scholarly journals DNAJB11 predicts a poor prognosis and is associated with immune infiltration in thyroid carcinoma: a bioinformatics analysis

2021 ◽  
Vol 49 (11) ◽  
pp. 030006052110537
Author(s):  
Rongxin Sun ◽  
Longyan Yang ◽  
Yan Wang ◽  
Yuanyuan Zhang ◽  
Jing Ke ◽  
...  
Keyword(s):  
Thyroid Carcinoma ◽  
Poor Prognosis ◽  
Prognostic Value ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Mrna Levels ◽  
Normal Tissues ◽  
Go Enrichment ◽  
Low Levels ◽  
Go Enrichment Analysis

Objective To investigate the prognostic value of the co-chaperone protein DnaJ Heat Shock Protein Family (Hsp40) Member B11 (DNAJB11) in thyroid carcinoma (THCA). Methods This bioinformatics analysis study evaluated the prognostic value of DNAJB11 mRNA levels in THCA based on data from The Cancer Genome Atlas (TCGA). The levels of DNAJB11 mRNA in THCA and normal tissues were compared with Wilcoxon signed rank test. Kaplan–Meier survival curve analysis and Cox regression analysis were performed to evaluate the correlation between DNAJB11 mRNA levels and survival. Gene Ontology (GO) enrichment analysis was used to elucidate the functional enrichment difference. Results Data from the 502 patients with THCA from the TCGA database were analysed. DNAJB11 mRNA was downregulated in THCA tissues compared with normal tissues. Decreased levels of DNAJB11 mRNA were significantly correlated with T stage, N stage, pathological stage, histological type, extrathyroidal extension and BRAF gene status. The low levels of DNAJB11 mRNA were associated with a shorter progression-free interval. GO enrichment analysis showed that DNAJB11 was involved in immune-related biological processes. Conclusion Low levels of DNAJB11 mRNA were associated with poor prognosis in THCA.

scholarly journals Systematic Analyses of the Expression, Function, and Prognostic Value of CCNBs in Breast Caner

2021 ◽  
Author(s):  
Xinyu Liu ◽  
Yuqi Tang ◽  
Shuang Wang ◽  
Shutong Liu ◽  
Chenglin Li ◽  
...  
Keyword(s):  
Prognostic Value ◽  
Enrichment Analysis ◽  
Good Prognosis ◽  
Interactive Analysis ◽  
Kaplan Meier ◽  
Go Enrichment ◽  
Level Function ◽  
Go Enrichment Analysis ◽  
Kaplan Meier Plotter ◽  
Breast Caner

Abstract Background Cyclin B (CCNB) family plays key roles in the cell cycle, cell division and proliferation. Three members of CCNB family have been identified, including CCNB1, CCNB2 and CCNB3. Many studies have explored the roles of CCNBs in the tumorigenesis and pathogenesis of different types of cancer. However, the expression level, function, and prognostic value of CCNBs in breast caner (BC) are still unclear.Methods We explored the specific alterations of CCNBs in BC and predicted their prognostic value for BC patients. Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier plotter, cBioPortal, STRING, Database for Annotation,Visualization and Integrated Discovery (DAVID) databases were used for above analyses.Results We found that CCNB1 amd CCNB2 were significantly overexpressed in BC compared with normal samples, but not CCNB3. Survival analysis showed that upregulated CCNB1 and CCNB2 expression levels were associated with poor prognosis of BC patients, while high CCNB3 expression was related to good prognosis for BC patients. Furthermore, gene oncology (GO) enrichment analysis was performed to reveal the functions of CCNBs and the interacted genes related to CCNBs. In addition, hsa-miR-139-5p and has-miR-944 were identified to be potentially involved in the regulation of CCNB1.Conclusion Our study suggests that CCNB1, CCNB2 are potential targets of precise therapy for BC patients and that CCNB3 is a novel biomarker for the good prognosis of BC patients.

scholarly journals Identification of potential and novel target genes in pituitary prolactinoma by bioinformatics analysis

2020 ◽  
Author(s):  
Vikrant Ghatnatti ◽  
Basavaraj Vastrad ◽  
Swetha Patil ◽  
Chanabasayya Vastrad ◽  
Iranna Kotturshetti
Keyword(s):  
Gene Ontology ◽  
Signaling Pathways ◽  
Target Gene ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Condensed Chromosome ◽  
Go Enrichment ◽  
Go Enrichment Analysis

AbstractPituitary prolactinoma is one of the most complicated and fatally pathogenic pituitary adenomas. Therefore, there is an urgent need to improve our understanding of the underlying molecular mechanism that drives the initiation, progression, and metastasis of pituitary prolactinoma. The aim of the present study was to identify the key genes and signaling pathways associated with pituitary prolactinoma using bioinformatics analysis. Transcriptome microarray dataset GSE119063 was acquired from Gene Expression Omnibus datasets, which included 5 pituitary prolactinoma samples and 4 normal pituitaries samples. We screened differentially expressed genes (DEGs) with limma and investigated their biological function by pathway and Gene Ontology (GO) enrichment analysis. A protein-protein interaction (PPI) network of the up and down DEGs were constructed and analyzed by HIPPIE and Cytoscape software. Module analyses were performed. In addition, a target gene - miRNA network and target gene - TF network of the up and down DEGs were constructed by NetworkAnalyst and Cytoscape software. The set of DEGs exhibited an intersection consisting of 989 genes (461 up-regulated and 528 down-regulated), which may be associated with pituitary prolactinoma. Pathway enrichment analysis showed that the 989 DEGs were significantly enriched in the retinoate biosynthesis II, signaling pathways regulating pluripotency of stem cells, ALK2 signaling events, vitamin D3 biosynthesis, cell cycle and aurora B signaling. Gene Ontology (GO) enrichment analysis also showed that sensory organ morphogenesis, extracellular matrix, hormone activity, nuclear division, condensed chromosome and microtubule binding. In the PPI network and modules, SOX2, PRSS45, CLTC, PLK1, B4GALT6, RUNX1 and GTSE1 were considered as hub genes. In the target gene miRNA network and target gene - TF network, LINC00598, SOX4, IRX1 and UNC13A were considered as hub genes. Using integrated bioinformatics analysis, we identified candidate genes in pituitary prolactinoma, which may improve our understanding of the mechanisms of the pathogenesis and integration; genes may be therapeutic targets and prognostic markers for pituitary prolactinoma.

scholarly journals Identification of 10 Hub genes related to the progression of colorectal cancer by co-expression analysis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9633
Author(s):  
Jie Meng ◽  
Rui Su ◽  
Yun Liao ◽  
Yanyan Li ◽  
Ling Li
Keyword(s):  
Colorectal Cancer ◽  
Network Analysis ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Data Sets ◽  
Ppi Network ◽  
Hub Genes ◽  
Normal Tissues ◽  
Go Enrichment ◽  
Go Enrichment Analysis

Background Colorectal cancer (CRC) is the third most common cancer in the world. The present study is aimed at identifying hub genes associated with the progression of CRC. Method The data of the patients with CRC were obtained from the Gene Expression Omnibus (GEO) database and assessed by weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses performed in R by WGCNA, several hub genes that regulate the mechanism of tumorigenesis in CRC were identified. Differentially expressed genes in the data sets GSE28000 and GSE42284 were used to construct a co-expression network for WGCNA. The yellow, black and blue modules associated with CRC level were filtered. Combining the co-expression network and the PPI network, 15 candidate hub genes were screened. Results After validation using the TCGA-COAD dataset, a total of 10 hub genes (MT1X, MT1G, MT2A, CXCL8, IL1B, CXCL5, CXCL11, IL10RA, GZMB, KIT) closely related to the progression of CRC were identified. The expressions of MT1G, CXCL8, IL1B, CXCL5, CXCL11 and GZMB in CRC tissues were higher than normal tissues (p-value < 0.05). The expressions of MT1X, MT2A, IL10RA and KIT in CRC tissues were lower than normal tissues (p-value < 0.05). Conclusions By combinating with a series of methods including GO enrichment analysis, KEGG pathway analysis, PPI network analysis and gene co-expression network analysis, we identified 10 hub genes that were associated with the progression of CRC.

HMMR Functions as a Prognostic Biomarker in Uterine Carcinosarcoma Identified by Comprehensive Bioinformatics Analysis

2020 ◽  
Author(s):  
Hui Sun ◽  
Li Ma ◽  
Jie Chen
Keyword(s):  
Cancer Progression ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Normal Tissues ◽  
Potential Biomarker

Abstract BackgroundUterine carcinosarcoma (UCS) is a rare aggressive tumor with a high metastasis rate and poor prognosis. Bioinformatics analysis has been widely applied to screen and analyze genes in linkage to various types of cancer progression. This study aims to explore the molecular mechanism of UCS. MethodsFirst, transcriptional different expression data between UCS and normal samples were got from the GEPIA database. Subsequently, differentially expressed genes were analyzed through the Metascape with Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the STRING website and Cytoscape software were applied to construct the protein-protein interaction network. Finally, the top 30 genes obtained through the MCC algorithm were selected as hub genes, which was finally validated in TIMER, and UALCAN databases. ResultsA total of 1894 DEGs (579 up-regulated and 1315 down-regulated) were identified, GO and KEGG functional enrichment analysis were performed for the DEGs. The PPI network was constructed based on DEGs, and four clusters were excavated for further analysis and the top 30 genes were identified as hub genes. Our data showed that the expression of HMMR is significantly higher in UCS tissues compared to the paired normal tissues (p<0.05) and the elevated expression of HMMR is related to poor prognosis in patients with UCS (p= 0.0031). TPX2, AURKA, BRCA1 and BARD1 are essential for the function of HMMR. TPX2 and AURKA were found to be significantly higher in UCS compared to the normal tissue (p<0.05), and there was a statistically significant positive correlation between the expression of HMMR and AURKA, TPX2, BRCA1, BARD1 in UCS (p=1.08e-07, p=1.62e-05, p=2.02e-3, p=6.54e-6). ConclusionsOur study suggested that HMMR may be a potential biomarker for predicting the prognosis of UCS patients.

scholarly journals High Expression of PDE8B and DUOX2 Associated with Ability of Metastasis in Thyroid Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Zhenguo Sun ◽  
Xiaoshuai Yuan ◽  
Peng Du ◽  
Peng Chen
Keyword(s):  
Thyroid Carcinoma ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Thyroid Stimulating Hormone ◽  
Hub Genes ◽  
Gene Expressions ◽  
Go Enrichment ◽  
Poorly Differentiated ◽  
Microarray Datasets ◽  
Go Enrichment Analysis

Background. Hormone is an independent factor that induces differentiation of thyroid cancer (TC) cells. The thyroid-stimulating hormone (TSH) could promote the progression and invasion in TC cells. However, few genes related to hormone changes are studied in poorly differentiated metastatic TC. This study is aimed at constructing a gene set’s coexpression correlation network and verifying the changes of some hub genes involved in regulating hormone levels. Methods. Microarray datasets of TC samples were obtained from public Gene Expression Omnibus (GEO) databases. R software and bioinformatics packages were utilized to identify the differentially expressed genes (DEGs), important gene module eigengenes, and hub genes. Subsequently, the Gene Ontology (GO) enrichment analysis was constructed to explore important biological processes that are associated with the mechanism of poorly differentiated TC. Finally, some hub gene expressions were validated through real-time PCR and immunoblotting. Results. Gene chip with category number GSE76039 was analyzed, and 1190 DEGs were screened with criteria of P < 0.05 and ∣ log 2 foldchange ∣ > 2 . Our analysis showed that human dual oxidase 2 (DUOX2) and phosphodiesterase 8B (PDE8B) are the two important hub genes in a coexpression network. In addition, the validated experimental results showed that the expression levels of both DUOX2 and PDE8B were elevated in poorly differentiated metastatic TC tissues. Conclusion. This study identified and validated that DUOX2 and PDE8B were significantly associated with the metastasis ability of thyroid carcinoma.

scholarly journals Cyclin-Dependent Kinase Regulatory Subunit 2 Indicated Poor Prognosis and Facilitated Aggressive Phenotype of Hepatocellular Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Jie Zhang ◽  
Qianqian Song ◽  
Jinxia Liu ◽  
Lina Lu ◽  
Yuqing Xu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Disease Free Survival ◽  
Normal Liver ◽  
Regulatory Subunit ◽  
Mrna Levels ◽  
Cyclin Dependent Kinase ◽  
Normal Tissues ◽  
Hcc Cells

Cyclin-dependent kinase regulatory subunit 2 (CKS2) is a member of the cell cycle-dependent protein kinase subunit family, which is implicated as an oncogene in various malignancies. However, the clinical significance, oncogenic functions, and related mechanisms of CKS2 in hepatocellular carcinoma (HCC) remain largely unclear. In the present study, expression features and prognostic value of CKS2 were evaluated in the bioinformatic databases and HCC tissues. The effects of CKS2 on the malignant phenotypes of HCC cells were explored in vitro. According to the analyses of three bioinformatic databases, mRNA levels of CKS2 were elevated in HCC tissues compared with the normal tissues. Immunohistochemical assays found that high CKS2 expression was closely associated with liver cirrhosis (P=0.019), poor differentiation (P=0.02), portal vein invasion (P<0.001), TNM stage (P=0.019), tumor metastasis (P=0.008), and recurrence (P=0.003). The multivariate regression analyses suggested that CKS2 was an independent prognostic factor for overall survival (HR=2.088, P=0.014) and disease-free survival (HR=2.511, P=0.002) of HCC patients. Moreover, the bioinformatic analyses indicated that CKS2 might be associated with the malignant phenotypes in HCC progression. In addition, in vitro assays showed that CKS2 expression was higher in HCC cell lines than in normal liver cells. Knockdown of CKS2 remarkably repressed the proliferation, colony formation (P=0.0003), chemoresistance, migration (P=0.0047), and invasion (P=0.0012) of HCC cells. Taken together, overexpression of CKS2 was significantly correlated with poor prognosis of HCC patients and the malignant phenotypes of HCC cells, suggesting that it was a novel prognostic biomarker and potential target of HCC.

METTL3-Induced miR-222-3p Upregulation Inhibits STK4 and Promotes the Malignant Behaviors of Thyroid Carcinoma Cells

2021 ◽  
Author(s):  
Shaojian Lin ◽  
Yue Zhu ◽  
Chengcheng Ji ◽  
Weiming Yu ◽  
Cheng Zhang ◽  
...  
Keyword(s):  
Thyroid Carcinoma ◽  
Nude Mice ◽  
Poor Prognosis ◽  
Carcinoma Cells ◽  
The Sun ◽  
Downstream Signaling ◽  
Functional Studies ◽  
Normal Tissues ◽  
Signaling Axis ◽  
Stress Kinase

Abstract Context Abnormally high expression of N6-methyladenosine (m6A) methyltransferase-like 3 (METTL3) has been implied to accompany thyroid carcinoma (TC) development. Objective This study aimed to explore the protumorigenic role and downstream signaling axis of METTL3 in TC. Methods This study was conducted at the Sun Yat-Sen Memorial Hospital Sun Yat-Sen University. METTL3 and miR-222-3p were overexpressed or downregulated in TC cells. Tumor and adjacent normal tissues were collected from 80 patients (19 men and 60 women, aged 30-70 years) with a pathological diagnosis of TC from January 2012 to January 2015. Cells were classified and subjected to different treatments. The expression of METTL3 was validated in TC tissues and cell lines. In functional studies, METTL3 and miR-222-3p were overexpressed or downregulated in TC cells to evaluate their effects on malignant behaviors, which were subsequently verified by xenografts in nude mice. Results The expression of METTL3 was elevated in TC, correlating with poor prognosis of TC patients. Heightened METTL3 expression accelerated malignant behaviors of TC cells. Mechanistically, METTL3 stimulated miR-222-3p expression by mediating the m6A modification of pri-miR-222-3p. miR-222-3p targeted and inversely regulated serine/threonine stress kinase 4 (STK4). Knockdown of METTL3 augmented STK4 expression by downregulating miR-222-3p, thereby suppressing the malignant behaviors of TC cells as well as tumor growth and lung metastasis in nude mice. Conclusion Silencing METTL3 suppresses miR-222-3p expression and thus stimulates STK4 expression, thereby repressing the malignancy and metastasis of TC.

scholarly journals Comprehensive biological information analysis of PTEN gene in pan-cancer

2021 ◽  
Author(s):  
Hang Zhang ◽  
Wenhan Zhou ◽  
Xiaoyi Yang ◽  
Shuzhan Wen ◽  
Baicheng Zhao ◽  
...  
Keyword(s):  
3D Structure ◽  
Enrichment Analysis ◽  
Biological Information ◽  
Pten Gene ◽  
Clinical Prognosis ◽  
Regulatory Pathways ◽  
Go Enrichment ◽  
Go Enrichment Analysis ◽  
Pan Cancer ◽  
Low Expression

