Integrated bioinformatics identifies the dysregulation induced by aberrant gene methylation in colorectal carcinoma.
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ABSTRACT:
SUBMITTER: Ye Z
PROVIDER: S-EPMC8209361 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Acute myeloid leukemia (AML) is a life-threatening hematological malignant disease. Methylation plays a crucial role in the etiology and pathogenesis of AML. The aim of the present study was to identify the aberrantly methylated differentially expressed genes (DEGs) in AML and determine the underlying mechanisms of tumorigenesis by conducting integrated bioinformatics analyses. Gene expression profiles (GSE109179, GSE142699, GSE49665 and GSE14772) and a gene methylation profile (GSE42042) were analyzed to identify the aberrantly methylated DEGs. Functional enrichment analyses of identified genes were conducted based on the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, and protein-protein interaction networks were established. Finally, the DEGs were validated by the reverse transcription-quantitative PCR analysis of patient samples. A total of seven downregulated hypermethylated genes and eight upregulated hypomethylated genes were validated. The differentially methylated DEGs were enriched in GO biological process terms associated with control of the immune response and the KEGG analysis indicated they were involved in AML, ferroptosis, TGF-β signaling and necroptosis pathways. Additionally, five downregulated hypermethylated genes that were also tumor suppressor genes (TSGs) were identified. In vitro assays revealed that the overexpression of transcription factor 7 (TCF7) and integrin a M (ITGAM) significantly inhibited the proliferation of HL60 cells; by contrast, the knockdown of TCF7 and CAMK4 promoted HL60 cell proliferation. Overall, the present study identified differentially methylated DEGs and pathways associated with AML, which may enhance the understanding of the underlying molecular mechanisms of AML. In the future, abnormally methylated oncogenes and TSGs may function as biomarkers and treatment targets for the diagnosis and treatment of AML.
| S-EPMC9494628 | biostudies-literature
Project description:BackgroundColorectal cancer (CRC) multiplicity has been mainly related to polyposis and non-polyposis hereditary syndromes. In sporadic CRC, aberrant gene promoter methylation has been shown to play a key role in carcinogenesis, although little is known about its involvement in multiplicity. To assess the effect of methylation in tumor multiplicity in sporadic CRC, hypermethylation of key tumor suppressor genes was evaluated in patients with both multiple and solitary tumors, as a proof-of-concept of an underlying epigenetic defect.Methodology/principal findingsWe examined a total of 47 synchronous/metachronous primary CRC from 41 patients, and 41 gender, age (5-year intervals) and tumor location-paired patients with solitary tumors. Exclusion criteria were polyposis syndromes, Lynch syndrome and inflammatory bowel disease. DNA methylation at the promoter region of the MGMT, CDKN2A, SFRP1, TMEFF2, HS3ST2 (3OST2), RASSF1A and GATA4 genes was evaluated by quantitative methylation specific PCR in both tumor and corresponding normal appearing colorectal mucosa samples. Overall, patients with multiple lesions exhibited a higher degree of methylation in tumor samples than those with solitary tumors regarding all evaluated genes. After adjusting for age and gender, binomial logistic regression analysis identified methylation of MGMT2 (OR, 1.48; 95% CI, 1.10 to 1.97; p = 0.008) and RASSF1A (OR, 2.04; 95% CI, 1.01 to 4.13; p = 0.047) as variables independently associated with tumor multiplicity, being the risk related to methylation of any of these two genes 4.57 (95% CI, 1.53 to 13.61; p = 0.006). Moreover, in six patients in whom both tumors were available, we found a correlation in the methylation levels of MGMT2 (r = 0.64, p = 0.17), SFRP1 (r = 0.83, 0.06), HPP1 (r = 0.64, p = 0.17), 3OST2 (r = 0.83, p = 0.06) and GATA4 (r = 0.6, p = 0.24). Methylation in normal appearing colorectal mucosa from patients with multiple and solitary CRC showed no relevant difference in any evaluated gene.ConclusionsThese results provide a proof-of-concept that gene promoter methylation is associated with tumor multiplicity. This underlying epigenetic defect may have noteworthy implications in the prevention of patients with sporadic CRC.
| S-EPMC2808250 | biostudies-literature
Project description:Malignant pheochromocytoma (PHEO) can only be fully diagnosed when metastatic foci develop. However, at this point in time, patients gain little benefit from traditional therapeutic methods. Methylation plays an important role in the pathogenesis of PHEO. The aim of this research was to use integrated bioinformatics analysis to identify differentially expressed genes (DEGs) showing aberrant methylation patterns in PHEO and therefore provide further understanding of the molecular mechanisms underlying this condition. Aberrantly methylated DEGs were first identified by using R software (version 3.6) to combine gene expression microarray data (GSE19422) with gene methylation microarray data (GSE43293). An online bioinformatics database (DAVID) was then used to identify all overlapping DEGs showing aberrant methylation; these were annotated and then functional enrichment was ascertained by gene ontology (GO) analysis. The online STRING tool was then used to analyze interactions between all overlapping DEGs showing aberrant methylation; these results were then visualized by Cytoscape (version 3.61). Next, using the cytoHubba plugin within Cytoscape, we identified the top 10 hub genes and found that these were predominantly enriched in pathways related to cancer. Reference to The Cancer Genome Atlas (TCGA) further confirmed our results and further identified an upregulated hypomethylated gene (SCN2A) and a downregulated hypermethylated gene (KCNQ1). Logistic regression analysis and receiver operating characteristic (ROC) curve analysis indicated that KCNQ1 and SCN2A represent promising differential diagnostic biomarkers between benign and malignant PHEO. Finally, clinical data showed that there were significant differences in the concentrations of potassium and sodium when compared between pre-surgery and post-surgery day 1. These suggest that KCNQ1 and SCN2A, genes that encode potassium and sodium channels, respectively, may serve as putative diagnostic targets for the diagnosis and prognosis of PHEO and therefore facilitate the clinical management of PHEO.
| S-EPMC6873930 | biostudies-literature
Project description:ABCG2 is a ubiquitous ATP-binding cassette transmembrane protein that is important in clinical drug resistance. Little is known about the mechanism(s) regulating the expression of ABCG2. We hypothesized that DNA methylation could play a role in the epigenetic regulation of ABCG2 gene expression. The promoter methylation status of three renal carcinoma cell lines was assessed with restriction enzyme digestion-coupled PCR and bisulfite genomic sequencing. Both UOK121 and UOK143, with known methylation of the VHL promoter, showed induction of ABCG2 expression after 5-aza-2'-deoxycytidine (5-aza-dC) treatment, suggesting that aberrant methylation of the ABCG2 gene was associated with gene silencing. In vitro methylation of the ABCG2 promoter-driven luciferase reporter vector resulted in a significant inhibition of transcription. Our data suggested that the ABCG2 gene is regulated coordinately at both histone and DNA levels. A chromatin immunoprecipitation assay demonstrated that the methylated promoter in UOK121 and UOK143, but not the unmethylated one in UOK181, is associated with the methyl CpG binding domain proteins (MBDs), MBD2 and MeCP2. Histone deacetylase 1 and a corepressor, mSin3A, were identified binding to the promoter region containing the CpG island, thereby suppressing ABCG2 transcription. Reactivation of ABCG2 was achieved by treatment with 5-aza-dC, a demethylating agent, concomitant with the release of MBDs from the promoter. Furthermore, the association of methylated lysine 9 on histone H3, a hallmark of promoter methylation, with the promoter was reduced following 5-aza-dC treatment. These data suggest that DNA methylation-dependent formation of a repressor complex in the CpG island contributes to inactivation of ABCG2.
| S-EPMC1636795 | biostudies-literature
Project description:Objective This study is aimed at integrating bioinformatics and machine learning to determine novel diagnostic gene signals in the progression of heart failure disease. Methods The heart failure microarray datasets and RNA-seq datasets have been downloaded from the public database. Differentially expressed genes (DE genes) are screened out, and then, we analyze their biological functions and pathways. Integrating three machine learning methods, the least absolute shrinkage and selection operator (LASSO) algorithm, random forest (RF) algorithm, and support vector machine recursive feature elimination (SVM-RFE) are used to determine candidate diagnostic gene signals. Then, external independent RNA-seq datasets evaluate the diagnostic value of gene signals. Finally, the convolution tool CIBERSORT estimated the composition pattern of immune cell subtypes in heart failure and carried out a correlation analysis combined with gene signals. Results Under the set threshold, we obtained 47 DE genes with the most significant differences. Enrichment analysis shows that most of them are related to hypertrophy, matrix structural constituent, protein binding, inflammatory immune pathway, cardiovascular disease, and inflammatory disease. Three machine learning methods assisted in determining the potential characteristic signals Fras1-related extracellular matrix 1 (FREM1) and meiosis-specific nuclear structural 1 (MNS1). Validation of external datasets confirms that FREM1 is a diagnostic gene signal for heart failure. Immune cell subtypes of tissue specimens found T cell CD8, mast cell resting, T cell CD4 memory resting, T cell regulation (Tregs), monocytes, macrophages M2, T cell CD4 naive, macrophages M0, and neutrophils are associated with HF. Conclusion The gene signal FREM1 may be a potential molecular target in the development of HF and is related to the difference in immune infiltration of HF tissue.
