysis were conducted to obtain more functional information. Additionally, functional analyses were conducted to determine the biological roles of si-LGALS1 in vitro. Results: We totally identified 2,249 significant differentially expressed genes (DEGs) in KIRC samples, meanwhile a significant distinct expression pattern was found in KIRC, involving Epithelial Mesenchymal Transition pathway. Among all cell types, significantly higher proportion of epithelial cells were observed in KIRC, and 289 DEGs were identified in epithelial cells. After cross analysis of all DEGs and 970 EMT related genes, SPARC, TMSB10, LGALS1, and VEGFA were optimal to build prognostic model. Our EMT related showed good predictive performance in KIRC. Remarkably, si-LGALS1 could inhibit migration and invasion ability of KIRC cells, which might be involved in suppressing EMT process. Conclusion: A novel powerful EMT related prognostic signature was built for KIRC patients, based on SPARC, TMSB10, LGALS1, and VEGFA. Of which, si-LGALS1 could inhibit migration and invasion ability of KIRC cells, which might be involved in suppressing EMT process.

Single-cell landscape and spatial transcriptomic analysis reveals macrophage infiltration and glycolytic metabolism in kidney renal clear cell carcinoma

The present study investigates the clinical relevance of glycolytic factors, specifically PGAM1, in the tumor microenvironment of kidney renal clear cell carcinoma (KIRC). Despite the established role of glycolytic metabolism in cancer pathophysiology, the prognostic implications and key targets in KIRC remain elusive. We analyzed GEO and TCGA datasets to identify DEGs in KIRC and studied their relationship with immune gene expression, survival, tumor stage, gene mutations, and infiltrating immune cells. We explored Pgam1 gene expression in different kidney regions using spatial transcriptomics after mouse kidney injury analysis. Single-cell RNA-sequencing was used to assess the association of PGAM1 with immune cells. Findings were validated with tumor specimens from 60 KIRC patients, correlating PGAM1 expression with clinicopathological features and prognosis using bioinformatics and immunohistochemistry. We demonstrated the expression of central gene regulators in renal cancer in relation to genetic variants, deletions, and tumor microenvironment. Mutations in these hub genes were positively associated with distinct immune cells in six different immune datasets and played a crucial role in immune cell infiltration in KIRC. Single-cell RNA-sequencing revealed that elevated PGAM1 was associated with immune cell infiltration, specifically macrophages. Furthermore, pharmacogenomic analysis of renal cancer cell lines indicated that inactivation of PGAM1 was associated with increased sensitivity to specific small-molecule drugs. Altered PGAM1 in KIRC is associated with disease progression and immune microenvironment. It has diagnostic and prognostic implications, indicating its potential in precision medicine and drug screening.

A comprehensive prognostic and immunological analysis of telomere-related lncRNAs in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent malignant tumors of the urinary system, with a high recurrence and metastasis rate. Telomeres and long non-coding RNAs (lncRNAs) have been documented playing critical roles in cancer progression. However, the prognostic significance of telomere-related lncRNA (TRLs) in KIRC is less well-defined. The Cancer Genome Atlas database was applied to retrieve the expression profiles and corresponding clinical information of KIRC patients. To create the TRLs prognostic signature, univariate Cox regression, least absolute shrinkage and selection operator analyses were performed. The prognostic signature, comprised of nine prognostic TRLs, was developed and demonstrated superior prognostic ability for KIRC patients. Additionally, the risk score acted as an independent prognostic indicator. A nomogram incorporating age, grade, stage, and signature-based risk scores was also developed and exhibited excellent predictive accuracy. Several immune activities were associated with the signature, as determined by gene function analysis. Further analysis revealed differences in the status of immunity and the tumor microenvironment between low- and high-risk groups. Notably, KIRC patients with high-risk scores were more responsive to immunotherapy and chemotherapy. To summarize, our study developed a new prognostic signature consisting of nine telomere-related lncRNA that can precisely predict the prognosis of KIRC patients. The signature was shown to be of substantial value for the tumor microenvironment and tumor mutation burden, thereby contributing to a framework for the individualized treatment of patients.

ARPC1B is a novel prognostic biomarker for kidney renal clear cell carcinoma and correlates with immune infiltration

Background: Actin-related protein 2/3 complex subunit 1B (ARPC1B) is reported to be involved in tumorigenesis and progression. However, its role in kidney renal clear cell carcinoma (KIRC), correlation with tumor-infiltrating immune cells, and prognostic significance remain unclear. Methods: Data sets from the TCGA, GTEx, GEPIA, GEO, UALCAN, and CPTAC databases were extracted and analyzed to investigate the expression difference, prognosis, and clinicopathological features of ARPC1B. Single-sample Gene Set Enrichment Analysis (ssGSEA), CIBERSORT, and TISCH2 analysis were used to examine the relationship between ARPC1B expression and tumor immune infiltration in KIRC. The potential function of ARPC1B in KIRC was explored by GO functional annotation and KEGG pathway analysis. The TIDE algorithm was used to predict and analyze the relationship between ARPC1B expression and response to immune checkpoint blockade (ICB). The expression of ARPC1B was further validated by using quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). Results: The study showed that ARPC1B expression was an independent prognostic factor of KIRC, with high ARPC1B expression being associated with poor overall survival (OS). Enrichment of GO annotation and pathway analysis showed multiple immune-related functional pathways affected by ARPC1B such as regulation of immune effector process, inflammatory response regulation, antigen processing and presentation, asthma, autoimmune thyroid disease, graft versus host disease, intestinal immune network for IgA production, and type I diabetic mellitus. Moreover, ARPC1B expression positively correlated with infiltrating levels of myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) in KIRC. Importantly, high ARPC1B expression predicted a low response to ICB in KIRC. Conclusion: This study indicates that ARPC1B expression is an independent prognostic biomarker for OS in KIRC patients. High ARPC1B expression is closely associated with MDSCs and Tregs infiltration. These findings suggest that ARPC1B may serve as a biomarker for prognosis and immune infiltration in KIRC, potentially aiding in the development of novel treatment strategies to improve the survival outcomes for KIRC patients.

Endogenous retrovirus group FRD member 1 is a potential biomarker for prognosis and immunotherapy for kidney renal clear cell carcinoma

Introduction

The activation of endogenous retroviral (ERV) genes in kidney renal clear cell carcinoma (KIRC) suggests the necessity for further research on their functions.

Methods

In this study, KIRC and healthy cohorts were obtained from TGGA and GEO datasets. Subsequently, differential analysis and functional annotation were conducted using GO, KEGG, and GSEA. Clinical outcomes were then observed and utilized in the development of a nomogram.

Results

We observed the general low expression of ERVFRD-1 in KIRC tumors compared to normal tissue (P < 0.001) across multiple cohorts. Differential analysis and functional annotation using GO, KEGG, GSEA analysis revealed significant involvement of ERVFRD-1 in tumor immunoregulation: a close relation to the infiltration levels of mast cells and Treg cell (P < 0.001) and occurrence with a variety of immune markers. Methylation status was then applied to uncover potential mechanisms of ERVFRD-1 in KIRC. Notably, higher expression levels of ERVFRD-1 were associated with extended overall survival, disease-specific survival, and progression-free survival. Finally, based on Cox regression analysis, we constructed a nomogram incorporating ERVFRD-1, pathologic T, and age, which exhibited promising predictive power in assessing the survival outcomes of KIRC patients.

Discussion

To sum up, our study suggests that ERVFRD-1 plays a role in regulating immunological activity within the tumor microenvironment and is associated with overall survival in KIRC patients. ERVFRD-1 may therefore be a sensitive biomarker for diagnosis, immunotherapy, and prognosis assessment of KIRC.

Cuproptosis-Related 4-Gene Risk Model for Predicting Immunotherapy Drug Response and Prognosis of Kidney Renal Clear Cell Carcinoma

Background Kidney renal clear cell carcinoma (KIRC) is one of the most common renal malignancies with a high mortality rate. Cuproptosis, a novel form of cell death, is strongly linked to mitochondrial metabolism and is mediated by protein lipoylation, leading to a proteotoxic stress response and cell death. To date, few studies have ellucidated the holistic role of cuproptosis-related genes (CRGs) in the pathogenesis of KIRC.Methods We comprehensively and completely analyzed the RNA sequencing data and corresponding clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We screened for differentially expressed CRGs and constructed a prognostic risk model using univariate and multivariate Cox proportional regression analyses. Kaplan-Meier analysis was performed and receiver operating characteristic (ROC) curves were plotted to predict the prognosis of KIRC patients. Functional enrichment analysis was utilized to explore the internal mechanisms. Immune-related functions were analyzed using single-sample gene set enrichment analysis (ssGSEA), tumour immune dysfunction and exclusion (TIDE) scores, and drug sensitivity analysis.Results We established a concise prognostic risk model consisting of four CRGs (DBT, DLAT, LIAS and PDHB) to predict the overall survival (OS) in KIRC patients. The results of the survival analysis indicated a significantly lower OS in the high-risk group as compared to the patients in the low-risk group. The area under the time-dependent ROC curve (AUC) at 1, 3, and 5 year was 0.691, 0.618, and 0.614 in KIRC. Functional enrichment analysis demonstrated that CRGs were significantly enriched in tricarboxylic acid (TCA) cycle-related processes and metabolism-related pathways. Sorafenib, doxorubicin, embelin, and vinorelbine were more sensitive in the high-risk group.Conclusions We constructed a concise CRGs risk model to evaluate the prognosis of KIRC patients and this may be a new direction for the diagnosis and treatment of KIRC.

