Kidney clear cell carcinoma (KIRC) commonly presents with metastases upon diagnosis, highlighting the critical need to identify more precise biomarkers for early detection, intervention, and personalized treatment. Although The REEP family has been investigated in cancer development, the specific relationship between REEP4 and cancer remains unclear. In our study, we employed bioinformatics analysis and conducted fundamental experiments to evaluate the potential of REEP4 as a biomarker for predicting the prognosis and therapeutic efficacy of KIRC. Comparing KIRC tumor tissues to normal tissues, we observed a significant upregulation in REEP4 expression, with higher levels of REEP4 correlating positively with tumor malignancy. Further COX regression analysis, as well as single and multifactorial analyses, confirmed that high REEP4 expression indicated lower survival rates in KIRC. Gene function analysis also identified associations between REEP4 and critical pathways such as the cell cycle, along with its involvement in protein binding. Furthermore, our investigation of the immune response suggests that a favorable immunotherapeutic response is linked to a reduction in REEP4 expression. Subsequently, we conducted in vitro experiments to confirm the overexpression of REEP4 in KIRC tumor tissues and renal cancer cells. In summary, our study revealed a close association between REEP4 expression and KIRC, emphasizing its correlation with prognosis and the immune response. These findings suggest that REEP4 is a potential biomarker for KIRC.

Troponin T1 (TNNT1) plays a crucial role in muscle contraction but its role in cancer, particularly in kidney renal clear cell carcinoma (KIRC), is not well-understood. This study explores the expression, clinical significance and biological functions of TNNT1 in various cancers, with an emphasis on its involvement in KIRC. We analysed TNNT1 expression in cancers using databases like TCGA and GTEx, assessing its prognostic value, mutation patterns, methylation status and functional implications. The study also examined TNNT1\'s effect on the tumour microenvironment and drug sensitivity in KIRC, complemented by in vitro TNNT1 knockdown experiments in KIRC cells. TNNT1 is overexpressed in several cancers and linked to adverse outcomes, showing frequent upregulation mutations and abnormal methylation. Functionally, TNNT1 connects to muscle and cancer pathways, affects immune infiltration and drug responses, and its overexpression in KIRC is associated with advanced disease and reduced survival. Knocking down TNNT1 curbed KIRC cell growth. TNNT1\'s aberrant expression plays a significant role in tumorigenesis and immune modulation, highlighting its value as a prognostic biomarker and a potential therapeutic target in KIRC and other cancers. Further studies are essential to understand TNNT1\'s oncogenic mechanisms in KIRC.

Kidney Clear Cell Carcinoma (KIRC), the predominant form of kidney cancer, exhibits a diverse therapeutic response to Immune Checkpoint Inhibitors (ICIs), highlighting the need for predictive models of ICI efficacy. Our study has constructed a prognostic model based on 13 types of Programmed Cell Death (PCD), which are intertwined with tumor progression and the immune microenvironment. Validated by analyses of comprehensive datasets, this model identifies seven key PCD genes that delineate two subtypes with distinct immune profiles and sensitivities to anti-PD-1 therapy. The high-PCD group demonstrates a more immune-suppressive environment, while the low-PCD group shows better responses to PD-1 treatment. In particular, TOP2A emerged as crucial, with its inhibition markedly reducing KIRC cell growth and mobility. These findings underscore the relevance of PCDs in predicting KIRC outcomes and immunotherapy response, with implications for enhancing clinical decision-making.

UNASSIGNED: Abnormally expressed Runt-associated transcription factor (RUNX) family has been reported in multiple tumors. Nevertheless, the immunological role of RUNX family in kidney renal clear cell carcinoma (KIRC) remains unknown.
UNASSIGNED: We studied the RNA-seq data regarding tumor and healthy subjects from several public databases in detail for evaluating the prognostic and immunological functions owned by three RUNX genes in cancer patients. Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) and immunohistochemical (IHC) staining served for detecting their expressions in tumor and normal samples.
UNASSIGNED: We observed that KIRC patients presented high expressions of RUNX1, RUNX2, and RUNX3. The expressions of three genes were validated by qRT-PCR, which was same as bioinformatical results. Prognostic analysis indicated that the overexpression of RUNX1 and RUNX2 negatively affects the outcomes in patients with KIRC. Related functional predictions indicated that the RUNXs and co-expression genes were significantly related to the immune response pathway. Moreover, three RUNX members were associated with immune infiltration cells and their related gene markers. The expression of RUNX family in several immune cells is positively or negatively correlated, and its dysregulation is obviously associated with the differential distribution of immune cells. RUNX family genes were abnormally expressed in KIRC patients, and were closely related to the crosstalk of immune cells.
UNASSIGNED: Our findings may help to understand the pathogenesis and immunologic roles of the RUNX family in KIRC patients from new perspectives.

