Gompertz Growth With a Shared Carrying Capacity Optimally Simulates Primary and Metastatic Tumor Growth Dynamics

Authors

Pirmin Schlicke
Preethi Korangath
Xiaoxi Pan
Caner Ercan
Kathleen Gabrielson
Lyndsey Werhane
Yinyin Yuan
Sébastien Benzekry
Robert Ivkov
Heiko Enderling

Language

English

Publication Date

4-1-2026

Journal

British Journal of Cancer

DOI

10.1038/s41416-025-03306-9

PMID

41735583

PMCID

PMC13035863

PubMedCentral® Posted Date

2-24-2026

PubMedCentral® Full Text Version

Post-print

Abstract

Background: Cancer is a systemic disease with most deaths attributed to metastatic burden. Primary and metastatic tumors, albeit at different anatomic locations, are interconnected through multiple biological processes. Pre-clinical and clinical observations of growth acceleration of metastases after surgery, or abscopal effects outside the radiation field are widely reported, yet reliably triggering favorable and avoiding unfavorable systemic responses remains an unmet clinical need. Understanding local and systemic tumor interaction dynamics will help guide future treatments.

Methods: We analyze the data of multiple in vivo tumor models. We formalize the systemic interplay of tumors as mathematical differential equation and calibrate parameters for each cell line and mouse type. Using model selection metrics, we identify classic tumor growth models with a novel shared carrying capacity parsimoniously describe the pan-cancer experimental data.

Results: Shared systemic carrying capacity, metastatic spread potential, and metastatic growth rates differ across tested cell lines and mouse strains. Bi-directional concomitant systemic interconnectivity explains the observed metastatic explosion after primary tumor surgery.

Discussion: Future investigations should reproduce this analysis in clinical settings and evaluate whether this shared carrying capacity model could help stratify patients at risk of metastatic disease below clinical detectability and inform strategies to control oligometastatic cancer.

Keywords

Animals, Mice, Humans, Neoplasm Metastasis, Neoplasms, Cell Line, Tumor, Models, Biological, Cell Proliferation, Metastasis, Differential equations, Metastasis, Computational models

Published Open-Access

yes

Recommended Citation

Schlicke, Pirmin; Korangath, Preethi; Pan, Xiaoxi; et al., "Gompertz Growth With a Shared Carrying Capacity Optimally Simulates Primary and Metastatic Tumor Growth Dynamics" (2026). Faculty, Staff and Student Publications. 6823.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/6823