Dataset Information

Antioxidant Gene Signature Impacts the Immune Infiltration and Predicts the Prognosis of Kidney Renal Clear Cell Carcinoma.

ABSTRACT: Background: Oxidative stress is related to oncogenic transformation in kidney renal clear cell carcinoma (KIRC). We intended to identify a prognostic antioxidant gene signature and investigate its relationship with immune infiltration in KIRC. Methods: With the support of The Cancer Genome Atlas (TCGA) database, we researched the gene expression and clinical data of KIRC patients. Antioxidant related genes with significant differences in expression between KIRC and normal samples were then identified. Through univariate and multivariate Cox analysis, a prognostic gene model was established and all patients were divided into high- and low-risk subgroups. Single sample gene set enrichment analysis was adopted to analyze the immune infiltration, HLA expression, and immune checkpoint genes in different risk groups. Finally, the prognostic nomogram model was established and evaluated. Results: We identified six antioxidant genes significantly correlated with the outcome of KIRC patients as independent predictors, namely DPEP1 (HR = 0.97, P < 0.05), GSTM3 (HR = 0.97, P < 0.05), IYD (HR = 0.33, P < 0.05), KDM3B (HR = 0.96, P < 0.05), PRDX2 (HR = 0.99, P < 0.05), and PRXL2A (HR = 0.96, P < 0.05). The high- and low-risk subgroups of KIRC patients were grouped according to the six-gene signature. Patients with higher risk scores had poorer prognosis, more advanced grade and stage, and more abundance of M0 macrophages, regulatory T cells, and follicular helper T cells. There were statistically significant differences in HLA and checkpoint gene expression between the two risk subgroups. The performance of the nomogram was favorable (concordance index = 0.766) and reliably predicted the 3-year (AUC = 0.792) and 5-year (AUC = 0.766) survival of patients with KIRC. Conclusion: The novel six antioxidant related gene signature could effectively forecast the prognosis of patients with KIRC, supply insights into the interaction between cellular antioxidant mechanisms and cancer, and is an innovative tool for selecting potential patients and targets for immunotherapy.

SUBMITTER: Ren X

PROVIDER: S-EPMC8416991 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundKidney renal clear cell carcinoma (KIRC) is the most common pathological subtype of renal cell cancer. APOBEC3 activity has been identified in a variety of human cancers. Although its involvement in cancer has been studied widely, its influence on the tumor immune microenvironment remains poorly understood. Therefore, this study aimed to focus on the effect of APOBEC3 on tumor immune microenvironment of KIRC.MethodsIn this study, we comprehensively analyzed the expression and prognostic significance of the APOBEC3 family in pan-cancer using multiple databases. The functions of key APOBEC3 family members were further investigated in KIRC, with APOBEC3G determined to be a candidate biomarker for unfavorable prognosis. We subsequently explored the correlation of APOBEC3G with the tumor immune environment in KIRC by analyzing the Cancer Genome Atlas (TCGA) dataset, then validated the prognostic significance and PD-L1 correlation of APOBEC3G by using tissue microarrays which included 233 primary tumor samples from patients with renal clear cell carcinoma.ResultsThe APOBEC3 family was overexpressed in KIRC and high APOBEC3 expression predicted poor prognosis. In addition, APOBEC3G was positively correlated with the expression of immunoinhibitors such as TIGIT, LAG3, CD96, PD-1, and CTLA4. In addition, APOBEC3G had a positive correlation with immunosuppressive cells, including regulatory T cell and myeloid-derived suppressor cell. Finally, based on 233 clinical samples, we validated that high expression of APOBEC3G contributed to a poor prognosis for KIRC patients and the positive relationship between APOBEC3G and PD-L1 expression. High APOBEC3G expression was also found to be more common in patients with sarcomatoid histology (P = 0.0026).ConclusionsOur study showed that APOBEC3G was a prognostic biomarker correlated with the immune response in KIRC. In addition, APOBE3G had a positive correlation with PD-L1 expression and sarcomatoid histology, perhaps suggesting the potential impact of APOBEC3G on immunotherapy.

Project description:Kidney renal clear cell carcinoma (KIRC or ccRCC) is the most notorious subtype of renal cell carcinoma for its poor prognosis. Mounting evidence has highlighted the key role of PRKCE in the initiation and development of several types of human cancer, including kidney renal clear cell carcinoma (KIRC). However, the mechanism of PRKCE aberrant expression and the specific clinical correlation of PRKCE expression with immune cell infiltration in KIRC remains elusive. Therefore, we analyzed the relationship between PRKCE and KIRC using many databases, including Oncomine, TCGA, GTEx, TIMER, and GEO. We found that PRKCE decreased in KIRC tumor tissue compared to normal tissue. The Kaplan-Meier Plotter analysis and Univariate and Multivariate Cox analyses were used to evaluate the association between PRKCE and clinicopathological variables and prognosis. Low PRKCE expression was associated with poor survival and histologic grade, T stage, pathologic stage, and M stage. Besides, the C-indexes and calibration plots of the nomogram based on multivariate analysis showed an effective predictive performance for KIRC patients. In addition, PRKCE may be positively correlated with inflammation and negatively correlated with proliferation, metastasis, and invasion as identified by CancerSEA. Moreover, overexpression of PRKCE suppressed ACHN and Caki-1 cell proliferation, migration, and invasion in vitro. Additionally, methylation level data acquired from UALCAN, DiseaseMeth, CCLE, LinkedOmics, and MEXPRESS was used to investigate the relationship between PRKCE expression and PRKCE methylation level. Furthermore, upstream potential miRNA predictions were further performed to explore the mechanism of PRKCE decreased expression in KIRC using multiple online databases available on publicly assessable bioinformatics platforms. High PRKCE methylation levels and hsa-miR-21-5p may contribute to PRKCE low expression in KIRC. Finally, an analysis of immune infiltration indicated that PRKCE was associated with immune cell infiltration. Importantly, PRKCE may affect prognosis partially by regulating immune infiltration in KIRC. In summary, PRKCE may serve as a novel prognostic biomarker reflecting immune infiltration level and a novel therapeutic target in KIRC.

Project description:Background: Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of renal cell carcinoma (RCC). Anoikis plays an essential function in tumourigenesis, whereas the role of anoikis in ccRCC remains unclear. Methods: Anoikis-related genes (ARGs) were collected from the MSigDB database. According to univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) algorithm was utilized to select the ARGs associated with the overall rate (OS). Multivariate Cox regression analysis was conducted to identify 5 prognostic ARGs, and a risk model was established. The Kaplan-Meier survival analysis was used to evaluate the OS rate of ccRCC patients. Gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and Gene set enrichment analysis (GSVA) were utilized to investigate the molecular mechanism of patients in the low- and high-risk group. ESTIMATE, CIBERSOT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape. Consensus clustering analysis was performed to divide the patients into different subgroups. Results: A fresh risk model was constructed based on the 5 prognostic ARGs (CHEK2, PDK4, ZNF304, SNAI2, SRC). The Kaplan-Meier survival analysis indicated that the OS rate of patients with a low-risk score was significantly higher than those with a high-risk score. Consensus clustering analysis successfully clustered the patients into two subgroups, with a remarkable difference in immune infiltration landscape and prognosis. The ESTIMATE, CIBERSORT, and ssGSEA results illustrated a significant gap in immune infiltration landscape of patients in the low- and high-risk group. Enrichment analysis and GSVA revealed that immune-related signaling pathways might mediate the role of ARGs in ccRCC. The nomogram results illustrated that the ARGs prognostic signature was an independent prognostic predictor that distinguished it from other clinical characteristics. TIDE score showed a promising immunotherapy response of ccRCC patients in different risk subgroups and cluster subgroups. Conclusion: Our study revealed that ARGs play a carcinogenic role in ccRCC. Additionally, we firstly integrated multiple ARGs to establish a risk-predictive model. This study highlights that ARGs could be implemented as a stratification factor for individualized and precise treatment in ccRCC patients.

Dataset Information

Antioxidant Gene Signature Impacts the Immune Infiltration and Predicts the Prognosis of Kidney Renal Clear Cell Carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets