ABSTRACT
Single-cell measurements combined with mathematical modeling and computer simulations are powerful tools for understanding and exploring dynamical behaviors of gene networks and cellular functions that they control. Here, we describe experimental and computational methods to study cellular quiescence and its heterogeneity at the single-cell level.
Subject(s)
Algorithms , Computer Simulation , Resting Phase, Cell Cycle , Single-Cell Analysis/methods , Cell Division , Humans , Signal Transduction , Stochastic ProcessesABSTRACT
Quiescence is a non-proliferative cellular state that is critical to tissue repair and regeneration. Although often described as the G0 phase, quiescence is not a single homogeneous state. As cells remain quiescent for longer durations, they move progressively deeper and display a reduced sensitivity to growth signals. Deep quiescent cells, unlike senescent cells, can still re-enter the cell cycle under physiological conditions. Mechanisms controlling quiescence depth are poorly understood, representing a currently underappreciated layer of complexity in growth control. Here, we show that the activation threshold of a Retinoblastoma (Rb)-E2F network switch controls quiescence depth. Particularly, deeper quiescent cells feature a higher E2F-switching threshold and exhibit a delayed traverse through the restriction point (R-point). We further show that different components of the Rb-E2F network can be experimentally perturbed, following computer model predictions, to coarse- or fine-tune the E2F-switching threshold and drive cells into varying quiescence depths.
Subject(s)
Cellular Senescence/genetics , E2F Transcription Factors/genetics , Models, Biological , Retinoblastoma Protein/genetics , Animals , Cell Division , Cell Proliferation/genetics , E2F Transcription Factors/metabolism , Fibroblasts , Gene Regulatory Networks , Humans , Rats , Retinoblastoma Protein/metabolismABSTRACT
Reactivating quiescent cells to proliferate is critical to tissue repair and homoeostasis. Quiescence exit is highly noisy even for genetically identical cells under the same environmental conditions. Deregulation of quiescence exit is associated with many diseases, but cellular mechanisms underlying the noisy process of exiting quiescence are poorly understood. Here we show that the heterogeneity of quiescence exit reflects a memory of preceding cell growth at quiescence induction and immediate division history before quiescence entry, and that such a memory is reflected in cell size at a coarse scale. The deterministic memory effects of preceding cell cycle, coupled with the stochastic dynamics of an Rb-E2F bistable switch, jointly and quantitatively explain quiescence-exit heterogeneity. As such, quiescence can be defined as a distinct state outside of the cell cycle while displaying a sequential cell order reflecting preceding cell growth and division variations.The quiescence-exit process is noisy even in genetically identical cells under the same environmental conditions. Here the authors show that the heterogeneity of quiescence exit reflects a memory of preceding cell growth at quiescence induction and immediate division history prior to quiescence entry.
Subject(s)
Algorithms , Cell Cycle/physiology , Cell Proliferation/physiology , Models, Biological , Animals , Cell Cycle/drug effects , Cell Cycle/genetics , Cell Division/drug effects , Cell Division/genetics , Cell Division/physiology , Cell Line , Cell Proliferation/drug effects , Cell Proliferation/genetics , Cell Size , Culture Media/pharmacology , Culture Media, Serum-Free/pharmacology , E2F Transcription Factors/genetics , E2F Transcription Factors/metabolism , Rats , Retinoblastoma Protein/genetics , Retinoblastoma Protein/metabolism , Time FactorsABSTRACT
The high-mobility group A protein 2 (HMGA2) is a non-histone chromatin factor highly expressed in fetal tissue and malignant tumors but rarely detected within normal adult tissues. The clinical implications and biological functions of HMGA2 in endometrial carcinoma are largely unknown. Here we report that HMGA2 expression was barely detected in benign endometrium samples (2 of 28 samples). However, HMGA2 expression increased significantly from precancerous lesion endometrial glandular dysplasia (7 of 17, 41.2%), to serous endometrial intraepithelial carcinoma (5 of 8, 62.5%) and to full blown endometrial serous carcinoma (39 of 59, 66.1%). Functional characterization of HMGA2 revealed that the gene has both tumor growth promotion and metastasis. In addition, HMGA2 induced epithelial-mesenchymal transition (EMT) through modulation vimentin and ß-catenin. Furthermore, HMGA2 overexpression started from endometrial serous precancers, non-invasive cancers, as well as in full blown carcinomas in a p53 knockout mouse model we recently established in our laboratory. Our findings suggest that HMGA2 may serve as a useful diagnostic marker in the assessment of endometrial serous cancer and its precursor lesions.
