Identification of the pyroptosis‑related prognostic gene signature and the associated regulation axis in lung adenocarcinoma

AbstractLung adenocarcinoma (LUAD) remains the most common deadly disease and has a poor prognosis. Pyroptosis could regulate tumour cell proliferation, invasion, and metastasis, thereby affecting the prognosis of cancer patients. However, the role of pyroptosis-related genes (PRGs) in LUAD remains unclear. In our study, comprehensive bioinformatics analysis was performed to construct a prognostic gene model and ceRNA network. The correlations between PRGs and tumour-immune infiltration, tumour mutation burden, and microsatellite instability were evaluated using Pearson’s correlation analysis. A total of 23 PRGs were upregulated or downregulated in LUAD. The genetic mutation variation landscape of PRG in LUAD was also summarised. Functional enrichment analysis revealed that these 33 PRGs were mainly involved in pyroptosis, the NOD-like receptor signalling pathway, and the Toll-like receptor signalling pathway. Prognosis analysis indicated a poor survival rate in LUAD patients with low expression of NLRP7, NLRP1, NLRP2, and NOD1 and high CASP6 expression. A prognostic PRG model constructed using the above five prognostic genes could predict the overall survival of LUAD patients with medium-to-high accuracy. Significant correlation was observed between prognostic PRGs and immune-cell infiltration, tumour mutation burden, and microsatellite instability. A ceRNA network was constructed to identify a lncRNA KCNQ1OT1/miR-335-5p/NLRP1/NLRP7 regulatory axis in LUAD. In conclusion, we performed a comprehensive bioinformatics analysis and identified a prognostic PRG signature containing five genes (NLRP7, NLRP1, NLRP2, NOD1, and CASP6) for LUAD patients. Our results also identified a lncRNA KCNQ1OT1/miR-335-5p/NLRP1/NLRP7 regulatory axis, which may also play an important role in the progression of LUAD. Further study needs to be conducted to verify this result.

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Investigation of Candidate Genes and Mechanism Associated with Immune Cell during the Progression of Glioblastoma based on Bioinformatics

10.21203/rs.3.rs-117485/v1 ◽

2020 ◽

Author(s):

Hui Xie ◽

Xiao-hui Ding ◽

Ce Yuan ◽

Jin-jiang Li ◽

Zhao-yang Li ◽

...

Keyword(s):

Immune Cell ◽

Risk Model ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Normal Group ◽

Functional Enrichment ◽

M2 Macrophage ◽

Survival Prognosis ◽

Cerna Network ◽

Tumor Group

Abstract Background: This study aimed to investigate the molecular mechanism of immune cell infiltration during the development of glioblastoma multiforme (GBM), and explore the potential immune cell associated prognostic genes for GBM. Methods: Gene expression data and corresponding clinical data of GBM samples (tumor group) and normal samples (normal group) in TCGA-GBM and GTEx dataset were downloaded. The differentially expression analysis was performed on samples between two groups. Based on tumor immune microenvironment analysis, the immune-related RNAs (lncRNAs and mRNAs) were further explored. Then, functional enrichment analysis, ceRNA network, risk prediction model and prognosis investigation were performed. Finally, the results of survival prognosis of key genes were tested by additional datasets. Results: A total of 4989 up-regulated genes and 2349 down-regulated genes were revealed between tumor group and normal group. M2 macrophages accounted for the largest proportion of tumor infiltrates immune cells in GBM, and was related to the prognosis of GBM patients. Totally 168 mRNAs (KIF18B) and 5 lncRNAs were related to infiltration of M2 Macrophage, of which 25 mRNAs and 5 lncRNAs forms a ceRNA network through 37 miRNAs (eg., miR-6849-3p). These genes were mainly assembled in functions like signal release. A risk model based on 5 mRNAs (such as FOX4 and ELFN2) and lncRNA PR11-161H23.5 was constructed. Verification test showed that all 5 mRNAs were significantly associated with OS prognosis.Conclusions: M2 Macrophage infiltration might participate in tumorigenesis of GBM via RP11-161H23.5-miR6849-3p-KIF18B ceRNA interaction. Furthermore, mRNAs such as FOX4 and ELFN2 might be potential prognostic markers for GBM patients.

