Speaker
Description
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 the underlying mechanisms for cancer formation. Here, we develop cancer models from the underlying gene regulatory networks either based on the available low throughput or the recent high throughput sequence experimental studies \cite{Zhu2024AdvSci, Zhu2024PNAS, ZhuWangSubmitted}. Cancer landscape can be quantified and cancer can be revealed as attractors representing cancer states. The landscape barrier and switching time become the measures of how difficult to transform from normal to cancer state. Furthermore, the cancer formation process can be quantified by the optimal paths between the normal state and cancer state. Due to the presence of the curl flux as the nonequilibrium driving force, the forward path and backward paths for cancer formation and normal state restoration are distinctly different. The global sensitivity analysis based on the landscape topography and nonequilibrium driving forces identify key genes and regulations responsible for the cancer formation. We further identify the nonequilibrium indicators through the curl flux, entropy production and time irreversibility as the early warning signals for the cancer formation. This helps to design practical strategy for cancer prevention and treatment.
Bibliography
@article{Zhu2024AdvSci,
author = {Zhu, Ligang and Wang, Jin},
title = {Quantifying Landscape-Flux via Single-Cell Transcriptomics Uncovers the Underlying Mechanism of Cell Cycle},
journal = {Advanced Science},
volume = {11},
pages = {2308879},
year = {2024}
}
@article{Zhu2024PNAS,
author = {Zhu, Ligang and Yang, Songlin and Zhang, Kun and Wang, Hong and Fang, Xiaona and Wang, Jin},
title = {Uncovering underlying physical principles and driving forces of cell differentiation and reprogramming from single-cell transcriptomics},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {121},
number = {34},
pages = {e2401540121},
year = {2024}
}
@misc{ZhuWangSubmitted,
author = {Zhu, Ligang and Wang, Jin},
title = {Deciphering physical mechanism of cancer from single cell transcriptomics and lineage-tracing},
note = {Submitted},
year = {2024}
}
