Dataset Information

CYP4B1 is a prognostic biomarker and potential therapeutic target in lung adenocarcinoma.

ABSTRACT: CYP4B1 belongs to the mammalian CYP4 enzyme family and is predominantly expressed in the lungs of humans. It is responsible for the oxidative metabolism of a wide range of endogenous compounds and xenobiotics. In this study, using data from The Cancer Genome Atlas (TCGA) project and the Gene Expression Omnibus (GEO) database, a secondary analysis was performed to explore the expression profile of CYP4B1, as well as its prognostic value in patients with lung adenocarcinoma (LUAD). Based on the obtained results, a significantly decreased CYP4B1 expression was discovered in patients with LUAD when compared with their normal counterparts (p<0.05), and was linked to age younger than 65 years (p = 0.0041), history of pharmaceutical (p = 0.0127) and radiation (p = 0.0340) therapy, mutations in KRAS/EGFR/ALK (p = 0.0239), and living status of dead (p = 0.0026). Survival analysis indicated that the low CYP4B1 expression was an independent prognostic indicator of shorter survival in terms of overall survival (OS) and recurrence-free survival (RFS) in patients with LUAD. The copy number alterations (CNAs) and sites of cg23440155 and cg23414387 hypermethylation might contribute to the decreased CYP4B1 expression. Gene set enrichment analysis (GSEA) suggested that CYP4B1 might act as an oncogene in LUAD by preventing biological metabolism pathways of exogenous and endogenous compounds and enhancing DNA replication and cell cycle activities. In conclusion, CYP4B1 expression may serve as a valuable independent prognostic biomarker and a potential therapeutic target in patients with LUAD.

SUBMITTER: Liu X

PROVIDER: S-EPMC7886130 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

CYP4B1 is a prognostic biomarker and potential therapeutic target in lung adenocarcinoma.

Liu Xiaoling X Jia Yichen Y Shi Changyuan C Kong Dechen D Wu Yuanming Y Zhang Tiantian T Wei Anjie A Wang Dan D

PloS one 20210216 2

CYP4B1 belongs to the mammalian CYP4 enzyme family and is predominantly expressed in the lungs of humans. It is responsible for the oxidative metabolism of a wide range of endogenous compounds and xenobiotics. In this study, using data from The Cancer Genome Atlas (TCGA) project and the Gene Expression Omnibus (GEO) database, a secondary analysis was performed to explore the expression profile of CYP4B1, as well as its prognostic value in patients with lung adenocarcinoma (LUAD). Based on the ob ...[more]

PMID: 33592039

Similar Datasets

Project description:BackgroundLung adenocarcinoma (LUAD) is the leading cause of cancer-related death. This study aimed to develop and validate reliable prognostic biomarkers and signature.MethodsDifferentially expressed genes were identified based on three Gene Expression Omnibus (GEO) datasets. Based on 1052 samples' data from our cohort, GEO and The Cancer Genome Atlas, we explored the relationship of clinicopathological features and NEIL3 expression to determine clinical effect of NEIL3 in LUAD. Western blotting (22 pairs of tumor and normal tissues), Real-time quantitative PCR (19 pairs of tumor and normal tissues), and immunohistochemical analyses (406-tumor tissues subjected to microarray) were conducted. TIMER and ImmuCellAI analyzed relationship between NEIL3 expression and the abundance of tumor-infiltrating immune cells in LUAD. The co-expressed-gene prognostic signature was established based on the Cox regression analysis.ResultsThis study identified 502 common differentially expressed genes and confirmed that NEIL3 was significantly overexpressed in LUAD samples (P < 0.001). Increased NEIL3 expression was related to advanced stage, larger tumor size and poor overall survival (p < 0.001) in three LUAD cohorts. The proportions of natural T regulatory cells and induced T regulatory cells increased in the high NEIL3 group, whereas those of B cells, Th17 cells and dendritic cells decreased. Gene set enrichment analysis indicated that NEIL3 may activate cell cycle progression and P53 signaling pathway, leading to poor outcomes. We identified nine prognosis-associated hub genes among 370 genes co-expressed with NEIL3. A 10-gene prognostic signature including NEIL3 and nine key co-expressed genes was constructed. Higher risk-score was correlated with more advanced stage, larger tumor size and worse outcome (p < 0.05). Finally, the signature was verified in test cohort (GSE50081) with superior diagnostic accuracy.ConclusionsThis study suggested that NEIL3 has the potential to be an immune-related therapeutic target and an independent predictor of LUAD prognosis. We also developed a prognostic signature for LUAD with a precise diagnostic accuracy.

