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Gene expression profiling and FDG-PET radiomics uncover radiometabolic signatures associated with outcome in DLBCL

Emerging evidence indicates that chemoresistance is closely related to altered metabolism in cancer. Here, we hypothesized that distinct metabolic gene expression profiling (GEP) signatures might be correlated with outcome and with specific fluorodeoxyglucose positron emission tomography (FDG-PET) r...

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Autores principales: Mazzara, Saveria, Travaini, Laura, Botta, Francesca, Granata, Chiara, Motta, Giovanna, Melle, Federica, Fiori, Stefano, Tabanelli, Valentina, Vanazzi, Anna, Ramadan, Safaa, Radice, Tommaso, Raimondi, Sara, Lo Presti, Giuliana, Ferrari, Mahila E., Jereczek-Fossa, Barbara Alicja, Tarella, Corrado, Ceci, Francesco, Pileri, Stefano, Derenzini, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society of Hematology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979764/
https://www.ncbi.nlm.nih.gov/pubmed/36806558
http://dx.doi.org/10.1182/bloodadvances.2022007825
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author Mazzara, Saveria
Travaini, Laura
Botta, Francesca
Granata, Chiara
Motta, Giovanna
Melle, Federica
Fiori, Stefano
Tabanelli, Valentina
Vanazzi, Anna
Ramadan, Safaa
Radice, Tommaso
Raimondi, Sara
Lo Presti, Giuliana
Ferrari, Mahila E.
Jereczek-Fossa, Barbara Alicja
Tarella, Corrado
Ceci, Francesco
Pileri, Stefano
Derenzini, Enrico
author_facet Mazzara, Saveria
Travaini, Laura
Botta, Francesca
Granata, Chiara
Motta, Giovanna
Melle, Federica
Fiori, Stefano
Tabanelli, Valentina
Vanazzi, Anna
Ramadan, Safaa
Radice, Tommaso
Raimondi, Sara
Lo Presti, Giuliana
Ferrari, Mahila E.
Jereczek-Fossa, Barbara Alicja
Tarella, Corrado
Ceci, Francesco
Pileri, Stefano
Derenzini, Enrico
author_sort Mazzara, Saveria
collection PubMed
description Emerging evidence indicates that chemoresistance is closely related to altered metabolism in cancer. Here, we hypothesized that distinct metabolic gene expression profiling (GEP) signatures might be correlated with outcome and with specific fluorodeoxyglucose positron emission tomography (FDG-PET) radiomic profiles in diffuse large B-cell lymphoma (DLBCL). We retrospectively analyzed a discovery cohort of 48 consecutive patients with DLBCL treated at our center with standard first-line chemoimmunotherapy by performing targeted GEP (T-GEP)– and FDG-PET radiomic analyses on the same target lesions at baseline. T-GEP–based metabolic profiling identified a 6-gene signature independently associated with outcomes in univariate and multivariate analyses. This signature included genes regulating mitochondrial oxidative metabolism (SCL25A1, PDK4, PDPR) that were upregulated and was inversely associated with genes involved in hypoxia and glycolysis (MAP2K1, HIF1A, GBE1) that were downregulated. These data were validated in 2 large publicly available cohorts. By integrating FDG-PET radiomics and T-GEP, we identified a radiometabolic signature (RadSig) including 4 radiomic features (histo kurtosis, histo energy, shape sphericity, and neighboring gray level dependence matrix contrast), significantly associated with the metabolic GEP–based signature (r = 0.43, P = .0027) and with progression-free survival (P = .028). These results were confirmed using different target lesions, an alternative segmentation method, and were validated in an independent cohort of 64 patients. RadSig retained independent prognostic value in relation to the International Prognostic Index score and metabolic tumor volume (MTV). Integration of RadSig and MTV further refined prognostic stratification. This study provides the proof of principle for the use of FDG-PET radiomics as a tool for noninvasive assessment of cancer metabolism and prognostic stratification in DLBCL.
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spelling pubmed-99797642023-03-03 Gene expression profiling and FDG-PET radiomics uncover radiometabolic signatures associated with outcome in DLBCL Mazzara, Saveria Travaini, Laura Botta, Francesca Granata, Chiara Motta, Giovanna Melle, Federica Fiori, Stefano Tabanelli, Valentina Vanazzi, Anna Ramadan, Safaa Radice, Tommaso Raimondi, Sara Lo Presti, Giuliana Ferrari, Mahila E. Jereczek-Fossa, Barbara Alicja Tarella, Corrado Ceci, Francesco Pileri, Stefano Derenzini, Enrico Blood Adv Lymphoid Neoplasia Emerging evidence indicates that chemoresistance is closely related to altered metabolism in cancer. Here, we hypothesized that distinct metabolic gene expression profiling (GEP) signatures might be correlated with outcome and with specific fluorodeoxyglucose positron emission tomography (FDG-PET) radiomic profiles in diffuse large B-cell lymphoma (DLBCL). We retrospectively analyzed a discovery cohort of 48 consecutive patients with DLBCL treated at our center with standard first-line chemoimmunotherapy by performing targeted GEP (T-GEP)– and FDG-PET radiomic analyses on the same target lesions at baseline. T-GEP–based metabolic profiling identified a 6-gene signature independently associated with outcomes in univariate and multivariate analyses. This signature included genes regulating mitochondrial oxidative metabolism (SCL25A1, PDK4, PDPR) that were upregulated and was inversely associated with genes involved in hypoxia and glycolysis (MAP2K1, HIF1A, GBE1) that were downregulated. These data were validated in 2 large publicly available cohorts. By integrating FDG-PET radiomics and T-GEP, we identified a radiometabolic signature (RadSig) including 4 radiomic features (histo kurtosis, histo energy, shape sphericity, and neighboring gray level dependence matrix contrast), significantly associated with the metabolic GEP–based signature (r = 0.43, P = .0027) and with progression-free survival (P = .028). These results were confirmed using different target lesions, an alternative segmentation method, and were validated in an independent cohort of 64 patients. RadSig retained independent prognostic value in relation to the International Prognostic Index score and metabolic tumor volume (MTV). Integration of RadSig and MTV further refined prognostic stratification. This study provides the proof of principle for the use of FDG-PET radiomics as a tool for noninvasive assessment of cancer metabolism and prognostic stratification in DLBCL. The American Society of Hematology 2022-09-19 /pmc/articles/PMC9979764/ /pubmed/36806558 http://dx.doi.org/10.1182/bloodadvances.2022007825 Text en © 2023 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Lymphoid Neoplasia
Mazzara, Saveria
Travaini, Laura
Botta, Francesca
Granata, Chiara
Motta, Giovanna
Melle, Federica
Fiori, Stefano
Tabanelli, Valentina
Vanazzi, Anna
Ramadan, Safaa
Radice, Tommaso
Raimondi, Sara
Lo Presti, Giuliana
Ferrari, Mahila E.
Jereczek-Fossa, Barbara Alicja
Tarella, Corrado
Ceci, Francesco
Pileri, Stefano
Derenzini, Enrico
Gene expression profiling and FDG-PET radiomics uncover radiometabolic signatures associated with outcome in DLBCL
title Gene expression profiling and FDG-PET radiomics uncover radiometabolic signatures associated with outcome in DLBCL
title_full Gene expression profiling and FDG-PET radiomics uncover radiometabolic signatures associated with outcome in DLBCL
title_fullStr Gene expression profiling and FDG-PET radiomics uncover radiometabolic signatures associated with outcome in DLBCL
title_full_unstemmed Gene expression profiling and FDG-PET radiomics uncover radiometabolic signatures associated with outcome in DLBCL
title_short Gene expression profiling and FDG-PET radiomics uncover radiometabolic signatures associated with outcome in DLBCL
title_sort gene expression profiling and fdg-pet radiomics uncover radiometabolic signatures associated with outcome in dlbcl
topic Lymphoid Neoplasia
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979764/
https://www.ncbi.nlm.nih.gov/pubmed/36806558
http://dx.doi.org/10.1182/bloodadvances.2022007825
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