scholarly journals Bioinformatic Evidence Reveals that Cell Cycle Correlated Genes Drive the Communication between Tumor Cells and the Tumor Microenvironment and Impact the Outcomes of Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Dongdong Chen ◽  
Zhijun Feng ◽  
Mingzhen Zhou ◽  
Zhijian Ren ◽  
Fan Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Tumor Microenvironment ◽  
Tumor Cells ◽  
Poor Prognosis ◽  
Interaction Network ◽  
Prognostic Biomarkers ◽  
Cancer Type ◽  
Hematopoietic Stem ◽  
Key Genes

Hepatocellular carcinoma (HCC) is an aggressive cancer type with poor prognosis; thus, there is especially necessary and urgent to screen potential prognostic biomarkers for early diagnosis and novel therapeutic targets. In this study, we downloaded target data sets from the GEO database, and obtained codifferentially expressed genes using the limma R package and identified key genes through the protein–protein interaction network and molecular modules, and performed GO and KEGG pathway analyses for key genes via the clusterProfiler package and further determined their correlations with clinicopathological features using the Oncomine database. Survival analysis was completed in the GEPIA and the Kaplan–Meier plotter database. Finally, correlations between key genes, cell types infiltrated in the tumor microenvironment (TME), and hypoxic signatures were explored based on the TIMER database. From the results, 11 key genes related to the cell cycle were determined, and high levels of these key genes’ expression were focused on advanced and higher grade status HCC patients, as well as in samples of TP53 mutation and vascular invasion. Besides, the 11 key genes were significantly associated with poor prognosis of HCC and also were positively related to the infiltration level of MDSCs in the TME and the HIF1A and VEGFA of hypoxic signatures, but a negative correlation was found with endothelial cells (ECs) and hematopoietic stem cells. The result determined that 11 key genes (RRM2, NDC80, ECT2, CCNB1, ASPM, CDK1, PRC1, KIF20A, DTL, TOP2A, and PBK) could play a vital role in the pathogenesis of HCC, drive the communication between tumor cells and the TME, and act as probably promising diagnostic, therapeutic, and prognostic biomarkers in HCC patients.

scholarly journals CAFs Interacting With TAMs in Tumor Microenvironment to Enhance Tumorigenesis and Immune Evasion

2021 ◽  
Vol 11 ◽  
Author(s):  
Gurcan Gunaydin
Keyword(s):  
Tumor Microenvironment ◽  
Tumor Progression ◽  
Tumor Cells ◽  
Immune Evasion ◽  
Poor Prognosis ◽  
Cancer Associated Fibroblasts ◽  
Mutual Relationship ◽  
Complex Interplay ◽  
Tumor Immune Evasion ◽  
Mechanisms Of Carcinogenesis

Cancer associated fibroblasts (CAFs) and tumor associated macrophages (TAMs) are among the most important and abundant players of the tumor microenvironment. CAFs as well as TAMs are known to play pivotal supportive roles in tumor growth and progression. The number of CAF or TAM cells is mostly correlated with poor prognosis. Both CAFs and TAMs are in a reciprocal communication with the tumor cells in the tumor milieu. In addition to such interactions, CAFs and TAMs are also involved in a dynamic and reciprocal interrelationship with each other. Both CAFs and TAMs are capable of altering each other’s functions. Here, the current understanding of the distinct mechanisms about the complex interplay between CAFs and TAMs are summarized. In addition, the consequences of such a mutual relationship especially for tumor progression and tumor immune evasion are highlighted, focusing on the synergistic pleiotropic effects. CAFs and TAMs are crucial components of the tumor microenvironment; thus, they may prove to be potential therapeutic targets. A better understanding of the tri-directional interactions of CAFs, TAMs and cancer cells in terms of tumor progression will pave the way for the identification of novel theranostic cues in order to better target the crucial mechanisms of carcinogenesis.

scholarly journals Identification of differentially expressed genes in hepatocellular carcinoma by integrated bioinformatic analysis

2019 ◽  
Author(s):  
Guangxin Yan ◽  
Zhaoyu Liu
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Dna Replication ◽  
Liver Cancer ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

