High-density sampling reveals volume growth in human tumours
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- dc.contributor.author Angaji, Arman
- dc.contributor.author Owusu, Michel
- dc.contributor.author Velling, Christoph
- dc.contributor.author Dick, Nicola
- dc.contributor.author Weghorn, Donate
- dc.contributor.author Berg, Johannes
- dc.date.accessioned 2025-02-07T08:08:28Z
- dc.date.available 2025-02-07T08:08:28Z
- dc.date.issued 2024
- dc.description.abstract In growing cell populations such as tumours, mutations can serve as markers that allow tracking the past evolution from current samples. The genomic analyses of bulk samples and samples from multiple regions have shed light on the evolutionary forces acting on tumours. However, little is known empirically on the spatio-temporal dynamics of tumour evolution. Here, we leverage published data from resected hepatocellular carcinomas, each with several hundred samples taken in two and three dimensions. Using spatial metrics of evolution, we find that tumour cells grow predominantly uniformly within the tumour volume instead of at the surface. We determine how mutations and cells are dispersed throughout the tumour and how cell death contributes to the overall tumour growth. Our methods shed light on the early evolution of tumours in vivo and can be applied to high-resolution data in the emerging field of spatial biology.
- dc.description.sponsorship This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) grant SFB1310/2 - 325931972. We acknowledge support of the Spanish Ministry of Science and Innovation through the Centro de Excelencia Severo Ochoa (CEX2020-001049-S, MCIN/AEI /10.13039/501100011033), and the Generalitat de Catalunya through the CERCA programme. We also acknowledge funding by the Spanish Ministry of Science and Innovation through grants PGC2018-100941-A-I00 and PID2021-128976NB-I00. This work was also partially funded by the FWF Austrian Science Fund (Erwin-Schrödinger postdoctoral fellowship, J4366). We thank Xuemei Lu and Chung-I Wu for discussions on the data sets (Li et al., 2022) and (Ling et al., 2015), respectively, and Martin Peifer and Michael Lässig for discussions. Many thanks to Alison Feder and Nicola Müller for discussions on their SDevo algorithm.
- dc.format.mimetype application/pdf
- dc.identifier.citation Angaji A, Owusu M, Velling C, Dick N, Weghorn D, Berg J. High-density sampling reveals volume growth in human tumours. Elife. 2024 Nov 26;13:RP95338. DOI: 10.7554/eLife.95338
- dc.identifier.doi http://dx.doi.org/10.7554/eLife.95338
- dc.identifier.issn 2050-084X
- dc.identifier.uri http://hdl.handle.net/10230/69522
- dc.language.iso eng
- dc.publisher eLife
- dc.relation.ispartof Elife. 2024 Nov 26;13:RP95338
- dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/CEX2020-001049-S
- dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PGC2018-100941-A-I00
- dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/PID2021-128976NB-I00
- dc.rights © 2024, Angaji et al. This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword Cancer biology
- dc.subject.keyword Evolutionary biology
- dc.subject.keyword Human
- dc.subject.keyword Multi-region tumour samples
- dc.subject.keyword Spatial genomics
- dc.subject.keyword Tumour samples
- dc.title High-density sampling reveals volume growth in human tumours
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion