Gleason Score Research Articles

A comprehensive analysis and comparison of lipid metabolism and inflammatory indices in patients with benign prostatic hyperplasia and prostate cancer

AimTo investigate the role of metabolic indices in benign prostatic hyperplasia (BPH) and prostate cancer (PCa).MethodsAfter exclusion of those with diabetes mellitus and incomplete characteristics, 552 PCa and 80 BPH patients who were diagnosed at Shandong University Affiliated Qilu Hospital between 2013 and 2022 were enrolled; and PCa patients were first compared to those with BPH in clinical characteristics. Then, we divided the patients into several groups according to the degree of risk and compared the variations in metabolic indices among the groups.ResultsCompared to those with BPH, patients with prostate cancer were significantly shorter (167.19±5.68 cm vs. 170.89±5.35 cm, p<0.001) and had greater BMI (25.13±3.06 kg/m2 vs. 24.25±3.08 kg/m2, p=0.019) and higher prealbumin (24.59±4.85 mg/dl vs. 23.21±4.76 mg/dl, p=0.017), TC (181.53±91.90 mg/dl vs. 167.71±30.20 mg/dl, p= 0.008), LDL (107.09±29.42 mg/dl vs. 100.22±25.01 mg/dl, p= 0.027), TG (120.74±135.60 mg/dl vs. 102.27±48.37 mg/dl, p= 0.020), and glucose levels (5.25±0.87 mmol/L vs. 5.04±0.62 mmol/L, p= 0.007). It seemed that PCa patients had a more severe inflammatory status, but this difference was not significant. However, no significant difference in PCa development was found for either the Gleason score or its extension.ConclusionPCa seems to be related to a more severe inflammatory status and more active metabolism, and lipid abnormalities are the main cause of prostate cancer, but the causal relationships between lipids and prostate cancer are still unclear and need further research.

Enhancing Prostate Cancer Diagnosis: Artificial Intelligence–Driven Virtual Biopsy for Optimal Magnetic Resonance Imaging-Targeted Biopsy Approach and Gleason Grading Strategy

An optimal approach to magnetic resonance imaging fusion targeted prostate biopsy (PBx) remains unclear (number of cores, intercore distance, Gleason grading [GG] principle). The aim of this study was to develop a precise pixel-wise segmentation diagnostic artificial intelligence (AI) algorithm for tumor detection and GG as well as an algorithm for virtual prostate biopsy that are used together to systematically investigate and find an optimal approach to targeted PBx. Pixel-wise AI algorithms for tumor detection and GG were developed using a high-quality, manually annotated data set (slides n = 442) after fast-track annotation transfer into segmentation style. To this end, a virtual biopsy algorithm was developed that can perform random biopsies from tumor regions in whole-mount whole-slide images with predefined parameters. A cohort of 115 radical prostatectomy (RP) patient cases with clinically significant, magnetic resonance imaging-visible tumors (n = 121) was used for systematic studies of the optimal biopsy approach. Three expert genitourinary (GU) pathologists (Y.T., A.P., A.Q.) participated in the validation. The tumor detection algorithm (aware version sensitivity/specificity 0.99/0.90, balanced version 0.97/0.97) and GG algorithm (quadratic kappa range vs pathologists 0.77-0.78) perform on par with expert GU pathologists. In total, 65,340 virtual biopsies were performed to study different biopsy approaches with the following results: (1) 4 biopsy cores is the optimal number for a targeted PBx, (2) cumulative GG strategy is superior to using maximal Gleason score for single cores, (3) controlling for minimal intercore distance does not improve the predictive accuracy for the RP Gleason score, (4) using tertiary Gleason pattern principle (for AI tool) in cumulative GG strategy might allow better predictions of final RP Gleason score. The AI algorithm (based on cumulative GG strategy) predicted the RP Gleason score of the tumor better than 2 of the 3 expert GU pathologists. In this study, using an original approach of virtual prostate biopsy on the real cohort of patient cases, we find the optimal approach to the biopsy procedure and the subsequent GG of a targeted PBx. We publicly release 2 large data sets with associated expert pathologists’ GG and our virtual biopsy algorithm.

GPC2 promotes prostate cancer progression via MDK-mediated activation of PI3K/AKT signaling pathway

Prostate cancer is a major medical problem for men worldwide. Advanced prostate cancer is currently incurable. Recently, much attention was paid to the role of GPC2 in the field of oncology. Nevertheless, there have been no investigations of GPC2 and its regulatory mechanism in prostate cancer. Here, we revealed a novel action of GPC2 and a tumor promoting mechanism in prostate cancer. GPC2 was upregulated in prostate cancer tissues and cell lines. Higher expression of GPC2 was correlated with higher Gleason score, lymphatic metastasis, and worse overall survival in prostate cancer patients. Decreased expression of GPC2 inhibited cell proliferation, migration, and invasion in prostate cancer, whereas GPC2 overexpression promoted these properties. Mechanistically, GPC2 promoted the activation of PI3K/AKT signaling pathway through MDK. The rescue assay results in prostate cancer cells demonstrated that overexpression of MDK could attenuate GPC2 knockdown induced inactivation of PI3K/AKT signaling and partly reverse GPC2 knockdown induced inhibition of cell proliferation, migration, and invasion. In all, our study identified GPC2 as an oncogene in prostate cancer. GPC2 promoted prostate cancer cell proliferation, migration, and invasion via MDK-mediated activation of PI3K/AKT signaling pathway. GPC2 might be a promising prognosis predictor and potential therapeutic target in prostate cancer.

Evaluation of Artificial Intelligence-Based Gleason Grading Algorithms “in the Wild”

The biopsy Gleason score is an important prognostic marker for prostate cancer patients. It is, however, subject to substantial variability among pathologists. Artificial intelligence (AI)–based algorithms employing deep learning have shown their ability to match pathologists’ performance in assigning Gleason scores, with the potential to enhance pathologists’ grading accuracy. The performance of Gleason AI algorithms in research is mostly reported on common benchmark data sets or within public challenges. In contrast, many commercial algorithms are evaluated in clinical studies, for which data are not publicly released. As commercial AI vendors typically do not publish performance on public benchmarks, comparison between research and commercial AI is difficult. The aims of this study are to evaluate and compare the performance of top-ranked public and commercial algorithms using real-world data. We curated a diverse data set of whole-slide prostate biopsy images through crowdsourcing containing images with a range of Gleason scores and from diverse sources. Predictions were obtained from 5 top-ranked public algorithms from the Prostate cANcer graDe Assessment (PANDA) challenge and 2 commercial Gleason grading algorithms. Additionally, 10 pathologists (A.C., C.R., J.v.I., K.R.M.L., P.R., P.G.S., R.G., S.F.K.J., T.v.d.K., X.F.) evaluated the data set in a reader study. Overall, the pairwise quadratic weighted kappa among pathologists ranged from 0.777 to 0.916. Both public and commercial algorithms showed high agreement with pathologists, with quadratic kappa ranging from 0.617 to 0.900. Commercial algorithms performed on par or outperformed top public algorithms.

Advances in multiparametric magnetic resonance imaging combined with biomarkers for the diagnosis of high-grade prostate cancer.

Clinical decisions based on the test results for prostate-specific antigen often result in overdiagnosis and overtreatment. Multiparametric magnetic resonance imaging (mpMRI) can be used to identify high-grade prostate cancer (HGPCa; Gleason score ≥3 + 4); however, certain limitations remain such as inter-reader variability and false negatives. The combination of mpMRI and prostate cancer (PCa) biomarkers (prostate-specific antigen density, Proclarix, TMPRSS2:ERG gene fusion, Michigan prostate score, ExoDX prostate intelliscore, four kallikrein score, select molecular diagnosis, prostate health index, and prostate health index density) demonstrates high accuracy in the diagnosis of HGPCa, ensuring that patients avoid unnecessary prostate biopsies with a low leakage rate. This manuscript describes the characteristics and diagnostic performance of each biomarker alone and in combination with mpMRI, with the intension to provide a basis for decision-making in the diagnosis and treatment of HGPCa. Additionally, we explored the applicability of the combination protocol to the Asian population.

Metabolic imaging across scales reveals distinct prostate cancer phenotypes

Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer.

Impact of a pharmacist-led intervention on prostate cancer illness perception.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Illness perception (IP) significantly determines illness outcomes. This study determined the impact of a pharmacist educational intervention on IP in patients with prostate cancer (PCa) and predictors of IP. Using a brief IP questionnaire, an interventional study of patients with PCa was conducted in all cancer reference hospitals in one Nigerian state. After a pre-post assessment of patients' IP, descriptive and inferential statistical analyses were performed. The impact of pharmacists' intervention on IP was determined by paired-sample statistics and correlation analysis at the 95% CI. Relationships and predictors of IP were determined using Kendall's tau-b (τb), likelihood ratio, and F tests of equality of means, respectively. P < 0.05 was considered statistically significant. Pharmacists' educational intervention significantly improved IP (SEM, 0.13; r = 0.875; P < 0.0001) among the 200 participants. The analyses also showed a significant paired sample difference (2.662; SEM, 0.06; 95%CI, 2.536-2.788; t = 41.69; df = 199; P < 0.0001). All subscales of patients' IP significantly improved except for illness consequences (P = 0.173) and identity (mean [SD], 4.40 [3.730] in both pre- and postintervention assessments). Pre- and postintervention assessments showed a significant negative relationship of IP with age (τb = -110 [P = 0.040] and τb = -14 [P = 0.021], respectively), Gleason score (τb = -0.125 [P = 0.021] and τb = -0.124 [P=0.012], respectively), and age at diagnosis (τb = -0.103 [P = 0.036] post intervention). IP was significantly dependent on the drug therapy (df = 8; mean square [M] = 6.292; F = 2.825; P = 0.006), alcohol intake (df = 1; M = 9.608; F = 4.082; P = 0.045) and Gleason score (df = 9; M = 6.706; F = 3.068; P = 0.002). Patients' IP significantly improved after pharmacists' educational intervention. Predictors of IP were drug therapies, alcohol use and Gleason score. Findings can be extrapolated in clinical settings to improve treatment outcomes.

LncRNA PITPNA-AS1 mediates the diagnostic potential of miR-129-5p in prostate cancer

BackgroundLncRNA has an effective value in many diseases, which has long been applied in the diagnosis, treatment and prognosis of prostate cancer. This study focused on lncRNA PITPNA-AS1, and its diagnostic potential in prostate cancer has been explored.MethodsThe expression of PITPNA-AS1 and miR-129-5p in prostate cancer serum and sample cells was determined by real-time quantitative polymerase chain reaction (RT-qPCR). The relationship between the expression of PITPNA-AS1 and clinicopathological parameters was considered. ROC curve prompted the diagnostic value of PITPNA-AS1. The effect of PITPNA-AS1 on prostate cancer cells was verified using vitro cells assay. Luciferase activity assay and RIP assay demonstrated the sponge relationship of PITPNA-AS1 to miR-129-5p.ResultsPITPNA-AS1 level was increased, while miR-129-5p was obviously decreased in prostate cancer. PITPNA-AS1 expression was associated with Gleason grade, lymph node metastasis and TNM stage in patients. The area under the curve (AUC) was 0.910, with high sensitivity and specificity. PITPNA-AS1 was elucidated to directly target miR-129-5p, whereas silencing PITPNA-AS1 negatively affected prostate cancer cell proliferation, migration and invasion. Intervention of miR-129-5p inhibitor reversed the effect of silencing PITPNA-AS1 on cells.ConclusionsPITPNA-AS1 was relatively highly expressed in prostate cancer and mediated the pathophysiological process of patients, which may serve as a diagnostic indicator. Silencing of the PITPNA-AS1 sponge miR-129-5p inhibited the biological function of the cells, indicating that PITPNA-AS1 may represent a novel therapeutic target for prostate cancer.

Tumor evolution metrics predict recurrence beyond 10 years in locally advanced prostate cancer.

Cancer evolution lays the groundwork for predictive oncology. Testing evolutionary metrics requires quantitative measurements in controlled clinical trials. We mapped genomic intratumor heterogeneity in locally advanced prostate cancer using 642 samples from 114 individuals enrolled in clinical trials with a 12-year median follow-up. We concomitantly assessed morphological heterogeneity using deep learning in 1,923 histological sections from 250 individuals. Genetic and morphological (Gleason) diversity were independent predictors of recurrence (hazard ratio (HR) = 3.12 and 95% confidence interval (95% CI) = 1.34-7.3; HR = 2.24 and 95% CI = 1.28-3.92). Combined, they identified a group with half the median time to recurrence. Spatial segregation of clones was also an independent marker of recurrence (HR = 2.3 and 95% CI = 1.11-4.8). We identified copy number changes associated with Gleason grade and found that chromosome 6p loss correlated with reduced immune infiltration. Matched profiling of relapse, decades after diagnosis, confirmed that genomic instability is a driving force in prostate cancer progression. This study shows that combining genomics with artificial intelligence-aided histopathology leads to the identification of clinical biomarkers of evolution.

An 18-gene signature of recurrence-associated endothelial cells predicts tumor progression and castration resistance in prostate cancer

BackgroundThe prognostic and therapeutic implications of endothelial cells (ECs) heterogeneity in prostate cancer (PCa) are poorly understood.MethodsWe investigated associations of EC heterogeneity with PCa recurrence and castration resistance in 8 bulk transcriptomic and 4 single-cell RNA-seq cohorts. A recurrence-associated EC (RAEC) signature was constructed by comparing 11 machine learning algorithms through nested cross-validation. Functional relevances of RAEC-specific genes were also tested.ResultsA subset of ECs was significantly associated with recurrence in primary PCa and named RAECs. RAECs were characteristic of tip and immature cells and were enriched in migration, angiogenesis, and collagen-related pathways. We then developed an 18-gene RAEC signature (RAECsig) representative of RAECs. Higher RAECsig scores independently predicted tumor recurrence and performed better or comparably compared to clinicopathological factors and commercial gene signatures in multiple PCa cohorts. Of the 18 RAECsig genes, FSCN1 was upregulated in ECs from PCa with higher Gleason scores; and the silencing of FSCN1, TMEME255B, or GABRD in ECs either attenuated tube formation or inhibited PCa cell proliferation. Finally, higher RAECsig scores predicted castration resistance in both primary and castration-resistant PCa.ConclusionThis study establishes an endothelial signature that links a subset of ECs to prostate cancer recurrence and castration resistance.

Feasibility study of ADCs targeting TROP-2, HER2, and CD46 in Ductal Adenocarcinoma and Intraductal Carcinoma of the prostate.

Ductal Adenocarcinoma (DAC) and Intraductal Carcinoma of the Prostate (IDC-P) respond poorly to all the currently available conventional therapies. Given their accurate and efficient elimination of cancer cells, Antibody-Drug Conjugates (ADCs) have become one of the most promising anticancer treatments. However, no ADCs have so far been approved for Prostate Cancer (PCa) treatment. This study investigated TROP-2, HER2, and CD46 expression in DAC/IDC-P samples, indirectly analyzing their preliminary feasibility as therapeutic targets for future treatment of the two conditions. We conducted a retrospective study involving 184 participants (87 DAC/IDC-P patients and 97 Prostatic Acinar Adenocarcinoma (PAC) patients with a Gleason score ≥ 8) without prior treatment between August 2017 and August 2022. Immunohistochemical staining was employed to detect the differential protein expressions of TROP-2, HER2, and CD46 in DAC/IDC-P, PAC, and normal prostate tissues. Compared to pure PAC tissues, TROP-2 expression was significantly higher in DAC/IDC-P and DAC/IDC-P-adjacent PAC tissues (H-score 68.8 vs. 43.8, p < 0.001, and 59.8 vs. 43.8, p = 0.022, respectively). No significant differences in HER2 expression were observed across different cancer tissues. Compared to both DAC/IDC-P-adjacent PAC and pure PAC tissues, CD46 expression was significantly higher in DAC/IDC-P tissues (42.3 vs. 28.6, p = 0.041, and 42.3 vs. 24.3, p = 0.0035, respectively). Herein, TROP-2 and CD46 expression was higher in DAC/IDC-P tissues than in pure PAC and normal prostate tissues. This finding implies that ADCs targeting the two proteins hold significant promise as potential future treatments for DAC/IDC-P.

