Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses.
Minafra, L., Bravata', V., Russo, G., Ripamonti, M., Gilardi, M. (2013). Gene expression profiles in irradiated cancer cells. In D. Margarone, P. Cirrone, G. Cuttone, G. Korn (a cura di), 2nd ELIMED Workshop and Panel (pp. 93-95) [10.1063/1.4816614].
Gene expression profiles in irradiated cancer cells
BRAVATA', Valentina;
2013-01-01
Abstract
Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses.
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