Abstract Background PTEN is a multifunctional tumor suppressor gene mutating at high frequency in a variety of cancers. However, its expression in pan-cancer, correlated genes, survival prognosis, and regulatory pathways are not completely described. Here, we aimed to conduct a comprehensive analysis from the above perspectives in order to provide reference for clinical application. Methods we studied the expression levels in cancers by using data from TCGA and GTEx database. Obtain expression box plot from UALCAN database. Perform mutation analysis on the cBioportal website. Obtain correlation genes on the GEPIA website. Construct protein network and perform KEGG and GO enrichment analysis on the STRING database. Perform prognostic analysis on the Kaplan-Meier Plotter website. We also performed transcription factor prediction on the PROMO database and performed RNA-RNA association and RNA-protein interaction on the RNAup Web server and RPISEq. The gene 3D structure, protein sequence and conserved domain were obtained in NCBI respectively. Results PTEN was underexpressed in all cancers we studied. It was closely related to the clinical stage of tumors, suggesting PTEN may involved in cancer development and progression. The mutations of PTEN were present in a variety of cancers, most of which were truncation mutations and missense mutations. Among cancers (KIRC, LUAD, THYM, UCEC, Gastric Cancer, Liver Cancer, Lung Cancer, Breast Cancer), patients with low expression of PTEN had a shorter OS time and poorer OS prognosis. The low expression of PTEN can cause the deterioration of RFS in certain cancers (TGCT, UCEC, LIHC, LUAD, THCA), suggesting that the expression of PTEN was related to the clinical prognosis. Our study identified genes correlated with PTEN and performed GO enrichment analysis on 100 PTEN-related genes obtained from the GEPIA website. Conclusions The understanding of PTEN gene and the in-depth exploration of its related regulatory pathways may provide insight for the discovery of tumor-specific biomarkers and clinical potential therapeutic targets.

Transcriptome Signatures Reveal Candidate Key Genes in the Peripheral Blood Mononuclear Cells of Patients With Coronary Artery Disease

2020 ◽  
Author(s):  
Vijayakrishna Kolur ◽  
Basavaraj Vastrad ◽  
Chanabasayya Vastrad ◽  
Iranna Kotturshetti ◽  
Anandkumar Tengli
Keyword(s):  
Coronary Artery Disease ◽  
Gene Ontology ◽  
Coronary Artery ◽  
Regulatory Network ◽  
Target Gene ◽  
Enrichment Analysis ◽  
Hub Genes ◽  
Go Enrichment ◽  
Artery Disease ◽  
Go Enrichment Analysis

Abstract BackgroundCoronary artery disease (CAD) is one of the most common disorders in the cardiovascular system. This study aims to explore potential signaling pathways and important biomarkers that drive CAD development. MethodsThe CAD GEO Dataset GSE113079 was featured to screen differentially expressed genes (DEGs). The pathway and Gene Ontology (GO) enrichment analysis of DEGs were analyzed using the ToppGene. We screened hub and target genes from protein-protein interaction (PPI) networks, target gene - miRNA regulatory network and target gene - TF regulatory network, and Cytoscape software. Validations of hub genes were performed to evaluate their potential prognostic and diagnostic value for CAD. Results1,036 DEGs were captured according to screening criteria (525upregulated genes and 511downregulated genes). Pathway and Gene Ontology (GO) enrichment analysis of DEGs revealed that these up and down regulated genes are mainly enriched in thyronamine and iodothyronamine metabolism, cytokine-cytokine receptor interaction, nervous system process, cell cycle and nuclear membrane. Hub genes were validated to find out potential prognostic biomarkers, diagnostic biomarkers and novel therapeutic target for CAD. ConclusionsIn summary, our findings discovered pivotal gene expression signatures and signaling pathways in the progression of CAD. CAPN13, ACTBL2, ERBB3, GATA4, GNB4, NOTCH2, EXOSC10, RNF2, PSMA1 and PRKAA1 might contribute to the progression of CAD, which could have potential as biomarkers or therapeutic targets for CAD.

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