Dataset Information

Comprehensive transcriptomic analysis identifies novel regulators of lung adenocarcinoma.

ABSTRACT: Lung adenocarcinoma (LA) is a subtype of lung cancer that accounts for about 40% of all lung cancers. Analysis of molecular mechanisms controlling this cancer can help scientists to detect, control and treat LA. Here, a microarray dataset (GSE118370) containing six normal lung (NL) and six LA samples was screened using GEO2R to find differentially expressed genes (DEGs). Then, DAVID, KEGG and ChEA were used to analyze DEGs-related gene ontology, pathways and transcription factors (TFs), respectively. The Protein-protein interaction network for DEGs and TFs was constructed by STRING and Cytoscape. To find microRNAs and metabolites associated with DEGs, miRTarBase and HMDB were used, respectively. It was found that 350 genes were upregulated and 608 genes were downregulated in LA. The upregulated genes or LA-related gens were enriched in biological process and pathways such as extracellular matrix disassembly and p53 signaling pathway, whereas the downregulated genes or NL-related genes were enriched in cell adhesion and cell-surface receptor signaling pathway. ESR1, KIF18B, BIRC5, CHEK1, CCNB1 and AURKA were determined as hub genes for LA. FOXA1 and TFAP2A had the highest number of connectivity in LA-related TFs. hsa-miR-192-5p and hsa-miR-215-5p could target the highest number of LA-related genes. Metabolite analysis showed that Estrone and NADPH were among the top ten metabolites associated with LA-related genes. Taken together, LA-related genes, especially the hub genes, TFs, and metabolites might be used as novel markers for LA, as well as for diagnosis and guiding therapeutic strategies of LA.

SUBMITTER: Mokhlesi A

PROVIDER: S-EPMC7642016 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comprehensive transcriptomic analysis identifies novel regulators of lung adenocarcinoma.

Mokhlesi Amir A Talkhabi Mahmood M

Journal of cell communication and signaling 20200515 4

Lung adenocarcinoma (LA) is a subtype of lung cancer that accounts for about 40% of all lung cancers. Analysis of molecular mechanisms controlling this cancer can help scientists to detect, control and treat LA. Here, a microarray dataset (GSE118370) containing six normal lung (NL) and six LA samples was screened using GEO2R to find differentially expressed genes (DEGs). Then, DAVID, KEGG and ChEA were used to analyze DEGs-related gene ontology, pathways and transcription factors (TFs), respecti ...[more]

PMID: 32415511

Similar Datasets

Project description:Influenza A virus (IAV) has a higher genetic variation, leading to the poor efficiency of traditional vaccine and antiviral strategies targeting viral proteins. Therefore, developing broad-spectrum antiviral treatments is particularly important. Host responses to IAV infection provide a promising approach to identify antiviral factors involved in virus infection as potential molecular drug targets. In this study, in order to better illustrate the molecular mechanism of host responses to IAV and develop broad-spectrum antiviral drugs, we systematically analyzed mRNA expression profiles of host genes in a variety of human cells, including transformed and primary epithelial cells infected with different subtypes of IAV by mining 35 microarray datasets from the GEO database. The transcriptomic results showed that IAV infection resulted in the difference in expression of amounts of host genes in all cell types, especially those genes participating in immune defense and antiviral response. In addition, following the criteria of P<0.05 and |logFC|≥1.5, we found that some difference expression genes were overlapped in different cell types under IAV infection via integrative gene network analysis. IFI6, IFIT2, ISG15, HERC5, RSAD2, GBP1, IFIT3, IFITM1, LAMP3, USP18, and CXCL10 might act as key antiviral factors in alveolar basal epithelial cells against IAV infection, while BATF2, CXCL10, IFI44L, IL6, and OAS2 played important roles in airway epithelial cells in response to different subtypes of IAV infection. Additionally, we also revealed that some overlaps (BATF2, IFI44L, IFI44, HERC5, CXCL10, OAS2, IFIT3, USP18, OAS1, IFIT2) were commonly upregulated in human primary epithelial cells infected with high or low pathogenicity IAV. Moreover, there were similar defense responses activated by IAV infection, including the interferon-regulated signaling pathway in different phagocyte types, although the differentially expressed genes in different phagocyte types showed a great difference. Taken together, our findings will help better understand the fundamental patterns of molecular responses induced by highly or lowly pathogenic IAV, and the overlapped genes upregulated by IAV in different cell types may act as early detection markers or broad-spectrum antiviral targets.

Project description: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.

Project description:BackgroundPrevious studies have demonstrated that transcriptional RNA methyladenosine modification significantly affects tumor initiation and progression. However, clinical implications of N1-methyladenosine (m1A) regulators and their effect on tumor immunity in lung adenocarcinoma (LUAD) are still poorly elucidated.MethodsHerein, the characteristics of somatic mutation, copy number variation (CNV), DNA methylation, and expression levels of m1A regulators were thoroughly analyzed. We classified 955 lung adenocarcinoma patients into different m1A modification patterns based on an unsupervised consensus clustering algorithm. We then calculated the differences in gene expression, prognosis outcomes, and immune profiles among different m1A clusters. Subsequently, we screened differently expressed genes (DEGs) related to prognosis among different m1A clusters. We identified m1A related gene clusters according to the prognosis-related different expressed genes. We further constructed a scoring standard named the m1A score and comprehensively analyzed the survival outcomes, clinical-pathological features, immune microenvironment, treatment responses of immunotherapy, and drug susceptibility in different m1A score groups.ResultsIn total, three different m1A modification patterns were identified, which contained cluster A, B, and C. Among them, cluster A processed the poorest clinical outcomes, the lowest immune cell infiltration rate, and the highest tumor purity score. Then, three m1A gene clusters (gene cluster A, B, C) were speculated. Subsequently, we combined m1A modification patterns and m1A gene cluster to classify lung adenocarcinoma patients into high and low m1A score groups. The low m1A score group was accompanied by higher mortality, higher tumor mutation burden (TMB) and genome mutation frequency, and lower programmed cell death-Ligand 1 (PD-L1) expression and tumor immune dysfunction and exclusion (TIDE) expression. Moreover, the m1A score exhibited positive correlation with almost all immune cells. Finally, common chemotherapeutic and targeted therapy agents exhibited obvious differences in drug susceptibility in different m1A score groups.ConclusionsCollectively, we explored the potential value of m1A regulators in the prognosis and treatment of lung adenocarcinoma in multiple dimensions and provided some preliminary basis for the follow-up study of m1A regulators in lung adenocarcinoma.

Project description:BackgroundThe abnormal expression of genes is an essential factor affecting the prognosis of cancer. RNA modification is a way of regulating post-transcriptional levels, including m6A, m5C, m1A RNA methylation. Studies have found that RNA methylation regulates tumorigenesis development and stem cell regeneration. However, there are few studies on lung adenocarcinoma. This study aims to explore the clinical value of RNA methylation for lung adenocarcinoma.MethodsWe summarized thirty-one RNA methylation regulators. The training set was obtained from The Cancer Genome Atlas (TCGA) database, and the test set was obtained from the Gene Expression Omnibus (GEO) database. The Wilcoxon test was used to analyze the expression of RNA methylation regulators. We constructed tumor subgroup models and risk models based on the expression of those regulators. Principal component analysis (PCA) and the receiver operating characteristic (ROC) confirmed the accuracy of the models. Real-time polymerase chain reaction (PCR) validates the results in vitro.ResultsMost RNA methylation regulators had distinct expressions in tumor tissues and adjacent tissues (P<0.05). All the models showed high predictive performance (AUC: 0.65-0.82), and the five-year survival of patients in each group was statistically different (P<0.05). The patients in the high-risk group were more likely to have a higher stage, more lymph node metastases, and distant metastases, showing a poor clinical outcome. Patients with high expression of NOP2 or HNRNP were more likely to have a poorly differentiated in vitro experiment.ConclusionsWith our study, we found that the expressions of most RNA methylation regulators were significantly different in cancer and para-cancerous tissues. Different molecular phenotypes constructed by RNA methylation regulators can be independent risk factors for the prognosis of lung adenocarcinoma. Our study demonstrates the critical role of RNA methylation in lung adenocarcinoma, and it is expected to supply a reference for the prognostic stratification and treatment strategy development of lung adenocarcinoma.

Dataset Information

Comprehensive transcriptomic analysis identifies novel regulators of lung adenocarcinoma.

Publications

Comprehensive transcriptomic analysis identifies novel regulators of lung adenocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets