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

Theranostics revolution in prostate cancer: Basics, clinical applications, open issues and future perspectives

In the last years, theranostics has expanded the therapeutic options available for prostate cancer patients. In this review, we explore this dynamic field and its potential to revolutionize precision medicine for prostate cancer. We delve into the foundational principles, clinical applications, and emerging opportunities, emphasizing the potential synergy between radioligand therapy and other systemic treatments. Additionally, we address the ongoing challenges, including optimizing patient selection, assessing treatment responses, and determining the role of theranostics within the broader landscape of prostate cancer treatment.

Kinetic 18F-FDG PET/CT imaging of hepatocellular carcinoma: a dual input four-compartment model

BACKGROUND

The endoplasmic reticulum plays an important role in glucose metabolism and has not been explored in the kinetic estimation of hepatocellular carcinoma (HCC) via 18F-fluoro-2-deoxy-D-glucose PET/CT.

METHODS

A dual-input four-compartment (4C) model, regarding endoplasmic reticulum was preliminarily used for kinetic estimation to differentiate 28 tumours from background liver tissue from 24 patients with HCC. Moreover, parameter images of the 4C model were generated from one patient with negative findings on conventional metabolic PET/CT.

RESULTS

Compared to the dual-input three-compartment (3C) model, the 4C model has better fitting quality, a close transport rate constant (K1) and a dephosphorylation rate constant (k6/k4), and a different removal rate constant (k2) and phosphorylation rate constant (k3) in HCC and background liver tissue. The K1, k2, k3, and hepatic arterial perfusion index (HPI) from the 4C model and k3, HPI, and volume fraction of blood (Vb) from the 3C model were significantly different between HCC and background liver tissues (all P < 0.05). Meanwhile, the 4C model yielded additional kinetic parameters for differentiating HCC. The diagnostic performance of the top ten genes from the most to least common was HPI(4C), Vb(3C), HPI(3C), SUVmax, k5(4C), k3(3C), k2(4C), v(4C), K1(4C) and Vb(4C). Moreover, a patient who showed negative findings on conventional metabolic PET/CT had positive parameter images in the 4C model.

CONCLUSIONS

The 4C model with the endoplasmic reticulum performed better than the 3C model and produced additional useful parameters in kinetic estimation for differentiating HCC from background liver tissue.

Change of glucometabolic activity per PSMA expression predicts survival in mCRPC patients non-responding to PSMA radioligand therapy: introducing a novel dual imaging biomarker

Purpose

The value of [18F]fluorodeoxyglucose ([18F]FDG) PET/CT in monitoring prostate-specific membrane antigen (PSMA) targeted radioligand therapy (RLT) is still unclear. The aim of this study was to identify appropriate prognostic dynamic parameters derived from baseline and follow-up [18F]FDG and dual [18F]FDG/[68Ga]Ga-PSMA-11 PET/CT for monitoring early non-responding mCRPC patients undergoing PSMA-RLT.

Methods

Twenty-three mCRPC patients of a prospective registry (NCT04833517), who were treated with [177Lu]Lu-PSMA-617 RLT and classified as early non-responders were included in this study. All patients received dual PET/CT imaging with [18F]FDG and [68Ga]Ga-PSMA-11 at baseline and after median two cycles of RLT. We tested potential biomarkers representing the "change of glucometabolic activity (cGA)" and "change of glucometabolic activity in relation to PSMA expression (cGAP)" composed of established parameters on [18F]FDG PET/CT as SUVmax, cumulative SUV of five lesions (SUV5), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) and its corresponding parameters on [68Ga]Ga-PSMA-11 PET/CT, respectively, for association with overall survival (OS).

Results

Kaplan-Meier analyses showed no significant association with OS for each tested cGA (cGASUVmaxp = 0.904, cGASUV5, p = 0.747 cGAMTVp = 0.682 and cGATLGp = 0.700), likewise the dual imaging biomarkers cGAPSUVmax (p = 0.136), cGAPSUV5 (p = 0.097), and cGAPTV (p = 0.113) failed significance. In contrast, cGAPTL, which is based on TLG and total lesion PSMA (TLP) showed a significant association with OS (p = 0.004). Low cGAPTL (cut-off 0.7) was associated with significant longer survival (17.6 vs. 12.9 months).

Conclusion

The novel biomarker cGAPTL, which represents the temporal change of whole-body TLG normalized by TLP, predicts overall survival in the challenging cohort of patients non-responding to PSMA-RLT.

PSMA PET/CT in Castration-Resistant Prostate Cancer: Myth or Reality?

BACKGROUND

prostate-specific membrane antigen (PSMA) ligand PET has been recently incorporated into international guidelines for several different indications in prostate cancer (PCa) patients. However, there are still some open questions regarding the role of PSMA ligand PET in castration-resistant prostate cancer (CRPC). The aim of this work is to assess the clinical value of PSMA ligand PET/CT in patients with CRPC.

