4.6 Article

Transcriptional Dynamics of DNA Damage Responsive Genes in Circulating Leukocytes during Radiotherapy

期刊

CANCERS
卷 14, 期 11, 页码 -

出版社

MDPI
DOI: 10.3390/cancers14112649

关键词

FDXR; radiation exposure; biomarkers; PBMCs; radiotherapy; ionizing radiation

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资金

  1. International Atomic Energy Agency (IAEA), Coordinated Research Project [E3.50.10, RC21066]
  2. National Institute for Health Research (NIHR) Health Protection Research Unit in Chemical and Radiation Threats and Hazards

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The FDXR gene was identified as the most sensitive and responsive to low dose radiation in cancer patients undergoing localized radiation treatment, showing a peak expression around 8-9 hours post-irradiation. The study also revealed the dynamic nature of DNA damage response in circulating blood leukocytes during radiotherapy, with FDXR expression correlating with the percentage of body exposed. Additionally, the upregulation of FDXR gene transcription was dose-dependent and could provide individual biological dosimetry information for predicting radiotherapy-associated adverse health outcomes.
Simple Summary In this study, the transcriptional response of a panel of radiation responsive genes was monitored over time in blood samples after radiation exposure in vivo. For this aim, cancer patients treated by radiotherapy were recruited after consent forms were obtained. Following the first fraction of radiotherapy, 2 mL blood samples were collected at different time points during the first 24h hours (before the second fraction was delivered) and at mid and end of treatment. Amongst the 9 genes studied, the gene FDXR stood out as the most sensitive and responsive to the low dose of radiation received from the localised radiation treatment by the circulating white blood cells. The activation of FDXR was found to depend on the volume of the body exposed with a peak of expression around 8-9 hours after irradiation was delivered. Finally results obtained ex vivo confirmed the results obtained in vivo. External beam radiation therapy leads to cellular activation of the DNA damage response (DDR). DNA double-strand breaks (DSBs) activate the ATM/CHEK2/p53 pathway, inducing the transcription of stress genes. The dynamic nature of this transcriptional response has not been directly observed in vivo in humans. In this study we monitored the messenger RNA transcript abundances of nine DNA damage-responsive genes (CDKN1A, GADD45, CCNG1, FDXR, DDB2, MDM2, PHPT1, SESN1, and PUMA), eight of them regulated by p53 in circulating blood leukocytes at different time points (2, 6-8, 16-18, and 24 h) in cancer patients (lung, neck, brain, and pelvis) undergoing radiotherapy. We discovered that, although the calculated mean physical dose to the blood was very low (0.038-0.169 Gy), an upregulation of Ferredoxin reductase (FDXR) gene transcription was detectable 2 h after exposure and was dose dependent from the lowest irradiated percentage of the body (3.5% whole brain) to the highest, (up to 19.4%, pelvic zone) reaching a peak at 6-8 h. The radiation response of the other genes was not strong enough after such low doses to provide meaningful information. Following multiple fractions, the expression level increased further and was still significantly up-regulated by the end of the treatment. Moreover, we compared FDXR transcriptional responses to ionizing radiation (IR) in vivo with healthy donors' blood cells exposed ex vivo and found a good correlation in the kinetics of expression from the 8-hours time-point onward, suggesting that a molecular transcriptional regulation mechanism yet to be identified is involved. To conclude, we provided the first in vivo human report of IR-induced gene transcription temporal response of a panel of p53-dependant genes. FDXR was demonstrated to be the most responsive gene, able to reliably inform on the low doses following partial body irradiation of the patients, and providing an expression pattern corresponding to the % of body exposed. An extended study would provide individual biological dosimetry information and may reveal inter-individual variability to predict radiotherapy-associated adverse health outcomes.

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