A Prospective Randomized Trial of Neoadjuvant Chemohormonal Therapy vs Hormonal Therapy in Locally Advanced Prostate Cancer Treated by Radical Prostatectomy.

PURPOSE: Benefits of docetaxel-based neoadjuvant chemohormonal therapy (NCHT) before radical prostatectomy (RP) remain largely unknown. We explored whether docetaxel-based NCHT would bring pathological benefits and improve biochemical progression-free survival (bPFS) over neoadjuvant hormonal therapy (NHT) in locally advanced prostate cancer. MATERIALS AND METHODS: A randomized trial was designed recruiting 141 locally advanced, high-risk prostate cancer patients who were randomly assigned at the ratio of 2:1 to the NCHT group (75 mg/m2 body surface area every 3 weeks plus androgen deprivation therapy for 6 cycles) and the NHT group (androgen deprivation therapy for 24 weeks). The primary end point was 3-year bPFS. Secondary end points were pathological response including pathological downstaging and minimal residual disease rates. RESULTS: The NCHT group showed significant benefits in 3-year bPFS compared to the NHT group (29% vs 9.5%, P = .002). At a median follow-up of 53 months, the NCHT group achieved a significantly longer median bPFS time than the NHT group (17 months vs 14 months). No significant differences were found between the 2 groups in pathological downstaging and minimal residual disease rates. CONCLUSIONS: NCHT plus RP achieved significant bPFS benefits when compared with NHT plus RP in high-risk, locally advanced prostate cancer. A larger cohort with longer follow-up duration is essential in further investigation.

Harnessing artificial intelligence for prostate cancer management.

Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is crucial for clinical decision-making, but traditional pathology review is labor intensive and subjective to some extent. Digital pathology and whole-slide imaging enable the application of artificial intelligence (AI) in pathology. This review highlights the success of AI in detecting and grading PCa, predicting patient outcomes, and identifying molecular subtypes. We propose that AI-based methods could collaborate with pathologists to reduce workload and assist clinicians in formulating treatment recommendations. We also introduce the general process and challenges in developing AI pathology models for PCa. Importantly, we summarize publicly available datasets and open-source codes to facilitate the utilization of existing data and the comparison of the performance of different models to improve future studies.

ß-cyclocitral induced rapid cell death of Microcystis aeruginosa.

ß-cyclocitral (BCC) is an odorous compound that can be produced by bloom-forming cyanobacteria, for example, Microcystis aeruginosa. BCC has been proposed to explain the rapid decline of cyanobacterial blooms in natural water bodies due to its lytic effects on cyanobacteria cells. However, few insights have been gained regarding the mechanisms of its lethality on cyanobacteria. In this study, M. aeruginosa was exposed to 0-300 mg/L BCC, and the physiological responses were comprehensively studied at the cellular, molecular, and transcriptomic levels. The result indicated that the lethal effect was concentration-dependent; 100 mg/L BCC only caused recoverable stress, while 150-300 mg/L BCC caused rapid rupture of cyanobacterial cells. Scanning electron microscope images suggested two typical morphological changes exposed to above 150 mg/LBCC: wrinkled/shrank with limited holes on the surface at 150 and 200 mg/L BCC exposure; no apparent shrinkage at the surface but with cell perforation at 250 and 300 mg/L BCC exposure. BCC can rapidly inhibit the photosynthetic activity of M. aeruginosa cells (40%∼100% decreases for 100-300 mg/L BCC) and significantly down-regulate photosynthetic system Ⅰ-related genes. Also, chlorophyll a (by 30%∼90%) and ATP (by ∼80%) contents severely decreased, suggesting overwhelming pressure on the energy metabolism in cells. Glutathione levels increased significantly, and stress response-related genes were upregulated, indicating the perturbation of intracellular redox homeostasis. Two cell death pathways were proposed to explain the lethal effect: apoptosis-like death as revealed by the upregulation of SOS response genes when exposed to 200 mg/L BCC and mazEF-mediated death as revealed by the upregulation of mazEF system genes when exposed to 300 mg/L BCC. Results of the current work not only provide insights into the potential role of BCC in inducing programmed cell death during bloom demise but also indicate the potential of using BCC for harmful algal control.

Sarcopenia augments the risk of excess weight on COVID-19 hospitalization: A prospective study using the Lifelines COVID-19 cohort.