RESULTS

PSMA ligand PET has demonstrated higher detection rates in comparison to conventional imaging and allows for a significant reduction in the number of M0 CRPC patients. However, its real impact on patients' prognosis is still an open question. Moreover, in CRPC patients, PSMA ligand PET presents some sensitivity and specificity limitations. Due to its heterogeneity, CRPC may present a mosaic of neoplastic clones, some of which could be PSMA-/FDG+, or vice versa. Likewise, unspecific bone uptake (UBU) and second primary neoplasms (SNPs) overexpressing PSMA in the neoangiogenic vessels represent potential specificity issues. Integrated multi-tracer imaging (PSMA ligand and [18F]FDG PET) together with a multidisciplinary discussion could allow for reaching the most accurate evaluation of each patient from a precision medicine point of view.

Glycometabolic reprogramming in cementoblasts: A vital target for enhancing cell mineralization

Cementum, a constituent part of periodontal tissues, has important adaptive and reparative functions. It serves to attach the tooth to alveolar bone and acts as a barrier delimit epithelial growth and bacteria evasion. A dynamic and highly responsive cementum is essential for maintaining occlusal relationships and the integrity of the root surface. It is a thin layer of mineralized tissue mainly produced by cementoblasts. Cementoblasts are osteoblast-like cells essential for the restoration of periodontal tissues. In recent years, glucose metabolism has been found to be critical in bone remodeling and osteoblast differentiation. However, the glucose metabolism of cementoblasts remains incompletely understood. First, immunohistochemistry staining and in vivo tracing with 18 F-fluorodeoxyglucose (18 F-FDG) revealed significantly higher glucose metabolism in cementum formation. To test the bioenergetic pathways of cementoblast differentiation, we compared the bioenergetic profiles of mineralized and unmineralized cementoblasts. As a result, we observed a significant increase in the consumption of glucose and production of lactate, coupled with the higher expression of glycolysis-related genes. However, the expression of oxidative phosphorylation-related genes was downregulated. The verified results were consistent with the RNA sequencing results. Likewise, targeted energy metabolomics shows that the levels of glycolytic metabolites were significantly higher in the mineralized cementoblasts. Seahorse assays identified an increase in glycolytic flux and reduced oxygen consumption during cementoblast mineralization. Apart from that, we also found that lactate dehydrogenase A (LDHA), a key glycolysis enzyme, positively regulates the mineralization of cementoblasts. In summary, cementoblasts mainly utilized glycolysis rather than oxidative phosphorylation during the mineralization process.

[18F]-FDHT PET for the Imaging of Androgen Receptor in Prostate and Breast Cancer: A Systematic Review

The aim of this systematic review is to provide a comprehensive overview of the role of fluoro-5α-dihydrotestosterone ([18F]-FDHT) for the in vivo imaging of androgen receptors (AR) through positron emission tomography (PET) in metastatic breast (mBC) and metastatic castration-resistant prostate cancer (mCRPC). Relevant studies published from 2013 up to May 2023 were selected by searching Scopus, PubMed and Web of Science. The selected imaging studies were analyzed using a modified version of the critical Appraisal Skills Programme (CASP). Eleven studies encompassing 321 patients were selected. Seven of the eleven selected papers included 266 subjects (82.2%) affected by mCRPC, while four encompassed 55 (17.2%) patients affected by mBC. [18F]-FDHT PET showed a satisfying test/retest reproducibility, and when compared to a histochemical analysis, it provided encouraging results for in vivo AR quantification both in mCRPC and mBC. [18F]-FDHT PET had a prognostic relevance in mCRPC patients submitted to AR-targeted therapy, while a clear association between [18F]-FDHT uptake and the bicalutamide response was not observed in women affected by AR-positive mBC. Further studies are needed to better define the role of [18F]-FDHT PET, alone or in combination with other tracers (i.e., [18F]-FDG/[18F]-FES), for patients' selection and monitoring during AR-targeted therapy, especially in the case of mBC.

[18F]FDG PET-TC radiomics and machine learning in the evaluation of prostate incidental uptake

AIM

To evaluate the relevance of incidental prostate [18F]FDG uptake (IPU) and to explore the potential of radiomics and machine learning (ML) to predict prostate cancer (PCa).

METHODS

We retrieved [18F]FDG PET/CT scans with evidence of IPU performed in two institutions between 2015 and 2021. Patients were divided into PCa and non-PCa, according to the biopsy. Clinical and PET/CT-derived information (comprehensive of radiomic analysis) were acquired. Five ML models were developed and their performance in discriminating PCa vs non-PCa IPU was evaluated. Radiomic analysis was investigated to predict ISUP Grade.

RESULTS

Overall, 56 IPU were identified and 31 patients performed prostate biopsy. Eighteen of those were diagnosed as PCa. Only PSA and radiomic features (eight from CT and nine from PET images, respectively) showed statistically significant difference between PCa and non-PCa patients. Eight features were found to be robust between the two institutions. CT-based ML models showed good performance, especially in terms of negative predictive value (NPV 0.733-0.867). PET-derived ML models results were less accurate except the Random Forest model (NPV = 0.933). Radiomics could not accurately predict ISUP grade.

CONCLUSIONS

Paired with PSA, radiomic analysis seems to be promising to discriminate PCa/non-PCa IPU. ML could be a useful tool to identify non-PCa IPU, avoiding further investigations.