RESUMEN
Deregulated metabolism is one of the hallmarks of cancer. It is well-known that tumour cells tend to metabolize glucose via glycolysis even when oxygen is available and mitochondrial respiration is functional. However, the lower energy efficiency of aerobic glycolysis with respect to mitochondrial respiration makes this behaviour, namely the Warburg effect, counter-intuitive, although it has now been recognized as source of anabolic precursors. On the other hand, there is evidence that oxygenated tumour cells could be fuelled by exogenous lactate produced from glycolysis. We employed a multi-scale approach that integrates multi-agent modelling, diffusion-reaction, stoichiometric equations, and Boolean networks to study metabolic cooperation between hypoxic and oxygenated cells exposed to varying oxygen, nutrient, and inhibitor concentrations. The results show that the cooperation reduces the depletion of environmental glucose, resulting in an overall advantage of using aerobic glycolysis. In addition, the oxygen level was found to be decreased by symbiosis, promoting a further shift towards anaerobic glycolysis. However, the oxygenated and hypoxic populations may gradually reach quasi-equilibrium. A sensitivity analysis using Latin hypercube sampling and partial rank correlation shows that the symbiotic dynamics depends on properties of the specific cell such as the minimum glucose level needed for glycolysis. Our results suggest that strategies that block glucose transporters may be more effective to reduce tumour growth than those blocking lactate intake transporters.
Asunto(s)
Neoplasias , Simbiosis , Humanos , Glucólisis , Ácido Láctico/metabolismo , Neoplasias/metabolismo , Glucosa/metabolismo , Hipoxia , OxígenoRESUMEN
Tumour hypoxia is associated with poor patient prognosis and therapy resistance. A unique transcriptional response is initiated by hypoxia which includes the rapid activation of numerous transcription factors in a background of reduced global transcription. Here, we show that the biological response to hypoxia includes the accumulation of R-loops and the induction of the RNA/DNA helicase SETX. In the absence of hypoxia-induced SETX, R-loop levels increase, DNA damage accumulates, and DNA replication rates decrease. Therefore, suggesting that, SETX plays a role in protecting cells from DNA damage induced during transcription in hypoxia. Importantly, we propose that the mechanism of SETX induction in hypoxia is reliant on the PERK/ATF4 arm of the unfolded protein response. These data not only highlight the unique cellular response to hypoxia, which includes both a replication stress-dependent DNA damage response and an unfolded protein response but uncover a novel link between these two distinct pathways.
Asunto(s)
Hipoxia de la Célula , Daño del ADN/genética , ADN Helicasas/metabolismo , Regulación de la Expresión Génica/genética , Enzimas Multifuncionales/metabolismo , Estructuras R-Loop/genética , ARN Helicasas/metabolismo , Respuesta de Proteína Desplegada/genética , Factor de Transcripción Activador 4/genética , Factor de Transcripción Activador 4/metabolismo , Muerte Celular/efectos de los fármacos , Muerte Celular/genética , Línea Celular Tumoral , Supervivencia Celular/efectos de los fármacos , Supervivencia Celular/genética , Inmunoprecipitación de Cromatina , ADN Helicasas/genética , Regulación de la Expresión Génica/efectos de los fármacos , Humanos , Enzimas Multifuncionales/genética , Inhibidores de la Síntesis del Ácido Nucleico/farmacología , Oxígeno/farmacología , Estructuras R-Loop/efectos de los fármacos , ARN Helicasas/genética , RNA-Seq , Respuesta de Proteína Desplegada/efectos de los fármacos , Regulación hacia Arriba , Cinostatina/farmacología , eIF-2 Quinasa/metabolismoRESUMEN
The application of modelling to solve problems in biology and medicine, and specifically in oncology and radiation therapy, is increasingly established and holds big promise. We provide an overview of the basic concepts of the field and its current state, along with new tools available and future directions for research. We will outline radiobiology models, examples of other anticancer therapy models, multiscale modelling, and we will discuss mechanistic and phenomenological approaches to modelling.