The Relationship Between Gene Expression Pattern and the Severity of Asthma

Abstract Background Because of heterogeneity, complexity of diagnosis and diversity of pathogenesis, the incidence and mortality of asthma are increased seriously. A structured and specific approach to assess and treat asthma may help clinicians. Results A total of 838 common genes were found from quietness to exacerbation then to recovery of asthma. PPI network analysis identified 7 modules, and found 7 hub genes with high degree. Then, we verified the expression of hub genes in patients by quantitative real-time polymerase chain reaction (qRT-PCR). Enrichment analysis and gene set enrichment analysis (GSEA) showed that exacerbation related genes were significantly related to immune and inflammatory response. Transcriptional regulators factor STAT1 had a significant regulatory effect on exacerbation related genes. Conclusions These results indicated that seven hub genes were potential biomarkers and targets of asthma exacerbation. they were involved in the development of asthma through immune inflammatory signaling pathway. The results of this study not only provide a new research direction and theoretical basis for the exacerbation mechanism of asthma, but also provide a new target for clinical treatment.

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Identification of potential therapeutic targets for atherosclerosis by analysing the gene signature related to different immune cells and immune regulators in atheromatous plaques

BMC Medical Genomics ◽

10.1186/s12920-021-00991-2 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Yang Shen ◽

Li-rong Xu ◽

Xiao Tang ◽

Chang-po Lin ◽

Dong Yan ◽

...

Keyword(s):

Immune Cells ◽

Plasma Cells ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gamma Delta ◽

Hub Genes ◽

Gene Set Enrichment ◽

Bioinformatics Analyses ◽

Immune Infiltration ◽

Atheromatous Plaques

Abstract Background Atherosclerosis is a chronic inflammatory disease that affects multiple arteries. Numerous studies have shown the inherent immune diversity in atheromatous plaques and suggest that the dysfunction of different immune cells plays an important role in atherosclerosis. However, few comprehensive bioinformatics analyses have investigated the potential coordinators that might orchestrate different immune cells to exacerbate atherosclerosis. Methods Immune infiltration of 69 atheromatous plaques from different arterial beds in GSE100927 were explored by single-sample-gene-set enrichment analysis (presented as ssGSEA scores), ESTIMATE algorithm (presented as immune scores) and CIBERSORT algorithm (presented as relative fractions of 22 types of immune cells) to divide these plaques into ImmuneScoreL cluster (of low immune infiltration) and ImmuneScoreH cluster (of high immune infiltration). Subsequently, comprehensive bioinformatics analyses including differentially-expressed-genes (DEGs) analysis, protein–protein interaction networks analysis, hub genes analysis, Gene-Ontology-terms and KEGG pathway enrichment analysis, gene set enrichment analysis, analysis of expression profiles of immune-related genes, correlation analysis between DEGs and hub genes and immune cells were conducted. GSE28829 was analysed to cross-validate the results in GSE100927. Results Immune-related pathways, including interferon-related pathways and PD-1 signalling, were highly enriched in the ImmuneScoreH cluster. HLA-related (except for HLA-DRB6) and immune checkpoint genes (IDO1, PDCD-1, CD274(PD-L1), CD47), RORC, IFNGR1, STAT1 and JAK2 were upregulated in the ImmuneScoreH cluster, whereas FTO, CRY1, RORB, and PER1 were downregulated. Atheromatous plaques in the ImmuneScoreH cluster had higher proportions of M0 macrophages and gamma delta T cells but lower proportions of plasma cells and monocytes (p < 0.05). CAPG, CECR1, IL18, IGSF6, FBP1, HLA-DPA1 and MMP7 were commonly related to these immune cells. In addition, the advanced-stage carotid plaques in GSE28829 exhibited higher immune infiltration than early-stage carotid plaques. Conclusions Atheromatous plaques with higher immune scores were likely at a more clinically advanced stage. The progression of atherosclerosis might be related to CAPG, IGSF6, IL18, CECR1, FBP1, MMP7, FTO, CRY1, RORB, RORC, PER1, HLA-DPA1 and immune-related pathways (IFN-γ pathway and PD-1 signalling pathway). These genes and pathways might play important roles in regulating immune cells such as M0 macrophages, gamma delta T cells, plasma cells and monocytes and might serve as potential therapeutic targets for atherosclerosis.