OBJECTIVE: We investigated the associations of sarcopenia alone, overweight or obesity, and sarcopenic overweight or obesity with COVID-19 hospitalization. METHODS: Participants from the Lifelines COVID-19 cohort who were infected with COVID-19 were included in this study. Sarcopenia was defined as a relative deviation of muscle mass of ≤ -1.0 SD from the sex-specific mean 24-h urinary creatinine excretion. Overweight or obesity was defined as a body mass index ≥ 25 kg/m2. Sarcopenic overweight or obesity was defined as the presence of overweight or obesity and low muscle mass. COVID-19 hospitalization was self-reported. Logistic regression models were used to analyze the associations of sarcopenia alone, overweight or obesity, and sarcopenic overweight or obesity with COVID-19 hospitalization. RESULTS: Of the 3594 participants infected with COVID-19 and recruited in this study, 173 had been admitted to the hospital. Compared with the reference group, individuals with overweight or obesity and sarcopenic overweight or obesity were 1.78-times and 2.09-times more likely to have been hospitalized for COVID-19, respectively, whereas sarcopenia alone did not increase the risk of COVID-19 hospitalization. CONCLUSIONS: In this middle-aged population, sarcopenic overweight or obesity elevated the risk of hospitalization for COVID-19 in those infected with COVID-19 more than overweight or obesity alone. These data support the relevance of sarcopenic overweight or obesity as a risk factor beyond the geriatric setting and should be considered in risk stratification in future public health and vaccination campaigns.

Identifying High Gleason Score Prostate Cancer by Prostate Fluid Metabolic Fingerprint-Based Multi-Modal Recognition.

Prostate cancer (PCa) is the second most common cancer in males worldwide. The Gleason scoring system, which classifies the pathological growth pattern of cancer, is considered one of the most important prognostic factors for PCa. Compared to indolent PCa, PCa with high Gleason score (h-GS PCa, GS ≥ 8) has greater clinical significance due to its high aggressiveness and poor prognosis. It is crucial to establish a rapid, non-invasive diagnostic modality to decipher patients with h-GS PCa as early as possible. In this study, ferric nanoparticle-assisted laser desorption/ionization mass spectrometry (FeNPALDI-MS) to extract prostate fluid metabolic fingerprint (PSF-MF) is employed and combined with the clinical features of patients, such as prostate-specific antigen (PSA), to establish a multi-modal diagnosis assisted by machine learning. This approach yields an impressive area under the curve (AUC) of 0.87 to diagnose patients with h-GS, surpassing the results of single-modal diagnosis using only PSF-MF or PSA, respectively. Additionally, using various screening methods, six key metabolites that exhibit greater diagnostic efficacy (AUC = 0.96) are identified. These findings also provide insights into related metabolic pathways, which may provide valuable information for further elucidation of the pathological mechanisms underlying h-GS PCa.

Extracellular vesicles related gene HSPH1 exerts anti-tumor effects in prostate cancer via promoting the stress response of CD8 + T cells.

BACKGROUND: T cell stress response state (TSTR), as a novel immune concept previous studies have proposed, has not yet been explored in prostate cancer (PC). As a type of cellular efflux, exosomes play important roles in the occurrence and development of PC. METHOD: Here, we conducted a combined analysis on extracellular vesicle related genes (EVRGs) in PC using data from single-cell RNA (scRNA), spatial transcriptome (ST), and bulk RNA sequencing. RESULT: Preliminary findings have revealed that heat shock protein family H (Hsp110) member 1 (HSPH1) possesses two identities, one being EVRGs and the other being a member of the heat shock protein family involved in TSTR, which may promote the differentiation of conventional T cells towards Th1 or Th2 cells through the pathway of IL2-MYC-IL2RA, thereby promoting the increase of CD8 + T cells in the tumor area, especially in the invasive zone, and inhibiting the invasion of PCs. We also notice the negative response of HSPH1 + CD8 + T cell related genes in immune checkpoint blockade (ICB). Western blot (WB) and droplet digital Polymerase Chain Reaction (ddPCR) demonstrated that the mRNA and protein levels of HSPH1 in EVs of PCs were significantly higher than those in adjacent tissues. CONCLUSION: Results above indicate the potential of HSPH1 as a critical therapeutic target in PC.

