{"title":"沉默肺腺癌细胞核定位胰岛素受体的基因敲除方法:生物信息学方法","authors":"Qiu Ren, Hui Ma, Lingling Wang, Jiayu Qin, Miao Tian, Wei Zhang","doi":"10.2174/0113892029298721240627095839","DOIUrl":null,"url":null,"abstract":"Background: Lung adenocarcinoma, the predominant subtype of lung cancer, presents a significant challenge to public health due to its notably low five-year survival rate. Recent epidemiological data highlights a concerning trend: patients with pulmonary adenocarcinoma and comorbid diabetes exhibit substantially elevated mortality rates compared to those without diabetes, suggesting a potential link between hyperinsulinemia in diabetic individuals and accelerated progression of pulmonary adenocarcinoma. Insulin Receptor (IR) is a tyrosine-protein kinase on the cell surface, and its over-expression is considered the pathological hallmark of hyperinsulinemia in various cancer cell types. Research indicates that IR can translocate to the nucleus of lung adenocarcinoma cells to promote their proliferation, but its precise molecular targets remain unclear. This study aims to silence IRs in lung adenocarcinoma cells and identify key genes within the ERK pathway that may serve as potential molecular targets for intervention. Methods: Gene expression data from lung adenocarcinoma and para cancer tissues were retrieved from the Gene Expression Omnibus (GEO) database and assessed through \"pheatmap\", GO annotation, KEGG analysis, R calculations, Cytoscape mapping, and Hub gene screening. Significant genes were visualized using the ggplot2 tool to compare expression patterns between the two groups. Additionally, survival analysis was performed using the R \"survminer\" and \"survival\" packages, along with the R \"pathview\" package for pathway visualization. Marker genes were identified and linked to relevant signaling pathways. Validation was conducted utilizing real-time quantitative polymerase chain reaction and immunoblotting assays in an A549 lung cancer cell model to determine the roles of these marker genes in associated signaling cascades. Results: The study examined 58 lung adenocarcinoma samples and paired para-neoplastic tissues. Analysis of the GSE32863 dataset from GEO revealed 1040 differentially expressed genes, with 421 up-regulated and 619 down-regulated. Visualization of these differences identified 172 significant alterations, comprising 141 up-regulated and 31 down-regulated genes. Functional enrichment analysis using Gene Ontology (GO) revealed 56 molecular functions, 77 cellular components, and 816 biological processes. KEGG analysis identified 17 strongly enriched functions, including cytokine interactions and tumor necrosis factor signaling. Moreover, the ERK signaling pathway was associated with four Hub genes (FGFR4, ANGPT1, TEK, and IL1B) in cellular biological processes. Further validation demonstrated a positive correlation between IL-1B expression in the ERK signaling pathway and lung cancer through real-time fluorescence quantitative enzyme- linked reaction with immunoblotting assays. Conclusion: In IR-silenced lung adenocarcinoma, the expression of the IL-1B gene exhibited a positive correlation with the ERK signaling pathway.","PeriodicalId":10803,"journal":{"name":"Current Genomics","volume":"21 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gene-Knockdown Methods for Silencing Nuclear-Localized Insulin Receptors in Lung Adenocarcinoma Cells: A Bioinformatics Approach\",\"authors\":\"Qiu Ren, Hui Ma, Lingling Wang, Jiayu Qin, Miao Tian, Wei Zhang\",\"doi\":\"10.2174/0113892029298721240627095839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Lung adenocarcinoma, the predominant subtype of lung cancer, presents a significant challenge to public health due to its notably low five-year survival rate. Recent epidemiological data highlights a concerning trend: patients with pulmonary adenocarcinoma and comorbid diabetes exhibit substantially elevated mortality rates compared to those without diabetes, suggesting a potential link between hyperinsulinemia in diabetic individuals and accelerated progression of pulmonary adenocarcinoma. Insulin Receptor (IR) is a tyrosine-protein kinase on the cell surface, and its over-expression is considered the pathological hallmark of hyperinsulinemia in various cancer cell types. Research indicates that IR can translocate to the nucleus of lung adenocarcinoma cells to promote their proliferation, but its precise molecular targets remain unclear. This study aims to silence IRs in lung adenocarcinoma cells and identify key genes within the ERK pathway that may serve as potential molecular targets for intervention. Methods: Gene expression data from lung adenocarcinoma and para cancer tissues were retrieved from the Gene Expression Omnibus (GEO) database and assessed through \\\"pheatmap\\\", GO annotation, KEGG analysis, R calculations, Cytoscape mapping, and Hub gene screening. Significant genes were visualized using the ggplot2 tool to compare expression patterns between the two groups. Additionally, survival analysis was performed using the R \\\"survminer\\\" and \\\"survival\\\" packages, along with the R \\\"pathview\\\" package for pathway visualization. Marker genes were identified and linked to relevant signaling pathways. Validation was conducted utilizing real-time quantitative polymerase chain reaction and immunoblotting assays in an A549 lung cancer cell model to determine the roles of these marker genes in associated signaling cascades. Results: The study examined 58 lung adenocarcinoma samples and paired para-neoplastic tissues. Analysis of the GSE32863 dataset from GEO revealed 1040 differentially expressed genes, with 421 up-regulated and 619 down-regulated. Visualization of these differences identified 172 significant alterations, comprising 141 up-regulated and 31 down-regulated genes. Functional enrichment analysis using Gene Ontology (GO) revealed 56 molecular functions, 77 cellular components, and 816 biological processes. KEGG analysis identified 17 strongly enriched functions, including cytokine interactions and tumor necrosis factor signaling. Moreover, the ERK signaling pathway was associated with four Hub genes (FGFR4, ANGPT1, TEK, and IL1B) in cellular biological processes. Further validation demonstrated a positive correlation between IL-1B expression in the ERK signaling pathway and lung cancer through real-time fluorescence quantitative enzyme- linked reaction with immunoblotting assays. Conclusion: In IR-silenced lung adenocarcinoma, the expression of the IL-1B gene exhibited a positive correlation with the ERK signaling pathway.\",\"PeriodicalId\":10803,\"journal\":{\"name\":\"Current Genomics\",\"volume\":\"21 1\",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Genomics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.2174/0113892029298721240627095839\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Genomics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.2174/0113892029298721240627095839","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Gene-Knockdown Methods for Silencing Nuclear-Localized Insulin Receptors in Lung Adenocarcinoma Cells: A Bioinformatics Approach
Background: Lung adenocarcinoma, the predominant subtype of lung cancer, presents a significant challenge to public health due to its notably low five-year survival rate. Recent epidemiological data highlights a concerning trend: patients with pulmonary adenocarcinoma and comorbid diabetes exhibit substantially elevated mortality rates compared to those without diabetes, suggesting a potential link between hyperinsulinemia in diabetic individuals and accelerated progression of pulmonary adenocarcinoma. Insulin Receptor (IR) is a tyrosine-protein kinase on the cell surface, and its over-expression is considered the pathological hallmark of hyperinsulinemia in various cancer cell types. Research indicates that IR can translocate to the nucleus of lung adenocarcinoma cells to promote their proliferation, but its precise molecular targets remain unclear. This study aims to silence IRs in lung adenocarcinoma cells and identify key genes within the ERK pathway that may serve as potential molecular targets for intervention. Methods: Gene expression data from lung adenocarcinoma and para cancer tissues were retrieved from the Gene Expression Omnibus (GEO) database and assessed through "pheatmap", GO annotation, KEGG analysis, R calculations, Cytoscape mapping, and Hub gene screening. Significant genes were visualized using the ggplot2 tool to compare expression patterns between the two groups. Additionally, survival analysis was performed using the R "survminer" and "survival" packages, along with the R "pathview" package for pathway visualization. Marker genes were identified and linked to relevant signaling pathways. Validation was conducted utilizing real-time quantitative polymerase chain reaction and immunoblotting assays in an A549 lung cancer cell model to determine the roles of these marker genes in associated signaling cascades. Results: The study examined 58 lung adenocarcinoma samples and paired para-neoplastic tissues. Analysis of the GSE32863 dataset from GEO revealed 1040 differentially expressed genes, with 421 up-regulated and 619 down-regulated. Visualization of these differences identified 172 significant alterations, comprising 141 up-regulated and 31 down-regulated genes. Functional enrichment analysis using Gene Ontology (GO) revealed 56 molecular functions, 77 cellular components, and 816 biological processes. KEGG analysis identified 17 strongly enriched functions, including cytokine interactions and tumor necrosis factor signaling. Moreover, the ERK signaling pathway was associated with four Hub genes (FGFR4, ANGPT1, TEK, and IL1B) in cellular biological processes. Further validation demonstrated a positive correlation between IL-1B expression in the ERK signaling pathway and lung cancer through real-time fluorescence quantitative enzyme- linked reaction with immunoblotting assays. Conclusion: In IR-silenced lung adenocarcinoma, the expression of the IL-1B gene exhibited a positive correlation with the ERK signaling pathway.
期刊介绍:
Current Genomics is a peer-reviewed journal that provides essential reading about the latest and most important developments in genome science and related fields of research. Systems biology, systems modeling, machine learning, network inference, bioinformatics, computational biology, epigenetics, single cell genomics, extracellular vesicles, quantitative biology, and synthetic biology for the study of evolution, development, maintenance, aging and that of human health, human diseases, clinical genomics and precision medicine are topics of particular interest. The journal covers plant genomics. The journal will not consider articles dealing with breeding and livestock.
Current Genomics publishes three types of articles including:
i) Research papers from internationally-recognized experts reporting on new and original data generated at the genome scale level. Position papers dealing with new or challenging methodological approaches, whether experimental or mathematical, are greatly welcome in this section.
ii) Authoritative and comprehensive full-length or mini reviews from widely recognized experts, covering the latest developments in genome science and related fields of research such as systems biology, statistics and machine learning, quantitative biology, and precision medicine. Proposals for mini-hot topics (2-3 review papers) and full hot topics (6-8 review papers) guest edited by internationally-recognized experts are welcome in this section. Hot topic proposals should not contain original data and they should contain articles originating from at least 2 different countries.
iii) Opinion papers from internationally recognized experts addressing contemporary questions and issues in the field of genome science and systems biology and basic and clinical research practices.