High Expression of TTK As Colon Stem Cell Marker Correlated With M1 Macrophages Infiltration

Abstract Background: Tumor stemness-related genes promote tumor progression and resistance to immunotherapy, but the relation between tumor-infiltrating immune cells and colon adenocarcinoma (COAD) stemness-related genes remains unclear. Methods: The mRNAsi scores, a stemness index derived from transcriptomic data of the TCGA COAD cohort were used for integrated bioinformatics analysis. The Weighted Gene Co-expression Network Analysis (WGCNA) was applied to classify the modules correlated with mRNAsi scores. The Gene Expression Omnibus (GEO) cohorts GSE76402 was used to verify the DEGs between colon cancer and normal tissues. Real-time PCR and Flow-cytometry were used to validate the expression of genes and cancer stem cells marker in the spheres of colon cancer cells. The Single-sample Gene Set Enrichment Analysis (ssGSEA) and CIBERSORT algorithm were used to explore the correlation between significant genes and the immune cells in tumor microenvironment. Result: The mRNAsi score was associated with tumor development and progression. TTK were identified as COAD stemness-related genes based on WGCNA analysis. TTK were negatively correlated with immunity. Interestingly, M1 Macrophages had a higher infiltration in COAD with high TTK expression. Higher infiltration of M1 Macrophages would result in the worse survival rate of COAD patients. Conclusion: TTK may have the potential as a prognostic biomarker and adjuvant target to promote immunotherapy sensitivity and improve outcomes of COAD patients.

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Identification of Key Claudin Genes Associated With Survival Prognosis and Diagnosis in the Colon Cancer Through Integrated Bioinformatic Analysis‏.

10.21203/rs.3.rs-1007190/v1 ◽

2021 ◽

Author(s):

Rana Alghamdi ◽

Maryam Al-Zahrani

Keyword(s):

Colon Cancer ◽

Differential Expression Analysis ◽

Colon Adenocarcinoma ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Survival Prognosis ◽

Diagnostic Efficacy ◽

Gene Set ◽

Protein Protein Interaction

Abstract Background: Claudin’s gene are associated with various aberrant physiological and cellular signaling. However, the association of claudins with survival prognosis, signaling pathways, and diagnostic efficacy in colon cancer remain lacking. Methods: We used various bioinformatics methods, including differential expression analysis, gene set enrichment analysis (GSEA), protein-protein interaction (PPI), survival analysis, single sample gene set enrichment analysis (ssGSEA), mutation analysis, and identifying receiver operating characteristic (ROC) curve of claudins in the TCGA colon adenocarcinoma (COAD). Results: We found that: CLDN2, CLDN1, CLDN14, CLDN16, CLDN18, CLDN9, CLDN12, and CLDN6 are elevated in COAD. In contrast, the CLDN8, CLDN23, CLDN5, CLDN11, CLDN7, and CLDN15 are downregulated in COAD. Various claudin’s genes are mutated and associated with diagnostic efficacy in the COAD. Conclusions: Claudin’s genes are associated with prognosis, immune regulation, signaling pathway regulations, and diagnosis. These findings may provide new molecular insight into the treatment of colon cancer.

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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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Comprehensive Analysis of ESRRA in Endometrial Cancer

Technology in Cancer Research & Treatment ◽

10.1177/1533033821992083 ◽

2021 ◽

Vol 20 ◽

pp. 153303382199208

Author(s):

Shufang Wang ◽

Xinlong Huo

Keyword(s):

Endometrial Cancer ◽

Protein Expression ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Expression Level ◽

Operating Characteristics ◽

Protein Expression Level ◽

Normal Tissues

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

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Transmembrane p24 Trafficking Protein 2 Regulates Inflammation Through the TLR4/NF-κB Signaling Pathway in Lung Adenocarcinoma

10.21203/rs.3.rs-794174/v1 ◽

2021 ◽

Author(s):

Longhua Feng ◽

Pengjiang Cheng ◽

Zhengyun Feng ◽

Xiaoyu Zhang

Keyword(s):

Lung Adenocarcinoma ◽

Signaling Pathway ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Inflammatory Factors ◽

