scholarly journals The relationship between PLOD1 expression level and glioma prognosis investigated using public databases

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11422
Author(s):  
Lei Tian ◽  
Huandi Zhou ◽  
Guohui Wang ◽  
Wen yan Wang ◽  
Yuehong Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Expression Level ◽  
Clinicopathologic Characteristics ◽  
Genome Atlas

Background Glioma is the most common type of intracranial tumor with high malignancy and poor prognosis despite the use of various aggressive treatments. Targeted therapy and immunotherapy are not effective and new biomarkers need to be explored. Some Procollagen-lysine 2-oxyglutarate 5-dioxygenase (PLOD) family members have been found to be involved in the metastasis and progression of tumors. Both PLOD2 and PLOD3 had been reported to be highly expressed in gliomas, while the prognostic value of PLOD1 remains to be further illustrated, so we want to investigate the PLOD1 expression in glioma and its clinical implication. Methods We collected gene expression and corresponding clinical data of glioma from the Chinese Glioma Genome Atlas (CGGA) database, The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. First, we analyzed the expression and mutation of PLOD1 in gliomas and its relationship with clinicopathologic characteristics. Then, we conducted survival analysis, prognostic analysis and nomogram construction of the PLOD1 gene. Finally, we conducted gene ontology (GO) enrichment analysis and gene set enrichment analysis (GSEA) to explore possible mechanisms and gene co-expression analysis was also be performed. Results The results showed that the expression level of PLOD1 was higher in gliomas than normal tissues, and high expression of PLOD1 was related to poor survival which can serve as an oncogenic factor and an independent prognostic indicator for glioma patients. Both the GO and GSEA analysis showed high expression of PLOD1 were enriched in Extracellular matrix (ECM) related pathways, the co-expression analysis revealed that PLOD1 was positively related to HSPG2, COL6A2, COL4A2, FN1, COL1A1, COL4A1, CD44, COL3A1, COL1A2 and SPP1, and high expression of these genes were also correlated to poor prognosis of glioma. Conclusions The results showed that high expression of PLOD1 leads to poor prognosis, and PLOD1 is an independent prognostic factor and a novel biomarker for the treatment of glioma. Furthermore, targeting PLOD1 is most likely a potential therapeutic strategy for glioma patients.

scholarly journals Expression of LOX Suggests Poor Prognosis in Gastric Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Jinfeng Zhu ◽  
Chen Luo ◽  
Jiefeng Zhao ◽  
Xiaojian Zhu ◽  
Kang Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
Expression Level ◽  
Cox Regression Analysis

Background: Lysyl oxidase (LOX) is a key enzyme for the cross-linking of collagen and elastin in the extracellular matrix. This study evaluated the prognostic role of LOX in gastric cancer (GC) by analyzing the data of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset.Methods: The Wilcoxon rank-sum test was used to calculate the expression difference of LOX gene in gastric cancer and normal tissues. Western blot and immunohistochemical staining were used to evaluate the expression level of LOX protein in gastric cancer. Kaplan-Meier analysis was used to calculate the survival difference between the high expression group and the low expression group in gastric cancer. The relationship between statistical clinicopathological characteristics and LOX gene expression was analyzed by Wilcoxon or Kruskal-Wallis test and logistic regression. Univariate and multivariate Cox regression analysis was used to find independent risk factors affecting the prognosis of GC patients. Gene set enrichment analysis (GSEA) was used to screen the possible mechanisms of LOX and GC. The CIBERSORT calculation method was used to evaluate the distribution of tumor-infiltrating immune cell (TIC) abundance.Results: LOX is highly expressed in gastric cancer tissues and is significantly related to poor overall survival. Wilcoxon or Kruskal-Wallis test and Logistic regression analysis showed, LOX overexpression is significantly correlated with T-stage progression in gastric cancer. Multivariate Cox regression analysis on TCGA and GEO data found that LOX (all p < 0.05) is an independent factor for poor GC prognosis. GSEA showed that high LOX expression is related to ECM receptor interaction, cancer, Hedgehog, TGF-beta, JAK-STAT, MAPK, Wnt, and mTOR signaling pathways. The expression level of LOX affects the immune activity of the tumor microenvironment in gastric cancer.Conclusion: High expression of LOX is a potential molecular indicator for poor prognosis of gastric cancer.

