Phenotypic heterogeneity of melanoma cells contributes to drug tolerance, increased metastasis, and immune evasion in patients with progressive disease. However, the dynamics of the co-existence and interconversion among these different phenotypes remains unclear. Here, we integrate dynamical systems modeling with transcriptomic data analysis at bulk and single-cell levels to investigate...
Acute myeloid leukemia (AML) progression reflects a stochastic and adaptive process driven by cellular plasticity and the continual reshaping of epigenetic regulatory programs. To capture these dynamics, we develop a stochastic modeling framework in which a Langevin equation describes noise‑driven fluctuations underlying shifts in differentiation potential, chromatin state, and lineage...
Cancer has been a serious disease for human health. Genetic mutations have often been thought to be mainly responsible for the cancer formation. More evidences have been accumulated that cancer emergence is not just caused by individual gene perturbation but also from the whole network or state of the system. This shift of thinking demands global quantification and physical understanding of...
Phenotypic plasticity in breast cancer can be viewed as stochastic switching between stable gene-expression states associated with clinically distinct subtypes. Building on our previously published NF-κB-centered regulatory network model for breast cancer heterogeneity \cite{Lopes2025}, I will present recent results showing that, in non-conservative gene regulatory systems, in which potential...
Phenotypic plasticity,the dynamic switching of cancer cells between phenotypes, is a fundamental, yet poorly quantified, driver of metastasis, therapy resistance, and relapse. A deep understanding of this process requires the integration of experimental data with advanced mathematical frameworks to move beyond description to prediction. This symposium brings together...
