In Silico Approach for the Definition of radiomiRNomic Signatures for Breast Cancer Differential Diagnosis.

ABSTRACT: Personalized medicine relies on the integration and consideration of specific characteristics of the patient, such as tumor phenotypic and genotypic profiling. Radiogenomics aim to integrate phenotypes from tumor imaging data with genomic data to discover genetic mechanisms underlying tumor development and phenotype. We describe a computational approach that correlates phenotype from magnetic resonance imaging (MRI) of breast cancer (BC) lesions with microRNAs (miRNAs), mRNAs, and regulatory networks, developing a radiomiRNomic map. We validated our approach to the relationships between MRI and miRNA expression data derived from BC patients. We obtained 16 radiomic features quantifying the tumor phenotype. We integrated the features with miRNAs regulating a network of pathways specific for

SUBMITTER: Gallivanone F 

PROVIDER: S-EPMC6929037 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature