scholarly journals Systemic Analysis of the DNA Replication Regulator MCM Complex in Ovarian Cancer and Its Prognostic Value

2021 ◽  
Vol 11 ◽  
Author(s):  
Yukun Li ◽  
Juan Zou ◽  
Qunfeng Zhang ◽  
Feifei Quan ◽  
Lu Cao ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Protein Structure ◽  
Dna Replication ◽  
Prognostic Value ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Multiple Cancer ◽  
Protein Levels ◽  
Network Analyses ◽  
Mcm Complex

Microliposome maintenance (MCM) 2, MCM3, MCM4, MCM5, MCM6, and MCM7 are DNA replication regulators and are involved in the progression of multiple cancer types, but their role in ovarian cancer is still unclear. The purpose of this study is to clarify the biological function and prognostic value of the MCM complex in ovarian cancer (OS) progression. We analyzed DNA alterations, mRNA and protein levels, protein structure, PPI network, functional enrichment, and prognostic value in OC based on the Oncomine, cBioPortal, TCGA, CPTAC, PDB, GeneMANIA, DAVID, KEGG, and GSCALite databases. The results indicated that the protein levels of these DNA replication regulators were increased significantly. Moreover, survival analysis showed a prognostic signature based on the MCM complex, which performed moderately well in terms of OS prognostic prediction. Additionally, protein structure, functional enrichment, and PPI network analyses indicated that the MCM complex synergistically promoted OC progression by accelerating DNA replication and the cell cycle. In conclusion, our study suggested that the MCM complex might be a potential target and prognostic marker for OC patients.

scholarly journals Systemic Analysis of the Dna Replication Regulators Origin Recognition Complex in Lung Adenocarcinomas Identifies Prognostic and Expression Significance

2021 ◽  
Author(s):  
Yun-bo Deng ◽  
Juan Chen ◽  
Xian-yu Luo ◽  
Tian Zeng ◽  
Dong-mei Ye ◽  
...  
Keyword(s):  
Protein Structure ◽  
Dna Replication ◽  
Origin Recognition Complex ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Immune Infiltration ◽  
Systemic Analysis ◽  
Lung Adenocarcinomas ◽  
Replication Initiator ◽  
Origin Recognition

Abstract Background: Origin recognition complex (ORC) 1, ORC2, ORC3, ORC4, ORC5 and ORC6, form a replication-initiator complex to mediate DNA replication, which play a key role in carcinogenesis, while their role in lung adenocarcinomas (LUAD) remains poorly understood.Methods: We confirmed the transcriptional and post-transcriptional levels, DNA alteration, DNA methylation, miRNA network, protein structure, PPI network, functional enrichment, immune infiltration and prognostic value of ORCs in LUAD based on Oncomine, GEPIA, HPA, cBioportal, TCGA, GeneMANIA, Metascape, KM-plot, GENT2, and TIMER database. Results: ORC mRNA and protein were both enhanced obviously based on Oncomine, Ualcan, GEPIA, TCGA and HPA database. Furthermore, ORC1 and ORC6 have significant prognostic values for LUAD patients based on GEPIA database. Protein structure, PPI network, functional enrichment and immune infiltration analysis indicated that ORC complex cooperatively accelerate the LUAD development by promoting DNA replication, cellular senescence and metabolic process. Conclusion: the ORC complex has an important prognostic and expression significance for LUAD patients.

scholarly journals Systemic Analysis of the DNA Replication Regulators Origin Recognition Complex in Lung Adenocarcinomas Identifies Prognostic and Expression Significance

2021 ◽  
Author(s):  
Juan Chen ◽  
Juan Zou ◽  
Juan Zeng ◽  
Tian Zeng ◽  
Qi-hao Hu ◽  
...  
Keyword(s):  
Protein Structure ◽  
Dna Replication ◽  
Origin Recognition Complex ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Immune Infiltration ◽  
Systemic Analysis ◽  
Lung Adenocarcinomas ◽  
Replication Initiator ◽  
Origin Recognition

