Comprehensive Analysis of ESRRA in Endometrial Cancer

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.

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Uncovering of the Association Between m5C Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

10.21203/rs.3.rs-580707/v1 ◽

2021 ◽

Author(s):

Xinyu Gu ◽

Haibo Zhou ◽

Qingfei Chu ◽

Qiuxian Zheng ◽

Jing Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cells ◽

Immune Cell ◽

Enrichment Analysis ◽

Tumour Microenvironment ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Gene Set ◽

Normal Tissues

Abstract Background: 5-Methylcytosine (m5C) plays essential roles in hepatocellular carcinoma (HCC), but the association between m5C regulation and immune cell infiltration in HCC has not yet been clarified.Methods: In this study, we analysed 371 patients with HCC from The Cancer Genome Atlas (TCGA) database, and the expression of 13 m5C regulators was investigated. Additionally, gene set variation analysis (GSVA), unsupervised clustering analysis, single-sample gene set enrichment analysis (ssGSEA), correlation analysis, and immunohistochemical (IHC) staining were performed.Results: Among the 371 patients, 41 had mutations in m5C regulators, the frequency of which was 11.26%. Then, we identified three m5C modification patterns that had obvious tumour microenvironment (TME) cell infiltration characteristics. Cluster-1 had an immune rejection phenotype; Cluster-2 had an immunoinflammatory phenotype; and Cluster-3 had an immune desert phenotype. In addition, we found that DNMT1 was highly expressed in tumour tissues compared with normal tissues in a tissue microarray (TMA) and that it was positively correlated with many TME-infiltrating immune cells. High expression of the m5C regulator DNMT1 was related to a poor prognosis in patients with HCC. Furthermore, we developed three Immu-clusters that were consistent with the immune characteristics of the m5C methylation modification patterns. We also discovered differences in the levels of immune cells and expression of chemokines and cytokines among the three Immu-clusters.Conclusions: Our work revealed the association between m5C modification and immune regulators in the TME. These findings also suggest that DNMT1 has great potential as a prognostic biomarker and therapeutic target for HCC.

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Multiomic analysis of the function of SPOCK1 across cancers: an integrated bioinformatics approach

Journal of International Medical Research ◽

10.1177/0300060520962659 ◽

2021 ◽

Vol 49 (6) ◽

pp. 030006052096265

Author(s):

Jie Han ◽

Yihui Rong ◽

Xudong Gao

Keyword(s):

Gene Expression ◽

Cancer Progression ◽

Immune Cells ◽

Immune Cell ◽

Cancer Cell Line ◽

Enrichment Analysis ◽

Tissue Expression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Normal Tissues

Objective To investigate SPARC (osteonectin), cwcv and kazal like domains proteoglycan 1 ( SPOCK1) gene expression across The Cancer Genome Atlas (TCGA) cancers, both in cancer versus normal tissues and in different stages across the cancer types. Methods This integrated bioinformatics study used data from several bioinformatics databases (Cancer Cell Line Encyclopedia, Genotype-Tissue Expression, TCGA, Tumor Immune Estimation Resource [TIMER]) to define the expression pattern of the SPOCK1 gene. A survival analysis was undertaken across the cancers. The search tool for retrieval of interacting genes (STRING) database was used to identify proteins that interacted with SPOCK1. Gene Set Enrichment Analysis was conducted to determine pathway enrichment. The TIMER database was used to explore the correlation between SPOCK1 and immune cell infiltration. Results This multiomic analysis showed that the SPOCK1 gene was expressed differently between normal tissues and tumours in several cancers and that it was involved in cancer progression. The overexpression of the SPOCK1 gene was associated with poor clinical outcomes. Analysis of gene expression and tumour-infiltrating immune cells showed that SPOCK1 correlated with several immune cells across cancers. Conclusions This research showed that SPOCK1 might serve as a new target for several cancer therapies in the future.

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DNM1: A Prognostic Biomarker Associated with Immune Infiltration in Colon Cancer—A Study Based on TCGA Database

BioMed Research International ◽

10.1155/2021/4896106 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Mingchao Hu ◽

Jianchun Gu ◽

Wenzhao Su ◽

Zhenjie Zhang ◽

Baosong Zhu ◽

...

Keyword(s):

Colon Cancer ◽

Immune Cell ◽

Cox Regression ◽

Univariate Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Receptor Interaction ◽

Regression Analyses ◽

Normal Tissues

Aim. The aim of our work was to determine the utility of DNM1 as a biomarker for the diagnosis and prognosis of colon cancer (CC). Methods. DNM1 expression variations in CC vs. normal tissues were investigated using The Cancer Genome Atlas (TCGA) database. The association of DNM1 expression levels with the clinicopathological variables in CC prognosis was investigated using logistic regression analyses. Independent prognostic factors for CC were evaluated using univariate and multivariate Cox regression analyses. The correlation between DNM1 expression and immune cell infiltration was estimated using single-sample Gene Set Enrichment Analysis (ssGSEA). Results. DNM1 expression in CC tissues was significantly higher than that in normal tissues. High DNM1 expression was significantly correlated with M stage, N stage, perineural invasion and lymphatic invasion and predicted poor prognosis. The univariate analysis highlighted that DNM1 was an independent CC risk factor. Results of ssGSEA showed that DNM1 was linked to several cancer-related pathways, including the neuroactive ligand-receptor interaction, hypertrophic cardiomyopathy, ECM-receptor interaction, dilated cardiomyopathy, and calcium signaling pathway. Moreover, DNM1 expression was positively correlated with the level of infiltration by Neutrophils, Tregs, NK cells, and Macrophages. Conclusion. DNM1 has a significant function and has diagnostic and prognostic potential for CC.

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ADAMTS12 acts as a tumor microenvironment related cancer promoter in gastric cancer

Scientific Reports ◽

10.1038/s41598-021-90330-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yangming Hou ◽

Yingjuan Xu ◽

Dequan Wu

Keyword(s):

Gastric Cancer ◽

Tumor Microenvironment ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Tumor Promoter ◽

Protein Protein Interaction ◽

Oxidative Phosphorylation Pathway ◽

Cox Proportional Hazard Regression

AbstractThe infiltration degree of immune and stromal cells has been shown clinically significant in tumor microenvironment (TME). However, the utility of stromal and immune components in Gastric cancer (GC) has not been investigated in detail. In the present study, ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cell (TIC) in GC cohort, including 415 cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were screened by Cox proportional hazard regression analysis and protein–protein interaction (PPI) network construction. Then ADAMTS12 was regarded as one of the most predictive factors. Further analysis showed that ADAMTS12 expression was significantly higher in tumor samples and correlated with poor prognosis. Gene Set Enrichment Analysis (GSEA) indicated that in high ADAMTS12 expression group gene sets were mainly enriched in cancer and immune-related activities. In the low ADAMTS12 expression group, the genes were enriched in the oxidative phosphorylation pathway. CIBERSORT analysis for the proportion of TICs revealed that ADAMTS12 expression was positively correlated with Macrophages M0/M1/M2 and negatively correlated with T cells follicular helper. Therefore, ADAMTS12 might be a tumor promoter and responsible for TME status and tumor energy metabolic conversion.

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Enolase 1 Correlated With Cancer Progression and Immune-Infiltrating in Multiple Cancer Types: A Pan-Cancer Analysis

Frontiers in Oncology ◽

10.3389/fonc.2020.593706 ◽

2021 ◽

Vol 10 ◽

Author(s):

Wenhua Xu ◽

Wenna Yang ◽

Chunfeng Wu ◽

Xiaocong Ma ◽

Haoyu Li ◽

...

Keyword(s):

Cancer Progression ◽

Stress Protein ◽

Enrichment Analysis ◽

Tumor Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Multiple Cancer ◽

Clinical Prognosis ◽

Multiple Tumor ◽

Normal Tissues

Enolase 1 (ENO1) is an oxidative stress protein expressed in endothelial cells. This study aimed to investigate the correlation of ENO1 with prognosis, tumor stage, and levels of tumor-infiltrating immune cells in multiple cancers. ENO1 expression and its influence on tumor stage and clinical prognosis were analyzed by UCSC Xena browser, Gene Expression Profiling Interactive Analysis (GEPIA), The Cancer Genome Atlas (TCGA), and GTEx Portal. The ENO1 mutation analysis was performed by cBio Portal, and demonstrated ENO1 mutation (1.8%) did not impact on tumor prognosis. The relationship between ENO1 expression and tumor immunity was analyzed by Tumor Immune Estimation Resource (TIMER) and GEPIA. The potential functions of ENO1 in pathways were investigated by Gene Set Enrichment Analysis. ENO1 expression was significantly different in tumor and corresponding normal tissues. ENO1 expression in multiple tumor tissues correlated with prognosis and stage. ENO1 showed correlation with immune infiltrates including B cells, CD8+ and CD4+ T cells, macrophages, neutrophils, and dendritic cells, and tumor purity. ENO1 was proved to be involved in DNA replication, cell cycle, apoptosis, glycolysis process, and other processes. These findings indicate that ENO1 is a potential prognostic biomarker that correlates with cancer progression immune infiltration.

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Identification and Validation of an 6-Metabolism-Related Gene Signature and Its Correlation With Immune Checkpoint in Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.783934 ◽

2021 ◽

Vol 11 ◽

Author(s):

He Ren ◽

Wanjing Li ◽

Xin Liu ◽

Shuliang Li ◽

Hao Guo ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Checkpoint ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Signature ◽

Clinicopathological Characteristics ◽

Gene Set Enrichment Analysis ◽

Operating Characteristics ◽

Kaplan Meier ◽

Characteristics Analysis

Hepatocellular carcinoma (HCC) is a common malignant tumor with relatively high malignancy and rapid disease progression. Metabolism-related genes (MRGs) are involved in the pathogenesis of HCC. This study explored potential key MRGs and their effect on T-cell immune function in the tumor immune microenvironment to provide new insight for the treatment of HCC. Of 456 differentially expressed MRGs identified from TCGA database, 21 were screened by MCODE and cytoHubba algorithms. From the key module, GAD1, SPP1, WFS1, GOT2, EHHADH, and APOA1 were selected for validation. The six MRGs were closely correlated with survival outcomes and clinicopathological characteristics in HCC. Receiver operating characteristics analysis and Kaplan-Meier plots showed that these genes had good prognostic value for HCC. Gene set enrichment analysis of the six MRGs indicated that they were associated with HCC development. TIMER and GEPIA databases revealed that WFS1 was significantly positively correlated and EHHADH was negatively correlated with tumor immune cell infiltration and immune checkpoint expression. Finally, quantificational real-time polymerase chain reaction (qRT-PCR) confirmed the expression of WFS1 and EHHADH mRNA in our own patients’ cohort samples and four HCC cell lines. Collectively, the present study identified six potential MRG biomarkers associated with the prognosis and tumor immune infiltration of HCC, thus providing new insight into the pathogenesis and treatment of HCC.

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Identification and Validation of Three Autophagy-Related Long Noncoding RNAs as Prognostic Signature in Cholangiocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.780601 ◽

2021 ◽

Vol 11 ◽

Author(s):

Ya Jun Liu ◽

Alphonse Houssou Hounye ◽

Zheng Wang ◽

Xiaowei Liu ◽

Jun Yi ◽

...

Keyword(s):

Risk Score ◽

Immune Cell ◽

Noncoding Rnas ◽

Enrichment Analysis ◽

Long Noncoding Rnas ◽

Gene Set Enrichment Analysis ◽

Risk Scores ◽

Roc Curve Analysis ◽

Good Reliability ◽

Normal Tissues

Cholangiocarcinoma (CCA) is featured by common occurrence and poor prognosis. Autophagy is a biological process that has been extensively involved in the progression of tumors. Long noncoding RNAs (lncRNAs) have been discovered to be critical in diagnosing and predicting various tumors. It may be valuable to elaborate autophagy-related lncRNAs (ARlncRNAs) in CCA, and indeed, there are still few studies concerning the role of ARlncRNAs in CCA. Here, a prognostic ARlncRNA signature was constructed to predict the survival outcome of CCA patients. Through identification, three differentially expressed ARlncRNAs (DEARlncRNAs), including CHRM3.AS2, MIR205HG, and LINC00661, were screened and were considered predictive signatures. Furthermore, the overall survival (OS) of patients with high-risk scores was significantly lower than that of patients with low scores. Interestingly, the risk score was an independent factor for the OS of patients with CCA. Moreover, receiver operating characteristic (ROC) curve analysis showed that the screened and constructed prognosis signature for 1 year (AUC = 0.884), 3 years (AUC =0.759), and 5 years (AUC = 0.788) presented a high score of accuracy in predicting OS of CCA patients. Gene set enrichment analysis (GSEA) revealed that the three DEARlncRNAs were significantly enriched in CCA-related signaling pathways, including “pathways of basal cell carcinoma”, “glycerolipid metabolism”, etc. Quantitative real-time PCR (qRT-PCR) showed that expressions of CHRM3.AS2, MIR205HG, and LINC00661 were higher in CCA tissues than those in normal tissues, similar to the trends detected in the CCA dataset. Furthermore, Pearson’s analysis reported an intimate correlation of the risk score with immune cell infiltration, indicating a predictive value of the signature for the efficacy of immunotherapy. In addition, the screened lncRNAs were found to have the ability to modulate the expression of mRNAs by interacting with miRNAs based on the established lncRNA-miRNA-mRNA network. In conclusion, our study develops a novel nomogram with good reliability and accuracy to predict the OS of CCA patients, providing a significant guiding value for developing tailored therapy for CCA patients.

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TRPV4 is a Prognostic Biomarker That Correlates With the Immunosuppressive Microenvironment and Chemoresistance of Anti-Cancer Drugs

10.21203/rs.3.rs-383566/v1 ◽

2021 ◽

Author(s):

kai wang ◽

Jun xing Feng ◽

Zhi ling Zheng ◽

Ying ze Chai ◽

Hui jun Yu ◽

...

Keyword(s):

Ovarian Cancer ◽

Transient Receptor Potential ◽

Immune Cell ◽

Colon Adenocarcinoma ◽

Enrichment Analysis ◽

Receptor Potential ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Free Interval ◽

Pan Cancer

Abstract Background: Transient receptor potential cation channel subfamily V member 4 (TRPV4) has been reported to regulate tumor progression in many tumor types. However, its association with the tumor immune microenvironment remains unclear.Methods: TRPV4 expression was assessed using data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database. The clinical features and prognostic roles of TRPV4 were assessed using TCGA cohort. Gene set enrichment analysis (GSEA) of TRPV4 was conducted using the R package clusterProfiler. We analyzed the association between TRPV4 and immune cell infiltration scores of TCGA samples downloaded from published articles and the TIMER2 database.Results: TRPV4 was highly expressed and associated with worse overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in colon adenocarcinoma (COAD) and ovarian cancer. Furthermore, TRPV4 expression was closely associated with immune regulation-related pathways. Moreover, tumor-associated macrophage (TAM) infiltration levels were positively correlated with TRPV4 expression in TCGA pan-cancer samples. Immunosuppressive genes such as PD-L1, PD-1, CTLA4, LAG3, TIGIT, TGFB1, and TGFBR1 were positively correlated with TRPV4 expression in most tumors.Conclusions: Our results suggest that TRPV4 is an oncogene and a prognostic marker in COAD and ovarian cancer. High TRPV4 expression is associated with tumor immunosuppressive status and may contribute to TAM infiltration based on TCGA data from pan-cancer samples.

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A Six-lncRNA Signature for Immunophenotype Prediction of Glioblastoma Multiforme

Frontiers in Genetics ◽

10.3389/fgene.2020.604655 ◽

2021 ◽

Vol 11 ◽

Author(s):

Ming Gao ◽

Xinzhuang Wang ◽

Dayong Han ◽

Enzhou Lu ◽

Jian Zhang ◽

...

Keyword(s):

Glioblastoma Multiforme ◽

Immune Cell ◽

Area Under The Curve ◽

Principal Component ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Non Coding Rna ◽

Cancer Genome Atlas ◽

The Central Nervous System

Glioblastoma multiforme (GBM) is the most aggressive primary tumor of the central nervous system. As biomedicine advances, the researcher has found the development of GBM is closely related to immunity. In this study, we evaluated the GBM tumor immunoreactivity and defined the Immune-High (IH) and Immune-Low (IL) immunophenotypes using transcriptome data from 144 tumors profiled by The Cancer Genome Atlas (TCGA) project based on the single-sample gene set enrichment analysis (ssGSEA) of five immune expression signatures (IFN-γ response, macrophages, lymphocyte infiltration, TGF-β response, and wound healing). Next, we identified six immunophenotype-related long non-coding RNA biomarkers (im-lncRNAs, USP30-AS1, HCP5, PSMB8-AS1, AL133264.2, LINC01684, and LINC01506) by employing a machine learning computational framework combining minimum redundancy maximum relevance algorithm (mRMR) and random forest model. Moreover, the expression level of identified im-lncRNAs was converted into an im-lncScore using the normalized principal component analysis. The im-lncScore showed a promising performance for distinguishing the GBM immunophenotypes with an area under the curve (AUC) of 0.928. Furthermore, the im-lncRNAs were also closely associated with the levels of tumor immune cell infiltration in GBM. In summary, the im-lncRNA signature had important clinical implications for tumor immunophenotyping and guiding immunotherapy in glioblastoma patients in future.

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

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/5970085 ◽

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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