The impact of high co-expression of Sp1 and HIF1? on prognosis of patients with hepatocellular cancer.
ABSTRACT: Transcription factor specificity protein 1 (Sp1) and hypoxia-inducible factor 1? (HIF1?) serve vital roles in tumor growth and metastasis. The present study aimed to evaluate the impact of co-expression of Sp1 and HIF1? on the prognosis of patients with hepatocellular cancer (HCC) using The Cancer Genome Atlas (TCGA) database and to validate the association between the expression levels of Sp1/HIF1? in HCC specimens and patient survival using immunohistochemical analysis. A total of 214 eligible patients with HCC from TCGA database were collected for the study. The expression profile of Sp1 and HIF1? were obtained from the TCGA RNAseq database. Clinicopathological characteristics, including age, height, weight, gender, race, ethnicity, family cancer history, serum ?-fetoprotein (AFP), surgical procedures and TNM stage were collected. The Cox proportional hazards regression model and Kaplan-Meier curves were used to assess the relative factors. Receiver operating characteristic (ROC) curves for cancer-specific survival (CSS) prediction were plotted to compare the prediction ability of expression of Sp1 and HIF1? and their co-expression. The location and expression of Sp1 and HIF1? in the HCC tissues were detected by immunohistochemistry (IHC) to verify the association between these two genes and CSS. The results demonstrated that the expressions of Sp1 and HIF1? were significantly increased in the succumbed group (P=0.001), compared with the surviving group. The CSS rates were 60.1% at 3 years (1,067 days), 35.8% at 5 years (1,823 days) and 9.5% at 10 years (3,528 days). Multivariate Cox regression analysis demonstrated that only the high expression levels of Sp1 and HIF1? (?2×10(3)) were independent predictors for cancer mortality, with P=0.001 and P=0.029, respectively. The area under the curve for the ROC was found to be higher using the combination testing for two genes (0.751) in predicting cancer mortality, compared to a single gene (0.632 for Sp1 and 0.717 for HIF1?). Based on the cutoff points for gene expression, patients were divided into 3 groups: G1 (both genes <2×10(3)), G2 (either gene ?2×10(3)) and G3 (both genes ?2×10(3)). The risk of cancer mortality increased with high expression of genes, and G3 exhibited a greater risk than G2 when compared with the G1 group (HR=5.420, 95% CI 2.767-10.616, P=0.001; HR=3.270, 95% CI 1.843-5.803, P=0.001). The IHC staining results indicated that patients who died of cancer presented with significantly higher expression levels of these genes compared with those that did not (P=0.001). In summary, high expression levels of Sp1 and HIF1? in HCC tissues were associated with poor prognosis; in particular, the co-expression of these two genes increased the risk of cancer mortality.
Project description:<h4>Background</h4>Kruppel family member zinc binding protein 89 (ZBP-89), also known as ZNF148, regulates Bak expression via binding to GC-rich promoter domain. It is not clear if other GC-rich binding factors, such as Sp family members, can interact with ZBPp-89 on Bak expression. This study aims to elucidate the mechanism of Bak expression regulation by ZBP-89 and Sp proteins, based on in vitro experiment and The Cancer Genome Atlas (TCGA) hepatocellular carcinoma (HCC) data cohort.<h4>Methods</h4>We downloaded TCGA hepatocellular carcinoma (HCC) cohort data to analysis the association of Bak transcription level with ZBP-89 and Sp proteins transcription level. HCC cell lines and liver immortal non-tumour cell lines were used for mechanism study, including western blotting analysis, expression vector mediated gene expression and siRNA interference.<h4>Results</h4>Results showed that cancer tissues have higher Bak transcription level compared with adjacent non-cancer tissues. Bak transcription level was correlated with Sp1 and Sp3 expression level, while no correlation was found in ZBP-89 and Bak, neither Sp2 nor Sp4. Mithramycin A (MMA) induced Bak expression in a dose-dependent manner. Western blotting results showed Sp1 overexpression increased Bak expression both in liver immortal non-tumour cells and HCC cells. Interference Sp1 expression could inhibit Bak expression alone. ZBP-89 siRNA suppressed Bak expression even in the presence of MMA treatment and S1 overexpression. Additionally, Bak and Sp1 level were associated with HCC patient survival.<h4>Conclusions</h4>Bak expression required ZBP-89 and Sp1 cooperative regulation simultaneously.