Abstract Background: Origin recognition complex (ORC) 1, ORC2, ORC3, ORC4, ORC5 and ORC6, form a replication-initiator complex to mediate DNA replication, which play a key role in carcinogenesis, while their role in lung adenocarcinomas (LUAD) remains poorly understood.Methods: We confirmed the transcriptional and post-transcriptional levels, DNA alteration, DNA methylation, miRNA network, protein structure, PPI network, functional enrichment, immune infiltration and prognostic value of ORCs in LUAD based on Oncomine, GEPIA, HPA, cBioportal, TCGA, GeneMANIA, Metascape, KM-plot, GENT2, and TIMER database. Results: ORC mRNA and protein were both enhanced obviously based on Oncomine, Ualcan, GEPIA, TCGA and HPA database. Furthermore, ORC1 and ORC6 have significant prognostic values for LUAD patients based on GEPIA database. Protein structure, PPI network, functional enrichment and immune infiltration analysis indicated that ORC complex cooperatively accelerate the LUAD development by promoting DNA replication, cellular senescence and metabolic process. Conclusion: the ORC complex has an important prognostic and expression significance for LUAD patients.

scholarly journals Identifcation of The Ferroptosis-Related Gene Signature In Placenta of Patients With Early-Onset Preeclampsia

2021 ◽  
Author(s):  
Nana Yang ◽  
Qianghua Wang ◽  
Biao Ding ◽  
Yinging Gong ◽  
Yue Wu ◽  
...  
Keyword(s):  
Iron Homeostasis ◽  
Molecular Mechanisms ◽  
Late Onset ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Network Analyses

Abstract Background: The accumulation of ROS resulting from upregulated levels of oxidative stress is commonly implicated in preeclampsia (PE). Ferroptosis is a novel form of iron-dependent cell death instigated by lipid peroxidation likely plays important role in PE pathogenesis. This study aims to investigate expression profiles and functions of the ferroptosis-related genes (FRGs) in early- and late-onset preeclampsia.Methods: The gene expression data and clinical information were downloaded from GEO database. The “limma” R package was used for screening differentially expressed genes. GO(Gene Ontology), Kyoto Encyclopedia of Genes and Genomes(KEGG) and protein protein interaction (PPI) network analyses were conducted to investigate the bioinformatics functions and molecular interactions of significantly different FRGs. Quantitative real-time reverse transcriptase PCR was used to verify the expression of hub FRGs in PE.Results: A total number of 4,215 DEGs were identified between EOPE and preterm cases and 3,356 DEGs were found between EOPE and LOPE subtypes. 20 significantly different FRGs were identified in EOPE, while only 3 in LOPE. Functional enrichment analysis revealed that the differentially expressed FRGs was mainly involved in EOPE and enriched in hypoxia- and iron-related pathways, such as response to hypoxia, iron homeostasis and iron ion binding process. The PPI network analysis and verification by RT-qPCR resulted in the identification of the following six interesting FRGs: FTH1, HIF1A, FTL, IREB2, MAPK8 and PLIN2. Conclusions: EOPE and LOPE owned distinct underlying molecular mechanisms and ferroptosis may be mainly implicated in pathogenesis of EOPE. Further studies are necessary for deeper inquiry into placental ferroptosis and its role in the pathogenesis of EOPE.

Increased Expression of Dachshund Homolog 1 in Ovarian Cancer as a Predictor for Poor Outcome

2012 ◽  
Vol 22 (3) ◽  
pp. 386-393 ◽  
Author(s):  
Fei Liang ◽  
Qingtao Lü ◽  
Shuyu Sun ◽  
Jie Zhou ◽  
Vladimir M. Popov ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Estrogen Receptor ◽  
Immunohistochemical Staining ◽  
Normal Tissue ◽  
Prognostic Value ◽  
Functional Relationship ◽  
Estrogen Receptor Α ◽  
Cancer Growth ◽  
Protein Levels

ObjectiveThis study aimed to determine the functional relationship between the levels of dachshund homolog 1 (DACH1) expression and different subtypes of ovarian cancer and to investigate the possible prognostic value of DACH1 in ovarian cancer.MethodsImmunohistochemical staining was deployed to determine the protein levels of DACH1. Staining was performed on patient samples, for whom the detailed follow-up data have been acquired during the last 10 years. Normal, benign, borderline, cancer, and metastatic ovarian cancer samples were included in this study.ResultsThe results of our study show that DACH1 protein levels increase with the invasiveness of the ovarian cancer. As the cancer progresses from benign and borderline to metastatic, DACH1 protein expression increases as well. Moreover, with the increase in expression, the subcellular distribution of DACH1 changes from nucleus in normal tissue to cytoplasm in cancer. Finally, DACH1 expression levels were compared with estrogen receptor α (ERα) levels, and the results showed that overall DACH1 levels were higher, whereas also DACH1 exhibited increased cytoplasmic expression in ERα-positive ovarian cancer samples.ConclusionsThese results indicate that DACH1 is highly expressed in metastatic ovarian cancer compared with that of normal, benign, and borderline ovarian tissues and that it could play an important role in cancer growth.

