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Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer
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 e...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5771567/ https://www.ncbi.nlm.nih.gov/pubmed/29342159 http://dx.doi.org/10.1371/journal.pone.0189582 |
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author | Makondi, Precious Takondwa Lee, Chia-Hwa Huang, Chien-Yu Chu, Chi-Ming Chang, Yu-Jia Wei, Po-Li |
author_facet | Makondi, Precious Takondwa Lee, Chia-Hwa Huang, Chien-Yu Chu, Chi-Ming Chang, Yu-Jia Wei, Po-Li |
author_sort | Makondi, Precious Takondwa |
collection | PubMed |
description | 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 1A(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. |
format | Online Article Text |
id | pubmed-5771567 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-57715672018-01-23 Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer Makondi, Precious Takondwa Lee, Chia-Hwa Huang, Chien-Yu Chu, Chi-Ming Chang, Yu-Jia Wei, Po-Li PLoS One Research Article 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 1A(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. Public Library of Science 2018-01-17 /pmc/articles/PMC5771567/ /pubmed/29342159 http://dx.doi.org/10.1371/journal.pone.0189582 Text en © 2018 Makondi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Makondi, Precious Takondwa Lee, Chia-Hwa Huang, Chien-Yu Chu, Chi-Ming Chang, Yu-Jia Wei, Po-Li Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer |
title | Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer |
title_full | Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer |
title_fullStr | Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer |
title_full_unstemmed | Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer |
title_short | Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer |
title_sort | prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5771567/ https://www.ncbi.nlm.nih.gov/pubmed/29342159 http://dx.doi.org/10.1371/journal.pone.0189582 |
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