Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis.

Abstract:: OBJECTIVES: To investigate the association between CT imaging traits and texture metrics with proteomic data in patients with high-grade serous ovarian cancer (HGSOC). METHODS: This retrospective, hypothesis-generating study included 20 patients with HGSOC prior to primary cytoreductive surgery. Two readers independently assessed the contrast-enhanced computed tomography (CT) images and extracted 33 imaging traits, with a third reader adjudicating in the event of a disagreement. In addition, all sites of suspected HGSOC were manually segmented texture features which were computed from each tumor site. Three texture features that represented intra- and inter-site tumor heterogeneity were used for analysis. An integrated analysis of transcriptomic and proteomic data identified proteins with conserved expression between primary tumor sites and metastasis. Correlations between protein abundance and various CT imaging traits and texture features were assessed using the Kendall tau rank correlation coefficient and the Mann-Whitney U test, whereas the area under the receiver operating characteristic curve (AUC) was reported as a metric of the strength and the direction of the association. P values

Authors:: L Beer, H Sahin, NW Bateman, I Blazic, HA Vargas, H Veeraraghavan, J Kirby, B Fevrier-Sullivan, JB Freymann, CC Jaffe, J Brenton, M Miccó, S Nougaret, KM Darcy, GL Maxwell, TP Conrads, E Huang, E Sala

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