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

  1. Author:
    Beer, Lucian
    Sahin, Hilal
    Bateman, Nicholas W
    Blazic, Ivana
    Vargas, Hebert Alberto
    Veeraraghavan, Harini
    Kirby,Justin
    Fevrier-Sullivan,Brenda
    Freymann,John
    Jaffe, C Carl
    Brenton, James
    Miccó, Maura
    Nougaret, Stephanie
    Darcy, Kathleen M
    Maxwell, G Larry
    Conrads, Thomas P
    Huang, Erich
    Sala, Evis [ORCID]
  2. Author Address

    Department of Radiology, Cancer Research UK Cambridge Center, Cambridge, CB2 0QQ, UK., Department of Obstetrics and Gynecology, Gynecologic Cancer Center of Excellence, Walter Reed National Military Medical Center, Uniformed Services University, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA., The John P. Murtha Cancer Center, Walter Reed National Military Medical Center, Uniformed Services University, 8901 Wisconsin Avenue, Bethesda, MD, 20889, USA., Department of Radiology, Clinical Hospital Center Zemun, Vukova 9, Belgrade, 11080, Serbia., Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA., Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA., Cancer Imaging Informatics Lab, Frederick National Laboratory for Cancer Research, Frederick, MD, USA., Department of Radiology, Boston University School of Medicine, Boston, MA, 02118, USA., Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, Cambridgeshire, UK., Cancer Research UK Cambridge Centre, Cambridge, Cambridgeshire, UK., Dipartimento Diagnostica per Immagini, Radiologia Diagnostica e Interventistica Generale, Area Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Rome, Italy., Department of Radiology, Montpellier Cancer Institute, INSERM, University of Montpellier, Montpellier, France., Department of Obstetrics and Gynecology, Inova Fairfax Medical Campus, 3300 Gallows Rd., Falls Church, VA, 22042, USA., Inova Center for Personalized Health, Inova Schar Cancer Institute, 3300 Gallows Rd., Falls Church, VA, 22042, USA., Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Rockville, MD, 20850, USA., Department of Radiology, Cancer Research UK Cambridge Center, Cambridge, CB2 0QQ, UK. es220@cam.ac.uk., Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK. es220@cam.ac.uk.,
    1. Year: 2020
    2. Date: Apr 06
    3. Epub Date: 2020 04 06
  1. Journal: European radiology
    1. Pages: pii: 10.1007/s00330-020-06755-3
  2. Type of Article: Article
  3. ISSN: 0938-7994
  1. 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, t = 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.

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  1. DOI: 10.1007/s00330-020-06755-3
  2. PMID: 32253542
  3. WOS: 000524370000001
  4. PII : 10.1007/s00330-020-06755-3

Library Notes

  1. Fiscal Year: FY2019-2020
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