{"title":"非小细胞肺癌(NSCLC)铂基化疗预测性生物标志物的分子谱","authors":"NiloofarTaleghani Seyedabadi , Sara YousefZadeh Shoushtari , Asma Soofi , Javad Arabpour , Zinat Shams , Homa Akhavan , Saied Hosseini-Asl","doi":"10.1016/j.mgene.2021.100993","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Non-small cell lung cancer (NSCLC) is the principal subtype of lung cancer. Among all therapeutic options, platinum-based chemotherapy agents, especially Cisplatin<span>, are still commonly used treatment for NSCLC patients. However, developing chemoresistance in NSCLC cells often gives rise to chemotherapy failure. Therefore, more studies are required to shed light on gene interaction and cellular pathways involved in initiating and developing resistance to platinum-based chemotherapy in NSCLC. Hence, it is urgent to find the key genes, microRNA (miRNAs), and potential molecular mechanisms implicated in chemoresistance and present markers to predict response to platinum-based chemotherapy in NSCLC patients.</span></p></div><div><h3>Methods</h3><p>The microarray datasets GSE6410, GSE7035, GSE14814, GSE26704, GSE73302 were downloaded from the Gene Expression Omnibus (GEO) database and were analyzed using R software. Functional and pathway enrichment analyses were performed using the Enrich R site. Then, the protein-protein interaction (PPI) network and hub genes<span> were obtained using the Cytoscape software. Further, the miRSystem database was performed to predict the miRNAs regulating the hub genes. Moreover, Cytoscape software and the CytoHubba plugin were used to construct the miRNA-target interaction network and hub modules. Finally, the Kaplan–Meier curve was used to demonstrate the survival curves and assess the association of the genes signature with clinical outcomes.</span></p></div><div><h3>Results</h3><p><span>A total of 142 differentially expressed genes (DEGs) were found. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses present the p53 </span>signaling pathway as the most significant pathway.</p><p><span>Besides, from the top ten terms obtained of Biological Process<span>, Molecular Function, and Cellular Component, the first ones, including cholesterol biosynthetic process, the extrinsic component of external side of plasma membrane, cytokine activity, were selected respectively. Based on the PPI network, the ten nodes with the highest degree were screened as hub genes. In addition, from the miRNA–target regulatory network in Cytoscape, ten hub nodes were found. Ultimately, according to Kaplan–Meier curve, BTG2 and TP53I3 with </span></span><em>p</em>-value <0.05 were associated with a better prognosis.</p></div><div><h3>Conclusions</h3><p>In the present study, DEGs, candidate miRNAs, and underlying mechanisms involved in chemoresistance were identified to suggest potential biomarkers to provide new clues for the prediction of response to platinum-based chemotherapy.</p></div>","PeriodicalId":38190,"journal":{"name":"Meta Gene","volume":"31 ","pages":"Article 100993"},"PeriodicalIF":0.8000,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Molecular profiles of predictive biomarkers for platinum-based chemotherapy in Non-Small Cell Lung Cancer (NSCLC)\",\"authors\":\"NiloofarTaleghani Seyedabadi , Sara YousefZadeh Shoushtari , Asma Soofi , Javad Arabpour , Zinat Shams , Homa Akhavan , Saied Hosseini-Asl\",\"doi\":\"10.1016/j.mgene.2021.100993\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Non-small cell lung cancer (NSCLC) is the principal subtype of lung cancer. Among all therapeutic options, platinum-based chemotherapy agents, especially Cisplatin<span>, are still commonly used treatment for NSCLC patients. However, developing chemoresistance in NSCLC cells often gives rise to chemotherapy failure. Therefore, more studies are required to shed light on gene interaction and cellular pathways involved in initiating and developing resistance to platinum-based chemotherapy in NSCLC. Hence, it is urgent to find the key genes, microRNA (miRNAs), and potential molecular mechanisms implicated in chemoresistance and present markers to predict response to platinum-based chemotherapy in NSCLC patients.</span></p></div><div><h3>Methods</h3><p>The microarray datasets GSE6410, GSE7035, GSE14814, GSE26704, GSE73302 were downloaded from the Gene Expression Omnibus (GEO) database and were analyzed using R software. Functional and pathway enrichment analyses were performed using the Enrich R site. Then, the protein-protein interaction (PPI) network and hub genes<span> were obtained using the Cytoscape software. Further, the miRSystem database was performed to predict the miRNAs regulating the hub genes. Moreover, Cytoscape software and the CytoHubba plugin were used to construct the miRNA-target interaction network and hub modules. Finally, the Kaplan–Meier curve was used to demonstrate the survival curves and assess the association of the genes signature with clinical outcomes.</span></p></div><div><h3>Results</h3><p><span>A total of 142 differentially expressed genes (DEGs) were found. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses present the p53 </span>signaling pathway as the most significant pathway.</p><p><span>Besides, from the top ten terms obtained of Biological Process<span>, Molecular Function, and Cellular Component, the first ones, including cholesterol biosynthetic process, the extrinsic component of external side of plasma membrane, cytokine activity, were selected respectively. Based on the PPI network, the ten nodes with the highest degree were screened as hub genes. In addition, from the miRNA–target regulatory network in Cytoscape, ten hub nodes were found. Ultimately, according to Kaplan–Meier curve, BTG2 and TP53I3 with </span></span><em>p</em>-value <0.05 were associated with a better prognosis.</p></div><div><h3>Conclusions</h3><p>In the present study, DEGs, candidate miRNAs, and underlying mechanisms involved in chemoresistance were identified to suggest potential biomarkers to provide new clues for the prediction of response to platinum-based chemotherapy.</p></div>\",\"PeriodicalId\":38190,\"journal\":{\"name\":\"Meta Gene\",\"volume\":\"31 \",\"pages\":\"Article 100993\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Meta Gene\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214540021001444\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Meta Gene","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214540021001444","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 2
摘要
非小细胞肺癌(NSCLC)是肺癌的主要亚型。在所有的治疗方案中,以铂为基础的化疗药物,尤其是顺铂,仍然是NSCLC患者常用的治疗方法。然而,在NSCLC细胞中产生化疗耐药往往导致化疗失败。因此,需要更多的研究来阐明基因相互作用和细胞通路在非小细胞肺癌铂基化疗的产生和发展中的作用。因此,迫切需要寻找与化疗耐药相关的关键基因、microRNA (miRNAs)和潜在分子机制,以及预测NSCLC患者对铂类化疗反应的标志物。方法从Gene Expression Omnibus (GEO)数据库中下载GSE6410、GSE7035、GSE14814、GSE26704、GSE73302微阵列数据集,使用R软件进行分析。利用富集R位点进行功能和途径富集分析。然后利用Cytoscape软件获得蛋白-蛋白相互作用(PPI)网络和枢纽基因。此外,使用miRSystem数据库预测调节枢纽基因的mirna。利用Cytoscape软件和CytoHubba插件构建mirna -靶点相互作用网络和集线器模块。最后,使用Kaplan-Meier曲线来展示生存曲线,并评估基因特征与临床结果的关联。结果共发现142个差异表达基因(DEGs)。基因本体(GO)和京都基因与基因组百科全书(KEGG)途径富集分析表明p53信号通路是最重要的途径。此外,从“生物过程”、“分子功能”和“细胞成分”三个方面获得的前十位术语中,分别选择了胆固醇生物合成过程、质膜外侧外在成分、细胞因子活性等前十位术语。基于PPI网络,筛选出10个度最高的节点作为枢纽基因。此外,在Cytoscape的mirna靶调控网络中,发现了10个枢纽节点。最终,根据Kaplan-Meier曲线,p值为<0.05的BTG2和TP53I3与较好的预后相关。结论本研究确定了deg、候选mirna和参与化疗耐药的潜在机制,为预测铂类化疗的反应提供了潜在的生物标志物。
Molecular profiles of predictive biomarkers for platinum-based chemotherapy in Non-Small Cell Lung Cancer (NSCLC)
Background
Non-small cell lung cancer (NSCLC) is the principal subtype of lung cancer. Among all therapeutic options, platinum-based chemotherapy agents, especially Cisplatin, are still commonly used treatment for NSCLC patients. However, developing chemoresistance in NSCLC cells often gives rise to chemotherapy failure. Therefore, more studies are required to shed light on gene interaction and cellular pathways involved in initiating and developing resistance to platinum-based chemotherapy in NSCLC. Hence, it is urgent to find the key genes, microRNA (miRNAs), and potential molecular mechanisms implicated in chemoresistance and present markers to predict response to platinum-based chemotherapy in NSCLC patients.
Methods
The microarray datasets GSE6410, GSE7035, GSE14814, GSE26704, GSE73302 were downloaded from the Gene Expression Omnibus (GEO) database and were analyzed using R software. Functional and pathway enrichment analyses were performed using the Enrich R site. Then, the protein-protein interaction (PPI) network and hub genes were obtained using the Cytoscape software. Further, the miRSystem database was performed to predict the miRNAs regulating the hub genes. Moreover, Cytoscape software and the CytoHubba plugin were used to construct the miRNA-target interaction network and hub modules. Finally, the Kaplan–Meier curve was used to demonstrate the survival curves and assess the association of the genes signature with clinical outcomes.
Results
A total of 142 differentially expressed genes (DEGs) were found. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses present the p53 signaling pathway as the most significant pathway.
Besides, from the top ten terms obtained of Biological Process, Molecular Function, and Cellular Component, the first ones, including cholesterol biosynthetic process, the extrinsic component of external side of plasma membrane, cytokine activity, were selected respectively. Based on the PPI network, the ten nodes with the highest degree were screened as hub genes. In addition, from the miRNA–target regulatory network in Cytoscape, ten hub nodes were found. Ultimately, according to Kaplan–Meier curve, BTG2 and TP53I3 with p-value <0.05 were associated with a better prognosis.
Conclusions
In the present study, DEGs, candidate miRNAs, and underlying mechanisms involved in chemoresistance were identified to suggest potential biomarkers to provide new clues for the prediction of response to platinum-based chemotherapy.
Meta GeneBiochemistry, Genetics and Molecular Biology-Genetics
CiteScore
1.10
自引率
0.00%
发文量
20
期刊介绍:
Meta Gene publishes meta-analysis, polymorphism and population study papers that are relevant to both human and non-human species. Examples include but are not limited to: (Relevant to human specimens): 1Meta-Analysis Papers - statistical reviews of the published literature of human genetic variation (typically linked to medical conditionals and/or congenital diseases) 2Genome Wide Association Studies (GWAS) - examination of large patient cohorts to identify common genetic factors that influence health and disease 3Human Genetics Papers - original studies describing new data on genetic variation in smaller patient populations 4Genetic Case Reports - short communications describing novel and in formative genetic mutations or chromosomal aberrations (e.g., probands) in very small demographic groups (e.g., family or unique ethnic group). (Relevant to non-human specimens): 1Small Genome Papers - Analysis of genetic variation in organelle genomes (e.g., mitochondrial DNA) 2Microbiota Papers - Analysis of microbiological variation through analysis of DNA sequencing in different biological environments 3Ecological Diversity Papers - Geographical distribution of genetic diversity of zoological or botanical species.