Identification Of Putative Gene Signatures Associated With Diagnosis And Prognosis Of Breast Cancer

2021 ◽  
Vol 44 (3) ◽  
pp. E45-54
Author(s):  
Chao Tan ◽  
Fang Zuo ◽  
Mingqian Lu ◽  
Sai Chen ◽  
Zhenzhen Tian ◽  
...  
Keyword(s):  
Risk Model ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Support Vector ◽  
Ppi Network ◽  
Hub Genes ◽  
Putative Gene ◽  
Network Analyses ◽  
Cluster 2

Purpose: This study aimed to identify potential diagnostic and therapeutic biomakers for the development ofbreast cancer (BC). Methods: GSE86374 dataset containing 159 samples was acquired from the Gene Expression Omnibus (GEO) database followed by differentially expressed genes (DEGs) identification and cluster analysis. Corresponding functional enrichment and protein-protein interaction (PPI) network analyses were performed to identify hub genes. Prognostic evaluation using clinical information obtained from TCGA database and hub genes was conducted to screen for crucial indicators for BC progression. The risk model was established and validated. Results: In total, 186 DEGs were identified and grouped into four clusters: 96 in cluster 1; 69 in cluster 2; 16 in  cluster 3; and 5 in cluster 4. Functional enrichment analysis showed that DEGs, including ADH1B in cluster 1,  were dramatically enriched in the tyrosine and drug metabolism pathways, while genes in cluster 2, including  SPP1 and RRM2, played crucial roles in PI3K-Akt and p53 signalling pathway. SPP1 and RRM2 served as hub  genes in the PPI network, resulting in an support vector machine classifier with good accuracy and specificity.Ad ditionally, the results of prognostic analysis suggest that age, metastasis stage, SPP1 and ADH1B were correlated with risk of BC, which was validated by using the established risk model analysis. Conclusion: SPP1, RRM2 and ADH1B appear to play vital roles in the development of BC. Age and TNM stage  were also preferentially associated with risk of developing BC. Evaluation of the risk model based on larger sample size and further experimental validation are required.

scholarly journals Identification of potential crucial genes and pathways associated with vein graft restenosis based on gene expression analysis in experimental rabbits

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4704 ◽  
Author(s):  
Qiang Liu ◽  
Xiujie Yin ◽  
Mingzhu Li ◽  
Li Wan ◽  
Liqiao Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Vein Graft ◽  
Molecular Mechanisms ◽  
Rapid Development ◽  
Bypass Graft ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Network Analyses

Occlusive artery disease (CAD) is the leading cause of death worldwide. Bypass graft surgery remains the most prevalently performed treatment for occlusive arterial disease, and veins are the most frequently used conduits for surgical revascularization. However, the clinical efficacy of bypass graft surgery is highly affected by the long-term potency rates of vein grafts, and no optimal treatments are available for the prevention of vein graft restenosis (VGR) at present. Hence, there is an urgent need to improve our understanding of the molecular mechanisms involved in mediating VGR. The past decade has seen the rapid development of genomic technologies, such as genome sequencing and microarray technologies, which will provide novel insights into potential molecular mechanisms involved in the VGR program. Ironically, high throughput data associated with VGR are extremely scarce. The main goal of the current study was to explore potential crucial genes and pathways associated with VGR and to provide valid biological information for further investigation of VGR. A comprehensive bioinformatics analysis was performed using high throughput gene expression data. Differentially expressed genes (DEGs) were identified using the R and Bioconductor packages. After functional enrichment analysis of the DEGs, protein–protein interaction (PPI) network and sub-PPI network analyses were performed. Finally, nine potential hub genes and fourteen pathways were identified. These hub genes may interact with each other and regulate the VGR program by modulating the cell cycle pathway. Future studies focusing on revealing the specific cellular and molecular mechanisms of these key genes and pathways involved in regulating the VGR program may provide novel therapeutic targets for VGR inhibition.

scholarly journals Screening of Hub Genes Associated with Pulmonary Arterial Hypertension by Integrated Bioinformatic Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yu Zeng ◽  
Nanhong Li ◽  
Zhenzhen Zheng ◽  
Riken Chen ◽  
Min Peng ◽  
...  
Keyword(s):  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
Drug Targets ◽  
Bioinformatic Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Hub Genes ◽  
Network Analyses ◽  
Pulmonary Arterial

Background. Pulmonary arterial hypertension (PAH) is a disease or pathophysiological syndrome which has a low survival rate with abnormally elevated pulmonary artery pressure caused by known or unknown reasons. In addition, the pathogenesis of PAH is not fully understood. Therefore, it has become an urgent matter to search for clinical molecular markers of PAH, study the pathogenesis of PAH, and contribute to the development of new science-based PAH diagnosis and targeted treatment methods. Methods. In this study, the Gene Expression Omnibus (GEO) database was used to downloaded a microarray dataset about PAH, and the differentially expressed genes (DEGs) between PAH and normal control were screened out. Moreover, we performed the functional enrichment analyses and protein-protein interaction (PPI) network analyses of the DEGs. In addition, the prediction of miRNA and transcriptional factor (TF) of hub genes and construction miRNA-TF-hub gene network were performed. Besides, the ROC curve was used to evaluate the diagnostic value of hub genes. Finally, the potential drug targets for the 5 identified hub genes were screened out. Results. 69 DEGs were identified between PAH samples and normal samples. GO and KEGG pathway analyses revealed that these DEGs were mostly enriched in the inflammatory response and cytokine-cytokine receptor interaction, respectively. The miRNA-hub genes network was conducted subsequently with 131 miRNAs, 7 TFs, and 5 hub genes (CCL5, CXCL12, VCAM1, CXCR1, and SPP1) which screened out via constructing the PPI network. 17 drugs interacted with 5 hub genes were identified. Conclusions. Through bioinformatic analysis of microarray data sets, 5 hub genes (CCL5, CXCL12, VCAM1, CXCR1, and SPP1) were identified from DEGs between control samples and PAH samples. Studies showed that the five hub genes might play an important role in the development of PAH. These 5 hub genes might be potential biomarkers for diagnosis or targets for the treatment of PAH. In addition, our work also indicated that paying more attention on studies based on these 5 hub genes might help to understand the molecular mechanism of the development of PAH.

scholarly journals Data Mining of Prognostic Microenvironment-Related Genes in Clear Cell Renal Cell Carcinoma: A Study with TCGA Database

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Bin Chen ◽  
Wei Chen ◽  
Jing Jin ◽  
Xueping Wang ◽  
Yifang Cao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Value ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Cancer Prognosis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent kidney malignancies. The tumor microenvironment (TME) is highly related to the oncogenesis, progress, and prognosis of ccRCC. The aim of this study was to infer the level of infiltrating stromal and immune cells and assess the prognostic value of them. The gene expression profile was obtained from TCGA and used for calculating the stromal and immune scores. Based on a cut-off value, patients were divided into low- and high-stromal/immune score groups. Survival analysis was performed to evaluate the prognostic value of stromal and immune scores. Moreover, differentially expressed genes (DEGs) that are highly related to TME were determined and applied for functional enrichment analysis and protein-protein interaction (PPI) network. The Kaplan-Meier plot demonstrated that patients with high-immune scores and stromal scores had poorer clinical outcome. In addition, a total of 89 DEGs were identified and mainly involved in 5 pathways. The top 5 degree genes were extracted from the PPI network; among them, IL10 and XCR1 were highly associated with prognosis of ccRCC. The results of the present study demonstrated that ESTIMATE algorithm-based stromal and immune scores may be a credible indicator of cancer prognosis and IL10 along with XCR1 may be a potential key regulator for the TME of ccRCC.

