Mathematicians from the Korea Advanced Institute of Science and Technology (KAIST) and Pohang University of Science and Technology (POSTECH) say they have identified a way to prevent cancer cells from escaping treatment by controlling random fluctuations in cell behavior, a breakthrough that could significantly improve the effectiveness of future therapies. The study was published in Nature Communications.
The new model allows scientists to govern activity at the single-cell level, rather than just managing the average behavior of a group.
This framework addresses a critical issue in medicine: how “outlier” cells evade therapy to repopulate a tumor or restart an infection even after potent drug treatments.
Protein in cells creates fluctuations known as biological noise
Cells, even those with identical genes, do not behave as clones. The amount of protein within them varies randomly, creating a spectrum of activity known as biological noise.
Until now, genetic circuit technologies could only regulate the average protein levels of a cell population, leaving individual variations unchecked. The research team compared the problem to a shower with a broken regulator.
“Even if the average water temperature is set to 40°C (104°F), a normal shower is impossible if the water alternates between scalding and icy,” the team explained in a statement. In a medical context, this fluctuation can be deadly. While a drug might work on the “average” cell, the outliers, those in the “scalding” or “icy” zones of protein production, often survive to reproduce.
A Dual Mechanism Solves the Cellular Noise Puzzle
To stabilize these fluctuations, the team, led by Professors Jae Kyoung Kim and Byung-Kwan Cho of KAIST and Professor Jinsu Kim of POSTECH, devised a dual-mechanism system that acts like a thermostat for cells.
The system works through two simplified steps. First, the model utilizes a reaction where molecules bind together in pairs. This acts as a biological sensor, detecting minute fluctuations in the cell’s state. Second, it integrates a degradation principle that triggers the immediate breakdown of proteins if they are overproduced.
The result is a system of “Noise Robust Perfect Adaptation.” Theoretically, this suppresses cell-to-cell deviation to the absolute minimum level of randomness achievable in biological systems.
To verify the model, researchers applied it virtually to DNA
To verify the model’s viability, the researchers applied it virtually to the DNA repair system of E. coli bacteria. In a standard system, protein levels vary so significantly that approximately 20% of the cells fail to repair their DNA and die. However, when the team applied their noise controller model to unify protein levels, the mortality rate dropped to 7%.
“The significance lies in bringing cellular noise, which was previously dismissed as luck or coincidence in biological phenomena, into the realm of controllable factors through mathematical design,” said Professor Jae Kyoung Kim.
Researchers believe that by solving the cellular noise puzzle, cancer treatment resistance and the development of high-efficiency smart microorganisms can finally be addressed, allowing doctors to target exceptions rather than just the average.
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