scholarly journals Identification of LINC01503 as Biomarker Regulated by CTBP1 with Prognostic and Diagnostic Role in Epithelial Ovarian Cancer

2021 ◽  
Author(s):  
Yanchun Wang ◽  
Zheng Wei ◽  
Junping Zhang ◽  
Xuemei Wang ◽  
Xiaohua Li
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Underlying Mechanism ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
High Morbidity ◽  
Promote Cell Proliferation ◽  
Important Relationship

Abstract Background: Epithelial ovarian cancer (EOC) is a disease with high morbidity and mortality worldwide, which is seriously harmful to female health. LncRNA has an important relationship with the occurrence and development of tumors. Hence, the investigation of the underlying mechanism between LncRNA and EOC is of great importance.Results: In this study, we found that LINC01503 was highly expressed in EOC with a poor prognosis based on microarray datasets GSE119056 and GSE135886 obtained from Gene Expression Omnibus (GEO) database, and this result was verified by RT-qPCR. The database lncBase Predicted v.2 and starBase v2.0 were used to predict the targeted relationship of lncRNA-miRNA-mRNA, then the ceRNA network was established by Cytoscape software. Following, the expression and overall survival (OS) analysis of key lncRNAs were analyzed by GEPIA and Kaplan-Meier plotter database. Gene Ontology (GO) functional enrichment analysis was performed by DAVID database and enriched two cancer related biological processes (BP) that response to endoplasmic reticulum stress and IRE1-mediated unfolded protein. Moreover, we verified that LINC01503 was an oncogene regulated by C-terminal binding protein 1 (CTBP1) to promote cell proliferation, migration and inhibited cell apoptosis in ovarian cancer. Conclusion: In conclusion, these results identified LINC01503 as a potential gene for EOC diagnosis and prognosis.

Identification of MEG8-miR378d-SOBP Axis as a Novel Regulatory Network and Associated With Immune Infiltrates in Ovarian Carcinoma by Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Jian Lei ◽  
Zhen-Yu He ◽  
Jun Wang ◽  
Min Hu ◽  
Ping Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Human Protein Atlas

Abstract BackgroundTo investigate the potential molecular mechanism of ovarian cancer (OC) evolution and immunological correlation using the integrated bioinformatics analysis.MethodsData from the Gene Expression Omnibus (GEO) was used to gain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were completed by utilizing the Database for Annotation, Visualization, and Integrated Discovery (DAVID). After multiple validation via The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis 2 (GEPIA 2), the Human Protein Atlas (HPA) and Kaplan-Meier (KM) plotter, immune logical relationships of the key gene SOBP were evaluated based on Tumor Immune Estimation Resource (TIMER), and Gene Set Enrichment Analysis (GSEA) software. Finally, the lncRNAs-miRNAs-mRNAs sub-network was predicted by starBase, Targetscan, miRBD, and LncBase, individually. Correlation of expression and prognosis for mRNAs, miRNAs and lncRNAs were confirmed by TCGA, GEPIA 2, starBase, and KM.ResultsA total of 192 shared DEGs were discovered from the four data sets, including 125 upregulated and 67 downregulated genes. Functional enrichment analysis presented that they were mainly enriched in cartilage development, pathway in PI3K-Akt signaling pathway. Lower expression of SOBP was the independent prognostic factor for inferior prognosis in OC patients. Intriguingly, downregulated SOBP enhanced the infiltration levels of B cells, CD8+ T cells, Macrophage, Neutrophil and Dendritic cells. GSEA also disclosed low SOBP showed significantly association with the activation of various immune-related pathways. Finally, we firstly reported that MEG8-miR378d-SOBP axis was linked to development and prognosis of ovarian cancer through regulating cytokines pathway.Conclusions Our study establishes a novel MEG8-miR378d-SOBP axis in the development and prognosis of OC, and the triple sub-network probably affects the progression of ovarian tumor by regulating cytokines pathway.

scholarly journals Underlying Genes and Molecular Mechanism of Keloids Investigated by Integrated Bioinformatics Analysis

