Dataset Information

Prognostic value of immune-related genes in the tumor microenvironment of lung adenocarcinoma and lung squamous cell carcinoma.

ABSTRACT: Non-small cell lung cancer (NSCLC), which consists mainly of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), are the leading cause of cancer deaths worldwide. In this study, we performed a comprehensive analysis of the tumor microenvironmental and genetic factors to identify prognostic biomarkers for NSCLC. We evaluated the immune and stromal scores of patients with LUAD and LUSC using data from The Cancer Genome Atlas database with the ESTIMATE algorithm. Based on these scores, the differentially expressed genes were obtained and immune-related prognostic genes were identified. Functional analysis and protein-protein interaction network further revealed the immune-related biological processes in which these genes participated. Additionally, 22 subsets of tumor-infiltrating immune cells (TIICs) in the tumor microenvironment were analyzed with the CIBERSORT algorithm. Finally, we validated these valuable genes using an independent cohort from the Gene Expression Omnibus database. The associations of the immune and stromal scores with patients' clinical characteristics and prognosis were positive in LUAD but negative in LUSC and the correlations of TIICs with clinical characteristics were clarified. Several differentially expressed genes were identified to be potential immune-related prognostic genes. This study comprehensively analyzed the tumor microenvironment and presented immune-related prognostic biomarkers for NSCLC.

SUBMITTER: Qu Y

PROVIDER: S-EPMC7138544 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Prognostic value of immune-related genes in the tumor microenvironment of lung adenocarcinoma and lung squamous cell carcinoma.

Qu Yan Y Cheng Bo B Shao Na N Jia Yibin Y Song Qingxu Q Tan Bingxu B Wang Jianbo J

Aging 20200325 6

Non-small cell lung cancer (NSCLC), which consists mainly of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), are the leading cause of cancer deaths worldwide. In this study, we performed a comprehensive analysis of the tumor microenvironmental and genetic factors to identify prognostic biomarkers for NSCLC. We evaluated the immune and stromal scores of patients with LUAD and LUSC using data from The Cancer Genome Atlas database with the ESTIMATE algorithm. Based on these scor ...[more]

PMID: 32209727

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Project description:Background Esophageal cancer (EC) is a highly aggressive malignancy that is classified as esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). Infiltrating stromal/immune cells, a major component of the tumor immune microenvironment (TIME), have prognostic significance in various cancers. Methods In this study we investigated genes and immune factors in the tumor microenvironment (TME) of ESCC and EAC that can serve as prognostic biomarkers. Stromal and immune scores were calculated using the Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) algorithm based on gene expression profiles of patient-derived tumor tissues in The Cancer Genome Atlas database. The correlation between ESTIMATE scores and survival rates in EC were analyzed. A comparison of high and low stromal/immune score groups revealed multiple differentially expressed genes (DEGs) as candidate prognostic genes; their role in immune-related biological processes was evaluated by functional and protein-protein interaction (PPI) network analyses, and the genes were validated using Gene Expression Omnibus datasets. Additionally, 22 tumor-infiltrating immune cell (TIIC) subsets were analyzed using the CIBERSORT algorithm. Results Median stromal score was higher whereas immune score was lower in ESCC than in EAC (both P<0.01). Stromal score was lower in female as compared to male ESCC patients (P<0.05), and was significantly correlated with T stage (P<0.05). In EAC, median immune score was higher in female as compared to male patients (P<0.05) and was correlated with tumor-node-metastasis stage (P<0.05). The identified DEGs were mainly involved in lymphocyte (especially T-lymphocyte) activation and carbohydrate binding. Moreover, the levels of infiltrating resting-stage dendritic cells, CD8+ T cells, naïve B cells, activated mast cells, and resting memory CD4+ T cells were significantly correlated with EC prognosis (P<0.05). Conclusions The immune microenvironment of ESCC and EAC are quite different. We have found genes with prognostic value in multiple tumor databases.

Project description:The host's immune system plays a pivotal role in many tumor types, including squamous cell carcinomas (SCCs). We aim to identify immunological prognosticators for lymph node metastases (LNM) and disease-specific survival (DSS) in penile SCC. For this retrospective observational cohort study, penile SCC patients (n?=?213) treated in the Netherlands Cancer Institute, were selected if sufficient formalin-fixed, paraffin-embedded tumor material was available. Analysis included previously described high-risk human papilloma virus (hrHPV) status, immunohistochemical scores for classical and non-classical human leukocyte antigen (HLA) class I, programmed death ligand-1 (PD-L1) expression, and novel data on tumor-infiltrating macrophages and cytotoxic an regulatory T-cells. Clinicopathological characteristics and extended follow-up were also included. Regression analyses investigated relationships of the immune parameters with LNM and DSS. In the total cohort, diffuse PD-L1 tumor-cell expression, CD163+ macrophage infiltration, non-classical HLA class I upregulation, and low stromal CD8+ T-cell infiltration were all associated with LNM. In the multivariable model, only tumor PD-L1 expression remained a significant predictor for LNM (odds ratio (OR) 2.8, p?=?0.05). hrHPV negativity and diffuse PD-L1 tumor-cell expression were significantly associated with poor DSS and remained so upon correction for clinical parameters [hazard ratio (HR) 9.7, p?<?0.01 and HR 2.8, p?=?0.03]. The only immune factor with different expression in HPV+ and HPV- tumors was PD-L1, with higher PD-L1 expression in the latter (p?=?0.03). In the HPV- cohort (n?=?158), LNM were associated with diffuse PD-L1 tumor-cell expression, high intratumoral CD163+ macrophage infiltration, and low number of stromal CD8+ T-cells. The first two parameters were also linked to DSS. In the multivariable regression model, diffuse PD-L1 expression remained significantly unfavorable for DSS (HR 5.0, p?<?0.01). These results emphasize the complexity of the tumor microenvironment in penile cancer and point toward several possible immunotherapy targets. Here described immune factors can aid risk-stratification and should be evaluated in clinical immunotherapy studies to ultimately lead to patient tailored treatment.

Project description:Background Lung squamous cell carcinoma (LUSC) is a prevalent and lethal malignancy with a poor clinical prognosis. Major constituents of the tumor microenvironment (TME) include infiltrating immune cells and stromal cells, which play a pivotal role in the progression and growth of the disease. To improve the understanding of the prognostic influence of immune and stromal cell-related genes for patients with the disease, we performed a comprehensive bioinformatics analysis to identify TME-relevant biomarkers, and investigated the potential role of these candidate signatures in LUSC. Methods Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) assessed the samples of LUSC obtained from The Cancer Genome Atlas (TCGA). The samples were grouped according to their immune/stromal scores (high or low). Multivariate cox regression and receiver operating characteristic curves (ROC) were implemented to construct the risk assessment model for prognosis prediction. The co-upregulated differentially expressed genes (DEGs) in the immune and stromal groups were used for further analyses. Overall survival (OS) curves were used to determine the prognostic value of the DEGs, and the TME-related DEGs were verified with Gene Expression Omnibus (GEO) datasets. The functional assessments were performed include Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein–protein interaction (PPI) analyses. Results The immune/stromal scores calculated by ESTIMATE showed significant associations with OS (log-rank P<0.05). In addition, the prognostic risk score model based on immune and stromal scores also showed significant correlations with OS. A total of 94 TME-related genes were obviously related to poor OS. Among them, BHMT2, FES, HSPB7, NOVA2, LPAP2, and SEMA3B (BFHNLS) were confirmed using GSE4573 and GSE17710 datasets. The functional assessments exhibited those TME-related genes mostly participate in immune response, cytokine-cytokine receptor interaction, and metabolic pathways, which elucidated the probable correlation of TME with tumorigenesis in LUSC. Conclusions In this study, 6 potential biomarkers named BFHNLS were identified as TME-related genes with prognostic value based on immune and stromal scores of LUSC patients of TCGA, and were verified using GEO datasets, which might serve as therapeutic targets.

Project description:AbstractThe tumor microenvironment (TME) plays an important role in the development of breast cancer. Due to limitations in experimental conditions, the molecular mechanism of TME in breast cancer has not yet been elucidated. With the development of bioinformatics, the study of TME has become convenient and reliable.Gene expression and clinical feature data were downloaded from The Cancer Genome Atlas database and the Molecular Taxonomy of Breast Cancer International Consortium database. Immune scores and stromal scores were calculated using the Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data algorithm. The interaction of genes was examined with protein-protein interaction and co-expression analysis. The function of genes was analyzed by gene ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes analysis and gene set enrichment analysis. The clinical significance of genes was assessed with Kaplan-Meier analysis and univariate/multivariate Cox regression analysis.Our results showed that the immune scores and stromal scores of breast invasive ductal carcinoma (IDC) were significantly lower than those of invasive lobular carcinoma. The immune scores were significantly related to overall survival of breast IDC patients and both the immune and stromal scores were significantly related to clinical features of these patients. According to the level of immune/stromal scores, 179 common differentially expressed genes and 5 hub genes with prognostic value were identified. In addition, the clinical significance of the hub genes was validated with data from the molecular taxonomy of breast cancer international consortium database, and gene set enrichment analysis analysis showed that these hub genes were mainly enriched in signaling pathways of the immune system and breast cancer.We identified five immune-related hub genes with prognostic value in the TME of breast IDC, which may partly determine the prognosis of breast cancer and provide some direction for development of targeted treatments in the future.

Dataset Information

Prognostic value of immune-related genes in the tumor microenvironment of lung adenocarcinoma and lung squamous cell carcinoma.

Publications

Prognostic value of immune-related genes in the tumor microenvironment of lung adenocarcinoma and lung squamous cell carcinoma.

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