{"title":"基于生物信息学分析的主要MicroRNA基因在乳腺癌中的表达及预后意义","authors":"Qiong Wang, Jiuli Hu, Junwei Liang, Lanfang Liu, Shuoyang Xiao, Rui Wang, Chanchan Hu","doi":"10.4236/abcr.2022.111001","DOIUrl":null,"url":null,"abstract":"Objective: Breast Cancer (BC) is characterized by high complexity and heterogeneity, and microRNA (miRNA) is bound up with the occurrence and development of BC. In this study, we evaluated the prognostic value of miRNA in BC. Background: Breast ductal and lobular cancers are the most common types of Breast Carcinomas (BC) and indicate the high complexity heterogeneity in this disease. Each BC patient has unique morphological and molecular features. MicroRNAs (miRNAs) play a critical role in human oncogenesis, progression, and prognosis. Our study aimed to identify potential prognostic biomarkers of breast ductal and lobular cancers to predict the overall survival outcome. Methods: All analyzed miRNA sequencing and clinical data were obtained from the Genomic Data Commons Data Porta. edgeR package in R software was used to analyze the differential miRNA expression profiles. Complete survival information and differentially expressed miRNA expression were obtained and the Caret package was used for random division of the samples along with their profiles into two groups (training group and test group). We performed univariate Cox regression analyses for miRNAs in the training group. We utilized three different web-based tools to identify the target genes of miRNAs and used the Perl language to evaluate the target genes for miRNA signature. STRING database was used to assess PPIs. Results: A total of 304 differentially expressed miRNAs were identified (213 were upregulated and 91 were downregulated). Among these, nine (hsa-miR-204-5p, by Cox regression analysis and miRNA signature risk score built. And then we performed the model of BC patients for three years survival risk, the AUCs of ROC were 0.804, 0.667, and 0.739 in the training, test, and entire groups, respectively. miRNAs were differentially expressed in tumor-related biological processes and pathways by functional enrichment and bioinformatic analysis. Conclusion: The current study provided novel insights into the mi-RNA-based mRNA network in BC. The nine miRNA and ten hub genes may be independent prognostic signatures for survival prediction in BC patients.","PeriodicalId":67095,"journal":{"name":"乳腺癌(英文)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Expression and Prognostic Significance of Major MicroRNA Genes in Breast Cancer Based on Bioinformatics Analysis\",\"authors\":\"Qiong Wang, Jiuli Hu, Junwei Liang, Lanfang Liu, Shuoyang Xiao, Rui Wang, Chanchan Hu\",\"doi\":\"10.4236/abcr.2022.111001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective: Breast Cancer (BC) is characterized by high complexity and heterogeneity, and microRNA (miRNA) is bound up with the occurrence and development of BC. In this study, we evaluated the prognostic value of miRNA in BC. Background: Breast ductal and lobular cancers are the most common types of Breast Carcinomas (BC) and indicate the high complexity heterogeneity in this disease. Each BC patient has unique morphological and molecular features. MicroRNAs (miRNAs) play a critical role in human oncogenesis, progression, and prognosis. Our study aimed to identify potential prognostic biomarkers of breast ductal and lobular cancers to predict the overall survival outcome. Methods: All analyzed miRNA sequencing and clinical data were obtained from the Genomic Data Commons Data Porta. edgeR package in R software was used to analyze the differential miRNA expression profiles. Complete survival information and differentially expressed miRNA expression were obtained and the Caret package was used for random division of the samples along with their profiles into two groups (training group and test group). We performed univariate Cox regression analyses for miRNAs in the training group. We utilized three different web-based tools to identify the target genes of miRNAs and used the Perl language to evaluate the target genes for miRNA signature. STRING database was used to assess PPIs. Results: A total of 304 differentially expressed miRNAs were identified (213 were upregulated and 91 were downregulated). Among these, nine (hsa-miR-204-5p, by Cox regression analysis and miRNA signature risk score built. And then we performed the model of BC patients for three years survival risk, the AUCs of ROC were 0.804, 0.667, and 0.739 in the training, test, and entire groups, respectively. miRNAs were differentially expressed in tumor-related biological processes and pathways by functional enrichment and bioinformatic analysis. Conclusion: The current study provided novel insights into the mi-RNA-based mRNA network in BC. The nine miRNA and ten hub genes may be independent prognostic signatures for survival prediction in BC patients.\",\"PeriodicalId\":67095,\"journal\":{\"name\":\"乳腺癌(英文)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"乳腺癌(英文)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4236/abcr.2022.111001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"乳腺癌(英文)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/abcr.2022.111001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Expression and Prognostic Significance of Major MicroRNA Genes in Breast Cancer Based on Bioinformatics Analysis
Objective: Breast Cancer (BC) is characterized by high complexity and heterogeneity, and microRNA (miRNA) is bound up with the occurrence and development of BC. In this study, we evaluated the prognostic value of miRNA in BC. Background: Breast ductal and lobular cancers are the most common types of Breast Carcinomas (BC) and indicate the high complexity heterogeneity in this disease. Each BC patient has unique morphological and molecular features. MicroRNAs (miRNAs) play a critical role in human oncogenesis, progression, and prognosis. Our study aimed to identify potential prognostic biomarkers of breast ductal and lobular cancers to predict the overall survival outcome. Methods: All analyzed miRNA sequencing and clinical data were obtained from the Genomic Data Commons Data Porta. edgeR package in R software was used to analyze the differential miRNA expression profiles. Complete survival information and differentially expressed miRNA expression were obtained and the Caret package was used for random division of the samples along with their profiles into two groups (training group and test group). We performed univariate Cox regression analyses for miRNAs in the training group. We utilized three different web-based tools to identify the target genes of miRNAs and used the Perl language to evaluate the target genes for miRNA signature. STRING database was used to assess PPIs. Results: A total of 304 differentially expressed miRNAs were identified (213 were upregulated and 91 were downregulated). Among these, nine (hsa-miR-204-5p, by Cox regression analysis and miRNA signature risk score built. And then we performed the model of BC patients for three years survival risk, the AUCs of ROC were 0.804, 0.667, and 0.739 in the training, test, and entire groups, respectively. miRNAs were differentially expressed in tumor-related biological processes and pathways by functional enrichment and bioinformatic analysis. Conclusion: The current study provided novel insights into the mi-RNA-based mRNA network in BC. The nine miRNA and ten hub genes may be independent prognostic signatures for survival prediction in BC patients.