2021 ◽  
Author(s):  
chuying LI ◽  
Mei-Tong Jin ◽  
Yin-Li Luo ◽  
Zhe-Hu Jin ◽  
Long-Quan PI
Keyword(s):  
Expression Profiles ◽  
Normal Skin ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Underlying Mechanism ◽  
Cholinergic Receptor ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes

Abstract Background: We aimed to identify the overlapping differentially expressed genes (DEGs) of keloids distinguished from normal scar and normal skin and relevant underlying mechanism using integrated bioinformatics methods.Methods: The expression profiles of 18 keloid samples, 7 normal skin and 5 normal scar, were obtained from the GSE7890, GSE44270, GSE92566, and GSE3189 datasets in the Gene Expression Omnibus database. DEGs were identified using the LIMMA package in R. Gene ontology (GO) functional enrichment analysis was performed using the R software. A DEG-associated protein–protein interaction (PPI) network was constructed using STRING and MCODE was used for module analysis of the PPI network. Moreover, the hub genes were verified by qRT-PCR. The predicted DEGs, their regulatory miRNA and TF regulation network was analyzed using miRnet. Results: A total of 978 common DEGs were identified in the keloid samples. Genes with more than 45 interaction degrees, including neuropeptide Y (NPY), opioid receptor mu 1 (OPRM1), cholinergic receptor muscarinic 2 (CHRM2), and proopiomelanocortin (POMC), were found in the PPI network. Hsa-miR-335 and Sp1 as upstream-regulators regulated CHRM2, NPY, and POMC. Functional enrichment analysis revealed that hub genes were commonly enriched in the “G protein-coupled receptor signaling pathway” GO_BP termConclusion: Taken together, CHRM2, NPY, POMC, and OPRM1 potentially have crucial roles in keloid disease. Furthermore, miR-335 and Sp1 are potential targets for preventing keloid formation.

scholarly journals Identification of PKP 2/3 as potential biomarkers of ovarian cancer based on bioinformatics and experiments

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Lingling Gao ◽  
Xiao Li ◽  
Qian Guo ◽  
Xin Nie ◽  
Yingying Hao ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Signaling Pathway ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Biological Behavior ◽  
Cell Junction ◽  
Immune Infiltration ◽  
Potential Biomarker

Abstract Background Plakophilins (PKPs) are widely involved in gene transcription, translation, and signal transduction, playing a crucial role in tumorigenesis and progression. However, the function and potential mechanism of PKP1/2/3 in ovarian cancer (OC) remains unclear. It’s of great value to explore the expression and prognostic values of PKP1/2/3 and their potential mechanisms, immune infiltration in OC. Methods The expression levels, prognostic values and genetic variations of PKP1/2/3 in OC were explored by various bioinformatics tools and databases, and PKP2/3 were selected for further analyzing their regulation network and immune infiltration. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathways (KEGG) enrichment were also conducted. Finally, the expression and prognosis of PKP2 were validated by immunohistochemistry. Results The expression level and prognosis of PKP1 showed little significance in ovarian cancer, and the expression of PKP2/3 mRNA and protein were upregulated in OC, showing significant correlations with poor prognosis of OC. Functional enrichment analysis showed that PKP2/3 and their correlated genes were significantly enriched in adaptive immune response, cytokine receptor activity, organization of cell–cell junction and extracellular matrix; KEGG analysis showed that PKP2/3 and their significantly correlated genes were involved in signaling pathways including cytokine-mediated signaling pathway, receptor signaling pathway and pathways in cancer. Moreover, PKP2/3 were correlated with lymphocytes and immunomodulators. We confirmed that high expression of PKP2 was significantly associated with advanced stage, poor differentiation and poor prognosis of OC patients. Conclusion Members of plakophilins family showed various degrees of abnormal expressions and prognostic values in ovarian cancer. PKP2/3 played crucial roles in tumorigenesis, aggressiveness, malignant biological behavior and immune infiltration of OC, and can be regarded as potential biomarker for early diagnosis and prognosis evaluation in OC.

scholarly journals Differential co-expression network analysis for identification of functional modules in HIV infection and tubercolosis-HIV co-infection