Precise diagnosis and risk stratification of prostate cancer by comprehensive serum metabolic fingerprints: a prediction model study.

OBJECTIVES: Prostate cancer (PCa) is one of the most common malignancies in men worldwide and has caused increasing clinical morbidity and mortality, making timely diagnosis and accurate staging crucial. The authors introduced a novel approach based on mass spectrometry for precise diagnosis and stratification of PCa to facilitate clinical decision-making. METHODS: Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry analysis of trace blood samples was combined with machine learning algorithms to construct diagnostic and stratification models. A total of 367 subjects, comprising 181 with PCa and 186 with non-PCa were enrolled. Additional 60 subjects, comprising 30 with PCa and 30 with non-PCa were enrolled as an external cohort for validation. Subsequent metabolomic analysis was carried out using Autoflex MALDI-TOF, and the mass spectra were introduced into various algorithms to construct different models. RESULTS: Serum metabolic fingerprints were successfully obtained from 181 patients with PCa and 186 patients with non-PCa. The diagnostic model based on the eight signals demonstrated a remarkable area under curve of 100% and was validated in the external cohort with the area under curve of 87.3%. Fifteen signals were selected for enrichment analysis, revealing the potential metabolic pathways that facilitate tumorigenesis. Furthermore, the stage prediction model with an overall accuracy of 85.9% precisely classified subjects with localized disease and those with metastasis. The risk stratification model, with an overall accuracy of 89.6%, precisely classified the subjects as low-risk and high-risk. CONCLUSIONS: Our study facilitated the timely diagnosis and risk stratification of PCa and provided new insights into the underlying mechanisms of metabolic alterations in PCa.

Assessing dynamic metabolic heterogeneity in prostate cancer patients via total-body [68Ga]Ga-PSMA-11 PET/CT imaging: quantitative analysis of [68Ga]Ga-PSMA-11 uptake in pathological lesions and normal organs.

PURPOSE: This study aimed to quantitatively assess [68Ga]Ga-PSMA-11 uptake in pathological lesions and normal organs in prostate cancer using the total-body [68Ga]Ga-PSMA-11 PET/CT and to characterize the dynamic metabolic heterogeneity of prostate cancer. METHODS: Dynamic total-body [68Ga]Ga-PSMA-11 PET/CT scans were performed on ten prostate cancer patients. Manual delineation of volume-of-interests (VOIs) was performed on multiple normal organs displaying high [68Ga]Ga-PSMA-11 uptake, as well as pathological lesions. Time-to-activity curves (TACs) were generated, and the four compartment models including one-tissue compartmental model (1T1k), reversible one-tissue compartmental model (1T2k), irreversible two-tissue compartment model (2T3k) and reversible two-tissue compartmental model (2T4k) were fitted to each tissue TAC. Various rate constants, including K1 (forward transport rate from plasma to the reversible compartment), k2 (reverse transport rate from the reversible compartment to plasma), k3 (tracer binding on the PSMA-receptor and its internalization), k4 (the externalization rate of the tracer) and Ki (net influx rate), were obtained. The selection of the optimal model for describing the uptake of both lesions and normal organs was determined using the Akaike information criteria (AIC). Receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off values for differentiating physiological and pathological [68Ga]Ga-PSMA-11 uptake. RESULTS: Both 1T1k and 1T2k models showed relatively high AIC values compared to the 2T3k and 2T4k models in both pathological lesions and normal organs. The kinetic behavior of pathological lesions was better described by the 2T3k model compared to the 2T4k model, while the normal organs were better described by the 2T4k model. Significant variations in kinetic metrics, such as K1, k2, and k3, and Ki, were observed among normal organs with high [68Ga]Ga-PSMA-11 uptake and pathological lesions. The high Ki value in normal organs was primarily determined by elevated K1 and low k3, rather than k2. Conversely, the high Ki value in pathological lesions, ranking second to the kidney and similar to salivary glands and spleen, was predominantly determined by the highest k3 value. Notably, k3 exhibited the highest performance in distinguishing between physiological and pathological [68Ga]Ga-PSMA-11 uptake, with an area under the curve (AUC) of 0.844 (95% CI, 0.773-0.915), sensitivity of 82.9%, and specificity of 74.1%. The k3 values showed better performance than SUVmean (AUC, 0.659), SUVmax (AUC, 0.637), and other kinetic parameter including K1 (AUC, 0.604), k2 (AUC, 0.634), and Ki (AUC, 0.651). CONCLUSIONS: Significant discrepancies in kinetic metrics were detected between pathological lesions and normal organs, despite their shared high uptake of [68Ga]Ga-PSMA-11. Notably, the k3 value exhibits a noteworthy capability to distinguish between pathological lesions and normal organs with elevated [68Ga]Ga-PSMA-11 uptake. This discovery implies that k3 holds promise as a prospective imaging biomarker for distinguishing between pathologic and non-specific [68Ga]Ga-PSMA-11 uptake in patients with prostate cancer.

Comparison of parametric imaging and SUV imaging with [68 Ga]Ga-PSMA-11 using dynamic total-body PET/CT in prostate cancer.

PURPOSE: Standardized uptake value (SUV) has been prevalently used to measure [68 Ga]Ga-PSMA-11 activity in prostate cancer, but it is susceptible to multiple factors. Parametric imaging allows for absolute quantification of tracer uptake and provides a better diagnostic accuracy that is crucial for lesion detection. However, the clinical significance of total-body parametric imaging of [68 Ga]Ga-PSMA-11 remains to be fully assessed. Therefore, the aim of our study is to delve into the diagnostic implications of total-body parametric imaging of [68 Ga]Ga-PSMA-11 PET/CT for patients with prostate cancer. METHODS: Twenty prostate cancer patients were included and underwent a dynamic total-body [68 Ga]Ga-PSMA-11 PET/CT scan. An irreversible two-tissue compartment model (2T3k) was fitted for each tissue time-to-activity curve, and the net influx rate (Ki) was obtained. The image quality and semi-quantitative analysis of lesion-to-background ratio (LBR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between parametric images and SUV images. RESULTS: Kinetic modeling using 2T3k demonstrated favorable model fitting in both normal organs and lesions. All of the lesions detected on SUV images (55-60 min) could be detected on Ki images. The correlation between Ki, SUVmean, and SUVmax in both normal organs and pathological lesions was found to be positive and statistically significant. Conversely, a moderate positive correlations were found between Ki and K1 (R = 0.69, P < 0.001; R = 0.61, P < 0.001) and Ki and k3 (R = 0.69, P < 0.001; R = 0.62, P < 0.001), in normal organs and pathological lesions, respectively. Visual assessment in Ki images showed less image noise and higher lesions conspicuity compared to SUV images. Ki image-derived LBR, SNR, and CBR of pathological lesions including primary tumors (PTs), lymph node metastases (LNMs) and bone metastases (BMs), exhibited remarkably higher folds (1.4-3.6 folds) compared to those derived from SUV of corresponding lesions. CONCLUSIONS: Total-body parametric imaging of [68 Ga]Ga-PSMA-11 enhanced lesion contrast and improved lesion detectability compared to SUV images. This may potentially serve as an imaging biomarker and theranostic tool for precise diagnosis and treatment evaluation in prostate cancer patients.

Types of fish consumption differ across socioeconomic strata and impact differently on plasma fish-based omega-3 fatty acids: a cross-sectional study.

PURPOSE: We investigated the associations of socioeconomic position (SEP) with total and type of fish intake in a large general population and validated whether types of fish intake were differently associated with plasma EPA and DHA in a subset of the population. METHODS: From the Lifelines Cohort Study, 94,246 participants aged 44 ± 13 years old were included to test the association of two SEP indicators, i.e., education level and household income level, with dietary intakes of total, oily, lean, fried, and other types of fish. In a subset of 575 participants (mean age: 50 ± 13 years), EPA and DHA levels were measured in plasma phospholipids and triglycerides. Dietary fish intake was assessed using Food Frequency Questionnaire. Linear regressions were applied and adjusted for relevant covariates. RESULTS: Compared to the high education level, lower education levels were negatively associated with total, oily, lean, and other fish intake (p < 0.001 for all), and positively associated with fried fish intake (ß (SE): 0.04 (0.04), p < 0.001 for middle education; 0.07 (0.04), p < 0.001 for low education), independently of relevant covariates. Similar results were observed for income levels. In the subset population, total and oily fish intakes were positively associated with plasma EPA and DHA (p < 0.02 for all). Lean and other fish intakes were positively associated with only DHA (p < 0.008 for all), but not EPA, while fried fish was not associated with either EPA or DHA in plasma (p > 0.1 for all). CONCLUSION: Lower SEP was associated with a lower total intake of fish, and of oily and lean fish, but with higher intake of fried fish. Fried fish was not associated with the fish-based EPA and DHA in plasma. Hence, SEP-related differences in fish consumption are both quantitative and qualitative.

The ELAVL3/MYCN positive feedback loop provides a therapeutic target for neuroendocrine prostate cancer.

Neuroendocrine prostate cancer is a rapidly progressive and lethal disease characterized by early visceral metastasis, poor prognosis, and limited treatment options. Uncovering the oncogenic mechanisms could lead to the discovery of potential therapeutic avenues. Here, we demonstrate that the RNA-binding protein ELAVL3 is specifically upregulated in neuroendocrine prostate cancer and that overexpression of ELAVL3 alone is sufficient to induce the neuroendocrine phenotype in prostate adenocarcinoma. Mechanistically, ELAVL3 is transcriptionally regulated by MYCN and subsequently binds to and stabilizes MYCN and RICTOR mRNA. Moreover, ELAVL3 is shown to be released in extracellular vesicles and induce neuroendocrine differentiation of adenocarcinoma cells via an intercellular mechanism. Pharmacological inhibition of ELAVL3 with pyrvinium pamoate, an FDA-approved drug, effectively suppresses tumor growth, reduces metastatic risk, and improves survival in neuroendocrine prostate cancer mouse models. Our results identify ELAVL3 as a critical regulator of neuroendocrine differentiation in prostate cancer and propose a drug repurposing strategy for targeted therapies.

Total-body [68 Ga]Ga-PSMA-11 PET/CT improves detection rate compared with conventional [68 Ga]Ga-PSMA-11 PET/CT in patients with biochemical recurrent prostate cancer.

PURPOSE: The purpose of this study was to assess whether total-body [68 Ga]Ga-PSMA-11 PET/CT could improve the detection rate compared with conventional [68 Ga]Ga-PSMA-11 PET/CT in patients with biochemical recurrent prostate cancer. METHODS: Two hundred biochemical recurrent prostate cancer patients with similar clinicopathological characteristics were included, of whom 100 patients underwent early total-body [68 Ga]Ga-PSMA-11 PET/CT and diuretic-delayed total-body [68 Ga]Ga-PSMA-11 PET/CT, and the other 100 patients received early conventional [68 Ga]Ga-PSMA-11 PET/CT and diuretic-delayed conventional [68 Ga]Ga-PSMA-11 PET/CT. The detection rates of total-body [68 Ga]Ga-PSMA-11 PET/CT and conventional [68 Ga]Ga-PSMA-11 PET/CT were compared using a chi-square test and stratified analysis. The image quality of total-body [68 Ga]Ga-PSMA PET/CT and conventional [68 Ga]Ga-PSMA-11 PET/CT was compared based on subjective scoring and objective parameters. Subjective scoring was conducted from background noise and lesion prominence using a 5-point scale. Objective parameters were evaluated by SUVmax, SUVmean, the standard deviation (SD) of SUV, and the signal-to-noise ratio (SNR) of liver and gluteus maximus. The SUVmax of the recurrent lesions was also measured. RESULTS: The liver SD of the total-body [68 Ga]Ga-PSMA-11 PET/CT was significantly lower than that of conventional [68 Ga]Ga-PSMA-11 PET/CT, the SNR was significantly higher than that of conventional [68 Ga]Ga-PSMA-11 PET/CT, and the subjective evaluation was significantly better than that of conventional [68 Ga]Ga-PSMA-11 PET/CT. The detection rate of total-body [68 Ga]Ga-PSMA PET/CT for biochemical recurrence of prostate cancer was significantly higher than that of conventional [68 Ga]Ga-PSMA-11 PET/CT (91.0% vs. 74.0%, P = 0.003). Total-body [68 Ga]Ga-PSMA-11 PET/CT had better detection efficiency for patients with a Gleason score ≤ 8 or PSA ≤ 2 ng/ml. The advantages of diuretic-delayed total-body [68 Ga]Ga-PSMA-11 PET/CT were more obvious. CONCLUSION: Total-body [68 Ga]Ga-PSMA-11 PET/CT could significantly improve the detection rate compared with conventional [68 Ga]Ga-PSMA-11 PET/CT in patients with biochemical recurrent prostate cancer.

Transcriptomic signature defines two subtypes of locally advanced PCa with distinct neoadjuvant therapy benefits.

Background: Patients with locally advanced prostate cancer (LAPCa) received docetaxel-based neoadjuvant chemo-hormonal therapy (NCHT) had better clinical outcomes after surgery compared to neoadjuvant hormonal therapy (NHT) groups, but not all patients experienced favorable clinical outcomes with NCHT, raising the necessity for potential biomarker assessment. The transcriptomic profiling offers a unique opportunity to interrogate the accurate response to NCHT and NHT treatment and to identify the predictive biomarkers for neoadjuvant therapy. Methods: The whole transcriptomic profiling was performed on baseline biopsies and surgical tissue specimens from 64 patients with LAPCa at Renji Hospital between 2014 and 2018. Biochemical progression-free survival (bPFS)-based gene-by-treatment interaction effects were used to identify predictive biomarkers for guiding treatment selection. Results: Comparing the transcriptome profiling of pre- and post-treatment LAPCa specimens, NHT and NCHT shared 1917 up- and 670 down-regulated DEGs at least 2-fold. Pathway enrichment analysis showed up-regulated pathways in response to NHT and NCHT were both enriched in cytokine receptor interaction pathways, and down-regulated pathways in response to NCHT were enriched in cell cycle pathways. By comprehensive transcriptome profiling of 64 baseline specimens, ten predictive markers were identified. We integrated them into the signature to evaluate the relative benefits of neoadjuvant therapy, which categorizes patients into two subgroups with relative bPFS benefits from either NHCT or NHT. In the high-score (≥ -95.798) group (n = 37), NCHT treatment led to significantly longer bPFS (P< 0.0001), with a clear and early separation of the Kaplan-Meier curves. In the low-score (< -95.798) group (n = 27), NHT also led to significantly longer bPFS (P=0.0025). Conclusions: In this study, we proposed the first predictive transcriptomic signature might potentially guide the effective selection of neoadjuvant therapy in LAPCa and might provide precise guidance toward future personalized adjuvant therapy. Trial registration: The study was approved by the Ethics Committee of Renji Hospital affiliated to Shanghai Jiao Tong University (Ky2019-087).

Early serial circulating tumor DNA sequencing predicts the efficacy of chemohormonal therapy in patients with metastatic hormone-sensitive prostate cancer.

Chemohormonal therapy is a standard treatment for metastatic hormone-sensitive prostate cancer (mHSPC); however, there are no biomarkers to guide clinical decisions regarding therapeutic options. We aimed to evaluate the clinical utility of serial circulating tumor DNA (ctDNA) sequencing in early prediction of the efficacy of chemohormonal therapy in patients with mHSPC. We conducted a retrospective observational study of 66 patients with mHSPC receiving chemohormonal therapy who underwent serial targeted gene-panel ctDNA sequencing. Peripheral blood samples were collected before treatment and after one cycle of chemotherapy. Kaplan-Meier and log-rank analyses were used to analyze the association between ctDNA status and disease progression-free survival. Serial changes in the ctDNA fraction and genetic alterations were also observed. After one cycle of chemotherapy, 23 (34.8%) patients displayed elevated ctDNA levels, whereas the other patients (65.2%, n = 43) did not. The median time to castration resistance in the group with reduced ctDNA levels was significantly longer than that in the group with increased ctDNA levels (17.70 vs. 8.43 months [mo], p < 0.001). Interestingly, patients with de novo alterations in homologous recombination pathway genes after treatment experienced a shorter time to castration resistance than that experienced by the remaining patients (8.02 vs. 13.20 mo, p = 0.011). The increased ctDNA levels or de novo alterations detected in homologous recombination pathway genes are a harbinger of disease progression. Early serial ctDNA sequencing could aid clinicians in making accurate treatment decisions.

Baseline PSMA-PET/CT as a predictor of PSA persistence following radical prostatectomy in high-risk nonmetastatic prostate cancer patients receiving neoadjuvant therapy.

