One of the most prevalent urinary illnesses is kidney stone formation, often known as nephrolithiasis. The precise processes of kidney stone remain poorly known after substantial investigation. In order to successfully prevent and cure stone formation and recurrence, additional research into the pathophysiology of stone formation is of paramount importance. Ferroptosis is linked to a variety of renal diseases and is a critical factor in the death of cells. However, little is known about how ferroptosis-related genes (FRGs) contribute to the development of kidney stones.

The Ferroptosis Database and the Gene Expression Omnibus (GEO) database provided us with information on kidney stones and FRGs, respectively (FerrDb).

Eight DE-FRGs related to kidney stones were found in total, and they were all closely related to immune response and autophagy management. Following this, among the 8 DE-FRGs, LASSO and SVM-RFE algorithms chose FZD7, STK11, SUV39H1, and LCN2 as marker genes with suitable diagnostic capabilities. These marker genes may be involved in the control of the PPAR signaling pathway, mTOR signaling system, and fatty acid production of kidney stones, according to the functional enrichment analysis that followed. Additionally, 24 drugs that target two marker genes have been found. Despite this, the ceRNA networks have gained that the regulatory relationship between marker genes is rather complex. Additionally, the findings of the CIBERSORT investigation indicated that FZD7 and SUV39H1 may be linked to variations in the immune milieu of people who have kidney stones.

We developed a diagnostic tool and provided information on the development of kidney stones. In order to confirm its diagnostic applicability for kidney stones, more studies are needed before it may be used in clinical practice.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal cell carcinoma, and immune checkpoint regulator-based immunotherapy has emerged as an effective treatment for advanced stages of the disease. However, the expression patterns, prognostic significance, and diagnostic value of immune checkpoint-related genes (ICRGs) in ccRCC remain underexplored. This study utilized large-scale ccRCC datasets from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the International Cancer Genome Consortium (ICGC) to analyze ICRGs and develop a prognostic and diagnostic model, which was validated using quantitative PCR in clinical samples from ccRCC patients.

RNA-seq data and clinical information were retrieved from TCGA, ICGC, and GEO databases. Differentially expressed genes (DEGs) were identified, and immune checkpoint-related genes (DICRGs) were selected by intersecting DEGs with ICRGs, followed by validation in independent datasets. Univariate and multivariate Cox regression analyses were used to develop the prognostic model. Protein expression of key genes was validated through immunohistochemistry (IHC) using data from the Human Protein Atlas (HPA). qRT-PCR confirmed gene expression levels in ccRCC and normal kidney tissues. Diagnostic models were constructed using machine learning, and functional enrichment and immune infiltration analyses were performed.

Fourteen DICRGs were identified, with four (EGFR, TRIB3, ZAP70, and CD4) showing prognostic significance in Cox analyses. IHC revealed high expression of these genes in ccRCC tissues, and qRT-PCR confirmed increased expression of EGFR, TRIB3, and CD4, while ZAP70 expression showed no significant change. A prognostic risk score was developed based on gene expression levels. Functional analysis identified enriched pathways related to organic anion transport and metabolism, while immune infiltration analysis revealed associations between ZAP70, CD4, and risk scores.

This study establishes a prognostic model for ccRCC based on four ICRGs, providing valuable insights into the molecular mechanisms underlying prognosis and diagnosis in ccRCC.

Kidney renal clear cell carcinoma (KIRC), a therapy-resistant aggressive kidney cancer, exhibits resistance to immune checkpoint inhibitors. Altered sialylation is involved in tumor development, affecting immune microenvironment dynamics. In the study, through systematic bioinformatics analysis and experimental verification, we demonstrated that ST3Gal5 expression was elevated in tumor tissues of KIRC patients, correlating with poor prognosis, and ST3Gal1 was downregulated and associated with a better prognosis. Immunohistochemistry analysis confirmed the expression patterns of ST3Gal1 and ST3Gal5 in 30 KIRC patients. Furthermore, KIRC patients were stratified into two clusters based on ST3Gal1 and ST3Gal5 levels using consensus clustering to investigate their roles in KIRC tumorigenesis, immune characteristics and treatment sensitivity. KIRC patients in Cluster 2, characterized by increased ST3Gal5 and downregulated ST3Gal1 expression, exhibited increased expression of immune checkpoints, immune cell infiltration, immune escape scores, and worse prognosis. Knockdown of ST3Gal5 in KIRC cell lines (786-O and 769-P) resulted in reduced tumor proliferation, migration, and invasion in vivo and in vitro. Together, the dysregulation of sialyltransferases (ST3Gal1 and ST3Gal5) in KIRC influences tumorigenesis and immune responses. These findings underscore the potential of ST3Gal1 and ST3Gal5 as prognostic factors and immunotherapy targets for KIRC.

Spatial transcriptomics has emerged as a powerful tool for discerning the heterogeneity of the tumour microenvironment across various cancers, including renal cell carcinoma (RCC). Spatial transcriptomics-based studies conducted in clear-cell RCC (the only RCC subtype studied using this technique to date) have given insights into spatial interactions within this disease. These insights include the role of epithelial-to-mesenchymal transitioning, revealing proximity-dependent interactions between tumour cells, fibroblasts, interleukin-2-expressing macrophages and hyalinized regions. Investigations into metabolic programmes have shown high transcriptional heterogeneity within tumours, with a tendency of increased metabolic activity towards the tumour centre. T cell infiltration has been shown to be independent of neoantigen burden, although T cell activity correlates with both metabolic states and various transcripts expressed by tumour cells, fibroblasts and monocytes. The role of tertiary lymphoid structures in both plasma cell maturation and their infiltration of the tumour has been shown through tracks of fibroblasts. Collectively, these findings indicate the potential of spatial transcriptomics to reveal predictive spatial features, supporting its promise in the development of biomarkers for clear-cell RCC management.

Mitophagy, an essential process within cellular autophagy, has a critical role in regulating key cellular functions such as reproduction, metabolism, and apoptosis. Its involvement in tumor development is complex and influenced by the cellular environment. Here, we conduct a comprehensive analysis of a mitophagy-related gene signature, composed of PRKN, PINK1, MAP1LC3A, SRC, BNIP3L, BECN1, and OPTN, across various cancer types, revealing significant differential expression patterns associated with molecular subtypes, stages, and patient outcomes. Pathway analysis revealed a complex interplay between the expression of the signature and potential effects on the activity of various cancer-related pathways in pan-cancer. Immune infiltration analysis linked the mitophagy signature with certain immune cell types, particularly OPTN with immune infiltration in melanoma. Methylation patterns correlated with gene expression and immune infiltration. Mutation analysis also showed frequent alterations in PRKN (34%), OPTN (21%), PINK1 (28%), and SRC (15%), with implications for the tumor microenvironment. We also found various correlations between the expression of the mitophagy-related genes and sensitivity in different drugs, suggesting that targeting this signature could improve therapy efficacy. Overall, our findings underscore the importance of mitophagy in cancer biology and drug resistance, as well as its potential for informing treatment strategies.

IntroductionRenal cancer, particularly Kidney Renal Clear Cell Carcinoma (KIRC), remains a major clinical challenge due to its aggressive nature and poor prognosis. Identifying reliable biomarkers for tumor progression and survival is critical for improving patient outcomes. This study aimed to investigate the role of Centromere Protein F (CENPF) as a potential prognostic biomarker for renal cancer.MethodData from the TCGA database, including Kidney Chromophobe (KICH), Kidney Renal Papillary Cell Carcinoma (KIRP), and KIRC, were analyzed to identify differentially expressed genes. Molecular Complex Detection (MCODE) was used to identify significant gene modules among upregulated genes, and univariate Cox regression analyses assessed the prognostic value of hub genes. Retrospective qPCR was conducted on tissue and plasma samples from KIRC patients to validate findings. Single-cell sequencing data from the GSE159115 dataset were analyzed, and the CIBERSORT algorithm was applied to evaluate the composition of tumor immune infiltrating cells (TIICs).ResultsCENPF was identified as a hub gene significantly upregulated in renal cancer subtypes, with overexpression linked to worse survival outcomes in KIRC patients. Retrospective qPCR confirmed high CENPF expression was associated with poorer prognosis. Single-cell sequencing revealed that CENPF is predominantly expressed in T-cell clusters. TIIC analysis showed a negative correlation between CENPF and resting mast cells, but positive correlations with follicular helper T-cells and memory-activated CD4T-cells. Prognostic analysis indicated that high follicular helper T-cell expression predicted poorer survival, while high plasma cell expression correlated with better outcomes.ConclusionCENPF plays a critical role in tumor progression and the modulation of the tumor immune microenvironment in KIRC. These findings suggest that CENPF could serve as a valuable prognostic biomarker and potential target for therapeutic intervention in renal cancer.

A thorough study of Clear Cell Renal Cell Carcinoma (ccRCC) shows that combining tyrosine kinase inhibitors (TKI) with immune checkpoint inhibitors (ICI) shows promising results in addressing the tumor-promoting influences of abnormal immunological and molecular biomarkers in metastatic Clear Cell Renal Cell Carcinoma (ccRCC). These abnormal biomarkers enhance drug resistance, support tumor growth, and trigger cancer-related genes. Ongoing clinical trials are testing new treatment options that appear more effective than earlier ones. However, more research is needed to confirm their long-term safety use and potential side effects. This study highlights vital molecular and immunological biomarkers associated with drug resistance in Clear Cell Renal Cell Carcinoma (ccRCC). Furthermore, this study identifies a number of promising drug candidates and biomarkers that serve as significant contributors to the enhancement of the overall survival of ccRCC patients. Consequently, this article offers pertinent insights on both recently completed and ongoing clinical trials, recommending further toxicity study for the prolonged use of this treatment strategy for patients with metastatic ccRCC, while equipping researchers with invaluable information for the progression of current treatment strategies.

To analyze hotspots and trends in renal cell carcinoma (RCC)-macrophage research using bibliometric analysis, although numerous studies on macrophages in RCC have been recently reported, understanding the progressive trends in this field remains challenging. Publications focused on macrophages in RCC were extracted from the Web of Science Core Collection. VOSviewer, Citespace, and Bibliometrics online platforms were used to visualize hot topics and global trends in RCC-macrophage research. In total, 778 papers were collected. China produced the most articles; however, the United States accounted for the largest number of citations. Oncology journals published the most articles, and these were cited most frequently. Based on keyword analysis, "prognosis," "immunotherapy," "tumor microenvironment," and "immune infiltration" represented the primary research hotspots. In summary, RCC-macrophage studies have emerged as a key research focus; particularly, incorporating multiomics data and applying artificial intelligence for predictive modeling have demonstrated significant potential. Our study suggests that the resistance mechanism of immune checkpoint inhibitors and the interaction between macrophages and immune checkpoint inhibitors will be pivotal areas for future research.

Ferroptosis has emerged as a critical mechanism in the development and progression of various tumors, particularly diffuse large B-cell lymphoma (DLBCL). However, the thorough characterization of ferroptosis-related genes in DLBCL remains inadequately explored. We retrieved datasets associated with DLBCL and ferroptosis gene sets from the Gene Expression Omnibus (GEO) database and the Ferroptosis Database (FerrDb), resulting in the identification of 27 differentially expressed ferroptosis-related genes (DE-FRGs) linked to DLBCL. Utilizing the LASSO and Support Vector Machine Recursive Feature Elimination (SVW-RFE) algorithms, we identified 10 genes-MT1G, MTOR, BRD4, ACO1, SAT1, PEBP1, LPIN1, ATM, SRXN1, and PRDX1-as key biomarker candidates with significant diagnostic potential. Functional enrichment analyses revealed that these biomarker genes are likely involved in regulating several critical biological pathways implicated in DLBCL pathogenesis, including immune response, oxidative phosphorylation, and cell cycle regulation. Moreover, we identified 246 potential therapeutic agents targeting these 10 biomarker genes. Concurrently, competitive endogenous RNA (ceRNA) network analysis uncovered a complex regulatory network centered on the identified biomarker genes. Additionally, CIBERSORT analysis highlighted notable alterations in the immune microenvironment of DLBCL patients. We propose a diagnostic strategy that provides novel insights into the molecular mechanisms underlying DLBCL. Nevertheless, further validation of the practical value of this strategy for DLBCL diagnosis is necessary before its clinical application.

Aggressive clear cell renal cell carcinoma (ccRCC) has a bad prognosis. We seek new ccRCC biomarkers for diagnosis and treatment. We used exoRBase and The Cancer Genome Atlas Database to compare DEmRNAs, DEmiRNAs, DElncRNAs, and DEcircRNAs in ccRCC and normal renal tissues. CircRNAs and circRNAs targeting microRNAs (miRNAs) were anticipated and taken intersections, and several databases assessed the targeted link between common miRNAs and messenger RNAs (mRNAs). The Cancer Genome Atlas database was used to create a predictive mRNA signature that was validated in E-MTAB-1980. Finally, we examined competing endogenous RNA network miRNAs and long noncoding RNAs for ccRCC predictive biomarkers using overall survival analysis. We built the first competing endogenous RNA regulation network of circRNA-lncRNA-miRNA-mRNA and found that it substantially correlates with ccRCC prognosis. We unveiled ccRCC's posttranscriptional regulation mechanism in greater detail. Our findings identified novel biomarkers for ccRCC diagnosis, therapy, and prognosis.

In recent years, knowledge regarding immune regulation has expanded rapidly, and major advancements have been made in immunotherapy for immune-associated disorders, particularly cancer. The programmed cell death 1 (PD-1) pathway is a cornerstone in immune regulation. It comprises PD-1 and its ligands mediating immune tolerance mechanisms and immune homeostasis. Accumulating evidence demonstrates that the PD-1 axis has a crucial immunosuppressive role in the tumor microenvironment and autoimmune diseases. PD-1 receptors and ligands on immune cells and renal parenchymal cells aid in maintaining immunological homeostasis in the kidneys. Here, we present a comprehensive review of PD-1 immunology in various kidney disorders, including renal cell carcinoma, glomerulonephritis, kidney transplantation, renal aging, and renal immune-related adverse events secondary to PD-1 immunotherapy.

CD8+ T lymphocytes are important elements of the tumor microenvironment, hence their involvement in the development and progression of tumors is complex. Data on the precise tumor-infiltrating lymphocytes gene signature in renal cell carcinoma (RCC) remain limited. Therefore, this study created a tumor-infiltrating lymphocytes-related predictive model for patients with RCC using data from The Cancer Genome Atlas. The most important genes associated with CD8 + T lymphocytes were identified using weighted gene co-expression network analysis. Functional categories of important genes were revealed using gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses. A CD8 + T lymphocyte-related prognostic model with 7 important genes was simultaneously created using the least absolute shrinkage and selection operator, univariate and multivariate Cox regressions, and the 7 genes were expressed particularly in CD8 + T lymphocytes according to single-cell sequencing data obtained from the Gene Expression Omnibus. This study identified a seven-gene prognostic model associated with CD8 + T lymphocytes that may significantly influence risk stratification in patients with RCC. The genes included in the model are apolipoprotein B mRNA editing catalytic polypeptide 3G, CD3 gamma, eomesodermin, protein tyrosine phosphatase, non-receptor type 7, signal regulatory protein gamma, Fas ligand, and T-cell immunoreceptor with Ig and ITIM domains.

Platelet-derived growth factor A (PDGFA) has been shown to be upregulated in several tumors, contributing to their malignant phenotypes. However, its expression and function in head and neck squamous cell carcinoma (HNSC) are not clearly understood. Thus, we aimed to evaluate this issue using bioinformatic analyses and primary experimental validation.

The expression of PDGFA was analyzed using popular bio-databases and further validated by RT-PCR and immunohistochemical staining. Survival analyses were then performed. The association between PDGFA expression levels and immune cell infiltration in the immune microenvironment was assessed.

PDGFA has been found to be significantly upregulated in a variety of cancers, including HNSC, and increased PDGFA expression may be an independent prognostic factor associated with immune cell infiltration in HNSC.

Overexpression of PDGFA in HNSC is significantly associated with poor prognosis and immune cell infiltration in the tumor microenvironment (TME). PDGFA has potential as a molecular indicator for diagnosis, prognosis, and immune processes in HNSC.

Many factors affect the prognosis of kidney renal clear cell carcinoma (KIRC). Early diagnosis can significantly improve the prognosis of KIRC patients. Therefore, a method needs to be developed to diagnose KIRC early, predict patient prognosis, and improve personalized treatments. The objective of this study is to utilize bioinformatics tools and public database resources to identify differentially expressed genes (DEGs) between renal cancer tissues and adjacent normal tissues, and to further screen for prognostic-related genes (PRGs) of KIRC.

KIRC was studied using R language and FunRich software and several databases, including the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), the University of Alabama at Birmingham cancer data analysis Portal (UALCAN), and Tumor Immune Estimation Resource (TIMER) databases. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expression of multiple genes in KIRC and adjacent normal tissues.

There were substantial differences in immune cell infiltration between the KIRC and adjacent normal tissues in the GSE40435 and GSE46699 datasets. In addition, we screened multiple PRGs of KIRC by combining the GEO and TCGA data. The UALCAN database verified that some representative PRGs were differently expressed depending on the lymph node metastasis status, grade, and stage of KIRC. The qRT-PCR results confirmed the expression of the PRGs in KIRC and adjacent normal tissues. Through the GO and KEGG analyses, interaction analysis, and TIMER database, we found that the prognosis of KIRC was closely related to immune microenvironment and vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) signaling.

Our findings could contribute to the prognosis prediction of KIRC, the selection of personalized treatments, and the early diagnosis of KIRC.

Clear cell renal cell carcinoma (ccRCC) is a renal cortical malignancy with a complex pathogenesis. Identifying ideal biomarkers to establish more accurate promising prognostic models is crucial for the survival of kidney cancer patients.

Seurat R package was used for single-cell RNA-sequencing (scRNA-seq) data filtering, dimensionality reduction, clustering, and differentially expressed genes analysis. Gene coexpression network analysis (WGCNA) was performed to identify the cytotoxicity-related module. The independent cytotoxicity-related risk model was established by the survival R package, and Kaplan-Meier (KM) survival analysis and timeROC with area under the curve (AUC) were employed to confirm the prognosis and effectiveness of the risk model. The risk and prognosis in patients suffering from ccRCC were predicted by establishing a nomogram. A comparison of the level of immune infiltration in different risk groups and subtypes using the CIBERSORT, MCP-counter, and TIMER methods, as well as assessment of drug sensitivity to conventional chemotherapeutic agents in risk groups using the pRRophetic package, was made.

Eleven ccRCC subpopulations were identified by single-cell sequencing data from the GSE224630 dataset. The identified cytotoxicity-related T-cell cluster and module genes defined three cytotoxicity-related molecular subtypes. Six key genes (SOWAHB, SLC16A12, IL20RB, SLC12A8, PLG, and HHLA2) affecting prognosis risk genes were selected for developing a risk model. A nomogram containing the RiskScore and stage revealed that the RiskScore contributed the most and exhibited excellent predicted performance for prognosis in the calibration plots and decision curve analysis (DCA). Notably, high-risk patients with ccRCC demonstrate a poorer prognosis with higher immune infiltration characteristics and TIDE scores, whereas low-risk patients are more likely to benefit from immunotherapy.

