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Identification of the potential therapeutic target gene UBE2C in human hepatocellular carcinoma: An investigation based on GEO and TCGA databases.

ABSTRACT: Hepatocellular carcinoma (HCC) ranks the third major cause of cancer-associated mortality globally. Numerous studies have attempted to elucidate the underlying mechanisms of HCC using various biomarkers. In the present study, two expression profiles datasets from Gene Expression Omnibus (GSE76427 and GSE84402) and data associated with liver cancer samples from The Cancer Genome Atlas (TCGA) were downloaded for integrated analysis. Five differentially expressed genes (DEGs) exhibiting high expression, including ubiquitin-conjugating enzyme 2C (UBE2C), topoisomerase II ?, pituitary tumor transforming gene 1, glypican-3 and polycomb-repressive complex 1, were selected and considered as candidate genes. Enrichment analysis demonstrated that these genes were associated with Gene Ontology terms of cellular components and molecular functions, including regulation of apoptosis, stabilization of p53 and Anaphase Promoting Complex/Cyclosome (APC/C) (APC/C:Cdc20)-mediated degradation of Securin. The expression profiles of these genes in HCC, other human malignancies and different human HCC cell lines were validated using GSE14520, GSE3500 and TCGA data. The results confirmed the upregulation of UBE2C in tissues from patients with HCC or other human malignancies and human liver cancer cell lines, compared with the expression levels in the corresponding adjacent non-tumor tissues and cell lines, respectively. Patients with HCC who exhibited an increased messenger RNA level of UBE2C exhibited a significantly shorter survival time. The results of the present study suggest that the overexpression of UBE2C may be used as a novel prognostic biomarker of HCC.

SUBMITTER: Wei Z

PROVIDER: S-EPMC6507459 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Identification of the potential therapeutic target gene UBE2C in human hepatocellular carcinoma: An investigation based on GEO and TCGA databases.

Wei Zilun Z Liu Yihai Y Qiao Shuaihua S Li Xueling X Li Qiaoling Q Zhao Jinxuan J Hu Jiaxin J Wei Zhonghai Z Shan Anqi A Sun Xuan X Xu Biao B

Oncology letters 20190409 6

Hepatocellular carcinoma (HCC) ranks the third major cause of cancer-associated mortality globally. Numerous studies have attempted to elucidate the underlying mechanisms of HCC using various biomarkers. In the present study, two expression profiles datasets from Gene Expression Omnibus (GSE76427 and GSE84402) and data associated with liver cancer samples from The Cancer Genome Atlas (TCGA) were downloaded for integrated analysis. Five differentially expressed genes (DEGs) exhibiting high expres ...[more]

PMID: 31186759

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Project description:Increasing evidence has demonstrated that microRNA (miR)‑133a‑3p is an important regulator of hepatocellular carcinoma (HCC). In the present study, the diagnostic role of miR‑133a‑3p in HCC, and the potential functional pathways, were both explored based on publicly available data. Eligible microarray datasets were collected from NCBI Gene Expression Omnibus (GEO) database and ArrayExpress database. The data related to HCC and matched adjacent normal tissues were also downloaded from The Cancer Genome Atlas (TCGA). Published studies reporting the association between miR‑133a‑3p expression and HCC were reviewed from multiple databases. By combining the data derived from three sources (GEO, TCGA and published studies), the authors analyzed the comprehensive relationship between miR‑133a‑3p expression and clinicopathological features of HCC. Eventually, putative targets of miR‑133a‑3p in HCC were selected for further bioinformatics prediction. A total of eight published microarray datasets were gathered, and the pooled results demonstrated that the expression of miR‑133a‑3p in the tumor group was lower than that in normal groups [standardized mean difference (SMD)=‑0.54; 95% confidence interval (CI), ‑0.74 to ‑0.35; P<0.001]. Consistently, the level of miR‑133a‑1 in HCC was reduced markedly compared to normal tissues (P<0.001) based on TCGA data, and the AUC value of low miR‑133a‑1 expression for HCC diagnosis was 0.670 (P<0.001). Furthermore, the combined SMD of all datasets (GEO, TCGA and literature) suggested that significant difference was observed between the HCC group and the normal control group, and lower miR‑133a‑3p expression in HCC group was noted (SMD=‑0.69; 95% CI, ‑1.10 to ‑0.29; P=0.001). In addition, the authors discovered five key genes of the calcium signaling pathway (NOS1, ADRA1A, ADRA1B, ADRA1D and TBXA2R) that may probably be targeted by miR‑133a‑3p in HCC. The study reveals that miR‑133a‑3p may function as a tumor suppressor in HCC. The prospective novel pathways and key genes of miR‑133a‑3p could offer potential biomarkers for HCC; however, the predictions require further confirmation.

Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is a commonly occurring tumor. Through a deeper understanding of the immune regulatory mechanisms in the tumor microenvironment, immunotherapy may serve as a potential treatment for cancer patients. This study aimed at identifying the survival-related immune cells and hub genes, which could be potential targets for immunotherapy in ccRCC.MethodsThe gene expression profiles and clinical data of ccRCC patients were extracted from UCSC Xena and Gene Expression Omnibus (GEO) databases. Kaplan-Meier (KM) survival and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were utilized to select the survival-related tumor-infiltrating immune cells. Multivariate Cox regression was utilized to develop a signature based on the tumor-infiltrating immune cells (TIICs). Based on the signature, the risk score was calculated, following which the samples were divided into high-risk and low-risk groups. Differentially expressed genes (DEGs) between the two risk groups were identified. Functional enrichment analysis was performed and cytoHubba plug-in of Cytoscape was used to identify the hub genes. Multiple datasets were utilized to validate these hub genes, including the Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and the Human Protein Atlas (HPA), and the GEO datasets. Finally, a correlation analysis was performed to evaluate the relationship between the hub genes and TIICs.ResultsFour immune survival-related cells, including T cell CD4 memory-activated, T cell regulatory (Tregs), eosinophils, and mast cell resting were identified. Nine immune-specific hub genes were identified, which included APOE, CASR, CTLA4, CXCL8, EGF, F2, KNG1, MMP9, and IL6. Furthermore, these hub genes were significantly correlated with clinical traits and closely associated with some TIICs.ConclusionA total of four survival-related immune cell types and nine hub genes were found to be closely associated with ccRCC. These findings may have implications for the development of novel potential immunotherapeutic targets for ccRCC.

Dataset Information

Identification of the potential therapeutic target gene UBE2C in human hepatocellular carcinoma: An investigation based on GEO and TCGA databases.

Publications

Identification of the potential therapeutic target gene UBE2C in human hepatocellular carcinoma: An investigation based on GEO and TCGA databases.

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