Identification of immunogenic cell death-related signature on prognosis and immunotherapy in kidney renal clear cell carcinoma

Background

Immunogenic cell death (ICD) is considered a particular cell death modality of regulated cell death (RCD) and plays a significant role in various cancers. The connection between kidney renal clear cell carcinoma (KIRC) and ICD remains to be thoroughly explored.

Methods

We conducted a variety of bioinformatics analyses using R software, including cluster analysis, prognostic analysis, enrichment analysis and immune infiltration analysis. In addition, we performed Quantitative Real-time PCR to evaluate RNA levels of specific ICD genes. The proliferation was measured through Cell Counting Kit-8 (CCK-8) assay and colony-formation assay in RCC cell lines.

Results

We determined two ICD subtypes through consensus clustering analysis. The two subtypes showed significantly different clinical outcomes, genomic alterations and tumor immune microenvironment. Moreover, we constructed the ICD prognostic signature based on TF, FOXP3, LY96, SLC7A11, HSP90AA1, UCN, IFNB1 and TLR3 and calculated the risk score for each patient. Kaplan-Meier survival analysis and ROC curve demonstrated that patients in the high-risk group had significantly poorer prognosis compared with the low-risk group. We then validated the signature through external cohort and further evaluated the relation between the signature and clinical features, tumor immune microenvironment and immunotherapy response. Given its critical role in ICD, we conducted further analysis on LY96. Our results indicated that downregulation of LY96 inhibited the proliferation ability of RCC cells.

Conclusions

Our research revealed the underlying function of ICD in KIRC and screened out a potential biomarker, which provided a novel insight into individualized immunotherapy in KIRC.

The combination of NDUFS1 with CD4+ T cell infiltration predicts favorable prognosis in kidney renal clear cell carcinoma

Background: Kidney renal clear cell carcinoma (KIRC) is an immunogenic tumor, and immune infiltrates are relevant to patients' therapeutic response and prognosis. NDUFS1, the core subunit of mitochondrial complex I, has been reported to be associated with KIRC patients' prognosis. However, the upstream regulator for NDUFS1 and their correlations with immune infiltration remain unclear. Methods: The expression of NDUFS genes in KIRC and their influences on patients' survival were investigated by UALCAN, ENCORI, Oncomine, TIMER as well as Kaplan-Meier Plotter. miRNAs regulating NDUFS1 were predicted and analyzed by TargetScan and ENCORI. The correlations between NDUFS1 expression and immune cell infiltration or gene marker sets of immune infiltrates were analyzed via TIMER. The overall survival in high/low NDUFS1 or hsa-miR-320b expressed KIRC patients with or without immune infiltrates were analyzed via Kaplan-Meier Plotter. The combined NDUFS1 expression and/or CD4⁺ T cell infiltration on KIRC patients' overall survival were validated by multiplexed immunofluorescence (mIF) staining in tissue microarray (TMA). Furthermore, the influences of NDUFS1 expression on the chemotaxis of CD4⁺ T cells to KIRC cells were performed by transwell migration assays. Results: We found that the low expression of NDUFS1 mRNA and protein in KIRC was correlated with unfavorable patients' survival and poor infiltration of CD4⁺ T cells. In patients with decreased CD4⁺ T cell infiltration whose pathological grade less than III, TMA mIF staining showed that low expression of NDUFS1 had significantly poor OS than that with high expression of NDUFS1 did. Furthermore, hsa-miR-320b, a possible negative regulator of NDUFS1, was highly expressed in KIRC. And, low NDUFS1 or high hsa-miR-320b consistently correlated to unfavorable outcomes in KIRC patients with decreased CD4⁺ T cell infiltration. In vitro, NDUFS1 overexpression significantly increased the chemotaxis of CD4⁺ T cell to KIRC cells. Conclusion: Together, NDUFS1, upregulated by decreased hsa-miR-320b expression in KIRC patients, might act as a biomarker for CD4⁺ T cell infiltration. And, the combination of NDUFS1 with CD4⁺ T cell infiltration predicts favorable prognosis in KIRC.

Construction and validation of a model based on immunogenic cell death-associated lncRNAs to predict prognosis and direct therapy for kidney renal clear cell carcinoma

BACKGROUND

Immunogenic cell death (ICD) is an important part of the antitumor effect, yet the role played by long noncoding RNAs (lncRNAs) remains unclear. We explored the value of ICD-related lncRNAs in tumor prognosis assessment in kidney renal clear cell carcinoma (KIRC) patients to provide a basis for answering the above questions.

METHODS

Data on KIRC patients were obtained from The Cancer Genome Atlas (TCGA) database, prognostic markers were identified, and their accuracy was verified. An application-validated nomogram was developed based on this information. Furthermore, we performed enrichment analysis, tumor mutational burden (TMB) analysis, tumor microenvironment (TME) analysis, and drug sensitivity prediction to explore the mechanism of action and clinical application value of the model. RT-qPCR was performed to detect the expression of lncRNAs.

RESULTS

The risk assessment model constructed using eight ICD-related lncRNAs provided insight into patient prognoses. Kaplan-Meier (K-M) survival curves showed a more unfavorable outcome in high-risk patients (p<0.001). The model had good predictive value for different clinical subgroups, and the nomogram constructed based on this model worked well (risk score AUC=0.765). Enrichment analysis revealed that mitochondrial function-related pathways were enriched in the low-risk group. The adverse prognosis of the higher-risk cohort might correspond to a higher TMB. The TME analysis revealed a higher resistance to immunotherapy in the increased-risk subgroup. Drug sensitivity analysis can guide the selection and application of antitumor drugs in different risk groups.

CONCLUSIONS

This prognostic signature based on eight ICD-associated lncRNAs has significant implications for prognostic assessment and treatment selection in KIRC.

Gene set enrichment analysis identifies immune subtypes of kidney renal clear cell carcinoma with significantly different molecular and clinical properties

Background

Kidney renal clear cell carcinoma (KIRC) is the most prevalent renal malignancy, marked by a high abundance of tumor-infiltrating lymphocytes (TILs) and an unfavorable prognosis upon metastasis. Numerous studies have demonstrated that KIRC possesses a tumor microenvironment that is highly heterogeneous, and this is associated with significant variations in the effectiveness of most first-line drugs administered to KIRC patients. Therefore, it is crucial to classify KIRC based on the tumor microenvironment, although these subtyping techniques are still inadequate.

Methods

By applying gene set enrichment scores of 28 immune signatures, we conducted a hierarchical clustering of KIRC and determined its immune subtypes. In addition, we conducted a comprehensive exploration of the molecular and clinical features of these subtypes, including survival prognosis, proliferation, stemness, angiogenesis, tumor microenvironment, genome instability, intratumor heterogeneity, and pathway enrichment.

Results

Through cluster analysis, two immune subtypes of KIRC were identified and termed Immunity-High (Immunity-H) and Immunity-Low (Immunity-L). This clustering outcome was consistent in four independent KIRC cohorts. The subtype Immunity-H exhibited elevated levels of TILs, tumor aneuploidy, homologous recombination deficiency, stemness, and proliferation potential, along with a poorer prognosis for survival. Despite this, the Immunity-L subtype demonstrated elevated intratumor heterogeneity and a stronger angiogenesis signature in contrast to Immunity-H. According to the results of pathway enrichment analysis, the Immunity-H subtype was found to be highly enriched in immunological, oncogenic, and metabolic pathways, whereas the Immunity-L subtype was highly enriched in angiogenic, neuroactive ligand-receptor interaction, and PPAR pathways.

Conclusions

Based on the enrichment of immune signatures in the tumor microenvironment, KIRC can be categorized into two immune subtypes. The two subtypes demonstrate considerably distinct molecular and clinical features. In KIRC, an increase in immune infiltration is linked to a poor prognosis. Patients with Immunity-H KIRC may exhibit active responses to PPAR and immune checkpoint inhibitors, whereas patients with Immunity-L may manifest favorable responses to anti-angiogenic agents and immune checkpoint inhibitors. The immunological classification provides molecular insights into KIRC immunity, as well as clinical implications for the management of this disease.

A novel prognostic signature of chemokines for survival and immune infiltration in kidney renal clear cell carcinoma

Objective: Studies have revealed the alteration of chemokines in the tumour microenvironment in renal clear cell carcinoma (KIRC), which is closely related with immune infiltration and the prognosis of patients with KIRC. This research aims to comprehensively clarify the signature of chemokines in KIRC and the correlation between chemokines and immune infiltration in the TME of KIRC. Methods: The chemokine expression in KIRC were investigated by using multiple multiomics and bioinformatics tools. Hub-chemokines that were significantly related with the cancer stage and survival were identified. The role of hub-chemokines in the tumor microenvironment of KIRC was further assessed by using enrichment analysis, cancer-related pathway and immune infiltration analysis. Results: A total of 20 chemokines were significantly elevated in KIRC. Based on the correlation with KIRC stages and survival, 13 hub-chemokines were identified. Among the hub-chemokines, the high expression of CXCL2, CXCL5 and CXCL13 were related with worse survival of KIRC patients. The hub-chemokines were associated with the activation of multiple cancer-related signaling pathways. The functions of hub-chemokines were mainly enriched in chemokine-mediated signaling pathway, immunocytes chemotaxis and chemokine activity. CCL4, CCL5, CXCL9, CXCL10 and CXCL11 were related with various types immune infiltration such as CD8⁺T cell, neutrophil, B cell and dendritic cell. Using the hub-chemokine CXCL10, multiple immune checkpoints including LAG3, CTLA-4 and PD-1 were identified. Conclusion: Our research sheds light on the chemokines and their important role in promoting the tumor microenvironment of KIRC. The findings could provide more data about the prognosis prediction and treatment targets for KIRC.

Cuproptosis-related LINC01711 promotes the progression of kidney renal clear cell carcinoma

This study utilized The Cancer Genome Atlas (TCGA) database to identify cuproptosis-related long non-coding RNAs (CRlncRNAs) in patients with kidney renal clear cell carcinoma (KIRC) which was further applied to construct risk signatures. All KIRC patients were divided into the training and the validation sets at a ratio of 7:3. Lasso regression analysis identified two prognosis-associated CRlncRNAs (LINC01204 and LINC01711), and prognostic risk signatures were constructed in both the training and the validation sets. Kaplan-Meier survival curves showed that patients with high-risk scores had significantly shorter overall survival (OS) than those with low-risk scores both in both the training and the validation sets. The area under the curve (AUC) of the prognostic nomogram generated based on age, grade, stage and risk signature to predict the 1-, 3- and 5-year OS were 0.84, 0.81 and 0.77, respectively, and the calibration curves also showed the high accuracy of the nomogram. In addition, we constructed the LINC01204/LINC01711-miRNA-mRNA ceRNA network graph. Finally, we experimentally investigated the function of LINC01711 by knocking down LINC01711 and revealed that knockdown of LINC01711 inhibited the proliferation, migration and invasion of KIRC cells. Hence, in this study, we developed a signature of prognostic risk-associated CRlncRNAs that could accurately predict the prognosis of KIRC patients and constructed a related ceRNA network to shed light on the mechanistic study of KIRC. LINC01711 might serve as a potential biomarker for the early diagnosis and prognosis of KIRC patients.

Overexpression of DBT suppresses the aggressiveness of renal clear cell carcinoma and correlates with immune infiltration

Conventional therapy for kidney renal clear cell carcinoma (KIRC) is unpromising. The tumor microenvironment (TME) is intimately linked to the invasiveness of a variety of tumor forms, including KIRC. The purpose of this research is to establish the prognostic and immune-related significance of dihydrolipoamide branched chain transacylase E2 (DBT) in individuals with KIRC. In this investigation, we discovered that DBT expression was down-regulated in a range of human malignancies, and low DBT expression in KIRC was linked to higher-level clinicopathological characteristics as well as a poor prognosis for KIRC patients. Based on the findings of univariate and multivariate Cox regression analyses, DBT might be employed as an independent prognostic factor in KIRC patients. Furthermore, we developed a nomogram to better investigate DBT's predictive usefulness. To confirm DBT expression, we examined KIRC cell lines using RT-qPCR and Western blotting. We also examined the role of DBT in KIRC using colony formation, CCK-8, EdU, transwell, and wound healing assays. We discovered that plasmid-mediated overexpression of DBT in KIRC cells slowed cell proliferation and decreased migration and invasion. Multiple enrichment analyses revealed that DBT may be involved in processes and pathways related to immunotherapy and drug metabolism. We computed the immune infiltration score and discovered that the immunological score and the ESTIMATE score were both greater in the DBT low expression group. According to the CIBERSORT algorithm, DBT seems to promote anti-cancer immune responses in KIRC by activating M1 macrophages, mast cells, and dendritic cells while inhibiting regulatory T cells. Finally, in KIRC, DBT expression was found to be highly linked to immunological checkpoints, targeted medicines, and immunotherapeutic agents. Our findings suggest that DBT is a distinct predictive biomarker for KIRC patients, playing a significant role in the TME of KIRC and serving as a reference for the selection of targeted treatment and immunotherapy.

TROAP Promotes the Proliferation, Migration, and Metastasis of Kidney Renal Clear Cell Carcinoma with the Help of STAT3

Kidney renal clear cell carcinoma (KIRC) is a subtype of renal cell carcinoma that threatens human health. The mechanism by which the trophinin-associated protein (TROAP)-an important oncogenic factor-functions in KIRC has not been studied. This study investigated the specific mechanism by which TROAP functions in KIRC. TROAP expression in KIRC was analyzed using the RNAseq dataset from the Cancer Genome Atlas (TCGA) online database. The Mann-Whitney U test was used to analyze the expression of this gene from clinical data. The Kaplan-Meier method was used for the survival analysis of KIRC. The expression level of TROAP mRNA in the cells was detected using qRT-PCR. The proliferation, migration, apoptosis, and cell cycle of KIRC were detected using Celigo, MTT, wound healing, cell invasion assay, and flow cytometry. A mouse subcutaneous xenograft experiment was designed to demonstrate the effect of TROAP expression on KIRC growth in vivo. To further investigate the regulatory mechanism of TROAP, we performed co-immunoprecipitation (CO-IP) and shotgun liquid chromatography-tandem mass spectrometry (LC-MS). TCGA-related bioinformatics analysis showed that TROAP was significantly overexpressed in KIRC tissues and was related to higher T and pathological stages, and a poor prognosis. The inhibition of TROAP expression significantly reduced the proliferation of KIRC, affected the cell cycle, promoted cell apoptosis, and reduced cell migration and invasion. The subcutaneous xenograft experiments showed that the size and weight of the tumors in mice were significantly reduced after TROAP-knockdown. CO-IP and post-mass spectrometry bioinformatics analyses revealed that TROAP may combine with signal transducer and activator of transcription 3 (STAT3) to achieve tumor progression in KIRC; this was verified by functional recovery experiments. TROAP may regulate KIRC proliferation, migration, and metastasis by binding to STAT3.

Supervised Learning and Multi-Omics Integration Reveals Clinical Significance of Inner Membrane Mitochondrial Protein (IMMT) in Prognostic Prediction, Tumor Immune Microenvironment and Precision Medicine for Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) accounts for approximately 75% of all renal cancers. The prognosis for patients with metastatic KIRC is poor, with less than 10% surviving five years after diagnosis. Inner membrane mitochondrial protein (IMMT) plays a crucial role in shaping the inner mitochondrial membrane (IMM), regulation of metabolism and innate immunity. However, the clinical relevance of IMMT in KIRC is not yet fully understood, and its role in shaping the tumor immune microenvironment (TIME) remains unclear. This study aimed to investigate the clinical significance of IMMT in KIRC using a combination of supervised learning and multi-omics integration. The supervised learning principle was applied to analyze a TCGA dataset, which was downloaded and split into training and test datasets. The training dataset was used to train the prediction model, while the test and the entire TCGA dataset were used to evaluate its performance. Based on the risk score, the cutoff between the low and high IMMT group was set at median value. A Kaplan-Meier curve, receiver operating characteristic (ROC) curve, principal component analysis (PCA) and Spearman's correlation were conducted to evaluate the prediction ability of the model. Gene Set Enrichment Analysis (GSEA) was used to investigate the critical biological pathways. Immunogenicity, immunological landscape and single-cell analysis were performed to examine the TIME. Databases including Gene Expression Omnibus (GEO), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were employed for inter-database verification. Pharmacogenetic prediction was analyzed via single-guide RNA (sgRNA)-based drug sensitivity screening using Q-omics v.1.30. Low expressions of IMMT in tumor predicted dismal prognosis in KIRC patients and correlated with KIRC progression. GSEA revealed that low expressions of IMMT were implicated in mitochondrial inhibition and angiogenetic activation. In addition, low IMMT expressions had associations with reduced immunogenicity and an immunosuppressive TIME. Inter-database verification corroborated the correlation between low IMMT expressions, KIRC tumors and the immunosuppressive TIME. Pharmacogenetic prediction identified lestaurtinib as a potent drug for KIRC in the context of low IMMT expressions. This study highlights the potential of IMMT as a novel biomarker, prognostic predictor and pharmacogenetic predictor to inform the development of more personalized and effective cancer treatments. Additionally, it provides important insights into the role of IMMT in the mechanism underlying mitochondrial activity and angiogenesis development in KIRC, which suggests IMMT as a promising target for the development of new therapies.

