Dataset Information

Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis.

ABSTRACT: Endometrial carcinoma (EC) is a common malignant neoplasm of the female reproductive tract. The malignant degree of type II EC is much greater than that of type I EC, usually presenting with a high recurrence rate and a poor prognosis. Therefore, the present study aimed to examine the principal genes associated with the degree of differentiation in type I and type II EC and reveal their potential mechanisms. Differentially expressed genes (DEGs) were selected from the gene expression profiles derived from The Cancer Genome Atlas. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. In the present study, the KEGG pathway enrichment analysis revealed that 5,962 upregulated DEGs were significantly enriched in the 'p53 signaling pathway' and involved in 'lysine degradation'. In addition, 3,709 downregulated DEGs were enriched in 'pathways in cancer', as well as 'tight junction regulation', the 'cell cycle' and the 'Wnt signaling pathway'. The 13 top hub genes MAPK1, PHLPP1, ESR1, MDM2, CDKN2A, CDKN1A, AURKA, BCL2L1, POLQ, PIK3R3, RHOQ, EIF4E and LATS2 were identified via the protein-protein interaction network. Furthermore, the OncoPrint algorithm from cBioPortal declared that 25% of EC cases carried genetic alterations. The altered DEGs (MAPK1, MDM2, AURKA, EIF4E and LATS2) may be involved in tumor differentiation and may be valuable diagnostic biomarkers. In conclusion, a number of principal genes were identified in the present study that may be determinants of poorly differentiated type II EC carcinogenesis, which may contribute to future research into potential molecular mechanisms. In addition, these genes may help identify candidate biomarkers and novel therapeutic targets for type II EC.

SUBMITTER: Zhang K

PROVIDER: S-EPMC6676660 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis.

Zhang Kai K Li Huiyang H Yan Ye Y Zang Yuqin Y Li Ke K Wang Yingmei Y Xue Fengxia F

Oncology letters 20190628 3

Endometrial carcinoma (EC) is a common malignant neoplasm of the female reproductive tract. The malignant degree of type II EC is much greater than that of type I EC, usually presenting with a high recurrence rate and a poor prognosis. Therefore, the present study aimed to examine the principal genes associated with the degree of differentiation in type I and type II EC and reveal their potential mechanisms. Differentially expressed genes (DEGs) were selected from the gene expression profiles de ...[more]

PMID: 31452737

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Project description: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.

Project description:Nasopharyngeal carcinoma (NPC) is one of the most common malignancies in the head and neck. The aim of the current study was to identify the key pathways and genes involved in NPC through bioinformatics analysis and to identify potential molecular mechanisms underlying NPC proliferation and progression. Three gene expression profiles (GSE12452, GSE34573 and GSE64634) were downloaded from the Gene Expression Omnibus database. A total of 76 samples were analyzed, of which 59 were NPC samples and 17 were normal samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were subsequently conducted. The protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed using Cytoscape software. Analysis of GSE12452, GSE34573 and GSE64634 datasets identified 1,301 (553 upregulated and 748 downregulated), 1,232 (348 upregulated and 884 downregulated) and 1,218 (555 upregulated and 663 downregulated) DEGs, respectively. Using Venn diagram analysis, 268 DEGs (59 upregulated and 209 downregulated) that intersected all three datasets, were selected for further analysis. The results of GO analysis revealed that upregulated DEGs were significantly enriched in biological processes, including 'cell adhesion', 'cell division', 'mitosis' and 'mitotic cell cycle'. The downregulated DEGs were mainly enriched in 'microtubule-based movement', 'cilium movement', 'cilium axoneme assembly' and 'epithelial cell differentiation'. The KEGG pathway analysis results revealed that the upregulated DEGs were highly associated with several pathways, including 'extracellular matrix-receptor interaction', 'human papillomavirus infection', 'arrhythmogenic right ventricular cardiomyopathy' and 'focal adhesion', whereas the downregulated DEGs were enriched in 'metabolic pathways', 'Huntington's disease', 'fluid shear stress and atherosclerosis' and 'chemical carcinogenesis'. On the basis of the PPI network of the DEGs, the following top 10 hub genes were identified: Dynein axonemal light intermediate chain 1, dynein axonemal intermediate chain 2, calmodulin 1, coiled-coil domain containing 114, dynein axonemal heavy chain 5, radial spoke head 9 homolog, radial spoke head component 4A, NDC80 kinetochore complex component, thymidylate synthetase and coiled-coil domain containing 39. In conclusion, by performing a comprehensive bioinformatics analysis of DEGs, putative targets that could be used to elucidate the molecular mechanisms underlying NPC were identified.

Project description:BackgroundAtherosclerosis (AS) is a chronic inflammatory disease that might induce severe cardiovascular events, such as myocardial infarction and cerebral infarction. These risk factors in the pathogenesis of AS remain uncertain and further research is needed. This study aims to explore the potential molecular mechanisms of AS by bioinformatics analyses.MethodsGSE100927 gene expression profiles, including 69 AS samples and 35 healthy controls, were downloaded from Gene Expression Omnibus database and indenfied for key genes and pathways in AS.ResultsA total of 443 differentially expressed genes (DEGs) between control and AS were identified, including 323 down-regulated genes and 120 up-regulated genes. The Gene ontology terms enriched by the up-regulated DEGs were associated with the regulation of leukocyte activation, endocytic vesicle, and cytokine binding, while the down-regulated DEGs were associated with negative regulation of cell growth, extracellular matrix, and G protein-coupled receptor binding. KEGG pathway analysis showed that the up-regulated DEGs were enriched in Osteoclast differentiation and Phagosome, while the down-regulated DEGs were enriched in vascular smooth muscle contraction and cGMP-PKG signaling pathway. Using the modular analysis of Cytoscape, we identified 3 modules mainly involved in Leishmaniasis and Osteoclast differentiation. The GSEA analysis showed the up-regulated gene sets were enriched in the ribosome, ascorbated metabolism, and propanoate metabolism. The LASSO Cox regression analysis showed the top 3 genes were TNF, CX3CR1, and COL1R1. Finally, we found these immune cells were conferred significantly higher infiltrating density in the AS group.ConclusionsOur data showed the pathway of Osteoclast differentiation and Leishmaniasis was involved in the AS process and we developed a three-gene model base on the prognosis of AS. These findings clarified the gene regulatory network of AS and may provide a novel target for AS therapy.

Dataset Information

Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis.

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Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis.

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