Project description:BackgroundIncreasing evidence has demonstrated the critical roles of mRNA modification regulators on multiple types of cancers. However, it is still poorly known about the prognostic and therapeutic value of mRNA modification regulators in HNSCC.MethodsThe gene expression profile of 36 mRNA modification regulators and their corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Stepwise regression in R with both directions was used to construct a model for the prognosis of HNSCC. Univariate Cox regression survival analysis was performed to identify the most significant risk gene. Gene set enrichment analysis (GSEA) was applied to determine the cancer-associated pathways with NAT10. Immunohistochemistry (IHC) staining was performed to evaluate the expression of NAT10 in formalin fixed paraffin-embedded (FFPE) samples of HNSCC. Univariate and multivariate Cox regression survival analysis performed to identify the independent risk factors associated with the OS of patients with HNSCC. HNSCC cell lines (Cal-27, FaDu, and Detroit-562) were transfected with short interfering RNA (siRNA) targeting NAT10 or treated with Remodelin, a small-molecule inhibitor of NAT10. Knockdown efficiency of siRNA was assessed by quantitative real-time PCR (qRT-PCR) and western blotting. In addition, CCK-8 assay, scratch assay and transwell assay were used to examine the proliferation, migration, and invasion abilities of the three HNSCC cell lines after NAT10 was inhibited genetically and pharmaceutically. Cell cycle and cell apoptosis assays were performed by flow cytometry. Finally, the therapeutic value of Remodelin in HNSCC was evaluated via a patient-derived xenograft (PDX) model. The statistical analysis was performed with SPSS 23.0.ResultsA risk prediction model containing 10 mRNA modification regulators was constructed and showed prognostic value in HNSCC. NAT10 was further identified as a key risk gene and independent prognostic factor in TCGA HNSCC dataset. The GSEA analysis suggested that high NAT10 expression was associated with MYC, E2F, G2M checkpoint, mTORC1, DNA repair and oxidative phosphorylation pathways. NAT10 protein expression was significantly up-regulated in tumour cells compared to normal epithelial cells in FFPE samples and increased NAT10 protein expression was correlated with poor overall survival of 267 HNSCC patients. Genetic depletion of NAT10 using siRNA or chemical inhibition of NAT10 using Remodelin resulted in reduced cell proliferation, migration and invasion abilities in Cal-27, FaDu and Detroit-562 cells. Knockdown of NAT10 using siRNA significantly increased cell cycle arrest in S/G2-phase. Remodelin significantly inhibited tumour growth and tumour cell proliferation in the PDX model of HNSCC.ConclusionsNAT10 could be a potential prognostic marker and a therapeutic target for HNSCC.

Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) is fatal cancer that causes death. Early metastasis, resistance to chemotherapy, and lack of treatment contribute to a poor prognosis. Therefore, finding new therapeutic targets and biomarkers is a particularly urgent need to improve the survival of PDAC patients. Oligoadenylate synthetases-like (OASL), an antiviral enzyme produced by interferon (IFN), has been found to be associated with the occurrence and development of multiple cancers. However, its role in PDAC has been less well-studied. The value of OASL in PDAC was evaluated by bioinformatics and in vitro experiments.MethodsThe expression of OASL was evaluated using the Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) online websites. The survival time was also calculated by GEPIA. The correlation between OASL messenger RNA (mRNA) expression and immune infiltration was analyzed by the Tumor Immune Estimation Resource (TIMER) database. Clinical characteristics were revealed by The Cancer Genome Atlas (TCGA) data. A nomogram and forest plot were constructed based on univariate and multivariate Cox regression. Cell experiments [western blot assays, 3-(4,5-dimethylathiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays, transwell assays, flow cytometry assays] were used to verify the value of OASL in PDAC cells (Panc-1, Mia paca-2, and Aspc-1).ResultsA higher expression of OASL was observed in PDAC (P<0.05). Patients with increased expression of OASL had worse overall survival (OS; P<0.05) and disease-specific survival (DSS; P<0.05). The expression of OASL was correlated with T stage (P=0.030) and N stage (P=0.004), radiation therapy (P=0.013), primary therapy outcome (P<0.001), residual tumor (P=0.028), and tumor location (P=0.004) by univariate analysis, which also confirmed that OASL was an independent prognostic factor. Moreover, OASL expression was positively associated with neutrophils. In vitro experiments indicated that knockdown of OASL inhibited cell viability and invasion while increasing apoptosis rate.ConclusionsHigh expression of OASL is associated with poor prognosis. Targeting OASL delays PDAC tumor progression in vitro. We highlight that OASL is a novel prognostic biomarker and therapeutic target of PDAC.

Dataset Information

CYP4B1 is a prognostic biomarker and potential therapeutic target in lung adenocarcinoma.

Publications

CYP4B1 is a prognostic biomarker and potential therapeutic target in lung adenocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets