scholarly journals Overexpression of SKA Complex Is Associated With Poor Prognosis in Gliomas

2022 ◽  
Vol 12 ◽  
Author(s):  
Shoukai Yu

The spindle and kinetochore-associated complex is composed of three members: SKA1, SKA2, and SKA3. It is necessary for stabilizing spindle microtubules attaching to kinetochore (KT) in the middle stage of mitosis. The SKA complex is associated with poor prognosis in several human cancers. However, the role of SKA complex in rare malignant diseases, such as gliomas, has not been fully investigated. We investigated several databases, including Oncomine, UALCAN, and cBioPortal to explore the expression profile and prognostic significance of SKA complex in patients with gliomas. Gene ontology and Kyoto Encyclopedia of Genes and Genome pathways were used to analyze the potential enriched pathways. The genes co-expressed with SKA complex were identified and used for developing a protein-protein interaction (PPI) network using the STRING database. We found a significant overexpression of the mRNA levels of SKA1, SKA2, and SKA3 in patients with glioma patients. Higher expression of SKA1 and SKA3, but not SKA2, was significantly correlated with shorter overall survival of patients with glioma. In glioma, SKA complex was found to be involved in nuclear division, chromosome segregation, and DNA replication. The results of PPI network identified 10 hub genes (CCNB2, UBE2C, BUB1B, TPX2, CCNA2, CCNB1, MELK, TOP2A, PBK, and KIF11), all of which were overexpressed and negatively associated with prognosis of patients with glioma. In conclusion, our study sheds new insights into the biological role and prognostic significance of SKA complex in glioma.

2020 ◽  
Author(s):  
Jingyang Zhou ◽  
Feng Xin ◽  
Chuyu Xiao ◽  
Wuyuan Zhou

Abstract Background: In western countries and China, back and neck pain has become a common problem that bothers daily life and severely influences the quality of our daily life. Among all factors that lead to chronic neck and back pain, IDD is the one that couldn’t be easily neglected. Methods: This study aims to figure out the critical genes and pathways involved in the development of IDD and provide a new aspect of following investigations on the etiology of IDD. We firstly systemically searched the GEO database and identified the differentially expressed genes (DEGs) from the expression profile dataset we selected. We secondly constructed the protein-protein interaction (PPI) network for DEGs, identified the top ten hub genes from the whole PPI network and found two statically and medically significant modules from the network, we then performed the GO and KEGG analysis on the DEGs, top ten hub genes, the PPI network and the two statically and medically modules. In the end, we provided the primers of the mRNAs of all DEGs, which will be useful for the validation experiment of this study. Results: FN1, MMP2, POSTN, COL3A1, TIMP3, FBN1, GJA1, TGFBI, EFEMP1 and ID1 were top ten hub genes identified from this study, and they may play a vital role in the development of IDD. Angiogenesis and integrin binging are crucial biological process and molecular function defined in this study, which are worthy of being intensely investigated.Conclusion: More studies on the top ten hub genes, the role of angiogenesis and integrin binding in IDD are urgently needed, which will benefit the prevention, screening, diagnosis and prognosis of IDD.


2020 ◽  
Author(s):  
Xilin Hu ◽  
Hanlin Xu ◽  
Wenjie Jiao ◽  
Kaihua Tian

Abstract Background: Cancer-related death is mainly caused by lung adenocarcinoma (LUAD), an aggressive malignant tumor. Therefore, the identification of important LUAD-related genes and the further analysis of its prognostic significance are critical for the survival of LUAD patients.Methods: Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods were adopted to screen out TCGA-LUAD database and the gene expression profiles of GSE32863 from GEO. Functional annotation analysis and protein-protein interaction (PPI) network were conducted on differential co-expression genes. Furthermore, survival analysis was carried out on twelve hub genes that were identified by applying the CytoHubba plugin of Cytoscape. Finally, we validated the protein level of survival-related gene in HPA database.Results: A total of 358 differential co-expression genes were extracted from the database of TCGA and GEO. These genes were mainly enriched in extracellular structure organization, cell−substrate adhesion and response to acid chemical (biological process), cell−cell junction and collagen−containing extracellular matrix (cellular component), DNA−binding transcription activator activity, glycosaminoglycan binding, and growth factor binding (molecular function). In the KEGG analysis, the main pathways were Drug metabolism−cytochrome P450. Moreover, in a PPI network, the 12 hub genes (GNG11, ADRB2, ADCY4, TGFBR2, IL6, GPC3, VIPR1, GRK5, CAV1, RAMP3, RAMP2, and CALCRL) were identified. The expression level of ADCY4, VIPR1, and TGFBR2 was corresponded with clinical stages and overall survival (OS) in LUAD patients. Finally, the protein level of ADCY4 and VIPR1 was down-regulated consistently with mRNA levels in LUAD samples.Conclusion: Perhaps, ADCY4, VIPR1 and TGFBR2 play important role in tumorigenesis, so they will serve as prognostic biomarkers and therapeutic targets of LUAD in the future.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Weishuang Xue ◽  
Jinwei Li ◽  
Kailei Fu ◽  
Weiyu Teng

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. Methods. We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. Results. Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. Conclusions. Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.


2022 ◽  
Vol 12 (3) ◽  
pp. 523-532
Author(s):  
Xin Yan ◽  
Chunfeng Liang ◽  
Xinghuan Liang ◽  
Li Li ◽  
Zhenxing Huang ◽  
...  

<sec> <title>Objective:</title> This study aimed to identify the potential key genes associated with the progression and prognosis of adrenocortical carcinoma (ACC). </sec> <sec> <title>Methods:</title> Differentially expressed genes (DEGs) in ACC cells and normal adrenocortical cells were assessed by microarray from the Gene Expression Omnibus database. The biological functions of the classified DEGs were examined by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses and a protein–protein interaction (PPI) network was mapped using Cytoscape software. MCODE software was also used for the module analysis and then 4 algorithms of cytohubba software were used to screen hub genes. The overall survival (OS) examination of the hub genes was then performed by the ualcan online tool. </sec> <sec> <title>Results:</title> Two GSEs (GSE12368, GSE33371) were downloaded from GEO including 18 and 43 cases, respectively. One hundred and sixty-nine DEGs were identified, including 57 upregulated genes and 112 downregulated genes. The Gene Ontology (GO) analyses showed that the upregulated genes were significantly enriched in the mitotic cytokines is, nucleus and ATP binding, while the downregulated genes were involved in the positive regulation of cardiac muscle contraction, extracellular space, and heparin-binding (P < 0.05). The Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) pathway examination showed significant pathways including the cell cycle and the complement and coagulation cascades. The protein– protein interaction (PPI) network consisted of 162 nodes and 847 edges, including mitotic nuclear division, cytoplasmic, protein kinase binding, and cell cycle. All 4 identified hub genes (FOXM1, UBE2C, KIF11, and NDC80) were associated with the prognosis of adrenocortical carcinoma (ACC) by survival analysis. </sec> <sec> <title>Conclusions:</title> The present study offered insights into the molecular mechanism of adrenocortical carcinoma (ACC) that may be beneficial in further analyses. </sec>


2020 ◽  
Vol 40 (7) ◽  
Author(s):  
Weiwei Liang ◽  
FangFang Sun

Abstract This research was carried out to reveal specific hub genes involved in diabetic heart failure, as well as remarkable pathways that hub genes locate. The GSE26887 dataset from the GEO website was downloaded. The gene co-expression network was generated and central modules were analyzed to identify key genes using the WGCNA method. Functional analyses were conducted on genes of the clinical interest modules via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment, associated with protein–protein interaction (PPI) network construction in a sequence. Centrality parameters of the PPI network were determined using the CentiScape plugin in Cytoscape. Key genes, defined as genes in the ≥95% percentile of the degree distribution of significantly perturbed networks, were identified. Twenty gene co-expression modules were detected by WGCNA analysis. The module marked in light yellow exhibited the most significant association with diabetes (P=0.08). Genes involved in this module were primarily located in immune response, plasma membrane and receptor binding, as shown by the GO analysis. These genes were primarily assembled in endocytosis and phagosomes for KEGG pathway enrichment. Three key genes, STK39, HLA-DPB1 and RAB5C, which may be key genes for diabetic heart failure, were identified. To our knowledge, our study is the first to have constructed the co-expression network involved in diabetic heart failure using the WGCNA method. The results of the present study have provided better understanding the molecular mechanism of diabetic heart failure.


