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

In the present study, the RNA sequencing (RNA-seq) data of uterine corpus endometrial carcinoma (UCEC) samples were collected and analyzed using bioinformatics tools to identify potential genes associated with the development of UCEC. UCEC RNA-seq data were downloaded from The Cancer Genome Atlas database. Differential analysis was performed using edgeR software. A false discovery rate <0.01 and |log2(fold change)|>1 were set as the cut-off criteria to screen for differentially expressed genes (DEGs). Differential gene co-expression analysis was performed using R/EBcoexpress package in R. DEGs in the gene co-expression network were subjected to Gene Ontology analysis using the Database for Annotation, Visualization and Integration Discovery. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was also performed on the DEGs using KOBAS 2.0 software. The ConnectivityMap database was used to identify novel drug candidates. A total of 3,742 DEGs were identified among the 552 UCEC samples and 35 normal controls, and comprised 2,580 upregulated and 1,162 downregulated genes. A gene co-expression network consisting of 129 DEGs and 368 edges was constructed. Genes were associated with the cell cycle and the tumor protein p53 signaling pathway. Three modules were identified, in which genes were associated with the mitotic cell cycle, nuclear division and the M phase of the mitotic cell cycle. Multiple key hub genes were identified, including cell division cycle 20, cyclin B2, non-SMC condensin I complex subunit H, BUB1 mitotic checkpoint serine/threonine kinase, cell division cycle associated 8, maternal embryonic leucine zipper kinase, MYB proto-oncogene like 2, TPX2, microtubule nucleation factor and non-SMC condensin I complex subunit G. In addition, the small molecule drug esculetin was implicated in the suppression of UCEC progression. Overall, the present study identified multiple key genes in UCEC and clinically relevant small molecule agents, thereby improving our understanding of UCEC and expanding perspectives on targeted therapy for this type of cancer.
 ...
PMID:Bioinformatics analysis of RNA sequencing data reveals multiple key genes in uterine corpus endometrial carcinoma. 2938 16

Endometrial cancer (EC) is the fourth most common cancer in women worldwide. Although researchers are exploring the biological processes of tumorigenesis and development of EC, the gene interactions and biological pathways of EC are not accurately verified. In the present study, bioinformatics methods were used to screen for key candidate genes and pathways that were associated with EC and to reveal the possible mechanisms at molecular level. Microarray datasets (GSE63678, GSE17025 and GSE3013) from the Gene Expression Omnibus database were downloaded and 118 differentially expressed genes (DEGs) were selected using a Venn diagram. Functional enrichment analyses were performed on the DEGs. A protein-protein interaction network was constructed, including the module analysis. A total of 11 hub genes were identified from the DEGs, and functional enrichment analyses were performed to clarify their possible biological processes. A total of 118 DEGs were selected from three mRNA datasets. Functional enrichment demonstrated 27 downregulated genes that were primarily involved in the positive regulation of transcription from RNA polymerase II promoter, protein binding and the nucleus. A total of 91 upregulated DEGs were mainly associated with cell division, protein binding and the nucleus. Pathway analysis indicated that the downregulated DEGs were mainly enriched in pathways associated with cancer, and the upregulated DEGs were mainly enriched in the cell cycle. The 11 hub genes were primarily enriched in the cell cycle, oocyte meiosis, progesterone-mediated oocyte maturation, the p53 signaling pathway and viral carcinogenesis. The integrated analysis showed that cyclin B1, ubiquitin conjugating enzyme E2 C and cell division cycle 20 may participate in the tumorigenesis, development and invasion of EC. In conclusion, the hub genes and pathways identified in the present study contributed to the understanding of carcinogenesis and progression of EC at the mechanistic and molecular-biological level. As candidate targets for the diagnosis and treatment of EC, these genes deserve further investigation.
 ...
PMID:Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis. 3180 78