Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0476089 (endometrial cancer)
 11,379 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

We performed RNA-seq on an Illumina platform for 7 patients with endometrioid endometrial carcinoma for which both tumor tissue and adjacent noncancer tissue were available. A total of 66 genes were differentially expressed with significance level at adjusted p value < 0.01. Using the gene functional classification tool in the NIH DAVID bioinformatics resource, 5 genes were found to be the only enriched group out of that list of genes. The gene IGSF9 was chosen for further characterization with immunohistochemical staining of a larger cohort of human endometrioid carcinoma tissues. The expression level of IGSF9 in cancer cells was significantly higher than that in control glandular cells in paired tissue samples from the same patients (p = 0.008) or in overall comparison between cancer and the control (p = 0.003). IGSF9 expression is higher in patients with myometrium invasion relative to those without invasion (p = 0.015). Reanalysis of RNA-seq dataset from The Cancer Genome Atlas shows higher expression of IGSF9 in endometrial cancer versus normal control and expression was associated with poor prognosis. These results suggest IGSF9 as a new biomarker in endometrial cancer and warrant further studies on its function, mechanism of action, and potential clinical utility.
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PMID:RNA-seq Reveals the Overexpression of IGSF9 in Endometrial Cancer. 2966 43

Purpose: N6-methyladenosine (m6A) methylation was the most abundant internal modification on messenger RNAs in eukaryotes. This study intended to explore the role of m6A methylation in endometrial cancer (EC). Materials and Methods: The m6A-sequencing data "GSE93911" of human EC were downloaded from Gene Expression Omnibus database. Hisat2 software and MACS2 were used to perform the alignment of reads and m6A methylation peak calling, and the peaks were annotated using Chipseeker. Then, differential m6A methylation peaks between normal and tumor samples were analyzed, followed by the functional enrichment analysis of the differentially methylated genes in promoter and 3' untranslated region (UTR) using Clusterprofiler. Based on the 450K methylated chip data, gene expression and clinical data in The Cancer Genome Atlas, the differentially methylated genes were verified, followed by Cox univariate/multivariate regression analysis and survival analysis. Finally, a risk prognosis model was constructed. Results: The m6A peak number was decreased in EC. The distribution of m6A peaks was highly enriched near transcriptional start site, in promoter, UTR, intron and exon, followed by distal intergenic. A total of 581 differentially methylated genes (361 hyper- and 220 hypomethylated genes) were identified in promoter and UTR regions that were enriched in insulin resistance (IR) and extracellular matrix (ECM). A total of 181 genes with significant differential expressions and differential methylation site in EC were selected. Of which, 31 genes were correlated with survival, and an 11-gene risk prognosis model was identified, including GDF7, BNC2, SLC8A1, B4GALNT3, DHCR24, ESRP1, HOXB9, IGSF9, KIAA1324, MSnX1, and PHGDH. Conclusion: The m6A methylation regulated EC progression by targeting the genes related to IR and ECM. A 11-gene risk prognosis model was identified to predict survival of patients with EC.
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PMID:The Role of N6-Methyladenosine Methylation in the Progression of Endometrial Cancer. 3305 42