ABSTRACT
BACKGROUND AND PURPOSE: Radiomics is a high-throughput approach that allows for quantitative analysis of imaging data for prognostic applications. Medical images are used in oropharyngeal cancer (OPC) diagnosis and treatment planning and these images may contain prognostic information allowing for treatment personalization. However, the lack of validated models has been a barrier to the translation of radiomic research to the clinic. We hypothesize that a previously developed radiomics model for risk stratification in OPC can be validated in a local dataset. MATERIALS AND METHODS: The radiomics signature predicting overall survival incorporates features derived from the primary gross tumor volume of OPC patients treated with radiation +/- chemotherapy at a single institution (n = 343). Model fit, calibration, discrimination, and utility were evaluated. The signature was compared with a clinical model using overall stage and a model incorporating both radiomics and clinical data. A model detecting dental artifacts on computed tomography images was also validated. RESULTS: The radiomics signature had a Concordance index (C-index) of 0.66 comparable to the clinical model's C-index of 0.65. The combined model significantly outperformed (C-index of 0.69, p = 0.024) the clinical model, suggesting that radiomics provides added value. The dental artifact model demonstrated strong ability in detecting dental artifacts with an area under the curve of 0.87. CONCLUSION: This work demonstrates model performance comparable to previous validation work and provides a framework for future independent and multi-center validation efforts. With sufficient validation, radiomic models have the potential to improve traditional systems of risk stratification, treatment personalization and patient outcomes.
Subject(s)
Oropharyngeal Neoplasms , Tomography, X-Ray Computed , Humans , Prognosis , Oropharyngeal Neoplasms/diagnostic imaging , Oropharyngeal Neoplasms/therapy , Retrospective StudiesABSTRACT
Post-translational glycosylation of proteins with O-linked ß-N-acetylglucosamine (O-GlcNAcylation) and changes of galectin expression profiles are essential in many cellular stress responses. We examine this regulation in the liver tissue of hibernating thirteen-lined ground squirrels (Ictidomys tridecemlineatus) representing a biological model of hypometabolism and physiological stress resistance. The tissue levels of O-GlcNAcylated proteins as well as galectin-1 and galectin-3 proteins detected by immunodot blot assay were significantly lower by 4.6-5.4-, 2.2-2.3- and 2.5-2.9-fold, respectively, in the non-hibernating summer squirrels compared with those in winter, whether hibernating or aroused. However, there were no differences in the expression of genes encoding enzymes involved in O-GlcNAc cycle (O-GlcNAc transferase and O-GlcNAcase) and such galectins as LGALS1, LGALS2, LGALS3, LGALS4 and LGALS9. Only the expression of LGALS8 gene in the liver tissue was significantly decreased by 37.6 ± 0.1% in hibernating ground squirrels relative to summer animals. Considering that the expression of a proven genetic biomarker ELOVL6 encoding ELOVL fatty acid elongase 6 was readily upregulated in non-hibernating animals by 11.3-32.9-fold, marginal differential changes in the expression of galectin genes cannot be classified as biomarkers of hibernation. Thus, this study provides evidence that hibernation in Ictidomys tridecemlineatus is associated with increasing O-GlcNAcylation of liver proteins and suggests that the contribution of galectins deserves further studies at the protein level.