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Near-infrared photoimmunotherapy (NIR-PIT) is a new cancer treatment that uses an antibody-photo-absorber conjugate (APC) composed of a targeting monoclonal antibody conjugated with a photoactivatable phthalocyanine-derivative dye, IRDye700DX (IR700). APCs injected into the body can bind to cancer cells where they are activated by local exposure to NIR light typically delivered by a NIR laser. NIR light alters the APC chemical conformation inducing damage to cancer cell membranes, resulting in necrotic cell death within minutes of light exposure. NIR-PIT selectivity kills cancer cells by immunogenic cell death (ICD) with minimal damage to adjacent normal cells thus, leading to rapid recovery by the patient. Moreover, since NIR-PIT induces ICD only on cancer cells, NIR-PIT initiates and activates antitumor host immunity that could be further enhanced when combined with immune checkpoint inhibition. NIR-PIT induces dramatic changes in the tumor vascularity causing the super-enhanced permeability and retention (SUPR) effect that dramatically enhances nanodrug delivery to the tumor bed. Currently, a worldwide Phase 3 study of NIR-PIT for recurrent or inoperable head and neck cancer patients is underway. In September 2020, the first APC and accompanying laser system were conditionally approved for clinical use in Japan. In this review, we introduce NIR-PIT and the SUPR effect and summarize possible applications of NIR-PIT in a variety of cancers.

To date, the delivery of nanosized therapeutic agents to cancers largely relies on the enhanced permeability and retention (EPR) effects that are caused by the leaky nature of cancer vasculature. Whereas leaky vessels are often found in mouse xenografts, nanosized agents have demonstrated limited success in humans due to the relatively small magnitude of the EPR effect in naturally occurring cancers. To achieve the superior delivery of nanosized agents, alternate methods of increasing permeability and retention are needed. Near-infrared photoimmunotherapy (NIR-PIT) is a recently reported therapy that relies on an antibody-photon absorber conjugate that binds to tumors and then is activated by light. NIR-PIT causes an increase in nanodrug delivery by up to 24-fold compared to untreated tumors in which only the EPR effect is present. This effect, termed super-EPR (SUPR), can enhance the delivery of a wide variety of nanosized agents, including nanoparticles, antibodies, and protein-binding small-molecular-weight agents into tumors. Therefore, taking advantage of the SUPR effect after NIR-PIT may be a promising avenue to use a wide variety of nanodrugs in a highly effective manner.

Abstract The discovery of fibroblast activation protein inhibitor positron emission tomography (FAPI-PET) has paved the way for a new class of PET tracers that target the tumor microenvironment (TME) rather than the tumor itself. Although 18F-fluorodeoxyglucose (FDG) is the most common PET tracer used in clinical imaging of cancer, multiple studies have now shown that the family of FAP ligands commonly outperform FDG in detecting cancers, especially those known to have lower uptake on FDG-PET. Moreover, FAPI-PET will have applications in benign fibrotic or inflammatory conditions. Thus, even while new FAPI-PET tracers are in development and applications are yet to enter clinical guidelines, a significant body of literature has emerged on FAPI-PET, suggesting it will have important clinical roles. This article summarizes the current state of clinical FAPI-PET imaging as well as potential uses as a theranostic agent.

Abstract Background Somatostatin receptor (SSR) targeting radiotracer 68Ga-DOTATATE is used for Positron Emission Tomography (PET)/Computed Tomography (CT) imaging to assess patients with Pheochromocytoma and paraganglioma (PPGL), rare types of Neuroendocrine tumor (NET) which can metastasize thereby becoming difficult to quantify. The goal of this study is to develop an artificial intelligence (AI) model for automated lesion segmentation on whole-body 3D DOTATATE-PET/CT and to automate the tumor burden calculation. 132 68Ga-DOTATATE PET/CT scans from 38 patients with metastatic and inoperable PPGL, were split into 70, and 62 scans, from 20, and 18 patients for training, and test sets, respectively. The training set was further divided into patient-stratified 5 folds for cross-validation. 3D-full resolution nnUNet configuration was trained with 5-fold cross-validation. The model’s detection performance was evaluated at both scan and lesion levels for the PPGL test set and two other clinical cohorts with NET (n = 9) and olfactory neuroblastoma (ONB, n = 5). Additionally, quantitative statistical analysis of PET parameters including SUVmax, total lesion uptake (TLU), and total tumor volume (TTV), was conducted. Results The nnUNet AI model achieved an average 5-fold validation dice similarity coefficient of 0.84 at the scan level. The model achieved dice similarity coefficients (DSC) of 0.88, 0.6, and 0.67 at the scan level, the sensitivity of 86%, 61.13%, and 61.64%, and a positive predictive value of 89%, 74%, and 86.54% at the lesion level for the PPGL test, NET and ONB cohorts, respectively. For PPGL cohorts, smaller lesions with low uptake were missed by the AI model (p

