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

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...

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Autores principales: Beer, Lucian, Sahin, Hilal, Bateman, Nicholas W., Blazic, Ivana, Vargas, Hebert Alberto, Veeraraghavan, Harini, Kirby, Justin, Fevrier-Sullivan, Brenda, Freymann, John B., Jaffe, C. Carl, Brenton, James, Miccó, Maura, Nougaret, Stephanie, Darcy, Kathleen M., Maxwell, G. Larry, Conrads, Thomas P., Huang, Erich, Sala, Evis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338824/
https://www.ncbi.nlm.nih.gov/pubmed/32253542
http://dx.doi.org/10.1007/s00330-020-06755-3
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author Beer, Lucian
Sahin, Hilal
Bateman, Nicholas W.
Blazic, Ivana
Vargas, Hebert Alberto
Veeraraghavan, Harini
Kirby, Justin
Fevrier-Sullivan, Brenda
Freymann, John B.
Jaffe, C. Carl
Brenton, James
Miccó, Maura
Nougaret, Stephanie
Darcy, Kathleen M.
Maxwell, G. Larry
Conrads, Thomas P.
Huang, Erich
Sala, Evis
author_facet Beer, Lucian
Sahin, Hilal
Bateman, Nicholas W.
Blazic, Ivana
Vargas, Hebert Alberto
Veeraraghavan, Harini
Kirby, Justin
Fevrier-Sullivan, Brenda
Freymann, John B.
Jaffe, C. Carl
Brenton, James
Miccó, Maura
Nougaret, Stephanie
Darcy, Kathleen M.
Maxwell, G. Larry
Conrads, Thomas P.
Huang, Erich
Sala, Evis
author_sort Beer, Lucian
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00330-020-06755-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-73388242020-07-09 Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis Beer, Lucian Sahin, Hilal Bateman, Nicholas W. Blazic, Ivana Vargas, Hebert Alberto Veeraraghavan, Harini Kirby, Justin Fevrier-Sullivan, Brenda Freymann, John B. Jaffe, C. Carl Brenton, James Miccó, Maura Nougaret, Stephanie Darcy, Kathleen M. Maxwell, G. Larry Conrads, Thomas P. Huang, Erich Sala, Evis Eur Radiol Urogenital 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00330-020-06755-3) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2020-04-06 2020 /pmc/articles/PMC7338824/ /pubmed/32253542 http://dx.doi.org/10.1007/s00330-020-06755-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Urogenital
Beer, Lucian
Sahin, Hilal
Bateman, Nicholas W.
Blazic, Ivana
Vargas, Hebert Alberto
Veeraraghavan, Harini
Kirby, Justin
Fevrier-Sullivan, Brenda
Freymann, John B.
Jaffe, C. Carl
Brenton, James
Miccó, Maura
Nougaret, Stephanie
Darcy, Kathleen M.
Maxwell, G. Larry
Conrads, Thomas P.
Huang, Erich
Sala, Evis
Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis
title Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis
title_full Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis
title_fullStr Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis
title_full_unstemmed Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis
title_short Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis
title_sort integration of proteomics with ct-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis
topic Urogenital
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338824/
https://www.ncbi.nlm.nih.gov/pubmed/32253542
http://dx.doi.org/10.1007/s00330-020-06755-3
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