PSMA-Targeted Radiopharmaceuticals for Prostate Cancer Diagnosis and Therapy.

ABSTRACT: Prostate cancer (PCa) is the most common noncutaneous malignancy in men. Until recent years, accurate imaging of men with newly diagnosed PCa, or recurrent or low-volume metastatic disease, was limited. Further, therapeutic options for men with advanced, metastatic, castration-resistant disease were increasingly limited as a result of increasing numbers of systemic therapies being combined in the upfront metastatic setting. The advent of urea-based, small-molecule inhibitors of prostate-specific membrane antigen (PSMA) has partially addressed those shortcomings in diagnosis and therapy of PCa. On the diagnostic side, there are multiple pivotal phase III trials with several different agents having demonstrated utility in the initial staging setting, with generally modest sensitivity but very high specificity for determining otherwise-occult pelvic nodal involvement. That latter statistic drives the utility of the scan by allowing imaging interpreters to read with very high sensitivity while maintaining a robust specificity. Other pivotal phase III trials have demonstrated high detection efficiency in patients with biochemical failure, with high positive predictive value at the lesion level, opening up possible new avenues of therapy such as metastasis-directed therapy. Beyond the diagnostic aspects of PSMA-targeted radiotracers, the same urea-based chemical scaffolds can be altered to deliver therapeutic isotopes to PCa cells that express PSMA. To date, one such agent, when combined with best standard-of-care therapy, has demonstrated an ability to improve overall survival, progression-free survival, and freedom from skeletal events relative to best standard-of-care therapy alone in men with metastatic, castration-resistant PCa who are post chemotherapy. Within the current milieu, there are a number of important future directions including the use of artificial intelligence to better leverage diagnostic findings, further medicinal chemistry refinements to the urea-based structure that may allow improved tumor targeting and decreased toxicities, and the incorporation of new radionuclides that may better balance efficacy with toxicities than those nuclides that are available.

An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer.

Uptake segmentation and classification on PSMA PET/CT are important for automating whole-body tumor burden determinations. We developed and evaluated an automated deep learning (DL)-based framework that segments and classifies uptake on PSMA PET/CT. We identified 193 [18F] DCFPyL PET/CT scans of patients with biochemically recurrent prostate cancer from two institutions, including 137 [18F] DCFPyL PET/CT scans for training and internally testing, and 56 scans from another institution for external testing. Two radiologists segmented and labelled foci as suspicious or non-suspicious for malignancy. A DL-based segmentation was developed with two independent CNNs. An anatomical prior guidance was applied to make the DL framework focus on PSMA-avid lesions. Segmentation performance was evaluated by Dice, IoU, precision, and recall. Classification model was constructed with multi-modal decision fusion framework evaluated by accuracy, AUC, F1 score, precision, and recall. Automatic segmentation of suspicious lesions was improved under prior guidance, with mean Dice, IoU, precision, and recall of 0.700, 0.566, 0.809, and 0.660 on the internal test set and 0.680, 0.548, 0.749, and 0.740 on the external test set. Our multi-modal decision fusion framework outperformed single-modal and multi-modal CNNs with accuracy, AUC, F1 score, precision, and recall of 0.764, 0.863, 0.844, 0.841, and 0.847 in distinguishing suspicious and non-suspicious foci on the internal test set and 0.796, 0.851, 0.865, 0.814, and 0.923 on the external test set. DL-based lesion segmentation on PSMA PET is facilitated through our anatomical prior guidance strategy. Our classification framework differentiates suspicious foci from those not suspicious for cancer with good accuracy.

Comparison of Multiple Segmentation Methods for Volumetric Delineation of Primary Prostate Cancer with Prostate-Specific Membrane Antigen-Targeted 18F-DCFPyL PET/CT.

This study aimed to assess the accuracy of intraprostatic tumor volume measurements on prostate-specific membrane antigen-targeted 18F-DCFPyL PET/CT made with various segmentation methods. An accurate understanding of tumor volumes versus segmentation techniques is critical for therapy planning, such as radiation dose volume determination and response assessment. Methods: Twenty-five men with clinically localized, high-risk prostate cancer were imaged with 18F-DCFPyL PET/CT before radical prostatectomy. The tumor volumes and tumor-to-prostate ratios (TPRs) of dominant intraprostatic foci of uptake were determined using semiautomatic segmentation (applying SUVmax percentage [SUV%] thresholds of SUV30%-SUV70%), adaptive segmentation (using adaptive segmentation percentage [A%] thresholds of A30%-A70%), and manual contouring. The histopathologic tumor volume (TV-Histo) served as the reference standard. The significance of differences between TV-Histo and PET-based tumor volume were assessed using the paired-sample Wilcoxon signed-rank test. The Spearman correlation coefficient was used to establish the strength of the association between TV-Histo and PET-derived tumor volume. Results: Median TV-Histo was 2.03 cm3 (interquartile ratio [IQR], 1.16-3.36 cm3), and median TPR was 10.16%. The adaptive method with an A40% threshold most closely determined the tumor volume, with a median difference of +0.19 (IQR, -0.71 to +2.01) and a median relative difference of +7.6%. The paired-sample Wilcoxon test showed no significant difference in PET-derived tumor volume and TV-Histo using A40%, A50%, SUV40%, and SUV50% threshold segmentation algorithms (P > 0.05). For both threshold-based segmentation methods, use of higher thresholds (e.g., SUV60% or SUV70% and A50%-A70%) resulted in underestimation of tumor volumes, and use of lower thresholds (e.g., SUV30% or SUV40% and A30%) resulted in overestimation of tumor volumes relative to TV-Histo and TPR. Manual segmentation overestimated the tumor volume, with a median difference of +2.49 (IQR, 0.42-4.11) and a median relative difference of +130%. Conclusion: Segmentation of intraprostatic tumor volume and TPR with an adaptive segmentation approach most closely approximates TV-Histo. This information might be used to guide the primary treatment of men with clinically localized, high-risk prostate cancer.

A Practical Guide to the Pearls and Pitfalls of PSMA PET Imaging.

Prostate-specific membrane antigen (PSMA)-targeted PET agents have revolutionized the care of patients with prostate cancer, supplanting traditional methods of imaging prostate cancer, and improving the selection and delivery of therapies. This has led to a rapid expansion in both the number of PSMA PET scans performed and the imaging specialists required to interpret those scans. To aid those imagers and clinicians who are new to the interpretation of PSMA PET, this review provides an overview of the interpretation of PSMA PET/CT imaging and pearls for overcoming commonly encountered pitfalls. We discuss the physiologic distribution of the clinically available PSMA-targeted radiotracers, the commonly encountered patterns of prostate cancer spread, as well as the benign and malignant mimics of prostate cancer. Additionally, we review the standardized PSMA PET reporting systems and the role of PSMA in selecting appropriate patients for PSMA-targeted therapies.

Evaluating Scalable Supervised Learning for Synthesize-on-Demand Chemical Libraries.

Traditional small-molecule drug discovery is a time-consuming and costly endeavor. High-throughput chemical screening can only assess a tiny fraction of drug-like chemical space. The strong predictive power of modern machine-learning methods for virtual chemical screening enables training models on known active and inactive compounds and extrapolating to much larger chemical libraries. However, there has been limited experimental validation of these methods in practical applications on large commercially available or synthesize-on-demand chemical libraries. Through a prospective evaluation with the bacterial protein-protein interaction PriA-SSB, we demonstrate that ligand-based virtual screening can identify many active compounds in large commercial libraries. We use cross-validation to compare different types of supervised learning models and select a random forest (RF) classifier as the best model for this target. When predicting the activity of more than 8 million compounds from Aldrich Market Select, the RF substantially outperforms a naïve baseline based on chemical structure similarity. 48% of the RF's 701 selected compounds are active. The RF model easily scales to score one billion compounds from the synthesize-on-demand Enamine REAL database. We tested 68 chemically diverse top predictions from Enamine REAL and observed 31 hits (46%), including one with an IC50 value of 1.3 µM.

