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The mechanism of action of UBE2C in lung adenocarcinoma (LUAD) and its significance in cancer diagnosis, targeted therapy and immunotherapy, even in pan-cancer, are still unclear. Several large public databases and online analysis tools were used for big data mining analysis. RNA interference technology, CCK8 assay, flow cytometry and apoptosis detection, and western blot were used for in vitro experiments. UBE2C was found to be overexpressed in various of tumors, including LUAD, and its expression level was found to be significantly related to gender, weight, tumor stage, grade and prognosis in LUAD. Downregulation of UBE2C expression induced proliferation suppression and G2/M phase arrest and cell apoptosis in LUAD cells and suppressed LUAD cell growth through inhibiting the Akt-mTOR signaling pathway. Expression level of UBE2C was negatively correlated with B cells and CD4+ T cell, and also with immune checkpoint genes in LUAD. Pan-cancer assay shown that UBE2C was significantly overexpressed in 28 cancers and was correlated with Ki-67 index in many cancers. Overexpression of UBE2C in BRCA, LUAD and MESO indicated worse Overall Survival (OS). UBE2C expression levels were positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI and MMRs in some cancers. Additionally, Single-cell functional analysis showed that UBE2C was positively correlated with cell cycle, proliferation, DNA damage, EMT, DNA repair, invasion and differentiation in some cancers. These findings suggested that UBE2C could be regarded as a latent diagnosis and prognostic biomarker and a new target for immunological therapy of cancers including LUAD.
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AIMS: We aimed to investigate the role of G protein subunit alpha Z(GNAZ) in the progression and prognosis of patients with hepatocellular carcinoma (HCC). METHODS: Oncomine, GEO, TCGA, GEPIA2, Kaplan-Meier Plotter, TIMER2, Metascape, CCLE, LinkedOmics, and UALCAN databases were used to analyze the differential expression of GNAZ in HCC and normal liver tissues, relationship between GNAZ expression and prognosis of patients with HCC, and expression of GNAZ in common human HCC cell lines. Western blotting was performed to analyze GNAZ expression, while the Cell Counting Kit 8 assay was used to determine cell proliferation, and flow cytometry was used to evaluate the cell cycle and apoptosis. Wound healing and transwell invasion assays were used to investigate cell metastasis and invasion. RESULTS: Using Oncomine, Gene Expression Omnibus (GEO), and GEPIA2 databases, GNAZ was found to be overexpressed in HCC tissues compared with that in adjacent normal liver tissues, and western blotting analysis showed GNAZ overexpression in seven patients with HCC who underwent surgical resection of HCC and para-cancerous tissues (p < 0.01). Survival analysis revealed that high GNAZ expression was negatively associated with overall survival (OS), recurrence-free survival, progression-free survival, and disease-specific survival in patients with HCC (p < 0.05). GNAZ overexpression was associated with worse 4- month, 6- month, 12- month, 24- month, 36- month, 48- month, and 60-month OS, as well as with different clinicopathological characteristics of patients with HCC, including hepatitis virus infection state; alcohol consumption state; male; female; Asian; microvascular invasion, Stage I-II, Stage II-III, and Stage III-IV; and grade II (Cox regression, p < 0.05). KEGG/GO biological process enrichment indicated that the genes similar to GNAZ in HCC were mainly enriched in the cell cycle, cell cycle phase transition, DNA replication checkpoint, and regulation of G0 to G1 transition. siRNA-GNAZ significantly reduced the viability of JHH-2 and SNU-761 cells from 12 to 96 h; increased the percentage of cells in the G0/G1 phase and decreased that of cells in the S and G2/M phases (p < 0.05); and markedly downregulated the expression of cyclin D, cyclin E, and CDK2 protein. siRNA-GNAZ also significantly increased the percentage of JHH-2 and SNU-761 cell apoptosis at late stages, while the number of surviving cells decreased (p < 0.05), and upregulated the expression of apoptosis-related proteins Bax and caspase 3 protein. Furthermore, siRNA-GNAZ remarkably reduced the healing of scratch wounds in JHH-2 and SNU-761 cells and the number of invasive cells compared with that in the control group (p < 0.001). CONCLUSION: Our study demonstrated that GNAZ plays a pivotal role as a potential oncogene and predicts poor prognosis in patients with HCC. It promotes tumor proliferation via cell cycle arrest, apoptosis, migration, and invasion. Thus, GNAZ may be a potential candidate biomarker providing useful insight into hepatocarcinogenesis and aggressiveness.
Asunto(s)
Carcinoma Hepatocelular/genética , Puntos de Control de la Fase G1 del Ciclo Celular/genética , Subunidades alfa de la Proteína de Unión al GTP/genética , Anciano , Apoptosis/genética , Pueblo Asiatico/genética , Biomarcadores de Tumor/genética , Carcinoma Hepatocelular/mortalidad , Ciclo Celular/genética , Proteínas de Ciclo Celular/genética , Línea Celular Tumoral , Movimiento Celular/genética , Proliferación Celular/genética , China , Femenino , Subunidades alfa de la Proteína de Unión al GTP/metabolismo , Expresión Génica/genética , Regulación Neoplásica de la Expresión Génica/genética , Células Hep G2 , Humanos , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/mortalidad , Masculino , Persona de Mediana Edad , Pronóstico , Receptores Acoplados a Proteínas G/genética , Receptores Acoplados a Proteínas G/metabolismo , Transcriptoma/genéticaRESUMEN
BACKGROUND: Acute myeloid leukemia (AML) is a common hematopoietic malignancy and have unsatisfactory prognosis. Our study aimed to identify hub genes in AML and explore potential biomarkers through integrated bioinformatics. METHODS: Microarray datasets were analyzed to screen the differentially expressed genes (DEGs). Functional enrichment analysis was performed, and protein-protein interaction (PPI) network was generated by the STRING (11.0) database and Cytoscape (3.7.2) software. Hub genes were screened and verified through GEPIA2 and GEO microarray database. Sensitivity of AML cell lines with high expression of hub genes to the small-molecule drugs were identified using GSCA Lite. RESULTS: A total of 456 DEGs were identified and top 100 genes were screened out, of which six genes (FLT3, PF4, CD163, MRC1, CSF2RB, PPBP) were upregulated in AML and individually had a worse prognosis by the overall survival (OS) analysis. AML cell lines with FLT3-overexpression and CSF2RB-overexpression were sensitive to most small-molecule drugs, while, AML cells with CD163-overexpression were only sensitive to a few drugs. However, sensitivity to Erlotinib was correlated with high expression of PF4 and PPBP. CONCLUSIONS: In summary, FLT3, PF4, CD163, MRC1, CSF2RB, PPBP may be potential biomarkers and potential sensitive small-molecule drugs were correlated with overexpression of the biomarkers in AML.
