Blood Based Biomarkers of Early Onset Breast Cancer

Abstract : Women with early-onset breast cancer are thought to have a higher contribution of inherited risk than those forming sporadic cancers at later ages. This inherited susceptibility to breast cancer might manifest as differences in gene expression patterns within key oncogenic pathways. While the normal breast is the ideal tissue in which to study this phenomenon, gene expression profiling of blood lymphocytes has been successfully used as a proxy in a variety of diseases including breast cancer. We investigated the gene expression profile of untransformed blood lymphocytes in order to discover gene expression (mRNA and miRNA) signatures which can differentiate BRCA 1/2 negative women with a personal history of early-onset breast cancer and family history of breast cancer (n=51) from asymptomatic aged-matched women without a personal history of cancer or family history of breast cancer (n=50). Using adaboost computer learning algorithm which discretizes the data, and also using logistic elastic net a form of linear regression - we were unable to build a classifier that could accurately differentiate cases from controls, at any level higher than that already available by history-based risk assessment algorithms.