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 The Partial Role of KLF4 and KLF5 in Gastrointestinal Tumors

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jun-Chen Li ◽  
Qiu-Han Chen ◽  
Rui Jian ◽  
Jiang-Rong Zhou ◽  
Yun Xu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Enrichment Analysis ◽  
Gastrointestinal Tumors ◽  
Gastric Cancer Cells ◽  
Interactive Analysis ◽  
Kaplan Meier ◽  
Online Databases ◽  
Go Enrichment ◽  
Gastric Cancer Cell Proliferation

Background. KLF4 and KLF5 are members of the KLF transcription factor family, which play an important role in many gastrointestinal tumors. To gain a deeper insight into its function and role, bioinformatics was used to analyze the function and role of KLF4 and KLF5 in gastrointestinal tumors. Methods. Data were collected from several online databases. Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN database analysis, Kaplan-Meier Plotter analysis, LOGpc system, the Pathology Atlas, and the STRING website were used to analyze the data. We download relevant data from TCGA and then perform GO enrichment and KEGG enrichment analysis. The effects of KLF5 on gastric cancer cell proliferation were measured by CCK-8 assay. The effect of KLF5 on the expression of CyclinD1 and MMP9 was detected by Western blot. Results. KLF4 and KLF5 were differentially expressed in normal and tumor tissues of the gastrointestinal tract, and their differential expression is related to several genes or pathways. KEGG analysis showed that KLF5 was coexpressed with endocytosis-related genes. KLF5 promotes the proliferation of gastric cancer cells and the expression of metastasis-related molecules. Conclusion. KLF4 and KLF5 are of great significance for developing gastrointestinal tumors and can be used as therapeutic targets.

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 Identification of Flap Endonuclease 1 With Diagnostic and Prognostic Value in Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Min Wu ◽  
Pan Zhang ◽  
Penghui Wang ◽  
Zhen Fang ◽  
Yaqin Zhu
Keyword(s):  
Breast Cancer ◽  
Prognostic Marker ◽  
Prognostic Value ◽  
Diagnostic Value ◽  
Roc Curve Analysis ◽  
Free Survival ◽  
Flap Endonuclease 1 ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

ObjectiveThis study aims to identify the potential value of flap endonuclease 1 (FEN1) as a diagnostic and prognostic marker for breast cancer (BC).MethodsELISA was used to measure serum FEN1 levels and ECLIA for CA153 and CEA levels. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value. Oncomine and UALCAN databases were used to analyze the differences in FEN1 mRNA and protein expressions. Kaplan-Meier Plotter database was then used to assess the prognostic value.ResultsBioinformatics analysis showed that the FEN1 mRNA and protein levels were significantly higher in BC tissues than in normal tissues. FEN1 was detected in culture medium of BC cell lines and serum FEN1 concentrations were significantly increased in BC patients than in cancer-free individuals. Besides, FEN1 exhibited higher diagnostic accuracy (AUC values>0.800) than CA153 and CEA for distinguishing BC patients, especially early BC, from the healthy and benign groups, or individually. Additionally, serum FEN1 levels were significantly associated with the stage (P=0.001) and lymph invasion (P=0.016), and serum FEN1 levels were increased with the development of BC. Furthermore, serum FEN1 levels were significantly decreased in post-operative patients than in pre-operative patients (P=0.016). Based on the Kaplan-Meier Plotter database, the survival analysis indicated that FEN1 overexpression was associated with poor prognoses for overall survival (OS), relapse-free survival (RFS), and distant metastasis-free survival (DMFS) in BC patients.ConclusionFEN1 might be a novel diagnostic and prognostic marker for BC.

