Cancer Cell Adaptation to Cycling Hypoxia: Integrating Mathematical Modeling with Experimental Validation of HIF-1 Dynamics

Abstract

The adaptive response of cancer cells to hypoxia, a key microenvironmental factor in solid tumors, is intricately orchestrated by Hypoxia-inducible factor 1 (HIF1). Evidence is accumulating on oxygen dynamics in tumor cores, showing that hypoxia is frequently unstable, or cycling, associated with specific phenotypic outcomes for the cancer. Transcriptomic analysis show that most gene expression changes in cycling hypoxia lie in between the change caused by stable hypoxia, suggesting multi-cycle averaging of dosage in the oxygen tension, and likely HIF-1 induced transcription. However, small subset of genes show an oscillation/cycling hypoxia specific response, suggesting that the transcriptional machinery of these genes may interpret cycling HIF-1 activity differently from stably high HIF-1 activity. Here, we model a gene regulatory circuit, the incoherent feed-forward loops (IFFLs) to explore parameter regimes where oscillatory specific transcription is plausible. In these IFFL models, HIF-1 regulates gene transcription of a target gene directly, as well indirectly via another transcription factor with an opposite effect on gene transcription. We have identified several plausible parameter regimes where oscillation specific gene expression can occur, with potentially significant effect on cancer growth and progression. Finally, we experimentally confirmed that HIF-1 can form IFFLs with two key transcription factors p53, and Notch1, resulting in cycling hypoxia specific gene expression linked to breast cancer progression and poor prognosis. Our models mechanistically reveal how temporal fluctuations in the tumor microenvironment may directly inform downstream transcription, identify hitherto unknown HIF-1 driven mechanism of cancer progression contributing to emergent tumor heterogeneity.