scholarly journals Increased expression of homeobox 5 predicts poor prognosis: A potential therapeutic target for glioma

2021 ◽  
Author(s):  
Chengran Xu ◽  
Jinhai Huang ◽  
Yi Yang ◽  
Lun Li ◽  
Guangyu Li
Keyword(s):  
Cox Regression ◽  
Homeobox Gene ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Who Grade ◽  
Forecast Efficiency ◽  
Genome Atlas

Abstract Background: The homeobox gene 5 (HOXB5) encodes a transcription factor that regulates the central nervous system embryonic development. Of note, its expression pattern and prognostic role in glioma remain unelucidated. This study aimed to identify the relationship between HOXB5 and glioma by investigating the HOXB5 expression data from the The Cancer Genome Atlas (TCGA) and The Genotype Tissue Expression (GTEx) databases and validating the obtained data using the Chinese Glioma Genome Atlas (CGGA) database. Kaplan-Meier and univariate cox regression analyses were performed to assess the prognostic value of HOXB5. The key functions and signaling pathways of HOXB5 were analyzed using GSEA and GSVA. Immune infiltration was calculated using Microenvironment Cell Populations-counter (MCP-counter), single-sample Gene Set Enrichment Analysis (ssGSEA), and ESTIMATE algorithms.Result: HOXB5 expression was elevated in glioma tissues. The increased levels of HOXB5 were significantly correlated with a higher WHO grade and aggressive cancer phenotypes. HOXB5 overexpression represented a risk factor that was associated with shorter overall survival (OS) while exhibiting a moderate forecast efficiency in most clinical subgroups. These results were validated using the CGGA and Rembrandt datasets. Furthermore, the functional analysis showed enrichment of angiogenesis, the IL6/JAK-STAT3 pathway, and inflammatory response in the tissues that showed high expression of HOXB5. Lastly, the high expression of HOXB5 was associated with enrichment of Tregs and MDSCs, and HOXB5 expression was shown to play a role in several immune checkpoint genes.Conclusions: HOXB5 may serve as a predictive factor of glioma malignancy and prognostic status and represents potential as a molecular treatment candidate.

scholarly journals Comprehensive Analysis of ESRRA in Endometrial Cancer

2021 ◽  
Vol 20 ◽  
pp. 153303382199208
Author(s):  
Shufang Wang ◽  
Xinlong Huo
Keyword(s):  
Endometrial Cancer ◽  
Protein Expression ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Operating Characteristics ◽  
Protein Expression Level ◽  
Normal Tissues

Background: Estrogen-related receptor alpha (ESRRA) was reported to play an important role in multiple biological processes of neoplastic diseases. The roles of ESRRA in endometrial cancer have not been fully investigated yet. Methods: Expression data and clinicopathological data of patients with uteri corpus endometrial carcinoma (UCEC) were obtained from The Cancer Genome Atlas (TCGA). Comprehensive bioinformatics analysis was performed, including receiver operating characteristics (ROC) curve analysis, Kaplan-Meier survival analysis, gene ontology (GO) enrichment analysis, and Gene Set Enrichment Analysis (GSEA). Immunohistochemistry was used to detect the protein expression level of ESRRA and CCK-8 assay was performed to evaluate the effect of ESRRA on the proliferation ability. Results: A total of 552 UCEC tissues and 35 normal tissues were obtained from the TCGA database. The mRNA and protein expression level of ESRRA was highly elevated in UCEC compared with normal tissues, and was closely associated with poor prognosis. ROC analysis indicated a very high diagnostic value of ESRRA for patients with UCEC. GO and GSEA functional analysis showed that ESRRA might be mainly involved in cellular metabolism processes, in turn, tumorigenesis and progression of UCEC. Knockdown of ESRRA inhibited the proliferation of UCEC cells in vitro. Further immune cell infiltration demonstrated that ESRRA enhanced the infiltration level of neutrophil cell and reduced that of T cell (CD4+ naïve), NK cell, and cancer associated fibroblast (CAF). The alteration of immune microenvironment will greatly help in developing immune checkpoint therapy for UCEC. Conclusions: Our study comprehensively analyzed the expression level, clinical value, and possible mechanisms of action of ESRRA in UCEC. These findings showed that ESRRA might be a potential diagnostic and therapeutic target.

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 Easy and efficient ensemble gene set testing with EGSEA

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 2010 ◽  
Author(s):  
Monther Alhamdoosh ◽  
Charity W. Law ◽  
Luyi Tian ◽  
Julie M. Sheridan ◽  
Milica Ng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set ◽  
P Gene ◽  
Wide Range ◽  
Gene Set Testing

Gene set enrichment analysis is a popular approach for prioritising the biological processes perturbed in genomic datasets. The Bioconductor project hosts over 80 software packages capable of gene set analysis. Most of these packages search for enriched signatures amongst differentially regulated genes to reveal higher level biological themes that may be missed when focusing only on evidence from individual genes. With so many different methods on offer, choosing the best algorithm and visualization approach can be challenging. The EGSEA package solves this problem by combining results from up to 12 prominent gene set testing algorithms to obtain a consensus ranking of biologically relevant results.This workflow demonstrates how EGSEA can extend limma-based differential expression analyses for RNA-seq and microarray data using experiments that profile 3 distinct cell populations important for studying the origins of breast cancer. Following data normalization and set-up of an appropriate linear model for differential expression analysis, EGSEA builds gene signature specific indexes that link a wide range of mouse or human gene set collections obtained from MSigDB, GeneSetDB and KEGG to the gene expression data being investigated. EGSEA is then configured and the ensemble enrichment analysis run, returning an object that can be queried using several S4 methods for ranking gene sets and visualizing results via heatmaps, KEGG pathway views, GO graphs, scatter plots and bar plots. Finally, an HTML report that combines these displays can fast-track the sharing of results with collaborators, and thus expedite downstream biological validation. EGSEA is simple to use and can be easily integrated with existing gene expression analysis pipelines for both human and mouse data.

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.

scholarly journals Increased IGFBP7 Expression Correlates with Poor Prognosis and Immune Infiltration in Gastric Cancer: An Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Qiaoyun Zhao ◽  
Rulin Zhao ◽  
Conghua Song ◽  
Huan Wang ◽  
Jianfang Rong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Biological Processes ◽  
Coexpressed Genes

Abstract Background Insulin-like growth factor binding protein-7 (IGFBP7) contributes to multiple biological processes in various tumors. However, the role of IGFBP7 in gastric cancer (GC) is still undetermined. The study aims to explore the role of IGFBP7 in GC via an integrated bioinformatics analysis.Methods IGFBP7 expression levels in GC and its normal gastric tissues were analyzed using multiple databases, including the Tumor Immune Estimation Resource (TIMER), Oncomine, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The methylation analysis was conducted with MEXPRESS, UALCAN and Xena online tools. The survival analysis was conducted using the Kaplan-Meier Plotter and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Coexpressed genes of IGFBP7 were selected with the cBioPortal tool and enrichment analysis was conducted with the clusterProfiler package in R software. Gene set enrichment analysis (GSEA) was performed to explore the IGFBP7-related biological processes involved in GC. Correlations between IGFBP7 and immune cell infiltrates were analyzed using the TIMER database.Results IGFBP7 expression was significantly upregulated in GC and correlated with stage, grade, tumor status and Helicobacter pylori infection. High IGFBP7 expression and low IGFBP7 methylation levels were significantly associated with short survival of patients with GC. Univariate and multivariate analyses revealed that IGFBP7 was an independent risk factor for GC. The coexpressed genes LHFPL6, SEPTIN4, HSPB2, LAYN and GGT5 predicted unfavorable outcomes of GC. Enrichment analysis showed that the coexpressed genes were involved in extracellular matrix (ECM)-related processes. GSEA indicated that IGFBP7 was positively related to ECM and inflammation-related pathways. TIMER analysis indicated that the IGFBP7 expression level was strongly correlated with genes related to various infiltrating immune cells in GC, especially with gene markers of tumor associated macrophages (TAMs).Conclusions We demonstrate that increased IGFBP7 expression correlates with poor prognosis and immune cell infiltration in GC. IGFBP7 might be a potential biomarker for the diagnosis and targeted therapy for GC.

scholarly journals ANXA9 as a novel prognostic biomarker associated with immune infiltrates in gastric cancer

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12605
Author(s):  
Tongtong Zhang ◽  
Suyang Yu ◽  
Shipeng Zhao
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Survival Curve ◽  
Enrichment Analysis ◽  
Prognostic Indicator ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Clinicopathological Parameters ◽  
The Relationship

