Core genes in lung adenocarcinoma identified by integrated bioinformatic analysis

Background: Long non-coding RNAs (lncRNAs) have been reported to play important roles in the progression of human cancers. Herein, bioinformatic analysis identified that LINC00942 was a highly overexpressed lncRNA in lung adenocarcinoma (LUAD). The present study aimed to explore the roles and possible molecular mechanisms of LINC00942 in LUAD. Methods: First, on the basis of TCGA database, the expression and prognosis of LINC00942 were analyzed in LUAD tissues. Then, si-LINC00942 was transfected into A549 and H1299 cells to knockdown the expression of LINC00942. Cell viability was detected by MTT assay. Flow cytometry was used to analyze cell apoptosis. The expressions of PCNA, Bax, Bcl-2, and wnt/β-catenin pathway proteins were detected by western blotting. Dual-luciferase reporter assay was used to evaluate the regulatory relationship between LINC00942 and miR-5006-5p, or miR-5006-5p and FZD1. Results: We discovered that LINC00942 was up-regulated in LUAD tissues compared with adjacent tissues. Besides, we found the increased LINC00942 expression was associated with poor survival. In addition, silencing of LINC00942 suppressed the proliferation, migration, invasion and facilitated the apoptosis of A549 and H1299 cells. Moreover, silencing of LINC00942 repressed the expression of PCNA, Bcl-2, and enhanced Bax expression in A549 and H1299 cells. Mechanically, LINC00942 exerted its effects via enhancing Wnt signaling. LINC00942 functioned as competing endogenous RNA (ceRNA) by binding to miR-5006-5p, upregulating the expression of FZD1, which was a direct target of miR-5006-5p. Conclusion: Our findings indicated that LINC00942/miR-5006-5p/FZD1 axis played important roles in LUAD growth through enhancing Wnt signaling. LINC00942/miR-5006-5p/FZD1 axis might serve as a potential biomarker and therapeutic target for LUAD treatment.

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Identification of Core Genes and Screening of Potential Targets in Glioblastoma Multiforme by Integrated Bioinformatic Analysis

Frontiers in Oncology ◽

10.3389/fonc.2020.615976 ◽

2021 ◽

Vol 10 ◽

Author(s):

Ji’an Yang ◽

Qian Yang

Keyword(s):

Glioblastoma Multiforme ◽

Enrichment Analysis ◽

Bioinformatic Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Low Grade ◽

Hypergeometric Test ◽

Ppi Network ◽

Neuropsychiatric Diseases ◽

Core Genes

Glioblastoma multiforme is the most common primary intracranial malignancy, but its etiology and pathogenesis are still unclear. With the deepening of human genome research, the research of glioma subtype screening based on core molecules has become more in-depth. In the present study, we screened out differentially expressed genes (DEGs) through reanalyzing the glioblastoma multiforme (GBM) datasets GSE90598 from the Gene Expression Omnibus (GEO), the GBM dataset TCGA-GBM and the low-grade glioma (LGG) dataset TCGA-LGG from the Cancer Genome Atlas (TCGA). A total of 150 intersecting DEGs were found, of which 48 were upregulated and 102 were downregulated. These DEGs from GSE90598 dataset were enriched using the overrepresentation method, and multiple enriched gene ontology (GO) function terms were significantly correlated with neural cell signal transduction. DEGs between GBM and LGG were analyzed by gene set enrichment analysis (GSEA), and the significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in synapse signaling and oxytocin signaling pathways. Then, a protein-protein interaction (PPI) network was constructed to assess the interaction of proteins encoded by the DEGs. MCODE identified 2 modules from the PPI network. The 11 genes with the highest degrees in module 1 were designated as core molecules, namely, GABRD, KCNC1, KCNA1, SYT1, CACNG3, OPALIN, CD163, HPCAL4, ANK3, KIF5A, and MS4A6A, which were mainly enriched in ionic signaling-related pathways. Survival analysis of the GSE83300 dataset verified the significant relationship between expression levels of the 11 core genes and survival. Finally, the core molecules of GBM and the DrugBank database were assessed by a hypergeometric test to identify 10 drugs included tetrachlorodecaoxide related to cancer and neuropsychiatric diseases. Further studies are required to explore these core genes for their potentiality in diagnosis, prognosis, and targeted therapy and explain the relationship among ionic signaling-related pathways, neuropsychiatric diseases and neurological tumors.

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Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

Lung Cancer Management ◽

10.2217/lmt-2020-0009 ◽

2020 ◽

Vol 9 (2) ◽

pp. LMT30

Author(s):

Chuanli Ren ◽

Weixiu Sun ◽

Xu Lian ◽

Chongxu Han

Keyword(s):

Lung Adenocarcinoma ◽

Differentially Expressed Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Kaplan Meier ◽

Key Genes ◽

Core Genes

Aim: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD). Materials & methods: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID. Results: Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD. Conclusion: 23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

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Comprehensive Profiling Reveals Distinct Microenvironment and Metabolism Characterization of Lung Adenocarcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.619821 ◽

2021 ◽

Vol 12 ◽

Author(s):

Chang Li ◽

Chen Tian ◽

Yangyang Liu ◽

Jinyan Liang ◽

Yulan Zeng ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Immune Cells ◽

Immune Checkpoint ◽

Immune Escape ◽

Cholesterol Biosynthesis ◽

Bioinformatic Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Metabolic State ◽

Metabolic States

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.

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Screening of Hub Genes Associated with Lung Adenocarcinoma by Integrated Bioinformatic Analysis

10.21203/rs.3.rs-580657/v1 ◽

2021 ◽

Author(s):

Zimeng Wei ◽

Min Zhao ◽

Linnan Zang

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Bioinformatic Analysis ◽

Analysis Tool ◽

Hub Genes ◽

Kegg Analysis ◽

Ppi Networks

Abstract Background Lung adenocarcinoma (LUAD) is the main histological subtype of lung cancer. However, the molecular mechanism underlying LUAD is not yet clearly defined, but elucidating this process in detail would be of great significance for clinical diagnosis and treatment. Methods Gene expression profiles were retrieved from Gene Expression Omnibus database (GEO), and the common differentially expressed genes (DEGs) were identified by online GEO2R analysis tool. Subsequently, the enrichment analysis of function and signaling pathways of DEGs in LUAD were performed by gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomics (KEGG) analysis. The protein-protein interaction (PPI) networks of the DEGs were established through the Search Tool for the Retrieval of Interacting Genes (STRING) database and hub genes were screened by plug-in CytoHubba in Cytoscape. Afterwards, we detected the expression of hub genes in LUAD and other cancers via GEPIA, Oncomine and HPA databases. Finally, Kaplan-Meier plotter were performed to analyze the prognosis efficacy of hub genes. Results 74 up-regulated and 238 down-regulated DEGs were identified. As for the up-regulated DEGs, KEGG analysis results revealed they were mainly enrolled in protein digestion and absorption. However, the down-regulated DEGs were primarily enriched in cell adhesion molecules. Subsequently, 9 hub genes: KIAA0101, CDCA7, TOP2A, CDC20, ASPM, TPX2, CENPF, UBE2T and ECT2, were identified and showed higher expression in both LUAD and other cancers. Finally, all these hub genes were found significantly related to the prognosis of LUAD (p < 0.05). Conclusions Our results screened out the hub genes and pathways that were related to the development and prognosis of LUAD, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of LUAD.

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Adding context to the pneumococcal core genes – a bioinformatic analysis of the intergenic pangenome of Streptococcus pneumoniae

10.1101/2021.08.29.458057 ◽

2021 ◽

Author(s):

Flemming Damgaard Nielsen ◽

Jakob Møller-Jensen ◽

Mikkel Girke Jørgensen

Keyword(s):

Streptococcus Pneumoniae ◽

Core Genome ◽

Biological Function ◽

Bioinformatic Analysis ◽

Bacterial Pathogenicity ◽

The Core ◽

Intergenic Regions ◽

Crucial Information ◽

Genetic Context ◽

Core Genes

AbstractWhole genome sequencing offers great opportunities for linking genotypes to phenotypes aiding in our understanding of human disease and bacterial pathogenicity. However, these analyses often overlook non-coding intergenic regions (IGRs). By disregarding the IGRs, crucial information is lost, as genes have little biological function without expression. In this study, we present the first complete pangenome of the important human pathogen Streptococcus pneumoniae (pneumococcus), spanning both the genes and IGRs. We show that the pneumococcus species retains a small core genome of IGRs that are present across all isolates. Gene expression is highly dependent on these core IGRs, and often several copies of these core IGRs are found across each genome. Core genes and core IGRs show a clear linkage as 81% of core genes are associated with core IGRs. Additionally, we identify a single IGR within the core genome that is always occupied by one of two highly distinct sequences, scattered across the phylogenetic tree. Their distribution indicates that this IGR is transferred between isolates through horizontal regulatory transfer independent of the flanking genes and that each type likely serves different regulatory roles depending on their genetic context.

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Identification of small proline‐rich protein 1B ( SPRR1B ) as a prognostically predictive biomarker for lung adenocarcinoma by integrative bioinformatic analysis

Thoracic Cancer ◽

10.1111/1759-7714.13836 ◽

2021 ◽

Author(s):

Zihe Zhang ◽

Ruifeng Shi ◽

Songlin Xu ◽

Yongwen Li ◽

Hongbing Zhang ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Predictive Biomarker ◽

Bioinformatic Analysis ◽

Small Proline Rich Protein ◽

Proline Rich Protein

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DCBLD2 Mediates Epithelial-Mesenchymal Transition-Induced Metastasis by Cisplatin in Lung Adenocarcinoma

Cancers ◽

10.3390/cancers13061403 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1403

Author(s):

Xiaosu Chen ◽

Yajing Lv ◽

Kejia Xu ◽

Xiaoshuang Wang ◽

Yujia Zhao ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Tumor Metastasis ◽

Epithelial Mesenchymal Transition ◽

Bioinformatic Analysis ◽

Critical Issue ◽

Chemotherapeutic Agents ◽

Clinical Practices ◽

Mesenchymal Transition

Growing evidence suggests that cisplatin and other chemotherapeutic agents promote tumor metastasis while inhibiting tumor growth, which is a critical issue for certain patients in clinical practices. However, the role of chemotherapeutics in promoting tumor metastasis and the molecular mechanism involved are unclear. Here, we investigated the roles of cisplatin in promoting tumor metastasis in lung adenocarcinoma (LUAD). We demonstrated that cisplatin promoted epithelial-mesenchymal transition (EMT), cell motility, and metastasis in vitro and in vivo. The bioinformatic analysis and molecular biology approaches also indicated that DCBLD2 (Discoidin, CUB and LCCL domain containing 2) is a key gene that mediates cisplatin-induced metastasis. DCBLD2 stabilizes β-catenin by phosphorylating GSK3β and transporting accumulated β-catenin to the nucleus to promote the expression of EMT-related transcriptional factors (TFs), ultimately resulting in tumor metastasis. We also identified that cisplatin enhanced DCBLD2 expression by phosphorylating ERK and hence the AP-1-driven transcription of DCBLD2. Furthermore, DCBLD2-specific siRNAs encapsulated by nanocarriers prominently inhibit cisplatin-induced metastasis in vivo. Therefore, DCBLD2 plays a key role in cisplatin-induced metastasis in LUAD and is a potential target for preventing chemotherapy-induced metastasis in vivo.

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