Expression and clinical significance of DOK3 in renal clear cell carcinoma

OBJECTIVES

Docking Protein 3 (DOK3) is an adapter protein that has been implicated in various cellular processes relevant to diseases, such as cancer. In this study, we aimed to evaluate the role of DOK3 in kidney renal clear cell carcinoma (KIRC) by examining how its expression levels are correlated with patient characteristics and prognosis.

METHODS

We analyzed KIRC-related data from The Cancer Genome Atlas and used several bioinformatics tools, such as LinkedOmics and Oncomine, to evaluate DOK3 mRNA expression in KIRC. DOK3 protein expression was examined in 150 clinical KIRC samples and 100 non-cancerous renal tissues with immunohistochemistry assays. The prognostic value of DOK3 mRNA expression on patient overall survival was analyzed retrospectively using Kaplan-Meier survival and Cox regression analyses.

RESULTS

DOK3 mRNA expression was notably higher in KIRC samples compared with normal tissues. Significant correlations were found between DOK3 mRNA expression levels and tumor size, lymph node metastasis, distant metastasis, and pathological grade using the bioinformatics data. This was confirmed at the protein level with immunohistochemistry data. Survival analyses indicated that elevated DOK3 expression is linked to a lower overall survival rate in KIRC patients.

CONCLUSIONS

DOK3 is a potential biomarker for determining KIRC patient clinical prognosis.

Bioinformatics Prediction and Experimental Verification Identify CAB39L as a Diagnostic and Prognostic Biomarker of Kidney Renal Clear Cell Carcinoma

Background and Objectives: Calcium-binding protein 39-like (CAB39L) has been reported to be downregulated and possessed diagnostic and prognostic values in several types of cancer. However, the clinical value and mechanism of CAB39L in kidney renal clear cell carcinoma (KIRC) remain unclear. Materials and Methods: Bioinformatics analysis was conducted using different databases including TCGA, UALCAN, GEPIA, LinkedOmics, STRING, and TIMER. One-way variance analysis and t-test were chosen to investigate the statistical differences of CAB39L expression in KIRC tissues with different clinical characteristics. The receiver operating characteristic (ROC) curve was chosen to assess the discriminatory capacity of CAB39L. Kaplan-Meier curves were employed for assessing the influence of CAB39L on the progression-free survival (PFS), disease-specific survival (DSS), and overall survival (OS) of KIRC patients. The independent prognostic significance of clinical parameters for OS such as CAB39L expression in KIRC patients was estimated by Cox analysis. A series of in vitro functional experiments and Western blot (WB) and immunohistochemistry (IHC) were used to validate the relative protein expression and function of CAB39L. Results: The mRNA and protein levels of CAB39L were relatively downregulated in KIRC samples. Meanwhile, hypermethylation of the CAB39L promoter region was possibly associated with its low expression in KIRC. The ROC curve showed that the mRNA expression of CAB39L had a strong diagnostic value for both early and late KIRC. Kaplan-Meier survival curves indicated that a higher mRNA level of CAB39L predicted good PFS, DSS, and OS. The mRNA expression of CAB39L was an independent prognostic factor (hazard ratio = 0.6, p = 0.034) identified by multivariate Cox regression analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis exhibited that CAB39L was mainly associated with substance and energy metabolism. Finally, overexpression of CAB39L impaired the proliferation and metastasis of KIRC cells in vitro. Conclusions: CAB39L possesses prognostic and diagnostic capacity in KIRC.

Expression profile and prognostic values of GATA family members in kidney renal clear cell carcinoma

To investigate the possible diagnostic and prognostic biomarkers of kidney renal clear cell carcinoma (KIRC), an integrated study of accumulated data was conducted to obtain more reliable information and more feasible measures. Using the Tumor Immune Estimation Resource (TIMER), University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), Human Protein Atlas (HPA), Kaplan-Meier plotter database, Gene Expression Profiling Interactive Analysis (GEPIA2) database, cBioPortal, and Metascape, we analyzed the expression profiles and prognoses of six members of the GATA family in patients with KIRC. Compared to normal samples, KIRC samples showed significantly lower GATA2/3/6 mRNA and protein expression levels. KIRC's pathological grades, clinical stages, and lymph node metastases were closely related to GATA2 and GATA5 levels. Patients with KIRC and high GATA2 and GATA5 expression had better overall survival (OS) and recurrence-free survival (RFS), while those with higher expression of GATA3/4/6 had worse outcomes. The role and underlying mechanisms of the GATA family in cell cycle, cell proliferation, metabolic processes, and other aspects were evaluated based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses. Furthermore, we found that infiltrating immune cells were highly correlated with GATA expression profiles. These results showed that GATA family members may serve as prognostic biomarkers and therapeutic targets for KIRC.

LRP2 and DOCK8 Are Potential Antigens for mRNA Vaccine Development in Immunologically 'Cold' KIRC Tumours

The administration of mRNA-based tumour vaccines is considered a promising strategy in tumour immunotherapy, although its application against kidney renal clear cell carcinoma (KIRC) is still at its infancy stage. The purpose of this study was to identify potential antigens and to further select suitable patients for vaccination. Gene expression data and clinical information were retrieved from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. GEPIA2 was used to evaluate the prognostic value of selected antigens. The relationship of antigens presenting cell infiltration with antigen expression was evaluated by TIMER, and immune subtypes were determined using unsupervised cluster analysis. Tumour antigens LRP2 and DOCK8, which are associated with prognosis and tumour-infiltrating antigen-presenting cells, were identified in KIRC. A total of six immune subtypes were identified, and patients with immune subtype 1-4 (IS1-4) tumours had an immune 'cold' phenotype, a higher tumour mutation burden, and poor survival. Moreover, these immune subtypes showed significant differences in the expression of immune checkpoint and immunogenic cell death modulators. Finally, the immune landscape of KIRC revealed the immune-related cell components in individual patients. This study suggests that LRP2 and DOCK8 are potential KIRC antigens in the development of mRNA vaccines, and patients with immune subtypes IS1-4 are suitable for vaccination.

Prognostic biomarker NEIL3 and its association with immune infiltration in renal clear cell carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is a malignant tumor with a high degree of immune infiltration. Identifying immune biomarkers is essential for the treatment of KIRC. Studies have identified the potential of NEIL3 to modulate the immune microenvironment and promote tumor progression. However, the role of NEIL3 in KIRC remains uncertain. This study was to investigate the effect of NEIL3 on the prognosis and immune infiltration of patients with KIRC.

Methods

TCGA and GEO databases were used to study the expression of NEIL3 in KIRC. Cox regression analysis was used to examine the relationship between the expression of NEIL3 and clinicopathological variables and survival. Furthermore, Gene Set Cancer Analysis (GSCA) was applied to study the impact of NEIL3 methylation on outcomes of KIRC. Through gene ontology (GO) and Gene set enrichment (GSEA) analysis, the biological processes and signal pathways related to NEIL3 expression were identified. In addition, immune infiltration analysis was conducted via CIBERSORT analysis, ssGSEA analysis and TISIDB database.

Results

NEIL3 was overexpressed in KIRC, and it was significantly related with histologic grade, pathologic stage, T stage, M stage, and vital status of KIRC patients (P < 0.001). The expression of NEIL3 was associated with worse outcomes. Univariate and multivariate Cox analysis showed that NEIL3 may be an indicator of adverse outcomes in KIRC. GSEA analysis revealed that NEIL3 may be involved in signal pathways including cell cycle, DNA replication, mismatch repair, P53 signal pathway, and antigen processing and presentation. In addition, immune infiltration analysis showed a positive correlation between NEIL3 expression and multiple immune cells (activated CD8 T cells, activated dendritic cells, myeloid-derived suppressor cells, follicular helper T cells, and regulatory T cells) and immunoinhibitors (PD1, CTLA4, LAG3, TIGHT, IL10, and CD96).

Conclusion

NEIL3 is a potential independent biomarker of KIRC, which is relevant to immune infiltration.

Cuproptosis-related gene FDX1 as a prognostic biomarker for kidney renal clear cell carcinoma correlates with immune checkpoints and immune cell infiltration

Background: Kidney renal clear cell carcinoma (KIRC) is not sensitive to radiotherapy and chemotherapy, and only some KIRC patients can benefit from immunotherapy and targeted therapy. Cuproptosis is a new mechanism of cell death, which is closely related to tumor progression, prognosis and immunity. The identification of prognostic markers related to cuproptosis in KIRC may provide targets for treatment and improve the prognosis of KIRC patients. Methods: Ten cuproptosis-related genes were analyzed for differential expression in KIRC-TCGA and a prognostic model was constructed. Nomogram diagnostic model was used to screen independent prognostic molecules. The screened molecules were verified in multiple datasets (GSE36895 and GSE53757), and in KIRC tumor tissues by RT-PCR and immunohistochemistry (IHC). Clinical correlation of cuproptosis-related independent prognostic molecules was analyzed. According to the molecular expression, the two groups were divided into high and low expression groups, and the differences of immune checkpoint and tumor infiltrating lymphocytes (TILs) between the two groups were compared by EPIC algorithm. The potential Immune checkpoint blocking (ICB) response of high and low expression groups was predicted by the "TIDE" algorithm. Results: FDX1 and DLAT were protective factors, while CDKN2A was a risk factor. FDX1 was an independent prognostic molecule by Nomogram, and low expressed in tumor tissues compared with adjacent tissues (p < 0.05). FDX1 was positively correlated with CD274, HAVCR2, PDCD1LG2, and negatively correlated with CTLA4, LAG3, and PDCD1. The TIDE score of low-FDX1 group was higher than that of high-FDX1 group. The abundance of CD4⁺ T cells, CD8⁺ T cells and Endothelial cells in FDX1-low group was lower than that in FDX1-high group (p < 0.05). Conclusion: FDX1, as a key cuproptosis-related gene, was also an independent prognostic molecule of KIRC. FDX1 might become an interesting biomarker and potential therapeutic target for KIRC.

Construction and verification of a novel prognostic risk model for kidney renal clear cell carcinoma based on immunity-related genes

Background: Currently, there are no useful biomarkers or prognostic risk markers for the diagnosis of kidney renal clear cell carcinoma (KIRC), although recent research has shown that both, the onset and progression of KIRC, are substantially influenced by immune-associated genes (IAGs). Objective: This work aims to create and verify the prognostic value of an immune risk score signature (IRSS) based on IAGs for KIRC using bioinformatics and public databases. Methods: Differentially expressed genes (DEGs) related to the immune systems (IAGs) in KIRC tissues were identified from The Cancer Genome Atlas (TCGA) databases. The DEGs between the tumor and normal tissues were identified using gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, a prognostic IRSS model was constructed and its prognostic and predictive performance was analyzed using survival analyses and nomograms. Kidney renal papillary cell carcinoma (KIRP) sets were utilized to further validate this model. Results: Six independent immunity-related genes (PAEP, PI3, SAA2, SAA1, IL20RB, and IFI30) correlated with prognosis were identified and used to construct an IRSS model. According to the Kaplan-Meier curve, patients in the high-risk group had significantly poorer prognoses than those of patients in the low-risk group in both, the verification set (p <0.049; HR = 1.84; 95% CI = 1.02-3.32) and the training set (p < 0.001; HR = 3.12, 95% CI = 2.23-4.37). The numbers of regulatory T cells (Tregs) were significantly positively correlated with the six immunity-related genes identified, with correlation coefficients were 0.385, 0.415, 0.399, 0.451, 0.485, and 0.333, respectively (p <0.001). Conclusion: This work investigated the association between immune infiltration, immunity-related gene expression, and severity of KIRC to construct and verify a prognostic risk model for KIRC and KIRP.

Inhibition of Cyclin F Promotes Cellular Senescence through Cyclin-dependent Kinase 1-mediated Cell Cycle Regulation

OBJECTIVE

Kidney renal clear cell carcinoma (KIRC) is a common renal malignancy that has a poor prognosis. As a member of the F box family, cyclin F (CCNF) plays an important regulatory role in normal tissues and tumors. However, the underlying mechanism by which CCNF promotes KIRC proliferation still remains unclear.

METHODS

Bioinformatics methods were used to analyze The Cancer Genome Atlas (TCGA) database to obtain gene expression and clinical prognosis data. The CCK8 assay, EdU assay, and xenograft assay were used to detect cell proliferation. The cell senescence and potential mechanism were assessed by SA-β-gal staining, Western blotting, as well as ELISA.

RESULTS

Our data showed that CCNF was highly expressed in KIRC patients. Meanwhile, downregulation of CCNF inhibited cell proliferation in vivo and in vitro. Further studies showed that the reduction of CCNF promoted cell senescence by decreasing cyclin-dependent kinase 1 (CDK1), increasing the proinflammatory factors interleukin (IL)-6 and IL-8, and then enhancing the expression of p21 and p53.

CONCLUSION

We propose that the high expression of CCNF in KIRC may play a key role in tumorigenesis by regulating cell senescence. Therefore, CCNF shows promise as a new biomarker to predict the clinical prognosis of KIRC patients and as an effective therapeutic target.

PIK3C2A is a prognostic biomarker that is linked to immune infiltrates in kidney renal clear cell carcinoma

Background

Phosphoinositide 3-kinases (PI3Ks) are lipid enzymes that regulate a wide range of intracellular functions. In contrast to Class I and Class III PI3K, which have more detailed descriptions, Class II PI3K has only recently become the focus of functional research. PIK3C2A is a classical member of the PI3Ks class II. However, the role of PIK3C2A in cancer prognosis and progression remains unknown.

Methods

The expression pattern and prognostic significance of PIK3C2A in human malignancies were investigated using multiple datasets and scRNA-seq data. The PIK3C2A expression in renal clear cell carcinoma (KIRC) was then validated utilizing Western blot. The functional role of PIK3C2A in KIRC was assessed using combined function loss experiments with in vitro experiments. Furthermore, the correlation of PIK3C2A expression with tumor immunity was investigated in KIRC. The TCGA database was employed to investigate PIK3C2A functional networks.

Results

Significant decrease in PIK3C2A expression in KIRC, demonstrated that it potentially influences the prognosis of diverse tumors, particularly KIRC. In addition, PIK3C2A was significantly correlated with the T stage, M stage, pathologic stage, and histologic grade of KIRC. Nomogram models were constructed and used to predict patient survival based on the results of multivariate Cox regression analysis. PIK3C2A knockdown resulted in significantly increased KIRC cell proliferation. Of note, PIK3C2A expression demonstrated a significant correlation with the infiltrating levels of primary immune cells in KIRC.

Conclusion

These findings support the hypothesis that PIK3C2A is a novel biomarker for tumor progression and indicates dynamic shifts in immune infiltration in KIRC. Furthermore, aberrant PIK3C2A expression can influence the biological activity of cancer cells.

Mitochondrial phosphoenolpyruvate carboxykinase inhibits kidney renal clear cell carcinoma malignant progression, leading to cell energy metabolism imbalance

Mitochondrial phosphoenolpyruvate carboxykinase (PCK2) is a key gluconeogenesis enzyme. Its differential expression is related to kidney renal clear cell carcinoma (KIRC) malignancy, possibly by influencing energy metabolism. Therefore, it is possible that PKC2 plays a significant part in the emergence and progression of KIRC. To systematically and comprehensively identify the significance of PCK2 in KIRC, we further studied PCK2 in terms of its relationship to clinical features and various clinical subgroups' prognoses. Moreover, we verified the effect of PCK2 and KIRC cells using experimental methods. PCR and western blotting analyses confirmed PCK2 expression in KIRC cell lines and tissues. As a cell model, we constructed cells that overexpress PCK2. Proliferation was detected by EdU experiments. Scratch tests and transwell assays were used, respectively, to analyze cell migration and invasion. Mass spectrometry detected energy metabolite expression in KIRC cells. The findings revealed that KIRC patients with lower levels of PCK2 expression exhibited shorter progression-free intervals, shorter disease-specific survival, and shorter overall survival. The experimental results showed that compared with 293t, PCK2 was downregulated in three KIRC lines (OSRC-2, 786-O, and A498). Relative to surrounding tissues, PCK2 was downregulated in KIRC. PCK2 overexpression inhibited KIRC cell proliferation, migration, and invasion and upregulated energy metabolite expression. Mass spectrometry revealed that thiamine pyrophosphate, cyclic AMP, beta-D-fructose 6-phosphate, lactate, flavin mononucleotide, NAD, NADP, and D-glucose 6-phosphate were upregulated. PCK2 has the potential to serve as both a diagnostic and prognostic molecular biomarker for KIRC, as well as an independent prognostic risk factor for KIRC. It is hoped that PCK2 will emerge as a therapeutic target for KIRC.