A ccRCC survival prognostic model was produced based on the cytotoxicity-related signature, which had important clinical significance and may provide guidance for ccRCC treatment.

CTLA4, an immune checkpoint, plays an important role in tumor immunotherapy. The purpose of this study was to develop a pathomics signature to evaluate CTLA4 expression and predict clinical outcomes in clear cell renal cell carcinoma (ccRCC) patients.

A total of 354 patients from the TCGA-KIRC dataset were enrolled in this study. The patients were stratified into two groups based on the level of CTLA4 expression, and overall survival rates were analyzed between groups. Pathological features were identified using machine learning algorithms, and a gradient boosting machine (GBM) was employed to construct the pathomics signatures for predicting prognosis and CTLA4 expression. The predictive performance of the model was subsequently assessed. Enrichment analysis was performed on diferentially expressed genes related to the pathomics score (PS). Additionally, correlations between PS and TMB, as well as immune infiltration profiles associated with different PS values, were explored. In vitro experiments, CTLA4 knockdown was performed to investigate its impact on cell proliferation, migration, invasion, TGF-β signaling pathway, and macrophage polarization.

High expression of CTLA4 was associated with an unfavorable prognosis in ccRCC patients. The pathomics signature displayed good performance in the validation set (AUC = 0.737; P < 0.001 in the log-rank test). The PS was positively correlated with CTLA4 expression. We next explored the underlying mechanism and found the associations between the pathomics signature and TGF-β signaling pathways, TMB, and Tregs. Further in vitro experiments demonstrated that CTLA4 knockdown inhibited cell proliferation, migration, invasion, TGF-β expression, and macrophage M2 polarization.

High expression of CTLA4 was found to correlate with poor prognosis in ccRCC patients. The pathomics signature established by our group using machine learning effectively predicted both patient prognosis and CTLA4 expression levels in ccRCC cases.

Background and Objectives: Renal cell carcinomas and upper tract urothelial carcinomas are types of malignancies that originate in the kidneys. Each of these examples shows an increasing trend in the frequency and the mortality rate. This study aims to comprehensively define carcinomas by analyzing clinical, paraclinical, and histological aspects to predict aggressiveness and mortality. Materials and Methods: We conducted a retrospective investigation on a group of patients suspected of kidney cancers. Results: We identified 188 cases. We observed a higher mortality rate and older age in individuals with urothelial carcinomas. Anemia, acute kidney injury, hematuria, and perineural invasion were the main risk factors that predicted their mortality. Tumor size in renal cell carcinomas correlates with the presence of necrosis and sarcomatoid areas. Factors that indicate a higher rate of death are older age, exceeding the renal capsule, a lesion that includes the entire kidney, lymphovascular invasion, acute kidney injury, and anemia. Conclusions: Even if they originate at the renal level, and the clinical-paraclinical picture is similar, the histopathological characteristics make the difference. In addition, to these are added the previously mentioned common parameters that can represent important prognostic factors. In conclusion, the characteristics commonly identified in one type of cancer may act as risk factors for the other tumor. The detected data include threshold values and risk factors, making a significant contribution to the existing literature.

Immune response is known to play an important role in local tumor control especially in renal cell carcinoma (RCC), which is considered highly immunogenic. For localized tumors, operative resection or local ablative procedures such as cryoablation are common therapeutical options. For thermal ablative procedures such as cryoablation, additional immunological anti-tumor effects have been described.The purpose of this prospective study was to determine changes in peripheral blood circulating lymphocytes and various of their subsets in RCC patients treated with cryoablation or surgery in a longitudinal approach using extensive flow cytometry. Additionally, lymphocytes of RCC patients were compared to a healthy control group.We included 25 patients with RCC. Eight underwent cryoablation and 17 underwent surgery. Univariate and multivariable analysis revealed significantly lower values of B cells, CD4 and CD8 T cells, and various of their subsets in the treatment groups versus the healthy control group. Comparing the two different therapeutical approaches, a significant decline of various lymphocyte subsets with a consecutive normalization after three months was seen for the surgery group, whereas cryoablation led to increased values of CD69 + CD4 + and CD69 + CD8 + cell counts as well as memory CD8 + cells after three months.Treatment-naïve RCC patients showed lower peripheral blood lymphocyte counts compared to healthy controls. The post-treatment course revealed different developments of lymphocytes in the surgery versus cryoablation group, and only cryoablation seems to induce a sustained immunological response after three months.

Papillary renal cell carcinoma (pRCC) is a rare and aggressive cancer with no specifically established therapeutic strategy in the metastatic setting. Combinations of tyrosine kinase and immune checkpoint inhibitors (ICI) are a promising option. We aimed to study the immune landscape of metastatic pRCC, and its interactions with angiogenesis pathways, to search for potential therapeutic targets.

The expression of immune markers (PD-L1, PD-1, PD-L2, LAG-3) and angiogenic pathways (CAIX, c-MET), was analyzed by immunohistochemistry on 68 metastatic pRCC retrieved from a retrospective multicenter GETUG cohort. Our primary endpoint was to estimate the prevalence of PD-L1 expression and its prognostic impact in metastatic pRCC. Secondary endpoints included the evaluation of other immune markers (PD-1, PD-L2, and LAG-3) and their association with PD-L1. We also assessed angiogenic markers and their association with PD-L1.

Overall, 27.9 % of tumors were PD-L1 positive. PD-L2 was more frequently expressed (45.6 %), PD-1 and LAG-3 were positive in 17.6 % and 19.1 % respectively. None of these markers was correlated with PD-L1 expression. 66 % (45/68) expressed at least one immune marker, and 43 % (29/68) were "double-positive", as they expressed both immune and angiogenic markers. OS was significantly shorter for patients with PD-L1 positive pRCC. A multivariate analysis confirmed a significant association between PD-L1 expression and shorter overall survival (HR = 4.0, p = 0.01).

These results reinforce clinical data on the expected benefit of ICI in metastatic pRCC treatment, as PD-L1 expression is a factor of poor prognosis in this multicenter cohort.

Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogeneous disease that requires personalized clinical treatment. Assigning patients to different risk categories and cytogenetic abnormality and genetic mutation groups has been widely applied for prognostic stratification of DLBCL. Increasing evidence has demonstrated that dysregulated metabolic processes contribute to the initiation and progression of DLBCL. Metabolic competition within the tumor microenvironment is also known to influence immune cell metabolism. However, metabolism- and immune-related stratification has not been established. Here, 1660 genes involved in 84 metabolic pathways were selected and tested to establish metabolic clusters (MECs) of DLBCL. MECs established based on independent lymphoma datasets distinguished different survival outcomes. The CIBERSORT algorithm and EcoTyper were applied to quantify the relative abundance of immune cell types and identify variation in cell states for 13 lineages comprising the tumor micro environment among different MECs, respectively. Functional characterization showed that MECs were an indicator of the immune microenvironment and correlated with distinctive mutational characteristics and oncogenic signaling pathways. The novel immune-related MECs exhibited promising clinical prognostic value and potential for informing DLBCL treatment decisions.

Previous reports have revealed that the abnormal expression of the cell division cycle-associated gene family (CDCAs) is closely associated with some human cancers. However, the precise functional roles and mechanisms of CDCAs in kidney renal papillary cell carcinoma (KIRP) remain unclear. In this study, RNA sequencing data from the Cancer Genome Atlas database and Genotype-Tissue Expression databases were utilized to perform the expression, correlation, survival, mutation, functional enrichment analysis, and immunoinfiltration analyses of CDCAs in KIRP. We found that the expression levels of CDCA genes were significantly increased in KIRP across multiple databases, as confirmed by immunohistochemistry and quantitative reverse transcription PCR (RT-qPCR). Moreover, increased expression of CDCA genes is significantly associated with poor prognosis. Univariate and multivariate Cox regression analyses demonstrated that pathologic T and N staging, NUF2, CDCA2, CDCA3, CDCA5, CBX2, CDCA7, and CDCA8 were independent prognostic factors for patients with KIRP. Utilizing these nine variables, we developed a nomogram prognostic model. Furthermore, the results of GO and KEGG functional enrichment analyses suggested that CDCA genes were associated with nuclear division, mitotic nuclear division, and chromosome segregation and were involved in the cell cycle, p53 signaling pathway, and cellular senescence. We found that the expression of NUF2, CDCA2, CDCA5, and CBX2 was closely associated with the expression of lymphocytes, immunostimulatory molecules, immunoinhibitory molecules, and chemokines. In summary, NUF2, CDCA2, CDCA3, CDCA5, CBX2, CDCA7, and CDCA8 are potential biomarkers for KIRP diagnosis and prognosis.

Renal cell carcinoma (RCC) is one of the most common malignant tumors of the kidney, presenting significant challenges for clinical diagnosis and treatment. Macrophages play crucial roles in RCC, promoting tumor progression and warranting further investigation. Previous studies have identified LHFPL2 as a transmembrane protein associated with reproduction, but its relationship with tumors or macrophages has not been discussed. This study utilized transcriptomic sequencing data from 609 KIRC patients in the TCGA database and single-cell sequencing data from 34,326 renal carcinoma cells for subsequent analysis. We comprehensively evaluated the expression of LHFPL2 and its relationship with clinical features, tumor prognosis, immune infiltration, and mutations. Additionally, we further assessed the correlation between LHFPL2 and macrophage M2 polarization using single-cell data and explored its potential as a cancer therapeutic target through molecular docking. The results demonstrated that LHFPL2 is upregulated in RCC and associated with poor survival rates. In clinical staging, the proportion of malignant and high-metastasis patients was higher in the high-LHFPL2 group than in the low-LHFPL2 group. Furthermore, we found that LHFPL2 influences RCC immune infiltration, with its expression positively correlated with various immune checkpoint and M2-related gene expressions, positively associated with M2 macrophage infiltration, and negatively correlated with activated NK cells. Moreover, LHFPL2 showed specific expression in macrophages, with the high-expression subgroup exhibiting higher M2 polarization, hypoxia, immune evasion, and angiogenesis scores, promoting tumor progression. Finally, we predicted several potential drugs targeting LHFPL2, such as conivaptan and nilotinib. Our analysis elaborately delineates the immune characteristics of LHFPL2 in the tumor microenvironment and its positive correlation with macrophage M2 polarization, providing new insights into tumor immunotherapy. We also propose potential FDA-approved drugs targeting this gene, which should be tested for their binding effects with LHFPL2 in future studies.

Gastric cancer (GC) is the world's third-leading cause of cancer-related mortality; the prognosis for GC patients remains poor in terms of a lack of reliable biomarkers for early diagnosis and immune therapy response prediction. Here, we aim to discover the connection between chemokine ligand 14 (CCL14) expression in the gastric tumor microenvironment (TME) and its clinical significance and investigate its correlation with immune cell infiltration.

We assessed CCL14 mRNA expression and its interrelation with tumor-infiltrating immune cells (TILs) using bioinformatics analysis in gastric cancer. CCL14 protein expression, TILs, and immune checkpoints were detected by multiple immunohistochemistry analyses in gastric cancer tissue microarrays. Then, we conducted statistics analysis to determine the association between CCL14-related patient survival and immune cell infiltration (p < 0.05).

We found that the CCL14 protein was separately expressed in the carcinoma cells and TILs in stomach cancer tissues. The CCL14 protein was related to tumor differentiation and tumor depth and positively correlated with the presentation of LAG3 and PD-L1 in gastric cancer cells. In addition, the CCL14 protein in the TILs of gastric cancer tissues was related to Lauren's type cells, T cells (CD4+ and CD8+), and CD68+ macrophages in the TME. Kaplan-Meier survival and multivariate analyses showed that the CCL14 expression in gastric cancer cells was an independent prognostic factor.

Our study illustrated that CCL14 is a poor prognosis biomarker in gastric cancer, which may be associated with the potential for immunotherapy.

Clear cell renal cell carcinoma (ccRCC) is the third most common type of urological malignancy worldwide, and it is associated with a silent progression and late manifestation. Patients with a metastatic form of ccRCC have a poor prognosis; however, when the disease is diagnosed early, it is largely curable. Currently, there are no biomarkers available in clinical practice for ccRCC. Thus, the aim of the present study was to measure 27 biologically relevant cytokines in preoperative and postoperative urine samples, and in preoperative plasma samples from 34 patients with ccRCC, and to evaluate their diagnostic significance. The concentrations of cytokines were assessed by multiplex immune assay. The results showed significantly higher levels of IL-1 receptor antagonist, IL-6, IL-15, chemokine (C-C motif) ligand (CCL)2, CCL3, CCL4, C-X-C motif ligand (CXCL)10, granulocyte-macrophage colony stimulating factor (GM-CSF) and platelet-derived growth factor-BB (PDGF-BB), and lower levels of granulocyte colony stimulating factor (G-CSF) in urine samples from patients prior to surgery compared with those in the controls. Notably, the urine levels of G-CSF, IL-5 and vascular endothelial growth factor differed following tumor removal compared with the preoperative urine levels. In addition, urinary G-CSF, GM-CSF, IL-6, CXCL10, CCL5 and PDGF-BB appeared to be potential markers of tumor grade. Plasma from patients with ccRCC contained significantly higher levels of IL-6 and lower levels of CCL2 than control plasma. In conclusion, the present findings indicated that urinary and circulating cytokines may represent a promising novel tool for the early diagnosis of ccRCC and/or prediction of tumor grade.

