Gene's expression underpinning the divergent predictive value of [18F]F-fluorodeoxyglucose and prostate-specific membrane antigen positron emission tomography in primary prostate cancer: a bioinformatic and experimental study

被引:12
作者
Bauckneht, Matteo [1 ,2 ]
Marini, Cecilia [2 ,3 ]
Cossu, Vanessa [1 ,2 ]
Campi, Cristina [4 ]
Riondato, Mattia [2 ]
Bruno, Silvia [5 ]
Orengo, Anna Maria [2 ]
Vitale, Francesca [2 ]
Carta, Sonia [2 ]
Chiola, Silvia [2 ]
Chiesa, Sabrina [2 ]
Miceli, Alberto [1 ]
D'Amico, Francesca [1 ]
Fornarini, Giuseppe [7 ]
Terrone, Carlo [8 ,9 ]
Piana, Michele [4 ,6 ]
Morbelli, Silvia [1 ,2 ]
Signori, Alessio [1 ]
Barboro, Paola [10 ]
Sambuceti, Gianmario [1 ,2 ]
机构
[1] Univ Genoa, Dept Hlth Sci, I-16132 Genoa, Italy
[2] Osped Policlin San Martino, Nucl Med Unit, IRCCS, I-16132 Genoa, Italy
[3] CNR, Inst Mol Bioimaging & Physiol IBFM, I-20054 Milan, Italy
[4] Univ Genoa, Dept Math DIMA, LISCOMP Lab, I-16132 Genoa, Italy
[5] Univ Genoa, Dept Expt Med, Human Anat, I-16132 Genoa, Italy
[6] CNR SPIN Genoa, I-16132 Genoa, Italy
[7] IRCCS Osped Policlin San Martino, Med Oncol Unit 1, I-16132 Genoa, Italy
[8] IRCCS Osped Policlin San Martino, Dept Urol, I-16132 Genoa, Italy
[9] Univ Genoa, Dept Surg & Diagnost Integrated Sci DISC, I-16132 Genoa, Italy
[10] Osped Policlin San Martino, Prote & Mass Spectrometry Unit, IRCCS, I-16132 Genoa, Italy
关键词
Prostate cancer; Glucose metabolism; Prostate-specific membrane antigen; Positron emission tomography; Prognosis; GLUCOSE TRANSPORTERS; RADIATION-THERAPY; RECURRENCE; ADJUVANT; SURVIVAL; TISSUE; PET/CT;
D O I
10.1186/s12967-022-03846-1
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Background Positron Emission Tomography (PET) imaging with Prostate-Specific Membrane Antigen (PSMA) and Fluorodeoxyglucose (FDG) represent promising biomarkers for risk-stratification of Prostate Cancer (PCa). We verified whether the expression of genes encoding for PSMA and enzymes regulating FDG cellular uptake are independent and additive prognosticators in PCa. Methods mRNA expression of genes involved in glucose metabolism and PSMA regulation obtained from primary PCa specimens were retrieved from open-source databases and analyzed using an integrative bioinformatics approach. Machine Learning (ML) techniques were used to create predictive Progression-Free Survival (PFS) models. Cellular models of primary PCa with different aggressiveness were used to compare [18F]F-PSMA-1007 and [18F] F-FDG uptake kinetics in vitro. Confocal microscopy, immunofluorescence staining, and quantification analyses were performed to assess the intracellular and cellular membrane PSMA expression. Results ML analyses identified a predictive functional network involving four glucose metabolism-related genes: ALDOB, CTH, PARP2, and SLC2A4. By contrast, FOLH1 expression (encoding for PSMA) did not provide any additive predictive value to the model. At a cellular level, the increase in proliferation rate and migratory potential by primary PCa cells was associated with enhanced FDG uptake and decreased PSMA retention (paralleled by the preferential intracellular localization). Conclusions The overexpression of a functional network involving four glucose metabolism-related genes identifies a higher risk of disease progression since the earliest phases of PCa, in agreement with the acknowledged prognostic value of FDG PET imaging. By contrast, the prognostic value of PSMA PET imaging is independent of the expression of its encoding gene FOLH1. Instead, it is influenced by the protein docking to the cell membrane, regulating its accessibility to tracer binding.
引用
收藏
页数:12
相关论文
共 51 条
[1]  
[Anonymous], 2001, MACH LEARN
[2]  
Avril N, 2004, J NUCL MED, V45, P930
[3]   Differential Expression of Glucose Transporters and Hexokinases in Prostate Cancer with a Neuroendocrine Gene Signature: A Mechanistic Perspective for 18F-FDG Imaging of PSMA-Suppressed Tumors [J].
Bakht, Martin K. ;
Lovnicki, Jessica M. ;
Tubman, Janice ;
Stringer, Keith F. ;
Chiaramonte, Jonathan ;
Reynolds, Michael R. ;
Derecichei, Iulian ;
Ferraiuolo, Rosa-Maria ;
Fifield, Bre-Anne ;
Lubanska, Dorota ;
Oh, So Won ;
Cheon, Gi Jeong ;
Kwak, Cheol ;
Jeong, Chang Wook ;
Kang, Keon Wook ;
Trant, John F. ;
Morrissey, Colm ;
Coleman, Ilsa M. ;
Wang, Yuzhuo ;
Ahmadzadehfar, Hojjat ;
Dong, Xuesen ;
Porter, Lisa A. .
