Impact on the Transcriptome of Proton Beam Irradiation Targeted at Healthy Cardiac Tissue of Mice.
Claudia SalaMartina TarozziFrancesco LanzaMartina PazzagliaFrancesco Paolo CammarataGiorgio Ivan RussoRosaria AcquavivaGiuseppe Antonio Pablo CirroneGiada PetringaRoberto CatalanoValerio Cosimo EliaFrancesca FedeLorenzo MantiGastone C CastellaniDaniel RemondiniIsabella ZironiPublished in: Cancers (2024)
Proton beam therapy is considered a step forward with respect to electromagnetic radiation, thanks to the reduction in the dose delivered. Among unwanted effects to healthy tissue, cardiovascular complications are a known long-term radiotherapy complication. The transcriptional response of cardiac tissue from xenografted BALB/c nude mice obtained at 3 and 10 days after proton irradiation covering both the tumor region and the underlying healthy tissue was analyzed as a function of dose and time. Three doses were used: 2 Gy, 6 Gy, and 9 Gy. The intermediate dose had caused the greatest impact at 3 days after irradiation: at 2 Gy, 219 genes were differently expressed, many of them represented by zinc finger proteins; at 6 Gy, there were 1109, with a predominance of genes involved in energy metabolism and responses to stimuli; and at 9 Gy, there were 105, mainly represented by zinc finger proteins and molecules involved in the regulation of cardiac function. After 10 days, no significant effects were detected, suggesting that cellular repair mechanisms had defused the potential alterations in gene expression. The nonlinear dose-response curve indicates a need to update the models built on photons to improve accuracy in health risk prediction. Our data also suggest a possible role for zinc finger protein genes as markers of proton therapy efficacy.
Keyphrases
- gene expression
- left ventricular
- genome wide
- radiation induced
- healthcare
- dna methylation
- oxide nanoparticles
- public health
- transcription factor
- type diabetes
- heart failure
- high fat diet induced
- risk factors
- big data
- locally advanced
- electronic health record
- adipose tissue
- metabolic syndrome
- risk assessment
- machine learning
- oxidative stress
- insulin resistance
- small molecule
- atrial fibrillation
- social media
- genome wide identification
- bioinformatics analysis
- cell therapy
- amino acid