Kidney renal clear cell carcinoma (KIRC) pathogenesis intricately involves immune system dynamics, particularly the role of T cells within the tumour microenvironment. Through a multifaceted approach encompassing single-cell RNA sequencing, spatial transcriptome analysis and bulk transcriptome profiling, we systematically explored the contribution of infiltrating T cells to KIRC heterogeneity. Employing high-density weighted gene co-expression network analysis (hdWGCNA), module scoring and machine learning, we identified a distinct signature of infiltrating T cell-associated genes (ITSGs). Spatial transcriptomic data were analysed using robust cell type decomposition (RCTD) to uncover spatial interactions. Further analyses included enrichment assessments, immune infiltration evaluations and drug susceptibility predictions. Experimental validation involved PCR experiments, CCK-8 assays, plate cloning assays, wound-healing assays and Transwell assays. Six subpopulations of infiltrating and proliferating T cells were identified in KIRC, with notable dynamics observed in mid- to late-stage disease progression. Spatial analysis revealed significant correlations between T cells and epithelial cells across varying distances within the tumour microenvironment. The ITSG-based prognostic model demonstrated robust predictive capabilities, implicating these genes in immune modulation and metabolic pathways and offering prognostic insights into drug sensitivity for 12 KIRC treatment agents. Experimental validation underscored the functional relevance of PPIB in KIRC cell proliferation, invasion and migration. Our study comprehensively characterizes infiltrating T-cell heterogeneity in KIRC using single-cell RNA sequencing and spatial transcriptome data. The stable prognostic model based on ITSGs unveils infiltrating T cells' prognostic potential, shedding light on the immune microenvironment and offering avenues for personalized treatment and immunotherapy.

Immunotherapy represents a significant and essential component of renal carcinoma therapy (RCC), but the selection of an optimal regimen for an individual patient remains unclear. Despite significant improvements in therapeutic options for RCC, predictive biomarkers for immunotherapeutic agents remain elusive. Neopterin is a biomarker of cell-mediated immune response, with concentrations increased in different disorders, including cancer. High neopterin levels herald, in general, a poor prognosis.

This review briefly overviews the contemporary clinical data on biomarkers in metastatic RCC therapy, focusing on neopterin.

Elevated neopterin levels have been observed in tumors of different primary locations. Research indicates that neopterin may serve as a potential biomarker for assessing the inflammatory status associated with certain cancers. However, it is necessary to interpret neopterin levels in the context of a comprehensive clinical evaluation, as elevated neopterin alone is not specific to cancer and can be influenced by other factors, including comorbid conditions. Neopterin has also been identified as a prognostic biomarker. An increasing neopterin level in serum and urine is associated with advanced cancer, but the role as a potential predictor of response to immunotherapy has yet to be established. A reliable biomarker for optimal therapy selection in metastatic RCC is still putative.

Tumor-associated macrophages (TAM) are abundant in several tumor types and usually correlate with poor prognosis. Previously, we demonstrated that anti-inflammatory macrophages (M2) inhibit NK cell effector functions. Here, we explored the impact of TAM on NK cells in the context of clear-cell renal cell carcinoma (ccRCC). Bioinformatics analysis revealed that an exhausted NK cell signature strongly correlated with an M2 signature. Analysis of TAM from human ccRCC samples confirmed that they exhibited an M2-skewed phenotype and inhibited IFN-γ production by NK cells. Moreover, human M0 macrophages cultured with conditioned media from ccRCC cell lines generated macrophages with an M2-skewed phenotype (TAM-like), which alike TAM, displayed suppressive activity on NK cells. Moreover, TAM depletion in the mouse Renca ccRCC model resulted in delayed tumor growth and reduced volume, accompanied by an increased frequency of IFN-γ-producing tumor-infiltrating NK cells that displayed heightened expression of T-bet and NKG2D and reduced expression of the exhaustion-associated co-inhibitory molecules PD-1 and TIM-3. Therefore, in ccRCC, the tumor microenvironment polarizes TAM toward an immunosuppressive profile that promotes tumor-infiltrating NK cell dysfunction, contributing to tumor progression. In addition, immunotherapy strategies targeting TAM may result in NK cell reinvigoration, thereby counteracting tumor progression.

Thyroid cancer (THCA) is the most common endocrine malignancy, mainly affecting women's unilateral glandular lobes. However, for relapsed and distant metastasis of THCA patients, the existing early diagnosis and treatment methods were still insufficient, and a new method was urgently needed to diagnose and treat them. Nucleolar and coiled-body phosphoprotein 1 (NOLC1) was one of the most phosphorylated proteins in the cell, which was located mainly in the nucleolus. In addition, more and more studies have confirmed that NOLC1 plays a crucial role in various pathological processes, such as the occurrence and progression of cancer and viral infection. A previous study showed that NOLC1, as a member of RNA-binding protein, was significantly correlated with the prognosis of THCA patients. However, further exploration of NOLC1 in THCA is limited. To further explore the role of NOLC1 in THCA, we conducted expression and survival prognosis analysis of NOLC1 using multiple databases. We also evaluated the correlation between NOLC1 gene expression and clinical characteristics of THCA patients. Furthermore, we analyzed the relationship between NOLC1 and other genes, followed by enrichment analysis to investigate its metabolic pathways and molecular metabolism processes. Additionally, we examined the association between immune cell infiltration in tumor microenvironment and NOLC1. Notably, through vitro experiments, we confirmed the tumor suppressive effect of NOLC1 on the proliferation and migration of human THCA cells, providing evidence for clinical diagnosis of THCA. Furthermore, we confirmed the tumor suppressive effect of NOLC1 in vivo xenograft assay. To sum up, our results suggest that NOLC1 is a tumor suppressor gene for THCA.

Neddylation, a post-translational modification process, plays a crucial role in various human neoplasms. However, its connection with kidney renal clear cell carcinoma (KIRC) remains under-researched.

We validated the Gene Set Cancer Analysis Lite (GSCALite) platform against The Cancer Genome Atlas (TCGA) database, analyzing 33 cancer types and their link with 17 neddylation-related genes. This included examining copy number variations (CNVs), single nucleotide variations (SNVs), mRNA expression, cellular pathway involvement, and methylation. Using Gene Set Variation Analysis (GSVA), we categorized these genes into three clusters and examined their impact on KIRC patient prognosis, drug responses, immune infiltration, and oncogenic pathways. Afterward, our objective is to identify genes that exhibit overexpression in KIRC and are associated with an adverse prognosis. After pinpointing the specific target gene, we used the specific inhibitor MLN4924 to inhibit the neddylation pathway to conduct RNA sequencing and related in vitro experiments to verify and study the specificity and potential mechanisms related to the target. This approach is geared towards enhancing our understanding of the prognostic importance of neddylation modification in KIRC.

We identified significant CNV, SNV, and methylation events in neddylation-related genes across various cancers, with notably higher expression levels observed in KIRC. Cluster analysis revealed a potential trade-off in the interactions among neddylation-related genes, where both high and low levels of gene expression are linked to adverse prognoses. This association is particularly pronounced concerning lymph node involvement, T stage classification, and Fustat score. Simultaneously, our research discovered that PSMB10 exhibits overexpression in KIRC when compared to normal tissues, negatively impacting patient prognosis. Through RNA sequencing and in vitro assays, we confirmed that the inhibition of neddylation modification could play a role in the regulation of various signaling pathways, thereby influencing the prognosis of KIRC. Moreover, our results underscore PSMB10 as a viable target for therapeutic intervention in KIRC, opening up novel pathways for the development of targeted treatment strategies.

This study underscores the regulatory function and potential mechanism of neddylation modification on the phenotype of KIRC, identifying PSMB10 as a key regulatory target with a significant role in influencing the prognosis of KIRC.

Immunotherapies, such as immune checkpoint inhibitors, have heralded impressive progress for patient care in renal cell carcinoma (RCC). Despite this success, some patients' disease fails to respond, and other patients experience significant side effects. Thus, development of biomarkers is needed to ensure that patients can be selected to maximize benefit from immunotherapies. Improving clinicians' ability to predict which patients will respond to immunotherapy and which are most at risk of adverse events - namely through clinical biomarkers - is indispensable for patient safety and therapeutic efficacy. Accordingly, an evolving suite of therapeutic biomarkers continues to be investigated. This review discusses biomarkers for immunotherapy in RCC, highlighting current practices and emerging innovations, aiming to contribute to improved outcomes for patients with RCC.

Immunoscore® is a prognostic parameter based on densities of lymphocyte populations in the tumor center and invasive margin. Immunoscore® is validated in colorectal cancer as a high Immunoscore® is associated with longer survival. Previous studies have suggested that Immunoscore® may also predict oncological outcomes in clear-cell renal cell carcinoma (ccRCC). This study aims to assess the prognostic role of immune cell score in ccRCC.

All patients with ccRCC undergoing surgery between 2007 and 2020 in Central Finland Central Hospital were retrospectively identified. CD3+ and CD8+ cell densities were calculated from tissue samples to determine the immune cell score using Immunoscore® principles. Receiver-operating characteristic analysis, Kaplan-Meier survival curve, and Cox regression were used to evaluate the association between immune cell score and survival.

A total of 203 patients (mean age 66.5 years) were identified. The median follow-up time was 6.2 years. Based on the immune cell score, the patients were divided into three groups: low, intermediate, and high. In Cox regression analysis, adjusted with age, sex, and Charlson Comorbidity Index, no significant differences in disease-specific mortality were observed among the three groups. The hazard ratios (HRs) for disease-specific mortality were 0.93 (95% confidence interval [CI] 0.48-1.79) and 1.12 (0.52-2.37) for intermediate- and high-immune cell score groups when compared to low-immune cell score group, respectively.

This study found no association between immune cell score and survival. These results indicate that immune cell score may not serve as a prognostic tool in ccRCC.

This review explores treating metastatic clear cell renal cell carcinoma (ccRCC) through current therapeutic modalities-anti-angiogenic therapies and immunotherapies. While these approaches represent the forefront, their limitations and variable patient responses highlight the need to comprehend underlying resistance mechanisms. We specifically investigate the role of fibrosis, prevalent in chronic kidney disease, influencing tumour growth and treatment resistance. Our focus extends to unravelling the intricate interplay between fibrosis, immunotherapy resistance, and the tumour microenvironment for effective therapy development. The analysis centres on connective tissue growth factor (CTGF), revealing its multifaceted role in ccRCC-promoting fibrosis, angiogenesis, and cancer progression. We discuss the potential of targeting CTGF to address the problem of fibrosis in ccRCC. Emphasising the crucial relationship between fibrosis and the immune system in ccRCC, we propose that targeting CTGF holds promise for overcoming obstacles to cancer treatment. However, we recognise that an in-depth understanding of the mechanisms and potential limitations is imperative and, therefore, advocate for further research. This is an essential prerequisite for the successful integration of CTGF-targeted therapies into the clinical landscape.

To better understand how to clear cell renal cell cancer (ccRCC) is affected by the regulator of G protein signaling-1 (RGS1), its effect on immune infiltration, macrophage polarization, tumor proliferation migration, and to explore whether RGS1 may serve as a marker and therapeutic target for ccRCC.

In this study, a total of 20 surgical specimens of patients with pathological diagnosis of ccRCC admitted to the Department of Urology of the Second Affiliated Hospital of Anhui Medical University from November 2021 to June 2022 were selected for pathological and protein testing, while the expression of RGS1 in tumors, immune infiltration, and macrophage polarization, particularly M2 macrophage linked to the development of tumor microenvironment (TME), were combined with TGCA database and GO analysis. We also further explored and studied the expression and function of RGS1 in TME, investigated how RGS1 affected tumor growth, migration, apoptosis, and other traits, and initially explored the signaling pathways and mechanisms that RGS1 may affect.

RGS1 was found to be expressed at higher quantities in ccRCC than in normal cells or tissues, according to bioinformatics analysis and preliminary experimental data from this work. Using the TCGA database and GO analysis to describe the expression of RGS1 in a range of tumors, it was found that ccRCC had a much higher level of RGS1 expression than other tumor types. The results of gene enrichment analysis indicated that overexpression of RGS1 may be associated with immune infiltration. The outcomes of in vitro tests revealed that RGS1 overexpression in ccRCC did not significantly alter the proliferation and migration ability of ccRCC, but RGS1 overexpression promoted apoptosis in ccRCC. By in vitro co-culture experiments, RGS1 overexpression inhibited M2 macrophage polarization and also suppressed the Jagged-1/Notch signaling pathway.

