Senescent Cells in Growing Tumors: Population Dynamics and Cancer Stem Cells

TL;DR

This paper models tumor growth considering senescent cells and cancer stem cells, showing that senescence is reversible and highlighting the importance of targeting cancer stem cells for effective therapy.

Contribution

It introduces a mathematical framework for tumor cell population dynamics incorporating senescence and cancer stem cells, supported by experimental validation in melanoma cells.

Findings

Senescence is a reversible process controlled by survivin.

Hierarchical cancer model aligns with experimental data.

Targeting senescence alone may not be effective against cancer.

Abstract

Tumors are defined by their intense proliferation, but sometimes cancer cells turn senescent and stop replicating. In the stochastic cancer model in which all cells are tumorigenic, senescence is seen as the result of random mutations, suggesting that it could represent a barrier to tumor growth. In the hierarchical cancer model a subset of the cells, the cancer stem cells, divide indefinitely while other cells eventually turn senescent. Here we formulate cancer growth in mathematical terms and obtain predictions for the evolution of senescence. We perform experiments in human melanoma cells which are compatible with the hierarchical model and show that senescence is a reversible process controlled by survivin. We conclude that enhancing senescence is unlikely to provide a useful therapeutic strategy to fight cancer, unless the cancer stem cells are specifically targeted