Clinical Significance And Potential Mechanisms of The RNA Methyltransferase KIAA1429 In Osteosarcoma

Abstract Background: KIAA1429, a member of the RNA methyltransferase complex, is involved in cancer progression. However, the clinical significance of KIAA1429 in osteosarcoma (OS) and the underlying mechanisms by which it contributes to disease progression remain unclear. Methods: The clinical significance of KIAA1429 in OS was evaluated based on the RT-qPCR, microarray, RNA sequencing, and published data. Two lentivirus-mediated KIAA1429-targeting siRNA constructs were transfected into SW1353 cells, and CCK-8 and flow cytometry assays were applied to investigate the biological function of KIAA1429 in OS cells. KIAA1429-related genes in OS were identified from lists of co-expressed genes (CEGs) and differentially expressed genes (DEGs). Functional enrichment analysis was employed to explore the potential mechanisms by which KIAA1429 contributes to the progression of OS.Results: The mRNA expression of KIAA1429 was notably overexpressed in 250 OS samples than 71 non-cancer samples (SMD=0.74). SROC curve analysis showed that KIAA1429 exhibits diagnostic capacity between OS samples and non-cancer samples (AUC=0.83). Survival analysis showed that overexpression of KIAA1429 was associated with shorter overall survival time. Knocking down KIAA1429 reduced the level of m6A methylation, inhibited proliferation, and accelerated apoptosis in OS cells. A total of 395 KIAA1429-related genes were identified, and were enriched in the cell cycle pathway. Protein–protein interaction (PPI) network analysis showed that CDK1, CCNA2, and CCNB1 were KIAA1429-related genes that act as major network hubs in OS. Conclusion: KIAA1429 plays an oncogenic role in OS and may facilitate the progression of OS through a mechanism involving the regulation of CDK1, CCNA2, and CCNB1.

Download Full-text

Proteomic Analysis of the Secretome and Exosomes of Feline Adipose-Derived Mesenchymal Stem Cells

Animals ◽

10.3390/ani11020295 ◽

2021 ◽

Vol 11 (2) ◽

pp. 295

Author(s):

Antonio J. Villatoro ◽

María del Carmen Martín-Astorga ◽

Cristina Alcoholado ◽

María del Mar Sánchez-Martín ◽

José Becerra

Keyword(s):

Stem Cells ◽

Mesenchymal Stem Cells ◽

Endocrine System ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Cell Junctions ◽

Bioactive Molecules ◽

Protein Protein Interaction ◽

Cell Signaling Pathways

Mesenchymal stem cells (MSCs) have been shown to have therapeutic efficacy in different complex pathologies in feline species. This effect is attributed to the secretion of a wide variety of bioactive molecules and extracellular vesicles, such as exosomes, with significant paracrine activity, encompassed under the concept of the secretome. However, at present, the exosomes from feline MSCs have not yet been studied in detail. The objective of this study is to analyze and compare the protein profiles of the secretome as a whole and its exosomal fraction from feline adipose-derived MSCs (fAd-MSCs). For this, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Protein–Protein Interaction Networks Functional Enrichment Analysis (STRING) were utilized. A total of 239 proteins were identified in the secretome, and 228 proteins specific to exosomes were identified, with a total of 133 common proteins. The proteins identified in the secretome were located in the extracellular regions and in the cytoplasm, while the exosomal proteins were located mainly in the membrane, cytoplasm and cytosol. Regarding function, in the secretome, proteins involved in different metabolic pathways, in pathways related to the immune system and the endocrine system and in the processing of proteins in the endoplasmic reticulum predominated. In contrast, proteins specific to exosomes were predominantly associated with endocytosis, cell junctions, platelet activation and other cell signaling pathways. The possible future use of the secretome, or some of its components, such as exosomes, would provide a non-cell-based therapeutic strategy for the treatment of different diseases that would avoid the drawbacks of cell therapy.

Download Full-text

Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

10.7287/peerj.preprints.27586v1 ◽

2019 ◽

Author(s):

Yunze Liu ◽

Xiaojie Sun ◽

Aijun Qu

Keyword(s):

Drosophila Melanogaster ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Protein Protein Interaction ◽

Neuronal Remodeling ◽

Gene Modules

As an evolutionarily conserved mechanism, developmental neuronal remodeling is needed for the proper wiring of the nervous system and is critical for understanding the neurodevelopment mechanisms. Previous studies have shown that during metamorphosis lots of Drosophila melanogaster mushroom body neurons experience stereotypic remodeling. However, the related regulators and downstream executors of pathways are yet unclear, especially studies of transcriptional gene co-expression analysis of nervous systems remain insufficient. In this study, we develop a weighted gene co-expression network (WGCNA) to classify gene modules associated with neuronal remodeling. Moreover, functional and pathway enrichment analysis with protein-protein network construction is applied to detect high informative hub genes in the targeted gene module. Thus, we select a total of five hub genes that play critical roles in neuronal remodeling and identify them with functional enrichment analysis and protein-protein interaction network. Overall, this study provides insight into the underlying molecular mechanism of developmental neuronal remodeling in Drosophila melanogaster.

Download Full-text

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

10.21203/rs.3.rs-154350/v3 ◽

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.

Download Full-text

Apolipoprotein B Is Associated With the Microenvironment of Cholangiocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.654689 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xiaofeng Xu ◽

Diyu Chen ◽

Xiaode Feng ◽

Jiating Hu ◽

Jiangzhen Ge ◽

...

Keyword(s):

Immune Cells ◽

Apolipoprotein B ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Abundance Ratio ◽

Functional Enrichment ◽

Score System ◽

Protein Protein Interaction ◽

New Ideas ◽

Differential Expressed Genes

BackgroundCholangiocarcinoma (CCA) is a kind of devastating malignancy, which is correlated with the extremely high mortality. Due to the occult pathogenesis of CCA, most patients are diagnosed in the advanced stage. However, the efficacy of chemotherapy and immunotherapy is limited for these patients. The cause for this phenomenon is unclear, the recent researches indicate that it could be related to predisposing genetic factors and tumor microenvironment (TME) changes. The TME is created by the tumor and dominated by tumor-induced interactions. And the tumor prognosis could be influenced by the extent of infiltrating immune cells and stromal cells in TME.Materials and methodsThe abundance ratio of immune cells for each sample was obtained via the CIBERSORT algorithm, and we used ESTIMATE score system to calculate the immune and stromal scores in CCA. The CCA cases in TCGA database were categorized into high and low score groups according to their immune/stromal scores. And then, we identified the differential expressed genes (DEGs) in two groups. Functional enrichment analysis and protein‐protein interaction networks were carried out for DEGs. Interestingly, we found out that apolipoprotein B (APOB) is the most down-regulated among these genes. Then we performed the immunohistochemistry staining of APOB in a CCA tumor microarray which contained 100 CCA cases, APOB was down-regulated in CCA samples. Thus, we evaluated the APOB function in the TME of CCA through TIMER.Results and ConclusionThe results demonstrate that the infiltration degree of immune cells in CCA could be influenced by the expression of APOB, and the APOB expression could be mediated by DNA methylation. Our study not only indicates APOB is a potential target for CCA immunotherapy but also provides new ideas for researchers to explore the immunotherapy of various tumors.

Download Full-text

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

10.21203/rs.3.rs-154350/v1 ◽

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.

Download Full-text

Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

10.7287/peerj.preprints.27586 ◽

2019 ◽

Author(s):

Yunze Liu ◽

Xiaojie Sun ◽

Aijun Qu

Keyword(s):

Drosophila Melanogaster ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Protein Protein Interaction ◽

Neuronal Remodeling ◽

Gene Modules

As an evolutionarily conserved mechanism, developmental neuronal remodeling is needed for the proper wiring of the nervous system and is critical for understanding the neurodevelopment mechanisms. Previous studies have shown that during metamorphosis lots of Drosophila melanogaster mushroom body neurons experience stereotypic remodeling. However, the related regulators and downstream executors of pathways are yet unclear, especially studies of transcriptional gene co-expression analysis of nervous systems remain insufficient. In this study, we develop a weighted gene co-expression network (WGCNA) to classify gene modules associated with neuronal remodeling. Moreover, functional and pathway enrichment analysis with protein-protein network construction is applied to detect high informative hub genes in the targeted gene module. Thus, we select a total of five hub genes that play critical roles in neuronal remodeling and identify them with functional enrichment analysis and protein-protein interaction network. Overall, this study provides insight into the underlying molecular mechanism of developmental neuronal remodeling in Drosophila melanogaster.

Download Full-text

Identification of associated molecular events in Helicobacter pylori infection and gastric cancer through integrated computational analysis of Microarray and RNA-Seq datasets

10.21203/rs.3.rs-1189424/v1 ◽

2021 ◽

Author(s):

Sabaoon Zeb ◽

Rehan Zafar Paracha ◽

Maryum Nisar ◽

Rimsha Khalid ◽

Zartasha Mustansar ◽

...

