The immune infiltration in clear cell Renal Cell Carcinoma and their clinical implications: A study based on TCGA and GEO databases.
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ABSTRACT:
SUBMITTER: Pan Q
PROVIDER: S-EPMC7097965 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is a commonly occurring tumor. Through a deeper understanding of the immune regulatory mechanisms in the tumor microenvironment, immunotherapy may serve as a potential treatment for cancer patients. This study aimed at identifying the survival-related immune cells and hub genes, which could be potential targets for immunotherapy in ccRCC.MethodsThe gene expression profiles and clinical data of ccRCC patients were extracted from UCSC Xena and Gene Expression Omnibus (GEO) databases. Kaplan-Meier (KM) survival and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were utilized to select the survival-related tumor-infiltrating immune cells. Multivariate Cox regression was utilized to develop a signature based on the tumor-infiltrating immune cells (TIICs). Based on the signature, the risk score was calculated, following which the samples were divided into high-risk and low-risk groups. Differentially expressed genes (DEGs) between the two risk groups were identified. Functional enrichment analysis was performed and cytoHubba plug-in of Cytoscape was used to identify the hub genes. Multiple datasets were utilized to validate these hub genes, including the Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and the Human Protein Atlas (HPA), and the GEO datasets. Finally, a correlation analysis was performed to evaluate the relationship between the hub genes and TIICs.ResultsFour immune survival-related cells, including T cell CD4 memory-activated, T cell regulatory (Tregs), eosinophils, and mast cell resting were identified. Nine immune-specific hub genes were identified, which included APOE, CASR, CTLA4, CXCL8, EGF, F2, KNG1, MMP9, and IL6. Furthermore, these hub genes were significantly correlated with clinical traits and closely associated with some TIICs.ConclusionA total of four survival-related immune cell types and nine hub genes were found to be closely associated with ccRCC. These findings may have implications for the development of novel potential immunotherapeutic targets for ccRCC.
| S-EPMC8754506 | biostudies-literature
Project description:The malignant phenotypes of cancer are defined not only by its intrinsic tumor cells but also by the tumor infiltrating immune cells (TIICs) recruited to the cancer microenvironment. Clear cell renal cell carcinoma (ccRCC) immune microenvironment plays an important role in the tumorigenesis. This research investigated the characteristics of immune cell invasion of renal cell carcinoma and provided clues for future clinical implementation. Retrospectively, ccRCC gene expression was analyzed with appropriate clinicopathological data from the Cancer Genome Atlas (TCGA) and GEO database up to December 2019. The CIBERSORT algorithm, meta-analysis, principal component analysis (PCA), Single-Sample Gene Set Enrichment Analysis (ssGSEA) and hierarchical agglomerative clustering were used to measure and evaluate the respective proportions of 22 cell types of immune infiltration using normalized gene expression data. We also focused on evaluating the association with TIICs subpopulations and clinical features and molecular subtypes. TIICs subpopulation, especially Macrophages subgroup, T follicular helper (Tfh) cells and CD8 T cells, all contribute to tumorigenesis. Unsupervised clustering analysis revealed that there existed two distinct TIICs subgroups with different survival patterns. TIICs are extensively involved in the pathogenesis and development of the ccRCC. Characterizing the composition of TIICs influences the metabolism of tumors, activity, level, stage, and survival of patients. Collectively, the TIIC analysis has the potential to assist in the assessment and selection of ccRCC prognosis and treatment.
