CYP1A2 suppresses hepatocellular carcinoma through antagonizing HGF/MET signaling

Yu, Jianqing; Xia, Xianfeng; Dong, Yujuan; Gong, Zhongqin; Li, Gang; Chen, George G; Lai, Paul Bo San

doi:10.7150/thno.49368

Cited by 27 publications

(17 citation statements)

References 45 publications

(31 reference statements)

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“…ADH4 served as an essential member of the ADH family and was suggested as a potential prognostic marker for HCC patients [16]. CYP1A2, predominantly expressed in the liver tissue, could inhibit cell viability and clonogenicity and reduce cell migration and invasion in HCC [17]. CYP2C19 played a crucial role in detoxifying or inactivating potential carcinogens through activating DNA-binding metabolites.…”

Section: Discussionmentioning

confidence: 99%

Identification of the critical genes and miRNAs in hepatocellular carcinoma by integrated bioinformatics analysis

Wang

Yang

et al. 2022

Med Oncol

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Hepatocellular carcinoma (HCC) is a global health problem with a complex etiology and pathogenesis.Microarray data is increasingly being used as a novel and effective method for cancer pathogenesis analysis. To unravel the potential prognosis of HCC, an integrative study of mRNA and miRNA for HCC was conducted. Two microarray datasets (GSE89377 and GSE101685) and two miRNAs expression pro les (GSE112264 and GSE113740) were obtained from Gene Expression Omnibus (GEO) database. A total of 177 DEGs and 80 DEMs were screened out. Functional enrichment of DEGs was proceeded by Clue GO, including GO and KEGG pathway analysis. These genes were signi cantly enriched in chemical carcinogenesis. PPI network was then established on the STRING platform, and ten hub genes (CDC20, TOP2A, ASPM, NCAPG, AURKA, CYP2E1, HMMR, PRC1, TYMS, and CYP4A11) were visualized via Cytoscape software. Then, a miRNA-target network was established to identify the dysregulated miRNA.A key miRNA (hsa-miR-124-3p) was ltered. Finally, the miRNA-target-transcription factor networks were constructed for hsa-miR-124-3p. The network for hsa-miR-124-3p included two transcription factors (TFs) and ve targets. These identi ed DEGs and DEMs, TFs, targets, and regulatory networks may help advance our understanding the underlying pathogenesis of HCC.

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Section: Discussionmentioning

confidence: 99%

Identification of the critical genes and miRNAs in hepatocellular carcinoma by integrated bioinformatics analysis

Wang

Yang

et al. 2022

Med Oncol

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“…CYP1A2 (cytochrome P450 1A2) and CYP2D6 (cytochrome P450 2D6) both belong to the cytochrome P450 superfamily, which regulates the metabolism of commonly used drugs and is predominantly distributed in the liver ( 34 ). In hepatocellular carcinoma, CYP1A2 inhibits cancer progression through antagonizing HGF/MET signaling ( 35 ). CYP2D6 is necessary for the activation of tamoxifen, and higher expression of CYP2D6 is associated with better survival in patients with breast cancer ( 36 ).…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a prognosis prediction model based on 18 endoplasmic reticulum stress-related genes for patients with lung adenocarcinoma

