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Comprehensive characterization of functional eRNAs in lung adenocarcinoma reveals novel regulators and a prognosis-related molecular subtype.

ABSTRACT: Rationale: As the transcriptional products of active enhancers, enhancer RNAs (eRNAs) are essential for the initiation of tumorigenesis. However, the landscape and functional characteristics of eRNAs in Chinese lung adenocarcinoma, and the clinical utility of eRNA-based molecular subtypes remain largely unknown. Methods: A genome-wide profiling of eRNAs was performed in 80 Chinese lung adenocarcinoma patients with RNA-seq data. Functional eRNAs and associated genes were identified between paired adenocarcinoma and adjacent samples. Unsupervised clustering of functional eRNAs was conducted and the associations with molecular characteristics and clinical outcomes were accessed by integrating whole-genome sequencing data and clinical data. Additionally, 481 lung adenocarcinoma patients were used for the validation based on The Cancer Genome Atlas (TCGA) dataset. Results: A total of 3297 eRNAs with sufficient expression were identified, which were globally upregulated in adenocarcinoma samples compared to matched-adjacent pairs (P = 7.61×10-3). Further analyses indicated that these upregulated eRNAs were correlated with copy number amplification (CNA) status (Cor = 0.22, P = 0.045), and eRNA-correlated genes were primarily involved in cell cycle and immune system-related pathways. Based on the co-expression analysis of eRNAs with protein-coding genes, we defined 188 functional eRNAs and their correlated genes were overrepresented in cancer driver genes (ER = 1.98, P = 5.95×10-12) and clinically-actionable genes (ER = 2.19, P = 3.44×10-4). The eRNA-based consensus clustering further identified a novel molecular subtype with immune deficiency and a high-level of genomic alterations, which was associated with poor clinical outcomes of lung adenocarcinoma patients (OS: HR = 1.91, P = 0.015; PFI: HR = 1.64, P = 0.034). Conclusions: The genome-wide identification and characterization of eRNAs reveal novel regulators for the development of lung cancer, which provides a new biological dimension for the understanding of eRNAs during lung carcinogenesis and emphasize the clinical utility of eRNA-based molecular subtypes in the treatment of lung adenocarcinoma.

SUBMITTER: Qin N

PROVIDER: S-EPMC7532687 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Comprehensive characterization of functional eRNAs in lung adenocarcinoma reveals novel regulators and a prognosis-related molecular subtype.

Qin Na N Ma Zijian Z Wang Cheng C Zhang Erbao E Li Yuancheng Y Huang Mingtao M Chen Congcong C Zhang Chang C Fan Jingyi J Gu Yayun Y Xu Xianfeng X Yang Liu L Wei Xiaoxia X Yin Rong R Jiang Yue Y Dai Juncheng J Jin Guangfu G Xu Lin L Hu Zhibin Z Shen Hongbing H Ma Hongxia H

Theranostics 20200914 24

<b>Rationale:</b> As the transcriptional products of active enhancers, enhancer RNAs (eRNAs) are essential for the initiation of tumorigenesis. However, the landscape and functional characteristics of eRNAs in Chinese lung adenocarcinoma, and the clinical utility of eRNA-based molecular subtypes remain largely unknown. <b>Methods:</b> A genome-wide profiling of eRNAs was performed in 80 Chinese lung adenocarcinoma patients with RNA-seq data. Functional eRNAs and associated genes were identified ...[more]

PMID: 33042282

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Project description:Lung adenocarcinoma has entered into an era of immunotherapy with the development of immune checkpoint inhibitors (ICIs). The identification of immune subtype is crucial to prolonging survival in patients. The tumor microenvironment (TME) and metabolism have a profound impact on prognosis and therapy. The majority of previous studies focused on only one aspect, while both of them are essential to the understanding of tumorigenesis and development. We hypothesized that lung adenocarcinoma can be stratified into immune subgroups with alterations in the TME infiltration. We aimed to explore the "TME-Metabolism-Risk" patterns in each subtypes and the mechanism behind. Glycolysis and cholesterol were selected for the analysis of metabolic states based on the first half of the study. Bioinformatic analysis was performed to investigate the transcriptomic and clinical data integrated by three lung adenocarcinoma cohorts (GSE30219, GSE31210, GSE37745, N = 415). The results were validated in an independent cohort (GSE50081, N = 127). In total, 415 lung adenocarcinoma samples were integrated and analyzed. Four major immune subtypes were indentified using bioinformatic analysis. Subtype NC1, characterized by a high level of glycolysis, with extremely low microenvironment cell infiltration. Subtype NC2, characterized by the "Silence" and "Cholesterol biosynthesis Predominant" metabolic states, with a middle degree infiltration of microenvironment cell. Subtype NC3, characterized by the lack of "Cholesterol biosynthesis Predominant" metabolic state, with abundant microenvironment cell infiltration. Subtype NC4, characterized by "Mixed" metabolic state, with a relatively low microenvironment cell infiltration. Least absolute shrinkage and selection operator (LASSO) regression and multivariate analyses were performed to calculate the risk of each sample, and we attempted to find out the potential immune escape mechanism in different subtypes. The result revealed that the lack of immune cells infiltration might contribute to the immune escape in subtypes NC1 and NC4. NC3 was characterized by the high expression of immune checkpoint molecules and fibroblasts. NC2 had defects in activation of innate immune cells. There existed an obviously survival advantage in subtype NC2. Gene set enrichment analysis (GSEA) and Gene Ontology analysis indicated that the PI3K-AKT-mTOR, TGF-β, MYC-related pathways might be correlated with this phenomenon. In addition, some differentially expressed genes (DEGs) were indentified in subtype NC3, which might be potential targets for survival phenotype transformation.

Project description:BackgroundLactic acid, as a product of glycolysis, increases tumor cell migration and the invasion of tumor cells in the tumor microenvironment. Besides this, lactic acid promotes the expression of programmed death-1 expression (PD-1) in regulatory T cells, which could cause the failure of PD-1 blockade therapy. However, the implications of lactic acid in the tumor microenvironment of lung adenocarcinoma (LUAD) remain largely unclear.MethodsWe performed unsupervised consensus clustering to identify lactic-associated subtypes using expression profile of lactate regulators in LUAD. Differentially expressed genes (DEGs) associated with lactic-associated subtypes was used to construct lactate signature (LaSig) using LASSO regression algorithm. Immune infiltration analysis was conducted by ESTIMATER and drug sensitivity was estimated by R package called "pRRophetic". The difference between two groups was calculated using Wilcox rank sum test and correlation analysis was calculated using Pearson correlation coefficient.ResultsIn this study, we evaluated DNA methylation and the mutation frequency of lactate regulators and found lactate regulators showed low mutation frequency in the TCGA-LUAD cohort, except TP53. At the RNA level, the expression level of lactate regulators was significantly associated with the immune cell component. In particular, expression of LDHA was positively correlated with CD4 T cell, CD8 T cell, M1 macrophages, and the enrichment score of multiple immune pathways. Two clusters were defined using the gene expression level of lactate regulators, and LDHA was significantly upregulated in cluster 1 with poor overall survival. A lactate signature (LaSig) had a robust performance in predicting the survival rate and immunotherapy response of LUAD patients. Moreover, patients in the high LaSig group may be more likely to benefit from these drugs (Cisplatin, Erlotinib, Gemcitabine, and Vinblastine) than those in the low LaSig group.ConclusionIn summary, our study explores the role of lactate regulators in guiding the clinical treatment of lung adenocarcinoma and provides additional help to supplement traditional molecular subtypes.

Project description:Background: Abnormal chromosome segregation is identified to be a common hallmark of cancer. However, the specific predictive value of it in lung adenocarcinoma (LUAD) is unclear. Method: The RNA sequencing and the clinical data of LUAD were acquired from The Cancer Genome Atlas (TACG) database, and the prognosis-related genes were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were carried out for functional enrichment analysis of the prognosis genes. The independent prognosis signature was determined to construct the nomogram Cox model. Unsupervised clustering analysis was performed to identify the distinguishing clusters in LUAD-samples based on the expression of chromosome segregation regulators (CSRs). The differentially expressed genes (DEGs) and the enriched biological processes and pathways between different clusters were identified. The immune environment estimation, including immune cell infiltration, HLA family genes, immune checkpoint genes, and tumor immune dysfunction and exclusion (TIDE), was assessed between the clusters. The potential small-molecular chemotherapeutics for the individual treatments were predicted via the connectivity map (CMap) database. Results: A total of 2,416 genes were determined as the prognosis-related genes in LUAD. Chromosome segregation is found to be the main bioprocess enriched by the prognostic genes. A total of 48 CSRs were found to be differentially expressed in LUAD samples and were correlated with the poor outcome in LUAD. Nine CSRs were identified as the independent prognostic signatures to construct the nomogram Cox model. The LUAD-samples were divided into two distinct clusters according to the expression of the 48 CSRs. Cell cycle and chromosome segregation regulated genes were enriched in cluster 1, while metabolism regulated genes were enriched in cluster 2. Patients in cluster 2 had a higher score of immune, stroma, and HLA family components, while those in cluster 1 had higher scores of TIDES and immune checkpoint genes. According to the hub genes highly expressed in cluster 1, 74 small-molecular chemotherapeutics were predicted to be effective for the patients at high risk. Conclusion: Our results indicate that the CSRs were correlated with the poor prognosis and the possible immunotherapy resistance in LUAD.

Project description:BackgroundWe aimed to comprehensively analyze the clinical value of immune-related eRNAs-driven genes in lung adenocarcinoma (LUAD) and find the potential biomarkers for prognosis and therapeutic response to improve the survival of this malignant disease.Materials and methodsPearson's correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues.ResultsFive immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan-Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD.ConclusionAbove all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.

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Comprehensive characterization of functional eRNAs in lung adenocarcinoma reveals novel regulators and a prognosis-related molecular subtype.

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Comprehensive characterization of functional eRNAs in lung adenocarcinoma reveals novel regulators and a prognosis-related molecular subtype.

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