Mine TCGA Database for Tumor Microenvironment-Related Genes of Prognostic value in lung squamous cell carcinoma

2020 ◽  
Author(s):  
Xiao Chen ◽  
Rui Li ◽  
Yun-Hong Yin ◽  
Xiao Liu ◽  
Xi-Jia Zhou ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Cells ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Hub Genes

Abstract Background: Tumor microenvironment (TME) plays a significant role in the development of cancer. However, the roles of TME in lung squamous cell carcinoma (LUSC) are not well studied. In our study, we aimed to identify differentially expressed tumor microenvironment-related genes as biomarker for predicting the prognosis of LUSC.Methods: We combined The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression data (ESTIMATE) datasets to identified differentially expressed genes in lung squamous cell carcinoma microenvironment. Then, functional enrichment analysis and protein-protein interaction (PPI) network were conducted. The top six genes in the PPI network were regarded as tumor microenvironment-related hub genes. Finally, the relationship between hub genes and tumor-infiltrating immune cells was deciphered using TIMER.Results: Our study revealed that immune and stromal scores are associated with specific clinicopathologic variables in LUSC. These variables include gender, age, distant metastasis and prognosis. In addition, a total of 874 upregulated and 72 downregulated genes were identified. Functional enrichment analysis demonstrated a correlation between DEGs and the tumor microenvironment, tumor immune cells differentiation and activation. C3AR1, CSF1R, CCL2, CCR1, TYROBP, CD14were selected as the hub genes. A positive correlation was obtained between the expression of hub genes and the abundance of six immune cells.Conclusions: The results of the present study showed that ESTIMATE algorithm-based stromal and immune scores may be a reference indicator of cancer prognosis. We identified five TME-related genes, which could be used to predict the prognosis of LUSC patients.

scholarly journals Screening and Identification of Potential Biomarkers Associated with Cutaneous Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Wenxing Su ◽  
Biao Huang ◽  
Qingyi Zhang ◽  
Wei Han ◽  
Lu An ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Cutaneous Squamous Cell Carcinoma ◽  
Functional Enrichment ◽  
Hub Genes

Abstract Cutaneous squamous cell carcinoma (cSCC) is the leading cause of death in patients with non-melanoma skin cancers (NMSC). However, unclear pathogenesis of cSCC limits the application of molecular targeted therapy. We downloaded three microarray data (GSE2503, GSE45164 and GSE66359) from Gene Expression Omnibus (GEO) and screened out their common difference genes between tumor and non-tumor tissues. Functional enrichment analysis was performed using DAVID. The STRING online website was used to construct a protein-protein interaction network (PPI), and then Cytoscape performed module analysis and degree calculation.A total of 146 DEGs was identified with significant differences, including 113 up-regulated genes and 33 down-regulated genes. The enriched functions and pathways of the DEGs include microtubule-based movement, ATP binding, cell cycle, p53 signaling pathway, oocyte meiosis and PLK1 signaling events. Nine hub genes were identified, namely CDK1, AURKA, RRM2, CENPE, CCNB1, KIAA0101, ZWINT, TOP2A, ASPM. The differential expression of these genes has been verified in other data sets. By integrated bioinformatic analysis, the hub genes identified in this study elucidated the molecular mechanism of the pathogenesis and progression of cSCC, and are expected to become future biomarkers or therapeutic targets.

scholarly journals Screening and Identification of Novel Biomarkers Associated with Cutaneous Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Wenxing Su ◽  
Biao Huang ◽  
Wei Han ◽  
Lu An ◽  
Yi Guan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Cutaneous Squamous Cell Carcinoma ◽  
Functional Enrichment ◽  
Data Sets ◽  
Hub Genes

Abstract Background: Cutaneous squamous cell carcinoma (cSCC) is the leading cause of death in patients with non-melanoma skin cancers (NMSC). However, unclear pathogenesis of cSCC limits the application of molecular targeted therapy. Results: To identify the hub genes in the pathogenesis and progression of cSCC, we downloaded the microarray data sets GSE2503, GSE45164 and GSE66359 from the Gene Expression Omnibus (GEO) database, and identified differentially expressed genes (DEGs) between tumor and non-tumor tissues. Functional enrichment analysis was performed using DAVID. The STRING online website was used to construct a protein-protein interaction network (PPI), and then Cytoscape performed module analysis and degree calculation. 146 DEGs were identified with significant differences, including 113 up-regulated genes and 33 down-regulated genes. The enriched functions and pathways of the DEGs include microtubule-based movement, ATP binding, cell cycle, p53 signaling pathway, oocyte meiosis and PLK1 signaling events. Nine hub genes were identified, namely CDK1, AURKA, RRM2, CENPE, CCNB1, KIAA0101, ZWINT, TOP2A, ASPM. The differential expression of these genes has been verified in other data sets. In addition, the ROC curve also confirmed their ability to predict disease. Conclusion: By integrated bioinformatic analysis, the DEGs and hub genes identified in this study elucidated the molecular mechanism of the pathogenesis and progression of cSCC, and are expected to become future biomarkers or therapeutic targets.

