A Five Collagen-Related Gene Signature to Estimate the Prognosis and Immune Microenvironment in Clear Cell Renal Cell Cancer.
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ABSTRACT:
SUBMITTER: Shi X
PROVIDER: S-EPMC8707639 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Kidney renal clear cell carcinoma (KIRC) is a heterogeneous malignant tumor with high incidence, metastasis, and mortality. The imbalance of copper homeostasis can produce cytotoxicity and cause cell damage. At the same time, copper can also induce tumor cell death and inhibit tumor transformation. The latest research found that this copper-induced cell death is different from the known cell death pathway, so it is defined as cuproptosis. We included 539 KIRC samples and 72 normal tissues from the Cancer Genome Atlas (TCGA) in our study. After identifying long non-coding RNAs (lncRNAs) significantly associated with cuproptosis, we clustered 526 KIRC samples based on the prognostic lncRNAs and obtained two different patterns (Cuproptosis.C1 and C2). C1 indicated an obviously worse prognostic outcome and possessed a higher immune score and immune cell infiltration level. Moreover, a prognosis signature (CRGscore) was constructed to effectively and accurately evaluate the overall survival (OS) of KIRC patients. There were significant differences in tumor immune microenvironment (TIME) and tumor mutation burden (TMB) between CRGscore-defined groups. CRGscore also has the potential to predict medicine efficacy.
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Project description:Kidney renal clear cell carcinoma (KIRC) is one of the most common cancers with high mortality all over the world. Many studies have proposed that genes could be used to predict prognosis in KIRC. In this study, RNA expression data from next-generation sequencing and clinical information of 523 patients downloaded from The Cancer Genome Atlas (TCGA) dataset were analyzed in order to identify the relationship between gene expression level and the prognosis of KIRC patients. A set of five genes that significantly associated with overall survival time was identified and a model containing these five genes was constructed by Cox regression analysis. By Kaplan-Meier and Receiver Operating Characteristic (ROC) analysis, we confirmed that the model had good sensitivity and specificity. In summary, expression of the five-gene model is associated with the prognosis outcomes of KIRC patients, and it may have an important clinical significance.
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Project description:Emerging evidence has highlighted that the immune and stromal cells formed the majority of tumor microenvironment (TME) which are served as important roles in tumor progression. In our study, we aimed to screen vital prognostic signature associated with TME in clear cell renal cell carcinoma (ccRCC). We obtained total 611 samples from TCGA database consisting of transcriptome profiles and clinical data. ESTIMATE algorithm was applied to estimate the infiltrating fractions of immune/stromal cells. We found that the immune scores revealed more prognostic significance in overall survival and positive associations with risk clinical factors than stromal scores. We carried out differential expression analysis between Immunescore and stromalscore groups to obtain the 72 intersect genes. Protein to protein interaction (PPI) network and functional analysis was performed to indicate potential altered pathways. Additionally, we further conducted multivariate Cox analysis to identify 12 hub genes associated highly with TME of ccRCC using a stepwise regression procedure. Accordingly, risk score was constructed from the multivariate Cox results and Receiver Operating Characteristic (ROC) curve was used to assess the predictive value (AUC = 0.781). The ccRCC patients with high risk scores suffered poor survival outcomes than that with low risk scores. In the validation cohort from GSE53757, TNFSF13B, CASP5, and GJB6 correlated positively with tumor stages, while FREM1 negatively correlated with tumor stages. Importantly, we further observed that TNFSF13B, CASP5 and XCR1 showed the remarkable correlations with tumor-infiltrating immune cells. Taken together, our research identified specific signatures that related to the infiltration of stromal and immune cells in TME of ccRCC using the transciptome profiles, which reached a comprehensive understanding of tumor microenvironment in ccRCC.