Dissecting order amidst chaos of programmed cell deaths: construction of a diagnostic model for KIRC using transcriptomic information in blood-derived exosomes and single-cell multi-omics data in tumor microenvironment

Background

Kidney renal clear cell carcinoma (KIRC) is the most frequently diagnosed subtype of renal cell carcinoma (RCC); however, the pathogenesis and diagnostic approaches for KIRC remain elusive. Using single-cell transcriptomic information of KIRC, we constructed a diagnostic model depicting the landscape of programmed cell death (PCD)-associated genes, namely cell death-related genes (CDRGs).

Methods

In this study, six CDRG categories, including apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, were collected. RNA sequencing (RNA-seq) data of blood-derived exosomes from the exoRBase database, RNA-seq data of tissues from The Cancer Genome Atlas (TCGA) combined with control samples from the GTEx databases, and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were downloaded. Next, we intersected the differentially expressed genes (DEGs) of the KIRC cohort from exoRBase and the TCGA databases with CDRGs and DEGs obtained from single-cell datasets, further screening out the candidate biomarker genes using clinical indicators and machine learning methods and thus constructing a diagnostic model for KIRC. Finally, we investigated the underlying mechanisms of key genes and their roles in the tumor microenvironment using scRNA-seq, single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq), and the spatial transcriptomics sequencing (stRNA-seq) data of KIRC provided by the GEO database.

Result

We obtained 1,428 samples and 216,155 single cells. After the rational screening, we constructed a 13-gene diagnostic model for KIRC, which had high diagnostic efficacy in the exoRBase KIRC cohort (training set: AUC = 1; testing set: AUC = 0.965) and TCGA KIRC cohort (training set: AUC = 1; testing set: AUC = 0.982), with an additional validation cohort from GEO databases presenting an AUC value of 0.914. The results of a subsequent analysis revealed a specific tumor epithelial cell of TRIB3^high subset. Moreover, the results of a mechanical analysis showed the relatively elevated chromatin accessibility of TRIB3 in tumor epithelial cells in the scATAC data, while stRNA-seq verified that TRIB3 was predominantly expressed in cancer tissues.

Conclusions

The 13-gene diagnostic model yielded high accuracy in KIRC screening, and TRIB3^high tumor epithelial cells could be a promising therapeutic target for KIRC.

Low Expression of TSTD2 Serves as a Biomarker for Poor Prognosis in Kidney Renal Clear Cell Carcinoma

Introduction

Kidney renal clear cell carcinoma (KIRC) is a common cancer in people worldwide, and one of the main issues is developing suitable biomarkers. This study aims to investigate the expression of TSTD2 in KIRC and its impact on prognosis.

Methods

RNA sequencing data from TCGA and GTEx were gathered to examine the functional enrichment of TSTD2-related differentially expressed genes (DEGs) using GO/KEGG, GSEA, immunocyte permeation analysis, and protein-protein interaction (PPI) network analysis. The Kaplan‒Meier-Cox regression model and the prognostic nomograph model were used to assess the clinical importance of TSTD2 in KIRC. R software was used to analyze the included studies. Finally, verification of cells and tissues was performed using immunohistochemical staining and quantitative real‒time PCR.

Results

In contrast to normal samples, it was discovered that TSTD2 was underexpressed in a number of malignancies, including KIRC. Furthermore, in 163 KIRC samples, low expression of TSTD2 was linked to a poor prognosis, as were subgroups with age greater than 60, the integrin pathway, the development of elastic fibers, and high TNM stage, pathologic stage, and histologic grade (P < 0.05). Age and TNM stage were included in the nomogram prognostic model, and low TSTD2 was a prognostic predictor that could be used independently in Cox regression analysis. In addition, 408 DEGs with 111 upregulated genes and 297 downregulated genes were found between the high- and low-expression groups.

Conclusion

The diminished expression of TSTD2 may serve as a biomarker for unfavorable outcomes in KIRC, and holds potential as a target for therapeutic interventions.

The expression and significance of long non-coding RNA ITGB2-AS1 in renal clear cell carcinoma

OBJECTIVES

To explore the expression and significance of long non-coding RNA ITGB2-AS1 in kidney renal clear cell carcinoma (KIRC).

METHODS

The expression of ITGB2-AS1 in KIRC tissues of 45 KIRC patients in the first affiliated hospital of Henan University, Henan, China, from September 2018 to December 2020, KIRC cells were detected and the relationship of ITGB2-AS1 and overall survival of KIRC patients were analyzed. The expression of ITGB2-AS1 in KIRC cells Caki-1 and ACHN was interfered, and the changes of cell proliferation, invasion, migration, and apoptosis were detected. Dual luciferase reporter gene assay and RNA pull-down assay were carried out to verify the relationship between ITGB2-AS1 and miR-338-3p or miR-338-3p and epidermal growth factor receptor (EGFR). The expression of miR-338-3p and EGFR were detected after the interference of ITGB2-AS1.

RESULTS

The expression of ITGB2-AS1 was expressed highly in KIRC tissues and cells (p<0.05). The overall survival of KIRC patients with high ITGB2-AS1 was poorer than those with low ITGB2-AS1. In Caki-1 cell, downregulation of ITGB2-AS1 suppressed the cell proliferation, invasion and migration, promoted the cell apoptosis (p<0.05). In ACHN cell, upregulation of ITGB2-AS1 promoted the cell proliferation, invasion and migration and inhibited the apoptosis (p<0.05). The ITGB2-AS1 targeted and regulated the expression of miR-338-3p/EGFR.

CONCLUSION

The ITGB2-AS1 is expressed highly in KIRC and affects the survival of patients by regulating cell proliferation, invasion, and apoptosis.

Prognostic and immunological significance of calcium-related gene signatures in renal clear cell carcinoma

Background: Calcium signaling is implicated in multiple processes including immune response that important in tumor progression. Kidney renal clear cell carcinoma (KIRC) is the most frequent histological type of renal cell carcinoma with up to a third of cases develop metastases. As a result of a lack of in-depth understanding of the mechanisms underlying KIRC, treatment options have been limited. Here, we aim to comprehensively investigate the landscape of Ca²⁺ channels, pumps and exchangers in KIRC patients. Methods: The mRNA expression profiles and gene variations of 58 calcium-related genes (CRGs) in KIRC patients and normal control cases were downloaded from TCGA database. CRGs-related risk score was constructed to quantify calcium patterns by using least absolute shrinkage and selection operator (LASSO) regression. The prognostic value, biological functions, immune landscape and therapeutic sensitivities based on CRGs-related risk score were then evaluated using multiple methods. Finally, key gene of CRGs was identified by weighted gene co-expression network analysis (WGCNA). TCGA-CPTAC, GSE53757 datasets, as well as human tissues were used for validation. Results: KIRC patients had significant differences in CRG expression, prognosis, and biological functions between two CRG clusters. CRGs-related risk score was then determined. The prognosis, tumor mutation burden, immune cell infiltration, immune checkpoints, and the response of targeted inhibitors were remarkably different between high and low CRGs-related risk subtypes. CRGs-related high-risk subtype was characterized by immunosuppressive microenvironment with poor prognosis. Meanwhile, several targeted drugs showed distinct sensitivity between CRGs-related risk subtypes. Finally, TRPM3 was identified as a key CRG based on risk score in KIRC patients. TRPM3 mRNA and protein expression were significantly lower in KIRC tumors than in normal controls. Low TRPM3 expression was associated with poor prognosis in KIRC patients. Conclusion: Our study highlighted the promising prognostic value of CRGs in KIRC tumors. The evaluation of CRGs-related risk score will contribute to predicting prognosis and clinical therapy in KIRC patients.

Prognosis and pain dissection of novel signatures in kidney renal clear cell carcinoma based on fatty acid metabolism-related genes

Renal cell carcinoma (RCC) is a malignant tumor that is characterized by the accumulation of intracellular lipid droplets. The prognostic value of fatty acid metabolism-related genes (FMGs) in RCC remains unclear. Alongside this insight, we collected data from three RCC cohorts, namely, The Cancer Genome Atlas (TCGA), E-MTAB-1980, and GSE22541 cohorts, and identified a total of 309 FMGs that could be associated with RCC prognosis. First, we determined the copy number variation and expression levels of these FMGs, and identified 52 overall survival (OS)-related FMGs of the TCGA-KIRC and the E-MTAB-1980 cohort data. Next, 10 of these genes-FASN, ACOT9, MID1IP1, CYP2C9, ABCD1, CPT2, CRAT, TP53INP2, FAAH2, and PTPRG-were identified as pivotal OS-related FMGs based on least absolute shrinkage and selection operator and Cox regression analyses. The expression of some of these genes was confirmed in patients with RCC by immunohistochemical analyses. Kaplan-Meier analysis showed that the identified FMGs were effective in predicting the prognosis of RCC. Moreover, an optimal nomogram was constructed based on FMG-based risk scores and clinical factors, and its robustness was verified by time-dependent receiver operating characteristic analysis, calibration curve analysis, and decision curve analysis. We have also described the biological processes and the tumor immune microenvironment based on FMG-based risk score classification. Given the close association between fatty acid metabolism and cancer-related pain, our 10-FMG signature may also serve as a potential therapeutic target with dual effects on ccRCC prognosis and cancer pain and, therefore, warrants further investigation.

Prognostic value and immunological characteristics of a novel cuproptosis-related long noncoding RNAs risk signature in kidney renal clear cell carcinoma

Background: Cuproptosis has been found as a novel cell death mode significantly associated with mitochondrial metabolism, which may be significantly associated with the occurrence and growth of tumors. LncRNAs take on critical significance in regulating the development of kidney renal clear cell carcinoma (KIRC), whereas the correlation between cuproptosis-related LncRNAs (CRLs) and KIRC is not clear at present. Therefore, this study built a prognosis signature based on CRLs, which can achieve accurate prediction of the outcome of KIRC patients. Methods: The TCGA database provided the expression profile information and relevant clinical information of KIRC patients. Univariate Cox, Lasso, and multivariate Cox were employed for building a risk signature based on CRLs. Kaplan-Meier (K-M) survival analysis and time-dependent receiver operating characteristic (ROC) curve were employed for the verification and evaluation of the reliability and accuracy of risk signature. Then, qRT-PCR analysis of risk LncRNAs was conducted. Finally, the possible effect of the developed risk signature on the microenvironment for tumor immunization was speculated in accordance with ssGSEA and ESTIMATE algorithms. Results: A prognosis signature composed of APCDD1L-DT, MINCR, AL161782.1, and AC026401.3 was built based on CRLs. As revealed by the results of the K-M survival study, the OS rate and progression-free survival rate of highrisk KIRC patients were lower than those of lowrisk KIRC patients, and the areas under ROC curves of 1, 3, and 5 years were 0.828, 0.780, and 0.794, separately. The results of the immune analysis showed that there were significant differences in the status of immunization and the microenvironment of tumor between groups at low-risk and at high-risk. The qRT-PCR results showed that the relative expression level of MINCR and APCDD1L-DT were higher in 786-O and 769-P tumor cells than in HK-2 cells, which were normal renal tubular epithelial cells. Conclusion: The developed risk signature takes on critical significance in the prediction of the prognosis of patients with KIRC, and it can bring a novel direction for immunotherapy and clinical drug treatment of KIRC. In addition, 4 identified risk LncRNAs (especially APCDD1L-DT and MINCR) can be novel targets for immunotherapy of KIRC patients.

Clinical significance and immune landscape of cuproptosis-related lncRNAs in kidney renal clear cell carcinoma: a bioinformatical analysis

Background

Kidney renal clear cell carcinoma (KIRC) is considered an immunogenic tumor. Cuproptosis is a newly identified copper-induced regulated cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) have emerged as significant players in tumorigenesis and metastasis. However, there is a huge knowledge gap on the prognostic role of cuproptosis-related lncRNAs in KIRC. And, the clinical value of them is still unknown. Here, we aimed to develop a cuproptosis-related lncRNA prognostic signature in KIRC.

Methods

The messenger RNA (mRNA)/lncRNA expression profiles and the clinical information including age, gender, tumor stage, grade, and overall survival (OS) were acquired from The Cancer Genome Atlas (TCGA) database. The included KIRC samples were further randomly assigned into training (n=258) or testing (n=257) data sets. We performed Pearson correlation analysis to identify the cuproptosis-related lncRNAs and then constructed the prognostic signature using Cox regression analysis and LASSO algorithm. Subsequently, Kaplan-Meier survival analysis, a nomogram, and receiver operating characteristic (ROC) curve were performed to assess the predictive performance of the signature. Moreover, the immune characteristics and drug sensitivity related to the signature were also explored.

Results

The signature comprised 7 cuproptosis-related lncRNAs. The patients with a low-risk score had superior OS compared with those with a high-risk score. The survival rates of the high- and low-risk groups were 44.96% and 83.72% (P<0.001). The area under the curve (AUC) value for 1-, 3-, 5-year survival rate reached 0.814, 0.762 and 0.825, respectively. In addition, a nomogram was also generated; the AUC was 0.785 for risk score, higher than that for age (0.593), gender (0.489), grade (0.679), and stage (0.721). The high-risk group had more enriched immune- and tumor-related genes. Patients with low-risk scores were more sensitive to immunotherapy and the small molecular drugs GSK1904529A, tipifarnib, BX-912, FR-180204, and GSK1070916. Meanwhile, the high-risk group tended to be more sensitive to pyrimethamine, MS-275, and CGP-60474.

Conclusions

Collectively, we constructed a cuproptosis-related lncRNA prognostic signature with a higher predictive accuracy compared to multiple clinicopathological parameters, which may provide vital guidance for therapeutic strategies in KIRC. Combination of more prognostic biomarkers may further improve the accuracy.

Cuproptosis status affects treatment options about immunotherapy and targeted therapy for patients with kidney renal clear cell carcinoma

The development of immunotherapy has changed the treatment landscape of advanced kidney renal clear cell carcinoma (KIRC), offering patients more treatment options. Cuproptosis, a novel cell death mode dependent on copper ions and mitochondrial respiration has not yet been studied in KIRC. We assembled a comprehensive cohort of The Cancer Genome Atlas (TCGA)-KIRC and GSE29609, performed cluster analysis for typing twice using seven cuproptosis-promoting genes (CPGs) as a starting point, and assessed the differences in biological and clinicopathological characteristics between different subtypes. Furthermore, we explored the tumor immune infiltration landscape in KIRC using ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) and the potential molecular mechanisms of cuproptosis in KIRC using enrichment analysis. We constructed a cuproptosis score (CUS) using the Boruta algorithm combined with principal component analysis. We evaluated the impact of CUS on prognosis, targeted therapy, and immunotherapy in patients with KIRC using survival analysis, the predictions from the Cancer Immunome Atlas database, and targeted drug susceptibility analysis. We found that patients with high CUS levels show poor prognosis and efficacy against all four immune checkpoint inhibitors, and their immunosuppression may depend on TGFB1. However, the high-CUS group showed higher sensitivity to sunitinib, axitinib, and elesclomol. Sunitinib monotherapy may reverse the poor prognosis and result in higher progression free survival. Then, we identified two potential CPGs and verified their differential expression between the KIRC and the normal samples. Finally, we explored the effect of the key gene FDX1 on the proliferation of KIRC cells and confirmed the presence of cuproptosis in KIRC cells. We developed a targeted therapy and immunotherapy strategy for advanced KIRC based on CUS. Our findings provide new insights into the relationship among cuproptosis, metabolism, and immunity in KIRC.

Identification of Immune-Related Subtypes and Characterization of Tumor Microenvironment Infiltration in Kidney Renal Clear Cell Carcinoma

Background: Tumor microenvironment (TME) plays indisputable role in the progression of cancers. Immune cell infiltration (ICI) in TME was related to the prognosis of tumor patients. In this paper, we identified the pattern of immune-related ICI subtypes based on the TME immune infiltration pattern.

Methods: The data from kidney renal clear cell carcinoma data (KIRC) was downloaded from the TCGA database. The distinct ICI subtypes were identified using CIBERSORT and ESTIMATE algorithms. The gene subgroups were identified based on DEGs in ICI subtypes. The single sample gene set enrichment analysis (ssGSEA) was used to ascertain the ICI score. Kaplan-Meier curve with log-rank test was conducted to analyze the survival probability of patients with KIRC in different subtypes.

Results: The patients with high ICI scores exhibited a longer survival time and lower expression of checkpoint-related and immune activity-related genes. The high ICI score clusters were positively related to TMB. The patients in the low TMB subgroups have a favorable prognosis. The prediction ICI score did not affect the TMB status, and the low TMB subgroups + low/high ICI score subgroups exhibited better survival.

Conclusion: In all, the tumor immune microenvironment, ICI score, and TMB were important determinants of KIRC patients’ survival outcomes. The TMB + ICI score may be a potential biomarker for predicting the prognosis of patients and for targeted immunotherapies to treating KIRC.

Construction of a Prognostic Model for KIRC and Identification of Drugs Sensitive to Therapies - A Comprehensive Biological Analysis Based on m6A-Related LncRNAs

As one of the common malignancies in the urinary system, kidney cancer has been receiving explorations with respect to its pathogenesis, treatment and prognosis due to its high morbidity, high mortality and low drug efficiency. Such epigenetic modifications for RNA molecules as N6-methyladenosine (m6A) usher in another perspective for the research on tumor mechanisms, and an increasing number of biological processes and prognostic markers have been revealed. In this study, the transcriptome data, clinical data and mutation spectrum data of KIRC in the TCGA database were adopted to construct an m6A-related lncRNA prognostic model. Besides, the predictive ability of this model for clinical prognosis was evaluated, and some compounds sensitive to therapies for KIRC were screened. The findings of this study demonstrate that this effective and stable model has certain clinical application value.