| S-EPMC9206587 | biostudies-literature
Project description:Colorectal cancer is one of the most common cancers of humans and the second highest in cancer-related death. Genes used as prognostic biomarkers play an imperative role in cancer detection and may direct the development of appropriate therapeutic strategies. Collagen type XI alpha 1 (COL11A1) is a minor fibrillary collagen that has an essential role in the regulation of cell division, differentiation, proliferation, migration, growth, and apoptosis of intestinal and colon cells. The present study seeks to evaluate the significance of the COL11A1 gene in the progression of colorectal cancer in humans across the various parameters using advanced bioinformatics approaches. The application of various databases and servers like ONCOMINE, UALCAN, and GEPIA were accessed for analyzing the differential expression of the COLL11A1 gene and its relative influence over the survival of the transformed subjects. In addition, oncogenomics of COL11A1 gene, mutations associated with this gene and interacting partners of the gene in the context of oncogenesis were studied using COSMIC, cBioPortal, GeneMANIA, and NetworkAnalyst. Our experimental data indicate that the COL11A1 gene is overexpressed in the transformed tissues across the various clinicopathological parameters reduces the probability of survival in both overall and disease-specific survival cases. Mutational studies imply that it can induce perturbations in various signaling pathways viz. RTK-RAS-PI3K, Wnt, TGF-β, and TP53 pathways influencing cancer development. Also, a positive association and correlation amongst the THBS2, COL10A1, COL5A2, and COL1A2 genes were observed, which most likely to contribute to the upregulation of carcinogenesis. Conclusively, this comprehensive study indicates the COL11A1 gene to be a significant contributor in the etiology of colorectal cancer, henceforth this gene can be considered as a prognostic biomarker for the conception of diagnostic and therapeutic strategies against colorectal cancer in the near future.
| S-EPMC7882494 | biostudies-literature
Project description:The extracellular matrix (ECM) is reported to be involved in tumorigenesis and progression. Collagen IIX is a major ECM protein. Abnormal COL12A1 expression is associated with carcinogenesis of colorectal cancer (CRC), but its clinical value and function have not yet been analyzed. Expression, methylation, and survival were analyzed by using Oncomine, UNCLA, and GEPIA, while COL12A1 alterations and related functional networks were identified using cBioPortal. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathways（KEGG）of COL12A1 in CRC were explored using LinkOmics. Gene set enrichment analysis (GSEA) examined target networks of kinases, miRNAs, and transcription factors. We found that COL12A1 was overexpressed in CRC and the COL12A1 gene was often amplified in CRC. Survival analysis revealed that patients with higher COL12A1 expression had a poor prognosis. Expression of COL12A1 was linked to functional networks via regulating pathways involving focal adhesion, PI3K-Akt signaling pathway, and ECM-receptor interaction. Functional network analysis suggested that COL12A1 regulated integrin binding, collage binding, and extracellular matrix structural constituent via pathways involving some several cancer-related kinases, miRNAs, and transcription factor. Furthermore, other FACITs genes (COL1A2, COL3A1, COL5A1, COL5A2, and COL6A3) for ECM in correlation with COL12A1 were identified to be related with the prognosis in CRC. These results suggested that the distinct fibril-associated collagens with interrupted triple helices (FACITs) genes may serve as prognostic and therapeutic biomarkers of CRC in the future.