2016 ◽  
Vol 89 (2) ◽  
Author(s):  
Mohit Jha ◽  
Anvita Gupta ◽  
Sudha Singh ◽  
Khushhali Menaria Pandey
Keyword(s):  
Network Analysis ◽  
Hiv Infection ◽  
Enrichment Analysis ◽  
Gene Interaction ◽  
Gene Clusters ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Specific Gene ◽  
Diagnostic Strategies

Co-infection with tuberculosis (TB) is the preeminent cause of demise in human immunodeficiency virus (HIV) infected individuals. However, diagnosis of TB, particularly in the presence of an HIV co-infection, can be limiting owing to the high inaccuracy associated with conventional diagnostic strategies. Here we determine dysregulated pathways in TB-HIV co-infection and HIV infection utilizing coexpression networks. Primarily, we utilized preservation statistics to identify gene modules that exhibit a weak conservation of network topology within HIV infected and TB-HIV co-infected networks. Raw data was downloaded from Gene Expression Omnibus (GSE50834) and duly pre-processed. Co-expression networks for each condition (HIV infected and TB-HIV co-infected) were constructed independently. Preservation of HIV infected network edges was evaluated with respect to TB-HIV co-infected and vice versa using weighted correlation network analysis. Two out of the 22 modules were identified as exhibiting weak preservation in both conditions. Functional enrichment analysis identified that weakly preserved modules were pertinent to the condition under study. For instance, weakly preserved TBHIV co-infected module T1 enriched for genes associated with mitochondrion exhibited the highest fraction of gene interaction pairs exclusive to TB-HIV co-infection. Concisely, we illustrated the application of using preservation statistics to detect modules functionally linked with dysregulated pathways in disease, as exemplified by the mitochondrion module T1. Our analyses discovered gene clusters that are non-randomly linked with the disease. Highly specific gene pairs pointed to interactions between known markers of disease and favoured identification of possible markers that are likely to be associated with the disease.

scholarly journals SPP1 is a Prognostic Related Biomarker and Correlated With Tumor-Infiltrating Immune Cells in Ovarian Cancer

2021 ◽  
Author(s):  
Wen Gao ◽  
Sheng Yin ◽  
Haiyan Sun ◽  
Zhuyan Shao ◽  
Peipei Shi ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
T Cells ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Vital Role ◽  
Functional Enrichment ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Secreted Phosphoprotein 1

Abstract Background: Secreted phosphoprotein 1 (SPP1) plays a vital role in tumor progression of some cancer types, but little is known whether it is a bystander or an actual player on driving immune infiltration in ovarian cancer.Methods: In this study, the expression of SPP1 was identified by Oncomine, GEPIA and TIMER databases, and SPP1 immumohistochemical staining analysis was assessed by The HPA database. The clinical outcomes between SPP1 expression and ovarian cancer patients were evaluated via Kaplan-Meier Plotter and PrognoScan dataset. Immune infiltration analyses were explored using TIMER and TISIDB dataset. In addition, Functional enrichment analyses were performed with Metascape and GeneMANIA database.Results: SPP1 was found overexpressed in ovarian tumor tissues and high SPP1 expression was correlated with shorter OS and PFS survivals. Particularly, elevated SPP1 expression was significantly associated with stage III ovarian cancer. Notably, SPP1 expression was positively correlated with infiltrating levels of CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells. Furthermore, SPP1 expression showed strong correlations with diverse immune hallmark sets in ovarian cancer. Of particular importance, functional enrichment analysis suggested that SPP1 strong related with immune response.Conclusions: These findings imply that SPP1 is correlated with prognosis and immune cell infiltrating, offering a new potential immunotherapeutic target in ovarian cancer.Trial registration: Not applicable.

scholarly journals Identification of novel potential biomarkers in hepatocarcinoma cancer; a transcriptome analysis

2021 ◽  
Author(s):  
Mohib kakar ◽  
Muhammad Mehboob ◽  
Muhammad Akram ◽  
Imran Iqbal ◽  
Hafza Ijaz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cancer Progression ◽  
Predictive Biomarkers ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Molecular Therapy ◽  
Hub Genes ◽  
Healthy Control

