Dataset Information

Immune Infiltration and Clinical Outcome of Super-Enhancer-Associated lncRNAs in Stomach Adenocarcinoma.

ABSTRACT: Super-enhancers (SEs) comprise large clusters of enhancers that highly enhance gene expression. Long non-coding RNAs (lncRNAs) tend to be dysregulated in cases of stomach adenocarcinoma (STAD) and are vital for balancing tumor immunity. However, whether SE-associated lncRNAs play a role in the immune infiltration of STAD remains unknown. In the present study, we identified SE-associated lncRNAs in the H3K27ac ChIP-seq datasets from 11 tumor tissues and two cell lines. We found that the significantly dysregulated SE-associated lncRNAs were strongly correlated with immune cell infiltration through the application of six algorithms (ImmuncellAI, CIBERSORT, EPIC, quantiSeq, TIMER, and xCELL), as well as immunomodulators and chemokines. We found that the expression of SE-associated lncRNA TM4SF1-AS1 was negatively correlated with the proportion of CD8+ T cells present in STAD. TM4SF1-AS1 suppresses T cell-mediated immune killing function and predicts immune response to anti-PD1 therapy. ChIP-seq, Hi-C and luciferase assay results verified that TM4SF1-AS1 was regulated by its super-enhancer. RNA-seq data showed that TM4SF1-AS1 is involved in immune and cancer-related processes or pathways. In conclusion, SE-associated lncRNAs are involved in the tumor immune microenvironment and act as indicators of clinical outcomes in STAD. This study highlights the importance of SE-associated lncRNAs in the immune regulation of STAD.

SUBMITTER: Peng L

PROVIDER: S-EPMC8927879 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Immune Infiltration and Clinical Outcome of Super-Enhancer-Associated lncRNAs in Stomach Adenocarcinoma.

Peng Li L Peng Jiang-Yun JY Cai Dian-Kui DK Qiu Yun-Tan YT Lan Qiu-Sheng QS Luo Jie J Yang Bing B Xie Hai-Tao HT Du Ze-Peng ZP Yuan Xiao-Qing XQ Liu Yue Y Yin Dong D

Frontiers in oncology 20220303

Super-enhancers (SEs) comprise large clusters of enhancers that highly enhance gene expression. Long non-coding RNAs (lncRNAs) tend to be dysregulated in cases of stomach adenocarcinoma (STAD) and are vital for balancing tumor immunity. However, whether SE-associated lncRNAs play a role in the immune infiltration of STAD remains unknown. In the present study, we identified SE-associated lncRNAs in the H3K27ac ChIP-seq datasets from 11 tumor tissues and two cell lines. We found that the significa ...[more]

PMID: 35311149

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Project description:Stomach adenocarcinoma (STAD) is a common gastric histological cancer type with a high mortality rate. Immunogenic cell death (ICD) plays a key factor during carcinogenesis progress, whereas the prognostic value and role of ICD-related genes (ICDRGs) in STAD remain unclear. The MSigDB database collecting ICDRGs were selected by univariate Cox regression analysis and LASSO algorithm to establish a novel risk model. The Kaplan-Meier survival analysis indicated a significant difference of OS rate of patients by risk score stratification. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape by risk stratification. Subgroup analysis and tumor mutation burden analysis were also analyzed to identify characteristics between groups. Differences in therapeutic responsiveness to chemotherapeutic drugs and targeted drugs were also analyzed between high-risk group and low-risk group. The impact of one ICDRG, GPX1, on the proliferation, migration and invasiveness of was confirmed by in vitro experiments in GC cells to test the reliability of bioinformatics results. This study gives evidence of the involvement of ICD process in STAD and provides a new perspective for further accurate assessment of prognosis and therapeutic efficacy in STAD patients. Stomach adenocarcinoma (STAD) is a common gastric histological cancer type with a high mortality rate. Immunogenic cell death (ICD) plays a key factor during carcinogenesis progress, whereas the prognostic value and role of ICD-related genes (ICDRGs) in STAD remains unclear. The MSigDB database collected ICDRGs were selected by univariate Cox regression analysis and LASSO algorithm to establish a novel risk model. The Kaplan-Meier survival analysis indicated a significant difference of OS rate of patients by risk score stratification. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape by risk stratification. Subgroup analysis and tumor mutation burden analysis were also analyzed to identify characteristics between groups. Differences in therapeutic responsiveness to chemotherapeutic drugs and targeted drugs were also analyzed between high-risk group and low-risk group. The impact of one ICDRG, GPX1, on the proliferation, migration and invasiveness of was confirmed by in vitro experiments in GC cells to test the reliability of bioinformatics results. This study gives evidence of the involvement of ICD process in STAD and provides a new perspective for further accurate assessment of prognosis and therapeutic efficacy in STAD patients.

Project description:BackgroundLung adenocarcinoma (LUAD) remains the most common type of lung cancer and is associated with distant metastasis and poor prognosis. Epithelial-mesenchymal transition (EMT) plays crucial roles in carcinogenesis, embryogenesis, and wound healing. EMT-related molecules may be adopted for early diagnosis and prognosis of cancer and targeting them may constitute an attractive strategy for treatment. This study aims to identify the EMT-related long non-coding RNAs (lncRNAs) and develop a risk signature to accurately predict the prognosis of LUAD patients.MethodsThe RNA-seq data and corresponding clinical profiles were obtained from LUAD cohort of The Cancer Genome Atlas (TCGA) database. EMT-related lncRNAs significantly associated with prognosis were identified by Pearson correlation analysis and univariate regression analysis. Subsequently, an EMT-related prognostic risk signature was developed through LASSO and multivariate regression analyses. Kaplan Meier and receiver operating characteristic curve analysis were implemented to assess the predictive performance of the signature. The nomogram was constructed to predict the 1-year, 3-year, and 5-year overall survival of LUAD patients. Additionally, enrichment analyses were carried out to identify probable biologic processes and cellular pathways involved in the signature. The correlation of immune cell infiltration and risk score was also evaluated by CIBERSORT algorithm. Finally, we constructed a ceRNA network to further study possible downstream targets and molecular mechanisms of EMT-related lncRNAs in LUAD.ResultsEight EMT-related lncRNAs were identified to develop a prognostic risk signature in LUAD. Patients with high-risk scores had worse survival outcomes than those with low-risk scores. The signature showed robust predictive potential, and was verified to be an independent prognostic factor. Moreover, the risk score based on the signature was significantly correlated with immune cell infiltration in LUAD.ConclusionsWe established and validated a prognostic signature that reflects the tumor microenvironment characteristics and predicts the outcomes for LUAD.

Project description:BackgroundCollagen (COL) genes, play a key role in tumor invasion and metastasis, are involved in tumor extracellular matrix (ECM)-receptor interactions and focal adhesion pathways. However, studies focusing on the diagnostic value of the COL4 family in stomach adenocarcinoma (STAD) are currently lacking.MethodsThe TCGA database was employed to retrieve the clinical features and RNA sequencing expression profiles of patients with STAD. We conducted an investigation to examine the expression disparities between STAD and adjacent normal tissues. Kaplan-Meier survival analysis was utilized to assess their prognostic significance, while Spearman correlation analysis was employed to determine their association with immune checkpoint genes and immunomodulatory molecules. Furthermore, GO and KEGG analyses were performed on the COL4s-related genes, revealing potential biological pathways through gene set enrichment analysis (GSEA). Subsequently, we explored the extent of immune infiltration of the COL4 family in STAD using the TIMER database. Lastly, the expression levels of the COL4 family in STAD were further validated through quantitative PCR (qPCR) and western blot techniques.ResultsThe expression levels of COL4A1/2 were significantly upregulated, while COL4A5/6 were conspicuously downregulated in STAD. The survival analysis revealed that the upregulated COL4s indicated poorer overall survival, first progression and post-progression survival outcomes. Additionally, our findings demonstrated a positive correlation between the expressions of COL4A1/2/3/4 and the infiltration of immune cells, including CD8 + T cells, dendritic cells, macrophages, neutrophils and CD4 + T cells. Further correlation analysis uncovered a favorable association between the expression of COL4A1/2/3/4 and various crucial immunomodulatory molecules, immunological checkpoint molecules, and chemokines. Quantitative PCR analysis confirmed that the expression patterns of COL4A1/3/4/6 genes aligned with the finding from the TCGA database. However, gastric cancer cells exhibited downregulation of COL4A2. Consistently, the protein level of COL4A1 was elevated, whereas the protein level of COL4A2 was reduced in the gastric cancer cell lines.ConclusionCOL4s could potentially serve as biomarkers for diagnosing and predicting the prognosis of STAD.

Project description:BackgroundPrevious studies have described that the SEC23A gene is involved in the occurrence and development of various tumor entities. However, little is known about its expression and relevance in stomach adenocarcinoma (STAD). The aim of this study was to bioinformatically analyze the role of SEC23A in STAD, followed by patient tissue sample analyses.Materials and methodsSEC23A expression levels in STAD and normal gastric tissues were analyzed in the Cancer Genome Atlas and Gene Expression Omnibus databases; results were verified in fresh clinical STAD specimens on both gene and protein expression levels. SEC23A expression correlated with survival parameters by Kaplan-Meier and multivariate Cox regression analyses. The top genes co-expressed with SEC23A were identified by gene set enrichment analysis (GSEA) using the clusterProfiler package in R. Furthermore, the R package (immunedeconv), integrating the CIBERSORT algorithm, was used to estimate immune cell infiltration levels in STAD.ResultsSEC23A gene and sec23a protein expression were both significantly upregulated in STAD, and this correlated with the pT stage. Moreover, high SEC23A expression was associated with poor disease-free and overall survival of STAD patients. Cox analyses revealed that besides age and pathologic stage, SEC23A expression is an independent risk factor for STAD. GSEA indicated that SEC23A was positively associated with ECM-related pathways. In the CIBERSORT analysis, the level of SEC23A negatively correlated with various infiltrating immune cell subsets, including follicular helper T cells, Tregs, activated NK cells and myeloid dendritic cells. Finally, the expression levels of immune checkpoint-related genes, including HAVCR2 and PDCD1LG2, were significantly increased in the high SEC23A expression group.ConclusionsWe observed the significantly upregulated expression of SEC23A in STAD, an association with disease progression, patients' prognosis and infiltrating immune cell subsets. Thus, we propose SEC23A as an independent prognostic factor with a putative role in immune response regulation in STAD.

Dataset Information

Immune Infiltration and Clinical Outcome of Super-Enhancer-Associated lncRNAs in Stomach Adenocarcinoma.

Publications

Immune Infiltration and Clinical Outcome of Super-Enhancer-Associated lncRNAs in Stomach Adenocarcinoma.

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