Since the development of fibroblast activation protein-targeted radiopharmaceuticals, 68Ga-fibroblast activation protein inhibitor (FAPI) PET/CT has been found to be suitable for detecting primary and metastatic lesions in many types of tumors. However, there is currently a lack of reliable data regarding the clinical impact of this family of probes. To address this gap, the present study aimed to analyze the clinical impact of 68Ga-FAPI PET/CT by examining a large cohort of patients with various tumors. Methods: In total, 226 patients (137 male and 89 female) were included in this retrospective analysis. Pancreatic cancer and head and neck cancers were the most common tumor types in this cohort. TNM stage and oncologic management were initially determined with gold standard imaging, and these results were compared with 68Ga-FAPI PET/CT. Changes were classified as major and minor. Results: For 42% of all patients, TNM stage was changed by 68Ga-FAPI PET/CT results. Most of these changes resulted in upstaging. A change in clinical management occurred in 117 of 226 patients. Although a major change in management occurred in only 12% of patients, there was a significant improvement in the ability to accurately plan radiation therapy. In general, the highest clinical impact of 68Ga-FAPI PET/CT imaging was found in patients with lung cancer, pancreatic cancer, and head and neck tumors. Conclusion: 68Ga-FAPI PET/CT is a promising imaging probe that has a significant impact on TNM stage and clinical management. 68Ga-FAPI PET/CT promises to be a crucial new technology that will improve on conventional radiologic imaging methods such as contrast-enhanced CT and contrast-enhanced MRI typically acquired for cancer staging.

Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The purpose of the study was to establish the clinical application of an in-house developed artificial intelligence (AI) image analysis workflow for automated detection of PTEN loss on digital images for identifying patients at risk of early recurrence and metastasis. Postsurgical tissue microarray sections from the Canary Foundation (n = 1264) stained with anti-PTEN antibody were evaluated independently by pathologist conventional visual scoring (cPTEN) and an automated AI-based image analysis pipeline (AI-PTEN). The relationship of PTEN evaluation methods with cancer recurrence and metastasis was analyzed using multivariable Cox proportional hazard and decision curve models. Both cPTEN scoring by the pathologist and quantification of PTEN loss by AI (high-risk AI-qPTEN) were significantly associated with shorter metastasis-free survival (MFS) in univariable analysis (cPTEN hazard ratio [HR], 1.54; CI, 1.07-2.21; P = .019; AI-qPTEN HR, 2.55; CI, 1.83-3.56; P < .001). In multivariable analyses, AI-qPTEN showed a statistically significant association with shorter MFS (HR, 2.17; CI, 1.49-3.17; P < .001) and recurrence-free survival (HR, 1.36; CI, 1.06-1.75; P = .016) when adjusting for relevant postsurgical clinical nomogram (Cancer of the Prostate Risk Assessment [CAPRA] postsurgical score [CAPRA-S]), whereas cPTEN does not show a statistically significant association (HR, 1.33; CI, 0.89-2; P = .2 and HR, 1.26; CI, 0.99-1.62; P = .063, respectively) when adjusting for CAPRA-S risk stratification. More importantly, AI-qPTEN was associated with shorter MFS in patients with favorable pathological stage and negative surgical margins (HR, 2.72; CI, 1.46-5.06; P = .002). Workflow also demonstrated enhanced clinical utility in decision curve analysis, more accurately identifying men who might benefit from adjuvant therapy postsurgery. This study demonstrates the clinical value of an affordable and fully automated AI-powered PTEN assessment for evaluating the risk of developing metastasis or disease recurrence after radical prostatectomy. Adding the AI-qPTEN assessment workflow to clinical variables may affect postoperative surveillance or management options, particularly in low-risk patients.

Regulatory T cells (Tregs) play a crucial role in mediating immunosuppression in the tumor microenvironment. Furthermore, Tregs contribute to the lack of efficacy and hyperprogressive disease upon Programmed cell death protein 1 (PD-1) blockade immunotherapy. Thus, Tregs are considered a promising therapeutic target, especially when combined with PD-1 blockade. However, systemic depletion of Tregs causes severe autoimmune adverse events, which poses a serious challenge to Treg-directed therapy. Here, we developed a novel treatment to locally and predominantly damage Tregs by near-infrared duocarmycin photorelease (NIR-DPR). In this technology, we prepared anti-CD25 F(ab’)2 conjugates, which site-specifically uncage duocarmycin in CD25-expressing cells upon exposure to NIR light. In vitro, CD25-targeted NIR-DPR significantly increased apoptosis of CD25-expressing HT2-A5E cells. When tumors were irradiated with NIR light in vivo, intratumoral CD25+ Treg populations decreased and Ki-67 and Interleukin-10 expression was suppressed, indicating impaired functioning of intratumoral CD25+ Tregs. CD25-targeted NIR-DPR suppressed tumor growth and improved survival in syngeneic murine tumor models. Of note, CD25-targeted NIR-DPR synergistically enhanced the efficacy of PD-1 blockade, especially in tumors with higher CD8+/Treg PD-1 ratios. Furthermore, the combination therapy induced significant anti-cancer immunity including maturation of dendritic cells, extensive intratumoral infiltration of cytotoxic CD8+ T cells, and increased differentiation into CD8+ memory T cells. Altogether, CD25-targeted NIR-DPR locally and predominantly targets Tregs in the tumor microenvironment and synergistically improves the efficacy of PD-1 blockade, suggesting that this combination therapy can be a rational anti-cancer combination immunotherapy.