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Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is, by far, the most prevalent and fatal kind of kidney cancer. Ferrochelatase (FECH) is an enzyme that performs a significant function in the onset and progression of many distinct kinds of malignant tumors. Nevertheless, its predictive usefulness in renal clear cell carcinoma (RCC) has not yet been fully investigated.MethodsFECH expression in ccRCC and healthy adjoining tissues was primarily screened utilizing data sourced from The Cancer Genome Atlas (TCGA) and subsequently validated using data from an independent cohort derived from the Gene Expression Omnibus (GEO) and the Human Protein Atlas HPA databases. The relationship among FECH expression, clinicopathological parameters, and overall survival (OS) was assessed utilizing multivariate analysis and Kaplan-Meier survival curves. Additionally, the protein networks with FECH interaction were constructed with the aid of the online Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Gene ontology (GO) analysis, and gene set enrichment analysis (GSEA) were conducted based on TCGA data, and a single-sample GSEA was utilized to explore the link between FECH expression and the infiltration status of immune cells in the tumor. The Gene Expression Profiling Interactive Analysis (GEPIA) and TIMER databases were utilized to investigate the relationships of FECH expression with the infiltrating immune cells and the matching gene marker sets.ResultsFECH expression was shown to be substantially lowered in ccRCC tumors as opposed to that observed in normal tissues (p < 0.05). Lower levels of FECH expression were shown to have a strong association with higher grades of cancer and more advanced TNM stages. The findings of multivariate and univariate analyses illustrated that the OS in patients with ccRCC with low FECH expression is shorter in contrast with that in the high FECH expression group (p < 0.05). It was discovered that CPOX and frataxin are key proteins that interact with FECH. ccRCC with FECH deficiency was linked to the lack of infiltrating immune cells and their respective marker sets, which included CD4+ T cells.ConclusionIn ccRCC, decreased FECH expression was linked to disease progression, unfavorable prognosis, and impaired immune cell infiltration.
| S-EPMC9436586 | biostudies-literature
Project description:Immune status affects the initiation and progression of clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell carcinoma. In this study, we identified an immune-related, five-gene signature that improves survival prediction in ccRCC. Patients were classified as high- and low-risk based on the signature risk score. Survival analysis showed differential prognosis, while principal component analysis revealed distinctly different immune phenotypes between the two risk groups. High-risk patients tended to have advanced stage, higher grade disease, and poorer prognoses. Functional enrichment analysis showed that the signature genes were mainly involved in the cytokine-cytokine receptor interaction pathway. Moreover, we found that tumors from high-risk patients had higher relative abundance of T follicular helper cells, regulatory T cells, and M0 macrophages, and higher expression of PD-1, CTLA-4, LAG3, and CD47 than low-risk patients. This suggests our gene signature may not only serve as an indicator of tumor immune status, but may be a promising tool to select high-risk patients who may benefit from immune checkpoint inhibitor therapy. Multivariate Cox regression analysis showed that the signature remained an independent prognostic factor after adjusting for clinicopathological variables, while prognostic accuracy was further improved after integrating clinical parameters into the analysis.
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Project description: Not available
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Project description:This study aimed to screen and verify the important prognostic genes related to clear cell renal cell carcinoma (ccRCC) and further analyze their relationship with the immune microenvironment. Gene expression profiles from the TCGA-KIRC, GSE46699, GSE36895, and GSE16449 datasets were utilized to explore differentially co-expressed genes in ccRCC. We screened 124 differentially co-expressed genes using a weighted gene co-expression network and differential gene expression analyses. Univariate and multivariate Cox survival analyses revealed that the expressions of genes CGN, FECH, UCHL1, and WT1 were independently related to the overall survival of ccRCC patients. Kaplan-Meier survival analysis was performed, and CGN was found to have the strongest correlation with the prognosis of ccRCC patients and was consequently selected for further analyses and experimental verification. The results showed that NK cell activation, resting dendritic cells, resting monocytes, and resting mast cells were positively correlated with CGN expression; CD4+ memory activated T cells, regulatory T cells, and M0 macrophages were negatively correlated with CGN expression. Finally, using western blotting and reverse transcription polymerase chain reaction, we verified that the CGN protein level was down-regulated in ccRCC samples, which was consistent with the mRNA levels. CGN was thus identified as diagnosis and prognosis biomarker for ccRCC and is related to the immune microenvironment.
| S-EPMC8865610 | biostudies-literature
Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is the most common malignant tumor of the kidney and is characterized by poor prognosis. We sought to build an immune-related prognostic signature and investigate its relationship with immunotherapy response in ccRCC.MethodsImmune-related genes were identified by ssGSEA and WGCNA. The prognostic signature was conducted via univariate, least absolute shrinkage and selection operator, and multivariable Cox regression analyses. Kaplan-Meier analysis, PCA, t-SNE, and ROC were used to evaluate the risk model.ResultsA total of 119 immune-related genes associated with prognosis were screened out. Six immune-related genes (CSF1, CD5L, AIM2, TIMP3, IRF6, and HHLA2) were applied to construct a prognostic signature for KIRC. Kaplan-Meier analysis showed that patients in high-risk group had a poorer survival outcome than in low-risk group. The 1-, 3- and 5-year AUC of the prognostic signature was 0.754, 0.715, and 0.739, respectively. Univariate and multivariate Cox regression models demonstrated that the risk signature was an independent prognostic factor for KIRC survival. GSEA analysis suggested that the high-risk group was concentrated on immune-related pathways. The high-risk group with more regulatory T-cell infiltration showed a higher expression of immune negative regulation genes. The risk score had positively relationship with TIDE score and negatively with the response of immunotherapy. The IC50 values of axitinib, sunitinib, sorafenib, and temsirolimus were lower in the high-risk group.ConclusionOur study defined a robust signature that may be promising for predicting clinical outcomes and immunotherapy and targeted therapy response in ccRCC patients.
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Project description:BackgroundKidney Renal Clear Cell Carcinoma (KIRC) is one of the most prevalent types of cancer worldwide. KIRC has a poor prognosis and, to date, immunotherapy based on immune checkpoints is the most promising treatment. However, the role of immune checkpoints in KIRC remains ambiguous.MethodsBioinformatics analyses and qRT-PCR were performed to explore and further confirm the prognostic value of immune checkpoint genes and their correlation with immune infiltration in KIRC samples.ResultsThe expression of the immune checkpoint genes CD274, PDCD1LG2, HAVCR2, CTLA4, TIGFT, LAG3, and PDCD1 was upregulated in KIRC tissues. These genes were involved in the activation of the apoptosis pathway in KIRC. Low expression of CD274 and HAVCR2 and high expression of CTLA4 were associated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of KIRC patients. The univariate and multivariate analyses revealed that CTLA4, HAVCR2, age, pTNM stage, and tumor grade were independent factors affecting the prognosis of KIRC patients. A predictive nomogram demonstrated that the calibration plots for the 3-year and 5-year OS probabilities showed good agreement compared to the actual OS of KIRC patients. The expression of CTLA4 and HAVCR2 were positively associated with immune cell infiltration, immune biomarkers, chemokines, and chemokine receptors. Moreover, miR-20b-5p was identified as a potential miRNA target of CTLA4 in KIRC.ConclusionOur study clarified the prognostic value of several immune checkpoint regulators in KIRC, revealing a CTLA4/miR-20b-5p axis in the control of immune cell infiltration in the tumor microenvironment.
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Project description:ObjectiveWe conducted an in-depth study of the immune system and ferroptosis to identify prognostic biomarkers and therapeutic targets for renal clear cell carcinoma.MethodsImmune ferroptosis-related differentially expressed genes (IFR-DEGs) were selected from The Cancer Genome Atlas (TCGA). A lasso-Cox risk scoring model was established; its prognostic value was determined using prognostic analysis and single multivariate Cox analysis. Model genes were subjected to subcellular fluorescence localization, mRNA and protein expression analyses, and single-cell RNA sequencing localization analysis. Risk score was analyzed using the immune score, immune infiltrating cell correlation, immune checkpoint, TIDE, and drug sensitivity.ResultsA total of 103 IFR-DEGs were identified; a risk model comprising ACADSB, CHAC1, LURAP1L, and PLA2G6 was established. The survival curve, single multivariate Cox regression, and receiver operating characteristic (ROC) curve analysis showed that the model had good predictive ability (p < 0.05). It was also validated using the validation set and total cohort. Subcellular fluorescence localization revealed that ACADSB, CHAC1, and PLA2G6 were distributed in the cytoplasm and LURAP1L in the nucleus. The mRNA and protein expression trends were consistent. Single-cell RNA sequencing mapping revealed that ACADSB was enriched in distal tubule cell clusters. In the Kidney renal clear cell carcinoma (KIRC) mutation correlation analysis, 1.56% of the patients were found to have genetic alterations; The Spearman correlation analysis of model gene mutations showed that ACADSB was positively correlated with LURAP1L, which may have a synergistic effect; it was negatively correlated with CHAC1 and PLA2G6, and CHAC1 was negatively correlated with LURAP1L, which may have an antagonistic effect. Model and immune correlation analyses found that high-risk patients had significantly higher levels of CD8+ T cells, regulatory T cells (Tregs), immune checkpoints, immune scores, and immune escape than those in low-risk patients. High-risk patients had a higher susceptibility to small-molecule drugs.ConclusionA novel prognostic model of immune ferroptosis-related genes (ACADSB, CHAC1, LURAP1L, and PLA2G6), which plays an important role in immune infiltration, microenvironment, and immune escape, was constructed. It effectively predicts the survival of patients with KIRC.
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