Lucas Olivia, Ward Sophia, Zaidi Rija, Bunkum Abigail, Frankell Alexander M, Moore David A, Hill Mark S, Liu Wing Kin, Marinelli Daniele, Lim Emilia L, Hessey Sonya, Naceur-Lombardelli Cristina, Rowan Andrew, Purewal-Mann Sukhveer Kaur, Zhai Haoran, Dietzen Michelle, Ding Boyue, Royle Gary, Aparicio Samuel, McGranahan Nicholas, Jamal-Hanjani Mariam, Kanu Nnennaya, Swanton Charles, Zaccaria Simone
Computational Cancer Genomics Research Group, University College London Cancer Institute, London, UK.
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
Nat Genet. 2025 Jan;57(1):103-114. doi: 10.1038/s41588-024-01989-z. Epub 2024 Nov 29.
Proliferation is a key hallmark of cancer, but whether it differs between evolutionarily distinct clones co-existing within a tumor is unknown. We introduce the Single-cell Proliferation Rate Inference in Non-homogeneous Tumors through Evolutionary Routes (SPRINTER) algorithm that uses single-cell whole-genome DNA sequencing 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 cells, SPRINTER revealed widespread clone proliferation heterogeneity, orthogonally supported by Ki-67 staining, nuclei imaging and clinical imaging. We further demonstrated that high-proliferation clones have increased metastatic seeding potential, increased circulating tumor DNA shedding and clone-specific altered replication timing in proliferation- or metastasis-related genes associated with expression changes. Applied to previously generated datasets of 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.
细胞增殖是癌症的一个关键特征，但肿瘤内共存的进化上不同的克隆之间的增殖情况是否存在差异尚不清楚。我们引入了通过进化路径推断非均质肿瘤单细胞增殖率（SPRINTER）算法，该算法使用单细胞全基因组DNA测序数据，通过生成准确的真实数据来准确识别S期和G2期细胞并进行克隆分配。将SPRINTER应用于新生成的包含14994个非小细胞肺癌细胞的纵向、原发-转移匹配数据集时，发现了广泛的克隆增殖异质性，这得到了Ki-67染色、细胞核成像和临床成像的正交支持。我们进一步证明，高增殖克隆具有增加的转移播种潜力、增加的循环肿瘤DNA脱落以及与表达变化相关的增殖或转移相关基因中克隆特异性改变的复制时间。将SPRINTER应用于先前生成的包含61914个乳腺癌和卵巢癌细胞的数据集时，发现不同基因组变体的单细胞率增加，并且在高增殖克隆中增殖相关基因扩增富集。