JOURNAL OF NUCLEAR MEDICINE, 2020, 61 (06) :904-910
[4]   Neuroendocrine differentiation of prostate cancer leads to PSMA suppression [J].
Bakht, Martin K. ;
Derecichei, Iulian ;
Li, Yinan ;
Ferraiuolo, Rosa-Maria ;
Dunning, Mark ;
Oh, So Won ;
Hussein, Abdulkadir ;
Youn, Hyewon ;
Stringer, Keith F. ;
Jeong, Chang Wook ;
Cheon, Gi Jeong ;
Kwak, Cheol ;
Kang, Keon Wook ;
Lamb, Alastair D. ;
Wang, Yuzhuo ;
Dong, Xuesen ;
Porter, Lisa A. .
ENDOCRINE-RELATED CANCER, 2019, 26 (02) :131-146
[5]   Prostate cancer: Prognostic significance of the association of heterogeneous nuclear ribonucleoprotein K and androgen receptor expression [J].
Barboro, Paola ;
Salvi, Sandra ;
Rubagotti, Alessandra ;
Boccardo, Simona ;
Spina, Bruno ;
Truini, Mauro ;
Carmignani, Giorgio ;
Introini, Carlo ;
Ferrari, Nicoletta ;
Boccardo, Francesco ;
Balbi, Cecilia .
INTERNATIONAL JOURNAL OF ONCOLOGY, 2014, 44 (05) :1589-1598
[6]   The prognostic power of 18F-FDG PET/CT extends to estimating systemic treatment response duration in metastatic castration-resistant prostate cancer (mCRPC) patients [J].
Bauckneht, Matteo ;
Bertagna, Francesco ;
Donegani, Maria Isabella ;
Durmo, Rexhep ;
Miceli, Alberto ;
De Biasi, Vincenzo ;
Laudicella, Riccardo ;
Fornarini, Giuseppe ;
Berruti, Alfredo ;
Baldari, Sergio ;
Versari, Annibale ;
Giubbini, Raffaele ;
Sambuceti, Gianmario ;
Morbelli, Silvia ;
Albano, Domenico .
PROSTATE CANCER AND PROSTATIC DISEASES, 2021, 24 (04) :1198-1207
[7]   The Prognostic Role of Baseline Metabolic Tumor Burden and Systemic Inflammation Biomarkers in Metastatic Castration-Resistant Prostate Cancer Patients Treated with Radium-223: A Proof of Concept Study [J].
Bauckneht, Matteo ;
Rebuzzi, Sara Elena ;
Signori, Alessio ;
Donegani, Maria Isabella ;
Murianni, Veronica ;
Miceli, Alberto ;
Borea, Roberto ;
Raffa, Stefano ;
Damassi, Alessandra ;
Ponzano, Marta ;
Catalano, Fabio ;
Martelli, Valentino ;
Marini, Cecilia ;
Boccardo, Francesco ;
Morbelli, Silvia ;
Sambuceti, Gianmario ;
Fornarini, Giuseppe .
CANCERS, 2020, 12 (11) :1-16
[8]   Role of Baseline and Post-Therapy 18F-FDG PET in the Prognostic Stratification of Metastatic Castration-Resistant Prostate Cancer (mCRPC) Patients Treated with Radium-223 [J].
Bauckneht, Matteo ;
Capitanio, Selene ;
Donegani, Maria Isabella ;
Zanardi, Elisa ;
Miceli, Alberto ;
Murialdo, Roberto ;
Raffa, Stefano ;
Tomasello, Laura ;
Vitti, Martina ;
Cavo, Alessia ;
Catalano, Fabio ;
Mencoboni, Manlio ;
Ceppi, Marcello ;
Marini, Cecilia ;
Fornarini, Giuseppe ;
Boccardo, Francesco ;
Sambuceti, Gianmario ;
Morbelli, Silvia .
CANCERS, 2020, 12 (01)
[9]   Increased myocardial 18F-FDG uptake as a marker of Doxorubicin-induced oxidative stress [J].
Bauckneht, Matteo ;
Pastorino, Fabio ;
Castellani, Patrizia ;
Cossu, Vanessa ;
Orengo, Anna Maria ;
Piccioli, Patrizia ;
Emionite, Laura ;
Capitanio, Selene ;
Yosifov, Nikola ;
Bruno, Silvia ;
Lazzarini, Edoardo ;
Ponzoni, Mirco ;
Ameri, Pietro ;
Rubartelli, Anna ;
Ravera, Silvia ;
Morbelli, Silvia ;
Sambuceti, Gianmario ;
Marini, Cecilia .
JOURNAL OF NUCLEAR CARDIOLOGY, 2020, 27 (06) :2183-2194
[10]   A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction [J].
Benvenuto, Federico ;
Piana, Michele ;
Campi, Cristina ;
Massone, Anna Maria .
ASTROPHYSICAL JOURNAL, 2018, 853 (01)