BACKGROUND: The precise staging and proper management of high-risk prostate cancer (PCa) continues to be a challenge. We aimed to demonstrate the prognostic value of baseline prostate-specific membrane antigen-ligand positron emission tomography/computed tomography (PSMA-PET/CT) in high-risk, nonmetastatic PCa patients who received neoadjuvant hormonal or chemohormonal treatment followed by radical prostatectomy (RP). METHODS: We performed retrospective analyses of 70 patients with high-risk, nonmetastatic PCa confirmed by biopsy between 2018 and 2021. All patients underwent neoadjuvant therapy followed by RP and pelvic lymph node dissection (PLND); PSMA-PET/CT was performed before initiation of neoadjuvant therapy. Acquired image information and clinical characteristics/outcomes were examined for possible associations. RESULTS: Among 70 high-risk PCa patients, median age was 69 years old and median prostate specific antigen (PSA) at presentation was 58.5 ng/mL. Thirty (42.9%) patients had uptake of the PSMA tracer only in the primary PCa lesions and 40 (57.1%) patients had PSMA-positive lesions in regional or distant sites. Sixteen (32%) localized PCa patients defined by pre-PET magnetic resonance imaging were found to have locally advanced PCa based on PSMA-PET/CT. Fifteen (30%) localized PCa patients and 7 (35%) locally advanced PCa patients were upstaged to metastatic PCa. The sensitivity and specificity of PSMA-PET/CT for the detection of lymph node involvement were 90.9% and 69.5%, respectively, with a positive prediction value of 35.7% and negative prediction value of 97.6%. The diagnostic accuracy was 72.9%. Univariate analysis showed upstaging, tumor stage, and metastasis location based on PSMA-PET/CT are predictors to PSA persistence after surgery, while multivariate logistic regression analysis showed only the tumor stage based on PSMA-PET/CT remained an independent predictor of the outcome. CONCLUSIONS: This study further highlights the accuracy and necessity of PSMA-PET/CT in newly diagnosed, high-risk, nonmetastatic PCa patients.

The prognostic nomogram for PSA-incongruent low-risk prostate cancer treated by radical prostatectomy.

OBJECTIVE: To establish a prognostic nomogram for PSA-incongruent low-risk prostate cancer (PCa) patients (Gleason score 6 and clinical stage T2a) at diagnosis and treated with radical prostatectomy (RP), based on clinical and pathological metrics. METHODS: In total, 217 patients diagnosed with PCa were included in this study. All patients had a Gleason score of 6 (GS6) in biopsy, had clinical T2a before surgery and were treated with RP. Biochemical progression-free survival (bPFS) was analyzed using the Kaplan-Meier method. Univariate and multivariate analyses were used to determine prognostic factors related to bPFS. A prognostic nomogram was established based on factors that were significant in the multivariate analyses. RESULTS: The median bPFS had a significant difference in the subgroup of PSA at diagnosis (' < 10 ng/mL': 71.698 [67.549-75.847] vs '10-20 ng/mL': 71.038 [66.220-75.857] vs ' ≥ 20 ng/mL': 26.746 [12.384-41.108] months [Log Rank P < 0.001]), the subgroup of T stage upgrade (Negative: 70.016 [65.846-74.187] vs 'T2b/c': 69.183 [63.544-74.822] vs 'T3/4': 32.235 [11.877-52.593] months [Log Rank P < 0.001]) and the subgroup of Gleason score upgrade (Negative: 72.63 [69.096-76.163] vs '3 + 4': 68.393 [62.243-74.543] vs '4 + 3': 41.427 [27.517-55.336] vs ' ≥ 8': 28.291 [7.527-49.055] [Log Rank P < 0.001]). PSA at diagnoses (Hazard Ratio (HR) 1.027, 95% CI 1.015-1.039, P < 0.001), T stage upgrade (HR 2.116, 95% CI 1.083-4.133, P = 0.028), and Gleason score upgrade (HR 2.831, 95% CI 1.892-4.237, P < 0.001) were identified as independent predictors with significance in multivariable Cox regression analysis. A nomogram was established based on these three factors. CONCLUSIONS: Our study indicated that PSA-incongruent low-risk PCa patients (PSA with 10-20 ng/mL) had a similar prognosis to those with real low-risk PCa (PSA < 10 ng/mL) in the D' Amico criteria. We also established a nomogram based on three significant prognostic factors, including PSA at diagnosis, T stage upgrade, and Gleason score upgrade, which were associated with clinical outcomes in prostate cancer patients with GS6 and T2a after surgery.

Repurposing ketotifen as a therapeutic strategy for neuroendocrine prostate cancer by targeting the IL-6/STAT3 pathway.

PURPOSE: Neuroendocrine prostate cancer (NEPC), a highly aggressive subtype of prostate cancer displaying resistance to hormone therapy, presents a poor prognosis and limited therapeutic options. Here, we aimed to find novel medication therapies for NEPC and explore the underlying mechanism. METHODS: A high-throughput drug screening utilizing an FDA-approved drug library was performed and ketotifen, an antihistamine agent, was identified as a potential therapeutic candidate for NEPC. The whole-transcriptome sequencing analysis was conducted to explore mechanism of ketotifen inhibitory in NEPC. Multiple cell biology and biochemistry experiments were performed to confirm the inhibitory effect of ketotifen in vitro. A spontaneous NEPC mice model (PBCre4:Ptenf/f;Trp53f/f;Rb1f/f) was used to reveal the inhibitory effect of ketotifen in vivo. RESULTS: Our in vitro experiments demonstrated that ketotifen effectively suppressed neuroendocrine differentiation, reduced cell viability, and reversed the lineage switch via targeting the IL-6/STAT3 pathway. Our in vivo results showed that ketotifen significantly prolonged overall survival and reduced the risk of distant metastases in NEPC mice model. CONCLUSION: Our findings repurpose ketotifen for antitumor applications and endorse its clinical development for NEPC therapy, offering a novel and promising therapeutic strategy for this formidable cancer subtype.

High-throughput drug screening identifies fluoxetine as a potential therapeutic agent for neuroendocrine prostate cancer.

Introduction: Neuroendocrine prostate cancer (NEPC) is an aggressive subtype of prostate cancer with poor prognosis and resistance to hormone therapy, which has limited therapeutic approaches. Therefore, this study aimed to identify a novel treatment for NEPC and provide evidence of its inhibitory effects. Methods: We performed a high-throughput drug screening and identified fluoxetine, originally an FDA-approved antidepressant, as candidate therapeutic agent for NEPC. We carried out both in vitro and in vivo experiments to demonstrate the inhibitory effects of fluoxetine on NEPC models and its mechanism in detail. Results: Our results demonstrated that fluoxetine effectively curbed the neuroendocrine differentiation and inhibited cell viability by targeting the AKT pathway. Preclinical test in NEPC mice model (PBCre4: Ptenf/f; Trp53f/f; Rb1f/f) showed that fluoxetine effectively prolonged the overall survival and reduced the risk of tumor distant metastases. Discussion: This work repurposed fluoxetine for antitumor application, and supported its clinical development for NEPC therapy, which may provide a promising therapeutic strategy.

Engineering the MoS2 /MXene Heterostructure for Precise and Noninvasive Diagnosis of Prostate Cancer with Clinical Specimens.

High-throughput metabolic fingerprinting has been deemed one of the most promising strategies for addressing the high false positive rate of prostate cancer (PCa) diagnosis in the prostate-specific antigen (PSA) gray zone. However, the current metabolic fingerprinting remains challenging in achieving high-precision metabolite detection in complex biological samples (e.g., serum and urine). Herein, a novel self-assembly MoS2 /MXene heterostructure nanocomposite with a tailored doping ratio of 10% is presented as a matrix for laser desorption ionization mass spectrometry analysis in clinical biosamples. Notably, owing to the two-dimensional architecture and doping effect, MoS2 /MXene demonstrates favorable laser desorption ionization performance with low adsorption energy, which is evidenced by efficient urinary metabolic fingerprinting with an enhanced area under curve (AUC) diagnosis capability of 0.959 relative to that of serum metabolic fingerprinting (AUC = 0.902) for the diagnosis of PCa in the PSA gray zone. Thus, this MoS2 /MXene heterostructure is anticipated to offer a novel strategy to precisely and noninvasively diagnose PCa in the PSA gray zone.