Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

Tumor microenvironment (TME) is emerging as an essential part of cervical cancer (CC) tumorigenesis and development, becoming a hotspot of research these years. However, comprehending the specific composition of TME is still facing enormous challenges, especially the immune and stromal components. In this study, we downloaded the RNA-seq profiles and somatic mutation data of 309 CC cases from The Cancer Genome Atlas (TCGA) database, which were analyzed by integrative bioinformatical methods. Initially, ESTIMATE computational method was employed to calculate the amount of immune and stromal components. Then, based on the high- and low-immunity cohorts, we recognized the differentially expressed genes (DEGs) as well as the differentially mutated genes (DMGs). Additionally, we conducted an intersection analysis of DEGs and DMGs, ultimately determining an immune-related prognostic signature, GTPase, IMAP Family Member 4 (GIMAP4). Moreover, sequential analyses demonstrated that GIMAP4 was a protective factor in CC, positively correlated with the overall survival (OS) and negatively with distant metastasis. Besides, we utilized the Gene Set Enrichment Analysis (GSEA) to explore the enrichment-pathways in high and low-expression cohorts of GIMAP4. The results indicated that the genes of the high-expression cohort had a high enrichment in immune-related biological processes and metabolic activities in the low one. Furthermore, CIBERSORT analysis was applied to evaluate the proportion of tumor-infiltrating immune cells (TICs), illustrating that several activated TICs were strongly associated with GIMAP4 expression, which suggested that GIMAP4 had the potential to be an indicator for the immune state in TME of CC. Hence, GIMAP4 contributed to predicting the CC patients’ clinical outcomes, such as survival rate, distant metastasis and immunotherapy response. Moreover, GIMAP4 could serve as a promising biomarker for TME remodeling, suggesting the possible underlying mechanisms of tumorigenesis and CC progression, which may provide different therapeutic perceptions of CC, and therefore improve treatment.

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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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High RPS27A Expression Predicts Poor Prognosis in Patients With HPV Type 16 Cervical Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.752974 ◽

2021 ◽

Vol 11 ◽

Author(s):

Qiming Wang ◽

Yan Cai ◽

Xuewen Fu ◽

Liang Chen

Keyword(s):

Cervical Cancer ◽

Poor Prognosis ◽

Biological Significance ◽

Enrichment Analysis ◽

Hpv Infection ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Protein Protein Interaction ◽

Cervical Cancer Cells ◽

Cancer Genome Atlas

In recent years, the incidence and the mortality rate of cervical cancer have been gradually increasing, becoming one of the major causes of cancer-related death in women. In particular, patients with advanced and recurrent cervical cancers present a very poor prognosis. In addition, the vast majority of cervical cancer cases are caused by human papillomavirus (HPV) infection, of which HPV16 infection is the main cause and squamous cell carcinoma is the main presenting type. In this study, we performed screening of differentially expressed genes (DEGs) based on The Cancer Genome Atlas (TCGA) database and GSE6791, constructed a protein–protein interaction (PPI) network to screen 34 hub genes, filtered to the remaining 10 genes using the CytoHubba plug-in, and used survival analysis to determine that RPS27A was most associated with the prognosis of cervical cancer patients and has prognostic and predictive value for cervical cancer. The most significant biological functions and pathways of RPS27A enrichment were subsequently investigated with gene set enrichment analysis (GSEA), and integration of TCGA and GTEx database analyses revealed that RPS27A was significantly expressed in most cancer types. In this study, our analysis revealed that RPS27A can be used as a prognostic biomarker for HPV16 cervical cancer and has biological significance for the growth of cervical cancer cells.

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Effects of Hypoxia in Intestinal Tumors on Immune Cell Behavior in the Tumor Microenvironment

10.21203/rs.3.rs-131685/v1 ◽

2020 ◽

Author(s):

Luping Zhang ◽

Shaokun Wang ◽

Yachen Wang ◽

Weidan Zhao ◽

Yingli Zhang ◽

...

Keyword(s):

Colorectal Cancer ◽

Tumor Microenvironment ◽

Risk Score ◽

Immune Cell ◽

Risk Groups ◽

Low Risk ◽

Computational Method ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Behavior

Abstract Background: Imbalanced nutritional supply and demand in the tumor microenvironment often leads to hypoxia. The subtle interaction between hypoxia and immune cell behavior plays an important role in tumor occurrence and development. However, the functional relationship between hypoxia and the tumor microenvironment remains unclear. Therefore, we aimed to investigate the effect of hypoxia on the intestinal tumor microenvironment.Method: We extracted the names of hypoxia-related genes from the Gene Set Enrichment Analysis (GSEA) database and screened them for those associated with the prognosis of colorectal cancer, with the final list including ALDOB, GPC1, ALDOC, and SLC2A3. Using the sum of the expression levels of these four genes, provided by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and the expression coefficients, we developed a hypoxia risk score model. Using the median risk score value, we divided the patients in the two databases into high- and low-risk groups.GSEA was used to compare the enrichment differences between the two groups.We used the CIBERSORT computational method to analyze immune cell infiltration.Finally,the correlation between these five genes and hypoxia was analyzed. Result: The prognosis of the two groups differed significantly, with a higher survival rate in the low-risk group than in the high-risk group.We found that the different risk groups were enriched by immune-related and inflammatory pathways. We identified activated CD4 memory T cells and M0 macrophages in TCGA and GEO databases and found that CCL2/4/5, CSF1, and CX3CL1 contributed toward the increased infiltration rate of these immune cell types. Finally, we observed a positive correlation between the five candidate genes’ expression and the risk of hypoxia, with significant differences in the level of expression of each of these genes between patient risk groups.Conclusion: Overall, our data suggest that hypoxia is associated with the prognosis and rate of immune system infiltration in patients with colorectal cancer. This finding may improve immunotherapy for colorectal cancer.

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m6 A Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization in Early Cervical Cancer

10.21203/rs.3.rs-1037825/v1 ◽

2021 ◽

Author(s):

Dan Sun ◽

Xingping Zhao ◽

Aiqian Zhang ◽

Lingxiao Zou ◽

Huan Huang ◽

...

Keyword(s):

Cervical Cancer ◽

Tumor Microenvironment ◽

Messenger Rna ◽

Early Stage ◽

Expression Profiles ◽

Enrichment Analysis ◽

Clinical Information ◽

Hpv Infection ◽

The Cancer Genome Atlas ◽

Early Cervical Cancer

Abstract Background Cervical cancer (CC) is the malignancy of female and almost cases of cervical cancer were caused by high-risk human papillomavirus (HPV) infection. Understanding the pathogenesis and characteristics of the postinfection microenvironment (PIM) in early-stage cervical cancer is needed. The mechanism of N6-methyladenosine (m6A) in the regulation of immune microenvironment in cervical cancer is unclear. Methods Messenger RNA (mRNA) expression profiles and clinical information of cervical cancer were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset GSE44001. We comprehensively evaluated the m6A modification patterns in early cervical cancer and systematically correlated these modification patterns with tumor microenvironment (TME) cell-infiltrating characteristics. Analysis of tumor mutational signatures and biological enrichment analysis were also conducted. Results LRPPRC had the highest mutation frequency. Writers METTL14 and ZC3H13, as well as reader YTHDF3, were prognostic risk-related genes. DEGs were significantly enriched in the C-type lectin receptor signaling pathway. The m6A cluster A showed a higher level of infiltration immunocytes, and the activity of most immune cells increased. The low-m6Sig score group was poor in prognosis compared with the high-m6Sig score group. Further, we found that the 23 immunocytes, excluding plasmacytoid dendritic cells, negatively correlated with the m6Sig score. Conclusions Dysregulation of m6A lays a critical foundation for understanding the regulation of early CC immunity. What’s more, evaluating the m6A modification pattern of early CC contributes to enhancing our knowledge of the characteristics of PIM and provides an important insight into the efficacy of HPV treatment.

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Mining the TCGA Database for Microenvironment‐Related Genes with Prognostic Value in Gastric Cancer

10.21203/rs.3.rs-175261/v1 ◽

2021 ◽

Author(s):

Ting Liu ◽

Zheng Gong ◽

Hong Zhang ◽

Yi Wan ◽

Ming-Han Ren ◽

...

Keyword(s):

Gastric Cancer ◽

Distant Metastasis ◽

Clinical Stage ◽

Enrichment Analysis ◽

Clinicopathological Characteristics ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Gene Set Enrichment ◽

Gene Set ◽

Protein Protein Interaction

Abstract BackgroundGastric cancer (GC) is the fifth most common cancer worldwide. Previous studies have suggested that the tumor microenvironment (TME) plays an important role in the development and prognosis of GC. In this study, we aimed to identify genes in tumor-infiltrating immune cells (TICs) that influence the progression and prognosis of GC. MethodsWe used the ESTIMATE algorithm to calculate the scores of the stromal and immune components of the TME in 407 GC samples collected from The Cancer Genome Atlas (TCGA) database.The differentially expressed genes (DEGs) were intersected by a protein-protein interaction (PPI) network and analyzed by univariate Cox regression.Further analysis showed the correlation between MCEMP1 and the clinicopathological characteristics of GC patients (clinical stage, distant metastasis) and survival.Then we used Gene set enrichment analysis (GSEA) and CIBERSORT analysis to examine the relationship between MCEMP1 and the TME.ResultsThe analysis revealed that the expression of MCEMP1 was positively correlated with the clinicopathological characteristics of GC patients (clinical stage, distant metastasis) and negatively correlated with survival. Gene set enrichment analysis (GSEA) indicated that gene sets in the MCEMP1 high expression group were concentrated mainly in immune-related pathways. CIBERSORT analysis of the proportion of TICs revealed that neutrophils and M2 macrophages were positively correlated with MCEMP1 expression, suggesting that MCEMP1 is responsible for preservation of the immune-dominant status of the TME. ConclusionHigh MCEMP1 expression might be a biomarker of a poor prognosis in GC patients and provide a clue regarding the different statuses of the TME, offering additional insight into therapy for GC.

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Pyroptosis Patterns Characterized by Distinct Tumor Microenvironment Infiltration Landscapes in Gastric Cancer

Genes ◽

10.3390/genes12101535 ◽

2021 ◽

Vol 12 (10) ◽

pp. 1535

Author(s):

Renshen Xiang ◽

Yuhang Ge ◽

Wei Song ◽

Jun Ren ◽

Can Kong ◽

...

Keyword(s):

Gastric Cancer ◽

Tumor Microenvironment ◽

Molecular Subtypes ◽

Principal Component ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Consensus Clustering ◽

Analysis Algorithm ◽

Signature Genes

Background: The potential role of pyroptosis in tumor microenvironment (TME) reprogramming and immunotherapy has received increasing attention. As most studies have concentrated on a single TME cell type or a single pyroptosis regulator (PR), the overall TME cell-infiltrating characteristics mediated by the integrated roles of multiple PRs have not been comprehensively recognized. Methods: This study curated 33 PRs and conducted consensus clustering to identify distinct pyroptosis patterns in gastric cancer (GC) patients. A single-sample gene set enrichment analysis algorithm was used to quantify the infiltration density of TME immune cells and the enrichment scores of well-defined biological signatures. The pyroptosis patterns of individuals were quantified using a principal component analysis algorithm called the pyroptosis score (PS). Results: Three distinct pyroptosis patterns with significant survival differences were identified from 1422 GC samples; these patterns were closely associated with three TME cell-infiltrating landscapes—namely, the immune-inflamed, immune-excluded, and immune-desert phenotypes. The PS model generated on the basis of the pyroptosis pattern-related signature genes could accurately predict the TME status, existing molecular subtypes, genetic variation, therapeutic response, and clinical outcome; among which, a relatively high PS was highly consistent with immune activation, molecular subtypes with survival advantages, high tumor mutation burden, high microsatellite instability, and other favorable characteristics. In particular, from the Cancer Genome Atlas database, the PS model exhibited significant prognostic relevance in a pan-cancer analysis, and patients with a relatively high PS exhibited durable therapeutic advantages and better prognostic benefits in anti-PD1/L1 therapy. Conclusions: This study demonstrates that pyroptosis is prominently correlated with TME diversity and complexity, and quantification of the pyroptosis patterns of individuals will enhance our cognition of TME infiltration landscapes and help in formulating more effective immunotherapeutic strategies.

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

Frontiers in Oncology ◽

10.3389/fonc.2021.654388 ◽

2021 ◽

Vol 11 ◽

Author(s):

Qinglong Guo ◽

Xing Xiao ◽

Jinsen Zhang

Keyword(s):

Tumor Microenvironment ◽

Cox Regression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Who Grade ◽

Cox Regression Analysis ◽

Clinical Cases

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

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Complement C1q (C1qA, C1qB, and C1qC) May Be a Potential Prognostic Factor and an Index of Tumor Microenvironment Remodeling in Osteosarcoma

Frontiers in Oncology ◽

10.3389/fonc.2021.642144 ◽

2021 ◽

Vol 11 ◽

Author(s):

Long-hao Chen ◽

Jin-Fu Liu ◽

Yan- Lu ◽

Xin-yu He ◽

Chi- Zhang ◽

...

Keyword(s):

Tumor Microenvironment ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Clinicopathological Feature ◽

Immune Functions ◽

Complement Components ◽

Cox Regression Analysis ◽

Matrix Components

The tumor microenvironment (TME) has important effects on the tumorigenesis and development of osteosarcoma (OS). However, the dynamic mechanism regulating TME immune and matrix components remains unclear. In this study, we collected quantitative data on the gene expression of 88 OS samples from The Cancer Genome Atlas (TCGA) database and downloaded relevant clinical cases of OS from the TARGET database. The proportions of tumor-infiltrating immune cells (TICs) and the numbers of immune and matrix components were determined by CIBERSORT and ESTIMATE calculation methods. Protein-protein interaction (PPI) network construction and Cox regression analysis were conducted to analyze differentially expressed genes (DEGs). The complement components C1qA, C1qB and C1qC were then determined to be predictive factors through univariate Cox analysis and PPI cross analysis. Further analysis found that the levels of C1qA, C1qB and C1qC expression were positively linked to OS patient survival time and negatively correlated with the clinicopathological feature percent necrosis at definitive surgery. The results of gene set enrichment analysis (GSEA) demonstrated that genes related to immune functions were significantly enriched in the high C1qA, C1qB and C1qC expression groups. Proportion analysis of TICs by CIBERSORT showed that the levels of C1qA, C1qB and C1qC expression were positively related to M1 and M2 macrophages and CD8+ cells and negatively correlated with M0 macrophages. These results further support the influence of the levels of C1qA, C1qB and C1qC expression on the immune activity of the TME. Therefore, C1qA, C1qB and C1qC may be potential indicators of remodeling in the OS TME, which is helpful to predict the prognosis of patients with OS and provide new ideas for immunotherapy for OS.

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Identification and Mechanism of the PD-1/PD-L1 Genomic Signature SORL1 as Protective Factor in Bladder Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.736158 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yajing Xu ◽

Didi Chen ◽

Lanxiao Shen ◽

Xiaowei Huang ◽

Yi Chen ◽

...

Keyword(s):

Bladder Cancer ◽

Protective Factor ◽

Epithelial Mesenchymal Transition ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Genomic Signature ◽

M2 Macrophage ◽

Mesenchymal Transition ◽

Human Protein Atlas

Background: Immunotherapy has recently shown remarkable efficacy for advanced bladder cancer patients. Accordingly, identifying a biomarker associated with the programmed cell death protein 1 (PD-1)/its ligand (PD-L1) genomic signature to predict patient prognosis is necessary.Methods: In this study, we used mutation data and RNA-seq data of bladder cancer samples acquired from The Cancer Genome Atlas (TCGA) database to combine PD-1/PD-L1-associated mutational signatures with PD-1/PD-L1-associated differentially expressed genes (DEGs). Then, we performed a Kaplan-Meier analysis on the corresponding clinical data of the TCGA bladder urothelial carcinoma (BLCA) cohort to identify prognostic genes, and the results were validated using the GSE48075 cohort. The online platform UCSC Xena was used to analyze the relationship between the candidate genes and clinical parameters. We utilized the Human Protein Atlas (HPA) database to validate the protein expression levels. Then, correlation analysis, cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) analysis, and gene set enrichment analysis (GSEA) were used to clarify the mechanism.Results: We identified one prognostic gene, sortilin related receptor 1 (SORL1), whose downregulation was associated with a comparatively advanced BLCA stage. While further exploring this finding, we found that SORL1 expression was negatively correlated with PD-1/PD-L1 expression and M2 macrophage levels. Furthermore, we found that the downregulation of SORL1 expression was significantly associated with a higher epithelial-mesenchymal transition (EMT) score.Conclusion: We described a novel PD-1/PD-L1-associated signature, SORL1, that predicts favorable outcomes in bladder cancer. SORL1 might reduce immune suppression and inhibit the M2 macrophage-induced EMT phenotype of tumor cells.

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CD2 Is a Novel Immune-Related Prognostic Biomarker of Invasive Breast Carcinoma That Modulates the Tumor Microenvironment

Frontiers in Immunology ◽

10.3389/fimmu.2021.664845 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yanzhu Chen ◽

Zhishang Meng ◽

Lin Zhang ◽

Feng Liu

Keyword(s):

Tumor Microenvironment ◽

Breast Carcinoma ◽

Cox Regression ◽

Immune Escape ◽

Enrichment Analysis ◽

Tnm Staging ◽

Invasive Breast Carcinoma ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Lymph Node Status

Female breast cancer (BCa) is the most commonly occurring cancer worldwide. The tumor microenvironment (TME) plays an essential role in tumor invasion, angiogenesis, unlimited proliferation, and even immune escape, but we know little about the TME of BCa. In this study, we aimed to find a TME-related biomarker for BCa, especially for invasive breast carcinoma (BRCA), that could predict prognosis and immunotherapy efficacy. Based on RNA-seq transcriptome data and the clinical characteristics of 1222 samples (113 normal and 1109 tumor samples) from The Cancer Genome Atlas (TCGA) database, we used the ESTIMATE algorithm to calculate the ImmuneScore and StromalScore and then identified differentially expressed genes (DEGs) between the high and low ImmuneScore groups and the high and low StromalScore groups. Thereafter, a protein–protein interaction (PPI) network analysis and univariate Cox regression analyses of overall survival were used to identify potential key genes. Five candidate genes were identified, comprising CD2, CCL19, CD52, CD3E, and ITK. Thereafter, we focused on CD2, analyzing CD2 expression and its association with survival. CD2 expression was associated with tumor size (T stage) to some extent, but not with overall TNM stage, lymph node status (N stage), or distant metastasis (M stage). High CD2 expression was associated with longer survival. METABRIC data were used to validate the survival result (n = 276). Gene set enrichment analysis (GSEA) showed that the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were significantly associated with high CD2 expression were mainly immune-related pathways. Furthermore, CD2 expression was correlated with 16 types of tumor-infiltrating immune cells (TICs). Hence, CD2 might be a novel biomarker in terms of molecular typing, and it may serve as a complementary approach to TNM staging to improve clinical outcome prediction for BCa patients.

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