The underpinnings of cancer metastasis remain poorly understood, in part due to a lack of tools for probing their emergence at high resolution. Here we present macsGESTALT, an inducible CRISPR-Cas9-based lineage recorder with highly efficient single-cell capture of both transcriptional and phylogenetic information. Applying macsGESTALT to a mouse model of metastatic pancreatic cancer, we recover ∼380,000 CRISPR target sites and reconstruct dissemination of ∼28,000 single cells across multiple metastatic sites. We find that cells occupy a continuum of epithelial-to-mesenchymal transition (EMT) states. Metastatic potential peaks in rare, late-hybrid EMT states, which are aggressively selected from a predominately epithelial ancestral pool. The gene signatures of these late-hybrid EMT states are predictive of reduced survival in both human pancreatic and lung cancer patients, highlighting their relevance to clinical disease progression. Finally, we observe evidence for in vivo propagation of S100 family gene expression across clonally distinct metastatic subpopulations.

癌症转移的基础仍然知之甚少，部分原因是缺乏高分辨率探测其出现的工具。在这里，我们展示了 macsGESTALT，一种基于 CRISPR-Cas9 的诱导型谱系记录仪，能够高效地单细胞捕获转录和系统发育信息。将 macsGESTALT 应用于转移性胰腺癌小鼠模型，我们恢复了约 380,000 个 CRISPR 靶位点，并重建了约 28,000 个单细胞在多个转移位点的分布。我们发现细胞处于上皮-间质转化（EMT）状态的连续体。转移潜能在罕见的晚期混合 EMT 状态中达到峰值，这些状态是从主要上皮祖先库中积极选择的。这些晚期混合 EMT 状态的基因特征可预测人类胰腺癌和肺癌患者的生存率降低，突显其与临床疾病进展的相关性。最后，我们观察到S100家族基因表达在克隆不同的转移亚群中体内传播的证据。