scholarly journals CCR2 and PTPRC are regulators of Tumor Microenvironment and potential prognostic biomarkers of lung adenocarcinoma

2021 ◽  
Author(s):  
Chengbang Wang ◽  
Jie Wei ◽  
DaLang Fang
Keyword(s):  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Immune Cells ◽  
Cox Regression ◽  
Γδt Cells ◽  
Cox Regression Analysis ◽  
Immune State ◽  
Protein Protein Interaction ◽  
Intersection Analysis ◽  
Key Genes

Abstract Tumor microenvironment (TME) plays an essential role in lung adenocarcinoma (LUAD) development and metastasis. With the development of TME research, it has been proved that differences in tumor-infiltrating immune cells (TICs) and gene expression profile are related to the prognosis of cancer. Our study aimed to identify key genes affecting immune state in TME of LUAD. We downloaded the RNA-seq data of LUAD cases from the TCGA database. ImmuneScore, StromalScore and ESTIMATEScore of each LUAD sample were calculated using ESTIMATE algorithm. Based on the median of different scores, LUAD samples were divided into high and low score groups. Differentially expressed genes (DEGs) between groups were obtained, and univariate Cox regression analysis and protein-protein interaction (PPI) network were used to screen shared DEGs generating in the intersection analysis. CIBORSORT algorithm was performed to calculate the relative contents of TICs for each LUAD sample, and correlation analysis between TICs and key genes was used to determine the influence of key genes to the TME. Finally, CCR2 and PTPRC, affecting the immune status of TME and the prognosis of LUAD, were acquired. Analysis based on the CIBERSORT algorithm suggested that CCR2 and PTPRC were correlated with a variety of TICs, and closely related to the clinical characteristics of the LUAD patients. Our research showed that CCR2 and PTPRC may be potential prognostic markers in LUAD, which may affect function of γδT cells and other immune cells by participating in the regulation of TME immune state.

scholarly journals Prognostic Value and Immune Infiltration of Novel Biomarkers in Glioma: Evidence From a Comprehensive Analysis of Tumor Microenvironment

2020 ◽  
Author(s):  
Bolun Zhang ◽  
Feng Guan ◽  
Bin Dai ◽  
Guangtong Zhu ◽  
Beibei Mao ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Tumor Progression ◽  
Immune Cells ◽  
Stromal Cells ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Ppi Network ◽  
Cox Regression Analysis ◽  
Intersection Analysis ◽  
Genome Atlas

Abstract BackgroundIn the glioma microenvironment, infiltrating immune cells has been shown to possess beneficial effects for tumor progression. Immune cells and stromal cells dominate the tumor microenvironment in glioma. The complex interplay between the tumor progression with immune cells or stromal cells was still unknown. MethodsIn this study, we used Estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE) calculations to calculate the proportion of tumour-infiltrating immune cells (TIC) and the number of immune and stromal components in glioma cases from the cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. Differentially expressed genes (DEG) were analyzed by COX regression analysis and protein-protein interaction (PPI) network construction. Then, JAK3, IL2RB and CD3E were identified as predictors by the intersection analysis of univariate COX and PPI, and further analysis showed that the expression of them were positively correlated with survival and clinicopathological characteristics of glioma patients. Finally, the Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT) deconvolution algorithm was applied to quantify the fraction and infiltration of 22 types of immune cells in glioma. ResultsOur results showed that ESTIMATEScores Were Correlated with the Survival of glioma Patients, DEGs Shared by ImmuneScore and StromalScore were predominantly presented as the enrichment of immune-related genes gene set enrichment analysis (GSEA). The intersection analysis of PPI network and univariate COX regression enabled us to identify three genes (JAK3, IL2RB and CD3E) that had never been reported before, whose expression was correlated with clinical characteristics such as survival and WHO grading of these patients. CITICSORT analysis of TIC ratio showed that B cell memory and CD8 + T cells were positively correlated with JAK3, IL2RB and CD3E expression, suggesting that these genes may be responsible for maintaining the immunodominant state of TME. CIBERSORT analysis for the proportion of TICs revealed that the levels of JAK3, IL2RB and CD3E affected the immune activity of TME.ConclusionOur results confirmed that the JAK3, IL2RB and CD3E can be used as diagnostic and prognostic biomarkers for glioma and may be used as therapeutic targets in the future.

scholarly journals A Novel Immune and Stroma Related Prognostic Marker for Invasive Breast Cancer in Tumor Microenvironment: A TCGA Based Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Yizhou Huang ◽  
Lizhi Chen ◽  
Ziyi Tang ◽  
Yu Min ◽  
Wanli Yu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Cox Regression ◽  
Statistical Significance ◽  
Deep Understanding ◽  
Gene Set Enrichment Analysis ◽  
Biological Behavior ◽  
Cox Regression Analysis ◽  
Intersection Analysis

BackgroundBreast cancer (BC) is the most frequent cancer in women. The tumor microenvironment (TME), consisting of blood vessels, immune cells, fibroblasts, and extracellular matrix, plays a pivotal role in tumorigenesis and progression. Increasing evidence has emphasized the importance of TME, especially the immune components, in patients with BC. Nevertheless, we still lack a deep understanding of the correlation between tumor invasion and TME status.MethodsTranscriptome and clinical data were retrieved from The Cancer Genome Atlas (TCGA) database. ESTIMATE algorithm was applied for quantifying stromal and immune scores. Then we screened out the differentially expressed genes (DEGs) through the intersection analysis. Furthermore, the establishment of protein-protein interaction (PPI) network and univariate COX regression analysis were utilized to determine the core genes in DEGs. In addition, we also performed Gene Set Enrichment Analysis (GSEA) and CIBERSORT analysis to distinguish the function of crucial gene expression and the proportion of tumor-infiltrating immune cells (TICs), respectively.ResultsA total of 1178 samples (112 normal samples and 1066 tumor samples) were extracted from TCGA for calculation, and 226 DEGs were obtained from this assessment. Further intersection analysis revealed eight key genes, including ITK, CD3E, CCL19, CD2, SH2D1A, CD5, SLAMF6, SPN, which were proven to correlate with BC status. Moreover, ITK was picked out for further study. The results illustrated that high expression of BC patients had a more prolonged overall survival (OS) time than ITK low expression BC patients (p = 0.009), and ITK expression also presented the statistical significance in age, TNM staging, tumor size classification, and metastasis classification. Additionally, GSEA and CIBERSORT analysis indicated that ITK expression had an association with immune activity in TME.ConclusionITK may be a potential indicator for prognosis prediction in patients with BC, and its biological behavior may promote our understanding of the molecular mechanism of tumor progression and targeted therapy.

NLRP3 is a Novel Prognostic Biomarker and Correlates With Immune Infiltrates in Lung Adenocarcinoma and Skin Cutaneous Melanoma

2021 ◽  
Author(s):  
Chenxi Yuan ◽  
Qingwei Wang ◽  
Xueting Dai ◽  
Yipeng Song ◽  
Jinming Yu
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Lung Adenocarcinoma ◽  
Immune Cells ◽  
Cutaneous Melanoma ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Potential Biomarker ◽  
The Impact ◽  
Nlrp3 Expression

Abstract Background: Lung adenocarcinoma (LUAD) and skin cutaneous melanoma (SKCM) are common tumors around the world. However, the prognosis in advanced patients is poor. Because NLRP3 was not extensively studied in cancers, so that we aimed to identify the impact of NLRP3 on LUAD and SKCM through bioinformatics analyses. Methods: TCGA and TIMER database were utilized in this study. We compared the expression of NLRP3 in different cancers and evaluated its influence on survival of LUAD and SKCM patients. The correlations between clinical information and NLRP3 expression were analyzed using logistic regression. Clinicopathologic characteristics associated with overall survival in were analyzed by Cox regression. In addition, we explored the correlation between NLRP3 and immune infiltrates. GSEA and co-expressed gene with NLRP3 were also done in this study. Results: NLRP3 expressed disparately in tumor tissues and normal tissues. Cox regression analysis indicated that up-regulated NLRP3 was an independent prognostic factor for good prognosis in LUAD and SKCM. Logistic regression analysis showed increased NLRP3 expression was significantly correlated with favorable clinicopathologic parameters such as no lymph node invasion and no distant metastasis. Specifically, a positive correlation between increased NLRP3 expression and immune infiltrating level of various immune cells was observed. Conclusion: Together with all these findings, increased NLRP3 expression correlates with favorable prognosis and increased proportion of immune cells in LUAD and SKCM. These conclusions indicate that NLRP3 can serve as a potential biomarker for evaluating prognosis and immune infiltration level.

scholarly journals Identification of Prognostic Gene Signature Associated with Tumor Microenvironment of Cholangiocarcinoma

2021 ◽  
Author(s):  
Jixiang Cao ◽  
Xi Chen ◽  
Guang Lu ◽  
Haowei Wang ◽  
Xinyu Zhang ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Prognostic Model ◽  
Cox Regression ◽  
Gene Signature ◽  
Risk Scores ◽  
Tumor Infiltration ◽  
Prognostic Signature ◽  
Cox Regression Analysis

Abstract Background: Cholangiocarcinoma (CCA) is the most common malignancy of the biliary tract with a dismal prognosis. Increasing evidence suggests that tumor microenvironment (TME) is closely associated with cancer prognosis. However, the prognostic signature for CCA based on TME has not yet been reported. This study aimed to develop a TME-related prognostic signature for accurately predicting the prognosis of patients with CCA. Methods: Based on the TCGA database, we calculated the stromal and immune scores using the ESTIMATE algorithm to assess TME in stromal and immune cells derived from CCA. TME-related differentially expressed genes were identified, followed by functional enrichment analysis and PPI network analysis. Univariate Cox regression analysis, Lasso Cox regression model and multivariable Cox regression analysis were performed to identify and construct the TME-related prognostic gene signature. Gene Set Enrichment Analyses (GSEA) was performed to further investigate the potential molecular mechanisms. The correlations between the risk scores and tumor infiltration immune cells were analyzed using Tumor Immune Estimation Resource (TIMER) database. Results: A total of 784 TME-related differentially expressed genes (DEGs) were identified, which were mainly enriched in immune-related processes and pathways. Among these TME-related DEGs, A novel two‑gene signature (including GAD1 and KLRB1) was constructed for CCA prognosis prediction. The AUC of the prognostic model for predicting the survival of patients at 1-, 2-, and 3- years was 0.811, 0.772, and 0.844, respectively. Cox regression analysis showed that the two‑gene signature was an independent prognostic factor. Based on the risk scores of the prognostic model, CCA patients were divided into high- and low-risk groups, and patients with high-risk score had shorter survival time than those with low-risk score. Furthermore, we found that the risk scores were negatively correlated with TME-scores and the number of several tumor infiltration immune cells, including B cells and CD4+ T cells. Conclusion: Our study established a novel TME-related gene signature to predict the prognosis of patients with CCA. This might provide a new understanding of the potential relationship between TME and CCA prognosis, and serve as a prognosis stratification tool for guiding personalized treatment of CCA patients.

scholarly journals IMUP and GPRC5A: Two Newly Identified Risk Score Indicators in Pancreatic Ductal Adenocarcinoma

2021 ◽  
Author(s):  
Rong Wei ◽  
Zixin Zeng ◽  
Ningning Shen ◽  
Ziyue Wang ◽  
Honghong Shen ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Immune Cells ◽  
Cox Regression ◽  
Bioinformatic Analysis ◽  
Cancer Development ◽  
Local Hospital ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Key Genes ◽  
The Difference

Abstract Background Pancreatic cancer has been a threateningly lethal malignant tumor worldwide. Despite the promising survival improvement in other cancer types attributing to the fast development of molecular precise medicine, the current treatment situation of pancreatic cancer is still woefully challenging since its limited response to neither traditional radiotherapy and chemotherapy nor emerging immunotherapy. The study is to explore potential responsible genes during the development of pancreatic cancer, thus identifying promising gene indicators and probable drug targets. Methods Different bioinformatic analysis were used to interpret the genetic events in pancreatic cancer development. Firstly, based on multiple cDNA microarray profiles from Gene Expression Omnibus (GEO) database, the genes with differently mRNA expression in cancer comparing to normal pancreatic tissues were identified, followed by being grouped based on the difference level. Then, GO and KEGG were performed to separately interpret the multiple groups of genes, and further Kaplan-Meier survival and Cox Regression analysis assisted us to scale down the candidate genes and select the potential key genes. Further, the basic physicochemical properties, the association with immune cells infiltration, mutation or other types variations besides expression gap in pancreatic cancer comparing to normal tissues of the selected key genes were analyzed. Moreover, the aberrant changed expression of key genes was validated by immunohistochemistry (IHC) experiment using local hospital tissue microarray samples and the clinical significance was explored based on TCGA clinical data. Results Firstly, a total of 22491 genes were identified to express differently in cancer comparing to normal pancreatic tissues based on 5 cDNA expression profiles, and the difference of 487/22491 genes was over 8-fold, and 55/487 genes were shared in multi profiles. Moreover, after genes interpretation which showed the >8-fold genes were mainly related to extracellular matrix structural constituent regulation, Kaplan-Meier survival and Cox-regression analysis were performed continually, and the result indicated that of the 55 extracellular locating genes, GPRC5A and IMUP were the only two independent prognostic indicators of pancreatic cancer. Further, detailed information of IMUP and GPRC5A were analyzed including their physicochemical properties, their expression and variation ratio and their association with immune cells infiltration in cancer, as well as the probable signaling pathways of genes regulation on pancreatic cancer development. Lastly, local IHC experiment performed on PAAD tissue array which was produced with 64 local hospital patients samples confirmed that GPRC5A and IMUP were abnormally up-regulated in pancreatic cancer, which directly associated with worse patients both overall (OS) and recurrence free survival (RFS). Conclusions Using multiple bioinformatic analysis as well as local hospital samples validation, we revealed that GPRC5A and IMUP expression were abnormally up-regulated in pancreatic cancer which associated statistical significantly with patients survival, and the genes’ biological features and clinical significance were also explored. However, more detailed experiments and clinical trials are obligatory to support their further potential drug-target role in clinical medical treatment.

scholarly journals TEAD4 Serves as a Prognostic Biomarker and Correlates With Immune Phenotype in Lower-Grade Gliomas

2021 ◽  
Author(s):  
Mu Chen ◽  
Bingsong Huang ◽  
Lei Zhu ◽  
Kui Chen ◽  
Hao Lian ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Clinical Outcome ◽  
Immune Cells ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Ppi Network ◽  
Mesenchymal Transition ◽  
Cox Regression Analysis ◽  
Genome Atlas

Abstract Background: Tumor-infiltrating immune cells (TIICs), which play a pivotal role in the tumor microenvironment, are intimately related to tumor progression and clinical outcome. It remains unclear which factors influence tumor immune infiltration in lower-grade gliomas (LGGs). TEAD4 (TEA Domain Transcription Factor 4) is an essential member of the Hippo pathway that is involved in cancer progression, epithelial-mesenchymal transition, metastasis, and cancer stem cell function across multiple types of cancers. However, the prognostic value of TEAD4 and its association with TIICs in LGG have been hardly studied. Methods: LGG data were obtained from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). TEAD4 expression between different groups was compared by R and survival analysis was implemented by Kaplan–Meier curves. In Virto experiments were conducted to investigate the role of TEAD4 in glioma cells. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network were used to investigate the differential biological processes and signaling pathways. Multiple computational methods were employed to estimate the association between TEAD4 expression and tumor microenvironment in LGG. Correlations were analyzed by Spearman correlationResults: TEAD4 expression was up-regulated in higher-grade gliomas and correlated with a poorer clinical outcome. Glioma cell proliferation and migration were promoted by TEAD4 overexpression. GSEA and PPI network indicated that multiple immune-related pathways and hub genes were closely associated with TEAD4 expression in LGG specimens. TEAD4 expression was negatively associated with glioma purity. Multivariate Cox regression analysis indicated that TEAD4 expression and tumor purity were independent prognostic factors in LGG. TEAD4 expression was positively correlated with the infiltration of multiple immune cells, including plasma cells, CD8+ T cells, and macrophages M1 and M2. Correlation analysis showed that the TEAD4 level can predict the efficacy of immune checkpoint blockade therapy. Conclusions: TEAD4 is highly related to glioma malignancy grades and multiple immune cell infiltration, suggesting TEAD4 can serve as a new biomarker for anti-cancer therapies in LGG.

scholarly journals CXCL10 is a Tumor Microenvironment and Immune Infiltration Related Prognostic Biomarker in Pancreatic Adenocarcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Huimin Huang ◽  
Wangxiao Zhou ◽  
Renpin Chen ◽  
Bingfeng Xiang ◽  
Shipeng Zhou ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Pancreatic Adenocarcinoma ◽  
Cox Regression ◽  
Predictive Biomarker ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Immune Infiltration ◽  
Protein Protein Interaction ◽  
Novel Biomarkers

Pancreatic adenocarcinoma (PAAD) is the 10th most common cancer worldwide and the outcomes for patients with the disease remain extremely poor. Precision biomarkers are urgently needed to increase the efficiency of early diagnosis and to improve the prognosis of patients. The tumor microenvironment (TME) and tumor immune infiltration are thought to impact the occurrence, progression, and prognosis of PAAD. Novel biomarkers excavated originating from the TME and immune infiltration may be effective in predicting the prognosis of PAAD patients. In the current study, the ESTIMATE and CIBERSORT algorithms were applied to estimate the division of immune and stromal components and the proportion of tumor-infiltrating immune cells in 182 PAAD cases downloaded from The Cancer Genome Atlas database. Intersection analyses of the Protein-Protein Interaction networks and Cox regression analysis identified the chemokine (CXC-motif) ligand 10 (CXCL10) as a predictive biomarker. We verified that CXCL10 in the TME negatively correlates with prognosis in PAAD and positively correlates with tumor cell differentiation. GSE62452 from the GEO database and cumulative survival analysis were performed to validate CXCL10 expression as an independent prognostic indicator. We also found that memory B cells, regulatory T cells, and macrophages M0 and M1 were correlated with the expression of CXCL10 indicating that expression of CXCL10 influenced the immune activity of the TME. Our data suggest that CXCL10 is beneficial as a prognostic indicator in PAAD patients and highlights the potential for immune targeted therapy in the treatment of PAAD.

scholarly journals SPOCK1 and POSTN are Valuable Prognostic Biomarkers and Correlate with Tumor Immune Infiltrates in Colorectal Cancer

2021 ◽  
Author(s):  
Caiqin Gan ◽  
Mengting Li ◽  
Ganjing Peng ◽  
Wenjie Li ◽  
Haizhou Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Immune Cells ◽  
Cox Regression ◽  
Prognostic Biomarkers ◽  
Immune Checkpoints ◽  
Cancer Tissue ◽  
Cox Regression Analysis ◽  
Colorectal Tissue ◽  
Key Genes ◽  
Immune Score

Abstract Background: Immune cells and stromal cells in the tumor microenvironment (TME) play a vital role in the initiation and progression of colorectal cancer (CRC). The study aimed to screen valuable prognostic biomarkers in CRC based on stromal and immune scores.Method: We used the ESTIMATE algorithm to calculate the immune and stromal scores of CRC samples in TCGA. Then the CRC samples were divided into high and low score groups based on the median value of the immune and stromal scores. Differentially expressed genes (DEGs) associated with immune score and stromal score were screened. WGCNA and univariate COX regression analysis were performed to further identify key prognostic genes. The prognostic value of key genes was validated based on The Gene Expression Profiling Interactive Analysis (GEPIA) and GSE17536 dataset.TIMER and CIBERSORT algorithms were applied to analyze the correlations among key genes and tumor-infiltrating immune cells. Several pairs of colon cancer tissue were used to be proven.Result: 1314 upregulated and 4 downregulated genes associated with immune score and stromal score were identified, which were significantly enriched in immune-related biological processes and pathways. Among these DEGs, SPOCK1 and POSTN were identified as key prognostic genes. High expression of SPCOK1 and POSTN was associated with advanced clinical stage, T stage, N stage, and poor prognosis of CRC. The results from CIBERSORT and TIMER revealed that SPOCK1 and POSTN were associated with tumor-infiltrating immune cells, especially macrophages and neutrophils. Meanwhile, in several pairs of human colorectal tissue samples, SPOK1 and POSTN were found to be significantly overexpressed in colorectal tissue compared with para-cancer tissue, and macrophage surface markers CD68 (co-expressed by M1 and M2 macrophages) and CD206 (M2-specific macrophage expression) were also overexpressed in cancer tissue. Besides, SPOCK1 and POSTN expression were positively correlated with the expression of immune checkpoints.Conclusion: Collectively, our results indicate that SPOCK1 and POSTN may be novel prognostic biomarkers in CRC and correlate with immune infiltrates.

scholarly journals The Role of CXCL10 in Prognosis of Patients with Colon Cancer and Tumor Microenvironment Remodeling

2020 ◽  
Author(s):  
Hongli Yin ◽  
Weiwei Song ◽  
Chenguang Han ◽  
Qiantai Mao ◽  
Zhaoshuai Ji ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Cox Regression Analysis ◽  
Immune Cell Subsets ◽  
Intersection Analysis ◽  
Immune Score

Abstract Background: In the past few years, tumor microenvironment (TME) has gradually become a hot topic in tumor research, which has important significance in the diagnosis, prevention and prognosis of tumors. Importantly, the immune system is a major contributing factor in TME, and studies have shown that tumors are partially infiltrated with various immune cell subsets. The immune characteristics of the TME play an essential role in evaluating the prognosis of patients. The immune scoring system based on the distribution of tumor local immune cell subsets and cell density has been an essential indicator in the evaluation of patient prognosis and has been verified in various tumor studies. TME is indispensable in the occurrence and development of Colorectal cancer (CRC). However, understanding the dynamic regulation of immunity and matrix components in TME of CRC is still a challenge and should be investigated further.Methods: In this study, we collected transcriptome RNA-seq data of 521 Colon adenocarcinoma (COAD) patients from The Cancer Genome Atlas (TCGA) data portal. We then estimate the fraction of stromal and immune cells in COAD cases by ESTIMATE algorithms [1]. A total of 1109 stromal-immune score-related differentially expressed genes (DEGs) were identified and used to generate a high-confidence protein–protein intersection (PPI) network and univariate COX regression analysis. Intersection analysis of the data from PPI network and univariate COX regression analysis showed the core gene. Then we performed Gene set enrichment analysis (GSEA), survival analysis and clinical analysis for CXCL10, and applied CIBERSORT algorithms to estimate the tumor-infiltrating immune cells (TICs) proportion in COAD cases.Results: The proportion of immune and stromal components in TME are associated with the progression of COAD. For example, tumor metastasis is inversely proportional to immune score. A total of 1109 DEGs were obtained by analyzing the low-score shared genes and the high-score shared genes by intersection analysis which might be the determinant of TME status. The GO enrichment analysis indicated that DEGs are associated with immune-related terms. KEGG pathway enrichment analysis showed that these DEGs are mainly enriched in cytokine cytokine receptor signaling pathway etc. Therefore, DEGs are related to immune regulation, which indicates that the participation of immune factors is the main characteristic of TME in COAD. Moreover, the expression level of CXCL10 has significantly connection with the prognosis of patients and the progression of COAD. Conclusion: Taken together, we conducted a comprehensive analysis of the TME in COAD, and predicted a prognostic indicator for COAD, which provided a novel insight for therapeutics of COAD.

scholarly journals MCEMP1 as a Tumor Microenvironment and Immune Infiltration Related Gene for Prognostic Prediction in Advanced Gastric Cancer

2021 ◽  
Author(s):  
Daijun Wang ◽  
Yanmei Gu ◽  
Yang Zhao ◽  
Yumin Li
Keyword(s):  
Gastric Cancer ◽  
Tumor Microenvironment ◽  
Advanced Gastric Cancer ◽  
Cancer Progression ◽  
Immune Cells ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Tissue Samples ◽  
Protein Protein Interaction ◽  
Immunotherapy Target

Abstract Background Tumor microenvironment (TME) has displayed profound clinical significance in cancer progression, prognosis and the efficacy of immunotherapy. However, the overall characteristics of TME in patients with advanced gastric cancer (AGC) have not been intensively studied. In order to get a more comprehensive understanding, this study aimed to investigate TME-related prognostic genes in patients with AGC based on bioinformatics, combined with histological verification.Methods Transcriptome and clinical data on stage III/IV GC were obtained from The Cancer Genome Atlas (TCGA) database. The data of stromal, immune scores and 22 infiltrating immune cells from AGC samples were evaluated by ESTIMATE and CIBERSORT algorithms. Then, mast cell-expressed membrane protein 1 (MCEMP1) was focused by integrated protein-protein interaction (PPI) network and Cox regression. The survival and expression analysis of MCEMP1 was evaluated and verified in tissues by immunohistochemistry (IHC) and quantitative real-time PCR (qRT-PCR).Results There was a positive correlation between TME scores and pathological grades. A total of 666 TME-related differential genes were screened. MCEMP1 was identified as a predictive factor related to the prognosis of AGC both in TCGA database and tissue samples. Further analysis indicated that MCEMP1 was involved in regulating pathways of immune activities. The results of CIBERSORT demonstrated that MCEMP1 expression was significantly correlated with the proportion of 8 kinds of infiltrating immune cells. Conclusion As a TME-related prognostic gene, MCEMP1 might play a crucial role in remodeling immune infiltrates in AGC patients, which might be a potential immunotherapy target for patients with AGC.

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