Kidney Renal Clear Cell Carcinoma (KIRC) is a malignant tumor that carries a substantial risk of morbidity and mortality. The MMP family assumes a crucial role in tumor invasion and metastasis. This study aimed to uncover the mechanistic relevance of the MMP gene family as a therapeutic target and diagnostic biomarker in Kidney Renal Clear Cell Carcinoma (KIRC) through a comprehensive approach encompassing both computational and molecular analyses. STRING, Cytoscape, UALCAN, GEPIA, OncoDB, HPA, cBioPortal, GSEA, TIMER, ENCORI, DrugBank, targeted bisulfite sequencing (bisulfite-seq), conventional PCR, Sanger sequencing, and RT-qPCR based analyses were used in the present study to analyze MMP gene family members to accurately determine a few hub genes that can be utilized as both therapeutic targets and diagnostic biomarkers for KIRC. By performing STRING and Cytohubba analyses of the 24 MMP gene family members, MMP2 (matrix metallopeptidase 2), MMP9 (matrix metallopeptidase 9), MMP12 (matrix metallopeptidase 12), and MMP16 (matrix metallopeptidase 16) genes were denoted as hub genes having highest degree scores. After analyzing MMP2, MMP9, MMP12, and MMP16 via various TCGA databases and RT-qPCR technique across clinical samples and KIRC cell lines, interestingly, all these hub genes were found significantly overexpressed at mRNA and protein levels in KIRC samples relative to controls. The notable effect of the up-regulated MMP2, MMP9, MMP12, and MMP16 was also documented on the overall survival (OS) of the KIRC patients. Moreover, targeted bisulfite-sequencing (bisulfite-seq) analysis revealed that promoter hypomethylation pattern was associated with up-regulation of hub genes (MMP2, MMP9, MMP12, and MMP16). In addition to this, hub genes were involved in various diverse oncogenic pathways. The MMP gene family members (MMP2, MMP9, MMP12, and MMP16) may serve as therapeutic targets and prognostic biomarkers in KIRC.

UNASSIGNED: COVID-19 is a severe infectious disease caused by the SARS-CoV-2 virus, and previous studies have shown that patients with kidney renal clear cell carcinoma (KIRC) are more susceptible to SARS-CoV-2 infection than the general population. Nevertheless, their co-pathogenesis remains incompletely elucidated.
UNASSIGNED: We obtained shared genes between these two diseases based on public datasets, constructed a prognostic risk model consisting of hub genes, and validated the accuracy of the model using internal and external validation sets. We further analyzed the immune landscape of the prognostic risk model, investigated the biological functions of the hub genes, and detected their expression in renal cell carcinoma cells using qPCR. Finally, we searched the candidate drugs associated with hub gene-related targets from DSigDB and CellMiner databases.
UNASSIGNED: We obtained 156 shared genes between KIRC and COVID-19 and constructed a prognostic risk model consisting of four hub genes. Both shared genes and hub genes were highly enriched in immune-related functions and pathways. Hub genes were significantly overexpressed in COVID-19 and KIRC. ROC curves, nomograms, etc., showed the reliability and robustness of the risk model, which was validated in both internal and external datasets. Moreover, patients in the high-risk group showed a higher proportion of immune cells, higher expression of immune checkpoint genes, and more active immune-related functions. Finally, we identified promising drugs for COVID-19 and KIRC, such as etoposide, fulvestrant, and topotecan.
UNASSIGNED: This study identified and validated four shared genes for KIRC and COVID-19. These genes are associated with immune functions and may serve as potential prognostic biomarkers for KIRC. The shared pathways and genes may provide new insights for further mechanistic research and treatment of comorbidities.

BACKGROUND: Kidney cancer is an immunogenic solid tumor, characterized by high tumor burden and infiltration of CD8+ T cells. Although immunotherapy targeting the PD1/CTLA-4 axis has demonstrated excellent clinical efficacy, clinical outcomes in most patients are poor.
METHODS: We used the RNA sequencing data from the GEO database for KIRC GSE121636 and normal kidney tissue GSE131685, and performed single-cell analysis for cluster identification, pathway enrichment, and CD8+ T cell-associated gene identification. Subsequently, the significance of different CD8+ T-cell associated gene subtypes was elucidated by consensus clustering, pathway analysis, mutated gene analysis, and KIRC immune microenvironment analysis in the TCGA-KIRC disease cohort. Single gene analysis identified LAG3 as the most critical CD8+ T-cell-associated gene and its function was verified by cell phenotype and immunohistochemistry in KIRC.
RESULTS: In the present study, CD8+ T-cell associated genes in KIRC were screened, including GZMK, CD27, CCL4L2, FXYD2, LAG3, RGS1, CST7, DUSP4, CD8A, and TRBV20-1 and an immunological risk prognostic model was constructed (risk score =  - 0.291858656434841*GZMK - 0.192758342489394*FXYD2 + 0.625023643446193*LAG3 + 0.161324477181591*RGS1 - 0.380169045328895*DUSP4 - 0.107221347575037*TRBV20-1). LAG3 was identified and proved as the most critical CD8+ T cell-associated gene in KIRC.
CONCLUSIONS: We proposed and constructed an immunological risk prognostic model for CD8+ T cell-associated genes and identified LAG3 as a pivotal gene for KIRC progression and CD8+ T-cell infiltration. The model comprehensively explained the immune microenvironment and provided novel immune-related therapeutic targets and biomarkers in KIRC.