2022

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BackgroundEndoplasmic reticulum (ER) stress had a crucial impact on cell survival, proliferation, and metastasis in various cancers. However, the role of ER stress in lung adenocarcinoma remains unclear.MethodGene expression and clinical data of lung adenocarcinoma (LUAD) samples were extracted from The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets. ER stress score (ERSS) was constructed based on hub genes selected from 799 ER stress-related genes by least absolute shrinkage and selection operator (LASSO) regression. A Cox regression model, integrating ERSS and the TNM stage, was developed to predict overall survival (OS) in TCGA cohort and was validated in GEO cohorts. Gene set enrichment analysis (GSEA), single-sample GSEA (ssGSEA), and gene mutation analyses were performed to further understand the molecular features of ERSS. The tumor immune infiltration was evaluated by ESTIMATE, CIBERSORT, and xCell algorithms. The receiver operating characteristic (ROC) curves were used to evaluate the predictive value of the risk model. p< 0.05 was considered statistically significant.ResultsOne hundred fifty-seven differentially expressed genes (DEGs) were identified between tumor and para-carcinoma tissues, and 45 of them significantly correlated with OS. Next, we identified 18 hub genes and constructed ERSS by LASSO regression. Multivariate analysis demonstrated that higher ERSS (p< 0.0001, hazard ratio (HR) = 3.8, 95%CI: 2.8–5.2) and TNM stage (p< 0.0001, HR = 1.55, 95%CI: 1.34–1.8) were independent predictors for worse OS. The prediction model integrating ERSS and TNM stage performed well in TCGA cohort (area under the curve (AUC) at five years = 0.748) and three GEO cohorts (AUC at 5 years = 0.658, 0.717, and 0.739). Pathway enrichment analysis showed that ERSS significantly correlated with unfolded protein response. Meanwhile, pathways associated with the cell cycle, growth, and metabolism were significantly enriched in the high ERSS group. Patients with SMARCA4, TP53, and EGFR mutations showed significantly higher ERSS (p = 4e−04, 0.0027, and 0.035, respectively). Tissues with high ERSS exhibited significantly higher infiltration of M1 macrophages, activated dendritic cells, and lower infiltration of CD8+ T cells and B cells, which indicate an activated tumor antigen-presenting but suppressive immune response status.ConclusionWe developed and validated an ER stress-related risk model that exhibited great predictive value for OS in patients with LUAD. Our work also expanded the understanding of the role of ER stress in LUAD.

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“…and participates in the biotransformation processes of different procarcinogens. CYP1A2 is markedly decreased in primary HCC tumors and is an independent predictor for post-surgical recurrence in early-stage HCC patients [136,137].…”

Section: Hcv Group Hub Genes and Proteinsmentioning

confidence: 99%

Comparative RNA-Sequencing Analysis Reveals High Complexity and Heterogeneity of Transcriptomic and Immune Profiles in Hepatocellular Carcinoma Tumors of Viral (HBV, HCV) and Non-Viral Etiology

et al. 2022

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Background and Objectives: Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, is the leading cause of cancer-related mortality. It arises and progresses against fibrotic or cirrhotic backgrounds mainly due to infection with hepatitis viruses B (HBV) or C (HCV) or non-viral causes that lead to chronic inflammation and genomic changes. A better understanding of molecular and immune mechanisms in HCC subtypes is needed. Materials and Methods: To identify transcriptional changes in primary HCC tumors with or without hepatitis viral etiology, we analyzed the transcriptomes of 24 patients by next-generation sequencing. Results: We identified common and unique differentially expressed genes for each etiological tumor group and analyzed the expression of SLC, ATP binding cassette, cytochrome 450, cancer testis, and heat shock protein genes. Metascape functional enrichment analysis showed mainly upregulated cell-cycle pathways in HBV and HCV and upregulated cell response to stress in non-viral infection. GeneWalk analysis identified regulator, hub, and moonlighting genes and highlighted CCNB1, ACTN2, BRCA1, IGF1, CDK1, AURKA, AURKB, and TOP2A in the HCV group and HSF1, HSPA1A, HSP90AA1, HSPB1, HSPA5, PTK2, and AURKB in the group without viral infection as hub genes. Immune infiltrate analysis showed that T cell, cytotoxic, and natural killer cell markers were significantly more highly expressed in HCV than in non-viral tumors. Genes associated with monocyte activation had the highest expression levels in HBV, while high expression of genes involved in primary adaptive immune response and complement receptor activity characterized tumors without viral infection. Conclusions: Our comprehensive study underlines the high degree of complexity of immune profiles in the analyzed groups, which adds to the heterogeneous HCC genomic landscape. The biomarkers identified in each HCC group might serve as therapeutic targets.

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CYP1A2 suppresses hepatocellular carcinoma through antagonizing HGF/MET signaling

Cited by 27 publications

References 45 publications

Identification of the critical genes and miRNAs in hepatocellular carcinoma by integrated bioinformatics analysis

Identification of the critical genes and miRNAs in hepatocellular carcinoma by integrated bioinformatics analysis

Development and validation of a prognosis prediction model based on 18 endoplasmic reticulum stress-related genes for patients with lung adenocarcinoma

Comparative RNA-Sequencing Analysis Reveals High Complexity and Heterogeneity of Transcriptomic and Immune Profiles in Hepatocellular Carcinoma Tumors of Viral (HBV, HCV) and Non-Viral Etiology

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