scholarly journals Bioinformatics Analysis to Screen the Key Prognostic Genes in Tumor Microenvironment of Bladder Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhao Zhang ◽  
Dongshan Chen ◽  
Zeyan Li ◽  
Zhao Liu ◽  
Lei Yan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cancer Genomics ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Marker Genes ◽  
High Morbidity ◽  
Tumor Prognosis

Bladder cancer (BLCA) is the fifth most common cancer and has the features of low survival rate and high morbidity and mortality. The Cancer Genome Atlas (TCGA) is a pool of global gene expression profile and contains huge amounts of cancer genomics data, which makes it possible to inquire the relationship between gene expression and prognosis of a series of malignant tumors including BLCA. Immune and stromal cells are two major components of tumor microenvironment (TME) which play an important role in judging the prognosis of tumor and influencing the progression of malignant, inflammatory, and metabolic disorders. In our study, we conducted a quantitative analysis of immune and stromal elements based on the ESTIMATE algorithm and thus divided BLCA cases into high and low groups. Then the differentially expressed genes closely related to tumor prognosis between groups were identified and had been shown to correlate with immune response and stromal alterations, which was further confirmed by functional enrichment analysis and protein-protein interaction networks. We validated those genes through BLCA dates downloaded from ArrayExpress and thus got the marker genes to predict prognosis of BLCA. Additionally, immune cell infiltration analysis explored the correlation between the verified genes and immune cells. In conclusion, we identified a series of TME-related genes that assess the prognosis and explored the interaction between TME and tumor prognosis to guide clinical individualized treatment.

scholarly journals Construction and Validation of an Immune Cell Signature Score to Evaluate Prognosis and Therapeutic Efficacy in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Linfeng Xu ◽  
Xingxing Jian ◽  
Zhenhao Liu ◽  
Jingjing Zhao ◽  
Siwen Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Expression Profiles ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Marker Genes ◽  
High Morbidity ◽  
Therapeutic Benefits

Background: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with high morbidity and mortality worldwide. Tumor immune microenvironment (TIME) plays a pivotal role in the outcome and treatment of HCC. However, the effect of immune cell signatures (ICSs) representing the characteristics of TIME on the prognosis and therapeutic benefit of HCC patients remains to be further studied.Materials and methods: In total, the gene expression profiles of 1,447 HCC patients from several databases, i.e., The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium, and Gene Expression Omnibus, were obtained and applied. Based on a comprehensive collection of marker genes, 182 ICSs were evaluated by single sample gene set enrichment analysis. Then, by performing univariate and multivariate Cox analysis and random forest modeling, four significant signatures were selected to fit an immune cell signature score (ICSscore).Results: In this study, an ICSscore-based prognostic model was constructed to stratify HCC patients into high-risk and low-risk groups in the TCGA-LIHC cohort, which was successfully validated in two independent cohorts. Moreover, the ICSscore values were found to positively correlate with the current American Joint Committee on Cancer staging system, indicating that ICSscore could act as a comparable biomarker for HCC risk stratification. In addition, when setting the four ICSs and ICSscores as features, the classifiers can significantly distinguish treatment-responding and non-responding samples in HCC. Also, in melanoma and breast cancer, the unified ICSscore could verify samples with therapeutic benefits.Conclusion: Overall, we simplified the tedious ICS to develop the ICSscore, which can be applied successfully for prognostic stratification and therapeutic evaluation in HCC. This study provides an insight into the therapeutic predictive efficacy of prognostic ICS, and a novel ICSscore was constructed to allow future expanded application.

scholarly journals An independent poor-prognosis subtype of hepatocellular carcinoma based on the tumor microenvironment

2021 ◽  
Vol 49 (2) ◽  
pp. 030006052098064
Author(s):  
Junfeng Wang ◽  
Jianying Lou ◽  
Lei Fu ◽  
Qu Jin
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Poor Prognosis ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Using Data