scholarly journals DPYSL2 as potential diagnostic and prognostic biomarker linked to immune infiltration in lung adenocarcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yang-Jie Wu ◽  
Ai-Tao Nai ◽  
Gui-Cheng He ◽  
Fei Xiao ◽  
Zhi-Min Li ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Roc Curve ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
List Type ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background Dihydropyrimidinase like 2 (DPYSL2) has been linked to tumor metastasis. However, the function of DPSY2L in lung adenocarcinoma (LUAD) is yet to be explored. Methods Herein, we assessed DPYSL2 expression in various tumor types via online databases such as Oncomine and Tumor Immune Estimation Resource (TIMER). Further, we verified the low protein and mRNA expressions of DPYSL2 in LUAD via the ULCAN, The TCGA and GEPIA databases. We applied the ROC curve to examine the role of DPYSL2 in diagnosis. The prognostic significance of DPYSL2 was established through the Kaplan–Meier plotter and the Cox analyses (univariate and multivariate). TIMER was used to explore DPYSL2 expression and its connection to immune infiltrated cells. Through Gene Set Enrichment Analysis, the possible mechanism of DPYSL2 in LUAD was investigated. Results In this study, database analysis revealed lower DPYSL2 expression in LUAD than in normal tissues. The ROC curve suggested that expression of DPYSL2 had high diagnostic efficiency in LUAD. The DPYSL2 expression had an association with the survival time of LUAD patients in the Kaplan–Meier plotter and the Cox analyses. The results from TIMER depicted a markedly positive correlation of DPYSL2 expression with immune cells infiltrated in LUAD, such as macrophages, dendritic cells, CD4+ T cells, and neutrophils. Additionally, many gene markers for the immune system had similar positive correlations in the TIMER analysis. In Gene Set Enrichment Analysis, six immune-related signaling pathways were associated with DPYSL2. Conclusions In summary, DPYSL2 is a novel biomarker with diagnostic and prognostic potential for LUAD as well as an immunotherapy target. Highlights Expression of DPYSL2 was considerably lower in LUAD than in normal tissues. Investigation of multiple databases showed a high diagnostic value of DPYSL2 in LUAD. DPYSL2 can independently predict the LUAD outcomes. Immune-related mechanisms may be potential ways for DPYSL2 to play a role in LUAD.

scholarly journals Comprehensive Analysis of the Expression and Prognosis for IRXs in Non-small Cell Lung Cancer

2020 ◽  
Author(s):  
Qiongzi Wang ◽  
Xueshan Qiu
Keyword(s):  
Lung Cancer ◽  
Human Lung ◽  
Expression Patterns ◽  
Human Lung Cancer ◽  
Prognostic Indicators ◽  
Normal Lung ◽  
Kaplan Meier ◽  
Go Enrichment ◽  
Cancer Tissues ◽  
Kaplan Meier Plotter

Abstract Iroquoishomeobox transcription factor family （IRXs）have been increasingly reported to play roles in suppressing or promoting a variety of cancers, however, little is known about their expression and prognostic value in terms of human lung cancer. In this study, Oncomine, GEPIA, Kaplan-Meier plotter, and cBioPortal databases were used to analyze the different expression patterns and prognostic values of six IRXs in NSCLC and examine their related functions and pathways using GO enrichment. Compared with normal lung cancer tissues, the expression of IRX1 and IRX2 in NSCLC tissues was significantly lower and was positively correlated with the 10-year survival rate of patients. Higher expression of IRX4 was related to terminal tumors, and suggested a poor prognosis. It was also found that IRXs may play a tumor-suppressive role in the localization of cytoplasm in NSCLC, while localization in the nucleus suggests a more malignant behavior. Together these results suggest that IRX1 and IRX2 may be prognostic indicators of LUAD, and that IRX4 could be a potential target for LUAD treatment.

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.

scholarly journals Integrative Analysis of Three Novel Competing Endogenous RNA Biomarkers with a Prognostic Value in Lung Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Juan Tan ◽  
Weimin Wang ◽  
Bin Song ◽  
Yingjian Song ◽  
Zili Meng
Keyword(s):  
High Risk ◽  
Lung Adenocarcinoma ◽  
Prognostic Value ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Function Enrichment Analysis ◽  
Pathway Function ◽  
Function Enrichment

Increasing evidence has shown competitive endogenous RNAs (ceRNAs) play key roles in numerous cancers. Nevertheless, the ceRNA network that can predict the prognosis of lung adenocarcinoma (LUAD) is still lacking. The aim of the present study was to identify the prognostic value of key ceRNAs in lung tumorigenesis. Differentially expressed (DE) RNAs were identified between LUAD and adjacent normal samples by limma package in R using The Cancer Genome Atlas database (TCGA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function enrichment analysis was performed using the clusterProfiler package in R. Subsequently, the LUAD ceRNA network was established in three steps based on ceRNA hypothesis. Hub RNAs were identified using degree analysis methods based on Cytoscape plugin cytoHubba. Multivariate Cox regression analysis was implemented to calculate the risk score using the candidate ceRNAs and overall survival information. The survival differences between the high-risk and low-risk ceRNA groups were determined by the Kaplan-Meier and log-rank test using survival and survminer package in R. A total of 2,989 mRNAs, 185 lncRNAs, and 153 miRNAs were identified. GO and KEGG pathway function enrichment analysis showed that DE mRNAs were mainly associated with “sister chromatid segregation,” “regulation of angiogenesis,” “cell adhesion molecules (CAMs),” “cell cycle,” and “ECM-receptor interaction.” LUAD-related ceRNA network was constructed, which comprised of 54 nodes and 78 edges. Top ten hub RNAs (hsa-miR-374a-5p, hsa-miR-374b-5p, hsa-miR-340-5p, hsa-miR-377-3p, hsa-miR-21-5p, hsa-miR-326, SNHG1, RALGPS2, and PITX2) were identified according to their degree. Kaplan-Meier survival analyses demonstrated that hsa-miR-21-5p and RALGPS2 had a significant prognostic value. Finally, we found that a high risk of three novel ceRNA interactions (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) was positively associated with worse prognosis. Three novel ceRNAs (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) might be potential biomarkers for the prognosis and treatment of LUAD.

scholarly journals Mining Featured Biomarkers Linked with Epithelial Ovarian Cancer Based on Bioinformatics

Diagnostics ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 39
Author(s):  
◽  
Chanabasayya Vastrad ◽  
◽  
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Target Gene ◽  
Enrichment Analysis ◽  
Microrna Target ◽  
Pathway Enrichment ◽  
Protein Protein Interaction ◽  
Go Enrichment ◽  
Gene Regulatory ◽  
Go Enrichment Analysis

: Epithelial ovarian cancer (EOC) is the18th most common cancer worldwide and the 8th most common in women. The aim of this study was to diagnose the potential importance of, as well as novel genes linked with, EOC and to provide valid biological information for further research. The gene expression profiles of E-MTAB-3706 which contained four high-grade ovarian epithelial cancer samples, four normal fallopian tube samples and four normal ovarian epithelium samples were downloaded from the ArrayExpress database. Pathway enrichment and Gene Ontology (GO) enrichment analysis of differentially expressed genes (DEGs) were performed, and protein-protein interaction (PPI) network, microRNA-target gene regulatory network and TFs (transcription factors ) -target gene regulatory network for up- and down-regulated were analyzed using Cytoscape. In total, 552 DEGs were found, including 276 up-regulated and 276 down-regulated DEGs. Pathway enrichment analysis demonstrated that most DEGs were significantly enriched in chemical carcinogenesis, urea cycle, cell adhesion molecules and creatine biosynthesis. GO enrichment analysis showed that most DEGs were significantly enriched in translation, nucleosome, extracellular matrix organization and extracellular matrix. From protein-protein interaction network (PPI) analysis, modules, microRNA-target gene regulatory network and TFs-target gene regulatory network for up- and down-regulated, and the top hub genes such as E2F4, SRPK2, A2M, CDH1, MAP1LC3A, UCHL1, HLA-C (major histocompatibility complex, class I, C) , VAT1, ECM1 and SNRPN (small nuclear ribonucleoprotein polypeptide N) were associated in pathogenesis of EOC. The high expression levels of the hub genes such as CEBPD (CCAAT enhancer binding protein delta) and MID2 in stages 3 and 4 were validated in the TCGA (The Cancer Genome Atlas) database. CEBPD andMID2 were associated with the worst overall survival rates in EOC. In conclusion, the current study diagnosed DEGs between normal and EOC samples, which could improve our understanding of the molecular mechanisms in the progression of EOC. These new key biomarkers might be used as therapeutic targets for EOC.

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