scholarly journals Exploring the Expression and Prognostic Value of the TCP1 Ring Complex in Hepatocellular Carcinoma and Overexpressing Its Subunit 5 Promotes HCC Tumorigenesis

2021 ◽  
Vol 11 ◽  
Author(s):  
Jiahui Liu ◽  
Ling Huang ◽  
Yi Zhu ◽  
Yongyin He ◽  
Weiyun Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Migration And Invasion ◽  
Protein Levels ◽  
T Complex ◽  
Complex Protein ◽  
Ring Complex

T-complex protein-1 ring complex (TRiC), also known as Chaperonin Containing T-complex protein-1 (CCT), is a multisubunit chaperonin required for the folding of nascent proteins. Mounting evidence suggests that TRiC also contributes to the development and progression of tumors, but there are limited studies on pathogenic functions in hepatocellular carcinoma (HCC). We comprehensively evaluated the expression pattern and biological functions of TRiC subunits using The Cancer Genome Atlas and The Human Protein Atlas. Expression levels of TRiC subunits TCP1, CCT2/3/4/5/6A/7/8 were significantly upregulated in HCC tissues at both transcript and protein levels, which predicted shorter overall survival (OS). Moreover, high mutation rates were found in several CCT subunits, and patients with altered CCT genes exhibited poorer clinical outcomes. Functional enrichment analysis showed that co-regulated genes were preferentially involved in ‘protein folding’ and ‘microtubule-based process’, while genes co-expressed with CCT subunits were primarily involved in ‘ribosome’ and ‘spliceosome’. Knockout of CCT5 in a HCC cell line reduced while overexpression enhanced proliferation rate, cycle transition, migration, and invasion. In conclusion, these findings suggest that subunits of the TRiC may be potential biomarkers for the diagnosis of HCC and play an important role in the occurrence and development of HCC.

scholarly journals Co-Expression Network Revealed the Potential Regulatory Mechanism of Lncrnas in Relapse Hepatocellular Carcinoma.

2021 ◽  
Author(s):  
Yuan Fang ◽  
Yang Yang ◽  
XiaoLi Zhang ◽  
Na Li ◽  
Bo Yuan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Clinical Samples ◽  
Survival Prediction ◽  
Cancer Type ◽  
Gene Modules ◽  
Prediction Functions

Abstract Background: The mechanistic basis for the relapse of hepatocellular carcinoma (HCC) remains poorly understood. Recent research has highlighted the important roles of long non-coding RNAs (lncRNAs) in HCC. However, there are only a few studies on lncRNAs associated with the relapse of HCC.Methods:We analyzed lncRNA and mRNA profiles in the GSE101432 dataset associated with HCC relapse. The differentially expressed lncRNAs and mRNAs were used to construct an lncRNA-mRNA co-expression network. Weighted gene co-expression network analysis followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted on the database. Furthermore, correlation and survival analyses were performed using The Cancer Genome Atlas database, and the clinical samples were verified by qRT-PCR.Results:In this study, lncRNAs and mRNAs associated with HCC recurrence were identified. Two gene modules were found to be closely linked to HCC relapse. The functional enrichment analysis results of lncRNAs and co-expression mRNAs indicated that they were closely related to the recurrence of HCC. In addition, we verified that the overall survival and recurrence-free survival of these genes in HCC have survival prediction functions. In total, we identified and validated two lncRNAs (LINC00941 and LINC00668) and six mRNAs (LOX, MICB, OTX1, BAIAP2L2, KCTD17, NDUFA4L2) associated with HCC relapse.Conclusion: In summary, we identified the key gene modules and central genes associated with recurrent HCC, and constructed lncRNA-mRNA networks related to this cancer type. These results provide a foundation for future basic research on the mechanism of recurrent liver cancer.

scholarly journals Co-Expression Network Revealed The Potential Regulatory Mechanism of lncRNAs In Relapse Hepatocellular Carcinoma.

2021 ◽  
Author(s):  
Yuan Fang ◽  
Yang Yang ◽  
XiaoLi Zhang ◽  
Na Li ◽  
Bo Yuan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Clinical Samples ◽  
Survival Prediction ◽  
Cancer Type ◽  
Gene Modules ◽  
Prediction Functions

Abstract Background: The mechanistic basis for the relapse of hepatocellular carcinoma (HCC) remains poorly understood. Recent research has highlighted the important roles of long non-coding RNAs (lncRNAs) in HCC. However, there are only a few studies on lncRNAs associated with the relapse of HCC.Methods:We analyzed lncRNA and mRNA profiles in the GSE101432 dataset associated with HCC relapse. The differentially expressed lncRNAs and mRNAs were used to construct a lncRNA-mRNA co-expression network. Weighted gene co-expression network analysis followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted on the database. Furthermore, correlation and survival analyses were performed using The Cancer Genome Atlas database, and the clinical samples were verified by qRT-PCR.Results:In this study, lncRNAs and mRNAs associated with HCC relapse were identified. Two gene modules were found to be closely linked to HCC relapse. The functional enrichment analysis results of lncRNAs and co-expression mRNAs indicated that they were closely related to the relapse of HCC. In addition, we verified that the overall survival and recurrence-free survival of these genes in HCC have survival prediction functions. In total, we identified and validated two lncRNAs (LINC00941 and LINC00668) and six mRNAs (LOX, MICB, OTX1, BAIAP2L2, KCTD17, NDUFA4L2) associated with HCC relapse.Conclusion: In summary, we identified the key gene modules and central genes associated with relapse of HCC, and constructed lncRNA-mRNA networks related to this cancer type. These results provide a foundation for future basic research on the mechanism of relapse of HCC.

scholarly journals Identification of Prognostic Stromal-Immune Score–Based Genes in Hepatocellular Carcinoma Microenvironment

2021 ◽  
Vol 12 ◽  
Author(s):  
Shanshan Liu ◽  
Guangchuang Yu ◽  
Li Liu ◽  
Xuejing Zou ◽  
Lang Zhou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Immune Cells ◽  
Malignant Tumors ◽  
Clinical Importance ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Score

A growing amount of evidence has suggested the clinical importance of stromal and immune cells in the liver cancer microenvironment. However, reliable prognostic signatures based on assessments of stromal and immune components have not been well-established. This study aimed to identify stromal-immune score–based potential prognostic biomarkers for hepatocellular carcinoma. Stromal and immune scores were estimated from transcriptomic profiles of a liver cancer cohort from The Cancer Genome Atlas using the ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm. Least absolute shrinkage and selection operator (LASSO) algorithm was applied to select prognostic genes. Favorable overall survivals and progression-free interval were found in patients with high stromal score and immune score, and 828 differentially expressed genes were identified. Functional enrichment analysis and protein–protein interaction networks further showed that these genes mainly participated in immune response, extracellular matrix, and cell adhesion. MMP9 (matrix metallopeptidase 9) was identified as a prognostic tumor microenvironment–associated gene by using LASSO and TIMER (Tumor IMmune Estimation Resource) algorithms and was found to be positively correlated with immunosuppressive molecules and drug response.

scholarly journals Immunogenomic Landscape Analysis of Prognostic Immune-Related Genes in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Peng Qin ◽  
Mengyu Zhang ◽  
Xue Liu ◽  
Ziming Dong
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Immune Related Genes

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death. HBV infection is an important risk factor for the tumorigenesis of HCC, given that the inflammatory environment is closely related to morbidity and prognosis. Consequently, it is of urgent importance to explore the immunogenomic landscape to supplement the prognosis of HCC. The expression profiles of immune‐related genes (IRGs) were integrated with 377 HCC patients to generate differentially expressed IRGs based on the Cancer Genome Atlas (TCGA) dataset. These IRGs were evaluated and assessed in terms of their diagnostic and prognostic values. A total of 32 differentially expressed immune‐related genes resulted as significantly correlated with the overall survival of HCC patients. The Gene Ontology functional enrichment analysis revealed that these genes were actively involved in cytokine‐cytokine receptor interaction. A prognostic signature based on IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) stratified patients into high-risk versus low-risk groups in terms of overall survival and remained as an independent prognostic factor in multivariate analyses after adjusting for clinical and pathologic factors. Several IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) of clinical significance were screened in the present study, revealing that the proposed clinical-immune signature is a promising risk score for predicting the prognosis of HCC.

scholarly journals Exosomal circRNA in Digestive System Tumors: The Main Player or Coadjuvants?

2021 ◽  
Vol 11 ◽  
Author(s):  
Haoying Wang ◽  
Xi Zeng ◽  
Ya Zheng ◽  
Yuping Wang ◽  
Yongning Zhou
Keyword(s):  
Colorectal Cancer ◽  
Gastric Cancer ◽  
Hepatocellular Carcinoma ◽  
Digestive System ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Circular Rna ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment

Exosomes are a type of extracellular microvesicles with a diameter of 40–160 nm. Circular RNA (circRNA) is a type of closed circular RNA molecule that is highly conserved in evolution. Exosomal circRNA plays a vital role in the proliferation, invasion, migration, and drug resistance of digestive system tumors. In this study, we used The Cancer Genome Atlas (TCGA) database, UALCAN, Python crawler, miRTargetLink Human, Database for Annotation, Visualization, and Integrated Discovery (DAVID), micBioinformatic online tool, and Cytoscape software (3.7.1). The results showed that circ-RanGAP1 in gastric cancer, circUHRF1 in hepatocellular carcinoma, and circFMN2 in colorectal cancer regulate the malignant behavior of tumors and affect the expression of their host gene through sponging miR-877-3p, miR-449c-5p, and miR-1182, respectively. Twenty exosomal circRNAs regulate 6,570 target genes through sponging 23 miRNAs. Firstly, 270 of those target genes are regulated by two or more miRNAs, which are highly correlated with 83 tumor-related pathways and six Kyoto Encyclopedia of Genes and Genomes pathways. Secondly, 1,146 target genes were significantly differentially expressed in corresponding digestive system tumors, and functional enrichment analysis revealed that 78 of those were involved in 20 cancer-related pathways. In short, the bioinformatics analysis showed that these exosomal circRNAs are stably expressed in body fluids, and regulate the occurrence and development of gastric cancer, hepatocellular carcinoma, colorectal cancer, and other digestive system tumors through sponging miRNAs. Exosomal circRNAs may be used as biomarkers for the diagnosis of disease and identification of effective therapeutic targets in the future, as well as improve the prognosis of patients with digestive system tumors.

scholarly journals A Comprehensive Analysis of the MAGE Family as Prognostic and Diagnostic Markers for Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Rong Li ◽  
Jiao Gong ◽  
Cuicui Xiao ◽  
Shuguang Zhu ◽  
Zhongying Hu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Molecular Mechanisms ◽  
Clinical Stage ◽  
Enrichment Analysis ◽  
Tumor Grade ◽  
Functional Enrichment Analysis ◽  
Genetic Alterations ◽  
Diagnostic Markers ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment

Abstract Background: The Melanoma Antigen Gene (MAGE) family is a large, highly conserved group of proteins that share a common MAGE homology domain. Multiple MAGEs are aberrantly expressed in a variety of cancers. However, the function of distinct MAGE genes in hepatocellular carcinoma (HCC) is largely unclear. Our study aimed to comprehensively analyze the MAGE family as prognostic and diagnostic markers for HCC. Methods: In this research, all HCC data were obtained from NCBI GEO DataSets, The Cancer Genome Atlas (TCGA) and our clinical center. UALCAN was used to reveal the expression profile of distinct MAGEs in HCC and further evaluate the association between the expression of MAGEs and the clinicopathological characteristics of HCC patients, including clinical stage, tumor grade. Kaplan-Meier Plotter (KM-Plot) was used to evaluate the correlation between MAGEs expression and the overall survival (OS) of HCC patients. qRT-PCR was used to detection the expression levels of MAGEs in HCC samples. cBioPortal was used to analyze the genetic alterations in MAGEs and their associations with OS of HCC patients. Gene Set Variation Analysis (GSVA) algorithm was used to do functional enrichment analysis of MAGE genes in HCC to reveal the molecular mechanisms of MAGEs functioned in HCC. Results: Our research showed that many MAGE genes were dysregulated in HCC and most of them were highly expressed. Among them, MAGEA1、MAGEC2、MAGED1、MAGED2、MAGEF1 and MAGEL2 were significantly correlated with clinical stage and differentiation of HCC patients. MAGED1、MAGED2、MAGEA6、MAGEA12、MAGEA10、MAGEB4、MAGEL2 and MAGEC3 had significant correlation with HCC prognosis. Further functional enrichment analysis suggested the dysregulated MAGEs may play important roles in signal transduction. Conclusions: Taken together, our research revealed that multiple MAGEs were dysregulated in HCC and they might play important roles in the development of HCC and can be exploited as useful biomarkers for diagnosis and treatment for HCC.

scholarly journals CCTs as new biomarkers for the prognosis of head and neck squamous cancer

Open Medicine ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 672-688
Author(s):  
Yanbo Dong ◽  
Siyu Lu ◽  
Zhenxiao Wang ◽  
Liangfa Liu
Keyword(s):  
Head And Neck ◽  
Survival Data ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Advanced Tumor Stage ◽  
Expression Levels ◽  
T Complex ◽  
Advanced Tumor ◽  
Squamous Cancer

AbstractThe chaperonin-containing T-complex protein 1 (CCT) subunits participate in diverse diseases. However, little is known about their expression and prognostic values in human head and neck squamous cancer (HNSC). This article aims to evaluate the effects of CCT subunits regarding their prognostic values for HNSC. We mined the transcriptional and survival data of CCTs in HNSC patients from online databases. A protein–protein interaction network was constructed and a functional enrichment analysis of target genes was performed. We observed that the mRNA expression levels of CCT1/2/3/4/5/6/7/8 were higher in HNSC tissues than in normal tissues. Survival analysis revealed that the high mRNA transcriptional levels of CCT3/4/5/6/7/8 were associated with a low overall survival. The expression levels of CCT4/7 were correlated with advanced tumor stage. And the overexpression of CCT4 was associated with higher N stage of patients. Validation of CCTs’ differential expression and prognostic values was achieved by the Human Protein Atlas and GEO datasets. Mechanistic exploration of CCT subunits by the functional enrichment analysis suggests that these genes may influence the HNSC prognosis by regulating PI3K-Akt and other pathways. This study implies that CCT3/4/6/7/8 are promising biomarkers for the prognosis of HNSC.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

scholarly journals Identifying and characterizing lincRNA genomic clusters reveals its cooperative functions in human cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Hanxiao Zhou ◽  
Yue Gao ◽  
Xin Li ◽  
Shipeng Shang ◽  
Peng Wang ◽  
...  
Keyword(s):  
Human Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Pathophysiological Mechanism ◽  
Multiple Cancer ◽  
Cancer Types ◽  
Genomic Clusters

Abstract Background Emerging evidence has revealed that some long intergenic non-coding RNAs (lincRNAs) are likely to form clusters on the same chromosome, and lincRNA genomic clusters might play critical roles in the pathophysiological mechanism. However, the comprehensive investigation of lincRNA clustering is rarely studied, particularly the characterization of their functional significance across different cancer types. Methods In this study, we firstly constructed a computational method basing a sliding window approach for systematically identifying lincRNA genomic clusters. We then dissected these lincRNA genomic clusters to identify common characteristics in cooperative expression, conservation among divergent species, targeted miRNAs, and CNV frequency. Next, we performed comprehensive analyses in differentially-expressed patterns and overall survival outcomes for patients from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) across multiple cancer types. Finally, we explored the underlying mechanisms of lincRNA genomic clusters by functional enrichment analysis, pathway analysis, and drug-target interaction. Results We identified lincRNA genomic clusters according to the algorithm. Clustering lincRNAs tended to be co-expressed, highly conserved, targeted by more miRNAs, and with similar deletion and duplication frequency, suggesting that lincRNA genomic clusters may exert their effects by acting in combination. We further systematically explored conserved and cancer-specific lincRNA genomic clusters, indicating they were involved in some important mechanisms of disease occurrence through diverse approaches. Furthermore, lincRNA genomic clusters can serve as biomarkers with potential clinical significance and involve in specific pathological processes in the development of cancer. Moreover, a lincRNA genomic cluster named Cluster127 in DLK1-DIO3 imprinted locus was discovered, which contained MEG3, MEG8, MEG9, MIR381HG, LINC02285, AL132709.5, and AL132709.1. Further analysis indicated that Cluster127 may have the potential for predicting prognosis in cancer and could play their roles by participating in the regulation of PI3K-AKT signaling pathway. Conclusions Clarification of the lincRNA genomic clusters specific roles in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types.

scholarly journals Long Noncoding RNA RP11-357H14.17 Plays an Oncogene Role in Gastric Cancer by Activating ATF2 Signaling and Enhancing Treg Cells

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Tang Xiaoli ◽  
Wang Wenting ◽  
Zhang Meixiang ◽  
Zuo Chunlei ◽  
Hu Chengxia
Keyword(s):  
Gastric Cancer ◽  
Noncoding Rna ◽  
Prognostic Value ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Treg Cells ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Biological Behavior

Background. Gastric cancer (GC) is one of the most common malignant tumors in the world. The potential functions and mechanisms of long noncoding RNAs (lncRNAs) in GC development are still unclear. It is of great significance to explore the prognostic value of LncRNA signatures for GC. Methods. LncRNAs differently expressed in GC and their prognostic value were studied based on The Cancer Genome Atlas (TCGA) database. The functional regulatory network and immune infiltration of RP11-357H14.17 were further studied using a variety of bioinformatics tools and databases. Results. We found that the high expression of RP11-357H14.17 was closely associated with shortened overall survival (OS) and poor prognosis in gastric cancer patients. We also found that its expression was related to clinical features including tumor volume, metastasis, and differentiation. Functional enrichment analysis revealed that RP11-357H14.17 is closely related to enhanced DNA replication and metabolism; ssGSEA analysis implied the oncogenic roles of RP11-357H14.17 was related to ATF2 signaling and Treg cell differentiation. Furthermore, we verified such link by using real-time PCR and IHC staining in human GC samples. Conclusion. We demonstrate that RP11-357H14.17 may play a crucial role in the occurrence, development, and malignant biological behavior of gastric cancer as a potential prognostic marker for gastric cancer.

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