Literature DB >> 30982140

Identification of Pathogenic Genes and Transcription Factors in Osteosarcoma.

Chenggang Yang1,2, Di Huang1,2, Cui Ma1,2, Jing Ren2, Lina Fu2, Cheng Cheng2, Bangling Li3, Xiaofeng Shi4,5.   

Abstract

Osteosarcoma (OS) is an aggressive malignant tumor of the bones. Our study intended to identify and analyze potential pathogenic genes and upstream regulators for OS. We performed an integrated analysis to identify candidate pathogenic genes of OS by using three Gene Expression Omnibus (GEO) databases (GSE66673, GSE49003 and GSE37552). GO and KEGG enrichment analysis were utilized to predict the functional annotation and potential pathways of differentially expressed genes (DEGs). The OS-specific transcriptional regulatory network was established to study the crucial transcriptional factors (TFs) which target the DEGs in OS. From the three GEO datasets, we identified 759 DEGs between metastasis OS samples and non-metastasis OS samples. After GO and KEGG analysis, 'cell adhesion' (FDR = 1.27E-08), 'protein binding' (FDR = 1.13E-22), 'cytoplasm' (FDR = 5.63E-32) and 'osteoclast differentiation' (FDR = 0.000992221) were significantly enriched pathways for DEGs. HSP90AA1 exhibited a highest degree (degree = 32) and was enriched in 'pathways in cancer' and 'signal transduction'. BMP6, regulated by Pax-6, was enriched in the 'TGF-beta signaling pathway'. We indicated that BMP6 may be downregulated by Pax-6 in the non-metastasis OS samples. The up-regulated HSP90AA1 and down-regulated BMP6 and 'pathways in cancer' and 'signal transduction' were deduced to be involved in the pathogenesis of OS. The identified biomarkers and biological process in OS may provide foundation for further study.

Entities:  

Keywords:  DEGs; Integrated analysis; Osteosarcoma; Transcription factors

Mesh:

Substances:

Year:  2019        PMID: 30982140     DOI: 10.1007/s12253-019-00645-w

Source DB:  PubMed          Journal:  Pathol Oncol Res        ISSN: 1219-4956            Impact factor:   3.201


  3 in total

1.  Identification of Osteosarcoma Metastasis-Associated Gene Biomarkers and Potentially Targeted Drugs Based on Bioinformatic and Experimental Analysis.

Authors:  Ming-De Cao; Yan-Cheng Song; Zhong-Meng Yang; Da-Wei Wang; Yi-Ming Lin; Hua-Ding Lu
Journal:  Onco Targets Ther       Date:  2020-08-14       Impact factor: 4.147

2.  Implication of ZNF217 in Accelerating Tumor Development and Therapeutically Targeting ZNF217-Induced PI3K-AKT Signaling for the Treatment of Metastatic Osteosarcoma.

Authors:  Branden A Smeester; Garrett M Draper; Nicholas J Slipek; Alex T Larsson; Natalie Stratton; Emily J Pomeroy; Kelsie L Becklin; Kenta Yamamoto; Kyle B Williams; Kanut Laoharawee; Joseph J Peterson; Juan E Abrahante; Susan K Rathe; Lauren J Mills; Margaret R Crosby; Wendy A Hudson; Eric P Rahrmann; David A Largaespada; Branden S Moriarity
Journal:  Mol Cancer Ther       Date:  2020-09-30       Impact factor: 6.261

3.  Identification of potential gene signatures associated with osteosarcoma by integrated bioinformatics analysis.

Authors:  Yutao Jia; Yang Liu; Zhihua Han; Rong Tian
Journal:  PeerJ       Date:  2021-05-27       Impact factor: 2.984

  3 in total

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