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 MYD88 Is a Potential Prognostic Gene and Immune Signature of Tumor Microenvironment for Gliomas

2021 ◽  
Vol 11 ◽  
Author(s):  
Qinglong Guo ◽  
Xing Xiao ◽  
Jinsen Zhang
Keyword(s):  
Tumor Microenvironment ◽  
Cox Regression ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Who Grade ◽  
Cox Regression Analysis ◽  
Clinical Cases

PurposeTo explore the profiles of immune and stromal components of the tumor microenvironment (TME) and their related key genes in gliomas.MethodsWe applied bioinformatic techniques to identify the core gene that participated in the regulation of the TME of the gliomas. And immunohistochemistry staining was used to calculate the gene expressions in clinical cases.ResultsThe CIBERSORT and ESTIMATE were used to figure out the composition of TME in 698 glioma cases from The Cancer Genome Atlas (TCGA) database. Differential expression analysis identified 2103 genes between the high and the low-score group. Then the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, univariate Cox regression analysis, and protein–protein interaction (PPI) network construction were conducted based on these genes. MYD88 was identified as the key gene by the combination univariate Cox and PPI analysis. Furthermore, MYD88 expression was significantly associated with the overall survival and WHO grade of glioma patients. The genes in the high-expression MYD88 group were mainly in immune-related pathways in the Gene Set Enrichment Analysis (GSEA). We found that macrophage M2 accounted for the largest portion with an average of 27.6% in the glioma TIICs and was associated with high expression of MYD88. The results were verified in CGGA database and clinical cases in our hospital. Furthermore, we also found the MYD88 expression was higher in IDH1 wild types. The methylation rate was lower in high grade gliomas.ConclusionMYD88 had predictive prognostic value in glioma patients by influencing TIICs dysregulation especially the M2-type macrophages.

scholarly journals Ferroptosis-related Gene Signature Correlates with the Tumor Immune features and Predicts the Prognosis of Glioma Patients

2021 ◽  
Author(s):  
Yan Hu ◽  
Zewei Tu ◽  
Kunjian Lei ◽  
Kai Huang ◽  
Xingen Zhu
Keyword(s):  
Immune Cell ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Related Gene ◽  
Who Grade ◽  
Glioma Microenvironment ◽  
Genome Atlas

Background: Glioma is a malignant intracranial tumor and the most fatal cancer. The role of ferroptosis in the clinical progression of gliomas is unclear.Method: Univariate and least absolute shrinkage and the selection operator (Lasso) Cox regression methods were used to develop a ferroptosis-related signature (FRSig) using a cohort of glioma patients from the Chinese Glioma Genome Atlas (CGGA), and was validated using an independent cohort of glioma patients from The Cancer Genome Atlas (TCGA). A single-sample gene-set enrichment analysis (ssGSEA) was used to calculate levels of the immune infiltration. Multivariate Cox regression was used to determine the independent prognostic role of clinicopathological factors and to establish a nomogram model for clinical application.Results: We analyzed the correlations between the clinicopathological features and ferroptosis-related gene (FRG) expression and established a FRSig to calculate the risk score for individual glioma patients. Patients were stratified into two subgroups with distinct clinical outcomes. Immune cell infiltration in the glioma microenvironment and immune-related indexes were identified that significantly correlated with the FRSig, the tumor mutation burden (TMB), copy number alteration (CNA), and immune check-point expression was also significantly positively correlated with the FRSig score. Ultimately, a FRSig-based nomogram model was constructed using the independent prognostic factors age, WHO grade, and FRSig score.Conclusion: We established the FRSig to assess the prognosis of glioma patients. The FRSig also represented the glioma microenvironment status. Our FRSig will contribute to improve patient management and individualized therapy by offering a molecular biomarker signature for precise treatment.

scholarly journals Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Qingyu Liang ◽  
Gefei Guan ◽  
Xue Li ◽  
Chunmi Wei ◽  
Jianqi Wu ◽  
...  
Keyword(s):  
Cox Regression ◽  
Expression Profiles ◽  
Treatment Strategies ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Risky Behaviors ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Mesenchymal Transition ◽  
Genome Atlas