Background Hepatocellular carcinoma (HCC) is a highly malignant tumor with a particularly poor prognosis. The tumor microenvironment (TME) is closely associated with tumorigenesis, progression, and treatment. However, the relationship between TME genes and HCC patient prognosis is poorly understood. Methods In this study, we identified two prognostic subtypes based on the TME using data from The Cancer Genome Atlas and Gene Expression Omnibus. The Microenvironment Cell Populations-counter method was used to evaluate immune cell infiltration in HCC. Differentially expressed genes between molecular subtypes were calculated with the Limma package, and clusterProfiler was used for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses to identify genes related to the independent subtypes. We also integrated mRNA expression data into our bioinformatics analysis. Results We identified 4227 TME-associated genes and 640 genes related to the prognosis of HCC. We defined two major subtypes (Clusters 1 and 2) based on the analysis of TME-associated gene expression. Cluster 1 was characterized by increased expression of immune-associated genes and a worse prognosis than Cluster 2. Conclusions The identification of these HCC subtypes based on the TME provides further insight into the molecular mechanisms and prediction of HCC prognosis.

scholarly journals Identification and Validation of Hub Genes Associated with Bladder Cancer by Integrated Bioinformatics and Experimental Assays

2021 ◽  
Vol 11 ◽  
Author(s):  
Kang Chen ◽  
Ji Xing ◽  
Weimin Yu ◽  
Yuqi Xia ◽  
Yunlong Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Survival Analysis ◽  
Quantitative Polymerase Chain Reaction ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
High Morbidity ◽  
Promoting Effect ◽  
Poor Overall Survival

Bladder cancer (BC) is the most common malignant tumor of the urinary system and is associated with high morbidity and mortality; however, the molecular mechanism underlying its occurrence is not clear. In this study, the gene expression profile and related clinical information of GSE13507 were downloaded from the Gene Expression Omnibus (GEO) database. RNA sequencing (RNA-seq) expression data and related clinical information were retrieved from The Cancer Genome Atlas (TCGA) database. Overlapping genes were identified by differential gene expression analysis and weighted gene co-expression network analysis (WGCNA). Then, we carried out functional enrichment analysis to understand the potential biological functions of these co-expressed genes. Finally, we performed a protein–protein interaction (PPI) analysis combined with survival analysis. Using the CytoHubba plug-in of Cytoscape, TROAP, CENPF, PRC1, AURKB, CCNB2, CDC20, TTK, CEP55, ASPM, and CDCA8 were identified as candidate central genes. According to the survival analysis, the high expression of TTK was related to the poor overall survival (OS) of patients with BC. TTK may also affect the bladder tumor microenvironment (TME) by affecting the number of immune cells. The expression level of TTK was verified by immunohistochemistry (IHC) and real-time quantitative polymerase chain reaction (RT-qPCR), and the tumor-promoting effect of TTK in BC cells was confirmed in vitro. Our results also identified the MSC-AS1/hsa-miR-664b-3p/TTK regulatory axis, which may also play an important role in the progression of BC, but further research is needed to verify this result. In summary, our results provide a new idea for accurate early diagnosis, clinical treatment, and prognosis of BC

scholarly journals Prognostic value of CLIC3 mRNA overexpression in bladder cancer

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8348
Author(s):  
Mei Chen ◽  
Shufang Zhang ◽  
Xiaohong Wen ◽  
Hui Cao ◽  
Yuanhui Gao
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Mrna Expression ◽  
Prognostic Value ◽  
Multivariate Analyses ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Normal Tissues

Background Human intracellular chloride channel 3 (CLIC3) is involved in the development of various cancers, but the expression and prognostic value of CLIC3 mRNA in bladder cancer (BC) remain unclear. Methods The gene expression data and clinical information of CLIC3 were obtained from the Gene Expression Omnibus (GEO) database and verified in the Oncomine and The Cancer Genome Atlas (TCGA) database. The expression of CLIC3 mRNA in BC tissues and adjacent normal tissues was detected by quantitative real-time polymerase chain reaction (qRT-PCR). The Kaplan-Meier method was used to analyze the relationship between the expression of CLIC3 mRNA and the prognosis of BC. Cox univariate and multivariate analyses were performed on the overall survival and tumor-specific survival of BC patients. The genes coexpressed with CLIC3 were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). CLIC3-related signal transduction pathways in BC were explored with gene set enrichment analysis (GSEA). Results The expression of CLIC3 mRNA in BC tissues was higher than that in normal tissues (P < 0.01). High CLIC3 mRNA expression was associated with age (P = 0.021) and grade (P = 0.045) in BC patients. High CLIC3 mRNA expression predicted a poor prognosis in BC patients (P < 0.05). Cox univariate and multivariate analyses showed that high CLIC3 mRNA expression was associated with tumor-specific survival in BC patients (P < 0.05). Functional enrichment analyses indicated that CLIC3 may be significantly associated with the cell cycle, focal adhesion, the extracellular matrix (ECM) receptor interaction and the P53 signaling pathway. Conclusions CLIC3 mRNA is highly expressed in BC, and its high expression is related to the adverse clinicopathological factors and prognosis of BC patients. CLIC3 can be used as a biomarker for the prognosis of BC patients.

