Department of Health Sciences, University of Genoa, 16132, Genoa, Italy.
Nuclear Medicine Unit, IRCCS, Ospedale Policlinico San Martino, 16132, Genoa, Italy.
J Transl Med. 2023 Jan 4;21(1):3. doi: 10.1186/s12967-022-03846-1.
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.
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.
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).
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.
正电子发射断层扫描（PET）成像使用前列腺特异性膜抗原（PSMA）和氟脱氧葡萄糖（FDG），代表了前列腺癌（PCa）风险分层的有前途的生物标志物。我们验证了编码 PSMA 的基因和调节 FDG 细胞摄取的酶的表达是否是 PCa 的独立且可累加的预后因素。
从公开来源的数据库中检索到来自原发性 PCa 标本的参与葡萄糖代谢和 PSMA 调节的基因的 mRNA 表达，并使用整合的生物信息学方法进行分析。使用机器学习（ML）技术创建无进展生存（PFS）预测模型。使用具有不同侵袭性的原发性 PCa 细胞模型在体外比较 [18F]F-PSMA-1007 和 [18F]F-FDG 摄取动力学。进行共聚焦显微镜、免疫荧光染色和定量分析，以评估细胞内和细胞膜 PSMA 表达。
ML 分析确定了一个涉及四个葡萄糖代谢相关基因的预测功能网络：ALDOB、CTH、PARP2 和 SLC2A4。相比之下，PSMA 编码基因 FOLH1 的表达不能为模型提供任何可累加的预测价值。在细胞水平上，原发性 PCa 细胞增殖率和迁移能力的增加与 FDG 摄取增加和 PSMA 保留减少（与优先的细胞内定位平行）相关。
涉及四个葡萄糖代谢相关基因的功能网络的过度表达鉴定出了更高的疾病进展风险，这与 FDG PET 成像的公认预后价值一致。相比之下，PSMA PET 成像的预后价值独立于其编码基因 FOLH1 的表达。相反，它受到蛋白质与细胞膜的对接影响，调节其与示踪剂结合的可及性。
