Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis
Bateman, Nicholas W.
Vargas, Hebert Alberto
Freymann, John B.
Jaffe, C. Carl
Darcy, Kathleen M.
Maxwell, G. Larry
Conrads, Thomas P.
Springer Berlin Heidelberg
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Beer, L., Sahin, H., Bateman, N. W., Blazic, I., Vargas, H. A., Veeraraghavan, H., Kirby, J., et al. (2020). Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis. European Radiology, 30 (8), 4306-4316. https://doi.org/10.1007/s00330-020-06755-3
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 < 0.05 were considered significant. Results: Four proteins were associated with CT-based imaging traits, with the strongest correlation observed between the CRIP2 protein and disease in the mesentery (p < 0.001, AUC = 0.05). The abundance of three proteins was associated with texture features that represented intra-and inter-site tumor heterogeneity, with the strongest negative correlation between the CKB protein and cluster dissimilarity (p = 0.047, τ = 0.326). Conclusion: This study provides the first insights into the potential associations between standard-of-care CT imaging traits and texture measures of intra- and inter-site heterogeneity, and the abundance of several proteins. Key Points: • CT-based texture features of intra- and inter-site tumor heterogeneity correlate with the abundance of several proteins in patients with HGSOC. • CT imaging traits correlate with protein abundance in patients with HGSOC.
Urogenital, Ovarian neoplasms, Radiomics, Proteomics, Gene expression profiling, Prognosis
National Cancer Institute (HHSN261200800001E)
National Insitutes of Health (HHSN261200800001E)
The Mark Foundation for Cancer Research (C9685)
Cancer Research UK Cambridge Centre (A25177)
Uniformed Services University of the Health Sciences (HU0001-16-2-0006)
External DOI: https://doi.org/10.1007/s00330-020-06755-3
This record's URL: https://www.repository.cam.ac.uk/handle/1810/307720