scholarly journals Controversial T1G3 bladder cancer is the key to revealing the changes in the biological functions of bladder cancer cells

2020 ◽  
Author(s):  
Shen Pan ◽  
Yunhong Zhan ◽  
Xiaonan Chen ◽  
Bin Wu ◽  
Bitian Liu
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Cancer Cells ◽  
Interaction Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Specific Gene ◽  
Gene Sets ◽  
Bladder Cancer Cells

Abstract Background T1G3 shows a higher chance of recurrence and progression among early bladder cancer types and the available treatment option is controversial. High recurrence and progression are the problems that need to be explored and solved. Changes in the internal signals of bladder cancer cells and differential genes may be the root cause of these problems. Methods GSE120736, GSE19915, GSE19423, GSE32548 and GSE37815 datasets were obtained from Gene Expression Omnibus (GEO ) to identify differentially expressed genes (DEGs). Bladder cancer transcript data from The Cancer Genome Atlas (TCGA) were clustered into different cell-specific gene sets according to weighted gene co-expression network analysis (WGCNA). Multiple sets of databases were used for gene expression comparison, functional enrichment, and protein interaction analysis, including The Human Protein Atlas, Cancer Dependency Map, Metascape, Gene set enrichment analysis, and DisNor. Results DEGs were obtained through GEO data comparison and intersection. After WGCNA was proven to recognise cell-specific gene sets, candidate DEGs were selected and shown to be specifically expressed in cancer cells. Candidate DEGs were related to mitosis and cell cycle. Further, 12 functional candidate markers were identified from the sequencing data of 30 bladder cancer cell lines. These genes were all up-regulated and previously shown to be closely related to bladder cancer progression. Conclusions Twelve functional genes with specific differential expression in bladder cancer cells were identified. WGCNA can identify the relatively specific expression sets of different cells in bladder cancer with greater tumour heterogeneity, which provides new perspectives for future cancer research.

NT5E expression and the immune landscape of prostate cancer (PC): An analysis from The Cancer Genome Atlas database.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e16591-e16591
Author(s):  
Abhishek Tripathi ◽  
Edwin Lin ◽  
Roberto Nussenzveig ◽  
Mark Yandell ◽  
Sumanta K. Pal ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
The Cancer Genome Atlas ◽  
Effector Memory ◽  
Marker Genes ◽  
Promote Tumor Growth ◽  
Tumor Phenotype ◽  
Tcga Dataset ◽  
Tumor Expression

e16591 Background: Immune checkpoint inhibitors targeting PD-1/L1 and CTLA-4 pathway have shown modest activity in patients with advanced PC. Additional immunosuppressive mechanisms in the PC tumor microenvironment need to be investigated. Increased CD73 (encoded by NT5E) expression results in generation of immunosuppressive adenosine in the tumor microenvironment and has been associated with metastasis and poor survival in PC. Utilizing the TCGA dataset, we investigated the association of NT5E expression with the immune landscape of PC. Methods: RNA-seq data for 331 PC tumor samples and 51 normal adjacent tissue (NAT) samples was downloaded and log2 transformed. Patients were split into low, intermediate, and high expression groups based on NT5E expression (≤ -1, -1 to 1 and ≥1 standard deviation from the overall mean) in tumor and NAT. A tumor inflammation signature (TIS) reflecting an inflamed tumor phenotype was calculated based on the averaged tumor expression of 18 previously validated genes (Ayers et al, 2017). Abundance of infiltrating immune cell subsets was estimated based on expression of previously identified 782 immune metagenes (Charoentong et al, 2017). Immune cell abundance scores and TIS were compared between NT5E expression groups using the Mann-Whitney U test and the Bonferroni correction was used to control for false discovery rate. Results: NT5E expression in NAT was not associated with the TIS or expression of immune cell marker genes. In contrast, NT5E expression in tumor tissue correlated positively with TIS (P < 0.001). Compared to tumors with low NT5E expression, those in high NT5E expression group had higher expression of central memory CD4+, effector memory CD8+, type 1 helper, NK and regulatory T (Treg) cell markers. Conclusions: In our analysis, NT5E expression correlated with markers of inflamed tumor phenotype in PC. Although NT5E expression was associated with higher CD8+and CD4+ T cells, concurrent increase in Tregs could inhibit the infiltrating lymphocytes and promote tumor growth. Our findings indicate a possible role for the adenosine pathway as a mediator of immunosuppression in PC and a potential therapeutic target. AT and EL: Equal contribution

scholarly journals Novel immune-related genes in the tumor microenvironment with prognostic value in breast cancer

2020 ◽  
Author(s):  
Wen Tan ◽  
Maomao Liu ◽  
Liangshan Wang ◽  
Yang Guo ◽  
Changsheng Wei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Overall Survival ◽  
Tumor Microenvironment ◽  
T Cell Activation ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Network Analyses ◽  
Immune Score ◽  
Go Terms

Abstract Background: Breast cancer is one of the most frequently diagnosed cancers among women worldwide. Alterations in the tumor microenvironment (TME) have been increasingly recognized as key in the development and progression of breast cancer in recent years. To deeply comprehend the gene expression profiling of the TME and identify immunological targets, as well as determine the relationship between gene expression and different prognoses is highly critical. Results: The stromal/immune scores of breast cancer patients from The Cancer Genome Atlas were employed to comprehensively evaluate the TME. Although the TME did not correlate with the stages of breast cancer, it was closely associated with the subtypes of breast cancer and gene mutations (CDH1, TP53 and PTEN), and had immunological characteristics. Based on Gene Ontology (GO) functional enrichment analysis, the upregulated genes from the high vs low immune score groups were mainly involved in T cell activation, the external side of the plasma membrane, and receptor ligand activity. We further analyzed and screened the overlapping genes of the top 3 GO terms and upregulated differentially expressed genes (DEGs). Overall survival, time-dependent receiver operating characteristic (ROC), and protein-protein interaction (PPI) network analyses revealed that the genes of the top GO terms of the upregulated DEGs from the high vs low immune score groups exhibited better prognosis in breast cancer; 15 of them were related to good prognosis in breast cancer, especially CD226 and KLRC4-KLRK1.Conclusions: High CD226 and KLRC4-KLRK1 expression levels were identified and validated to correlate with better overall survival in specific stages or subtypes of breast cancer. CD226, KLRC4-KLRK1 and other new targets seem to be promising avenues for promoting antitumor targeted immunotherapy in breast cancer.

scholarly journals Identification and Validation of Hub Genes Associated With Hepatocellular Carcinoma Via Integrated Bioinformatics Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Sumei Wang ◽  
Zuoli Song ◽  
Bing Tan ◽  
Jinjuan Zhang ◽  
Jiandong Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Survival Analysis ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
High Morbidity ◽  
Hub Genes ◽  
Study Gene Expression

Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver, with high morbidity and mortality, yet its molecular mechanisms of tumorigenesis are still unclear. In this study, gene expression profile of GSE62232 was downloaded from the Gene Expression Omnibus (GEO). The RNA-seq expression data and relative clinical information were retrieved from the Cancer Genome Atlas (TCGA) database. The datasets were analyzed by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to obtain the overlapping genes. Then, we performed a functional enrichment analysis to understand the potential biological functions of these co-expression genes. Finally, we constructed the protein-protein interaction (PPI) analysis combined with survival analysis. MARCO, CLEC4M, FCGR2B, LYVE1, TIMD4, STAB2, CFP, CLEC4G, CLEC1B, FCN2, FCN3 and FOXO1 were identified as the candidate hub genes using the CytoHubba plugin of Cytoscape. Based on survival analysis, the lower expression of FCN3 and FOXO1 were associated with worse overall survival (OS) in HCC patients. Furthermore, the expression levels of FCN3 and FOXO1 were validated by the Human Protein Atlas (HPA) database and the qRT-PCR. In summary, our findings contribute new ideas for the precise early diagnosis, clinical treatment and prognosis of HCC in the future.

