Characterising the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER
Proliferation is a key hallmark of cancer, but whether it differs between evolutionarily distinct clones co-existing within a tumour is unknown. We introduce the SPRINTER algorithm which uses single-cell whole-genome DNA sequencing (scDNA-seq) data to enable accurate identification and clone assignment of S and G2 phase cells, as assessed by generating accurate ground truth data. Applied to a newly generated longitudinal, primary-metastasis matched dataset of 14,994 non-small cell lung cancer (NSCLC) cells, SPRINTER revealed widespread clone proliferation heterogeneity, orthogonally supported by Ki-67 pathology, nuclei imaging, and clinical imaging. We further demonstrated that high proliferation clones have increased metastatic seeding potential, increased circulating tumour DNA (ctDNA) shedding, and clone-specific altered replication timing (ART) in proliferation- or metastasis-related genes associated with expression changes. On previous datasets comprising 61,914 breast and ovarian cancer cells, SPRINTER revealed increased single-cell rates of different genomic variants and enrichment of proliferation-related gene amplifications in high proliferation clones.