Keyword(s):

Gastric Cancer ◽

Helicobacter Pylori ◽

Cancer Progression ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

World Health ◽

Separate Analysis ◽

Rna Seq ◽

Molecular Events

Abstract According to the World Health Organization, Gastric cancer (GC) is the third leading cause of death worldwide, where, the major precursor of cancer progression is infection with Helicobacter pylori. It has been reported that 50% of the total populace is infected with H.pylori, while in 80% the ulcer emerges in later stages of the infection. Although extensive separate analysis has been performed on H.pylori infection and GC data, however, there is a need to perform comparative analysis to identify the cross-talk between the conditions and to hunt significant molecular events that occurs during H.pylori induced GC. The aim of this multi-population study was to identify common molecular events and potential bio-markers against H.pylori induced GC. We performed microarray and RNA-seq analysis on publicly available H.pylori infection, gastritis, H.pylori induced GC and GC datasets to obtain Differentially Expressed Genes (DEGs). After obtaining the DEGs, integrative analysis, functional enrichment analysis and network biology approaches were utilized to identify common markers and hub genes between various disease conditions. Functional enrichment analysis revealed the DEGs of H.pylori infection, gastritis, H.pylori induced GC and GC were strongly associated with spliceosome, adherens junction, focal adhesion and ribosome. Being one of the common DEG, and highly interactive hub protein in the networks of all the conditions, translationally controlled tumour protein (TPT1) was identified as a significant predictive biomarker for early prognosis and diagnosis of H.pylori induced GC. Therefore, the mechanisms behind TPT1 should be further studied using in vitro cell-based functional assays, to determine its role in the progression of H.pylori induced GC.

Download Full-text

Gene Clusters Based on OLIG2 and CD276 Could Distinguish Molecular Profiling in Glioblastoma

10.21203/rs.3.rs-599543/v1 ◽

2021 ◽

Author(s):

Minjie Fu ◽

Jinsen Zhang ◽

Weifeng Li ◽

Shan He ◽

Jingwen Zhang ◽

...

Keyword(s):

Gene Cluster ◽

Efficient Method ◽

Enrichment Analysis ◽

Gene Clusters ◽

Functional Enrichment Analysis ◽

Molecular Classification ◽

Functional Enrichment ◽

Protein Protein Interaction ◽

Dna Elements

Abstract BackgroundThe molecular classification of glioblastoma (GBM) based on transcriptomic analysis could provide precise treatment and prognosis. However, current subtyping (Classic, Mesenchymal, Neural, Proneural) is a time-consuming and cost-intensive process, which hinders its clinical application. A simple and efficient method for classification was imperative.MethodsRandom forest algorithm was applied to conduct a gene cluster featured with hub genes, OLIG2 and CD276. Functional enrichment analysis and Protein-protein interaction were performed using the genes in this gene cluster. The classification efficiency of the gene cluster was validated by WGCNA and LASSO algorithms, and tested in GSE84010 and Gravandeel’s GBM datasets. ResultsThe gene cluster (n = 26) could distinguish mesenchymal and proneural excellently (AUC = 0.92), which could be validated by multiple algorithms (WGCNA, LASSO) and datasets (GSE84010 and Gravandeel’s GBM dataset). The gene cluster could be functionally enriched in DNA elements and T cell associated pathways. Additionally, five genes in the signature could predict the prognosis well (p = 0.0051 for training cohort, p = 0.065 for test cohort). ConclusionsThis study proved the accuracy and efficiency of random forest classifier for GBM subtyping and provided a convenient and efficient method for subtyping Proneural and Mesenchymal GBM.

Download Full-text

Role of COL3A1 and POSTN on Pathologic Stages of Esophageal Cancer

Technology in Cancer Research & Treatment ◽

10.1177/1533033820977489 ◽

2020 ◽

Vol 19 ◽

pp. 153303382097748

Author(s):

Shao-wei Zhang ◽

Nan Zhang ◽

Na Wang

Keyword(s):

Gene Expression ◽

Esophageal Cancer ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Protein Protein Interaction ◽

And Control ◽

The Impact

Background: Esophageal cancer (EC) is a primary malignant tumor originating from the esophageal of the epithelium. Surgical resection is a potential treatment for EC, but this is only appropriate for patients who have locally resectable lesions suitable for surgery. However, most patients with EC are at a late stage when diagnosed. Therefore, there is an urgent need to further explore the pathogenesis of EC to enable early diagnosis and treatment. Methods: Our study downloaded 2 expression spectrum datasets (GSE92396 and GSE100942) in the Gene Expression Omnibus (GEO) database. GEO2 R was used to identify the Differentially expressed genes (DEGs) between the samples of EC and control. Using the DAVID tool to make the Functional enrichment analysis. Constructing A protein–protein interaction (PPI) network. Identifying the Hub genes. The impact of hub gene expression on overall survival and their expression based on immunohistochemistry were analyzed. Associated microRNAs were also predicted. Results: There were 36 common DEGs identified. The analysis of GO and KEGG results shown that the variations were predominantly concentrated in the extracellular matrix (ECM), ECM organization, DNA binding, platelet activation, and ECM-receptor interactions. COL3A1 and POSTN had high expression in EC tissues which was compared with their expression in healthy tissues. Analysis of pathologic stages showed that when COL3A1 and POSTN were highly expressed, the stage of the pathologic of EC patients was relatively high (P < 0.005). Conclusions: COL3A1 and POSTN may play an important role in the advancement and occurrence of EC. These genes could provide some novel ideas and basis for the diagnosis and targeted treatment of EC.

Download Full-text