Image acquisition and interpretation of 18F-DCFPyL (piflufolastat F 18) PET/CT: How we do it.

Prostate-specific membrane antigen (PSMA)-targeted positron emission tomography (PET) is rapidly becoming widely accepted as the standard-of-care for imaging of men with prostate cancer. Labeled indications for regulatoryapproved agents include primary staging and recurrent disease in men at risk of metastases. The first commercial PSMA PET agent to become available was 18F-DCFPyL (piflufolastat F 18), a radiofluorinated small molecule with high-affinity for PSMA. The regulatory approval of 18F-DCFPyL hinged upon two key, multi-center, registration trials, OSPREY (patient population: highrisk primary staging) and CONDOR (patient population: biochemical recurrence). In this manuscript, we will (1) review key findings from the OSPREY and CONDOR trials, (2) discuss the clinical acquisition protocol we use for 18F-DCFPyL PET scanning, (3) present information on important pearls and pitfalls, (4) provide an overview of the PSMA reporting and data system (PSMA-RADS) interpretive framework, and (5) posit important future directions for research in PSMA PET. Our overall goal is to provide a brief introduction for practices and academic groups that are adopting 18F-DCFPyL PET scans for use in their patients with prostate cancer.

Piflufolastat F-18 (18F-DCFPyL) for PSMA PET imaging in prostate cancer .

INTRODUCTION: Accurate imaging is essential for staging prostate cancer and guiding management decisions. Conventional imaging modalities are hampered by a limited sensitivity for metastatic disease. Nearly all prostate cancers express prostate-specific membrane antigen (PSMA) and 18F-DCFPyL (piflufolastat F 18) is a new FDA-approved positron emission tomography (PET) agent that targets PSMA for improved staging of prostate cancer. AREAS COVERED: This article provides an overview of PSMA, the mechanism of action of 18F-DCFPyL, and compares the performance of 18F-DCFPyL to conventional prostate imaging modalities. Current prostate cancer imaging guidelines are reviewed, as well as what changes can be expected in the future with increased access to PSMA-PET. EXPERT OPINION: The OSPREY and CONDOR clinical trials have demonstrated the superiority of 18F-DCFPyL over conventional imaging modalities for the staging and restaging of prostate cancer. The remarkable diagnostic accuracy of PSMA-PET is reshaping prostate cancer imaging and the modularity of these agents hint at exciting new diagnostic and therapeutic opportunities that have the potential to improve the care of patients with prostate cancer as a whole. .

Diagnostic Accuracy and Failure Mode Analysis of a Deep Learning Algorithm for the Detection of Intracranial Hemorrhage.

OBJECTIVE: To determine the institutional diagnostic accuracy of an artificial intelligence (AI) decision support systems (DSS), Aidoc, in diagnosing intracranial hemorrhage (ICH) on noncontrast head CTs and to assess the potential generalizability of an AI DSS. METHODS: This retrospective study included 3,605 consecutive, emergent, adult noncontrast head CT scans performed between July 1, 2019, and December 30, 2019, at our institution (51% female subjects, mean age of 61 ± 21 years). Each scan was evaluated for ICH by both a certificate of added qualification certified neuroradiologist and Aidoc. We determined the diagnostic accuracy of the AI model and performed a failure mode analysis with quantitative CT radiomic image characterization. RESULTS: Of the 3,605 scans, 349 cases of ICH (9.7% of studies) were identified. The neuroradiologist and Aidoc interpretations were concordant in 96.9% of cases and the overall sensitivity, specificity, positive predictive value, and negative predictive value were 92.3%, 97.7%, 81.3%, and 99.2%, respectively, with positive predictive values unexpectedly lower than in previously reported studies. Prior neurosurgery, type of ICH, and number of ICHs were significantly associated with decreased model performance. Quantitative image characterization with CT radiomics failed to reveal significant differences between concordant and discordant studies. DISCUSSION: This study revealed decreased diagnostic accuracy of an AI DSS at our institution. Despite extensive evaluation, we were unable to identify the source of this discrepancy, raising concerns about the generalizability of these tools with indeterminate failure modes. These results further highlight the need for standardized study design to allow for rigorous and reproducible site-to-site comparison of emerging deep learning technologies.

High-Throughput Screening to Identify Inhibitors of SSB-Protein Interactions.

The bacterial single-stranded DNA-binding protein (SSB) uses an acidic C-terminal tail to interact with over a dozen proteins, acting as a genome maintenance hub. These SSB-protein interactions are essential, as mutations to the C-terminal tail that disrupt these interactions are lethal in Escherichia coli. While the roles of individual SSB-protein interactions have been dissected with mutational studies, small-molecule inhibitors of these interactions could serve as valuable research tools and have potential as novel antimicrobial agents. This chapter describes a high-throughput screening campaign used to identify inhibitors of SSB-protein interactions. A screen targeting the PriA-SSB interface from Klebsiella pneumoniae is presented as an example, but the methods may be adapted to target nearly any SSB interaction.

Incidental discovery of a rare right ventricular aneurysm.

Three types of cardiac outpouchings are encountered on cardiovascular imaging: diverticula, aneurysms and pseudoaneurysms. The underlying physiology, imaging findings, risk of rupture, and optimal treatment varies for each and a correct diagnosis is critical. We report a case of a rare, incidentally discovered right ventricular aneurysm that was characterized by transthoracic echocardiogram, computed tomography, and cardiac MRI. The types of cardiac outpouchings are reviewed, and we discuss the selection of imaging modality, keys to distinguishing the outpouchings, and management strategies.

E. coli Rep helicase and RecA recombinase unwind G4 DNA and are important for resistance to G4-stabilizing ligands.

G-quadruplex (G4) DNA structures can form physical barriers within the genome that must be unwound to ensure cellular genomic integrity. Here, we report unanticipated roles for the Escherichia coli Rep helicase and RecA recombinase in tolerating toxicity induced by G4-stabilizing ligands in vivo. We demonstrate that Rep and Rep-X (an enhanced version of Rep) display G4 unwinding activities in vitro that are significantly higher than the closely related UvrD helicase. G4 unwinding mediated by Rep involves repetitive cycles of G4 unfolding and refolding fueled by ATP hydrolysis. Rep-X and Rep also dislodge G4-stabilizing ligands, in agreement with our in vivo G4-ligand sensitivity result. We further demonstrate that RecA filaments disrupt G4 structures and remove G4 ligands in vitro, consistent with its role in countering cellular toxicity of G4-stabilizing ligands. Together, our study reveals novel genome caretaking functions for Rep and RecA in resolving deleterious G4 structures.

Antigenic Variation in Neisseria gonorrhoeae Occurs Independently of RecQ-Mediated Unwinding of the pilE G Quadruplex.