| S-EPMC7333847 | biostudies-literature
Project description:BackgroundColorectal cancer (CRC) is one of the most lethal malignancies and the incidence of CRC has been on the rise. Herein, we aimed to identify effective biomarkers for early diagnosis and treatment of colorectal cancer via bioinformatic tools.MethodsTo identify differentially expressed genes (DEGs) in CRC, we downloaded CRC gene expression data from GSE24514 and GSE110223 datasets in Gene Expression Omnibus (GEO) and employed R to analyze the data. We further performed functional enrichment analysis of the DEGs on the DAVID gene ontology analysis tool. STRING database and Cytoscape visualization tool were employed to construct a PPI (protein-protein interaction) network and establish intensive intervals in the network. Immunohistochemistry, qRT-PCR and Western blotting were performed to identify the expression level of GINS1 in CRC. In vitro and in vivo experiments were performed to assess the impact of GINS1 in the pathogenesis of CRC in terms of proliferation, migration and metastasis.ResultsAmong the two datasets, 389 DEGs were identified and used to construct a PPI network. These genes were mainly involved in cell proliferation and cell cycle. Among them, 15 genes including GINS1 were found to be strongly associated with the PPI network. We further performed immunohistochemistry, qRT-PCR and Western blotting to identify that GINS1 expression was higher in CRC than in paired normal tissues. Moreover, in vitro and in vivo experiments demonstrated GINS1 could promote the proliferation, invasion and migration of colorectal cancer cells.ConclusionsGINS1 could be considered as a potential biomarker for CRC patients.
| S-EPMC7680165 | biostudies-literature
Project description:Esophageal squamous cell carcinoma (ESCC) accounts for over 90% of all esophageal tumors. However, the molecular mechanism underlying ESCC development and prognosis remains unclear, and there are still no effective molecular biomarkers for diagnosing or predicting the clinical outcome of patients with ESCC. Here, using bioinformatics analyses, we attempted to identify potential biomarkers and therapeutic targets for ESCC. Differentially expressed genes (DEGs) between ESCC and normal esophageal tissue samples were obtained through comprehensive analysis of three publicly available gene expression profile datasets from the Gene Expression Omnibus database. The biological roles of the DEGs were identified by Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Moreover, the Cytoscape 3.7.1 platform and subsidiary tools such as Molecular Complex Detection (MCODE) and CytoHubba were used to visualize the protein-protein interaction (PPI) network of the DEGs and identify hub genes. A total of 345 DEGs were identified between normal esophageal and ESCC samples, which were enriched in the KEGG pathways of the cell cycle, endocytosis, pancreatic secretion, and fatty acid metabolism. Two of the highest scoring models were selected from the PPI network using Molecular Complex Detection. Moreover, CytoHubba revealed 21 hub genes with a valuable influence on the progression of ESCC in these patients. Among these, the high expression levels of five genes-SPP1, SPARC, BGN, POSTN, and COL1A2-were associated with poor disease-free survival of ESCC patients, as indicated by survival analysis. Taken together, we identified that elevated expression of five hub genes, including SPP1, is associated with poor prognosis in ESCC patients, which may serve as potential prognostic biomarkers or therapeutic target for ESCC.
| S-EPMC6948276 | biostudies-literature
Project description:Colorectal cancer (CRC) has become the second leading cause of new cancer cases and the fifth of cancer deaths in China, and early detection is the most effective way to reduce the incidence and mortality of CRC. A number of methylated DNA biomarkers have been found to associate with CRC and precancerous lesions in stool samples, indicating stool methylated DNA biomarkers are potential tools for CRC early detection. In this study, approximately 5 g of stool specimen was collected from 230 subjects (124 in the training set and 106 in the validation set). Stool DNA was extracted and bisulfite-converted, followed by ColoDefense test, a multiplex qPCR assay, that simultaneously detects methylated SEPT9 (mSEPT9) and methylated SDC2 (mSDC2). Youden index was employed to determine the cut-off value of ColoDefense test for stool specimens. In the training set, the optimized cut-off value of stool ColoDefense test was: mSEPT9 analyzed with 3/3 algorithm and mean mSEPT9 Ct values of <38, or mSDC2 with 2/3 algorithm. Stool ColoDefense test achieved Youden indexes of 79.9 and 57.4% in detecting CRC and advanced adenomas (AA), respectively. Its sensitivities in the training set for AA and CRC were 66.7% (95% CI: 24.1-94.0%) and 89.1% (95% CI: 77.1-95.5%) with a 90.8% (95% CI: 80.3-96.2%) specificity, and AUC was 0.956 (95% CI: 0.924-0.988). In the validation set, its sensitivities for AA and CRC were 66.7% (95% CI: 24.1-94.0%) and 92.3% (95% CI: 78.0-98.0%) with a 93.2% (95% CI: 82.7-97.8%) specificity, and AUC was 0.977 (95% CI: 0.952-1.000). Positive detection rate of stool ColoDefense test has been found to be independent of age, gender, tumor location, and tumor size. In conclusion, stool ColoDefense test demonstrated high sensitivities and specificity for the detection of AA and CRC. Therefore, it has the potential to become a low-cost, convenient, and highly effective tool for CRC early detection.
| S-EPMC7314930 | biostudies-literature