| S-EPMC7923891 | biostudies-literature
Project description:BackgroundIntratumoral fibrosis was positively correlated with histological grade of renal clear cell carcinoma (ccRCC) and intratumoral inflammation. However, the association of intratumoral fibrosis with the immune infiltration of ccRCC was few evaluated.MethodsWe used the second harmonic generation (SHG)-based imaging technology and evaluated the intratumoral fibrosis in ccRCC, and then divided the patients into the high fibrosis group (HF) and the low fibrosis group (LF). Meanwhile, the Kaplan-Meier survival curve analysis was performed to analyze the relationship between intratumoral fibrosis and the disease-free survival rate. Antibody arrays were used for seeking difference in cytokines and immune infiltration between the HF group (N = 11) and LF group (N = 11). The selected immune infiltration marker was then verified by immunohistochemistry (IHC) staining in 45 ccRCC samples.ResultsOut of 640 cytokines and immune infiltration markers, we identified 115 proteins that were significantly different in quantity between ccRCC and adjacent normal tissues. In addition, the Venn diagram indicated that six proteins, including Cytotoxic T-Lymphocyte Associated Protein 4 (CTLA4), were significantly associated with intratumoral fibrosis (p < 0.05). The GO/KEGG enrichment analysis indicated that the proteins associated with intratumoral fibrosis were involved in the immunity and tumor-infiltrating lymphocytes. The expression of the CTLA4 was negatively correlated with collagen level, confirmed by IHC staining of CTLA4 (p < 0.05).ConclusionsThe study indicated that the intratumoral fibrosis level was negatively correlated with the expression of CTLA4 in the tumor immune microenvironment of the ccRCC, which posed the potential value of targeting the stroma of the tumor, a supplement to immunotherapy. However, the specific mechanism of this association is still unclear and needs further investigation.
| S-EPMC9205105 | biostudies-literature
Project description:The tumor microenvironment, comprised of tumor cells and tumor-infiltrating immune cells, is closely associated with the clinical outcome of clear cell renal cell carcinoma (ccRCC) patients. However, the landscape of immune infiltration in ccRCC has not been fully elucidated. Herein, we applied multiple computational methods and various datasets to reveal the immune infiltrative landscape of ccRCC patients. The tumor immune infiltration (TII) levels of 525 ccRCC patients using a single-sample gene were examined and further categorized into immune infiltration subgroups. The TII score was characterized by distinct clinical traits and showed a significant divergence based on gender, grade, and stage. A high TII score was associated with the ERBB signaling pathway, the TGF-β signaling pathway, and the MTOR signaling pathway, as well as a better prognosis. Furthermore, patients with high TII scores exhibited greater sensitivity to pazopanib. The low TII score was characterized by a high immune infiltration level of CD8+ T cells, T follicular helper cells, and regulatory T cells (Tregs). Moreover, the immune check point genes, including CTLA-4, LAG3, PD-1, and IDO1, presented a high expression level in the low TII score group. Patients in the high TII score group demonstrated significant therapeutic advantages and clinical benefits. The findings in this study have the potential to assist in the strategic design of immunotherapeutic treatments for ccRCC.
| S-EPMC8177771 | biostudies-literature
Project description:Mammalian target of rapamycin (mTOR), a serine/threonine kinase involved in cell proliferation, survival, metabolism and immunity, was reportedly activated in various cancers. However, the clinical role of mTOR in renal cell carcinoma (RCC) is controversial. Here we detected the expression and prognosis of total mTOR and phosphorylated mTOR (p-mTOR) in clear cell RCC (ccRCC) patients, and explored the interactions between mTOR and immune infiltrates in ccRCC. The protein level of mTOR and p-mTOR was determined by western blotting (WB), and their expression was evaluated in 145 ccRCC and 13 non-tumor specimens by immunohistochemistry (IHC). The relationship to immune infiltration of mTOR was further investigated using TIMER and TISIDB databases, respectively. WB demonstrated the ratio of p-mTOR to mTOR was higher in ccRCC than adjacent specimens (n = 3), and IHC analysis elucidated that p-mTOR expression was positively correlated with tumor size, stage and metastasis status, and negatively correlated with cancer-specific survival (CSS). In univariate analysis, high grade, large tumor, advanced stage, metastasis, and high p-mTOR expression were recognized as prognostic factors of poorer CSS, and multivariate survival analysis elucidated that tumor stage, p-mTOR and metastasis were of prognostic value for CSS in ccRCC patients. Further TIMER and TISIDB analyses uncovered that mTOR gene expression was significantly associated with numerous immune cells and immunoinhibitors in patients with ccRCC. Collectively, these findings revealed p-mTOR was identified as an independent predictor of poor survival, and mTOR was associated with tumor immune infiltrates in ccRCC patients, which validated mTOR could be implicated in the initiation and progression of ccRCC.