RGS1 is highly expressed in ccRCC, while overexpression of RGS1 may increase immune infiltration in the TME and reduce the polarization of M2 macrophages while promoting apoptosis in ccRCC.

BCL-2-associated athanogene 3 (BAG3) is an anti-apoptotic protein that plays an essential role in the onset and progression of multiple cancer types. However, the clinical significance of BAG3 in kidney renal clear cell carcinoma (KIRC) remains unclear.

Using Tumor IMmune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) database, we explored the expression, prognostic value, and clinical correlations of BAG3 in KIRC. In addition, immunohistochemistry (IHC) of HKH cohort further validated the expression of BAG3 in KIRC and its impact on prognosis. Gene Set Cancer Analysis (GSCA) was utilized to scrutinize the prognostic value of BAG3 methylation. Gene Ontology (GO) term analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene set enrichment analysis (GSEA) were used to identify potential biological functions of BAG3 in KIRC. Single-sample gene set enrichment analysis (ssGSEA) was performed to confirm the correlation between BAG3 expression and immune cell infiltration.

BAG3 mRNA expression and protein expression were significantly downregulated in KIRC tissues compared to normal kidney tissues, associated with adverse clinical-pathological factors and poor clinical prognosis. Multivariate Cox regression analysis indicated that low expression of BAG3 was an independent prognostic factor in KIRC patients. GSEA analysis showed that BAG3 is mainly involved in DNA methylation and the immune-related pathways in KIRC. In addition, the expression of BAG3 is closely related to immune cell infiltration and immune cell marker set.

BAG3 might be a potential therapeutic target and valuable prognostic biomarker of KIRC and is closely related to immune cell infiltration.

Kidney renal clear cell cancer (KIRC) is a type of urological cancer that occurs worldwide. Core fucosylation (CF), as the most common post-translational modification, is involved in the tumorigenesis.

The alterations of CF-related genes were summarized in pan-cancer. The "ConsensusClusterPlus" package was utilized to identify two CF-related KIRC subtypes. The "ssgsea" function was chosen to estimate the CF score, signaling pathways and cell deaths. Multiple algorithms were applied to assess immune responses. The "oncoPredict" was utilized to estimate the drug sensitivity. The IHC and subgroup analysis was performed to reveal the molecular features of FUT8. Single-cell RNA sequencing (scRNA-seq) data were scrutinized to evaluate the CF state.

In pan-cancer, there was a noticeable alteration in the expression of CF-related genes. In KIRC, two CF-related subtypes (i.e., C1, C2) were obtained. In comparison to C2, C1 exhibited a higher CF score and correlated with poorer overall survival. Additionally, the TME of C2 demonstrated increased activity in neutrophils, macrophages, myeloid dendritic cells, and B cells, alongside a higher presence of silent mast cells, NK cells, and endothelial cells. Compared to normal samples, higher expression of FUT8 is observed in KIRC. The mutation of SETD2 was more frequent in low-FUT8 samples while the mutation of DNAH9 was more frequent in high-FUT8 samples. scRNA-seq analyses revealed that the CF score was predominantly higher in endothelial cells and fibroblast cells.

Two CF-related subtypes with distinct prognosis and TME were identified in KIRC. FUT8 exhibited elevated expression in KIRC samples.

Protein phosphatase 1 regulatory subunit 14B (PPP1R14B) is an oncogenic gene found in a variety of tumors, but its role in the prognosis and development of kidney renal clear cell carcinoma (KIRC) remains unknown. Our study aimed to determine whether PPP1R14B could be a prognostic biomarker for KIRC and its role in the development of KIRC.

In this work, we used The Cancer Genome Atlas (TCGA) database to explore the expression of PPP1R14B in tumor tissues, its relationship with the prognosis of tumor patients, and its role in tumor occurrence and development. We validated our findings using the International Cancer Genome Consortium (ICGC) cohort, our clinical samples, and in vitro experiments.

PPP1R14B was upregulated in KIRC compared to adjacent normal tissue. Moreover, multivariate analysis revealed that upregulated PPP1R14B expression was an independent risk factor for KIRC progression. High-PPP1R14B groups had shorter overall survival (OS) and disease-free survival (DFS) in TCGA and ICGC cohorts. We used Cell Counting Kit-8 (CCK8) and scratch wound healing assay to explore the proliferation and migration of KIRC cells following PPP1R14B knockdown. Our results indicated that PPP1R14B knockdown significantly reduced the proliferation and migration of KIRC cells in vitro. We also explored the possible cellular mechanisms of PPP1R14B through the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene ontology (GO) analysis, and TISIDB analysis. The function enrich analysis revealed that PPP1R14B-related genes were mainly enriched in purine metabolism and the macromolecule catabolic process. PPP1R14B expression was associated with tumor-infiltrating immune cells (TIICs) in the TCGA cohort, and the results of single-cell RNA-seq (scRNA) further demonstrated that PPP1R14B expression was associated with the enhanced infiltration of CD8 + T lymphocytes.

PPP1R14B may serve as a prognostic biomarker in KIRC, affect purine metabolism, activate immune infiltration, and promote KIRC cell migration.

Kidney Renal Clear Cell Carcinoma (KIRC) is a malignant tumor that seriously threatens human health. Rho GTPase-activating protein 4 (ARHGAP4) plays an important role in the occurrence and development of tumors.

The purpose of this study was to explore the role of ARHGAP4 in the progression of KIRC and its diagnostic and prognostic value.

Multiple analytical methods and in vitro cell assays were used to explore the expression of ARHGAP4 and its value in the progression, diagnosis and prognosis of KIRC. The biological function of ARHGAP4 was studied by GO analysis and KEGG pathway analysis, and then the relationship between ARHGAP4 and immune infiltration was analyzed.

The expression of ARHGAP4 was significantly up-regulated in KIRC. We found that the high expression of ARHGAP4 was related to the progression of KIRC and suggested a poor prognosis. Compared with normal tissues, ARHGAP4 had a better diagnostic value in KIRC. The biological function of ARHGAP4 was related to immunity, and its expression was also closely related to tumor immune infiltration and immune checkpoints.

Our study demonstrated that ARHGAP4 may be a biomarker, which is related to the progression, diagnosis and prognosis of KIRC. Its biological functions are related to tumor immune infiltration.