The protein-protein interaction network of intestinal gastric cancer patients reveals hub proteins with potential prognostic value

2021 ◽  
pp. 1-14
Author(s):  
Everton Cruz Santos ◽  
Renata Binato Gomes ◽  
Priscila Valverde Fernandes ◽  
Maria Aparecida Ferreira ◽  
Eliana Saul Furquim Werneck Abdelhay
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Prognostic Value ◽  
Protein Profile ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Label Free ◽  
Ppi Network ◽  
Tissue Samples ◽  
Hub Proteins

BACKGROUND: Gastric cancer (GC) is the third leading cause of cancer worldwide. According to the Lauren classification, gastric adenocarcinoma is divided into two subtypes: diffuse and intestinal. The development of intestinal gastric cancer (IGC) can take years and involves multiple factors. OBJECTIVE: To investigate the protein profile of tumor samples from patients with IGC in comparison with adjacent nontumor tissue samples. METHODS: We used label-free nano-LC-MS/MS to identify proteins from the tissues samples. The results were analyzed using MetaCore™ software to access functional enrichment information. Protein-protein interactions (PPI) were predicted using STRING analysis. Hub proteins were determined using the Cytoscape plugin, CytoHubba. Survival analysis was performed using KM plotter. We identified 429 differentially expressed proteins whose pathways and processes were related to protein folding, apoptosis, and immune response. RESULTS: The PPI network of these proteins showed enrichment modules related to the regulation of cell death, immune system, neutrophil degranulation, metabolism of RNA and chromatin DNA binding. From the PPI network, we identified 20 differentially expressed hub proteins, and assessed the prognostic value of the expression of genes that encode them. Among them, the expression of four hub genes was significantly associated with the overall survival of IGC patients. CONCLUSIONS: This study reveals important findings that affect IGC development based on specific biological alterations in IGC patients. Bioinformatics analysis showed that the pathogenesis of IGC patients is complex and involves different interconnected biological processes. These findings may be useful in research on new targets to develop novel therapies to improve the overall survival of patients with IGC.

scholarly journals Identification of Core Predication-Related Candidate Genes in Ovarian Cancer Based on Integrated Bioinformatics and Experienment

2021 ◽  
Author(s):  
Jiaqing Bi ◽  
Qian Qin ◽  
Huihan Ma ◽  
Meijie Ma ◽  
Qinmei Feng
Keyword(s):  
Ovarian Cancer ◽  
Survival Analysis ◽  
Early Diagnosis ◽  
Correlation Analysis ◽  
Candidate Genes ◽  
Functional Enrichment ◽  
Biological Behavior ◽  
Clinical Staging ◽  
Ppi Network ◽  
Joint Monitoring

Abstract Background: Ovarian cancer is one of the deadliest and most common gynecological malignancies. This study aims to use comprehensive bioinformatics analysis to try to identify the core candidate genes related to the prediction of ovarian cancer for the early diagnosis and prognosis of ovarian cancer. Methods: Obtain expression profiles from Gene Expression Omnibus database, identify differentially expressed genes (DEG) with p<0.05 and (logFC)>1.5, perform functional enrichment, protein-protein interaction (PPI) network construction, functional module analysis, and survival analysis And correlation analysis to obtain the target gene, through immunohistochemical staining, clinicopathological feature analysis to verify the expression and clinical significance of TTK.Results: 1. Identified 135 genes with the same expression. 33 up-regulated DEG were mainly enriched in mitotic spindle assembly checkpoints, chromosome segregation regulation, etc.; 102 down-regulated DEG was mainly enriched in neurotransmitter level regulation, protein serine/threonine Regulation of acid kinase activity, etc. Then the PPI network was constructed to screen 20 hub genes and perform survival analysis and expression correlation analysis. At the same time, the modules that met the requirements were screened and the genes were analyzed by pathway enrichment. It was found that TTK was highly expressed in ovarian cancer and led to a poor prognosis.2. Distant metastasis, lymph node metastasis, clinical staging (stage III-IV), and poor differentiation are independent risk factors for high TTK expression (P<0.05).3. TTK, CA125, HE4 three biological indicators show excellent diagnostic value in joint monitoring of ovarian cancer.Conclusions: TTK plays a vital role in the tumorigenesis, aggressiveness and malignant biological behavior of EOC, and can be used as a potential biomarker and potential therapeutic target for early diagnosis and predictive evaluation of EOC.

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