The obligate human pathogen Neisseria gonorrhoeae alters its cell surface antigens to evade the immune system in a process known as antigenic variation (AV). During pilin AV, portions of the expressed pilin gene (pilE) are replaced with segments of silent pilin genes (pilS) through homologous recombination. The pilE-pilS exchange is initiated by formation of a parallel guanine quadruplex (G4) structure near the pilE gene, which recruits the homologous recombination machinery. The RecQ helicase, which has been proposed to aid AV by unwinding the pilE G4 structure, is an important component of this machinery. However, RecQ also promotes homologous recombination through G4-independent duplex DNA unwinding, leaving the relative importance of its G4 unwinding activity unclear. Previous investigations revealed a guanine-specific pocket (GSP) on the surface of RecQ that is required for G4, but not duplex, DNA unwinding. To determine whether RecQ-mediated G4 resolution is required for AV, N. gonorrhoeae strains that encode a RecQ GSP variant that cannot unwind G4 DNA were created. In contrast to the hypothesis that G4 unwinding by RecQ is important for AV, the RecQ GSP variant N. gonorrhoeae strains had normal AV levels. Analysis of a purified RecQ GSP variant confirmed that it retained duplex DNA unwinding activity but had lost its ability to unwind antiparallel G4 DNA. Interestingly, neither the GSP-deficient RecQ variant nor the wild-type RecQ could unwind the parallel pilE G4 nor the prototypical c-myc G4. Based on these results, we conclude that N. gonorrhoeae AV occurs independently of RecQ-mediated pilE G4 resolution.IMPORTANCE The pathogenic bacteria Neisseria gonorrhoeae avoids clearance by the immune system through antigenic variation (AV), the process by which immunogenic surface features of the bacteria are exchanged for novel variants. RecQ helicase is critical in AV and its role has been proposed to stem from its ability to unwind a DNA secondary structure known as a guanine quadruplex (G4) that is central to AV. In this work, we demonstrate that the role of RecQ in AV is independent of its ability to resolve G4s and that RecQ is incapable of unwinding the G4 in question. We propose a new model of RecQ's role in AV where the G4 might recruit or orient RecQ to facilitate homologous recombination.

Practical Model Selection for Prospective Virtual Screening.

Virtual (computational) high-throughput screening provides a strategy for prioritizing compounds for experimental screens, but the choice of virtual screening algorithm depends on the data set and evaluation strategy. We consider a wide range of ligand-based machine learning and docking-based approaches for virtual screening on two protein-protein interactions, PriA-SSB and RMI-FANCM, and present a strategy for choosing which algorithm is best for prospective compound prioritization. Our workflow identifies a random forest as the best algorithm for these targets over more sophisticated neural network-based models. The top 250 predictions from our selected random forest recover 37 of the 54 active compounds from a library of 22,434 new molecules assayed on PriA-SSB. We show that virtual screening methods that perform well on public data sets and synthetic benchmarks, like multi-task neural networks, may not always translate to prospective screening performance on a specific assay of interest.

A guanine-flipping and sequestration mechanism for G-quadruplex unwinding by RecQ helicases.

Homeostatic regulation of G-quadruplexes (G4s), four-stranded structures that can form in guanine-rich nucleic acids, requires G4 unwinding helicases. The mechanisms that mediate G4 unwinding remain unknown. We report the structure of a bacterial RecQ DNA helicase bound to resolved G4 DNA. Unexpectedly, a guanine base from the unwound G4 is sequestered within a guanine-specific binding pocket. Disruption of the pocket in RecQ blocks G4 unwinding, but not G4 binding or duplex DNA unwinding, indicating its essential role in structure-specific G4 resolution. A novel guanine-flipping and sequestration model that may be applicable to other G4-resolving helicases emerges from these studies.

Development of Protein-Protein Interaction Inhibitors for the Treatment of Infectious Diseases.

Protein-protein interaction (PPI) inhibitors are a rapidly expanding class of therapeutics. Recent advances in our understanding of PPIs and success of early examples of PPI inhibitors demonstrate the feasibility of targeting PPIs. This review summarizes the techniques used for the discovery and optimization of a diverse set PPI inhibitors, focusing on the development of PPI inhibitors as new antibacterial and antiviral agents. We close with a summary of the advances responsible for making PPI inhibitors realistic targets for therapeutic intervention and brief outlook of the field.

A High-Throughput Screening Strategy to Identify Inhibitors of SSB Protein-Protein Interactions in an Academic Screening Facility.

Antibiotic-resistant bacterial infections are increasingly prevalent worldwide, and there is an urgent need for novel classes of antibiotics capable of overcoming existing resistance mechanisms. One potential antibiotic target is the bacterial single-stranded DNA binding protein (SSB), which serves as a hub for DNA repair, recombination, and replication. Eight highly conserved residues at the C-terminus of SSB use direct protein-protein interactions (PPIs) to recruit more than a dozen important genome maintenance proteins to single-stranded DNA. Mutations that disrupt PPIs with the C-terminal tail of SSB are lethal, suggesting that small-molecule inhibitors of these critical SSB PPIs could be effective antibacterial agents. As a first step toward implementing this strategy, we have developed orthogonal high-throughput screening assays to identify small-molecule inhibitors of the Klebsiella pneumonia SSB-PriA interaction. Hits were identified from an initial screen of 72,474 compounds using an AlphaScreen (AS) primary screen, and their activity was subsequently confirmed in an orthogonal fluorescence polarization (FP) assay. As an additional control, an FP assay targeted against an unrelated eukaryotic PPI was used to confirm specificity for the SSB-PriA interaction. Nine potent and selective inhibitors produced concentration-response curves with IC50 values of <40 µM, and two compounds were observed to directly bind to PriA, demonstrating the success of this screen strategy.

A High-Throughput Screening Strategy to Identify Protein-Protein Interaction Inhibitors That Block the Fanconi Anemia DNA Repair Pathway.

Induction of the Fanconi anemia (FA) DNA repair pathway is a common mechanism by which tumors evolve resistance to DNA crosslinking chemotherapies. Proper execution of the FA pathway requires interaction between the FA complementation group M protein (FANCM) and the RecQ-mediated genome instability protein (RMI) complex, and mutations that disrupt FANCM/RMI interactions sensitize cells to DNA crosslinking agents. Inhibitors that block FANCM/RMI complex formation could be useful therapeutics for resensitizing tumors that have acquired chemotherapeutic resistance. To identify such inhibitors, we have developed and validated high-throughput fluorescence polarization and proximity assays that are sensitive to inhibitors that disrupt interactions between the RMI complex and its binding site on FANCM (a peptide referred to as MM2). A pilot screen of 74,807 small molecules was performed using the fluorescence polarization assay. Hits from the primary screen were further tested using the proximity assay, and an orthogonal proximity assay was used to assess inhibitor selectivity. Direct physical interaction between the RMI complex and the most selective inhibitor identified through the screening process was measured by surface plasmon resonance and isothermal titration calorimetry. Observation of direct binding by this small molecule validates the screening protocol.

Synthesis of Macrocyclic Polymers Formed via Intramolecular Radical Trap-Assisted Atom Transfer Radical Coupling.

The synthesis of cyclic polystyrene (PSt) with an alkoxyamine functionality has been accomplished by intramolecular radical coupling in the presence of a nitroso radical trap. Linear α,ω-dibrominated polystyrene, produced by the atom transfer radical polymerization (ATRP) of styrene using a dibrominated initiator, was subjected to chain-end activation via the atom transfer radical coupling (ATRC) process under pseudodilute conditions in the presence of 2-methyl-2-nitrosopropane (MNP). This radical trap-assisted, intramolecular ATRC (RTA-ATRC) produced cyclic polymers in greater than 90% yields, possessing ⟨G⟩ values in the 0.8-0.9 range as determined by gel permeation chromatography (GPC). Thermal-induced opening of the cycles, made possible by the incorporated alkoxyamine, resulted in a return to the original apparent molecular weight, further supporting the formation of cyclic polymers in the RTA-ATRC reaction. Liquid chromatography-mass spectrometry (LC-MS) provided direct confirmation of the cyclic architecture and the incorporation of the nitroso group into the macrocycle. RTA-ATRC cyclizations carried out with faster rates of polymer addition into the redox active solution and/or in the presence of a much larger excess of MNP (up to a 250:1 ratio of MNP:C-Br chain end) still yielded cyclic polymers that contained alkoxyamine functionality.