title: Single-molecule genomic data delineate patient-specific tumor profiles and cancer stem cell organization.
abstract: Substantial evidence supports the concept that cancers are organized in a cellular hierarchy with cancer stem cells (CSC) at the apex. To date, the primary evidence for CSCs derives from transplantation assays, which have known limitations. In particular, they are unable to report on the fate of cells within the original human tumor. Because of the difficulty in measuring tumor characteristics in patients, cellular organization and other aspects of cancer dynamics have not been quantified directly, although they likely play a fundamental role in tumor progression and therapy response. As such, new approaches to study CSCs in patient-derived tumor specimens are needed. In this study, we exploited ultradeep single-molecule genomic data derived from multiple microdissected colorectal cancer glands per tumor, along with a novel quantitative approach to measure tumor characteristics, define patient-specific tumor profiles, and infer tumor ancestral trees. We show that each cancer is unique in terms of its cellular organization, molecular heterogeneity, time from malignant transformation, and rate of mutation and apoptosis. Importantly, we estimate CSC fractions between 0.5% and 4%, indicative of a hierarchical organization responsible for long-lived CSC lineages, with variable rates of symmetric cell division. We also observed extensive molecular heterogeneity, both between and within individual cancer glands, suggesting a complex hierarchy of mitotic clones. Our framework enables the measurement of clinically relevant patient-specific characteristics in vivo, providing insight into the cellular organization and dynamics of tumor growth, with implications for personalized patient care.
authors.affiliation: Department of Oncology, University of Cambridge, UK.
authors.forename: Andrea
authors.initials: A
authors.lastname: Sottoriva
authors.forename: Inmaculada
authors.initials: I
authors.lastname: Spiteri
authors.forename: Darryl
authors.initials: D
authors.lastname: Shibata
authors.forename: Christina
authors.initials: C
authors.lastname: Curtis
authors.forename: Simon
authors.initials: S
authors.lastname: Tavaré
mesh_terms: D000328:Adult; D000369:Aged, 80 and over; D019070:Cell Lineage; D002471:Cell Transformation, Neoplastic / Q000473:pathology; D015179:Colorectal Neoplasms / Q000235:genetics* / Q000473:pathology*; D019295:Computational Biology; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D042282:Microdissection; D008875:Middle Aged; D014411:Neoplastic Stem Cells / Q000378:metabolism* / Q000473:pathology*; D057285:Precision Medicine; D059467:Transcriptome