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

Author:

Mazzara Saveria1,Travaini Laura2,Botta Francesca3,Granata Chiara4,Motta Giovanna1ORCID,Melle Federica1,Fiori Stefano1,Tabanelli Valentina1ORCID,Vanazzi Anna4ORCID,Ramadan Safaa45,Radice Tommaso4,Raimondi Sara6ORCID,Lo Presti Giuliana6ORCID,Ferrari Mahila E.3ORCID,Jereczek-Fossa Barbara Alicja78,Tarella Corrado4,Ceci Francesco28ORCID,Pileri Stefano1ORCID,Derenzini Enrico49ORCID

Affiliation:

1. 1Haematopathology Division, European Institute of Oncology (IEO) Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy

2. 2Nuclear Medicine Division, IEO IRCCS, Milan, Italy

3. 3Medical Physics Unit, IEO IRCCS, Milan, Italy

4. 4Oncohematology Division, IEO IRCCS, Milan, Italy

5. 5NCI-Cairo University, Cairo, Egypt

6. 6Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO IRCCS, Milan, Italy

7. 7Division of Radiation Oncology, IEO IRCCS, Milan, Italy

8. 8Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy

9. 9Department of Health Sciences, University of Milan, Milan, Italy

Abstract

Abstract 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.

Publisher

American Society of Hematology

Subject

Hematology

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