The most prevalent and insidious type of kidney cancer is kidney clear cell carcinoma (KIRC). Thioredoxin-interacting protein (TXNIP) encodes a thioredoxin-binding protein involved in cellular energy metabolism, redox homeostasis, apoptosis induction and inflammatory responses. However, the relationship between TXNIP, immune infiltration and its prognostic value in KIRC remains unclear. Thus, the present study evaluated the potential for TXNIP as a prognostic marker in patients with KIRC. Data from The Cancer Genome Atlas were used to assess relative mRNA expression levels of TXNIP in different types of cancer. The protein expression levels of TXNIP were evaluated using the Human Protein Atlas. Enrichment analysis of genes co-expressed with TXNIP was performed to assess relevant biological processes that TXNIP may be involved in. CIBERSORT was used to predict the infiltration of 21 tumor-infiltrating immune cells (TIICs). Univariate and multivariate Cox regression analyses were used to assess the relationship between TXNIP expression and prognosis. Single-cell RNA-sequencing datasets were used to evaluate the mRNA expression levels of TXNIP in certain immune cells in KIRC. The CellMiner database was used to analyze the relationship between TXNIP mRNA expression and drug sensitivity in KIRC. The results from the present study demonstrated that TXNIP expression was significantly decreased in KIRC tissue compared with that in normal tissue, as confirmed by western blotting and reverse transcription-quantitative PCR. In addition, downregulated TXNIP expression was significantly associated with poor prognosis, a high histological grade and an advanced stage. The Cell Counting Kit-8 assay demonstrated that TXNIP overexpression significantly suppressed tumor cell proliferation. Univariate and multivariate Cox regression analyses indicated that TXNIP served as a separate prognostic factor in KIRC. Moreover, TXNIP expression was significantly correlated with the accumulation of several TIICs and its overexpression significantly downregulated the mRNA expression levels of CD25 and cytotoxic T-lymphocyte-associated protein 4, immune cell surface markers in CD4+ T lymphocytes. In conclusion, TXNIP may be used as a possible biomarker to assess unfavorable prognostic outcomes and identify immunotherapy targets in KIRC.

Immune checkpoint blockade (ICB) therapy has resulted in improved overall survival in kidney renal clear cell carcinoma (KIRC), but most treated patients fail to show durable clinical responses. Lymphocyte activation gene-3 (LAG3) is a novel inhibitory immune checkpoint, but its expression pattern, prognostic value, and immunological role in KIRC remain unknown. In this study, we utilized TCGA_KIRC RNA-sequencing data to analyze the relationship between LAG3 expression and clinical features. The single-cell sequencing data and tissue immunofluorescence are employed to investigate the subcellular localization of LAG3 in KIRC. Kaplan-Meier plotter, TIMER, and TISIDB were used to assess the association between LAG3 expression and prognosis, as well as its correlation with immune-related components. We constructed the LAG3 interaction network by using STRING, GeneMANIA, BioGRID, and HitPredict databases. We found that LAG3 is upregulated and correlates with poor prognostic phenotype in KIRC. LAG3 is predominantly expressed on exhausted CD8+ T cells and shows strong co-expression with PDCD1 in KIRC. Moreover, our findings indicated that LAG3 not only inhibits T cell activation but also potentially regulates cell adhesion in KIRC. In conclusion, our study implies that LAG3 can serve as a potential prognostic biomarker for KIRC. Furthermore, blocking both LAG3 and PDCD1 may alleviate resistance to anti-PDCD1 therapy, providing novel insights for immunotherapy decision-making in KIRC patients.

The Purinergic pathway is involved in a variety of important physiological processes in living organisms, and previous studies have shown that aberrant expression of the Purinergic pathway may contribute to the development of a variety of cancers, including kidney renal clear cell carcinoma (KIRC). The aim of this study was to delve into the Purinergic pathway in KIRC and to investigate its potential significance in prognostic assessment and clinical treatment. 33 genes associated with the Purinergic pathway were selected for pan-cancer analysis. Cluster analysis, targeted drug sensitivity analysis and immune cell infiltration analysis were applied to explore the mechanism of Purinergic pathway in KIRC. Using the machine learning process, we found that combining the Lasso+survivalSVM algorithm worked well for predicting survival accuracy in KIRC. We used LASSO regression to pinpoint nine Purinergic genes closely linked to KIRC, using them to create a survival model for KIRC. ROC survival curve was analyzed, and this survival model could effectively predict the survival rate of KIRC patients in the next 5, 7 and 10 years. Further univariate and multivariate Cox regression analyses revealed that age, grading, staging, and risk scores of KIRC patients were significantly associated with their prognostic survival and were identified as independent risk factors for prognosis. The nomogram tool developed through this study can help physicians accurately assess patient prognosis and provide guidance for developing treatment plans. The results of this study may bring new ideas for optimizing the prognostic assessment and therapeutic approaches for KIRC patients.