scholarly journals Bioinformatics and Immune Infiltration Analyses Reveal the Key Pathway and Immune Cells in the Pathogenesis of Hypertrophic Cardiomyopathy

2021 ◽  
Vol 8 ◽  
Author(s):  
Xu-Zhe Zhang ◽  
Si Zhang ◽  
Ting-Ting Tang ◽  
Xiang Cheng
Keyword(s):  
Gender Differences ◽  
Hypertrophic Cardiomyopathy ◽  
Immune Cells ◽  
Gene Set Enrichment Analysis ◽  
Clinical Samples ◽  
Cardiac Tissues ◽  
Immune Infiltration ◽  
Healthy Control ◽  
Public Datasets ◽  
Compositional Patterns

Objective: This study was designed to identify the key pathway and immune cells for hypertrophic cardiomyopathy (HCM) via bioinformatics analyses of public datasets and evaluate the significance of immune infiltration in the pathogenesis of HCM.Methods: Expressional profiling from two public datasets (GSE36961 and GSE141910) of human HCM and healthy control cardiac tissues was obtained from the GEO database. After data preprocessing, differentially expressed genes (DEGs) were then screened between HCM and healthy control cardiac tissues in parallel. Gene Ontology, pathway functional enrichment, and gene set enrichment analysis were performed using DAVID and GSEA application. The compositional patterns of immune and stromal cells in HCM and control cardiac tissues were estimated based on the merged data using xCell. Protein–protein interaction (PPI) network and module analyses were constructed by STRING and Cytoscape applications. Gender-based expressional differences analyses were also conducted to explore gender differences in HCM. GSE130036 and clinical samples were used for verification analyses.Results: A total of 310 DEGs were identified. Upregulated DEGs were mainly enriched in “adhesion” and “apoptotic process” in the biological process. As for the downregulated DEGs, “inflammatory response,” “innate immune response,” “phagosome,” and “JAK-STAT signaling pathway” were highly enriched. Immune infiltration analyses suggested that the scores of macrophages, monocytes, DC, Th1, Treg, and plasma cells in the HCM group were significantly decreased, while CD8+ T cells, basophils, fibroblasts, and platelets were significantly enriched. Module analyses revealed that STAT3, as the hub genes in HCM together with LYVE1+CD163+ macrophages, may play a key role in the pathogenesis of HCM while there were no obvious gender differences in the HCM samples from selected datasets. Verification analyses performed on GSE130036 and clinical samples showed a strong positive correlation (Spearman correlation = 0.7646) and a good co-localization relationship between LYVE1 and CD163, suggesting the potential function of LYVE1+CD163+ macrophages in maintaining the homeostasis of cardiac tissue.Conclusion: STAT3-related pathway and CD163+LYVE1+ macrophages were identified as the potential key pathway and immune cells in HCM and may serve as interesting targets for further in-depth research.

scholarly journals Prognostic and immunological value of LTB4R in pan-cancer

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><p>LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain.</p> </sec> <sec><title>Methods</title><p>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.</p> </sec> <sec><title>Results</title><p>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.</p> </sec> <sec><title>Conclusion</title><p>The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer.</p> </sec> </abstract>

scholarly journals APOC1 is a Potential Prognostic Biomarker and Correlated With Immune Infiltration in ESCC

2020 ◽  
Author(s):  
Jia-yi XIE ◽  
Ming Liu ◽  
Yaxin Luo ◽  
Zhen Wang ◽  
Zhenghong Lu ◽  
...  
Keyword(s):  
T Cells ◽  
Transcription Factors ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Killer Cell ◽  
Gene Set Enrichment Analysis ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract PurposeEsophageal cancer (EC) is the sixth leading cause of cancer death worldwide. Esophageal squamous cell carcinoma (ESCC) is a predominant subtype of EC. Identifying diagnostic biomarkers for ESCC is necessary for cancer practice. Increasing evidence illustrates that apolipoprotein C-1 (APOC1) participates in the carcinogenesis. However, the biological function of APOC1 in ESCC remains unclear. Patients and methodsWe investigated the expression level of APOC1 using TIMER2.0 and GEO databases, the prognostic value of APOC1 in ESCC using Kaplan-Meier plotter and TCGA databases. We used LinkedOmics to identify co-expressed genes with APOC1 and perform GO and KEGG pathway analysis. The target networks of kinases, miRNAs and transcription factors were predicted by gene set enrichment analysis (GSEA). The correlations between APOC1 and immune infiltration were calculated using TIMER2.0 and CIBERSORT databases. We further performed the prognostic analysis based on APOC1 expression levels in related immune cells subgroups via Kaplan-Meier plotter database. ResultsAPOC1 was found overexpressed in tumor tissues in multiple ESCC cohorts and high APOC1 expression was related to a dismal prognosis. Multivariate analysis confirmed that APOC1 overexpression was an independent indicator of poor OS. Functional network analysis indicated that APOC1 might regulate the natural killer cell mediated cytotoxicity, phagosome, AMPK and hippo signaling through pathways involving some cancer-related kinases, miRNA and transcription factors. Immune infiltration analysis showed that APOC1 was significantly positively correlated with M0 macrophages cells, M1 macrophages cells and activated NK cells, negatively correlated with regulatory T cells, CD8 T cells, neutrophils and monocytes. High APOC1 expression had a poor prognosis in server immune cells subgroups in ESCC, including decreased CD8+ T cells subgroups. ConclusionThese findings suggest that increased expression of APOC1 is related to poor prognosis and immune infiltration in ESCC. APOC1 holds promise for serving as a valuable diagnostic and prognostic marker in ESCC.

scholarly journals Identification of potential therapeutic targets for atherosclerosis by analysing the gene signature related to different immune cells and immune regulators in atheromatous plaques

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yang Shen ◽  
Li-rong Xu ◽  
Xiao Tang ◽  
Chang-po Lin ◽  
Dong Yan ◽  
...  
Keyword(s):  
Immune Cells ◽  
Plasma Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gamma Delta ◽  
Hub Genes ◽  
Gene Set Enrichment ◽  
Bioinformatics Analyses ◽  
Immune Infiltration ◽  
Atheromatous Plaques

Abstract Background Atherosclerosis is a chronic inflammatory disease that affects multiple arteries. Numerous studies have shown the inherent immune diversity in atheromatous plaques and suggest that the dysfunction of different immune cells plays an important role in atherosclerosis. However, few comprehensive bioinformatics analyses have investigated the potential coordinators that might orchestrate different immune cells to exacerbate atherosclerosis. Methods Immune infiltration of 69 atheromatous plaques from different arterial beds in GSE100927 were explored by single-sample-gene-set enrichment analysis (presented as ssGSEA scores), ESTIMATE algorithm (presented as immune scores) and CIBERSORT algorithm (presented as relative fractions of 22 types of immune cells) to divide these plaques into ImmuneScoreL cluster (of low immune infiltration) and ImmuneScoreH cluster (of high immune infiltration). Subsequently, comprehensive bioinformatics analyses including differentially-expressed-genes (DEGs) analysis, protein–protein interaction networks analysis, hub genes analysis, Gene-Ontology-terms and KEGG pathway enrichment analysis, gene set enrichment analysis, analysis of expression profiles of immune-related genes, correlation analysis between DEGs and hub genes and immune cells were conducted. GSE28829 was analysed to cross-validate the results in GSE100927. Results Immune-related pathways, including interferon-related pathways and PD-1 signalling, were highly enriched in the ImmuneScoreH cluster. HLA-related (except for HLA-DRB6) and immune checkpoint genes (IDO1, PDCD-1, CD274(PD-L1), CD47), RORC, IFNGR1, STAT1 and JAK2 were upregulated in the ImmuneScoreH cluster, whereas FTO, CRY1, RORB, and PER1 were downregulated. Atheromatous plaques in the ImmuneScoreH cluster had higher proportions of M0 macrophages and gamma delta T cells but lower proportions of plasma cells and monocytes (p < 0.05). CAPG, CECR1, IL18, IGSF6, FBP1, HLA-DPA1 and MMP7 were commonly related to these immune cells. In addition, the advanced-stage carotid plaques in GSE28829 exhibited higher immune infiltration than early-stage carotid plaques. Conclusions Atheromatous plaques with higher immune scores were likely at a more clinically advanced stage. The progression of atherosclerosis might be related to CAPG, IGSF6, IL18, CECR1, FBP1, MMP7, FTO, CRY1, RORB, RORC, PER1, HLA-DPA1 and immune-related pathways (IFN-γ pathway and PD-1 signalling pathway). These genes and pathways might play important roles in regulating immune cells such as M0 macrophages, gamma delta T cells, plasma cells and monocytes and might serve as potential therapeutic targets for atherosclerosis.

scholarly journals CLDN6 and CLDN10 are Associated with Immune Infiltration of Ovarian Cancer: A Study of Claudin Family

2020 ◽  
Author(s):  
Peipei Gao ◽  
Ting Peng ◽  
Canhui Cao ◽  
Shitong Lin ◽  
Ping Wu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
T Cell ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Markers ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
The Relationship

Abstract Background: Claudin family is a group of membrane proteins related to tight junction. There are many studies about them in cancer, but few studies pay attention to the relationship between them and the tumor microenvironment. In our research, we mainly focused on the genes related to the prognosis of ovarian cancer, and explored the relationship between them and the tumor microenvironment of ovarian cancer.Methods: The cBioProtal provided the genetic variation pattern of claudin gene family in ovarian cancer. The ONCOMINE database and Gene Expression Profiling Interactive Analysis (GEPIA) were used to exploring the mRNA expression of claudins in cancers. The prognostic potential of these genes was examined via Kaplan-Meier plotter. Immunologic signatures were enriched by gene set enrichment analysis (GSEA). The correlations between claudins and the tumor microenvironment of ovarian cancer were investigated via Tumor Immune Estimation Resource (TIMER).Results: In our research, claudin genes were altered in 363 (62%) of queried patients/samples. Abnormal expression levels of claudins were observed in various cancers. Among them, we found that CLDN3, CLDN4, CLDN6, CLDN10, CLDN15 and CLDN16 were significantly correlated with overall survival of patients with ovarian cancer. GSEA revealed that CLDN6 and CLDN10 were significantly enriched in immunologic signatures about B cell, CD4 T cell and CD8 T cell. What makes more sense is that CLDN6 and CLDN10 were found related to the tumor microenvironment. CLDN6 expression was negatively correlated with immune infiltration level in ovarian cancer, and CLDN10 expression was positively correlated with immune infiltration level in ovarian cancer. Further study revealed the CLDN6 expression level was negatively correlated with gene markers of various immune cells in ovarian cancer. And, the expression of CLDN10 was positive correlated with gene markers of immune cells in ovarian cancer.Conclusions: CLDN6 and CLDN10 were prognostic biomarkers, and correlated with immune infiltration in ovarian cancer. Our results revealed new roles for CLDN6 and CLDN10, and they were potential therapeutic targets in the treatment of ovarian cancer.

scholarly journals DOCK2 is a Biomarker for Predicting the Prognosis of Lung Adenocarcinoma and Associated with Immune Infiltration

2021 ◽  
Author(s):  
Jie He ◽  
Tongtong Zhang ◽  
Jian Sun ◽  
Guangnan Liu
Keyword(s):  
Immune Response ◽  
Lung Adenocarcinoma ◽  
Immune Cells ◽  
Bioinformatics Analysis ◽  
Cox Regression ◽  
Clinical Sample ◽  
Clinical Samples ◽  
Data Set ◽  
Immune Infiltration ◽  
Low Expression

Abstract Background: dedicator of cytokinesis 2 is an atypical guanine exchange factor, which is particularly expressed in hematopoietic cells and modulates the activation along with the migration of immune cells by activating Ras--related C3 botulinum toxin substrate (Rac). Nevertheless, the role of DOCK2 in lung adenocarcinoma (LUAD) remains unclear.Methods: Herein, we performed bioinformatics analysis of lung adenocarcinoma data abstracted from TCGA (The Cancer Genome Altas) and GEO (Gene Expression Omnibus) data resources, and combined with web tools consisting of LinkedOmics, TIMER, and TISIDB. Finally, combined with clinical lung adenocarcinoma samples, we verified the expression of DOCK2 in tissue and its effect on the prognosis of lung adenocarcinoma.Results: In the TCGA lung adenocarcinoma data set, the expression of DOCK2 was down-regulated in tumor tissues and verified in multiple independent cohorts. In addition, the low expression of DOCK2 indicates a poor overall survival(OS) in both TCGA and other GEO data sets and in our clinical samples. COX regression data illustrated that the low expression of DOCK2 was an independent predictor for OS. Functional network analysis shows that DOCK2 participates in immune response through interleukin production, neuroinflammatory response, acquired immune response, leukocyte migration and activation of lymph node cells, and is related to multiple immune-related pathways. Besides, the expression of DOCK2 was remarkably related with many kinds of tumor infiltrating immune cells.Conclusion: combined with bioinformatics analysis and clinical sample verification, our study shows that DOCK2 can independently estimate the prognosis of lung adenocarcinoma and is related to immune infiltration. As a promising prognostic indicator and potential target of immunotherapy, the potential effect of DOCK2 on lung adenocarcinoma and its molecular mechanism are worthy of further discussion.

scholarly journals Identification of Diagnostic Markers Correlated With HIV+ Immune Non-response Based on Bioinformatics Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Ruojing Bai ◽  
Zhen Li ◽  
Yuying Hou ◽  
Shiyun Lv ◽  
Ran Wang ◽  
...  
Keyword(s):  
T Cell ◽  
Microarray Data ◽  
Immune Cells ◽  
Mononuclear Cells ◽  
Enrichment Analysis ◽  
Diagnostic Markers ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Clinical Samples ◽  
Pathway Enrichment Analysis

Background: HIV-infected immunological non-responders (INRs) are characterized by their inability to reconstitute CD4+ T cell pools after antiretroviral therapy. The risk of non-AIDS-related diseases in INRs is increased, and the outcome and prognosis of INRs are inferior to that of immunological responders (IRs). However, few markers can be used to define INRs precisely. In this study, we aim to identify further potential diagnostic markers associated with INRs through bioinformatic analyses of public datasets.Methods: This study retrieved the microarray data sets of GSE106792 and GSE77939 from the Gene Expression Omnibus (GEO) database. After merging two microarray data and adjusting the batch effect, differentially expressed genes (DEGs) were identified. Gene Ontology (GO) resource and Kyoto Encyclopedia of Genes and Genomes (KEGG) resource were conducted to analyze the biological process and functional enrichment. We performed receiver operating characteristic (ROC) curves to filtrate potential diagnostic markers for INRs. Gene Set Enrichment Analysis (GSEA) was conducted to perform the pathway enrichment analysis of individual genes. Single sample GSEA (ssGSEA) was performed to assess scores of immune cells within INRs and IRs. The correlations between the diagnostic markers and differential immune cells were examined by conducting Spearman’s rank correlation analysis. Subsequently, miRNA-mRNA-TF interaction networks in accordance with the potential diagnostic markers were built with Cytoscape. We finally verified the mRNA expression of the diagnostic markers in clinical samples of INRs and IRs by performing RT-qPCR.Results: We identified 52 DEGs in the samples of peripheral blood mononuclear cells (PBMC) between INRs and IRs. A few inflammatory and immune-related pathways, including chronic inflammatory response, T cell receptor signaling pathway, were enriched. FAM120AOS, LTA, FAM179B, JUN, PTMA, and SH3YL1 were considered as potential diagnostic markers. ssGSEA results showed that the IRs had significantly higher enrichment scores of seven immune cells compared with IRs. The miRNA-mRNA-TF network was constructed with 97 miRNAs, 6 diagnostic markers, and 26 TFs, which implied a possible regulatory relationship.Conclusion: The six potential crucial genes, FAM120AOS, LTA, FAM179B, JUN, PTMA, and SH3YL1, may be associated with clinical diagnosis in INRs. Our study provided new insights into diagnostic and therapeutic targets.

Integrative characterization and validation of tumor-associated immune signature combined with immune-infiltration analysis in clear cell renal cell carcinoma

2020 ◽  
Author(s):  
Hongxi Chen ◽  
Jinliang Xie ◽  
Peng Jin
Keyword(s):  
Functional Analysis ◽  
Immune Cells ◽  
Immune Cell ◽  
Differential Analysis ◽  
T Regulatory Cell ◽  
Cell Renal Cell Carcinoma ◽  
Differential Abundance ◽  
Immune Signature ◽  
Immune Infiltration ◽  
Public Datasets

Abstract Background We aimed to explore and validate a prognostic immune signature for predicting the prognosis of ccRCC patients, combined with immune-infiltration analysis. Methods We obtained the multi-omics data from public datasets. Differential analysis was performed by edgeR package. Prognostic immune signature was identified by univariate Cox analysis, and we constructed an integrative tumor-associated immune Genes (TAIG) model from the multivariate Cox results. Functional analysis was conducted to uncover the related crosstalk. Importantly, we implemented the CIBERSORT algorithm to estimate the immune cell fractions in ccRCC samples and analyzed the differential abundance of tumor-infiltrating immune cells in two TAIG groups using Wilcoxon rank-sum test. The prognostic role of differential immune cells was further assessed by Kaplan-Meier analysis. In addition, we investigated the associations of single immune signature with specific immune cells. Results A total of 628 ccRCC patients were included in our integrative analysis, including 537 ccRCC patients in discovery group and 91 patients in validation group. Then, we identified the 14 key immune signatures. The AUC was 0.802 and patients with higher TAIG suffered from worse prognosis. Correlation analysis indicated that TAIG correlated tightly with clinical variables and TMB. Moreover, functional analysis also implicated the immune-related GO items or crosstalk. Therefore, we discovered the relationships of TAIG with tumor-infiltrating immune cells. The differential abundance of immune cells showed significant prognostic difference consisted of memory activated CD4 + T cell, T follicular helper cells, T regulatory cell, and so on. Moreover, we also characterized the associations between identified signature with specific immune cells. Finally, the 5-year AUC in ICGC cohort was 0.72, suggesting the robustness of TAIG that we constructed. Conclusions Totally, our team characterized the tumor-associated immune signature in ccRCC and further uncovered the prognostic tumor-infiltrating immune cells related with TAIG, providing a comprehensive foundation for investigating mechanisms or individualized immunotherapy.

HSF2 is a Promising Prognostic Biomarker and is Correlated With Immune Infiltration in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Bihui Han ◽  
Yanxiu Meng ◽  
Yumei Fan ◽  
Bing Liu ◽  
Jiajie Hou ◽  
...  
Keyword(s):  
Immune Cells ◽  
Critical Role ◽  
Enrichment Analysis ◽  
Normal Liver ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
The Relationship ◽  
Kaplan Meier Plotter

Abstract BackgroundHepatocellular carcinoma (HCC) is one of the most common malignancies and ranks as the second leading cause of cancer-related mortality worldwide. Heat shock factor 2 (HSF2) is a transcription factor that plays a critical role in development, particularly corticogenesis and spermatogenesis. However, studies on the expression and prognostic value of HSF2 and its association with tumor-infiltrating immune cells in HCC are still rare. MethodsThe TCGA, Oncomine, UALCAN, HCCDB and HPA databases were used to investigate HSF2 expression in HCC. Kaplan-Meier plotter, GEPIA and HCCDB databases were used to evaluate the association of HSF2 with the prognosis of HCC patients. Genetic alteration of HSF2 was examined by the cBioPortal database. The mechanism was investigated with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GESA), and the relationship between HSF2 expression and immune infiltration was explored through the TIMER database and CIBERSORT algorithm.Results In the present study, we found that HSF2 expression was significantly upregulated in HCC compared with normal liver tissues. High HSF2 expression was associated with poor survival in HCC patients. GO, KEGG and GESA analyses demonstrated that HSF2 was associated with various signaling pathways, including the immune response. Notably, HSF2 expression was significantly correlated with the infiltration levels of different immune cells. HSF2 expression also displayed a significant correlation with multiple immune marker sets in HCC. ConclusionsIn summary, we explored the clinical significance of HSF2 and provided a therapeutic basis for the early diagnosis, prognostic judgment, and immunotherapy of HCC.

scholarly journals Identification of key genes and novel immune infiltration-associated biomarkers of sepsis

2020 ◽  
Vol 26 (8) ◽  
pp. 666-682
Author(s):  
Chao Xu ◽  
Jianbo Xu ◽  
Ling Lu ◽  
Wendan Tian ◽  
Jinling Ma ◽  
...  
Keyword(s):  
B Cells ◽  
Nk Cells ◽  
Immune Cells ◽  
Gene Set Enrichment Analysis ◽  
Cell Mediated Immunity ◽  
Related Gene ◽  
Immune Infiltration ◽  
Immune Related Gene ◽  
Convolution Algorithm ◽  
Significant Difference

Sepsis is the major cause of mortality in the intensive care unit. The aim of this study was to identify the key prognostic biomarkers of abnormal expression and immune infiltration in sepsis. In this study, a total of 36 differentially expressed genes were identified to be mainly involved in a number of immune-related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The hub genes ( MMP9 and C3AR1) were significantly related to the prognosis of sepsis patients. The immune infiltration analysis indicated a significant difference in the relative cell content of naive B cells, follicular Th cells, activated NK cells, eosinophils, neutrophils and monocytes between sepsis and normal controls. Weighted gene co-expression network analysis and a de-convolution algorithm that quantifies the cellular composition of immune cells were used to analyse the sepsis expression data from the Gene Expression Omnibus database and to identify modules related to differential immune cells. CEBPB is the key immune-related gene that may be involved in sepsis. Gene set enrichment analysis revealed that CEBPB is involved in the processes of T cell selection, B cell–mediated immunity, NK cell activation and pathways of T cells, B cells and NK cells. Therefore, CEBPB may play a key role in the biological and immunological processes of sepsis.

scholarly journals Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Shibai Yan ◽  
Juntao Fang ◽  
Yongcai Chen ◽  
Yong Xie ◽  
Siyou Zhang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
T Cells ◽  
Immune Cells ◽  
Malignant Tumors ◽  
Treatment Strategies ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Immune Infiltration

Abstract Background Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV. Methods Based on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored. Results A prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8). Conclusion The present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.

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