Noisy-threshold control of cell death

TL;DR

This paper presents a quantitative model showing how intracellular variability and a threshold-based control mechanism explain cell death responses, with implications for understanding cancer therapy resistance.

Contribution

It introduces a novel threshold-based control model for cell death that accounts for cellular variability and adaptation, validated with T-cell apoptosis data.

Findings

Model accurately predicts experimental apoptosis data.

Oncogene Bcl-xL influences variability and adaptation in cell death.

Threshold mechanism links noise to cell survival outcomes.

Abstract

Cellular responses to death-promoting stimuli typically proceed through a differentiated multistage process, involving a lag phase, extensive death, and potential adaptation. Deregulation of this chain of events is at the root of many diseases. Improper adaptation is particularly important because it allows cell sub-populations to survive even in the continuous presence of death conditions, which results, among others, in the eventual failure of many targeted anticancer therapies. Here, I show that these typical responses arise naturally from the interplay of intracellular variability with a threshold-based control mechanism that detects cellular changes in addition to just the cellular state itself. Implementation of this mechanism in a quantitative model for T-cell apoptosis, a prototypical example of programmed cell death, captures with exceptional accuracy experimental observations for different expression levels of the oncogene Bcl-xL and directly links adaptation with noise in an ATP threshold below which cells die. These results indicate that oncogenes like Bcl-xL, besides regulating absolute death values, can have a novel role as active controllers of cell-cell variability and the extent of adaptation.