Project description:Uveal autoantigen with coiled-coil domains and ankyrin repeats (UACA/Nucling), has been reported to be upregulated in various cancers. However, its expression and function have not been studied in hepatocellular carcinoma (HCC). In the present study, expression of UACA was detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and the results revealed that UACA was upregulated in 23 cases of HCC compared with paired corresponding non-tumor liver tissues. In addition, the upregulation of UACA in HCC was further validated by analyzing the datasets from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and GSE36376. Furthermore, knockdown of UACA suppressed the proliferative and invasive ability as well as inducing senescence of HCC cells. Besides, the expression level of UACA was positively associated with Hif1? (hypoxia-inducible factor 1?) in HCC datasets from TCGA-LIHC and GSE54236. Moreover, treatment with CoCl2 led to the increased expression and the localization alteration of UACA in HCC cells. In summary, UACA is upregulated in HCC and knockdown of UACA ameliorated malignant behaviors of HCC cells, and UACA was correlated with and under control of Hif1?.
Project description:BACKGROUND:Studies which focused on the character of miR-144-3p in hepatocellular carcinoma (HCC) are limited. This study aimed to explore the expression, clinical significance and the potential targets of miR-144-3p in HCC. METHODS:The Cancer Genome Atlas (TCGA) and a cohort of 95 cases of HCC were applied to investigate aberrant miR-144-3p expression in HCC. A meta-analysis was performed to accumulate data on miR-144-3p expression in HCC based on TCGA, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Gene Expression Omnibus (GEO). Additionally, the potential regulatory mechanisms of miR-144-3p in HCC were explored by bioinformatics. RESULTS:MiR-144-3p expression was downregulated distinctly in HCC compared to para-HCC tissue both in TCGA data (8.9139±1.5986 vs 10.7721±0.9156, P<0.001) and in our qRT-PCR validation (1.3208±0.7594 vs 2.6200±0.9263, P<0.001). The meta-analysis based on TCGA, qRT-PCR and GEO data confirmed a consistent result (standard mean difference =-0.854, 95% CI: -1.224 to -0.484, P<0.001). The receiver operating characteristic curve of miR-144-3p gained a significant diagnostic value both in TCGA data (area under the curve [AUC] =0.852, 95% CI: 0.810 to 0.894, P<0.001) and in qRT-PCR validation (AUC =0.867, 95% CI: 0.817 to 0.916, P<0.001), especially in alpha-fetoprotein-negative HCC patients (AUC =0.900, 95% CI: 0.839 to 0.960, P<0.001). Furthermore, we identified 119 potential targets of miR-144-3p in HCC by bioinformatics. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that several significant biologic functions and pathways correlated with the pathogenesis of HCC, including the p53 signaling pathway. CONCLUSION:MiR-144-3p may function as a cancer suppressor microRNA, which is essential for HCC progression through the regulation of various signaling pathways. Thus, interactions with miR-144-3p may provide a novel treatment strategy for HCC in the future.
Project description:Prognostic markers of bone metastatic clear cell renal cell cancer (ccRCC) are poorly established. We tested prognostic value of HIF1?/HIF2? and their selected target genes in primary tumors and corresponding bone metastases.Expression of HIF2? was lower in mRCC both at mRNA and protein levels (p/mRNA/=0.011, p/protein/=0.001) while HIF1? was similar to nmRCC. At the protein level, CAIX, GAPDH and GLUT1 were increased in mRCC. In all primary RCCs, low HIF2? and high HIF1? as well as CAIX, GAPDH and GLUT1 expressions correlated with adverse prognosis, while VEGFR2 and EPOR gene expressions were associated with favorable prognosis. Multivariate analysis confirmed high HIF2? protein expression as an independent risk factor. Prognostic validation of HIFs, LDH, EPOR and VEGFR2 in RNA-Seq data confirmed higher HIF1? gene expression in primary RCC as an adverse (p=0.07), whereas higher HIF2? and VEGFR2 expressions as favorable prognostic factors. HIF1?/HIF2?-index (HIF-index) proved to be an independent prognostic factor in both the discovery and the TCGA cohort.Expressions of HIF1? and HIF2? as well as their 7 target genes were analysed on the mRNA and protein level in 59 non-metastatic ccRCCs (nmRCC), 40 bone metastatic primary ccRCCs (mRCC) and 55 corresponding bone metastases. Results were validated in 399 ccRCCs from the TCGA project.We identified HIF2? protein as an independent marker of the metastatic potential of ccRCC, however, unlike HIF1?, increased HIF2? expression is a favorable prognostic factor. The HIF-index incorporated these two markers into a strong prognostic biomarker of ccRCC.
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:In order to determine the diagnostic efficacy of microRNA (miR)-122-5p and to identify the potential molecular signaling pathways underlying the function of miR-122-5p in hepatocellular carcinoma (HCC), the expression profiles of data collected from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and literature databases were analyzed, along with any associations between clinicopathological characteristics and the diagnostic value of miR-122-5p in HCC. The intersection of 12 online prediction databases and differentially expressed genes from TCGA and GEO were utilized in order to select the prospective target genes of miR-122-5p in HCC. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction network (PPI) analyses were subsequently performed based on the selected target genes. The average expression level of miR-122-5p was decreased in HCC patients compared with controls from TCGA database (P<0.001), and the downregulation of miR-122-5p was significantly associated with HCC tissues (P<0.001), tumor vascular invasion (P<0.001), metastasis (P=0.001), sex (P=0.006), virus infection status (P=0.001) and tissue (compared with serum; P<0.001) in cases from the GEO database. The pooled sensitivity and specificity for miR-122-5p to diagnose HCC were 0.60 [95% confidence interval (CI), 0.48-0.71] and 0.81 (95% CI, 0.70-0.89), respectively. The area under the curve (AUC) value was 0.76 (95% CI, 0.72-0.80), while in Meta-DiSc 1.4, the AUC was 0.76 (Q*=0.70). The pooled sensitivity and specificity were 0.60 (95% CI, 0.57-0.62) and 0.79 (95% CI, 0.76-0.81), respectively. A total of 198 overlapping genes were selected as the potential target genes of miR-122-5p, and 7 genes were defined as the hub genes from the PPI network. Cell division cycle 6 (CDC6), minichromosome maintenance complex component 4 (MCM4) and MCM8, which serve pivotal functions in the occurrence and development of HCC, were the most significant hub genes. The regulation of cell proliferation for cellular adhesion and the biosynthesis of amino acids was highlighted in the GO and KEGG pathway analyses. The downregulation of miR-122-5p in HCC demonstrated diagnostic value, worthy of further attention. Therefore, miR-122-5p may function as a tumor suppressor by modulating genome replication.