scholarly journals Bioinformatics-based analysis of the lncRNA–miRNA–mRNA and TF regulatory networks reveals functional genes in esophageal squamous cell carcinoma

2020 ◽  
Vol 40 (8) ◽  
Author(s):  
Zhimin Ye ◽  
Jun Fang ◽  
Zhun Wang ◽  
Lei Wang ◽  
Bin Li ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Diagnostic Efficiency ◽  
Hub Genes

Abstract Esophageal squamous cell carcinoma (ESCC) is a 5-year survival rate unsatisfied malignancies. The study aimed to identify the novel diagnostic and prognostic targets for ESCC. Expression profiling (GSE89102, GSE97051, and GSE59973) data were downloaded from the GEO database. Then, differentially expressed (DE) lncRNAs, DEmiRNAs, and genes (DEGs) with P-values < 0.05, and |log2FC| ≥ 2, were identified using GEO2R. Functional enrichment analysis of miRNA-related mRNAs and lncRNA co-expressed mRNA was performed. LncRNA–miRNA–mRNA, protein–protein interaction of miRNA-related mRNAs and DEGs, co-expression, and transcription factors-hub genes network were constructed. The transcriptional data, the diagnostic and prognostic value of hub genes were estimated with ONCOMINE, receiver operating characteristic (ROC) analyses, and Kaplan–Meier plotter, respectively. Also, the expressions of hub genes were assessed through qPCR and Western blot assays. The CDK1, VEGFA, PRDM10, RUNX1, CDK6, HSP90AA1, MYC, EGR1, and SOX2 used as hub genes. And among them, PRDM10, RUNX1, and CDK6 predicted worse overall survival (OS) in ESCC patients. Our results showed that the hub genes were significantly up-regulated in ESCA primary tumor tissues and cell lines, and exhibited excellent diagnostic efficiency. These results suggest that the hub genes may server as potential targets for the diagnosis and treatment of ESCC.

scholarly journals Significance of mucin type glucosaminyl (N-acetyl) transferase 3 expression in lung squamous cell carcinoma

2021 ◽  
Author(s):  
Yu-Jun Chen ◽  
Li Gao ◽  
Rui Zhang ◽  
Gang Chen ◽  
Zhen-bo Feng ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Methylation Level ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Genetic Mutation ◽  
Functional Enrichment ◽  
Standard Mean Difference

Abstract Background: The clinical significance and role of glycan synthase glucosamine (N-acetyl) transferase 3 (GCNT3) has not been investigated in lung squamous cell carcinoma (LUSC).Materials & Methods: In the present study, multiple detection technologies including tissue microarrays, external microarrays and RNA-seq were adopted for evaluating the clinic-pathological significance of GCNT3 in 1632 LUSC samples and 1478 non-cancer samples. Standard mean difference and hazard ratio value were calculated from all included datasets for assessing differential expression and prognostic value of GCNT3 in LUSC. The molecular basis underlying GCNT3 in LUSC was also explored through methylation level, genetic mutation and functional enrichment analysis of GCNT3-correlated genes in LUSC. Results: GCNT3 was obviously upregulated in LUSC samples. GCNT3 overexpression exerted unfavorable impact on the progression-free survival and overall survival of LUSC patients from GSE29013. The mRNA expression of GCNT3 was negatively correlated with methylation level of GCNT3 in LUSC and the predominant type of genetic alteration for GCNT3 in LUSC was mRNA high. Genes correlated with GCNT3 in LUSC mainly assembled in pathways such as adherens junction, p53 signaling pathway, protein digestion and absorption pathway. Conclusions: In conclusion, overexpressed GCNT3 had clinical potential as therapeutic target for LUSC.

scholarly journals Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of esophageal squamous cell carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Mingdi Liu ◽  
Faping Li ◽  
Bin Liu ◽  
Yongping Jian ◽  
Dan Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment

Abstract Background As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC). Methods ESTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC. Results Based on the immune and stromal scores, ESCC samples were divided into high and low score groups and 299 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in muscle-related function. Prognostic genes including COL9A3, GFRA2, and VSIG4 were used to establish a risk prediction model using Cox regression analyses. Then multivariate analysis showed that COL9A3 was an independent discriminator of a better prognosis. Kaplan–Meier survival analysis showed that the expression of COL9A3 was significantly correlated with the overall survival of ESCC patients. The area under the curve for the risk model in predicting 1- and 3- year survival rates were 0.660 and 0.942, respectively. The risk score was negatively correlated with plasma cells, while positively correlated with the proportions of activated CD4 memory T cells, M1 Macrophages and M2 Macrophages (p < 0.001 for each comparison). Gene set enrichment analysis suggested that both immune response and immune system process gene sets were significantly enriched in high-risk group. Conclusions Our study provided a comprehensive understanding of the TME in ESCC patients. The establishment of the risk model is valuable for the early identification of high-risk patients to facilitate individualized treatment and improve the possibility of immunotherapy response.

scholarly journals Identification of novel immunomodulators in lung squamous cell carcinoma based on transcriptomic data

2021 ◽  
Vol 19 (2) ◽  
pp. 1843-1860
Author(s):  
Xin Lin ◽  
◽  
Xingyuan Li ◽  
Binqiang Ma ◽  
Lihua Hang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Cells ◽  
Survival Data ◽  
Prognostic Model ◽  
Patient Survival ◽  
Lung Squamous Cell Carcinoma ◽  
Training Data

<abstract> <p>Cells in the tumor microenvironment are well known for their role in cancer development and prognosis. The processes of genetic changes and possible remodeling in the tumor microenvironment of lung squamous cell carcinoma, on the other hand, are mainly unclear. In this investigation, 1164 immunological differentially expressed genes (DEGs) were shown to have predictive significance. A prognostic model with high prediction accuracy was constructed using these genes and survival data. There were 1020 upregulated genes and 144 downregulated genes found, with 57 genes found to be important in the development of LUSC. We used least absolute shrinkage and selection operator (LASSO) regression analysis to determine the risk profiles of 9 genes based on the expression values of 57 prognosis-related genes. The AUCs of the developed prognostic model for predicting patient survival at 1, 3, and 5 years were 0.66, 0.61, and 0.63, respectively, based on the training data. For immune-correlation analysis in this survival model, we chose IGLC7, which was seen to predict patient survival with high accuracy. The effects on immune cells and synergistic effects with other immunomodulators were then investigated. We discovered that IGLC7 is involved in immune response and inflammatory activity using gene ontology analysis and genomic sequence variance analysis (GSVA), with a potential effect, especially on B cells and T cells. In conclusion, IGLC7 expression levels are related to the malignancy of LUSC based on the constructed prognostic model and can thus be a therapeutic target for patients with LUSC. Furthermore, IGLC7 may work in concert with other immune checkpoint members to regulate the immune microenvironment of LUSC. These discoveries might lead to a fresh understanding of the complicated interactions between cancer cells and the tumor microenvironment, particularly the population of immune cells, and a novel approach to future immunotherapeutic treatments for patients with LUSC.</p> </abstract>

scholarly journals Profiles of Immune Cell Infiltration and Immune-Related Genes in the Tumor Microenvironment of Esophageal Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Mingdi Liu ◽  
Faping Li ◽  
Bin Liu ◽  
Yongping Jian ◽  
Dan Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment

Abstract Backgrounds: As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC).Methods: ESTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC. Results: Based on the immune and stromal scores, ESCC samples were divided into high and low score groups and 299 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in muscle-related function. Prognostic genes including COL9A3, GFRA2, and VSIG4 were used to establish a risk prediction model using Cox regression analyses. Then multivariate analysis showed that COL9A3 was an independent discriminator of a better prognosis. Kaplan-Meier survival analysis showed that the expression of COL9A3 was significantly correlated with the overall survival of ESCC patients. The area under the curve for the risk model in predicting 1- and 3- year survival rates were 0.660 and 0.942, respectively. The risk score was negatively correlated with plasma cells, while positively correlated with the proportions of activated CD4 memory T cells, M1 Macrophages and M2 Macrophages (P<0.001 for each comparison). Gene set enrichment analysis suggested that both immune response and immune system process gene sets were significantly enriched in high-risk group.Conclusions: Our study provided a comprehensive understanding of the TME in ESCC patients. The establishment of the risk model is valuable for the early identification of high-risk patients to facilitate individualized treatment and improve the possibility of immunotherapy response.

