Jolly Mohit Kumar, Tripathi Satyendra C, Somarelli Jason A, Hanash Samir M, Levine Herbert
Center for Theoretical Biological Physics, Rice University, Houston, TX, USA.
Department of Clinical Cancer Prevention, UT MD Anderson Cancer Center, Houston, TX, USA.
Mol Oncol. 2017 Jul;11(7):739-754. doi: 10.1002/1878-0261.12084. Epub 2017 Jun 19.
Phenotypic plasticity, the ability of cells to reversibly alter their phenotypes in response to signals, presents a significant clinical challenge to treating solid tumors. Tumor cells utilize phenotypic plasticity to evade therapies, metastasize, and colonize distant organs. As a result, phenotypic plasticity can accelerate tumor progression. A well-studied example of phenotypic plasticity is the bidirectional conversions among epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M) phenotype(s). These conversions can alter a repertoire of cellular traits associated with multiple hallmarks of cancer, such as metabolism, immune evasion, invasion, and metastasis. To tackle the complexity and heterogeneity of these transitions, mathematical models have been developed that seek to capture the experimentally verified molecular mechanisms and act as 'hypothesis-generating machines'. Here, we discuss how these quantitative mathematical models have helped us explain existing experimental data, guided further experiments, and provided an improved conceptual framework for understanding how multiple intracellular and extracellular signals can drive E/M plasticity at both the single-cell and population levels. We also discuss the implications of this plasticity in driving multiple aggressive facets of tumor progression.
表型可塑性是指细胞响应信号而可逆地改变其表型的能力，这给实体瘤治疗带来了重大临床挑战。肿瘤细胞利用表型可塑性来逃避治疗、发生转移并在远处器官定植。因此，表型可塑性会加速肿瘤进展。一个经过充分研究的表型可塑性例子是上皮、间充质和混合上皮/间充质（E/M）表型之间的双向转换。这些转换可以改变一系列与癌症多个特征相关的细胞特性，如代谢、免疫逃逸、侵袭和转移。为了解决这些转变的复杂性和异质性，已经开发了数学模型，旨在捕捉经过实验验证的分子机制，并充当“假设生成机器”。在这里，我们讨论这些定量数学模型如何帮助我们解释现有实验数据、指导进一步实验，并为理解多种细胞内和细胞外信号如何在单细胞和群体水平驱动E/M可塑性提供一个改进的概念框架。我们还讨论了这种可塑性在驱动肿瘤进展的多个侵袭性方面的意义。
