摘要
<strong>Objective:</strong><span style="font-family:""><span style="font-family:Verdana;"> Breast Cancer (BC) is characterized by high complexity and heterogeneity, and microRNA (miRNA) is bound up with the occurrence and </span><span style="font-family:Verdana;">development of BC. In this study, we evaluated the prognostic value of</span><span style="font-family:Verdana;"> miR</span><span><span style="font-family:Verdana;">NA in BC. </span><b><span style="font-family:Verdana;">Background:</span></b><span style="font-family:Verdana;"> Breast ductal and lobular cancers are the most </span></span><span style="font-family:Verdana;">common types of Breast Carcinomas (BC) and indicate the high complexity heterogeneity in this disease. Each BC patient has unique morphological and </span><span style="font-family:Verdana;">molecular features. MicroRNAs (miRNAs) play a critical role in human </span><span style="font-family:Verdana;">oncoge</span><span style="font-family:Verdana;">nesis, progression, and prognosis. Our study aimed to identify potential</span><span style="font-family:Verdana;"> prognostic biomarkers of breast ductal and lobular cancers to predict the overall </span><span><span style="font-family:Verdana;">survival outcome. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> All analyzed miRNA sequencing and clinical </span></span><span style="font-family:Verdana;">data were obtained from the Genomic Data Commons Data Porta. edgeR package in R </span><span style="font-family:Verdana;">software was used to analyze the differential miRNA expression profiles</span><span style="font-family:Verdana;">. Com</span><span style="font-family:Verdana;">plete survival information and differentially expressed miRNA expression</span><span style="font-family:Verdana;"> 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 </span><span style="font-family:Verdana;">performed
<strong>Objective:</strong><span style="font-family:""><span style="font-family:Verdana;"> Breast Cancer (BC) is characterized by high complexity and heterogeneity, and microRNA (miRNA) is bound up with the occurrence and </span><span style="font-family:Verdana;">development of BC. In this study, we evaluated the prognostic value of</span><span style="font-family:Verdana;"> miR</span><span><span style="font-family:Verdana;">NA in BC. </span><b><span style="font-family:Verdana;">Background:</span></b><span style="font-family:Verdana;"> Breast ductal and lobular cancers are the most </span></span><span style="font-family:Verdana;">common types of Breast Carcinomas (BC) and indicate the high complexity heterogeneity in this disease. Each BC patient has unique morphological and </span><span style="font-family:Verdana;">molecular features. MicroRNAs (miRNAs) play a critical role in human </span><span style="font-family:Verdana;">oncoge</span><span style="font-family:Verdana;">nesis, progression, and prognosis. Our study aimed to identify potential</span><span style="font-family:Verdana;"> prognostic biomarkers of breast ductal and lobular cancers to predict the overall </span><span><span style="font-family:Verdana;">survival outcome. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> All analyzed miRNA sequencing and clinical </span></span><span style="font-family:Verdana;">data were obtained from the Genomic Data Commons Data Porta. edgeR package in R </span><span style="font-family:Verdana;">software was used to analyze the differential miRNA expression profiles</span><span style="font-family:Verdana;">. Com</span><span style="font-family:Verdana;">plete survival information and differentially expressed miRNA expression</span><span style="font-family:Verdana;"> 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 </span><span style="font-family:Verdana;">performed
