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Detection of Hypoxia in Cancer Models: Significance, Challenges, and Advances

The rapid proliferation of cancer cells combined with deficient vessels cause regions of nutrient and O(2) deprivation in solid tumors. Some cancer cells can adapt to these extreme hypoxic conditions and persist to promote cancer progression. Intratumoral hypoxia has been consistently associated wit...

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Detalles Bibliográficos
Autores principales: Godet, Inês, Doctorman, Steven, Wu, Fan, Gilkes, Daniele M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8869817/
https://www.ncbi.nlm.nih.gov/pubmed/35203334
http://dx.doi.org/10.3390/cells11040686
Descripción
Sumario:The rapid proliferation of cancer cells combined with deficient vessels cause regions of nutrient and O(2) deprivation in solid tumors. Some cancer cells can adapt to these extreme hypoxic conditions and persist to promote cancer progression. Intratumoral hypoxia has been consistently associated with a worse patient prognosis. In vitro, 3D models of spheroids or organoids can recapitulate spontaneous O(2) gradients in solid tumors. Likewise, in vivo murine models of cancer reproduce the physiological levels of hypoxia that have been measured in human tumors. Given the potential clinical importance of hypoxia in cancer progression, there is an increasing need to design methods to measure O(2) concentrations. O(2) levels can be directly measured with needle-type probes, both optical and electrochemical. Alternatively, indirect, noninvasive approaches have been optimized, and include immunolabeling endogenous or exogenous markers. Fluorescent, phosphorescent, and luminescent reporters have also been employed experimentally to provide dynamic measurements of O(2) in live cells or tumors. In medical imaging, modalities such as MRI and PET are often the method of choice. This review provides a comparative overview of the main methods utilized to detect hypoxia in cell culture and preclinical models of cancer.