AbstractHepatocellular carcinoma is one of the most common tumors in the world and has a high mortality rate. This study elucidates the mechanism of hepatocellular carcinoma- (HCC) related development. The HCC gene expression profile (GSE54238, GSE84004) was downloaded from Gene Expression Omnibus for comprehensive analysis. A total of 359 genes were identified, of which 195 were upregulated and 164 were downregulated. Analysis of the condensed results showed that “extracellular allotrope” is a substantially enriched term. “Cell cycle”, “metabolic pathway” and “DNA replication” are three significantly enriched Kyoto Encyclopedia of Genes and Genomespathways. Subsequently, a protein-protein interaction network was constructed. The most important module in the protein-protein interaction network was selected for path enrichment analysis. The results showed thatCCNA2, PLK1, CDC20, UBE2CandAURKAwere identified as central genes, and the expression of these five hub genes in liver cancer was significantly increased in The Cancer Genome Atlas. Univariate regression analysis was also performed to show that the overall survival and disease-free survival of patients in the high expression group were longer than in the expression group. In addition, genes in important modules are mainly involved in “cell cycle”, “DNA replication” and “oocyte meiosis” signaling pathways. Finally, through upstream miRNA analysis, mir-300 and mir-381-3p were found to coregulateCCNA2,AURKAandUBE2C. These results provide a set of targets that can help researchers to further elucidate the underlying mechanism of liver cancer.

scholarly journals NAP1L1 Functions as a Tumor Promoter via Recruiting Hepatoma-Derived Growth Factor/c-Jun Signal in Hepatocellular Carcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Ye-wei Zhang ◽  
Qian Chen ◽  
Bo Li ◽  
Hai-Yang Li ◽  
Xue-Ke Zhao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Growth Factor ◽  
Poor Prognosis ◽  
Quantitative Polymerase Chain Reaction ◽  
The Cancer Genome Atlas ◽  
Tumor Promoter ◽  
Mechanism Analysis ◽  
Factor C

NAP1L1 has been reported to be significantly involved in the carcinogenesis of hepatocellular carcinoma (HCC). Yet, its detailed molecular basis is still to be determined. Based on the analysis of The Cancer Genome Atlas (TCGA) database, NAP1L1 mRNA was found to be upregulated and predicted the poor prognosis initially. Subsequently, consistent with the prediction, the upregulated expression of NAP1L1 mRNA and protein levels was confirmed by quantitative polymerase chain reaction (qPCR), Western blot, and immunohistochemistry assays. Upregulated NAP1L1 protein positively promoted the disease progression and poor prognosis of HCC. In addition, NAP1L1 protein expression was considered as an independent prognostic factor in HCC. Inhibition of NAP1L1 expression by siRNA or shRNA pathway significantly reduced the cell proliferation and cell cycle transformation in vitro and in vivo. Mechanism analysis first showed that the function of NAP1L1 was to recruit hepatoma-derived growth factor (HDGF), an oncogene candidate widely documented in tumors. Furthermore, the latter interacted with c-Jun, a key oncogenic transcription factor that can induce the expression of cell cycle factors and thus stimulate the cell growth in HCC. Finally, transfecting HDGF or c-Jun could reverse the suppressive effects on HCC growth in NAP1L1-suppressed HCC cells. Our data indicate that NAP1L1 is a potential oncogene and acts via recruiting HDGF/c-Jun in HCC.

scholarly journals Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jia Wang ◽  
Rui Peng ◽  
Zheng Zhang ◽  
Yixi Zhang ◽  
Yuke Dai ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Primary Liver Cancer ◽  
Interaction Network ◽  
Chemical Carcinogenesis ◽  
Parameter Analysis ◽  
Qrt Pcr ◽  
Key Genes

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and has poor outcomes. However, the potential molecular biological process underpinning the occurrence and development of HCC is still largely unknown. The purpose of this study was to identify the core genes related to HCC and explore their potential molecular events using bioinformatics methods. HCC-related expression profiles GSE25097 and GSE84005 were selected from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) between 306 HCC tissues and 281 corresponding noncancerous tissues were identified using GEO2R online tools. The protein-protein interaction network (PPIN) was constructed and visualized using the STRING database. Gene Ontology (GO) and KEGG pathway enrichment analyses of the DEGs were carried out using DAVID 6.8 and KOBAS 3.0. Additionally, module analysis and centrality parameter analysis were performed by Cytoscape. The expression differences of key genes in normal hepatocyte cells and HCC cells were verified by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR). Additionally, survival analysis of key genes was performed by GEPIA. Our results showed that a total of 291 DEGs were identified including 99 upregulated genes and 192 downregulated genes. Our results showed that the PPIN of HCC was made up of 287 nodes and 2527 edges. GO analysis showed that these genes were mainly enriched in the molecular function of protein binding. Additionally, KEGG pathway analysis also revealed that DEGs were mainly involved in the metabolic, cell cycle, and chemical carcinogenesis pathways. Interestingly, a significant module with high centrality features including 10 key genes was found. Among these, CDK1, NDC80, HMMR, CDKN3, and PTTG1, which were only upregulated in HCC patients, have attracted much attention. Furthermore, qRT-PCR also confirmed the upregulation of these five key genes in the normal human hepatocyte cell line (HL-7702) and HCC cell lines (SMMC-7721, MHCC-97L, and MHCC-97H); patients with upregulated expression of these five key genes had significantly poorer survival and prognosis. CDK1, NDC80, HMMR, CDKN3, and PTTG1 can be used as molecular markers for HCC. This finding provides potential strategies for clinical diagnosis, accurate treatment, and prognosis analysis of liver cancer.

scholarly journals Transcriptome analysis revealed key prognostic genes and microRNAs in hepatocellular carcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8930 ◽  
Author(s):  
Xi Ma ◽  
Lin Zhou ◽  
Shusen Zheng
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Survival Analysis ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Pathway Enrichment Analysis ◽  
Cox Regression Analysis ◽  
Key Genes ◽  
Overall Survival Analysis

Background Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. However, the molecular mechanisms involved in HCC remain unclear and are in urgent need of elucidation. Therefore, we sought to identify biomarkers in the prognosis of HCC through an integrated bioinformatics analysis. Methods Messenger RNA (mRNA) expression profiles were obtained from the Gene Expression Omnibus database and The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) for the screening of common differentially expressed genes (DEGs). Function and pathway enrichment analysis, protein-protein interaction network construction and key gene identification were performed. The significance of key genes in HCC was validated by overall survival analysis and immunohistochemistry. Meanwhile, based on TCGA data, prognostic microRNAs (miRNAs) were decoded using univariable and multivariable Cox regression analysis, and their target genes were predicted by miRWalk. Results Eleven hub genes (upregulated ASPM, AURKA, CCNB2, CDC20, PRC1 and TOP2A and downregulated AOX1, CAT, CYP2E1, CYP3A4 and HP) with the most interactions were considered as potential biomarkers in HCC and confirmed by overall survival analysis. Moreover, AURKA, PRC1, TOP2A, AOX1, CYP2E1, and CYP3A4 were considered candidate liver-biopsy markers for high risk of developing HCC and poor prognosis in HCC. Upregulation of hsa-mir-1269b, hsa-mir-518d, hsa-mir-548aq, hsa-mir-548f-1, and hsa-mir-6728, and downregulation of hsa-mir-139 and hsa-mir-4800 were determined to be risk factors of poor prognosis, and most of these miRNAs have strong potential to help regulate the expression of key genes. Conclusions This study undertook the first large-scale integrated bioinformatics analysis of the data from Illumina BeadArray platforms and the TCGA database. With a comprehensive analysis of transcriptional alterations, including mRNAs and miRNAs, in HCC, our study presented candidate biomarkers for the surveillance and prognosis of the disease, and also identified novel therapeutic targets at the molecular and pathway levels.

Identification of novel prognostic biomarkers in head and neck squamous cell carcinoma using bioinformatics analysis

2020 ◽  
Vol 23 ◽  
Author(s):  
Yi Ding ◽  
Min Li ◽  
Tuersong Tayier ◽  
Long Chen ◽  
ShuMei Feng
Keyword(s):  
Cell Cycle ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Interaction Network ◽  
Tumor Grade ◽  
Neck Squamous Cell Carcinoma ◽  
Hub Genes ◽  
Key Genes

Background: : Head and neck squamous cell carcinoma (HNSCC) is a common cancer that is characterized by a complex pathogenesis. Only limited data are available on the primary pathogenic genes and pathways in HNSCC. Objective: This study aimed to identify potential biomarkers of HNSCC and explore its underlying mechanisms. Methods: We screened differentially expressed genes (DEGs) using the Gene Expression Omnibus(GEO) database. Gene Ontology (GO) and Reactome pathway enrichment were analyzed using the STRING database. The protein-protein interaction network of the DEGs was reconstructed using Cytoscape software in STRING. The ONCOMINE and UNLCAN databases were used to identify the expression of hub genes. In addition, we employed UNLCAN to correlate tumor grade with key genes. Results: Finally, the effect of hub genes on overall survival (OS) was analyzed using the Kaplan-Meier method. In total, 22 DEGs were identified, These were related to the mitotic cell cycle, mitotic G1-G1, and S phases, G2/M transition, NOTCH signaling, and regulation of TP53 activity. Seven hub genes were screened with Cytoscape. Increased expression of five hub genes (AURKA, BIRC5, MKI67, UBE2C, and TOP2A) was related to a higher tumor grade and worse OS. Conclusion: We have identified five key genes that may help us understand the carcinogenic mechanisms related to the cell cycle in HNSCC. These genes may be used as biomarkers for survival and treatment of HNSCC.

