Prediction of novel target genes and pathways involved in irinotecan-resistant colorectal cancer.
Prediction of novel target genes and pathways involved in irinotecan-resistant colorectal cancer.
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DOI：
10.1371/journal.pone.0180616
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Chang YJ
中科院分区：
文献类型：
--
作者：
Makondi PT;Chu CM;Wei PL;Chang YJ
对化疗药物伊立替康（其活性代谢产物是SN-38）的获得性耐药是晚期结直肠癌（CRC）治疗的重要障碍之一。介导伊立替康耐药的分子机制或靶点尚不清楚。寻找伊立替康应答的生物标志物对提高结直肠癌患者的治疗效果具有重要意义。使用包含亲本和伊立替康耐药HCT-116细胞系的基因表达谱的遗传综合数据库GSE 42387。进行亲本细胞和伊立替康耐药细胞之间的差异表达基因（DEG）、蛋白质-蛋白质相互作用（PPI）、基因本体论（PIB）和途径分析，以确定总体生物学变化。确定了PPI、PPI和通路中最常见的DEG，并通过其预测总生存期和无病生存期的能力进行了临床验证。还使用癌症基因组图谱数据（TCGA）评估了CRC患者的基因-基因表达相关性和基因-耐药相关性。鉴定了135个DEG，其中36个上调，99个下调。在绘制PPI网络、PIB和途径之后，发现9个基因（GNAS、PRKACB、MECOM、PLA 2G 4C、BMP 6、BDNF、DLG 4、FGF 2和FGF 9）通常富集。信号转导途径是最重要的GO途径，MAPK途径是最重要的GO途径。MAPK信号转导通路中的5个基因（FGF 2、FGF 9、PRKACB、MECOM和PLA 2G 4C）均参与信号转导，且表达水平上调。FGF 2、FGF 9和MECOM的表达与结直肠癌患者的生存率高度相关，而PRKACB和PLA 2G 4C的表达与结直肠癌患者的生存率无关。此外，FGF 9还与伊立替康耐药性和无病生存率差相关。基因-基因表达相关分析表明，FGF 2、FGF 9与PRKACB之间呈正相关，MECOM与FGF 9、PLA 2G 4C之间呈正相关，与FGF 2、PRKACB之间呈负相关。通过靶向FGF 2、FGF 9、MECOM、PLA 2G 4C和PRKACB靶向MAPK信号转导途径可能会增加肿瘤对伊立替康治疗的反应性。
Acquired drug resistance to the chemotherapeutic drug irinotecan (the active metabolite of which is SN-38) is one of the significant obstacles in the treatment of advanced colorectal cancer (CRC). The molecular mechanism or targets mediating irinotecan resistance are still unclear. It is urgent to find the irinotecan response biomarkers to improve CRC patients’ therapy. Genetic Omnibus Database GSE42387 which contained the gene expression profiles of parental and irinotecan-resistant HCT-116 cell lines was used. Differentially expressed genes (DEGs) between parental and irinotecan-resistant cells, protein-protein interactions (PPIs), gene ontologies (GOs) and pathway analysis were performed to identify the overall biological changes. The most common DEGs in the PPIs, GOs and pathways were identified and were validated clinically by their ability to predict overall survival and disease free survival. The gene-gene expression correlation and gene-resistance correlation was also evaluated in CRC patients using The Cancer Genomic Atlas data (TCGA). The 135 DEGs were identified of which 36 were upregulated and 99 were down regulated. After mapping the PPI networks, the GOs and the pathways, nine genes (GNAS, PRKACB, MECOM, PLA2G4C, BMP6, BDNF, DLG4, FGF2 and FGF9) were found to be commonly enriched. Signal transduction was the most significant GO and MAPK pathway was the most significant pathway. The five genes (FGF2, FGF9, PRKACB, MECOM and PLA2G4C) in the MAPK pathway were all contained in the signal transduction and the levels of those genes were upregulated. The FGF2, FGF9 and MECOM expression were highly associated with CRC patients’ survival rate but not PRKACB and PLA2G4C. In addition, FGF9 was also associated with irinotecan resistance and poor disease free survival. FGF2, FGF9 and PRKACB were positively correlated with each other while MECOM correlated positively with FGF9 and PLA2G4C, and correlated negatively with FGF2 and PRKACB after doing gene-gene expression correlation. Targeting the MAPK signal transduction pathway through the targeting of the FGF2, FGF9, MECOM, PLA2G4C and PRKACB might increase tumor responsiveness to irinotecan treatment.
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