Background and objective: Focal therapy (FT) is increasingly recognized as a promising approach for managing localized prostate cancer (PCa), notably reducing treatment-related morbidities. However, post-treatment anatomical changes present significant challenges for surveillance using current imaging techniques. This study aimed to evaluate the inter-reader agreement and efficacy of the Prostate Imaging after Focal Ablation (PI-FAB) scoring system in detecting clinically significant prostate cancer (csPCa) on post-FT multiparametric magnetic resonance imaging (mpMRI). Methods: A retrospective cohort study was conducted involving patients who underwent primary FT for localized csPCa between 2013 and 2023, followed by post-FT mpMRI and a prostate biopsy. Two expert genitourinary radiologists retrospectively evaluated post-FT mpMRI using PI-FAB. The key measures included inter-reader agreement of PI-FAB scores, assessed by quadratic weighted Cohen’s kappa (κ), and the system’s efficacy in predicting in-field recurrence of csPCa, with a PI-FAB score cutoff of 3. Additional diagnostic metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy were also evaluated. Key findings and limitations: Scans from 38 patients were analyzed, revealing a moderate level of agreement in PI-FAB scoring (κ = 0.56). Both radiologists achieved sensitivity of 93% in detecting csPCa, although specificity, PPVs, NPVs, and accuracy varied. Conclusions and clinical implications: The PI-FAB scoring system exhibited high sensitivity with moderate inter-reader agreement in detecting in-field recurrence of csPCa. Despite promising results, its low specificity and PPV necessitate further refinement. These findings underscore the need for larger studies to validate the clinical utility of PI-FAB, potentially aiding in standardizing post-treatment surveillance. Patient summary: Focal therapy has emerged as a promising approach for managing localized prostate cancer, but limitations in current imaging techniques present significant challenges for post-treatment surveillance. The Prostate Imaging after Focal Ablation (PI-FAB) scoring system showed high sensitivity for detecting in-field recurrence of clinically significant prostate cancer. However, its low specificity and positive predictive value necessitate further refinement. Larger, more comprehensive studies are needed to fully validate its clinical utility.

Per- and polyfluoroalkyl substances (PFAS) receive global attention due to their adverse effects on human health and the environment. Fish consumption is a major source of human PFAS exposure. The aim of this work was to address the lack of harmonization within legislations (in the EU and the USA) and highlight the level of PFAS in fish exposed to pollution from diffuse sources in the context of current safety thresholds. A non-exhaustive literature review was carried out to obtain PFAS concentrations in wild fish from the Norwegian mainland, Svalbard, the Netherlands, the USA, as well as sea regions (North Sea, English Channel, Atlantic Ocean), and farmed fish on the Dutch market. Median sum wet weight concentrations of PFOA, PFNA, PFHxS, and PFOS ranged between 0.1 µg kg−1 (farmed fish) and 22 µg kg−1 (Netherlands eel). Most concentrations fell below the EU environmental quality standard (EQSbiota) for PFOS (9.1 µg kg−1) and would not be defined as polluted in the EU. However, using recent tolerable intake or reference dose values in the EU and the USA revealed that even limited fish consumption would lead to exceedance of these thresholds – possibly posing a challenge for risk communication.

IntroductionProstate-specific membrane antigen (PSMA) is present in high amounts in salivary glands, but it is unclear whether labeled binders of PSMA are excreted in the saliva.MethodsTen patients with prostate cancer underwent whole-body [18F]DCFPyL PET/CT (NCT03181867), and saliva samples were collected between 0-120 minutes post-injection. [18F]DCFPyL salivary excretion was measured over 120 minutes and expressed as %ID/g. Protein-associated binding was estimated by the percentage of [18F]DCFPyL versus parent radiotracer.ResultsAll PET scans of 10 patients (69 ± 8 years) with histologically confirmed prostate cancer (PSA= 2.4 ± 2.4, and Gleason Grade = 6-9) showed high uptake of [18F]-DCFPyL in salivary glands while 8 patients demonstrated high uptake in the saliva at 45 minutes. The intact [18F]-DCFPyL (98%) was also confirmed in the saliva samples at 120 min with increasing salivary radioactivity between 30-120 min.ConclusionSystemically injected [18F]DCFPyL shows salivary gland uptake, an increasing amount of which is secreted in saliva over time and is not maximized by 120 minutes post-injection. Although probably insignificant for diagnostic studies, patients undergoing PSMA-targeted therapies should be aware of radioactivity in saliva.

Summary: Background: Noninvasive in vivo cell tracking is valuable in understanding the mechanisms that enhance anti-cancer immunity. We have recently developed a new method called phototruncation-assisted cell tracking (PACT), that uses photoconvertible cell tracking technology to detect in vivo cell migration. This method has the advantages of not requiring genetic engineering of cells and employing tissue-penetrant near-infrared light. Methods: We applied PACT to monitor the migration of immune cells between a tumour and its tumour-draining lymph node (TDLN) after near-infrared photoimmunotherapy (NIR-PIT). Findings: PACT showed a significant increase in the migration of dendritic cells (DCs) and macrophages from the tumour to the TDLN immediately after NIR-PIT. This migration by NIR-PIT was abrogated by inhibiting the sphingosine-1-phosphate pathway or Gαi signaling. These results were corroborated by intranodal immune cell profiles at two days post-treatment; NIR-PIT significantly induced DC maturation and increased and activated the CD8+ T cell population in the TDLN. Furthermore, PACT revealed that NIR-PIT significantly enhanced the migration of CD8+ T cells from the TDLN to the tumour four days post-treatment, which was consistent with the immunohistochemical assessment of tumour-infiltrating lymphocytes and tumour regression. Interpretation: Immune cells dramatically migrated between the tumour and TDLN following NIR-PIT, indicating its potential as an immune-stimulating therapy. Also, PACT is potentially applicable to a wide range of immunological research. Funding: This work was supported by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Centre for Cancer Research (grant number: ZIA BC011513 and ZIA BC011506).

PurposeThe underlying premise of prostate cancer active surveillance (AS) is that cancers likely to metastasize will be recognized and eliminated before cancer-related disease can ensue. Our study was designed to determine the prostate cancer upgrading rate when biopsy guided by magnetic resonance imaging (MRGBx) is used before entry and during AS.Materials and methodsThe cohort included 519 men with low- or intermediate-risk prostate cancer who enrolled in prospective studies (NCT00949819 and NCT00102544) between February 2008 and February 2020. Subjects were preliminarily diagnosed with Gleason Grade Group (GG) 1 cancer; AS began when subsequent MRGBx confirmed GG1 or GG2. Participants underwent confirmatory MRGBx (targeted and systematic) followed by surveillance MRGBx approximately every 12 to 24 months. The primary outcome was tumor upgrading to ≥GG3.ResultsUpgrading to ≥GG3 was found in 92 men after a median followup of 4.8 years (IQR 3.1-6.5) after confirmatory MRGBx. Upgrade-free probability after 5 years was 0.85 (95% CI 0.81-0.88). Cancer detected in a magnetic resonance imaging lesion at confirmatory MRGBx increased risk of subsequent upgrading during AS (HR 2.8; 95% CI 1.3-6.0), as did presence of GG2 (HR 2.9; 95% CI 1.1-8.2) In men who upgraded ≥GG3 during AS, upgrading was detected by targeted cores only in 27%, systematic cores only in 25% and both in 47%. In 63 men undergoing prostatectomy, upgrading from MRGBx was found in only 5 (8%).ConclusionsWhen AS begins and follows with MRGBx (targeted and systematic), upgrading rate (≥GG3) is greater when tumor is initially present within a magnetic resonance imaging lesion or when pathology is GG2 than when these features are absent.

This Special Topics Issue, “Imaging-based Diagnosis of Prostate Cancer—State of the Art”, of Diagnostics compiles 10 select articles [...]

Abstract Background Near infrared (NIR) photoimmunotherapy (PIT) is a new type of cancer treatment based on a monoclonal antibody (mAb)-NIR phthalocyanine dye, (IR700) conjugate. In vitro cancer-specific cell death occurs during NIR light exposure in cells previously incubated with mAb-IR700 conjugates. However, documenting rapid cell death in vivo is more difficult. Methods A luciferase-transfected breast cancer cell (epidermal growth factor receptor+, MDA-MB-468luc cells) was produced and used for both in vitro and in vivo experiments for monitoring the cell killing effect of PIT. After validation of cytotoxicity with NIR exposure up to 8 J/cm2in vitro, we employed an orthotopic breast cancer model of bilateral MDA-MB-468luc tumors in female athymic mice, which subsequently received a panitumumab-IR700 conjugate in vivo. One side was used as a control, while the other was treated with NIR light of dose ranging from 50 to 150 J/cm2. Bioluminescence imaging (BLI) was performed before and after PIT. Results Dose-dependent cell killing and regrowth was successfully monitored by the BLI signal in vitro. Although tumor sizes were unchanged, BLI signals decreased by >95% immediately after PIT in vivo when light intensity was high (>100 J/cm2), however, in mice receiving lower intensity NIR (50 J/cm2), tumors recurred with gradually increasing BLI signal. Conclusion PIT induced massive cell death of targeted tumor cells immediately after exposure of NIR light that was demonstrated with BLI in vivo.

ObjectiveTo demonstrate enabling multi-institutional training without centralizing or sharing the underlying physical data via federated learning (FL).Materials and methodsDeep learning models were trained at each participating institution using local clinical data, and an additional model was trained using FL across all of the institutions.ResultsWe found that the FL model exhibited superior performance and generalizability to the models trained at single institutions, with an overall performance level that was significantly better than that of any of the institutional models alone when evaluated on held-out test sets from each institution and an outside challenge dataset.DiscussionThe power of FL was successfully demonstrated across 3 academic institutions while avoiding the privacy risk associated with the transfer and pooling of patient data.ConclusionFederated learning is an effective methodology that merits further study to enable accelerated development of models across institutions, enabling greater generalizability in clinical use.

Abstract Background To assess the feasibility and early toxicity of selective, IMRT-based dose escalation (simultaneous integrated boost) to biopsy proven dominant intra-prostatic lesions visible on MRI. Methods Patients with localized prostate cancer and an abnormality within the prostate on endorectal coil MRI were eligible. All patients underwent a MRI-guided transrectal biopsy at the location of the MRI abnormality. Gold fiducial markers were also placed. Several days later patients underwent another MRI scan for fusion with the treatment planning CT scan. This fused MRI scan was used to delineate the region of the biopsy proven intra-prostatic lesion. A 3 mm expansion was performed on the intra-prostatic lesions, defined as a separate volume within the prostate. The lesion + 3 mm and the remainder of the prostate + 7 mm received 94.5/75.6 Gray (Gy) respectively in 42 fractions. Daily seed position was verified to be within 3 mm. Results Three patients were treated. Follow-up was 18, 6, and 3 months respectively. Two patients had a single intra-prostatic lesion. One patient had 2 intra-prostatic lesions. All four intra-prostatic lesions, with margin, were successfully targeted and treated to 94.5 Gy. Two patients experienced acute RTOG grade 2 genitourinary (GU) toxicity. One had grade 1 gastrointestinal (GI) toxicity. All symptoms completely resolved by 3 months. One patient had no acute toxicity. Conclusion These early results demonstrate the feasibility of using IMRT for simultaneous integrated boost to biopsy proven dominant intra-prostatic lesions visible on MRI. The treatment was well tolerated.

Abstract Background Germ-cell testicular cancer has not been definitively linked to any known hereditary cancer susceptibility disorder. Familial testicular cancer in the presence of other findings in affected and unaffected family members might indicate a previously-unidentified hereditary cancer syndrome. Case presentation The patient was diagnosed with a left testicular seminoma at age 28, and treated with left orchiectomy followed by adjuvant cobalt radiation. His family history is significant for testicular seminoma in his son, bladder cancer in his sister, and lipomatosis in his father. His evaluation as part of an etiologic study of familial testicular cancer revealed multiple colon polyps (adenomatous, hyperplastic, and hamartomatous) first found in his 50 s, multiple lipomas, multiple hyperpigmented skin lesions, left kidney cancer diagnosed at age 64, and a growth-hormone producing pituitary adenoma with associated acromegaly diagnosed at age 64. The patient underwent genetic testing for Cowden syndrome (PTEN gene), Carney complex (PRKAR1A gene), and multiple endocrine neoplasia syndrome type 1 (MEN1 gene); no deleterious mutations were identified. Discussion The constellation of benign and malignant neoplasms in the context of this patient's familial testicular cancer raised the possibility that these might be manifestations of a known hereditary susceptibility cancer syndrome; however, genetic testing for the three syndromes that were most likely to explain these findings did not show any mutation. Alternatively, this family's phenotype might represent a novel neoplasm susceptibility disorder. This possibility cannot be evaluated definitively on the basis of a single case report; additional observations and studies are necessary to investigate this hypothesis further.

IntroductionThe Prostate Cancer Foundation (PCF) convened a PCF prostate-specific membrane antigen (PSMA) Theranostics State of the Science Meeting on 18 November 2019, at Weill Cornell Medicine, New York, NY.MethodsThe meeting was attended by 22 basic, translational, and clinical researchers from around the globe, with expertise in PSMA biology, development and use of PSMA theranostics agents, and clinical trials. The goal of this meeting was to discuss the current state of knowledge, the most important biological and clinical questions, and critical next steps for the clinical development of PSMA positron emission tomography (PET) imaging agents and PSMA-targeted radionuclide agents for patients with prostate cancer.ResultsSeveral major topic areas were discussed including the biology of PSMA, the role of PSMA-targeted PET imaging in prostate cancer, the physics and performance of different PSMA-targeted PET imaging agents, the current state of clinical development of PSMA-targeted radionuclide therapy (RNT) agents, the role of dosimetry in PSMA RNT treatment planning, barriers and challenges in PSMA RNT clinical development, optimization of patient selection for PSMA RNT trials, and promising combination treatment approaches with PSMA RNT.DiscussionThis article summarizes the presentations from the meeting for the purpose of globally disseminating this knowledge to advance the use of PSMA-targeted theranostic agents for imaging and treatment of patients with prostate cancer.

Abstract Background The activities of MYC, the androgen receptor, and its associated pioneer factors demonstrate substantial reprogramming between early and advanced prostate cancer. Although previous studies have shown a shift in cellular metabolic requirements associated with prostate cancer progression, the epigenetic regulation of these processes is incompletely described. Here, we have integrated chromatin immunoprecipitation sequencing (ChIP-seq) and whole-transcriptome sequencing to identify novel regulators of metabolism in advanced prostate tumors characterized by elevated MYC activity. Results Using ChIP-seq against MYC, HOXB13, and AR in LNCaP cells, we observed redistribution of co-bound sites suggestive of differential KMT2A activity as a function of MYC expression. In a cohort of 177 laser-capture microdissected foci of prostate tumors, KMT2A expression was positively correlated with MYC activity, AR activity, and HOXB13 expression, but decreased with tumor grade severity. However, KMT2A expression was negatively correlated with these factors in 25 LuCaP patient-derived xenograft models of advanced prostate cancer and 99 laser-capture microdissected foci of metastatic castration-resistant prostate cancer. Stratified by KMT2A expression, ChIP-seq against AR and HOXB13 in 15 LuCaP patient-derived xenografts showed an inverse association with sites involving genes implicated in lipid metabolism, including the arachidonic acid metabolic enzyme PLA2G4F. LuCaP patient-derived xenograft models grown as organoids recapitulated the inverse association between KMT2A expression and fluorine-18 labeled arachidonic acid uptake in vitro. Conclusions Our study demonstrates that the epigenetic activity of transcription factor oncogenes exhibits a shift during prostate cancer progression with distinctive phenotypic effects on metabolism. These epigenetically driven changes in lipid metabolism may serve as novel targets for the development of novel imaging agents and therapeutics.

Biological nanoparticles, including viruses and extracellular vesicles (EVs), are of interest to many fields of medicine as biomarkers and mediators of or treatments for disease. However, exosomes and small viruses fall below the detection limits of conventional flow cytometers due to the overlap of particle-associated scattered light signals with the detection of background instrument noise from diffusely scattered light. To identify, sort, and study distinct subsets of EVs and other nanoparticles, as individual particles, we developed nanoscale Fluorescence Analysis and Cytometric Sorting (nanoFACS) methods to maximise information and material that can be obtained with high speed, high resolution flow cytometers. This nanoFACS method requires analysis of the instrument background noise (herein defined as the "reference noise"). With these methods, we demonstrate detection of tumour cell-derived EVs with specific tumour antigens using both fluorescence and scattered light parameters. We further validated the performance of nanoFACS by sorting two distinct HIV strains to >95% purity and confirmed the viability (infectivity) and molecular specificity (specific cell tropism) of biological nanomaterials sorted with nanoFACS. This nanoFACS method provides a unique way to analyse and sort functional EV- and viral-subsets with preservation of vesicular structure, surface protein specificity and RNA cargo activity.

PurposeTo define the role of focal laser ablation (FLA) as clinical treatment of prostate cancer (PCa) using the Delphi consensus method.MethodsA panel of international experts in the field of focal therapy (FT) in PCa conducted a collaborative consensus project using the Delphi method. Experts were invited to online questionnaires focusing on patient selection and treatment of PCa with FLA during four subsequent rounds. After each round, outcomes were displayed, and questionnaires were modified based on the comments provided by panelists. Results were finalized and discussed during face-to-face meetings.ResultsThirty-seven experts agreed to participate, and consensus was achieved on 39/43 topics. Clinically significant PCa (csPCa) was defined as any volume Grade Group 2 [Gleason score (GS) 3+4]. Focal therapy was specified as treatment of all csPCa and can be considered primary treatment as an alternative to radical treatment in carefully selected patients. In patients with intermediate-risk PCa (GS 3+4) as well as patients with MRI-visible and biopsy-confirmed local recurrence, FLA is optimal for targeted ablation of a specific magnetic resonance imaging (MRI)-visible focus. However, FLA should not be applied to candidates for active surveillance and close follow-up is required. Suitability for FLA is based on tumor volume, location to vital structures, GS, MRI-visibility, and biopsy confirmation.ConclusionFocal laser ablation is a promising technique for treatment of clinically localized PCa and should ideally be performed within approved clinical trials. So far, only few studies have reported on FLA and further validation with longer follow-up is mandatory before widespread clinical implementation is justified.

The increased use of prostate-specific membrane antigen (PSMA) based PET imaging for prostate cancer (Pca) detection has revolutionized the clinical management of Pca, with higher diagnostic sensitivity for extraprostatic disease and increasing clinical utility across different stages of the disease. The integration of PSMA PET imaging into clinical guidelines and consensus documents reflects its growing importance in the personalized management of Pca. This review of recent literature highlights the rapid evolution of PSMA PET into the mainstream of staging and restaging and the decreasing reliance on conventional imaging modalities. This comprehensive review serves as a resource for clinicians and researchers involved in the domains of Pca diagnosis and management. [ABSTRACT FROM AUTHOR]

Extraprostatic extension (EPE) is well established as a significant predictor of prostate cancer aggression and recurrence. Accurate EPE assessment prior to radical prostatectomy can impact surgical approach. We aimed to utilize a deep learning-based AI workflow for automated EPE grading from prostate T2W MRI, ADC map, and High B DWI. An expert genitourinary radiologist conducted prospective clinical assessments of MRI scans for 634 patients and assigned risk for EPE using a grading technique. The training set and held-out independent test set consisted of 507 patients and 127 patients, respectively. Existing deep-learning AI models for prostate organ and lesion segmentation were leveraged to extract area and distance features for random forest classification models. Model performance was evaluated using balanced accuracy, ROC AUCs for each EPE grade, as well as sensitivity, specificity, and accuracy compared to EPE on histopathology. A balanced accuracy score of.390 ± 0.078 was achieved using a lesion detection probability threshold of 0.45 and distance features. Using the test set, ROC AUCs for AI-assigned EPE grades 0–3 were 0.70, 0.65, 0.68, and 0.55 respectively. When using EPE ≥ 1 as the threshold for positive EPE, the model achieved a sensitivity of 0.67, specificity of 0.73, and accuracy of 0.72 compared to radiologist sensitivity of 0.81, specificity of 0.62, and accuracy of 0.66 using histopathology as the ground truth. Our AI workflow for assigning imaging-based EPE grades achieves an accuracy for predicting histologic EPE approaching that of physicians. This automated workflow has the potential to enhance physician decision-making for assessing the risk of EPE in patients undergoing treatment for prostate cancer due to its consistency and automation. [ABSTRACT FROM AUTHOR]

(1) Background: Non-invasive prostate cancer assessments using multi-parametric MRI are essential to the reliable detection of lesions and proper management of patients. While current guidelines call for the administration of Gadolinium-containing intravenous contrast injections, eliminating such injections would simplify scanning and reduce patient risk and costs. However, augmented image analysis is necessary to extract important diagnostic information from MRIs. Purpose: This study aims to extend previous work on the signal to clutter ratio and test whether prostate tumor eccentricity and volume are indicators of tumor aggressiveness using bi-parametric (BP)-MRI. (2) Methods: This study retrospectively processed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRIs (apparent diffusion coefficient, high b-value, and T2 images) were resized, translated, cropped, and stitched to form spatially registered BP-MRIs. The International Society of Urological Pathology (ISUP) grade was used to judge cases of prostate cancer as either clinically significant prostate cancer (CsPCa) (ISUP ≥ 2) or clinically insignificant prostate cancer (CiPCa) (ISUP < 2). The Adaptive Cosine Estimator (ACE) algorithm was applied to the BP-MRIs, followed by thresholding, and then eccentricity and volume computations, from the labeled and blobbed detection maps. Then, univariate and multivariate linear regression fittings of eccentricity and volume were applied to the ISUP grade. The fits were quantitatively evaluated by computing correlation coefficients (R) and p-values. Area under the curve (AUC) and receiver operator characteristic (ROC) curve scores were used to assess the logistic fitting to CsPCa/CiPCa. (3) Results: Modest correlation coefficients (R) (>0.35) and AUC scores (0.70) for the linear and/or logistic fits from the processed prostate tumor eccentricity and volume computations for the spatially registered BP-MRIs exceeded fits using the parameters of prostate serum antigen, prostate volume, and patient age (R~0.17). (4) Conclusions: This is the first study that applied spectral approaches to BP-MRIs to generate tumor eccentricity and volume metrics to assess tumor aggressiveness. This study found significant values of R and AUC (albeit below those from multi-parametric MRI) to fit and relate the metrics to the ISUP grade and CsPCA/CiPCA, respectively.

Objective. Sialic acid-binding immunoglobulin-like lectin 15 (Siglec-15) is overexpressed in various cancers which has led to the development of therapeutic anti-Siglec-15 monoconal antibodies (mAbs). In these preclinical studies, the therapeutic mAb, NC318 (antihuman/murine Siglec-15 mAb), was labeled with zirconium-89 and evaluated in human Siglec-15 expressing cancer cells and mouse xenografts for potential use as a clinical diagnostic imaging agent. Methods. Desferrioxamine-conjugated NC318 was radiolabeled with zirconium-89 to synthesize [89Zr]Zr-DFO-NC318. Cancer cell lines expressing variable Siglec-15 levels were used for in vitro cell binding studies and tumor xenograft mouse models for biodistributions. [89Zr]Zr-DFO-NC318 biodistribution and PET imaging studies to determine tissue uptakes (tissue : muscle ratios, T : M) included pharmacokinetic evaluation in Siglec-15+tumor xenografts and immunocompetent mice, blocking with nonradioactive NC318 (20, 100, and 300 μg) and xenografts with low/negligible Siglec-15 expressing tumors. Results. [89Zr]Zr-DFO-NC318 exhibited high affinity (Kd~4 nM) for Siglec-15 and distinguished between moderate and negligible Siglec-15 expression levels in cancer cell lines. The highest [89Zr]Zr-DFO-NC318 uptakes occurred in the spleen and lymph nodes of the Siglec-15+tumor xenografts at all time points followed by Siglec-15+tumor uptake which was lower although highly retained. In immunocompetent mice, the spleen and lymph nodes exhibited lower uptakes indicating that the athymic xenografts had increased Siglec-15+ immune cells. Specific [89Zr]Zr-DFO-NC318 binding to Siglec-15 was proven with NC318 blocking studies in which dose-dependent decreases in Siglec-15+tumor T : Ms were observed. Higher than expected, tumor T : Ms were seen in lower expressing tumors likely due to the contribution of murine Siglec-15+ immune cells in the tumor microenvironment as confirmed by immunohistochemistry. Siglec-15+tumors were identified on PET images whereas low/negligible expressing tumors showed lower uptakes. Conclusions. In vitro and in vivo [89Zr]Zr-DFO-NC318 uptakes correlated with Siglec-15 expression levels in target tissues. Despite uptake in immune cell subsets in the tumor microenvironment, these results suggest that clinical [89Zr]Zr-DFO-NC318 PET imaging may have value in selecting patients for Siglec-15-targeted therapies.

BackgroundCurrent prostate cancer evaluation can be inaccurate and burdensome. To help non-invasive prostate tumor assessment, recent algorithms applied to spatially registered multi-parametric (SRMP) MRI extracted novel clinically relevant metrics, namely the tumor’s eccentricity (shape), signal-to-clutter ratio (SCR), and volume.PurposeConduct a pilot study to predict the risk of developing clinically significant prostate cancer using nomograms and employing Decision Curves Analysis (DCA) from the SRMP MRI-based features to help clinicians non-invasively manage prostate cancer.MethodsThis study retrospectively analyzed 25 prostate cancer patients. MP-MRI (T1, T2, diffusion, dynamic contrast-enhanced) were resized, translated, and stitched to form SRMP MRI. Target detection algorithm [adaptive cosine estimator (ACE)] applied to SRMP MRI determines tumor’s eccentricity, noise reduced SCR (by regularizing or eliminating principal components (PC) from the covariance matrix), and volume. Pathology assessed wholemount prostatectomy for Gleason score (GS). Tumors with GS >=4+3 (0.70) for ROC curves and p-values (

BackgroundEvaluating and displaying prostate cancer through non-invasive imagery such as Multi-Parametric MRI (MP-MRI) bolsters management of patients. Recent research quantitatively applied supervised target algorithms using vectoral tumor signatures to spatially registered T1, T2, Diffusion, and Dynamic Contrast Enhancement images. This is the first study to apply the Reed-Xiaoli (RX) multi-spectral anomaly detector (unsupervised target detector) to prostate cancer, which searches for voxels that depart from the background normal tissue, and detects aberrant voxels, presumably tumors.MethodsMP-MRI (T1, T2, diffusion, dynamic contrast-enhanced images, or seven components) were prospectively collected from 26 patients and then resized, translated, and stitched to form spatially registered multi-parametric cubes. The covariance matrix (CM) and mean μ were computed from background normal tissue. For RX, noise was reduced for the CM by filtering out principal components (PC), regularization, and elliptical envelope minimization. The RX images were compared to images derived from the threshold Adaptive Cosine Estimator (ACE) and quantitative color analysis. Receiver Operator Characteristic (ROC) curves were used for RX and reference images. To quantitatively assess algorithm performance, the Area Under the Curve (AUC) and the Youden Index (YI) points for the ROC curves were computed.ResultsThe patient average for the AUC and [YI] from ROC curves for RX from filtering 3 and 4 PC was 0.734[0.706] and 0.727[0.703], respectively, relative to the ACE images. The AUC[YI] for RX from modified Regularization was 0.638[0.639], Regularization 0.716[0.690], elliptical envelope minimization 0.544[0.597], and unprocessed CM 0.581[0.608] using the ACE images as Reference Image. The AUC[YI] for RX from filtering 3 and 4 PC was 0.742[0.711] and 0.740[0.708], respectively, relative to the quantitative color images. The AUC[YI] for RX from modified Regularization was 0.643[0.648], Regularization 0.722[0.695], elliptical envelope minimization 0.508[0.605], and unprocessed CM 0.569[0.615] using the color images as Reference Image. All standard errors were less than 0.020.ConclusionsThis first study of spatially registered MP-MRI applied anomaly detection using RX, an unsupervised target detection algorithm for prostate cancer. For RX, filtering out PC and applying Regularization achieved higher AUC and YI using ACE and color images as references than unprocessed CM, modified Regularization, and elliptical envelope minimization.