scholarly journals Characteristics of the Immune Cell Infiltration Landscape in Gastric Cancer to Assistant Immunotherapy

2022 ◽  
Vol 12 ◽  
Author(s):  
Chenlu Li ◽  
Jingjing Pan ◽  
Yinyan Jiang ◽  
Yan Yu ◽  
Zhenlin Jin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Signaling Pathways ◽  
Poor Prognosis ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Therapeutic Responses

Background: Gastric cancer (GC) was usually associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. It is urgent to screen reliable indices especially immunotherapy-associated parameters that can predict the therapeutic responses to immunotherapy of GC patients.Methods: Gene expression profile of 854 GC patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets (GSE84433) with their corresponding clinical and somatic mutation data. Based on immune cell infiltration (ICI) levels, molecular clustering classification was performed to identify subtypes and ICI scores in GC patients. After functional enrichment analysis of subtypes, we further explored the correlation between ICI scores and Tumor Mutation Burden (TMB) and the significance in clinical immunotherapy response.Results: Three subtypes were identified based on ICI scores with distinct immunological and prognostic characteristics. The ICI-cluster C, associated with better outcomes, was characterized by significantly higher stromal and immune scores, T lymphocytes infiltration and up-regulation of PD-L1. ICI scores were identified through using principal component analysis (PCA) and the low ICI scores were consistent with the increased TMB and the immune-activating signaling pathways. Contrarily, the high-ICI score cluster was involved in the immunosuppressive pathways, such as TGF-beta, MAPK and WNT signaling pathways, which might be responsible for poor prognosis of GC. External immunotherapy and chemotherapy cohorts validated the patients with lower ICI scores exhibited significant therapeutic responses and clinical benefits.Conclusion: This study elucidated that ICI score could sever as an effective prognostic and predictive indicator for immunotherapy in GC. These findings indicated that the systematic assessment of tumor ICI landscapes and identification of ICI scores have crucial clinical implications and facilitate tailoring optimal immunotherapeutic strategies.

scholarly journals Identification of Tumor Microenvironment-related Prognostic Genes in Colorectal Cancer based on Bioinformatic Methods

2021 ◽  
Author(s):  
Yi Liu ◽  
Long Cheng ◽  
Chao Li ◽  
Chen Zhang ◽  
Wang Lei ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Networks ◽  
Chemokine Signaling ◽  
Chemokine Signaling Pathway

Abstract Colorectal cancer (CRC) ranks fourth among the deadliest cancers globally, and the progression is highly affected by the tumor microenvironment (TME). This study explores the relationship between TME and colorectal cancer prognosis and identifies prognostic genes related to the CRC microenvironment. We collected the gene expression data from The Cancer Genome Atlas (TCGA) and calculated the scores of stromal/immune cells and their relations to clinical outcomes in colorectal cancer by the ESTIMATE algorithm. Lower immune scores were significantly related to malignant progression of CRC (stage, p=0.014; metastasis, p=0.001). We screened 292 differentially expressed genes (DEGs) by dividing CRC cases into high and low stromal/immune score groups. Functional enrichment analyses and protein-protein interaction (PPI) networks illustrated that these DEGs were closely involved in immune response, cytokine-cytokine receptor interaction, and chemokine signaling pathway. Six DEGs (FABP4, MEOX2, MMP12, ERMN, TNFAIP6, and CHST11) with prognostic value were identified by survival analysis and validated in an independent cohort (GSE17386). The six DEGs were significantly related to immune cell infiltration levels based on the Tumor Immune Estimation Resource (TIMER). The results might contribute to discovering new diagnostic and prognostic biomarkers and new treatment targets for colorectal cancer.

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