| S-EPMC8378334 | biostudies-literature
Project description:BackgroundIdentify key biomarkers to improve the clinical prognosis of patients with advanced and metastatic clear cell renal cell carcinoma (ccRCC) remains an important research topic. Recently, ccRCC has been regarded as a metabolic disease. Pantothenate kinase-1 (PANK1) has been shown to play an important regulatory role in global metabolism and associates with the pathogenesis of hepatocellular carcinoma. Therefore, we aimed to investigate the role of PANK1 in the prognosis of ccRCC and in metabolism and immunity.MethodsPANK1 messenger ribonucleic acid (RNA) expression patterns in ccRCC using The Cancer Genome Atlas (TCGA) database. The clinical prognostic significance of PANK1 in ccRCC and a Cox regression was performed to evaluate the clinical factors associated with prognosis with confounding factors adjusted. The signaling pathways related to PANK1 expression were identified by Gene Ontology (GO) investigation and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The Tumor Immune Estimation Resource database was used to analyze the correlation between PANK1 and tumor-infiltrating immune cells.ResultsA total of 539 ccRCC patients and corresponding clinical samples and data from TCGA were included in this analysis. Significant differences were observed in PANK1 expression levels between tumor tissues and adjacent normal tissues in both TCGA-Kidney Renal Clear Cell Carcinoma cohort (4.40 vs. 2.94, P<0.001). PANK1 expression was found to be correlated with pathological stage, histological grade, age, sex, and clinical prognosis. Specifically, the low expression of PANK1 was found to be closely related to poor overall survival (OS), disease-specific survival (DSS), and the progression-free survival (PFS) in ccRCC patients. The receiver operating characteristic curve suggested that PANK1 could be a potential prognostic biomarker (area under the curve =0.880), and that the promoter methylation levels of PANK1 were correlated with clinical factors. Further, PANK1 expression was found to be associated with multiple immune cell types and correlated with the enrichment of these cells. Finally, we further investigated the role of PANK1 in tumor growth and mitochondrial metabolism using ccRCC cells.ConclusionsPANK1 correlates with ccRCC prognosis, tumor immune status and metabolism using the TCGA data. PANK1 might be a prognostic marker of clinical prognosis for ccRCC patients.
| S-EPMC9372198 | biostudies-literature
Project description:Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the urinary system. Ferroptosis plays a vital role in ccRCC development and progression. We did an update of ferroptosis-related multigene expression signature for individualized prognosis prediction in patients with ccRCC. Differentially expressed ferroptosis-related genes in ccRCC and normal samples were screened using The Cancer Genome Atlas. Univariate and multivariate Cox regression analyses and machine learning methods were employed to identify optimal prognosis-related genes. CARS1, CD44, FANCD2, HMGCR, NCOA4, SLC7A11, and ACACA were selected to establish a prognostic risk score model. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that these genes were mainly enriched in immune-related pathways; single-sample Gene Set Enrichment Analysis revealed several immune cells potentially related to ferroptosis. Kaplan-Meier survival analysis demonstrated that patients with high-risk scores had significantly poor overall survival (log-rank P = 7.815 × 10-11). The ferroptosis signature was identified as an independent prognostic factor. Finally, a prognostic nomogram, including the ferroptosis signature, age, histological grade, and stage status, was constructed. Analysis of The Cancer Genome Atlas-based calibration plots, C-index, and decision curve indicated the excellent predictive performance of the nomogram. The ferroptosis-related seven-gene risk score model is useful as a prognostic biomarker and suggests therapeutic targets for ccRCC. The prognostic nomogram may assist in individualized survival prediction and improve treatment strategies.
| S-EPMC8220217 | biostudies-literature
Project description:Growing evidence has highlighted the immune response as an important feature of carcinogenesis and therapeutic efficacy in clear cell renal cell carcinoma (ccRCC). This study categorized ccRCC cases into high and low score groups based on their immune/stromal scores generated by the ESTIMATE algorithm, and identified an association between these scores and prognosis. Differentially expressed tumor environment (TME)-related genes extracted from common upregulated components in immune and stromal scores were described using functional annotations and protein-protein interaction (PPI) networks. Most PPIs were selected for further prognostic investigation. Many additional previously neglected signatures, including AGPAT9, AQP7, HMGCS2, KLF15, MLXIPL, PPARGC1A, exhibited significant prognostic potential. In addition, multivariate Cox analysis indicated that MIXIPL and PPARGC1A were the most significant prognostic signatures, and were closely related to immune infiltration in TCGA cohort. External prognostic validation of MIXIPL and PPARGC1A was undertaken in 380 ccRCC cases from a real-world cohort. These findings indicate the relevance of monitoring and manipulation of the microenvironment for ccRCC prognosis and precision immunotherapy.
| S-EPMC6756904 | biostudies-literature
Project description:The role and underlying mechanism of cytoplasmic polyadenylation element binding protein 3 (CPEB3) in clear cell renal cell carcinoma [ccRCC progression remain poorly characterized. The present study was designed to evaluate the role of CPEB3 in ccRCC and its clinical associations. The overall response rate of first-line therapies (ICIs combined with VEGFR-TKIs or ICI combination) for ccRCC] is 42.0-59.3%, so a number of patients with ccRCC do not benefit from these therapies. To avoid immunosurveillance and immune killing, tumor cells decrease immunogenicity and recruit immunosuppressive cells such as regulatory T cells (Tregs). Tregs inhibit the development of anti-tumor immunity, thereby hindering immune surveillance of cancer and preventing effective anti-tumor immune response in tumor-bearing hosts. The present study analyzed clinical specimens from patients ccRCC and then examined the role of CPEB3 in ccRCC via bioinformatics analysis. CPEB3 expression was significantly reduced in ccRCC compared with normal tissue and low CPEB3 expression was associated with poor overall survival. Moreover, CPEB3 expression was an independent predictor of survival. CPEB3 expression was positively associated with immune biomarkers [CD274, programmed cell death 1 ligand 2, Hepatitis a virus cellular receptor 2, Chemokine (C-X-C motif) ligand (CXCL)9, CXCL10, Inducible T cell costimulatory, CD40, CD80 and CD38] that improve the outcome of anti-tumor immune responses. CPEB3 expression in ccRCC also affected the status of 24 types of infiltrating immune cell, of which Tregs were the most significantly negatively correlated cell type. CPEB3 may serve as a prognostic biomarker in ccRCC and its mechanism may be related to the regulation of Tregs.
| S-EPMC10928475 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) has become the fifth most common cancer globally, with the second-highest mortality rate and poor survival outcomes. In our research, we aimed to use The Cancer Genome Atlas and gene expression omnibus databases to identify potential genetic biomarkers to predict and improve the survival rate of HCC patients.MethodsIn GSE60502, GSE76427, and GSE84402, we performed differential expression analysis to obtain differentially expressed genes (DEGs). In the The Cancer Genome Atlas database, the FPKM expression profile was subjected to weighted gene co-expression analysis to obtain modules closely related to HCC. We received common genes by intersecting the genes in the module with the differential genes. Then, we fused the common genes' expression profiles, survival time, and survival status for univariate, Least Absolute Shrinkage and Selection Operator, and multivariate COX regression analysis to obtain prognostic genes. Predictive genes were performed in K-M survival analysis and combined with clinical data for independent predictive analysis.ResultsAfter differential expression analysis, GSE60502 obtained 1107 DEGs, GSE76427 obtained 424 DEGs, and GSE84402 obtained 1668 DEGs. Through weighted gene co-expression analysis analysis, we can see that the blue and brown modules were closely associated with HCC. After single and multivariate COX regression analysis, we found that suppressor of cytokine signaling 2 (SOCS2) and SERPINF2 were independent prognostic genes for HCC. After survival analysis, HCC patients with high expression of SOCS2 and SERPINF2 had a longer survival time. These 2 genes in normal liver tissues were higher than in HCC at the transcriptional level.ConclusionSOCS2 and SERPINF2 were new independent prognostic genes of HCC. So, they may provide new treatment methods and measures for diagnosing HCC.
| S-EPMC9622571 | biostudies-literature