Role of hypermethylated-lncRNAs in the prognosis of bladder cancer patients

Objective To explore the hypermethylated long non-coding (lnc)RNAs involved in bladder carcinogenesis and prognosis. Methods Reduced representation bisulfite sequencing and RNA sequencing were performed on five paired tumor and adjacent normal tissue samples from bladder cancer patients. The differentially methylated regions around transcription start sites and differentially expressed genes, including lncRNAs, were analyzed. Correlations between DNA methylation modifications and the expression of lncRNAs were examined. Survival analysis was surveyed on the GEPIA web server. Results We identified 19,560 hypomethylated and 68,781 hypermethylated differentially methylated regions around transcription start sites in bladder cancer tissues. In total, 2321 differentially expressed genes were found in bladder tumors, among which, 367 were upregulated and 1954 were downregulated. There were 141 downregulated genes involving eight lncRNAs that were consistently hypermethylated, while 24 upregulated genes were consistently hypomethylated. Survival analysis demonstrated that hypermethylation of lncRNAs LINC00683 and MSC-AS1 were associated with poor overall survival in bladder cancer patients. Conclusion Some lncRNAs are controlled by DNA methylation in bladder cancer and they might be important factors in bladder carcinogenesis. Hypermethylated lncRNAs including LINC00683 and MSC-AS1 have the potential to be prognostic biomarkers for bladder cancer.

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Identification of Methylation-Regulated Differentially Expressed Genes and Related Pathways in Hepatocellular Carcinoma: A Study Based on TCGA Database and Bioinformatics Analysis

Frontiers in Oncology ◽

10.3389/fonc.2021.636093 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yu Liang ◽

Bin Ma ◽

Peng Jiang ◽

Hong-Mei Yang

Keyword(s):

Hepatocellular Carcinoma ◽

Dna Methylation ◽

Survival Analysis ◽

Differentially Expressed Genes ◽

Kegg Pathway ◽

Excision Repair ◽

Methylation Status ◽

Differentially Expressed ◽

Kaplan Meier ◽

Pathway Analyses

BackgroundIn recent years, DNA methylation modification has been shown to be a critical mechanism in the field of epigenetics.MethodsHepatocellular carcinoma (HCC) data were obtained from The Cancer Genome Atlas project, including RNA expression profiles, Illumina Human Methylation 450K BeadChip data, clinical information, and pathological features. Then, differentially expressed genes (DEGs) and differentially methylated genes were identified using R software. Methylation-regulated DEGs (MeDEGs) were further analyzed using Spearman’s correlation analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the DAVID database and ClueGO in Cytoscape software. Kaplan–Meier survival analysis explored the relationship between methylation, expression of MeDEGs, and survival time. Gene set enrichment analysis (GSEA) was conducted to predict the function of prognosis-related MeDEGs.ResultsA total of nine up-regulated and 72 down-regulated MeDEGs were identified. GO and KEGG pathway analyses results indicated that multiple cancer-related terms were enriched. Kaplan–Meier survival analysis showed that the methylation status of four MeDEGs (CTF1, FZD8, PDK4, and ZNF334) was negatively associated with overall survival. Moreover, the methylation status of CDF1 and PDK4 was identified as an independent prognostic factor. According to GSEA, hypermethylation of prognosis-related MeDEGs was enriched in pathways that included “Spliceosome”, “Cell cycle”, “RNA degradation”, “RNA polymerase”, “DNA replication”, “Mismatch repair”, “Base excision repair”, “Nucleotide excision repair”, “Homologous recombination”, “Protein export”, and “Pyrimidine metabolism”.ConclusionsAberrant DNA methylation plays a critical role in malignant progression of HCC. Prognosis-related MeDEGs identified in this research may be potential biomarkers and targets in diagnosis and treatment.

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Integrated Bioinformatics Analysis for Identification of the Hub Genes Linked with Prognosis of Ovarian Cancer Patients

Computational and Mathematical Methods in Medicine ◽

10.1155/2022/5113447 ◽

2022 ◽

Vol 2022 ◽

pp. 1-9

Author(s):

Xiaofeng Li ◽

Qiu Wang ◽

Zhicheng Wu ◽

Jiantong Zheng ◽

Ling Ji

Keyword(s):

Ovarian Cancer ◽

Survival Analysis ◽

Cancer Patients ◽

Differentially Expressed Genes ◽

Early Stage ◽

Central Carbon Metabolism ◽

Differentially Expressed ◽

Hub Genes ◽

Human Protein Atlas ◽

Excessive Body Weight

Background. One of the most usual gynecological state of tumor is ovarian cancer and is a major reason of gynecological tumor-related global mortality rate. There have been multiple risk elements related to ovarian cancer like the background of past cases associated with breast cancer or ovarian cancer, or excessive body weight issues, case history of smoking, and untimely menstruation or menopause. Because of unclear expressions, more than 70% of the ovarian cancer patient cases are determined during the early stage. Material and Methods. GSE38666, GSE40595, and GSE66957 were the three microarray datasets which were analyzed using GEO2R for screening the differentially expressed genes. GO, Kyoto Encyclopedia of Genes, and protein expression studies were performed for analysis of hub genes. Then, survival analysis was performed for all the hub genes. Results. From the dataset, a total of 199 differentially expressed genes (DEGs) were identified. Through the KEGG pathway study, it was noted that the DEGs are mainly linked with the AGE-RAGE signaling pathway, central carbon metabolism, and human papillomavirus infection. The survival analysis showed 4 highly expressed hub genes COL4A1, SDC1, CDKN2A, and TOP2A which correlated with overall survival in ovarian cancer patients. Moreover, the expression of the 4 hub genes was validated by the GEPIA database and the Human Protein Atlas. Conclusion. The results have shown that all 4 hub genes were found to be upregulated in ovarian cancer tissues which predict poor prognosis in patients with ovarian cancer.

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Gene expression and DNA methylation analyses suggest that two immune related genes are prognostic factors of colorectal cancer

BMC Medical Genomics ◽

10.1186/s12920-021-00966-3 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Xiao-Liang Xing ◽

Zhi-Yong Yao ◽

Chaoqun Xing ◽

Zhi Huang ◽

Jing Peng ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Risk Assessment ◽

Dna Methylation ◽

Differentially Expressed Genes ◽

Risk Score ◽

Immune Cells ◽

Assessment Model ◽

Differentially Expressed ◽

Risk Assessment Model

Abstract Background Colorectal cancer (CRC) is the second most prevalent cancer, as it accounts for approximately 10% of all annually diagnosed cancers. Studies have indicated that DNA methylation is involved in cancer genesis. The purpose of this study was to investigate the relationships among DNA methylation, gene expression and the tumor-immune microenvironment of CRC, and finally, to identify potential key genes related to immune cell infiltration in CRC. Methods In the present study, we used the ChAMP and DESeq2 packages, correlation analyses, and Cox regression analyses to identify immune-related differentially expressed genes (IR-DEGs) that were correlated with aberrant methylation and to construct a risk assessment model. Results Finally, we found that HSPA1A expression and CCRL2 expression were positively and negatively associated with the risk score of CRC, respectively. Patients in the high-risk group were more positively correlated with some types of tumor-infiltrating immune cells, whereas they were negatively correlated with other tumor-infiltrating immune cells. After the patients were regrouped according to the median risk score, we could more effectively distinguish them based on survival outcome, clinicopathological characteristics, specific tumor-immune infiltration status and highly expressed immune-related biomarkers. Conclusion This study suggested that the risk assessment model constructed by pairing immune-related differentially expressed genes correlated with aberrant DNA methylation could predict the outcome of CRC patients and might help to identify those patients who could benefit from antitumor immunotherapy.

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Genomic Expression Profiling of Colorectal Cancer in Silico

10.21203/rs.3.rs-310514/v1 ◽

2021 ◽

Author(s):

Feifei Liu ◽

Yu Wang ◽

Wenxue Li ◽

Diancheng Li ◽

Yuwei Xin ◽

...

Keyword(s):

Colorectal Cancer ◽

Survival Analysis ◽

Mrna Expression ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Functional Enrichment ◽

Differentially Expressed ◽

Analysis Tool ◽

Hub Genes ◽

Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

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New differentially expressed genes and differential DNA methylation underlying refractory epilepsy

Oncotarget ◽

10.18632/oncotarget.13642 ◽

2016 ◽

Vol 7 (52) ◽

pp. 87402-87416 ◽

Cited By ~ 13

Author(s):

Xi Liu ◽

Shu Ou ◽

Tao Xu ◽

Shiyong Liu ◽

Jinxian Yuan ◽

...

Keyword(s):

Dna Methylation ◽

Differentially Expressed Genes ◽

Refractory Epilepsy ◽

Differentially Expressed

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Identification of differentially expressed genes and biological pathways in bladder cancer

Molecular Medicine Reports ◽

10.3892/mmr.2018.8711 ◽

2018 ◽

Cited By ~ 1

Author(s):

Fucai Tang ◽

Zhaohui He ◽

Hanqi Lei ◽

Yuehan Chen ◽

Zechao Lu ◽

...

Keyword(s):

Bladder Cancer ◽

Differentially Expressed Genes ◽

Biological Pathways ◽

Differentially Expressed

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DNA-methylation analysis of differentially expressed genes in fibroblast cell-lines, derived from monozygotic twins discordant for Parkinson’s disease

Nauchno-prakticheskii zhurnal «Medicinskaia genetika» ◽

10.25557/2073-7998.2020.12.73-74 ◽

2020 ◽

pp. 73-74

Author(s):

И.Н. Рыболовлев ◽

И.Н. Власов ◽

А.Х. Алиева ◽

П.А. Сломинский ◽

М.И. Шадрина

Keyword(s):

