PROJECT SUMMARY Cancer metastasis, which accounts for 8 million deaths worldwide annually, is a multistep process that includes the emergence of metastatic subclones in primary tumors, dissemination and survival in circulation, seeding and colonization at distant sites. Deciphering the evolutionary dynamics, the spatial context, and the molecular nature of each step during metastasis is critical to understanding this lethal phase of tumor evolution, and to potentially develop effective therapeutic strategies. However, it remains challenging to directly study these events due to their stochastic and rare occurrence over long time frames, diverse interactions within the microenvironment, and transient shifts in cellular plasticity. Among the most highly metastatic and lethal cancer types, small cell lung cancer (SCLC) is a neuroendocrine subtype of lung cancer with a median survival of only 7– 12 months, which has not improved over the past 30 years. Despite its clinical importance, SCLC metastasis remains underexplored due to the paucity of clinical metastatic samples, which raised several fundamental questions: what is the origin and evolutionary dynamics of SCLC metastases? Whether and how does the microenvironment contribute to metastasis? Whether and how key intermediate cell states influence evolutionary fate decisions? Our overarching goal is to elucidate the cell intrinsic and extrinsic mechanisms underlying SCLC metastasis, and ultimately develop a comprehensive, spatiotemporally-resolved roadmap of SCLC metastasis using a genetically engineered mouse model of SCLC. To achieve this goal, we will develop a suite of cutting-edge technologies that will overcome substantial technical hurdles that have thus far precluded progress, and will allow us to establish a comprehensive, spatiotemporally-resolved lineage tracing platform capable of recording the entire course of SCLC metastasis. Specifically, we will 1) map the evolutionary dynamics and trajectories of SCLC metastasis by the generation and analysis of an evolving lineage tracing mouse model of SCLC, 2) dissect the spatial context and cellular composition of the pro-metastatic niche by creating a high resolution spatial- lineage platform, and 3) investigate transient cell state changes during metastasis through signal recording. Our systematic effort will culminate in the generation of a comprehensive blueprint of SCLC metastatic progression. This blueprint will integrate the evolutionary dynamics, the spatial and microenvironmental context, and the molecular features and gene expression dynamics underlying SCLC metastasis, offering significant insights for future functional dissection and therapeutic development. The technical advances and biological discoveries generated here will transform our conceptual understanding of cancer metastasis, create cutting-edge technologies for dissecting the mechanisms of tumor evolution, and potentially reveal novel ways for stage/gene/environment-spec...