High-density sampling reveals volume growth in human tumours

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.

Authors

Institutions

Publication Details

Journal
eLife
Published
2024-11-26
DOI
https://doi.org/10.7554/elife.95338.3
Citations
2
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.57

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High-density sampling reveals volume growth in human tumours

Christoph Velling, Arman Angaji, Donate Weghorn, Michel Owusu et al.
2 citations
eLife
Cancer Genomics and Diagnostics
0.57
article

High-density sampling reveals volume growth in human tumours

Christoph Velling, Arman Angaji, Donate Weghorn, Michel Owusu, Johannes Berg, Nicola Dick
article en
2 citations

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.

eLifeVol. 13
Universitat Pompeu Fabra (ES), University of Cologne (DE), Centre for Genomic Regulation (ES)
Deutsche Forschungsgemeinschaft, Austrian Science Fund, Generalitat de Catalunya, Ministerio de Ciencia e Innovación
Openalex Percentile: Top 30%
Cancer Genomics and Diagnostics
0.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.