Abstract Objective The goal of this study was to understand possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis. Methods GEO contains datasets of gene expression, miRNA and methylation patterns of diseased and healthy/control patients. GSE62232 Dataset was selected by employing the server Gene Expression Omnibus. A total of 91 samples were collected, including 81 HCC samples and 10 healthy samples as control. GSE62232 was analyzed through GEO2R, and Functional Enrichment Analysis was performed to extract rational information from a set of DEGs. The Protein-Protein Relationship Networking search method has been used for extracting genes interacting. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analyzed using GEPIA to estimate the effect of their differential expression on cancer progression. Results We identified the top 10 hub genes through Cytohubba plugin. These genes include Cell Cycle Regulatory Cyclins and Cyclin-dependent proteins CCNA2, CCNB1 and CDK1. The pathogenesis and prognosis of HCC may be directly linked with the aforementioned genes. Conclusion In this analysis, we found critical genes for HCC that showed recommendations for more diagnostic and predictive biomarkers studies that could promote selective molecular therapy for HCC.

scholarly journals Molecular characterization of metabolic subtypes of gastric cancer based on metabolism-related lncRNA

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lingdi Li ◽  
Jianfei Ma
Keyword(s):  
Gastric Cancer ◽  
Metabolic Pathways ◽  
Metabolic Regulation ◽  
Protective Factor ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Underlying Mechanism ◽  
Functional Enrichment ◽  
Biological Processes

AbstractIncreasing evidence has demonstrated that lncRNAs are critical regulators in diverse biological processes, but the function of lncRNA in metabolic regulation remains largely unexplored. In this study, we evaluated the association between lncRNA and metabolic pathways and identified metabolism-related lncRNAs. Gastric cancer can be mainly subdivided into 2 clusters based on these metabolism-related lncRNA regulators. Comparative analysis shows that these subtypes are found to be highly consistent with previously identified subtypes based on other omics data. Functional enrichment analysis shows that they are enriched in distinct biological processes. Mutation analysis shows that ABCA13 is a protective factor in subtype C1 but a risk factor in C2. Analysis of chemotherapeutic and immunotherapeutic sensitivity shows that these subtypes tend to display distinct sensitivity to the same chemical drugs. In conclusion, these findings demonstrated the significance of lncRNA in metabolic regulation. These metabolism-related lncRNA regulators can improve our understanding of the underlying mechanism of lncRNAs and advance the research of immunotherapies in the clinical management of gastric cancer.

scholarly journals Bioinformatic Analysis: Screening and Identification of Differentially Expressed Genes Modified by m6A in Ovarian Cancer

2020 ◽  
Author(s):  
Huidong Liu ◽  
Wen-wen Zhang ◽  
Ge Lou
Keyword(s):  
Ovarian Cancer ◽  
Differentially Expressed Genes ◽  
Clinical Sample ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Kegg Pathways

Abstract Background: N6-methyladenosine(m6A) is one of the most common RNA modifications that occurs at the nitrogen-6 position of adenine. Emerging evidence has revealed that regulatory functions of m6A play an essential role in the development of cancer. However the study of m6A in ovarian cancer(OC) is still in our infancy. In this work ,we aimed to identify and analysis the differentially expressed genes(DEGs） modified by m6A which can provide new therapeutic targets and key biomarkers in OC.Methods: We downloaded Microarray datasets GSE146553 and GSE124766 from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by GEO2R analysis tools. Subsequently, The DAVID database was used to construct Enrichment analysis of GO and KEGG pathways. Next, the DEGs modified by m6A were identified by m6AVar database. Finally, the functional analysis and clinical sample validation of these genes were verified by ONCOMINE, GEPIA, cBioPortal online platform and Kaplan-Meier Plotter.Results:152 DEGs were selected ,and the DEGs were mainly enriched in extracellular exosome, spindle microtubule, response to hypoxia and cell cycle .And we identified 15 DEGs which were modified by m6A:MAPK10、MXRA5、CHD7、MECOM、SCN7A、GREB、PRUNE2、MX2、TOP2A、JAM2、DST、LAPTM5、CDKN2A、GATM and ANGPTL1. After statistical analysis, two DEGs (SCN7A and GAMT) were selected for detailed study. We revealed that SCN7A and GAMT were expressed at a low level in OC. Afterwards, Survival analysis showed that SCN7A and GAMT expression were correlated with OC overall survival. And the expression of SCN7A and GAMT mRNA decreasing in different TNM stages. Finally, we presumed that the modification of m6A spongs GAMT via EIF4A3 or FUS to participate in the occcurrence and the development of OC.Conclusion: Altogether, the current study identified and analysised the DEGs modified by m6A in OC. It will help us to investigate the underlying mechanism and progression of OC. In addition, it can provide new diagnostic markers and potential therapeutic targets in OC.

