Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer

被引:15
作者
Makondi, Precious Takondwa [1 ,2 ]
Lee, Chia-Hwa [3 ]
Huang, Chien-Yu [4 ,5 ]
Chu, Chi-Ming [6 ]
Chang, Yu-Jia [1 ,2 ,7 ]
Wei, Po-Li [4 ,7 ,8 ,9 ,10 ]
机构
[1] Taipei Med Univ, Coll Med, Int PhD Program Med, Taipei, Taiwan
[2] Taipei Med Univ, Coll Med, Grad Inst Clin Med, Taipei, Taiwan
[3] Taipei Med Univ, Coll Med Sci & Technol, Sch Med Lab Sci & Biotechnol, Taipei, Taiwan
[4] Taipei Med Univ, Coll Med, Dept Surg, Taipei, Taiwan
[5] Taipei Med Univ, Shuang Ho Hosp, Dept Surg, Div Gen Surg, Taipei, Taiwan
[6] Natl Def Med Ctr, Sch Publ Hlth, Taipei, Taiwan
[7] Taipei Med Univ, Taipei Med Univ Hosp, Dept Med Res, Canc Res Ctr & Translat Lab, Taipei, Taiwan
[8] Taipei Med Univ, Wan Fang Hosp, Dept Surg, Div Colorectal Surg, Taipei, Taiwan
[9] Taipei Med Univ, Taipei Med Univ Hosp, Dept Surg, Div Colorectal Surg, Taipei, Taiwan
[10] Taipei Med Univ, Grad Inst Canc Biol & Drug Discovery, Taipei, Taiwan
来源
PLOS ONE | 2018年 / 13卷 / 01期
关键词
NEGATIVE BREAST-CANCER; RECEPTOR; 4; CYTOSCAPE PLUGIN; PHASE-III; EXPRESSION; THERAPY; SURVIVAL; CHEMOTHERAPY; COLON; FLUOROURACIL;
D O I
10.1371/journal.pone.0189582
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC) therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). Protein protein interaction (PPI) networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING) and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs); the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1 A(CDKN1A), toll-like receptor 4 (TLR4), CD19 molecule (CD19), breast cancer 1, early onset (BRCA1), platelet-derived growth factor subunit A (PDGFA), and matrix metallopeptidase 1 (MMP1) were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4) revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS). The identified genes and pathways can be potential targets and predictors of therapeutic resistance and prognosis in bevacizumab-treated patients with mCRC.
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页数:18
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