Identification of a Five-miRNA Signature for Diagnosis of Kidney Renal Clear Cell Carcinoma

Motivation: Kidney renal clear cell carcinoma, which is a common type and accounts for 70-80% of renal cell carcinoma, can easily lead to metastasis and even death. A reliable signature for diagnosis of this cancer is in need. Hence, we seek to select miRNAs for identifying kidney renal clear cell carcinoma. Method: A feature selection strategy is used and improved to identify microRNAs for diagnosis of kidney renal clear cell carcinoma. Samples representing kidney renal clear cell carcinoma and normal tissues are split into training and testing groups. Accumulated scores representing the variable importance of each miRNA are derived from an iteration of resampling, training, and scoring. Those miRNAs with higher scores are selected based on the Gaussian mixture model. The sample split is repeated ten times to get more central miRNAs. Results: A total of 611 samples are downloaded from TCGA, each of which contains 1,343 miRNAs. The improved feature selection method is implemented, and five miRNAs are identified as a biomarker for diagnosis of kidney renal clear cell carcinoma. GSE151419 and GSE151423 are selected as the independent testing sets. Experimental results indicate the effectiveness of the selected signature. Both data-driven measurements and knowledge-driven evidence are given to show the effectiveness of our selection results.

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

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

An in silico investigation of SPC24 as a putative biomarker of Kidney Renal Clear Cell Carcinoma and Kidney Renal Papillary Cell Carcinoma for predicting prognosis and/or immune infiltration

BACKGROUND AND OBJECTIVE

SPC24 was reported to be correlated with the development of many cancers. However, its role in renal cancer was unclear. Our aim was to explore role of SPC24 in Kidney Renal Clear Cell Carcinoma (KIRC) and Kidney Renal Papillary Cell Carcinoma (KIRP) of types of renal cancer.

METHODS

SPC24 expression in KIRC and KIRP were firstly analyzed. Subsequently, the correlation between SPC24 expression and TNM staging of KIRC and KIRP and accuracy of SPC24 in diagnosing KIRC and KIRP were explored. Moreover, the correlation between SPC24 expression and prognosis of KIRC and KIRP were analyzed. Univariate and multivariate analysis were performed to identify prognostic factors in KIRC and KIRP and nomograms were constructed. The correlation between SPC24 expression and immune cell infiltration, immune molecules, microsatellite instability (MSI), and tumor mutational burden (TMB) were further explored. Finally, the correlations between SPC24 expression and prognosis of KIRC based on different immune cell enrichment were analyzed.

RESULTS

SPC24 was significantly up-regulated in multiple cancers, especially KIRC and KIRP. SPC24 expression was significantly correlated with the T.N.M stage of KIRC and KIRP, and up-regulated SPC24 suggested worse prognosis. Besides, SPC24 possess good accuracy in diagnosing KIRC and KIRP. The SPC24-based nomograms displayed satisfactory efficacy in KIRC and KIRP. Moreover, we found SPC24 expression was closely correlated with immune cell infiltration, immune molecules and TMB in KIRC and up-regulated SPC24 revealed poor prognosis based on different immune cell enrichment.

CONCLUSION

SPC24 has potential to be a biomarker predicting the prognosis and/or immune infiltration of KIRC and KIRP.

Generation and Analysis of Pyroptosis-Based and Immune-Based Signatures for Kidney Renal Clear Cell Carcinoma Patients, and Cell Experiment

Background: Pyroptosis is a programmed cell death caused by inflammasomes, which is closely related to immune responses and tumor progression. The present study aimed to construct dual prognostic indices based on pyroptosis-associated and immune-associated genes and to investigate the impact of the biological signatures of these genes on Kidney Renal Clear Cell Carcinoma (KIRC).

Materials and Methods: All the KIRC samples from the Cancer Genome Atlas (TCGA) were randomly and equally divided into the training and testing datasets. Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis were used to screen crucial pyroptosis-associated genes (PAGs), and a pyroptosis-associated genes prognostic index (PAGsPI) was constructed. Immune-associated genes (IAGs) related to PAGs were identified, and then screened through Cox and LASSO regression analyses, and an immune-associated genes prognostic index (IAGsPI) was developed. These two prognostic indices were verified by using the testing and the Gene Expression Omnibus (GEO) datasets and an independent cohort. The patients’ response to immunotherapy was analyzed. A nomogram was constructed and calibrated. qRT-PCR was used to detect the expression of PAGs and IAGs in the tumor tissues and normal tissues. Functional experiment was carried out.

Results: 86 PAGs and 1,774 differentially expressed genes (DEGs) were obtained. After intersecting PAGs with DEGs, 22 differentially expressed PAGs (DEPAGs) were included in Cox and LASSO regression analyses, identifying 5 crucial PAGs. The PAGsPI was generated. Patients in the high-PAGsPI group had a poor prognosis. 82 differentially expressed IAGs (DEIAGs) were highly correlated with DEPAGs. 7 key IAGs were screened out, and an IAGsPI was generated. Patients in the high-IAGsPI group had a poor prognosis. PAGsPI and IAGsPI were verified to be robust and reliable. The results revealed patients in low-PAGsPI group and high-IAGsPI group may be more sensitive to immunotherapy. The calibrated nomogram was proved to be reliable. An independent cohort study also proved that PAGsPI and IAGsPI performed well in prognosis prediction. We found that the expression of AIM2 may affect proliferation of KIRC cells.

Conclusion: PAGsPI and IAGsPI could be regarded as potential biomarkers for predicting the prognosis of patients with KIRC.

Comprehensive analysis of PTEN-related ceRNA network revealing the key pathways WDFY3-AS2 - miR-21-5p/miR-221-3p/miR-222-3p - TIMP3 as potential biomarker in tumorigenesis and prognosis of kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most common malignancies, and there is still a lack of effective biomarkers for early detection and prognostic prediction. In here, we compared the characteristics of RNA sequencing data sets of KIRC samples based on the tumor suppressor gene phosphatase and tensin homolog (PTEN). The 1016 long noncoding RNAs, 48 microRNAs (miRNAs), and 2104 messenger RNAs associated with PTEN were identified and these genes were differentially expressed between tumor and paracancerous tissues. The most relevant pathway was found to be WDFY3-AS2 - miR-21-5p/miR-221-3p/miR-222-3p - TIMP3 according to the rules of competing endogenous RNA (ceRNA) regulation. WDFY3-AS2 and TIMP3 expression were positively correlated and reduced in KIRC samples, while miR-21-5p, miR-221-3p, and miR-222-3p were relatively highly expressed. The relatively low expression of WDFY3-AS2 and TIMP3 in KIRC were associated with poor prognosis in KIRC patients, while higher expression of miR-21-5p, miR-221-3p, and miR-222-3p predicted reduced survival (p < 0.05). Univariate and multivariate Cox regression analysis showed that lower expression of WDFY3-AS2 and TIMP3 was significantly related to tumor grade, tumor size, lymph node metastasis, distant metastasis, and TNM stage. The expression of TIMP3 in KIRC tissues was also verified by immunohistochemistry, and the results were consistent with our analytical data. In summary, this study constructed a new model with clinical predictive value and identified the WDFY3-AS2/TIMP3 pathway that was closely associated with the prognosis of KIRC, which could serve as a promising biomarker for the diagnosis and treatment of KIRC.

Identification of a Novel Defined Immune-Autophagy-Related Gene Signature Associated With Clinical and Prognostic Features of Kidney Renal Clear Cell Carcinoma

Background: As a common cancer of the urinary system in adults, renal clear cell carcinoma is metastatic in 30% of patients, and 1-2 years after diagnosis, 60% of patients die. At present, the rapid development of tumor immunology and autophagy had brought new directions to the treatment of renal cancer. Therefore, it was extremely urgent to find potential targets and prognostic biomarkers for immunotherapy combined with autophagy. Methods: Through GSE168845, immune-related genes, autophagy-related genes, and immune-autophagy-related differentially expressed genes (IAR-DEGs) were identified. Independent prognostic value of IAR-DEGs was determined by differential expression analysis, prognostic analysis, and univariate and multivariate Cox regression analyses. Then, the lasso Cox regression model was established to evaluate the correlation of IAR-DEGs with the immune score, immune checkpoint, iron death, methylation, and one-class logistic regression (OCLR) score. Results: In this study, it was found that CANX, BID, NAMPT, and BIRC5 were immune-autophagy-related genes with independent prognostic value, and the risk prognostic model based on them was well constructed. Further analysis showed that CANX, BID, NAMPT, and BIRC5 were significantly correlated with the immune score, immune checkpoint, iron death, methylation, and OCLR score. Further experimental results were consistent with the bioinformatics analysis. Conclusion: CANX, BID, NAMPT, and BIRC5 were potential targets and effective prognostic biomarkers for immunotherapy combined with autophagy in kidney renal clear cell carcinoma.