Normal Tissues ◽

Kaplan Meier ◽

New Strategy

Abstract Background: To investigate the role of transmembrane p24 trafficking protein 2 (TMED2) in lung adenocarcinoma (LUAD) and determine whether TMED2 knockdown could inhibit LUAD in vitro and in vivo.Methods: TIMER2.0, Kaplan-Meier plotter, gene set enrichment analysis (GSEA), Target Gene, and pan-cancer systems were used to predict the potential function of TMED2. Western blotting and immunohistochemistry were performed to analyze TMED2 expression in different tissues or cell lines. The proliferation, development, and apoptosis of LUAD were observed using a lentivirus-mediated TMED2 knockdown. Bioinformatics and western blot analysis of TMED2 against inflammation via the TLR4/NF-κB signaling pathway were conducted. Results: TMED2 expression in LUAD tumor tissues was higher than that in normal tissues and positively correlated with poor survival in lung cancer and negatively correlated with apoptosis in LUAD. The expression of TMED2 was higher in tumors or HCC827 cells. TMED2 knockdown inhibited LUAD development in vitro and in vivo and increased the levels of inflammatory factors via the TLR4/NF-κB signaling pathway. TMED2 was correlated with TME, immune score, TME-associated immune cells, their target markers, and some mechanisms and pathways, as determined using the TIMER2.0, GO, and KEGG assays.Conclusions: TMED2 may regulate inflammation in LUAD through the TLR4/NF-κB signaling pathway, and enhance the proliferation, development, and prognosis of LUAD by regulating inflammation, which provide a new strategy for treating LUAD by regulating inflammation.

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Comprehensive Analysis of CPA4 as a Poor Prognostic Biomarker Correlated with Immune Cells Infiltration in Bladder Cancer

Biology ◽

10.3390/biology10111143 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1143

Author(s):

Chengcheng Wei ◽

Yuancheng Zhou ◽

Qi Xiong ◽

Ming Xiong ◽

Yaxin Hou ◽

...

Keyword(s):

Bladder Cancer ◽

T Cell ◽

Immune Cells ◽

Prognostic Significance ◽

Gene Set Enrichment Analysis ◽

Marker Genes ◽

Gene Marker ◽

Normal Tissues ◽

Kaplan Meier ◽

Diagnostic Potential

Carboxypeptidase A4 (CPA4) has shown the potential to be a biomarker in the early diagnosis of certain cancers. However, no previous research has linked CPA4 to therapeutic or prognostic significance in bladder cancer. Using data from The Cancer Genome Atlas (TCGA) database, we set out to determine the full extent of the link between CPA4 and BLCA. We further analyzed the interacting proteins of CPA4 and infiltrated immune cells via the TIMER2, STRING, and GEPIA2 databases. The expression of CPA4 in tumor and normal tissues was compared using the TCGA + GETx database. The connection between CPA4 expression and clinicopathologic characteristics and overall survival (OS) was investigated using multivariate methods and Kaplan–Meier survival curves. The potential functions and pathways were investigated via gene set enrichment analysis. Furthermore, we analyze the associations between CPA4 expression and infiltrated immune cells with their respective gene marker sets using the ssGSEA, TIMER2, and GEPIA2 databases. Compared with matching normal tissues, human CPA4 was found to be substantially expressed. We confirmed that the overexpression of CPA4 is linked with shorter OS, DSF(Disease-specific survival), PFI(Progression-free interval), and increased diagnostic potential using Kaplan–Meier and ROC analysis. The expression of CPA4 is related to T-bet, IL12RB2, CTLA4, and LAG3, among which T-bet and IL12RB2 are Th1 marker genes while CTLA4 and LAG3 are related to T cell exhaustion, which may be used to guide the application of checkpoint blockade and the adoption of T cell transfer therapy.

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

Bioscience Reports ◽

10.1042/bsr20201427 ◽

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.

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Prognostic and immunological value of LTB4R in pan-cancer

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2021459 ◽

2021 ◽

Vol 18 (6) ◽

pp. 9336-9356

Author(s):

Sidan Long ◽

◽

Shuangshuang Ji ◽

Kunmin Xiao ◽

Peng Xue ◽

...

Keyword(s):

Immune Cells ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Negative Influence ◽

Leukotriene B4 ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Immune Infiltration ◽

Significant Difference ◽

Pan Cancer

<abstract> <sec><title>Background</title>LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain. </sec> <sec><title>Methods</title>We investigated the expression pattern and prognostic significance of LTB4R in pan-cancer across different databases, including ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter, in this study. Meanwhile, we explored the significance of LTB4R in tumor metastasis by HCMDB. Then functional enrichment analysis of related genes was performed using GeneMANIA and DAVID. Lastly, utilizing the TIMER datasets, we looked into the links between LTB4R expression and immune infiltration in malignancies. </sec> <sec><title>Results</title>In general, tumor tissue displayed higher levels of LTB4R expression than normal tissue. Although LTB4R had a negative influence on pan-cancer, a high expression level of LTB4R was protective of LIHC (liver hepatocellular carcinoma) patients' survival. There was no significant difference in the distribution of LTB4R between non-metastatic and metastatic tumors. Based on Gene Set Enrichment Analysis, LTB4R was implicated in pathways involved in inflammation, immunity, metabolism, and cancer diseases. The correlation between immune cells and LTB4R was found to be distinct across cancer types. Furthermore, markers of infiltrating immune cells, such as Treg, T cell exhaustion and T helper cells, exhibited different LTB4R-related immune infiltration patterns. </sec> <sec><title>Conclusion</title>The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer. </sec> </abstract>

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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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