Acute vs. Chronic vs. Cyclic Hypoxia: Their Differential Dynamics, Molecular Mechanisms, and Effects on Tumor Progression

Abstract

Hypoxia has been shown to increase the aggressiveness and severity of tumor progression. Along with chronic and acute hypoxic regions, solid tumors contain regions of cycling hypoxia (also called intermittent hypoxia or IH). Cyclic hypoxia is mimicked in vitro and in vivo by periodic exposure to cycles of hypoxia and reoxygenation (H–R cycles). Compared to chronic hypoxia, cyclic hypoxia has been shown to augment various hallmarks of cancer to a greater extent: angiogenesis, immune evasion, metastasis, survival etc. Cycling hypoxia has also been shown to be the major contributing factor in increasing the risk of cancer in obstructive sleep apnea (OSA) patients. Here, we first compare and contrast the effects of acute, chronic and intermittent hypoxia in terms of molecular pathways activated and the cellular processes affected. We highlight the underlying complexity of these differential effects and emphasize the need to investigate various combinations of factors impacting cellular adaptation to hypoxia: total duration of hypoxia, concentration of oxygen (O2), and the presence of and frequency of H–R cycles. Finally, we summarize the effects of cycling hypoxia on various hallmarks of cancer highlighting their dependence on the abovementioned factors. We conclude with a call for an integrative and rigorous analysis of the effects of varying extents and durations of hypoxia on cells, including tools such as mechanism-based mathematical modelling and microfluidic setups.

A mathematical dissection of the adaptation of cell populations to fluctuating oxygen levels

“…Previous empirical and theoretical work has suggested that cycling hypoxia makes it necessary for cancer cells to adapt to fluctuating environmental conditions (Gillies et al, 2018;Amend et al, 2018) and impacts on tumour growth by increasing clonal diversity, promoting metastasis and supporting more plastic phenotypic variants (Cairns et al, 2001;Cairns and Hill, 2004;Louie et al, 2010;Verduzco et al, 2015;Chen et al, 2018;Saxena and Jolly, 2019). In particular, it has been hypothesised that -by analogy with bacterial populations facing unpredictable environmental changes (Kussell and Leibler, 2005;Smits et al, 2006;Veening et al, 2008;Acar et al, 2008;Beaumont et al, 2009;Nichol et al, 2016) -cancer cell populations could utilise risk spreading through stochastic phenotype switching, which is also known as bet-hedging (Philippi and Seger, 1989), as an adaptive strategy to survive in the harsh, constantly changing environmental conditions associated with cycling hypoxia (Gravenmier et al, 2018;Gillies et al, 2018).…”

Intermittent hypoxia exacerbates tumor progression in a mouse model of lung cancer

“…In previous studies, basal level of HIF-1α expression is high in lung cancer mouse model in normoxic condition even though the level of HIF-1α is increased in hypoxic conditions [63][64][65] . Also, it is assumed that HIF-1α and HIF-2α are activated differentially depending on the duration of hypoxia 66 . In breast cancer cells, acute hypoxia increased HIF-1α expression, while chronic hypoxia continuously enhanced HIF-2α expression and induced the resistance of breast cancer cells to chemotherapy 67 .…”

“…In breast cancer cells, acute hypoxia increased HIF-1α expression, while chronic hypoxia continuously enhanced HIF-2α expression and induced the resistance of breast cancer cells to chemotherapy 67 . HIF-1α protein levels typically peak around 4-8 h and continuously decrease thereafter and are undetectable around 18-24 h; while HIF-2α levels are stabilized relatively later and tend to play a key role during chronic hypoxia (24-72 h) 66,68 . This phenomenon is explained that HIF-1α in hypoxia leads to accelerated degradation on reoxygenation after hypoxia by induction of HIF-α-prolyl-4-hydroxylases 69 .…”

What is the storage effect, why should it occur in cancers, and how can it inform cancer therapy?

“…Radiographic and histologic images show cancer at a point in time. Although they reveal, and provide data for, modeling spatial heterogeneity in cancer, they do not capture or inform the potential variation in time that small-scale physiological studies indicate is there as well 12,14,58 .…”