Data from Integration of CT-based Qualitative and Radiomic Features with Proteomic Variables in Patients with High-Grade Serous Ovarian Cancer: An Exploratory Analysis (TCGA-OV-Proteogenomics)

PURPOSE:To investigate the association between CT imaging traits and texture metrics with proteomic data in patients with high grade serous ovarian cancer (HGSOC).
This retrospective multi-institutional study enrolled 20 patients with HGSOC prior to primary cytoreductive surgery. Two readers independently assessed the contrast enhanced computed tomography (CT) and extracted 33 imaging traits. In addition all sites of suspected HGSOC were manually segmented and grey-level correlation matrix-based texture features were computed from each tumor site. Three texture features representing inter-site tumor heterogeneity were used for further analysis. Combined analysis of transcriptomics proteomics was used to identify stably expressed proteins between primary tumor sites and metastasis. The correlation between the different imaging traits and texture features with measurement of protein abundance were assessed using Kendall tau rank correlation coefficient and Mann-Whitney U test, whereby the area under the receiver operating characteristic curve (AUC) was reported as a metric of strength and direction of the association. P values < 0.05 were considered significant.
This study provides first insights on potentially strong associations between standard of care CT imaging traits and CT-based texture measures of tumor burden inter-site heterogeneity and abundance of several associated proteins.