scholarly journals Low Expression of ADCY4 Predicts Worse Survival of Lung Squamous Cell Carcinoma Based on Integrated Analysis and Immunohistochemical Verification

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhicong Liu ◽  
Lixin Ru ◽  
Zhenchao Ma
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Real World ◽  
Lung Squamous Cell Carcinoma ◽  
Functional Enrichment ◽  
Cell Junctions ◽  
Integrated Analysis ◽  
Hub Genes ◽  
The Real

PurposeThe molecular mechanism underlying the carcinogenesis and development of lung squamous cell carcinoma (LUSC) has not been sufficiently elucidated. This analysis was performed to find pivotal genes and explore their prognostic roles in LUSC.MethodsA microarray dataset from GEO (GSE19188) and a TCGA-LUSC dataset were used to identify differentially co-expressed genes through Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. We conducted functional enrichment analyses of differentially co-expressed genes and established a protein-protein interaction (PPI) network. Then, we identified the top 10 hub genes using the Maximal Clique Centrality (MCC) algorithm. We performed overall survival (OS) analysis of these hub genes among LUSC cases. GSEA analyses of survival-related hub genes were conducted. Ultimately, the GEO and The Human Protein Atlas (THPA) databases and immunohistochemistry (IHC) results from the real world were used to verify our findings.ResultsA list of 576 differentially co-expressed genes were selected. Functional enrichment analysis indicated that regulation of vasculature development, cell−cell junctions, actin binding and PPAR signaling pathways were mainly enriched. The top 10 hub genes were selected according to the ranking of MCC scores, and 5 genes were closely correlated with OS of LUSC. Additionally, GSEA analysis showed that spliceosome and cell adhesion molecules were associated with the expression of GNG11 and ADCY4, respectively. The GSE30219 and THPA databases and IHC results from the real world indicated that although GNG11 was not detected, ADCY4 was obviously downregulated in LUSC tissues at the mRNA and protein levels.ConclusionsThis analysis showed that survival-related hub genes are highly correlated to the tumorigenesis and development of LUSC. Additionally, ADCY4 is a candidate therapeutic and prognostic biomarker of LUSC.

scholarly journals High Expression Levels of CDK1 and CDC20 in Patients With Lung Squamous Cell Carcinoma are Associated With Worse Prognosis

2021 ◽  
Vol 8 ◽  
Author(s):  
Huan Deng ◽  
Qingqing Hang ◽  
Dijian Shen ◽  
Hangjie Ying ◽  
Yibi Zhang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Expression Patterns ◽  
Lung Squamous Cell Carcinoma ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Basic Experiments

Purpose: Progress related to the early detection and molecular targeted therapy of lung squamous cell carcinoma (LUSC) remains limited. The goal of our study was to identify key candidate indicators of LUSC.Methods: Three microarray datasets (GSE33532, GSE30219 and GSE19188) were applied to find differentially expressed genes (DEGs). Functional enrichment analyses of DEGs were carried out, and their protein-protein interaction (PPI) network was established. Hub genes were chosen from the PPI network according to their degree scores. Then, overall survival (OS) analyses of hub genes were carried out using Kaplan-Meier plotter, and their GSEA analyses were performed. Public databases were used to verify the expression patterns of CDK1 and CDC20. Furthermore, basic experiments were performed to verify our findings.Results: A total of 1,366 DEGs were identified, containing 669 downregulated and 697 upregulated DEGs. These DEGs were primarily enriched in cell cycle, chromosome centromeric region and nuclear division. Seventeen hub genes were selected from PPI network. Survival analyses demonstrated that CDK1 and CDC20 were closely associated with OS. GSEA analyses revealed that cell cycle, DNA replication, and mismatch repair were associated with CDK1 expression, while spliceosome, RNA degradation and cell cycle were correlated with CDC20 expression. Based on The Cancer Genome Atlas (TCGA) and The Human Protein Atlas (THPA) databases, CDK1 and CDC20 were upregulated in LUSC at the mRNA and protein levels. Moreover, basic experiments also supported the obvious upregulation of CDK1 and CDC20 in LUSC.Conclusion: Our study suggests and validates that CDK1 and CDC20 are potential therapeutic targets and prognostic biomarkers of LUSC.

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