Abstract Background Molecular classification has laid the framework for exploring glioma biology and treatment strategies. Pro-neural to mesenchymal transition (PMT) of glioma is known to be associated with aggressive phenotypes, unfavorable prognosis, and treatment resistance. Recent studies have highlighted that long non-coding RNAs (lncRNAs) are key mediators in cancer mesenchymal transition. However, the relationship between lncRNAs and PMT in glioma has not been systematically investigated. Methods Gene expression profiles from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, and Rembrandt with available clinical and genomic information were used for analyses. Bioinformatics methods such as weighted gene co-expression network analysis (WGCNA), gene set enrichment analysis (GSEA), Cox analysis, and least absolute shrinkage and selection operator (LASSO) analysis were performed. Results According to PMT scores, we confirmed that PMT status was positively associated with risky behaviors and poor prognosis in glioma. The 149 PMT-related lncRNAs were identified by WGCNA analysis, among which 10 (LINC01057, TP73-AS1, AP000695.4, LINC01503, CRNDE, OSMR-AS1, SNHG18, AC145343.2, RP11-25K21.6, RP11-38L15.2) with significant prognostic value were further screened to construct a PMT-related lncRNA risk signature, which could divide cases into two groups with distinct prognoses. Multivariate Cox regression analyses indicated that the signature was an independent prognostic factor for high-grade glioma. High-risk cases were more likely to be classified as the mesenchymal subtype, which confers enhanced immunosuppressive status by recruiting macrophages, neutrophils, and regulatory T cells. Moreover, six lncRNAs of the signature could act as competing endogenous RNAs to promote PMT in glioblastoma. Conclusions We profiled PMT status in glioma and established a PMT-related 10-lncRNA signature for glioma that could independently predict glioma survival and trigger PMT, which enhanced immunosuppression.

scholarly journals Decreased Expression of CBX7 is an Independent Predictor of Poor Survival in Cervical Cancer

2021 ◽  
Author(s):  
Lanfen An ◽  
Jun Zhang ◽  
Zhishan Jin ◽  
Xia Yan ◽  
Pu Wang ◽  
...  
Keyword(s):  
Unsaturated Fatty Acids ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Cervical Squamous Cell Carcinoma ◽  
Tissue Expression ◽  
Clinicopathological Characteristics ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Potential Biomarker ◽  
Tcga Dataset

Abstract Background: CBX7, a component of the PRC1, has been investigated as a potential biomarker in human malignant neoplasias. In present study, the value of CBX7 expression in the diagnostic and prognosis of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) as examined via bioinformatics analysis of data obtained from Genotype-Tissue Expression (GTEx) database and The Cancer Genome Atlas (TCGA) database.Methods: Relationships between clinical factors and CBX7 were explored. The Kaplan-Meier method and Cox regression were used to identify the associations between clinicopathological characteristics and overall survival (OS) in CESC. Gene set enrichment analysis (GSEA) was performed using TCGA dataset. Results: Our results indicated the decreased expression of CBX7 in CESC, and difference in CBX7 expression was also identified according to age subgroups. CESC patients with decreased CBX7 expression had worse prognosis than those with high CBX7 expression. Multivariate analysis showed that CBX7 was an independent risk factor for OS. GSEA demonstrated pathways involved in the biosynthesis of unsaturated fatty acids, glycosaminoglycan biosynthesis-chondroitin sulfate, glyoxylate and dicarboxylate metabolism, nod-like receptor signaling pathway, O-glycan biosynthesis, one carbon pool by folate and protein export as differentially enriched in CESC with decreased CBX7 expression.Conclusion: We demonstrated that decreased CBX7 expression may be a potential independent biomarker for poor prognosis in CESC.

scholarly journals High expression of PIMREG predicts poor survival outcomes and is correlated with immune infiltrates in lung adenocarcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11697
Author(s):  
Feng Jiang ◽  
Min Liang ◽  
Xiaolu Huang ◽  
Wenjing Shi ◽  
Yumin Wang
Keyword(s):  
Prognostic Value ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Background PIMREG is upregulated in multiple cancer types. However, the potential role of PIMREG in lung adenocarcinoma (LUAD) remains unclear. The present study aimed to explore its clinical significance in LUAD. Methods Using the Cancer Genome Atlas (TCGA) databases, we obtained 513 samples of LUAD and 59 normal samples from the Cancer Genome Atlas (TCGA) databases to analyze the relationship between PIMREG and LUAD. We used t and Chi-square tests to evaluate the level of expression of PIMREG and its clinical implication in LUAD. The prognostic value of PIMREG in LUAD was identified through the Kaplan–Meier method, Cox regression analysis, and nomogram. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to screen biological pathways and analyze the correlation of the immune infiltrating level with the expression of PIMREG in LUAD. Results PIMREG was highly expressed in patients with LUAD. Specifically, the level of PIMREG gradually increased from pathological stage I to IV. Further, we validated the higher expression of PIMREG expressed in LUAD cell lines. Moreover, PIMREG had a high diagnostic value, with an -AUC of 0.955. Kaplan–Meier survival and Cox regression analyses revealed that the high expression of PIMREG was independently associated with poor clinical outcomes. In our prognostic nomogram, the expression of PIMREG implied a significant prognostic value. Gene set enrichment analysis (GSEA) identified that the high expression PIMREG phenotype was involved in the mitotic cell cycle, mRNA splicing, DNA repair, Rho GTPase signaling, TP53 transcriptional regulation, and translation pathways. Next, we also explored the correlation of PIMREG and tumor-immune interactions and found a negative correlation between PIMREG and the immune infiltrating level of T cells, macrophages, B cells, dendritic cells (DCs) , and CD8+ T cells in LUAD. Conclusions High levels of PIMREG correlated with poor prognosis and immune infiltrates in LUAD.

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 APLN: A potential novel biomarker for cervical cancer

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110113
Author(s):  
Yusha Chen ◽  
Xiaoqian Lin ◽  
Jinwen Zheng ◽  
Jiancui Chen ◽  
Huifeng Xue ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cox Regression ◽  
Clinical Stage ◽  
Mapk Signaling ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Receptor Interaction ◽  
Primary Therapy ◽  
Advanced Clinical Stage

Apelin (APLN) is recently demonstrated a direct association with many malignant diseases. However, its effects on cervical cancer remain unclear. This study therefore aims to evaluate the association between APLN expression and cervical cancer using publicly available data from The Cancer Genome Atlas (TCGA). The Pearson χ2 test and Fish exact test, as well as logistic regression, were used to evaluate the relationship between clinicopathological factors in cervical cancer and the expression of APLN. Additionally, the Cox regression and Kaplan-Meier methods were conducted to analyze the Overall Survival (OS) of cervical cancer patients in TCGA. Finally, gene set enrichment analysis (GSEA) was performed to establish its biological functions. High expression of APLN in cervical cancer was significantly associated with a more advanced clinical stage (OR = 1.91 (1.21–3.05) for Stage II, Stage III, and Stage IV vs Stage I, p = 0.006). Additionally, it was associated with poor outcome after primary therapy (OR = 2.14 (1.03–4.59) for Progressive Disease (PD), Stable Disease (SD), and Partial Response (PR) vs Complete Remission (CR), p = 0.045) and high histologic grade (OR = 1.67 (1.03–2.72) for G3 and G4 vs G1 and G2, p = 0.037). Moreover, multivariate analysis showed that high expression of APLN was associated with a shorter OS. GSEA demonstrated that six KEGG pathways, including PPAR signaling, ECM-receptor interaction, focal adhesion, MAPK signaling, TGF-beta signaling, and Gap junction pathways were differentially enriched in the high expression APLN phenotype. The recent study suggests that APLN plays an important role in the progression of cervical cancer and might be a promising prognostic biomarker of the disease.

scholarly journals Development of a Novel Prognostic Signature Based on Antigen Processing and Presentation in Patients with Breast Cancer

2021 ◽  
Vol 27 ◽  
Author(s):  
Aoshuang Qi ◽  
Mingyi Ju ◽  
Yinfeng Liu ◽  
Jia Bi ◽  
Qian Wei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Antigen Processing ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Gene Set ◽  
Antigen Processing And Presentation

Background: Complex antigen processing and presentation processes are involved in the development and progression of breast cancer (BC). A single biomarker is unlikely to adequately reflect the complex interplay between immune cells and cancer; however, there have been few attempts to find a robust antigen processing and presentation-related signature to predict the survival outcome of BC patients with respect to tumor immunology. Therefore, we aimed to develop an accurate gene signature based on immune-related genes for prognosis prediction of BC.Methods: Information on BC patients was obtained from The Cancer Genome Atlas. Gene set enrichment analysis was used to confirm the gene set related to antigen processing and presentation that contributed to BC. Cox proportional regression, multivariate Cox regression, and stratified analysis were used to identify the prognostic power of the gene signature. Differentially expressed mRNAs between high- and low-risk groups were determined by KEGG analysis.Results: A three-gene signature comprising HSPA5 (heat shock protein family A member 5), PSME2 (proteasome activator subunit 2), and HLA-F (major histocompatibility complex, class I, F) was significantly associated with OS. HSPA5 and PSME2 were protective (hazard ratio (HR) < 1), and HLA-F was risky (HR > 1). Risk score, estrogen receptor (ER), progesterone receptor (PR) and PD-L1 were independent prognostic indicators. KIT and ACACB may have important roles in the mechanism by which the gene signature regulates prognosis of BC.Conclusion: The proposed three-gene signature is a promising biomarker for estimating survival outcomes in BC patients.