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Increased Expression of LYNX1 in Ovarian Serous Cystadenocarcinoma Predicts Poor Prognosis

BioMed Research International ◽

10.1155/2020/1392674 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Hui Liu ◽

Ao Wang ◽

Yushan Ma

Keyword(s):

Ovarian Cancer ◽

Univariate Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Gene Set ◽

Serous Cystadenocarcinoma ◽

Kaplan Meier ◽

Pathologic Features ◽

The Relationship

Few studies have reported the function of LYNX1 in ovarian cancer. We retrieved LYNX1 gene expression data and clinical information of 376 patients with ovarian cancer from The Cancer Genome Atlas (TCGA) project website. Wilcoxon signed-rank test and logistic regression were used to analyze the relationship between clinical pathologic features and LYNX1 expression. The Kaplan–Meier method was used to draw survival curves of patients, and Cox regression was used to calculate the relationship between LYNX1 expression and survival rate or the clinicopathological characteristics of the patients. Gene set enrichment analysis (GSEA) was performed, and the correlation between LYNX1 expression and cancer immune infiltrates was investigated via single sample gene set enrichment analysis (ssGSEA). High LYNX1 expression in ovarian serous cystadenocarcinoma (OVs) was associated with tumor residual disease (RD). In Kaplan–Meier survival analysis, patients with OVs who also displayed high LYNX1 expression had decreased overall survival (OS) and disease-specific survival (DSS) than those with low LYNX1 expression. Univariate analysis also supported that patients with high LYNX1 expression had lower OS than those with low LYNX1 expression. LYNX1 expression has the potential to be a prognostic molecular marker of poor survival in OVs.

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RNA N6-Methyladenosine Regulator-Mediated Methylation Modifications Pattern and Immune Infiltration Features in Glioblastoma

Frontiers in Oncology ◽

10.3389/fonc.2021.632934 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yimin Pan ◽

Kai Xiao ◽

Yue Li ◽

Yuzhe Li ◽

Qing Liu

Keyword(s):

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Lasso Regression ◽

Gene Set Enrichment ◽

Clinical Prognosis ◽

Prognostic Assessment ◽

The Relationship

Glioblastoma (GBM) is a group of intracranial neoplasms with intra-tumoral heterogeneity. RNA N6-methyladenosine (m6A) methylation modification reportedly plays roles in immune response. The relationship between the m6A modification pattern and immune cell infiltration in GBM remains unknown. Utilizing expression data of GBM patients, we thoroughly explored the potential m6A modification pattern and m6A-related signatures based on 21 regulators. Thereafter, the m6A methylation modification-based prognostic assessment pipeline (MPAP) was constructed to quantitatively assess GBM patients’ clinical prognosis combining the Robustness and LASSO regression. Single-sample gene-set enrichment analysis (ssGSEA) was used to estimate the specific immune cell infiltration level. We identified two diverse clusters with diverse m6A modification characteristics. Based on differentially expressed genes (DEGs) within two clusters, m6A-related signatures were identified to establish the MPAP, which can be used to quantitatively forecast the prognosis of GBM patients. In addition, the relationship between 21 m6A regulators and specific immune cell infiltration was demonstrated in our study and the m6A regulator ELAVL1 was determined to play an important role in the anticancer response to PD-L1 therapy. Our findings indicated the relationship between m6A methylation modification patterns and tumor microenvironment immune cell infiltration, through which we could comprehensively understand resistance to multiple therapies in GBM, as well as accomplish precise risk stratification according to m6A-related signatures.

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Wnt pathway-related three-mRNA clinical outcome signature in bladder urothelial carcinoma: computational biology and experimental analyses

Journal of Translational Medicine ◽

10.1186/s12967-021-03061-4 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Siqing Sun ◽

Yutao Wang ◽

Jianfeng Wang ◽

Jianbin Bi

Keyword(s):

Wnt Signaling ◽

Signaling Pathway ◽

Wnt Pathway ◽

Cox Regression ◽

Wnt Signaling Pathway ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Immune Infiltration ◽

The Relationship

Abstract Background The Wnt signaling pathway is core to the growth of bladder tumors. Epithelial-to-mesenchymal transition (EMT) is significant for bladder tumor metastasis. Nevertheless, the relationship between the Wnt signaling pathway, outcomes of bladder cancer (BLCA), and the specific mechanisms driving immune infiltration have not been studied. Methods We obtained Wnt pathway-related gene mRNA and clinicopathological data from the Cancer Genome Atlas (TCGA). We obtained 34 genes that were greatly correlated with outcome using univariate Cox regression analysis and conducted a completely randomized data t-test to perform clinical staging. According to the single-sample gene set enrichment analysis (ssGSEA), the weighted correlation network analysis (WGCNA) was applied to identify relevant biological functions. Various subtypes were identified using consensus cluster analysis. Univariate Cox regression and least absolute shrinkage sum selection operator–Cox regression algorithm analysis were conducted on TCGA and Gene Expression Omnibus data to identify risk characteristics. The Kaplan–Meier method and receiver running feature curves were adopted to calculate overall survival. Single-sample gene set enrichment analysis (ssGSEA) was adopted for the assessment of the degree of immune infiltration. Then, we demonstrated the relationship between PPP2CB and EMT function in two cell lines. Results Thirty-four Wnt signaling pathway-related genes were risk factors for BLCA outcome, and their expression levels differed by clinical stage. The co-expression of WGCNA showed the relationship between the Wnt signaling pathway and biological functions and was closely associated with EMT. We divided BLCA patients into two subtypes using consensus clustering. Survival curves and clinical analysis showed that the Wnt pathway enriched group had worse outcomes. The Wnt signature showed the significance of the outcome for MAPK10, PPP2CB, and RAC3. Based on these genes, the degree of immune infiltration was evaluated. Cell function experiments suggested that PPP2CB drives the proliferation and migration of BLCA cells. Conclusion We found that Wnt signaling pathway-related genes can be used as prognostic risk factors for BLCA, and the Wnt signaling pathway is a cancer-promoting signaling pathway associated with EMT. We identified three critical genes: MAPK10, RAC3, and PPP2CB. The genes in these three Wnt signaling pathways are associated with tumor cell EMT and immune cell infiltration. The most important finding was that these three genes were independent prognostic factors for BLCA.

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Identification of AREG, STAG3, C19orf57 and CAV1 as key prognostic factors in HPV- negative head and neck squamous cell carcinoma

10.21203/rs.3.rs-38063/v1 ◽

2020 ◽

Author(s):

Guocai Tian ◽

You Fu ◽

Jiang Li ◽

Zhiyuan Zhang ◽

Xi Yang

Keyword(s):

Squamous Cell Carcinoma ◽

Prognostic Factors ◽

Cell Carcinoma ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Hub Genes ◽

Gene Set Enrichment ◽

Hpv Status ◽

Hnscc Cell

Abstract Background Head and neck squamous cell carcinoma (HNSCC) is a common tumor worldwide with poor prognosis. The pathogenesis of human papillomavirus (HPV)-positive and HPV-negative HNSCCs differs. However, few studies have considered the HPV status when identifying biomarkers for HNSCC. Thus, the identification of biomarkers for HPV-positive and HPV-negative HNSCCs is urgently needed. Methods Three microarray datasets from Gene Expression Omnibus (GEO) were analyzed, and the differentially expressed genes (DEGs) were obtained. Then, functional enrichment pathway analysis was performed and protein-protein interaction (PPI) networks were constructed. The expression of hub genes at both the mRNA and protein level was determined in Oncomine, The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA). In addition, survival analyses of the patient stratified by HPV status and the expression levels of key genes were performed based on TCGA data. The role of AREG, STAG3, CAV1 and C19orf57 in cancer were analyzed through Gene set enrichment analysis (GSEA). Finally, the top ten small molecule drugs were identified and the therapeutic value of zonisamide, NVP-AUY922, PP-2 and fostamatinib was further evaluated in six HPV-negative HNSCC cell lines. Results In total, 47 DEGs were obtained, 11 of which were identified as hub genes. Biological process analysis indicated that the hub genes were associated with the G1/S transition of the mitotic cell cycle. Survival analysis uncovered that the prognostic value of AREG, STAG3, C19orf57 and CAV1 differed between HPV-positive and HPV-negative patients. Gene set enrichment analysis (GSEA) showed the role of AREG, STAG3 and CAV1 in dysregulated pathways of tumor. Ten small molecules were identified as potential drugs specifically for HPV-positive or HPV-negative patients; three—NVP-AUY922, fostamatinib and PP-2—greatly inhibited the proliferation of six HPV-negative HNSCC cell lines in vitro. Conclusions In conclusion, AREG, STAG3, C19orf57 and CAV1 are key prognostic factors and potential therapeutic targets in HPV-negative HNSCC. NVP-AUY922, fostamatinib and PP-2 may be effective drugs for HPV-negative HNSCC.

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Identification of Four Key Prognostic Genes and Three Potential Drugs in Human Papillomavirus Negative Head and Neck Squamous Cell Carcinoma

10.21203/rs.3.rs-113482/v1 ◽

2020 ◽

Author(s):

Guocai Tian ◽

You Fu ◽

Dahe Zhang ◽

Jiang Li ◽

Zhiyuan Zhang ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Survival Analysis ◽

Human Papillomavirus ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Hub Genes ◽

Gene Set Enrichment ◽

Hpv Status ◽

Hnscc Cell

Abstract BackgroundHead and neck squamous cell carcinoma (HNSCC) is a common tumor worldwide with poor prognosis. The pathogenesis of human papillomavirus (HPV)-positive and HPV-negative HNSCCs differs. However, few studies have considered the HPV status when identifying biomarkers for HNSCC. Thus, the identification of biomarkers for HPV-positive and HPV-negative HNSCCs is urgently needed.MethodsThree microarray datasets from Gene Expression Omnibus (GEO) were analyzed, and the differentially expressed genes (DEGs) were obtained. Then, functional enrichment pathway analysis was performed and protein-protein interaction (PPI) networks were constructed. The expression of hub genes at both the mRNA and protein level was determined in Oncomine, The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA). In addition, survival analysis of the patient stratified by HPV status and the expression levels of key genes were performed based on TCGA data. The role of AREG, STAG3, CAV1 and C19orf57 in cancer were analyzed through Gene set enrichment analysis (GSEA). Finally, the top ten small molecule drugs were identified and the therapeutic value of zonisamide, NVP-AUY922, PP-2 and fostamatinib was further evaluated in six HPV-negative HNSCC cell lines.ResultsIn total, 47 DEGs were obtained, 11 of which were identified as hub genes. Biological process analysis indicated that the hub genes were associated with the G1/S transition of the mitotic cell cycle. Survival analysis uncovered that the prognostic value of AREG, STAG3, C19orf57 and CAV1 differed between HPV-positive and HPV-negative patients. Gene set enrichment analysis (GSEA) showed the role of AREG, STAG3 and CAV1 in dysregulated pathways of tumor. Ten small molecules were identified as potential drugs specifically for HPV-positive or HPV-negative patients; three—NVP-AUY922, fostamatinib and PP-2—greatly inhibited the proliferation of six HPV-negative HNSCC cell lines in vitro, and NVP-AUY922 inhibited three HPV-negative HNSCC xenografts in vivo.ConclusionsIn conclusion, AREG, STAG3, C19orf57 and CAV1 are key prognostic factors and potential therapeutic targets in HPV-negative HNSCC. NVP-AUY922, fostamatinib and PP-2 may be effective drugs for HPV-negative HNSCC.

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HSF2 is a Promising Prognostic Biomarker and is Correlated With Immune Infiltration in Hepatocellular Carcinoma

10.21203/rs.3.rs-89953/v1 ◽

2020 ◽

Author(s):

Bihui Han ◽

Yanxiu Meng ◽

Yumei Fan ◽

Bing Liu ◽

Jiajie Hou ◽

...

Keyword(s):

Immune Cells ◽

Critical Role ◽

Enrichment Analysis ◽

Normal Liver ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Immune Infiltration ◽

Kaplan Meier ◽

The Relationship ◽

Kaplan Meier Plotter

Abstract BackgroundHepatocellular carcinoma (HCC) is one of the most common malignancies and ranks as the second leading cause of cancer-related mortality worldwide. Heat shock factor 2 (HSF2) is a transcription factor that plays a critical role in development, particularly corticogenesis and spermatogenesis. However, studies on the expression and prognostic value of HSF2 and its association with tumor-infiltrating immune cells in HCC are still rare. MethodsThe TCGA, Oncomine, UALCAN, HCCDB and HPA databases were used to investigate HSF2 expression in HCC. Kaplan-Meier plotter, GEPIA and HCCDB databases were used to evaluate the association of HSF2 with the prognosis of HCC patients. Genetic alteration of HSF2 was examined by the cBioPortal database. The mechanism was investigated with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GESA), and the relationship between HSF2 expression and immune infiltration was explored through the TIMER database and CIBERSORT algorithm.Results In the present study, we found that HSF2 expression was significantly upregulated in HCC compared with normal liver tissues. High HSF2 expression was associated with poor survival in HCC patients. GO, KEGG and GESA analyses demonstrated that HSF2 was associated with various signaling pathways, including the immune response. Notably, HSF2 expression was significantly correlated with the infiltration levels of different immune cells. HSF2 expression also displayed a significant correlation with multiple immune marker sets in HCC. ConclusionsIn summary, we explored the clinical significance of HSF2 and provided a therapeutic basis for the early diagnosis, prognostic judgment, and immunotherapy of HCC.

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Identification of four key prognostic genes and three potential drugs in human papillomavirus negative head and neck squamous cell carcinoma

Cancer Cell International ◽

10.1186/s12935-021-01863-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Guocai Tian ◽

You Fu ◽

Dahe Zhang ◽

Jiang Li ◽

Zhiyuan Zhang ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Hub Genes ◽

Gene Set Enrichment ◽

Therapeutic Value ◽

Hpv Status ◽

Hnscc Cell

Abstract Background Head and neck squamous cell carcinoma (HNSCC) is a common tumor worldwide with poor prognosis. The pathogenesis of human papillomavirus (HPV)-positive and HPV-negative HNSCCs differs. However, few studies have considered the HPV status when identifying biomarkers for HNSCC. Thus, the identification of biomarkers for HPV-positive and HPV-negative HNSCCs is urgently needed. Methods Three microarray datasets from Gene Expression Omnibus (GEO) were analyzed, and the differentially expressed genes (DEGs) were obtained. Then, functional enrichment pathway analysis was performed and protein–protein interaction (PPI) networks were constructed. The expression of hub genes at both the mRNA and protein level was determined in Oncomine, The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA). In addition, survival analysis of the patient stratified by HPV status and the expression levels of key genes were performed based on TCGA data. The role of AREG, STAG3, CAV1 and C19orf57 in cancer were analyzed through Gene set enrichment analysis (GSEA). The top ten small molecule drugs were identified and the therapeutic value of zonisamide, NVP-AUY922, PP-2 and fostamatinib was further evaluated in six HPV-negative HNSCC cell lines. Finally, the therapeutic value of NVP-AUY922 was tested in vivo based on three HPV-negative HNSCC models, and statistical analysis was performed. Results In total, 47 DEGs were obtained, 11 of which were identified as hub genes. Biological process analysis indicated that the hub genes were associated with the G1/S transition of the mitotic cell cycle. Survival analysis uncovered that the prognostic value of AREG, STAG3, C19orf57 and CAV1 differed between HPV-positive and HPV-negative patients. Gene set enrichment analysis (GSEA) showed the role of AREG, STAG3 and CAV1 in dysregulated pathways of tumor. Ten small molecules were identified as potential drugs specifically for HPV-positive or HPV-negative patients; three—NVP-AUY922, fostamatinib and PP-2—greatly inhibited the proliferation of six HPV-negative HNSCC cell lines in vitro, and NVP-AUY922 inhibited three HPV-negative HNSCC xenografts in vivo. Conclusions In conclusion, AREG, STAG3, C19orf57 and CAV1 are key prognostic factors and potential therapeutic targets in HPV-negative HNSCC. NVP-AUY922, fostamatinib and PP-2 may be effective drugs for HPV-negative HNSCC.

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Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary Syndrome

Cardiology Research and Practice ◽

10.1155/2020/3162581 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Mingshuang Li ◽

Conglin Ren ◽

Chenxia Wu ◽

Xinyao Li ◽

Xinyi Li ◽

...

Keyword(s):

Acute Coronary Syndrome ◽

Enrichment Analysis ◽

Roc Curves ◽

Functional Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Hub Genes ◽

Coronary Syndrome ◽

Incidence And Mortality ◽

Expression Matrix

Background. Acute coronary syndrome (ACS) has a high incidence and mortality rate. Early detection and intervention would provide clinical benefits. This study aimed to reveal hub genes, transcription factors (TFs), and microRNAs (miRNAs) that affect plaque stability and provide the possibility for the early diagnosis and treatment of ACS. Methods. We obtained gene expression matrix GSE19339 for ACS patients and healthy subjects from public database. The differentially expressed genes (DEGs) were screened using Limma package in R software. The biological functions of DEGs were shown by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Protein-protein interaction (PPI) network was mapped in Cytoscape, followed by screening of hub genes based on the Molecular Complex Detection (MCODE) plug-in. Functional Enrichment analysis tool (FunRich) and Database for Annotation, Visualization and Integrated Discovery (DAVID) were used to predict miRNAs and TFs, respectively. Finally, GSE60993 expression matrix was chosen to plot receiver operating characteristic (ROC) curves with the aim of further assessing the reliability of our findings. Results. We obtained 176 DEGs and further identified 16 hub genes by MCODE. The results of functional enrichment analysis showed that DEGs mediated inflammatory response and immune-related pathways. Among the predicted miRNAs, hsa-miR-4770, hsa-miR-5195, and hsa-miR-6088 all possessed two target genes, which might be closely related to the development of ACS. Moreover, we identified 11 TFs regulating hub gene transcriptional processes. Finally, ROC curves confirmed three genes with high confidence (area under the curve > 0.9), including VEGFA, SPP1, and VCAM1. Conclusion. This study suggests that three genes (VEGFA, SPP1, and VCAM1) were involved in the molecular mechanisms of ACS pathogenesis and could serve as biomarkers of disease progression.

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Epigenetic-dysregulated lncRNAs in Prostate Cancer Based on Multi-omics Analysis

10.21203/rs.3.rs-948350/v1 ◽

2021 ◽

Author(s):

Jianxiao Zheng ◽

Xuexiao Xiang ◽

Zhipeng Xu ◽

Yangjing Xu ◽

Xiaowei Huang ◽

...

Keyword(s):

Prostate Cancer ◽

Prognostic Markers ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Epigenetic Changes ◽

Gene Set Enrichment ◽

Protein Coding ◽

Non Coding Rnas ◽

The Relationship

Abstract Background: The purpose of this study was to investigate the relationship between Long non-coding RNAs (lncRNAs) expression and epigenetic changes, and explore the prognostic value of these findings in patients with prostate cancer. Methods: In this study, we systematically compared the histone modification and methylation regions on lncRNAs promoter and enhancer elements by multiomics. We analyzed the distribution characteristics of histone modified apparent lncRNAs promoters and enhancers in the genome. Single sample Gene Set Enrichment Analysis (ssGSEA) and Kyoto Encyclopedia of Gene and Genomes (KEGG) were used to analyze the functional enrichment of epigenetic dysregulated lncRNAs. The prostate cancer associated lncRNAs were downloaded from lnc2cancer V3.0 and survival analysis was performed. Results: We found 1124 epigenetic-dysregulated lncRNAs (epi-lncRNAs) and 9734 epigenetic-dysregulated protein coding genes (epi-PCGs) in prostate cancer, and the abnormal frequency of lncRNAs was much lower than that of PCGs. H3K4me3, H3K4me1, H3K27ac and H3K27me3 abnormally modified histones accounted for a large proportion and were mainly concentrated in the promoter region. Epigenetic abnormal lncRNAs affects the biological specific molecular function of prostate cancer by changing the abnormal modification of histone. The abnormal expression of lncRNAs caused by abnormal modification of H3K36me3 may be an important factor in the occurrence of prostate cancer. Finally, based on lncRNAs analysis of the prognosis of prostate cancer samples, three lncRNAs (HAR1A, SNHG12 and SNHG17) were identified as prognostic markers of prostate cancer.Conclusions: These findings may help to better understand the abnormal epigenetic regulation of lncRNAs expression in prostate cancer.

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