Abstract
Breast cancer is a common cancer worldwide. Hyperplastic enlarged lobular units (HELUs) are common changes in the breasts of adult women. HELUs may be closely related to the occurrence and development of breast cancer. In this study, genes that are commonly contained in the expression profiles of the genomes of the two diseases and have significant differences in expression before and after the respective diseases were identified. Various enrichment analyses were performed according to the expression levels of these differentially expressed genes. Furthermore, LASSO regression analysis was performed on the differentially expressed genes to identify genes significantly related to survival. The optimal risk model for the survival of patients with breast cancer was established, and the accuracy of the model was verified on multiple data sets. A gene combination containing 17 genes was ultimately determined to be an independent prognostic factor. Kaplan‒Meier survival analysis demonstrated the good performance of this risk model. The study found that Shared Gene Signatures and Biological Mechanisms in Hyperplastic Enlarged Lobular Units and Breast Cancer, screened 17 important Shared Gene Signatures of Hyperplastic Enlarged Lobular Units which are closely related to the survival of breast cancer patients through machine learning, and established a prognosis model with high-accuracy, which is worthy of further exploration.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call