Project description:Hepatocellular carcinoma (HCC) ranks fourth in cancer-related mortality worldwide. N1-methyladenosine (m1A), a methylation modification on RNA, is gaining attention for its role across diverse biological processes. However, m1A-related regulatory genes expression, its relationship with clinical prognosis, and its role in HCC remain unclear. In this study, we utilized The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) database to investigate alterations within 10 m1A-related regulatory genes and observed a high mutation frequency (23/363). Cox regression analysis and least absolute shrinkage and selection operator were used to explore the association between m1A-related regulatory genes expression and HCC patient survival and identified four regulators that were remarkably associated with HCC patient prognosis. Additionally, an independent cohort from International Cancer Genome Consortium was studied to validate our discoveries and found to be consistent with those in the TCGA dataset. In terms of mechanism, gene set enrichment analysis linked these four genes with various physiological roles in cell division, the MYC pathway, protein metabolism, and mitosis. Kyoto Encyclopedia of Genes and Genomes analysis revealed that PI3K/Akt signaling pathway had potential relevance to m1A-related regulatory genes in HCC. These findings indicate that m1A-related regulatory genes may play crucial roles in regulating HCC progression and be exploited for diagnostic and prognostic purposes.
Project description: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.
Project description:There is accumulating evidence that miRNA might serve as potential diagnostic and prognostic markers for various types of cancer. Hepatocellular carcinoma (HCC) is the most common type of malignant lesion but the significance of miRNAs in HCC remains largely unknown. The present study aimed to establish the diagnostic value of miR-101-3p/5p in HCC and then further investigate the prospective molecular mechanism via a bioinformatic analysis. First, the miR-101 expression profiles and parallel clinical parameters from 362 HCC patients and 50 adjacent non-HCC tissue samples were downloaded from The Cancer Genome Atlas (TCGA). Second, we aggregated all miR-101-3p/5p expression profiles collected from published literature and the Gene Expression Omnibus and TCGA databases. Subsequently, target genes of miR-101-3p and miR-101-5p were predicted by using the miRWalk database and then overlapped with the differentially expressed genes of HCC identified by natural language processing. Finally, bioinformatic analyses were conducted with the overlapping genes. The level of miR-101 was significantly lower in HCC tissues compared with adjacent non-HCC tissues (P < 0.001), and the area under the curve of the low miR-101 level for HCC diagnosis was 0.925 (P < 0.001). The pooled summary receiver operator characteristic (SROC) of miR-101-3p was 0.86, and the combined SROC curve of miR-101-5p was 0.80. Bioinformatic analysis showed that the target genes of both miR-101-3p and miR-101-5p are involved in several pathways that are associated with HCC. The hub genes for miR-101-3p and miR-101-5p were also found. Our results suggested that both miR-101-3p and miR-101-5p might be potential diagnostic markers in HCC, and that they exert their functions via targeting various prospective genes in the same pathways.
Project description:Background:Hepatocellular carcinoma (HCC) is a major cause of cancer mortality and an increasing incidence worldwide; however, there are very few effective diagnostic approaches and prognostic biomarkers. Materials and methods:One hundred forty-nine pairs of HCC samples from Gene Expression Omnibus (GEO) were obtained to screen differentially expressed genes (DEGs) between HCC and normal samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses, and protein-protein interaction network were used. Cox proportional hazards regression analysis was used to identify significant prognostic DEGs, with which a gene expression signature prognostic prediction model was identified in The Cancer Genome Atlas (TCGA) project discovery cohort. The robustness of this panel was assessed in the GSE14520 cohort. We verified details of the gene expression level of the key molecules through TCGA, GEO, and qPCR and used immunohistochemistry for substantiation in HCC tissues. The methylation states of these genes were also explored. Results:Ninety-eight genes, consisting of 13 upregulated and 85 downregulated genes, were screened out in three datasets. KEGG and Gene ontology analysis for the DEGs revealed important biological features of each subtype. Protein-protein interaction network analysis was constructed, consisting of 64 nodes and 115 edges. A subset of four genes (SPINK1, TXNRD1, LCAT, and PZP) that formed a prognostic gene expression signature was established from TCGA and validated in GSE14520. Next, the expression details of the four genes were validated with TCGA, GEO, and clinical samples. The expression panels of the four genes were closely related to methylation states. Conclusion:This study identified a novel four-gene signature biomarker for predicting the prognosis of HCC. The biomarkers may also reveal molecular mechanisms underlying development of the disease and provide new insights into interventional strategies.