Clonal Lineage Tracing with Somatic Delivery of Recordable Barcodes Reveals Migration Histories of Metastatic Prostate Cancer

前列腺癌 谱系(遗传) 生物 癌症 体细胞 癌症研究 计算生物学 基因 遗传学
作者
Ryan N. Serio,Armin Scheben,Billy Lu,Domenic V. Gargiulo,Lucrezia Patruno,Caroline L. Buckholtz,Ryan J. Chaffee,Megan C. Jibilian,Steven G. Persaud,Stephen J. Staklinski,R. P. Hassett,Lise M. Brault,Daniele Ramazzotti,Christopher E. Barbieri,Adam Siepel,Dawid G. Nowak
出处
期刊:Cancer Discovery [American Association for Cancer Research]
卷期号:14 (10): 1990-2009 被引量:3
标识
DOI:10.1158/2159-8290.cd-23-1332
摘要

The patterns by which primary tumors spread to metastatic sites remain poorly understood. Here, we define patterns of metastatic seeding in prostate cancer using a novel injection-based mouse model-EvoCaP (Evolution in Cancer of the Prostate), featuring aggressive metastatic cancer to bone, liver, lungs, and lymph nodes. To define migration histories between primary and metastatic sites, we used our EvoTraceR pipeline to track distinct tumor clones containing recordable barcodes. We detected widespread intratumoral heterogeneity from the primary tumor in metastatic seeding, with few clonal populations instigating most migration. Metastasis-to-metastasis seeding was uncommon, as most cells remained confined within the tissue. Migration patterns in our model were congruent with human prostate cancer seeding topologies. Our findings support the view of metastatic prostate cancer as a systemic disease driven by waves of aggressive clones expanding their niche, infrequently overcoming constraints that otherwise keep them confined in the primary or metastatic site. Significance: Defining the kinetics of prostate cancer metastasis is critical for developing novel therapeutic strategies. This study uses CRISPR/Cas9-based barcoding technology to accurately define tumor clonal patterns and routes of migration in a novel somatically engineered mouse model (EvoCaP) that recapitulates human prostate cancer using an in-house developed analytical pipeline (EvoTraceR).
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