PROJECT 2 SUMMARY Exacerbating replication stress is a powerful means to kill cancer cells through mitotic catastrophe due to intolerable levels of DNA replication-associated lesions and DNA breaks. Replication stress is a hallmark of SCLC due to several intrinsic factors, including the loss of tumor suppressors p53 and RB1 in nearly 100% of SCLC. As a consequence of replication stress, constitutive activation of the replication stress response (RSR) pathway(s) is a critical measure to counterbalance cancer cell survival and genomic instability in SCLC. In dealing with high levels of endogenous and/or exogenous replication stress, we hypothesize that SCLC cells have acquired an intricate genome-wide protective mechanism to counteract high levels of replication stress. However, the molecular details and signaling pathways that mediate replication stress tolerance in SCLC cells remains ill-defined, especially in conditions leading to relapsed SCLC. In Project 2, we will address this knowledge gap with the following specific Aims: in Aim 1, we will characterize the RSR pathway(s) that enable replication stress tolerance in SCLC cells. In Aim 2, we will determine how RSR pathways regulate chemo-resistance in SCLC models. Defining the unique therapeutic vulnerabilities of these SCLC subtypes and how they can overcome chemotherapy resistance should help to focus and accelerate therapeutics research, leading to rationally- targeted approaches that may ultimately improve clinical outcomes for patients with this disease. The research work will be highly coordinated within the Program Project with the other three Projects and the three Cores. Our combined diverse approaches include molecular biology, functional genomics, and cell biology. We will employ mutants of different RSR proteins and initiate experiments based on results shared with projects 1, 3, and 4, which will be constantly monitored with feedback via Core A. SCLC cell lines and PDX models will be supported by Core B, and advanced imaging platform and computational analysis will be supported by Core C.