Repository logo
 

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

Accepted version
Peer-reviewed

No Thumbnail Available

Type

Article

Change log

Authors

Beer, Lucian 
Sahin, Hilal 
Bateman, Nicholas W 
Blazic, Ivana 
Vargas, Hebert Alberto 

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.

Description

Keywords

Gene expression profiling, Ovarian neoplasms, Prognosis, Proteomics, Radiomics, Abdominal Cavity, Adaptor Proteins, Signal Transducing, Aged, Aged, 80 and over, Aldehyde Oxidoreductases, Antigens, Neoplasm, Carcinoma, Ovarian Epithelial, Cytokines, Female, Gene Expression Profiling, Glucose-6-Phosphate Isomerase, Humans, LIM Domain Proteins, Mesentery, Middle Aged, Neoplasm Grading, Neoplasm Proteins, Neoplasms, Cystic, Mucinous, and Serous, Omentum, Ovarian Neoplasms, Peritoneal Neoplasms, Pilot Projects, Proteomics, ROC Curve, Retrospective Studies, Tomography, X-Ray Computed

Journal Title

Eur Radiol

Conference Name

Journal ISSN

0938-7994
1432-1084

Volume Title

30

Publisher

Springer Science and Business Media LLC

Rights

All rights reserved
Sponsorship
Mark Foundation for Cancer Research US Ltd (Unknown)
Cancer Research UK (C96/A25177)
This work was supported by The Mark Foundation for Cancer Research and Cancer Research UK Cambridge Centre [C9685/A25177] and the U.S. Department of Defence - Uniformed Services University of the Health Sciences (HU0001-16-2-0006). In addition this project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. Data used in this publication were generated by the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC). The results published here are in whole or part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/