Breast cancer is the most common cancer among women, and the second leading cause of cancer mortality in females in the U.S., with 300,000 new diagnoses and 41,000 fatalities annually. Recently, the dysfunction of a new class of gene expression regulators, named microRNAs (miRNAs), was linked to breast cancer initiation, progression and metastasis. miRNAs are short non-coding RNAs that bind to complementary sequences in the 3' UnTranslated Regions (3'UTRs) in the cytoplasm and repress gene expression. Based on bioinformatic analysis each miRNA is predicted to control a network of gene products, such that hundreds of transcripts are likely to be regulated by a single miRNA. The pairing with target 3'UTRs does not require a perfect match between the sequences. Since these elements are degenerate and small, they are generally difficult to detect, thus the vast majority of cancer relevant miRNA targets are still unknown. To overcome these gaps in our knowledge, we have developed an unbiased high-throughput screening method named 3'LIFE assay (Luminescence-based Identification of Functional Elements in 3'UTRs). 3'LIFE systematically maps miRNA targets in 3'UTRs with an unprecedented scale, allowing us to study the dynamics of genetic networks triggered by miRNAs during the initiation and the progression of breast cancer. We will use the 3'LIFE assay to detect miRNA targets in a pilot library composed of 1,880 3'UTRs, and probe two breast cancer relevant miRNAs: let-7c and miR-10b. We will map their network of interaction and will use their binding requirements in order to extend the targets to the entire human transcriptome. We will then validate the targets in vivo and compare our results to the transcriptome and miRNA changes in matched normal and early stage breast cancer biopsies using the human mammary conditionally reprogrammed cell (HMCRC) system. Our approach 1) pioneers an innovative method to detect miRNA:3'UTR interactions, 2) will detect the genetic network controlled by two breast cancer-relevant miRNAs, 3) will pinpoint tumor-specific miRNA and transcriptome changes of early stage primary breast cancers, and 4) will discover biomarkers and potential drug targets for early breast cancer detection and screening.