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Review
. 2014 Mar;87(1035):20130676.
doi: 10.1259/bjr.20130676.

Defining normoxia, physoxia and hypoxia in tumours-implications for treatment response

Affiliations
Review

Defining normoxia, physoxia and hypoxia in tumours-implications for treatment response

S R McKeown. Br J Radiol. 2014 Mar.

Abstract

Tumour hypoxia is increasingly recognized as a major deleterious factor in cancer therapies, as it compromises treatment and drives malignant progression. This review seeks to clarify the oxygen levels that are pertinent to this issue. It is argued that normoxia (20% oxygen) is an extremely poor comparator for "physoxia", i.e. the much lower levels of oxygen universally found in normal tissues, which averages about 5% oxygen, and ranges from about 3% to 7.4%. Importantly, it should be recognized that the median oxygenation in untreated tumours is significantly much lower, falling between approximately 0.3% and 4.2% oxygen, with most tumours exhibiting median oxygen levels <2%. This is partially dependent on the tissue of origin, and it is notable that many prostate and pancreatic tumours are profoundly hypoxic. In addition, therapy can induce even further, often unrecognized, changes in tumour oxygenation that may vary longitudinally, increasing or decreasing during treatment in ways that are not always predictable. Studies that fail to take cognizance of the actual physiological levels of oxygen in tissues (approximately 5%) and tumours (approximately 1%) may fail to identify the real circumstances driving tumour response to treatment and/or malignant progression. This can be of particular importance in genetic studies in vitro when comparison to human tumours is required.

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Figures

Figure 1
Figure 1
The number of publications on tumour hypoxia as listed in PubMed, over the previous six decades. [The numbers for 1948–52 (3) and 1953–62 (20) are too small to be visible.]
Figure 2
Figure 2
The relation between tissue oxygenation and radiosensitivity. Schematic representation of the radiosensitivity of tissue summarising the data from many sources. (Adapted from Hall and Giaccia.) *Estimated approximate mean/median from published data (summarized in Table 2).

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