scholarly journals Mining novel cell glycolysis related gene markers that can predict the survival of colon adenocarcinoma patients

2020 ◽  
Vol 40 (8) ◽  
Author(s):  
Sihan Chen ◽  
Guodong Cao ◽  
Wei Wu ◽  
Yida Lu ◽  
Xiaobo He ◽  
...  
Keyword(s):  
Cox Regression ◽  
Mechanistic Model ◽  
Single Gene ◽  
Colon Adenocarcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Gene Markers ◽  
Cox Regression Analysis

Abstract Colon adenocarcinoma (COAD) is a malignant gastrointestinal tumor, often occurring in the left colon, which is regulated by glycolysis-related processes. In past studies, multiple genes that influence the prognosis for survival have been discovered through bioinformatics analysis. However, the prediction of disease prognosis using a single gene is not an accurate method. In the present study, a mechanistic model was established to achieve better prediction for the prognosis of COAD. COAD-related data downloaded from The Cancer Genome Atlas (TCGA) were correlated with the glycolysis process using gene set enrichment analysis (GSEA) to determine the glycolysis-related genes that regulate COAD. Using COX regression analysis, glycolysis-related genes associated with the prognosis of COAD were identified, and the genes screened to establish a predictive model. The risk scores of this model were correlated with relevant clinical data to obtain a connection diagram between the model and survival rate, tumor characteristic data, etc. Finally, genes in the model were correlated with cells in the tumor microenvironment, finding that they affected specific immune cells in the model. Seven genes related to glycolysis were identified (PPARGC1A, DLAT, 6PC2, P4HA1, STC2, ANKZF1, and GPC1), which affect the prognosis of patients with COAD and constitute the model for prediction of survival of COAD patients.

scholarly journals Identification of the HMMR Gene as a Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma Based on Integrated Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Honglan Guo ◽  
Qinqiao Fan
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Roc Curve Analysis ◽  
Cox Regression Analysis ◽  
Normal Tissues

Background. We aimed to investigate the expression of the hyaluronan-mediated motility receptor (HMMR) gene in hepatocellular carcinoma (HCC) and nonneoplastic tissues and to investigate the diagnostic and prognostic value of HMMR. Method. With the reuse of the publicly available The Cancer Genome Atlas (TCGA) data, 374 HCC patients and 50 nonneoplastic tissues were used to investigate the diagnostic and prognostic values of HMMR genes by receiver operating characteristic (ROC) curve analysis and survival analysis. All patients were divided into low- and high-expression groups based on the median value of HMMR expression level. Univariate and multivariate Cox regression analysis were used to identify prognostic factors. Gene set enrichment analysis (GSEA) was performed to explore the potential mechanism of the HMMR genes involved in HCC. The diagnostic and prognostic values were further validated in an external cohort from the International Cancer Genome Consortium (ICGC). Results. HMMR mRNA expression was significantly elevated in HCC tissues compared with that in normal tissues from both TCGA and the ICGC cohorts (all P values <0.001). Increased HMMR expression was significantly associated with histologic grade, pathological stage, and survival status (all P values <0.05). The area under the ROC curve for HMMR expression in HCC and normal tissues was 0.969 (95% CI: 0.948–0.983) in the TCGA cohort and 0.956 (95% CI: 0.932–0.973) in the ICGC cohort. Patients with high HMMR expression had a poor prognosis than patients with low expression group in both cohorts (all P < 0.001 ). Univariate and multivariate analysis also showed that HMMR is an independent predictor factor associated with overall survival in both cohorts (all P values <0.001). GSEA showed that genes upregulated in the high-HMMR HCC subgroup were mainly significantly enriched in the cell cycle pathway, pathways in cancer, and P53 signaling pathway. Conclusion. HMMR is expressed at high levels in HCC. HMMR overexpression may be an unfavorable prognostic factor for HCC.

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