2020 ◽  
Author(s):  
Sizhe Hu ◽  
Peipei Li ◽  
Chenying Wang ◽  
Xiyong Liu

Abstract Background: BGN (biglycan) is a family member of small leucine-rich repeat proteoglycans. High expression of BGN might enhance the invasion and metastasis in some types of tumors. Here, the prognostic significance of BGN was evaluated in gastric cancer.Material and Methods: Two independent Gene Expression Omnibus (GEO) gastric cancer microarray datasets( n= 64, n=432) were collected for this study. Kaplan-Meier analysis was applied to evaluate if BGN impacts the outcomes of gastric cancer. The gene set enrichment analysis (GSEA) was used to explore BGN and cancer-related gene signatures. Bioinformatic analysis predicted the putative transcription factors of BGN.Results: For gastric cancer, the mRNA expression level of BGN in tumor tissues was significantly higher than that in normal tissues. Kaplan-Meier analysis showed that higher expression of BGN mRNA was significantly associated with more reduced recurrence-free survival (RFS). GSEA results suggested that BGN significantly enriched metastasis and poor prognosis gene signatures, revealing that BGN might be associated with cell proliferation, poor differentiation, high invasiveness of gastric cancer. Meanwhile, the putative transcription factors, including AR, E2F1, and TCF4, weres predicted by bioinformatic analysis and also significantly correlated with expression of BGN in mRNA levels. Conclusion: High expression of BGN mRNA was significantly related to poor prognosis, which suggested BGN was a potential prognostic biomarker and therapeutic target of gastric cancer.


2019 ◽  
Vol 20 (17) ◽  
pp. 4156 ◽  
Author(s):  
Glatzel-Plucińska ◽  
Piotrowska ◽  
Dzięgiel ◽  
Podhorska-Okołów

Carcinogenesis is a long-drawn, multistep process, in which metastatic spread is an unequivocal hallmark of a poor prognosis. The progression and dissemination of epithelial cancers is commonly thought to rely on the epidermal-mesenchymal transition (EMT) process. During EMT, epithelial cells lose their junctions and apical-basal polarity, and they acquire a mesenchymal phenotype with its migratory and invasive capabilities. One of the proteins involved in cancer progression and EMT may be SATB1 (Special AT-Rich Binding Protein 1)—a chromatin organiser and a global transcriptional regulator. SATB1 organizes chromatin into spatial loops, providing a “docking site” necessary for the binding of further transcription factors and chromatin modifying enzymes. SATB1 has the ability to regulate whole sets of genes, even those located on distant chromosomes. SATB1 was found to be overexpressed in numerous malignancies, including lymphomas, breast, colorectal, prostate, liver, bladder and ovarian cancers. In the solid tumours, an elevated SATB1 level was observed to be associated with an aggressive phenotype, presence of lymph node, distant metastases, and a poor prognosis. In this review, we briefly describe the prognostic significance of SATB1 expression in most common human cancers, and analyse its impact on EMT and metastasis.


2021 ◽  
Vol 11 ◽  
Author(s):  
Miao Xu ◽  
Tianxiang Ouyang ◽  
Kaiyang Lv ◽  
Xiaorong Ma

BackgroundInfantile hemangioma (IH) is characterized by proliferation and regression.MethodsBased on the GSE127487 dataset, the differentially expressed genes (DEGs) between 6, 12, or 24 months and normal samples were screened, respectively. STEM software was used to screen the continued up-regulated or down-regulated in common genes. The modules were assessed by weighted gene co-expression network analysis (WGCNA). The enrichment analysis was performed to identified the biological function of important module genes. The area under curve (AUC) value and protein-protein interaction (PPI) network were used to identify hub genes. The differential expression of hub genes in IH and normal tissues was detected by qPCR.ResultsThere were 5,785, 4,712, and 2,149 DEGs between 6, 12, and 24 months and normal tissues. We found 1,218 DEGs were up-regulated or down-regulated expression simultaneously in common genes. They were identified as 10 co-expression modules. Module 3 and module 4 were positively or negatively correlated with the development of IH, respectively. These two module genes were significantly involved in immunity, cell cycle arrest and mTOR signaling pathway. The two module genes with AUC greater than 0.8 at different stages of IH were put into PPI network, and five genes with the highest degree were identified as hub genes. The differential expression of these genes was also verified by qRTPCR.ConclusionFive hub genes may distinguish for proliferative and regressive IH lesions. The WGCNA and PPI network analyses may help to clarify the molecular mechanism of IH at different stages.


2021 ◽  
Author(s):  
Xiao Liang ◽  
Yali Chen ◽  
Yuchao Fan

Abstract Coronavirus disease 2019 (COVID-19) continues as a global pandemic. Patients with lung cancer infected with COVID-19 may develop severe disease or die. Treating such patients severely burdens overwhelmed healthcare systems. Here we identified potential pathological mechanisms shared between patients with COVID-19 and lung adenocarcinoma (LUAD). Co-expressed, differentially expressed genes (DEGs) in patients with COVID-19 and LUAD were identified and used to construct a protein-protein interaction (PPI) network and to perform enrichment analysis. We used the NetworkAnalyst platform to establish a co-regulatory of the co-expressed DEGs, and we used Spearman’s correlation to evaluate the significance of associations of hub genes with immune infiltration and immune checkpoints. Analysis of three datasets identified 112 shared DEGs, which were used to construct a protein-PPI network. Subsequent enrichment analysis revealed co-expressed genes related to biological process (BP), molecular function (MF), cellular component (CC) as well as to pathways, specific organs, cells and diseases. Ten co-expressed hub genes were employed to construct a gene-miRNA, transcription factor (TF)-gene and TF-miRNA network. Hub genes were significantly associated with immune infiltration and immune checkpoints. Finally methylation level of hub genes in LUAD was obtained via UALCAN database. The present multi-dimensional study reveals commonality in specific gene expression by patients with COVID-19 and LUAD. These findings provide insights into developing strategies for optimising the management and treatment of patients with LUAD with COVID-19.


2020 ◽  
Author(s):  
Ying Liu ◽  
Jintuo Zhou ◽  
Peiguang Niu ◽  
Fanxiang Zeng ◽  
Ruihong Cai ◽  
...  

Abstract Background: Phosphatase and tensin homolog (PTEN) is a frequently mutated genes found in endometrial cancer (EC), making it a potential biomarker for individualized treatment opinions. In this study, a method was designed to evaluate the role of the PTEN mutation in the prognosis and drug selection of EC. We identified the potential alterations in pathways and genes related to the mechanism. Methods: cBioPortal database was used to analyze the PTEN mutation status for EC patients. Kaplan-Meier was used to analyze the prognosis of PTEN mutation in EC patients. GDSC dataset was used to identified the drugs that sensitive to cell lines with PTEN mutation. DEGs between PTEN mutation and wide type group were identified using the edgeR package. GO and KEGG analysis were carried out using the DAVID database. GSEA v3.0 were used to dig out the differences in gene mRNA levels of biological function annotation and pathways between PTEN mutation and wide type patients. PPI network of DEGs was performed using STRING and then visualized using Cytoscope software (3.7.2).Results: Our results showed that PTEN mutation was carried in 68% of EC patients. The mRNA expression level of PTEN was lower in patients with PTEN mutation than that with wide type. Prognosis analysis showed that there were favorable overall survival and progression free survival in EC patients with PTEN mutation. Moreover, it is more sensitive to AKT inhibitor (Afuresertib and AZD5363), and Mcl-1 inhibitor (MIM1) on EC cell lines with PTEN mutation than that with wide type. A total of 216 genes were identified as DEGs. GO analysis showed that DEGs significantly enriched in chemical synaptic transmission, extracellular region, etc.. KEGG analysis suggested that DEGs significantly enriched in categories associated with metabolic progression. GSEA analysis identified signaling pathways including fatty acid metabolism, fructose and mannose metabolism, etc.. PPI network analysis identified top 10 genes and top three clusters.Conclusions: Multiple genes and pathways may play an important role in EC patients with PTEN mutation. These results provide a potential target and therapeutic strategies for patients with PTEN mutation.


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