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Construction and Analysis of Survival-Associated Competing Endogenous RNA Network in Lung Adenocarcinoma

BioMed Research International ◽

10.1155/2021/4093426 ◽

2021 ◽

Vol 2021 ◽

pp. 1-17

Author(s):

Lixian Chen ◽

Zhonglu Ren ◽

Yongming Cai

Keyword(s):

Prognostic Factors ◽

Lung Adenocarcinoma ◽

Molecular Mechanisms ◽

Cox Regression ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Competing Endogenous Rna ◽

Cox Regression Analysis ◽

Cerna Network

Increasing evidence has shown that noncoding RNAs play significant roles in the initiation, progression, and metastasis of tumours via participating in competing endogenous RNA (ceRNA) networks. However, the survival-associated ceRNA in lung adenocarcinoma (LUAD) remains poorly understood. In this study, we aimed to investigate the regulatory mechanisms underlying ceRNA in LUAD to identify novel prognostic factors. mRNA, lncRNA, and miRNA sequencing data obtained from the GDC data portal were utilized to identify differentially expressed (DE) RNAs. Survival-related RNAs were recognized using univariate Kaplan-Meier survival analysis. We performed functional enrichment analysis of survival-related mRNAs using the clusterProfiler package of R and STRING. lncRNA-miRNA and miRNA-mRNA interactions were predicted based on miRcode, Starbase, and miRanda. Subsequently, the survival-associated ceRNA network was constructed for LUAD. Multivariate Cox regression analysis was used to identify prognostic factors. Finally, we acquired 15 DE miRNAs, 49 DE lncRNAs, and 843 DE mRNAs associated with significant overall survival. Functional enrichment analysis indicated that survival-related DE mRNAs were enriched in cell cycle. The survival-associated lncRNA-miRNA-mRNA ceRNA network was constructed using five miRNAs, 49 mRNAs, and 21 lncRNAs. Furthermore, seven hub RNAs (LINC01936, miR-20a-5p, miR-31-5p, TNS1, TGFBR2, SMAD7, and NEDD4L) were identified based on the ceRNA network. LINC01936 and miR-31-5p were found to be significant using the multifactorial Cox regression model. In conclusion, we successfully constructed a survival-related lncRNA-miRNA-mRNA ceRNA regulatory network in LUAD and identified seven hub RNAs, which provide novel insights into the regulatory molecular mechanisms associated with survival of LUAD, and identified two independent prognostic predictors for LUAD.

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Comprehensive Analysis of Aquaporin Superfamily in Lung Adenocarcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.736367 ◽

2021 ◽

Vol 8 ◽

Author(s):

Guofu Lin ◽

Luyang Chen ◽

Lanlan Lin ◽

Hai Lin ◽

Zhifeng Guo ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Immune Cell ◽

Enrichment Analysis ◽

Tumor Infiltrating Lymphocytes ◽

Functional Enrichment Analysis ◽

Tumor Stage ◽

Stage I ◽

Functional Enrichment ◽

Gene Expressions ◽

Kaplan Meier

Background: Lung adenocarcinoma (LUAD) is the most predomintnt lung cancer subtype with increasing morbidity and mortality. Previous studies have shown that aquaporin (AQP) family genes were correlated with tumor progression and metastasis in several kinds of malignancies. However, their biological behaviors and prognostic values in LUAD have not been comprehensively elucidated.Methods: RNA sequencing and real-time reverse transcription PCR (RT-PCR) were used to assess AQP1/3/4/5 gene expressions in LUAD patients using GEPIA and UALCAN databases. And then Kaplan–Meier analysis, cBioPortal, Metascape, GeneMANIA, TISIDB, and TIMER were utilized to determine the prognostic value, mutation frequency, and immune cell infiltration of AQP family members in LUAD.Results: We found that AQP3 expression was significantly elevated and AQP1 expression was markedly reduced in LUAD patients, whereas the expression levels of AQP4 and AQP5 exhibited no significant changes. The Kaplan–Meier survival analysis indicated that the higher expressions of AQP1/4/5 were related to longer overall survival (OS). Of interest, AQP3 was significantly correlated with the clinical tumor stage and lower AQP3 expression showed favorable prognosis in stage I LUAD patients, which indicated that AQP3 may be a potential prognostic biomarker for patients. Through functional enrichment analysis, the functions of these four AQPs genes were mainly involved in the passive transport by aquaporins, water homeostasis, and protein tetramerization. Moreover, AQP1/3/4/5 expression was strongly associated with tumor-infiltrating lymphocytes (TILs) in LUAD.Conclusion: AQP3 can be used as a prognosis and survival biomarker for stage I LUAD. These findings may provide novel insights into developing molecular targeted therapies in LUAD.

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Comprehensive analysis of dysregulated long non-coding RNA – microRNA – mRNA involved in the progression of human lung adenocarcinoma

10.21203/rs.3.rs-16347/v1 ◽

2020 ◽

Author(s):

Dan Yang ◽

Yang He ◽

Bo Wu ◽

Yan Deng ◽

Ruxi Liu ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Risk Score ◽

Molecular Mechanisms ◽

Cox Regression ◽

Roc Curves ◽

Functional Enrichment ◽

Differentially Expressed ◽

Score System ◽

Cerna Network ◽

Risk Score System

Abstract Background: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer worldwide. Until now, the molecular mechanisms underlying LUAD progression have not been fully explained. This study aimed to identify a competing endogenous RNA (ceRNA) network in LUAD.Methods: Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and mRNAs (DEGs) were identified from The Cancer Genome Atlas (TCGA) database with a |log2FC| > 1.0 and a false discovery rate (FDR) < 0.05. Then, these DELs, DEMs, and DEGs were used to construct the initial ceRNA network. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI) network, and survival analyses were performed to analyse these DEGs involved in the ceRNA network. Subsequently, the drug-gene interaction database (DGIdb) was utilized to select candidate LUAD drugs interacting with significant DEGs. Then, lasso-penalized Cox regression and multivariate Cox regression models were used to construct the risk score system. Kaplan-Meier (K-M) survival curves and receiver operating characteristic (ROC) curves were utilized to validate the reliability of the risk score system. Finally, based on the correlations between DELs and DEGs involved in the risk score system, the final ceRNA network was identified. Meanwhile, the GEPIA2 database and immunohistochemical (IHC) results were utilized to validate the expression levels of selected DEGs. GEPIA2 was further used to verify the correlations between DEGs and DELs.Results: A total of 340 DELs, 29 DEMs, and 218 DEGs were selected to construct the initial ceRNA network. Functional enrichment analyses indicated that 218 DEGs were significantly enriched in the GO terms “nucleoplasm”, “transcription factor complex”, “protein binding”, and “metal ion binding”, whereas these DEGs were associated with the KEGG pathway terms “microRNAs in cancer”, “pathways in cancer”, “cell cycle”, “HTLV-1 infection”, and the “PI3K-Akt signalling pathway”. K-M survival analysis of all differentially expressed genes involved in the ceRNA network identified 24 DELs, 4 DEMs, and 29 DEGs, all of which were significantly correlated with LUAD progression (P < 0.05). Furthermore, 15 LUAD drugs interacting with 29 DEGs were selected. After lasso-penalized Cox regression and multivariate Cox regression modelling, 4 DEGs, PRKCE, DLC1, LATS2, and DPY19L1, were incorporated into the risk score system. The area under the curve (AUC) values of the time-dependent ROC curves at 3 years and 5 years were both higher than 0.5. Finally, the correlation coefficients between these 4 DEGs and their corresponding DELs involved in the ceRNA network suggested that there were 2 DEL-DEG pairs, NAV2-AS2 – PRKCE (r = 0.430, P < 0.001) and NAV2-AS2 – LATS2 (r = 0.338, P < 0.001). Considering the previously constructed ceRNA network, NAV2-AS2 – mir-31 – PRKCE and NAV2-SA2 – mir-31 – LATS2 were identified.Conclusions: The lncRNA-miRNA-mRNA ceRNA network plays an essential role in LUAD. These results may improve our understanding and provide novel mechanistic insights to explore diagnostics, tumourigenesis, prognosis, and therapeutic drugs for LUAD patients.

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LncRNA MIR155HG functions as a ceRNA for inhibition of lung adenocarcinoma growth and prediction of prognosis

Archives of Medical Science ◽

10.5114/aoms/131198 ◽

2021 ◽

Author(s):

Jing Wang ◽

Jie Li

Keyword(s):

Lung Adenocarcinoma ◽

Tumour Progression ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Migration And Invasion ◽

Cerna Network ◽

Limma Package ◽

Competing Endogenous Rnas ◽

Prediction Of Prognosis

IntroductionLong non-coding RNAs (lncRNAs) functioning as competing endogenous RNAs (ceRNAs) play critical roles in tumour progression. However, prognosis-related ceRNA networks in lung adenocarcinoma (LUAD) have not been well characterised.Material and methodsLUAD datasets were downloaded from the TCGA database, and the patients were divided into metastasis and non-metastasis groups. The differential expression of lncRNAs (DELs), miRNAs (DEMs), and mRNAs (DEGs) was analysed using the Limma package. Next, interactions between miRNA, lncRNA, and mRNA were predicted by miRcode, miRTarBase, miRDB, and TargetScan. The ceRNA network was constructed based on these interactions using Cytoscape software. DEG enrichment analysis was performed by GO and KEGG. After the prognosis analysis, we further screened molecules and constructed the prognosis-related ceRNA network. Moreover, the interactions between lncRNA, miRNA, and mRNA were validated by biological experiments.Results854 DELs, 150 DEMs, and 2211 DEGs between metastasis and non-metastasis LUAD patients were identified. Functional enrichment analysis suggested that DEGs were closely related to key biological processes involved in LUAD progression. The prognosis-related ceRNA network included 1 miRNA, 2 lncRNAs, and 4 mRNAs. In this network, MIR155HG and ADAMTS9-AS2 can function as ceRNAs of miR-212 to regulate EPM2AIP1, LAX1, PRICKLE2, and CD226. Moreover, our study confirmed that MIR155HG inhibited the proliferation, migration, and invasion of LUAD cells by sponging miR-212-3p to regulate CD226.ConclusionsThis ceRNA network contributes to understanding the pathogenesis of LUAD. Furthermore, the molecules in the network are valuable predictive factors for LUAD prognosis as well as potential therapeutic biomarkers.

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Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Cells ◽

10.3390/cells10123484 ◽

2021 ◽

Vol 10 (12) ◽

pp. 3484

Author(s):

Jisun Lim ◽

Yeon Bi Han ◽

Soo Young Park ◽

Soyeon Ahn ◽

Hyojin Kim ◽

...

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Immune Cell ◽

Expression Profiles ◽

Expression Patterns ◽

Killer Cell ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Stepwise Change

Many studies support a stepwise continuum of morphologic changes between atypical adenomatous hyperplasia (AAH) and lung adenocarcinoma (ADC). Here we characterized gene expression patterns and the association of differentially expressed genes and immune tumor microenvironment behaviors in AAH to ADC during ADC development. Tumor tissues from nine patients with ADC and synchronous multiple ground glass nodules/lesions (GGN/Ls) were analyzed using RNA sequencing. Using clustering, we identified genes differentially and sequentially expressed in AAH and ADC compared to normal tissues. Functional enrichment analysis using gene ontology terms was performed, and the fraction of immune cell types was estimated. We identified up-regulated genes (ACSL5 and SERINC2) with a stepwise change of expression from AAH to ADC and validated those expressions by quantitative PCR and immunohistochemistry. The immune cell profiles revealed increased B cell activities and decreased natural killer cell activities in AAH and ADC. A stepwise change of differential expression during ADC development revealed potential effects on immune function in synchronous precursors and in tumor lesions in patients with lung cancer.

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Identification of a ZC3H12D-Regulated Competing Endogenous RNA Network for Prognosis of Lung Adenocarcinoma at Single-Cell Level

10.21203/rs.3.rs-603118/v1 ◽

2021 ◽

Author(s):

Wenhan Chen ◽

Zhifeng Guo ◽

Jingyang Wu ◽

Guofu Lin ◽

Shaohua Chen ◽

...

Keyword(s):

T Cells ◽

Lung Adenocarcinoma ◽

Single Cell ◽

Rna Sequencing ◽

Immune Cells ◽

Functional Enrichment ◽

Receptor Interaction ◽

Competing Endogenous Rna ◽

Hub Genes ◽

Cerna Network

Abstract Objective To identify hub genes from the competing endogenous RNA (ceRNA) network of lung adenocarcinoma (LUAD) and to explore their potential function on prognosis of patients from a single-cell perspective.Methods We performed RNA-sequencing of LUAD to construct ceRNA regulatory network, integrating with public databases to identify the vital pathways related to patients’ prognosis and to reveal the expression level of hub genes under different conditions, the functional enrichment of co-expressed genes and their potential immune-related mechanisms.Results ZC3H12D-hsa-miR-4443-ENST00000630242 axis was found to be related with LUAD. Lower ZC3H12D expression was significantly associated with shorter overall survival (OS) of patients (HR=2.007, P<0.05), and its expression was higher in early-stage patients, including T1 (P<0.05) and N0 (P<0.05). Additionally, ZC3H12D expression was higher in immune cells displayed by single-cell RNA-sequencing data, especially in Treg cells of lung cancer and CD8 T cells, B cells and CD4 T cells of LUAD. In the brain metastasized, the expression of ZC3H12D in macrophages was relatively abundant. The functional enrichment analysis showed that the co-expressed genes mainly played a role in lymphocyte activation and cytokine-cytokine receptor interaction. In addition, ZC3H12D was associated with multiple immune cells and immune molecules, including immune checkpoints CTLA4, CD96 and TIGIT.Conclusion ZC3H12D-hsa-miR-4443-ENST00000630242 ceRNA network was identified in LUAD. ZC3H12D could affect the survival and prognosis of patients by regulating mRNA, miRNA, lncRNA, immune cells and immune molecules. Therefore, it may serve as a vital predictive marker and could be regarded as a potential therapeutic target for LUAD in the future.

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POS0363 IDENTIFICATION OF MOLECULAR PHENOTYPES AND IMMUNE CELL INFILTRATION IN PSORIATIC ARTHRITIS PATIENTS’ SKIN TISSUES BY INTEGRATED BIOINFORMATICS ANALYSIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.2171 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 411.1-411

Author(s):

T. Cheng ◽

S. X. Zhang ◽

J. Qiao ◽

R. Zhao ◽

S. Song ◽

...

Keyword(s):

T Cells ◽

Psoriatic Arthritis ◽

Nk Cells ◽

Bioinformatics Analysis ◽

Immune Cell ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Signature Genes ◽

Molecular Phenotypes

Background:Psoriatic arthritis (PsA) is an inflammatory musculoskeletal disease associated with cutaneous psoriasis1. Heterogeneity of clinical manifestation often makes differential diagnosis difficult 2. Thus, the underlying molecular pathogenesis of PsA need to be further studied to diagnose early and ensure optimal management of arthritis and key comorbidities.Objectives:This research was conducted to identify molecular phenotypes and immune infiltration in the skin tissues of psoriatic arthritis patients according to bioinformatics analysis.Methods:The mRNA expression profiles of GSE13355 (116 samples), GSE14905 (56 samples) and GSE30999 (162 samples) were obtained from the publicly GEO databases. Non-negative matrix factorization (NMF), functional enrichment and cibersort algorithm were applied to illustrate the conditions of PsA patients’ skin tissues for classification after screening the differentially expressed genes (DEGs) between lesion biopsy and non-lesion biopsy.Results:Two subsets (Sub1 and Sub2) were identified and validated by NMF typing of 612 detected DEGs (Figure 1a). A total of 54 signature genes (18 in Sub1 and 36 in Sub2) were obtained (Figure 1b). GO and KEGG enrichment analysis showed the signature genes in Sub1 were mainly involved in proliferation and differentiation of immune cells, whereas genes in Sub2 were related to humoral immune response mediated by antimicrobial peptide (Figure 1c.1d). Further, immune cell infiltration results revealed Sub2 had higher levels of resting NK cells (P<0.001), macrophages M1(P<0.001), resting mast cells (P<0.001) and regulatory T cells (P<0.001) but lower concentrations of activated CD4+ memory T cells (P<0.001), activated NK cells (P<0.05), activated dendritric cells(P<0.001), eosinophils (P<0.05) and neutrophil (P<0.001) (Figure 1e).Conclusion:The pathogenesis of psoriatic arthritis is related to both cellular immunity and humoral immunity. It is indispensable to adjust the treatment strategies according to patient’s immune status.References:[1]Ritchlin CT, Colbert RA, Gladman DD. Psoriatic Arthritis. The New England journal of medicine 2017;376(10):957-70. doi: 10.1056/NEJMra1505557 [published Online First: 2017/03/09].[2]Veale DJ, Fearon U. The pathogenesis of psoriatic arthritis. Lancet (London, England) 2018;391(10136):2273-84. doi: 10.1016/s0140-6736(18)30830-4 [published Online First: 2018/06/13].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

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Prognostic value of SEC61G in lung adenocarcinoma: a comprehensive study based on bioinformatics and in vitro validation

BMC Cancer ◽

10.1186/s12885-021-08957-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Qunhao Zheng ◽

Zhiping Wang ◽

Mengyan Zhang ◽

Yilin Yu ◽

Rui Chen ◽

...

Keyword(s):

T Cell ◽

Lung Adenocarcinoma ◽

Methylation Level ◽

Prognostic Value ◽

Immune Cell ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Biological Behavior

Abstract Background Studies have shown that the Sec61 gamma subunit (SEC61G) is overexpressed in several tumors and could serve as a potential prognostic marker. However, the correlation between SEC61G and lung adenocarcinoma (LUAD) remains unclear. In the current study, we aimed to demonstrate the prognostic value and potential biological function of the SEC61G gene in LUAD. Methods Public datasets were used for SEC61G expression analyses. The prognostic value of SEC61G in LUAD was investigated using the Kaplan–Meier survival and Cox analyses. The correlation between the methylation level of SEC61G and its mRNA expression was evaluated via cBioPortal. Additionally, MethSurv was used to determine the prognostic value of the SEC61G methylation levels in LUAD. Functional enrichment analysis was conducted to explore the potential mechanism of SEC61G. Also, single sample GSEA (ssGSEA) and TIMER online tool were applied to identify the correlation between SEC61G and immune filtration. Furthermore, cell functional experiments were conducted to verify the biological behavior of SEC61G in lung adenocarcinoma cells (LAC). Results SEC61G was upregulated in pan-cancers, including LUAD. High SEC61G expression was significantly correlated with worse prognosis in LUAD patients. Multivariate analysis demonstrated that high SEC61G expression was an independent prognostic factor in the TCGA cohort. (HR = 1.760 95% CI: 1.297–2.388, p < 0.001). The methylation level of SEC61G negatively correlated with the SEC61G expression (R = − 0.290, p < 0.001), and patients with low SEC61G methylation had worse overall survival. (p = 0.0014). Proliferation-associated terms such as cell cycle and cell division were significantly enriched in GO and KEGG analysis. Vitro experiments demonstrated that knockdown of SEC61G resulted in decreased cell proliferation, invasion and facilitated apoptosis in LAC. GSEA analysis found that SEC61G expression was associated with the E2F targets. Moreover, SEC61G expression was negatively correlated with the immune cell infiltration including CD4+ T cell, CD8+ T cell, B cell, macrophage, neutrophil, and dendritic cell. Conclusion Our study indicated that overexpression of SEC61G was significantly associated with poor prognosis of LUAD patients and the malignant phenotypes of LUAD cells, suggesting that it could be a novel prognostic biomarker and potential therapeutic target of LUAD.

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Identification of Hub Genes Associated with Immune Cells in Dilated Cardiomyopathy via Weighted Gene Co-expression Network Analysis

10.21203/rs.3.rs-652198/v1 ◽

2021 ◽

Author(s):

Jielin Deng ◽

Yunqiu Jiang ◽

Changjin Deng ◽

hong jiang

Keyword(s):

Network Analysis ◽

Dilated Cardiomyopathy ◽

Immune Cells ◽

Bioinformatics Analysis ◽

Immune Cell ◽

Gene Profiling ◽

Functional Enrichment ◽

Pathophysiological Mechanism ◽

Hub Genes ◽

Key Genes

Abstract Background: Dilated cardiomyopathy (DCM) is the most common cardiomyopathy which account for a majority of heart failure. Although massive clinic experiments and gene profiling analyses on DCM have been conducted, the molecular mechanism of DCM associated with immune cells has not been fully elucidated. This study was designed to discover the immune mechanism of DCM using integrative bioinformatics analysis and provide new insights into the pathophysiology of DCM. Methods: The GSE29819 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells based on 14 samples of 7 DCM patients. Weighted gene co-expression network analysis (WGCNA) was performed to cluster the 2500 genes with the highest average expression into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on key genes in significant modules identified by WGCNA and Cibersort. Key genes were then applied to Cytoscape to construct protein-protein interaction (PPI) network. Differentially expressed genes (DEGs) were identified based on DCM and normal controls in GSE29819 through R language. Hub genes were selected based on the DEGs and the genes identified by PPI and then verified via public GEO databases. Results: The yellow and tan modules with 163 genes were identified as the key modules based on top 2500 DCM microarrays, significantly correlated with M1 and M2 macrophages. The intersection of newly screened 17 genes based on 163 key genes through Cytoscape and 2682 DEGs were defined as hub genes including CCT2, CCL2, and TXN. The results were finally verified via GSE116250 datasets.Conclusions: The three hub genes associated with two immune cells identified by comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism of DCM, which provided potential immunological therapeutic targets and new insights into the treatment of DCM.

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