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 | 2020
REPOSITORIES: biostudies-literature
Publications
The immune infiltration in clear cell Renal Cell Carcinoma and their clinical implications: A study based on TCGA and GEO databases.
Pan Qiufeng Q Wang Longwang L Chai Shuaishuai S Zhang Hao H Li Bing B
Journal of Cancer 20200305 11
The tumor immune microenvironment in clear cell Renal Cell Carcinoma (ccRCC) still remains poorly understood. Previous methods to study the tumor immune microenvironment have a limitation when accounting for the functionally distinct cell types. In this study, we investigated the differently infiltrated immune cells and their clinical significance in ccRCC for the purpose of shedding some important light on the complex immune microenvironment in ccRCC. The devolution algorithm (CIBERSORT) was ap ...[more]
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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.
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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.
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Project description:Hepatocellular carcinoma (HCC) is a primary liver cancer with extremely high mortality in worldwide. HCC is hard to diagnose and has a poor prognosis due to the less understanding of the molecular pathological mechanisms and the regulation mechanism on immune cell infiltration during hepatocarcinogenesis. Herein, by performing multiple bioinformatics analysis methods, including the RobustRankAggreg (RRA) rank analysis, weighted gene co-expression network analysis (WGCNA), and a devolution algorithm (CIBERSORT), we first identified 14 hub genes (NDC80, DLGAP5, BUB1B, KIF20A, KIF2C, KIF11, NCAPG, NUSAP1, PBK, ASPM, FOXM1, TPX2, UBE2C, and PRC1) in HCC, whose expression levels were significantly up-regulated and negatively correlated with overall survival time. Moreover, we found that the expression of these hub genes was significantly positively correlated with immune infiltration cells, including regulatory T cells (Treg), T follicular helper (TFH) cells, macrophages M0, but negatively correlated with immune infiltration cells including monocytes. Among these hub genes, KIF2C and UBE2C showed the most significant correlation and were associated with immune cell infiltration in HCC, which was speculated as the potential prognostic biomarker for guiding immunotherapy.
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Project description:BackgroundChromatin regulators (CRs) are capable of causing epigenetic alterations, which are significant features of cancer. However, the function of CRs in controlling Clear Cell Renal Cell Carcinoma (ccRCC) is not well understood. This research aims to discover a CRs prognostic signature in ccRCC and to elucidate the roles of CRs-related genes in tumor microenvironment (TME).MethodsExpression profiles and relevant clinical annotations were retrieved from the Cancer Genome Atlas (TCGA) and UCSC Xena platform for progression-free survival (PFS) data. The R package "limma" was used to identify differentially expressed CRs. A predictive model based on five CRs was developed using LASSO-Cox analysis. The model's predictive power and applicability were validated using K-M curves, ROC curves, nomograms, comparisons with other models, stratified survival analyses, and validation with the ICGC cohort. GO and GSEA analyses were performed to investigate mechanisms differentiating low and high riskScore groups. Immunogenicity was assessed using Tumor Mutational Burden (TMB), immune cell infiltrations were inferred, and immunotherapy was evaluated using immunophenogram analysis and the expression patterns of human leukocyte antigen (HLA) and checkpoint genes. Differentially expressed CRs (DECRs) between low and high riskScore groups were identified using log2|FC|> 1 and FDR < 0.05. AURKB, one of the high-risk DECRs and a component of our prognostic model, was selected for further analysis.ResultsWe constructed a 5 CRs signature, which demonstrated a strong capacity to predict survival and greater applicability in ccRCC. Elevated immunogenicity and immune infiltration in the high riskScore group were associated with poor prognosis. Immunotherapy was more effective in the high riskScore group, and certain chemotherapy medications, including cisplatin, docetaxel, bleomycin, and axitinib, had lower IC50 values. Our research shows that AURKB is critical for the immunogenicity and immune infiltration of the high riskScore group.ConclusionOur study produced a reliable prognostic prediction model using only 5 CRs. We found that AURKB promotes immunogenicity and immune infiltration. This research provides crucial support for the development of prognostic biomarkers and treatment strategies for ccRCC.
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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.
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Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is known as the most common and malignant histologic subtype of renal carcinoma. Sorting nexin 4 (SNX4) plays a regulatory role in recycling from endosomes to the plasma membrane and promotes autophagosome assembly and transport, which may exert the cancerous growth and progression. This study aimed to assess the biological role of SNX4 in ccRCC and their clinical association via public biological data platforms combined with experimental verification.MethodsIn our study, we analyzed the mRNA and protein expression of SNX4 in ccRCC under different clinicopathological characteristics through The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases. We used the Gene Expression Profiling Interactive Analysis (GEPIA) platform to conduct the survival analysis and figure out the immune cell infiltration level under different expression levels of SNX4 combined with Tumor Immune Estimation Resource (TIMER) database. Furthermore, we predicted competing endogenous RNA (ceRNA) regulatory network using TargetScan, miRDB, starBase and miRTarBase online databases. We totally collected six paired ccRCC tissues and adjacent tissues and applied quantitative real-time polymerase chain reaction (qRT-PCR) and western blot (WB) to detect the expression of SNX4 in the collected clinical specimens.ResultsThe mRNA and protein expression level of SNX4 was significantly lower in ccRCC than those in normal tissues. The results proposed that lower SNX4 was expressed in patients with higher histologic grade and in male patients. Kaplan-Meier analysis demonstrated that lower mRNA expression level of SNX4 was correlated with poorer prognosis. SNX4 had positive correlation with immune cell infiltrating levels and programmed cell death-ligand 1 (PD-L1) expression. Furthermore, we constructed the SNX4/miR-221-3p/miR-222-3p/DHRS4-AS1 axis, which may be the underlying ceRNA interaction network. Finally, we verified the reduced expression of SNX4 in ccRCC by qRT-PCR and WB.ConclusionThe expression of SNX4 in ccRCC was lower than adjacent tissues and its downregulated expression was associated with poor prognosis of ccRCC patients. SNX4 may exert critical roles in the tumorigenesis, development and migration of ccRCC via various mechanisms.
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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.
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Project description:BackgroundReduced expression of thyroid hormone receptors (TRs) has been observed in various human malignancies, though its predictive value in hepatocellular carcinoma (HCC) remains uncertain.ObjectiveTo explore the predictive value of TRs in patients with hepatocellular carcinoma.DesignThe design was bioinformatic analysis combined with experimental study.MethodsThis study utilized Kaplan-Meier analysis of TR expression profiles from The Cancer Genome Atlas (TCGA). Expression levels of TRs in HCC and immune single cells were assessed using datasets from the Gene Expression Omnibus (GEO) and TCGA, analyzed with R software. Cox and logistic regression analyses were also conducted. Functional assays, including wound healing, CCK-8, and Transwell migration assays, were employed to investigate the role of the THRB gene.ResultsKaplan-Meier analysis revealed that low THRB expression was significantly associated with reduced overall survival (OS), 5-year OS and disease-specific survival (DSS) in HCC patients (P < 0.05), while no significant association was found with THRA expression. Both Cox regression and logistic regression identified low THRB expression as an independent risk factor for HCC. THRB expression was significantly downregulated in tumor tissues compared to non-tumorous tissues in 3 GEO datasets and the TCGA profile. Functional assays confirmed that THRB inhibited HCC cell proliferation and migration. Additionally, single-cell RNA sequencing revealed that THRB was primarily expressed in CD16+ monocytes within tumor tissues and was associated with a poor OS rate.ConclusionReduced THRB expression, but not THRA, was correlated with decreased OS in HCC patients.
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