scholarly journals Microarray Data Mining and Preliminary Bioinformatics Analysis of Hepatitis D Virus-Associated Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Zhe Yu ◽  
Xuemei Ma ◽  
Wei Zhang ◽  
Xiujuan Chang ◽  
Linjing An ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
The Cancer Genome Atlas ◽  
Venn Diagram ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Hepatitis D ◽  
Increased Risk ◽  
Key Genes

Several studies have demonstrated that chronic hepatitis delta virus (HDV) infection is associated with a worsening of hepatitis B virus (HBV) infection and increased risk of hepatocellular carcinoma (HCC). However, there is limited data on the role of HDV in the oncogenesis of HCC. This study is aimed at assessing the potential mechanisms of HDV-associated hepatocarcinogenesis, especially to screen and identify key genes and pathways possibly involved in the pathogenesis of HCC. We selected three microarray datasets: GSE55092 contains 39 cancer specimens and 81 paracancer specimens from 11 HBV-associated HCC patients, GSE98383 contains 11 cancer specimens and 24 paracancer specimens from 5 HDV-associated HCC patients, and 371 HCC patients with the RNA-sequencing data combined with their clinical data from the Cancer Genome Atlas (TCGA). Afterwards, 948 differentially expressed genes (DEGs) closely related to HDV-associated HCC were obtained using the R package and filtering with a Venn diagram. We then performed gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to determine the biological processes (BP), cellular component (CC), molecular function (MF), and KEGG signaling pathways most enriched for DEGs. Additionally, we performed Weighted Gene Coexpression Network Analysis (WGCNA) and protein-to-protein interaction (PPI) network construction with 948 DEGs, from which one module was identified by WGCNA and three modules were identified by the PPI network. Subsequently, we validated the expression of 52 hub genes from the PPI network with an independent set of HCC dataset stored in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Finally, seven potential key genes were identified by intersecting with key modules from WGCNA, including 3 reported genes, namely, CDCA5, CENPH, and MCM7, and 4 novel genes, namely, CDC6, CDC45, CDCA8, and MCM4, which are associated with nucleoplasm, cell cycle, DNA replication, and mitotic cell cycle. The CDCA8 and stage of HCC were the independent factors associated with overall survival of HDV-associated HCC. All the related findings of these genes can help gain a better understanding of the role of HDV in the underlying mechanism of HCC carcinogenesis.

scholarly journals TDO2 Was Downregulated in Hepatocellular Carcinoma and Inhibited Cell Proliferation by Upregulating the Expression of p21 and p27

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chengpeng Yu ◽  
Dean Rao ◽  
He Zhu ◽  
Qiumeng Liu ◽  
Wenjie Huang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Clinical Outcomes ◽  
Poor Prognosis ◽  
Kynurenine Pathway ◽  
Potential Biomarker ◽  
In Vivo Flow Cytometry

Background. Tryptophan-2,3-dioxygenase (TDO2) converts tryptophan into kynurenine in the initial limiting step of the kynurenine pathway. During the past decade, the overexpression of TDO2 has been found in various human tumors. However, the role of TDO2 in hepatocellular carcinoma is controversial, and we sought to clarify it in this study. Methods. Western blot analysis and immunochemistry were used to detect the expression of TDO2 in human tissue specimens. The effect of TDO2 on cell proliferation in vitro was assessed using CCK8 and colony formation assays, and a xenograft mouse model was used to detect the effect of TDO2 on tumor growth in vivo. Flow cytometry was used to assess the cell cycle status. Results. Low TDO2 expression was found in HCC and was associated with poor prognosis and adverse clinical outcomes. Conversely, TDO2 could restrain the proliferation of HCC cells in vivo and in vitro. Furthermore, TDO2 upregulated the expression of p21 and p27, inducing cell-cycle arrest. Conclusions. The loss of TDO2 expression in HCC was correlated with a poor prognosis and adverse clinical outcomes. At the same time, TDO2 could restrain the growth of HCC in vivo and in vitro. The results indicate that TDO2 is a potential biomarker and therapeutic target for HCC.

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