scholarly journals Identification of ALDH3A2 as novel prognostic biomarker in gastric adenocarcinoma by integrated bioinformatics analysis

2020 ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Xiyi Wei ◽  
Jianping Shi ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Protein Protein Interaction ◽  
Cancer Genome Atlas

Abstract Extensive experiments and researches have elucidated that genes plays a pivotal role in tumorigenesis and development. Nonetheless, its latent involvement in gastric carcinoma (GC) remains to be further investigated. In this study, we identified overlapping differentially expressed genes (DEGs) by comparing the tumor tissue and adjacent normal tissue from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database, which included 79 up-regulated and 10 down-regulated genes. Based on these genes, functional enrichment analysis, protein-protein interaction (PPI) and prognosis analysis were conducted, and thus the gene ALDH3A2 was chosen for further analysis. Then, we performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations and checkpoints) to comprehend the in-deep mechanism of ALDH3A2. In a word, ALDH3A2 might have potential reference value for the relief and immunotherapy, and become an independent predictive marker for the prognosis of GC.

scholarly journals Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

2020 ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Jianping Shi ◽  
Xiyi Wei ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Fatty Aldehyde ◽  
Low Grade

Abstract Background: Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further.Methods: In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database.Results: Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4.Conclusion: We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

Bioinformatics analysis of prognostic value genes in colorectal cancer microenvironment

2019 ◽  
Author(s):  
Taohua Yue ◽  
Jing Zhu ◽  
Xin Wang ◽  
Yisheng Pan ◽  
Yucun Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Large Scale ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Previous Literature ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Gastrointestinal Malignancies ◽  
Protein Protein Interaction ◽  
Cancer Genome Atlas

Abstract Colorectal cancer (CRC) is one of the most deadly gastrointestinal malignancies. The openness of the Cancer Genome Atlas (TCGA) allows us to perform correlation analysis between large-scale transcriptome data and overall survival (OS) of multiple malignancies. Previous literature reports that the infiltration of immune cells and stromal cells in the tumor microenvironment (TME) significantly associate with the prognosis of cancers. Based on the ESTIMATE algorithm, the immune and stromal components in TME can be quantified by immune and stromal scores. To determine the effects of immune and stromal cell associated genes on CRC prognosis, we divided the CRC cases into high- and low-groups based on the immune/stromal scores and identified 999 differentially expressed genes (DEGs). Heatmaps, functional enrichment analysis and protein‐protein interaction (PPIs) networks further indicated that 999 DEGs mainly participated in stromal composition and immune response. Finally, we obtained 56 genes that were significantly associated with CRC prognosis from 999 DEGs and identified the PPIs networks. The role of 41 genes in CRC has been reported in previous literature, and the other 15 genes have never been reported. Therefore, we found 15 novel TME genes associated with CRC prognosis waiting for more researches.

scholarly journals Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

2020 ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Jianping Shi ◽  
Xiyi Wei ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Fatty Aldehyde ◽  
Low Grade

Abstract Background: Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further. Methods: In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Results: Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4. Conclusion: We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

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 Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Jianping Shi ◽  
Xiyi Wei ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Fatty Aldehyde ◽  
Low Grade

Abstract Background Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further. Methods In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Results Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4. Conclusion We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

scholarly journals High RPS27A Expression Predicts Poor Prognosis in Patients With HPV Type 16 Cervical Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Qiming Wang ◽  
Yan Cai ◽  
Xuewen Fu ◽  
Liang Chen
Keyword(s):  
Cervical Cancer ◽  
Poor Prognosis ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Hpv Infection ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Cervical Cancer Cells ◽  
Cancer Genome Atlas

In recent years, the incidence and the mortality rate of cervical cancer have been gradually increasing, becoming one of the major causes of cancer-related death in women. In particular, patients with advanced and recurrent cervical cancers present a very poor prognosis. In addition, the vast majority of cervical cancer cases are caused by human papillomavirus (HPV) infection, of which HPV16 infection is the main cause and squamous cell carcinoma is the main presenting type. In this study, we performed screening of differentially expressed genes (DEGs) based on The Cancer Genome Atlas (TCGA) database and GSE6791, constructed a protein–protein interaction (PPI) network to screen 34 hub genes, filtered to the remaining 10 genes using the CytoHubba plug-in, and used survival analysis to determine that RPS27A was most associated with the prognosis of cervical cancer patients and has prognostic and predictive value for cervical cancer. The most significant biological functions and pathways of RPS27A enrichment were subsequently investigated with gene set enrichment analysis (GSEA), and integration of TCGA and GTEx database analyses revealed that RPS27A was significantly expressed in most cancer types. In this study, our analysis revealed that RPS27A can be used as a prognostic biomarker for HPV16 cervical cancer and has biological significance for the growth of cervical cancer cells.

scholarly journals Role of COL3A1 and POSTN on Pathologic Stages of Esophageal Cancer

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.

scholarly journals Prognostic Biomarker SYK and its Correlation with Immune Infiltrates in Glioma

2021 ◽  
Author(s):  
Pei Liu ◽  
Jiamin Guo ◽  
Xiaoxiao Xu ◽  
Haixin Sun ◽  
Zheng Gong
Keyword(s):  
Development Process ◽  
Prognostic Biomarker ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Ppi Network ◽  
Glioma Patient ◽  
Gene Set Enrichment ◽  
Protein Protein Interaction ◽  
Cancer Genome Atlas

Abstract Background: Tumor microenvironment (TME) has great effects on the development process of glioma, and we sought to identify effective prognostic factors by analyzing data from patients with glioma. In this paper, CIBERSORT and ESTIMATE calculations were employed to figure up the ratio of tumor-infiltrating immune cells (TICs) and the quantity of immune and stromal components in 698 glioma dates from The Cancer Genome Atlas (TCGA) database. In addition, differentially expressed genes (DEGs) were studied by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and single genes associated with prognosis were identified by PPI network and COX combined analysis. Results: Immune and stromal scores of TME were significantly correlated with glioma patient survival. Through protein–protein interaction (PPI) network and regression analysis of COX, we finally determined that SYK was the best prognostic factor for patients with glioma. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analysis were also employed, with the former showed that high-expression SYK group’s genes are principally enriched immune-related activities and the latter revealed that SYK expression was positively associated with T cells CD4 memory resting and Monocytes. All the above experimental analyses provided the theoretical basis for the biological prediction of SYK.Conclusions: SYK contributes to immune predictors in glioma patients by facilitating the shift of TME from immune dominance to metabolic activity, which provides promising insights into the treatment of glioma.

scholarly journals Identification of a FLG-wide-type bladder cancer subtype with poor prognosis and prediction use in immune checkpoint

2021 ◽  
Author(s):  
Liang Chen ◽  
Liulin Xiong ◽  
Weinan Chen ◽  
Lizhe An ◽  
Huanrui Wang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Immune Checkpoint ◽  
Poor Prognosis ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Biomarkers

Abstract Background Bladder cancer (BLCA) is one of most common urinary tract malignant tumor and immunotherapy have generated a great deal of interest in BLCA. Immune checkpoint blockade (ICB) therapy has significantly progressed the treatment of BLCA. Multiple studies have suggested that specific genetic mutations may serve as immune biomarkers for ICB therapy. Objective In this study, we aimed to investigate the role of mutations genes and subtypes in prognosis and immune checkpoint prediction in BLCA. Method Mutation information and expression profiles were acquired from The Cancer Genome Atlas (TCGA) database. Integrated bioinformatics analysis was carried out to explore the mutation genes of BLCA. Functional enrichment analysis Gene Ontology (GO) and Gene set enrichment analysis (GSEA) was conducted. The infiltrating immune cells and the prediction of ICB between different subtypes group were explored using immuCellAI algorithm. Results The mutation genes Filaggrin (FLG) gene were identified. Following the study on its subtypes and functional enrichment analysis, Sub2 of FLG-wide type was found to have relationships with poor prognosis and immune infiltration BLCA. What’s more, Sub2 of FLG-wide type may be used as a biomarker to predict the prognosis of BLCA patients receiving ICB. Conclusion This research provides a new basis and ideas for guiding the clinical application of BLCA immunotherapy.

scholarly journals Bioinformatics analysis of key biomarkers for retinoblastoma

2021 ◽  
Vol 49 (6) ◽  
pp. 030006052110222
Author(s):  
Xin-mei Zhao ◽  
Yuan-Bin Li ◽  
Peng Sun ◽  
Ya-di Pu ◽  
Meng-jie shan ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Microarray Dataset ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Protein Protein Interaction ◽  
Bilateral Retinoblastoma ◽  
Endopeptidase Activity ◽  
Novel Biomarkers ◽  
Geo Database

Objective To identify key genes involved in occurrence and development of retinoblastoma. Methods The microarray dataset, GSE5222, was downloaded from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between unilateral and bilateral retinoblastoma were identified and functional enrichment analysis performed. The protein–protein interaction (PPI) network was constructed and analysed by STRING and Cytoscape. Results DEGs were mainly associated with activation of cysteine-type endopeptidase activity involved in apoptotic process and small molecule catabolic process. Seven genes (WAS, GNB3, PTGER1, TACR1, GPR143, NPFF and CDKN2A) were identified as HUB genes. Conclusion Our research provides more understanding of the mechanisms of the disease at a molecular level and may help in the identification of novel biomarkers for retinoblastoma.

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