A FUNCTIONAL MAP OF LNCRNAS IN ADAPTIVE PHENOTYPES OF BREAST CANCER CELLS

In this project, we investigate the contribution of long non-coding RNAs (lncRNAs) in the acquisition of adaptive phenotypes in breast cancer. LncRNAs have multiple regulatory functions that define these transcripts as fine regulators of gene expression, engaging in different oncogenic networks. However, the functional classification of these RNA molecules is still limited. We aim at building a functional map of lncRNAs in the context non-genetic adaptive mechanisms occurring in breast cancer by means of pooled CRISPRinterference (CRISPRi) screenings. We selected 620 lncRNAs for their positive association with models of adaptive responses in breast cancer. Specifically, we evaluated the expression of adaptive response signatures in primary tumors, modeled the chemo-tolerance to the neo-adjuvant drug Paclitaxel and evaluated the inherent plasticity of the MaSC-like population of the HMLE cell line. We designed a CRISPRi library for the simultaneous perturbation of 620 lncRNAs. To precisely map the TSS of candidates lncRNAs, the design of the lentiviral library was aided by NET-Cage data. We tested how the perturbation of lncRNAs modulates the adaptive properties of the TNBC cell line SUM159PT by growing cells in increasingly stringent conditions (2D, 3D, chemo-response, in vivo). In this setting, cells must address different responses to survive. Overall, we could identify 18.8% of genes DROP-OUTs, and 19% of genes DROP-INs in one or multiple screenings. We will broaden the characterization of lncRNAs hits by evaluating the transcriptomic response upon their perturbation. With this work, we outline a sound and reliable approach for identifying lncRNAs that are relevant in cancer and provide new insights into the regulatory roles lncRNAs play in cancer cell plasticity.