Background Gastric cancer (GC) is the most prevalent malignancy among the digestive system tumors. Increasing evidence has revealed that lower mRNA expression of ANXA9 is associated with a poor prognosis in colorectal cancer. However, the role of ANXA9 in GC remains largely unknown. Material and Methods The Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas databases were used to investigate the expression of ANXA9 in GC, which was then validated in the four Gene Expression Omnibus (GEO) datasets. The diagnostic value of ANXA9 for GC patients was demonstrated using a receiver operating characteristic (ROC) curve. The correlation between ANXA9 expression and clinicopathological parameters was analyzed in The Cancer Genome Atlas (TCGA) and UALCAN databases. The Kaplan-Meier (K-M) survival curve was used to elucidate the relationship between ANXA9 expression and the survival time of GC patients. We then performed a gene set enrichment analysis (GSEA) to explore the biological functions of ANXA9. The relationship of ANXA9 expression and cancer immune infiltrates was analyzed using the Tumor Immune Estimation Resource (TIMER). In addition, the potential mechanism of ANXA9 in GC was investigated by analyzing its related genes. Results ANXA9 was significantly up-regulated in GC tissues and showed obvious diagnostic value. The expression of ANXA9 was related to the age, gender, grade, TP53 mutation, and histological subtype of GC patients. We also found that ANXA9 expression was associated with immune-related biological function. ANXA9 expression was also correlated with the infiltration level of CD8+ T cells, neutrophils, and dendritic cells in GC. Additionally, copy number variation (VNV) of ANXA9 occurred in GC patients. Function enrichment analyses revealed that ANXA9 plays a role in the GC progression by interacting with its related genes. Conclusions Our results provide strong evidence of ANXA9 expression as a prognostic indicator related to immune responses in GC.

scholarly journals Comprehensive analysis of ceRNA networks reveals prognostic lncRNAs related to immune infiltration in colorectal cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jingyi Chen ◽  
Yuxuan Song ◽  
Mei Li ◽  
Yu Zhang ◽  
Tingru Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Target Genes ◽  
Immune Cell ◽  
Pearson Correlation ◽  
Enrichment Analysis ◽  
Cell Types ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cerna Network

Abstract Background Competing endogenous RNA (ceRNA) represents a class of RNAs (e.g., long noncoding RNAs [lncRNAs]) with microRNA (miRNA) binding sites, which can competitively bind miRNA and inhibit its regulation of target genes. Increasing evidence has underscored the involvement of dysregulated ceRNA networks in the occurrence and progression of colorectal cancer (CRC). The purpose of this study was to construct a ceRNA network related to the prognosis of CRC and further explore the potential mechanisms that affect this prognosis. Methods RNA-Seq and miRNA-Seq data from The Cancer Genome Atlas (TCGA) were used to identify differentially expressed lncRNAs (DElncRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs), and a prognosis-related ceRNA network was constructed based on DElncRNA survival analysis. Subsequently, pathway enrichment, Pearson correlation, and Gene Set Enrichment Analysis (GSEA) were performed to determine the function of the genes in the ceRNA network. Gene Expression Profiling Interactive Analysis (GEPIA) and immunohistochemistry (IHC) were also used to validate differential gene expression. Finally, the correlation between lncRNA and immune cell infiltration in the tumor microenvironment was evaluated based on the CIBERSORT algorithm. Results A prognostic ceRNA network was constructed with eleven key survival-related DElncRNAs (MIR4435-2HG, NKILA, AFAP1-AS1, ELFN1-AS1, AC005520.2, AC245884.8, AL354836.1, AL355987.4, AL591845.1, LINC02038, and AC104823.1), 54 DEmiRNAs, and 308 DEmRNAs. The MIR4435-2HG- and ELFN1-AS1-associated ceRNA subnetworks affected and regulated the expression of the COL5A2, LOX, OSBPL3, PLAU, VCAN, SRM, and E2F1 target genes and were found to be related to prognosis and tumor-infiltrating immune cell types. Conclusions MIR4435-2HG and ELFN1-AS1 are associated with prognosis and tumor-infiltrating immune cell types and could represent potential prognostic biomarkers or therapeutic targets in colorectal carcinoma.

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