PEtracer, a prime editing-based evolving lineage tracing system, enables accurate phylogenetic reconstruction of tens of thousands of cells through installation of eight balanced, predefined lineage marks that are compatible with both single-cell sequencing and high-resolution spatial transcriptomic imaging, revealing that metastatic tumor growth is driven by spatially organized fitness gradients where cancer cells at the lung-tumor interface achieve heritable high-fitness states through integration of cell-intrinsic gene expression programs (Cldn4, Fgf1/Fgfbp1) with permissive microenvironmental signals.

Charting the spatiotemporal dynamics of cell fate determination in development and disease is a long-standing objective in biology. Here we present the design, development, and extensive validation of PEtracer, a prime editing-based, evolving lineage tracing technology compatible with both single-cell sequencing and multimodal imaging methodologies to jointly profile cell state and lineage in dissociated cells or while preserving cellular context in tissues with high spatial resolution. Using PEtracer coupled with MERFISH spatial transcriptomic profiling in a syngeneic mouse model of tumor metastasis, we reconstruct the growth of individually-seeded tumors in vivo and uncover distinct modules of cell-intrinsic and cell-extrinsic factors that coordinate tumor growth. More generally, PEtracer enables systematic characterization of cell state and lineage relationships in intact tissues over biologically-relevant temporal and spatial scales.