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Article Dans Une Revue Journal of Nuclear Medicine Année : 2014

FDG PET derived quantitative heterogeneity features reflect gene expression profiles in head and neck cancer

Résumé

FDG PET has a well-established diagnostic role in oncology and has been shown as a powerful tool for patient treatment management. Quantifying tumor heterogeneity in PET images was shown to be of added value since such characteristics are supposed to be related to tumor underlying physiological processes. The aim of this study was thus to study the relationship between FDG PET derived tumor features and gene expression profiles provided by microarray analysis. 25 patients with head and neck cancer treated by radio-chemotherapy were prospectively recruited. Patients underwent an FDG PET scan at diagnosis and a biopsy on both healthy and tumor tissues for transcriptomic analysis. 15 PET image derived features, including functional tumor volume, SUVs and heterogeneity quantification by textural analysis, were considered. Transcriptomic analysis was carried out with Agilent 4x44k microarrays. A module network algorithm was used to identify groups of genes related to the PET features. Finally, a functional annotation was carried out to establish a correspondence between PET features and biological pathways. Microarrays allowed the identification of 1177 genes differentially expressed between tumor and healthy tissues with a fold change above 2 (p<0.05). The module network algorithm separated these genes in 33 groups that could be related to 4 intra-tumor tracer uptake heterogeneity features. Finally, functional annotation on these groups of genes allowed establishing a link between PET images derived features and cancer biological pathways. Despite the limited number of included patients, these results highlight the potential link between FDG PET intra-tumor activity distribution characterization and underlying tumor biological pathways. Quantification of tracer uptake heterogeneity in PET images of tumors might provide information about tumor underlying physiological processes.
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Dates et versions

hal-01208453 , version 1 (02-10-2015)

Identifiants

  • HAL Id : hal-01208453 , version 1

Citer

Florent Tixier, Catherine Cheze-Le Rest, Stéphanie Chezeaud, Stéphane Key, Brigitte Simon, et al.. FDG PET derived quantitative heterogeneity features reflect gene expression profiles in head and neck cancer. Journal of Nuclear Medicine, 2014, 55. ⟨hal-01208453⟩
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