Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer.

ABSTRACT: In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence

SUBMITTER: Tamez-Pena JG 

PROVIDER: S-EPMC5875760 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature