Cytochrome P450 4B1 (CYP4B1) as a target in cancer treatment

Lim, Sharoen Yu Ming; Alshagga, Mustafa Ahmed; Ong, Chin Eng; Chieng, Jin Yu; Pan, Yan

doi:10.1177/0960327120905959

Cited by 23 publications

(27 citation statements)

References 65 publications

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“…Patients with LUAD, BLCA and LGG with low expression of CRTAC1 have poor prognosis, which is consistent with that found in glioma (Xiao et al, 2020). Cytochrome P450 4B1 (CYP4B1) is a tissue-specific detoxification-related monooxygenase and is down-expressed in LUAD, but its role in tumorigenesis is still unclear (Lim et al, 2020;Ni and Sun, 2019). The prognosis of LUAD, CESC and KIRC patients with low expression of CYP4B1 is poor, which is consistent with the findings of urethral cancer and adrenal cancer (Genter et al, 2006;Murtha et al, 2017;Lin et al, 2019).…”

Section: Discussionsupporting

confidence: 81%

Identification of Key Genes in Lung Adenocarcinoma and Establishment of Prognostic Mode

Xing

Zhang

et al. 2020

Front. Mol. Biosci.

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Background: The development of human tumors is associated with the abnormal expression of various functional genes, and a massive tumor-based database needs to be deeply mined. Based on a multigene prediction model, access to urgent prognosis of patients has become possible. Materials and Methods: We selected three RNA expression profiles (GSE32863, GSE10072, and GSE43458) from the lung adenocarcinoma (LUAD) database of the Gene Expression Omnibus (GEO) and analyzed the differentially expressed genes (DEGs) between tumor and normal tissue using GEO2R program. After that, we analyzed the transcriptome data of 479 LUAD samples (54 normal tissue samples and 425 cancer tissue samples) and their clinical follow-up data from the (TCGA) database. Kaplan-Meier (KM) curve and receiver operating characteristic (ROC) were used to assess the prediction model. Multivariate Cox analysis was used to identify independent predictors. TCGA pancreatic adenocarcinoma datasets were used to establish a nomogram model. Results: We found 98 significantly prognosis-related genes using KM and COX analysis, among which six genes were found to be the DEGs in GEO. Using multivariate analysis, it was found that a single gene could not be used as an independent predictor of prognosis. However, the risk score calculated by weighting these six genes could serve as an independent prognosis predictor. COX analysis performed with multiple covariates such as age, gender, tumor stage, and TNM typing showed that risk score could still be utilized as an independent risk factor for patient survival rate (p = 0.013) and had an applicable reliability (area under the curve, AUC = 0.665). By combining risk score and various clinical features, the nomogram model was constructed, which had been proven to have high consistency for the prediction of 3-and 5-year survival rate (concordance = 0.751) and high accuracy as tested by ROC (AUC = 0.71;AUC = 0.708). Conclusion: We proposed a method to predict the prognosis of LUAD by weighting multiple genes and constructed a nomogram model suitable for the prognostic evaluation of LUAD, which could provide a new tool for the identification of therapeutic targets and the efficacy evaluation of LUAD.

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Section: Discussionsupporting

confidence: 81%

Identification of Key Genes in Lung Adenocarcinoma and Establishment of Prognostic Mode

Xing

Zhang

et al. 2020

Front. Mol. Biosci.

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“…CYP4B1 is an interface between the metabolism of xenobiotics such as 2-aminofluorene and endobiotic, including ligands where P450 acts on them to modify endogenous processes [ 44 ]. It is predominantly expressed in human lungs and might contribute to carcinogenesis [ 45 ]. About 20% of our samples carried CYP4B1*2 .…”

Section: Discussionmentioning

confidence: 99%

Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population

Wankaew

Chariyavilaskul²,

Chamnanphon³

et al. 2022

PLoS ONE

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Differences in drug responses in individuals are partly due to genetic variations in pharmacogenes, which differ among populations. Here, genome sequencing of 171 unrelated Thai individuals from all regions of Thailand was used to call star alleles of 51 pharmacogenes by Stargazer, determine allele and genotype frequencies, predict phenotype and compare high-impact variant frequencies between Thai and other populations. Three control genes, EGFR, VDR, and RYR1, were used, giving consistent results. Every individual had at least three genes with variant or altered phenotype. Forty of the 51 pharmacogenes had at least one individual with variant or altered phenotype. Moreover, thirteen genes had at least 25% of individuals with variant or altered phenotype including SLCO1B3 (97.08%), CYP3A5 (88.3%), CYP2C19 (60.82%), CYP2A6 (60.2%), SULT1A1 (56.14%), G6PD (54.39%), CYP4B1 (50.00%), CYP2D6 (48.65%), CYP2F1 (46.41%), NAT2 (40.35%), SLCO2B1 (28.95%), UGT1A1 (28.07%), and SLCO1B1 (26.79%). Allele frequencies of high impact variants from our samples were most similar to East Asian. Remarkably, we identified twenty predicted high impact variants which have not previously been reported. Our results provide information that contributes to the implementation of pharmacogenetic testing in Thailand and other Southeast Asian countries, bringing a step closer to personalized medicine.

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“…CYP4B1 (cytochrome P450 family 4 subfamily B member 1) is an extrahepatic form of cytochrome P450 predominantly and responsible for the bioactivation of multiple protoxins with tissuespecific toxicological effects [34]. CYP4B1 was found to be associated with a variety of cancers [35] and Czerwinski et al discovered that CYP4B1 from normal and neoplastic lung tissues, compared with normal tissues, had mRNA levels in tumor tissues that were reduced by 2.4 times [36].…”

Section: Discussionmentioning

confidence: 99%

Prognostic Ability of Enhancer RNAs in Metastasis of Non-Small Cell Lung Cancer

Liu

Wang²,

Zhang³

et al. 2022

Molecules

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(1) Background: Non-small cell lung cancer (NSCLC) is the most common lung cancer. Enhancer RNA (eRNA) has potential utility in the diagnosis, prognosis and treatment of cancer, but the role of eRNAs in NSCLC metastasis is not clear; (2) Methods: Differentially expressed transcription factors (DETFs), enhancer RNAs (DEEs), and target genes (DETGs) between primary NSCLC and metastatic NSCLC were identified. Prognostic DEEs (PDEEs) were screened by Cox regression analyses and a predicting model for metastatic NSCLC was constructed. We identified DEE interactions with DETFs, DETGs, reverse phase protein arrays (RPPA) protein chips, immunocytes, and pathways to construct a regulation network using Pearson correlation. Finally, the mechanisms and clinical significance were explained using multi-dimensional validation unambiguously; (3) Results: A total of 255 DEEs were identified, and 24 PDEEs were selected into the multivariate Cox regression model (AUC = 0.699). Additionally, the NSCLC metastasis-specific regulation network was constructed, and six key PDEEs were defined (ANXA8L1, CASTOR2, CYP4B1, GTF2H2C, PSMF1 and TNS4); (4) Conclusions: This study focused on the exploration of the prognostic value of eRNAs in the metastasis of NSCLC. Finally, six eRNAs were identified as potential markers for the prediction of metastasis of NSCLC.

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Cytochrome P450 4B1 (CYP4B1) as a target in cancer treatment

Cited by 23 publications

References 65 publications

Identification of Key Genes in Lung Adenocarcinoma and Establishment of Prognostic Mode

Identification of Key Genes in Lung Adenocarcinoma and Establishment of Prognostic Mode

Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population

Prognostic Ability of Enhancer RNAs in Metastasis of Non-Small Cell Lung Cancer

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