Parkinson’S Disease ◽

Dna Methylation ◽

Parkinson's Disease ◽

Cell Lines ◽

Differentially Expressed Genes ◽

Regulation Of Gene Expression ◽

Monozygotic Twins ◽

Fibroblast Cell ◽

Differentially Expressed ◽

Pathogenesis Related

Болезнь Паркинсона (БП) является многофакторным гетерогенным нейродегенеративным заболеванием. Поскольку этиопатогенез БП недостаточно изучен, кроме поиска и анализа изменений на уровне ДНК, необходимо распространить фокус исследований на другие уровни: транскриптом и метилом. Изменения на уровне эпигенома можно исследовать у лиц с идентичной генетической конституцией, такой «моделью» являются дискордантные по этому заболеванию монозиготные близнецы. В исследовании приняло участие 3 пары фенотипически и генотипически монозиготных близнецов русского происхождения; В исследовании приняло участие 3 пары фенотипически и генотипически монозиготных близнецов русского происхождения. БП была уточнена у одного из каждой пары близнецов; длительность течения болезни у близнеца с БП составило по меньшей мере 7 лет.; длительность течения болезни у близнеца с БП составила по меньшей мере 7 лет. Были проанализированы метиломы крови и отобраны точки варьирующегося метилирования. Нами было найдено 8 дифференциально экспрессирующихся генов, которые могут быть дифференциально метилированы. Были выявлены различия между здоровым близнецом и близнецом с БП по уровню метилирования ДНК для ряда этих генов в клеточных линиях фибробластов. Полученные нами данные могут указывать на участие процесса ДНК-метилирования в регуляции транскрипции кандидатных генов-участников патогенеза БП. In recent years it has been convincingly demonstrated that genetic factors play an important role in progression of Parkinson’s disease (PD). Since the etiology of PD has not been elucidated completely yet, it is crucial to shift focus of the research to the broader areas - to dive into investigations of methylome and transcriptome. Epigenetic regulation of gene expression may take part in pathogenesis of PD. Changes in epigenome can be conveniently investigated in case of individuals with almost identical genetic makeup, and monozygotic twins discordant for PD may be such “model”. 3 pairs phenotypically and genotypically monozygous twins of Russian ancestry were enrolled in the study. PD was diagnosed in one of each pair. The disease duration was at least 7 years. Data on blood methylomes was analyzed. Points of variable methylation in blood methylomes were selected. With this approach, 8 differentially expressed genes were found that also may be differentially methylated. Changes in methylation level for some of this genes were found in monozygotic twins discordant for PD fibroblasts cell-lines between healthy and afflicted siblings. Acquired data might suggest participation of DNA-methylation in transcription regulation of PD pathogenesis-related candidate genes.

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Identification of Differentially Expressed Genes and miRNAs Associated with Esophageal Squamous Cell Carcinoma by Integrated Analysis of Microarray Data

BioMed Research International ◽

10.1155/2020/1980921 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Lemeng Zhang ◽

Jianhua Chen ◽

Tianli Cheng ◽

Hua Yang ◽

Changqie Pan ◽

...

Keyword(s):

Gene Expression ◽

Squamous Cell Carcinoma ◽

Survival Analysis ◽

Esophageal Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Differentially Expressed Genes ◽

Microarray Data ◽

Regulatory Network ◽

Differentially Expressed ◽

Pathway Enrichment

To identify candidate key genes and miRNAs associated with esophageal squamous cell carcinoma (ESCC) development and prognosis, the gene expression profiles and miRNA microarray data including GSE20347, GSE38129, GSE23400, and GSE55856 were downloaded from the Gene Expression Omnibus (GEO) database. Clinical and survival data were retrieved from The Cancer Genome Atlas (TCGA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) was analyzed via DAVID, while the DEG-associated protein-protein interaction network (PPI) was constructed using the STRING database. Additionally, the miRNA target gene regulatory network and miRNA coregulatory network were constructed, using the Cytoscape software. Survival analysis and prognostic model construction were performed via the survival (version 2.42-6) and rbsurv R packages, respectively. The results showed a total of 2575, 2111, and 1205 DEGs, and 226 differentially expressed miRNAs (DEMs) were identified. Pathway enrichment analyses revealed that DEGs were mainly enriched in 36 pathways, such as the proteasome, p53, and beta-alanine metabolism pathways. Furthermore, 448 nodes and 1144 interactions were identified in the PPI network, with MYC having the highest random walk score. In addition, 7 DEMs in the microarray data, including miR-196a, miR-21, miR-205, miR-194, miR-103, miR-223, and miR-375, were found in the regulatory network. Moreover, several reported disease-related miRNAs, including miR-198a, miR-103, miR-223, miR-21, miR-194, and miR-375, were found to have common target genes with other DEMs. Survival analysis revealed that 85 DEMs were related to prognosis, among which hsa-miR-1248, hsa-miR-1291, hsa-miR-421, and hsa-miR-7-5p were used for a prognostic survival model. Taken together, this study revealed the important roles of DEGs and DEMs in ESCC development, as well as DEMs in the prognosis of ESCC. This will provide potential therapeutic targets and prognostic predictors for ESCC.

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