scholarly journals Identification of Novel Potential Biomarkers in Hepatocarcinoma Cancer; A Transcriptome Analysis

2021 ◽  
Author(s):  
Mohib kakar ◽  
Muhammad Mehboob ◽  
Muhammad Akram ◽  
Imran Iqbal ◽  
Hafza Ijaz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cancer Progression ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Predictive Biomarker ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Molecular Therapy ◽  
Hub Genes ◽  
Healthy Control

Abstract The goal of this study was to understand possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis. Gene Expression Omnibus (GEO) contains datasets of gene expression, miRNA and methylation patterns of diseased and healthy/control patients. GSE62232 Dataset was selected by employing the server GEO. A total of 91 samples were collected, including 81 HCC samples and 10 healthy samples as control. GSE62232 was analyzed through GEO2R, and functional enrichment analysis was performed to extract rational information from a set of DEGs. The protein-protein relationship networking search method was used for extracting interacting genes. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analyzed using GEPIA to estimate the effect of their differential expression on cancer progression. We identified the top 10 hub genes through Cytohubba plugin. These genes include cell cycle regulatory cyclins and cyclin-dependent proteins CCNA2, CCNB1 and CDK1. The pathogenesis and prognosis of HCC may be directly linked with the aforementioned genes. In this analysis, we found critical genes for HCC that showed recommendations for more diagnostic and predictive biomarker studies that could promote selective molecular therapy for HCC.

scholarly journals Comprehensive Analysis of Lysine Crotonylation Modification in Patients with Chronic Renal Failure

2021 ◽  
Author(s):  
Jiahuang Huang ◽  
Donge Tang ◽  
Fengping Zheng ◽  
Huixuan Xu ◽  
Yong Dai
Keyword(s):  
Renal Failure ◽  
Chronic Renal Failure ◽  
Affinity Purification ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Post Translational Modifications ◽  
Lysine Modification ◽  
Important Relationship ◽  
Liquid Chromatography Tandem Mass

Abstract Background： Post-translational modifications (PTMs) are at the heart of many cellular signaling events, which changes the function of protein. Crotonylation, one of the most important and common PTMs, plays a key role in the regulation of various biological processes. However, no study has evaluated the role of lysine crotonylation modification and chronic renal failure patients. Methods: Here, we comparatively evaluated the crotonylation proteome of normal controls and chronic renal failure patients using liquid chromatography tandem mass spectrometry (LC-MS/MS) coupled with highly sensitive immune-affinity purification.Results: A total of 1109 lysine modification sites were identified, of which 772 sites were up-regulated and 69 sites were down-regulated; this suggests that crotonylation modification maintains high levels in the patients’ kidneys with chronic renal failure. Gene ontology enrichment analysis showed that the crotonylated proteins were significantly enriched in the platelet alpha granule lumen, platelet degradulation, and cell adhesion molecule binding. In addition, KEGG-based gene and genomic functional enrichment analysis in Kyoto encyclopedia showed that battoacyl protein was enriched in CD36, which has an important relationship with renal failure.Conclusion: This is the first report on the global crotonylation proteome of chronic renal failure patients. crotonylation of histone and non-histone may play an important role in delaying the continuous deterioration of renal function in patients with chronic renal failure.

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