External validation of an artificial intelligence model for Gleason grading of prostate cancer on prostatectomy specimens.

To externally validate the performance of the DeepDx Prostate artificial intelligence (AI) algorithm (Deep Bio Inc., Seoul, South Korea) for Gleason grading on whole-mount prostate histopathology, considering potential variations observed when applying AI models trained on biopsy samples to radical prostatectomy (RP) specimens due to inherent differences in tissue representation and sample size. The commercially available DeepDx Prostate AI algorithm is an automated Gleason grading system that was previously trained using 1133 prostate core biopsy images and validated on 700 biopsy images from two institutions. We assessed the AI algorithm's performance, which outputs Gleason patterns (3, 4, or 5), on 500 1-mm2 tiles created from 150 whole-mount RP specimens from a third institution. These patterns were then grouped into grade groups (GGs) for comparison with expert pathologist assessments. The reference standard was the International Society of Urological Pathology GG as established by two experienced uropathologists with a third expert to adjudicate discordant cases. We defined the main metric as the agreement with the reference standard, using Cohen's kappa. The agreement between the two experienced pathologists in determining GGs at the tile level had a quadratically weighted Cohen's kappa of 0.94. The agreement between the AI algorithm and the reference standard in differentiating cancerous vs non-cancerous tissue had an unweighted Cohen's kappa of 0.91. Additionally, the AI algorithm's agreement with the reference standard in classifying tiles into GGs had a quadratically weighted Cohen's kappa of 0.89. In distinguishing cancerous vs non-cancerous tissue, the AI algorithm achieved a sensitivity of 0.997 and specificity of 0.88; in classifying GG ≥2 vs GG 1 and non-cancerous tissue, it demonstrated a sensitivity of 0.98 and specificity of 0.85. The DeepDx Prostate AI algorithm had excellent agreement with expert uropathologists and performance in cancer identification and grading on RP specimens, despite being trained on biopsy specimens from an entirely different patient population.

The impact of positive surgical margin parameters and pathological stage on biochemical recurrence after radical prostatectomy: A systematic review and meta-analysis.

To systematically review and perform a meta-analysis on the predictive value of the primary Gleason grade (PGG) at the positive surgical margin (PSM), length of PSM, number of PSMs, and pathological stage of the primary tumor on biochemical recurrence (BCR) in patients with prostate cancer (PCa) after radical prostatectomy (RP). A systematic literature search was performed using electronic databases, including PubMed, EMBASE, Cochrane Library, and Web of Science, from January 1, 2005, to October 1, 2023. The protocol was pre-registered in PROSPERO. Subgroup analyses were performed according to the different treatments and study outcomes. Pooled hazard ratios with 95% confidence intervals were extracted from multivariate analyses, and a fixed or random effect model was used to pool the estimates. Subgroup analyses were performed to explore the reasons for the heterogeneity. Thirty-one studies that included 50,028 patients with PCa were eligible for this meta-analysis. The results showed that, compared to PGG3, PGG4/5 was associated with a significantly increased risk of BCR. Compared with PSM ≤3 mm, PSM ≥3 mm was associated with a significantly increased risk of BCR. Compared with unifocal PSM, multifocal PSM (mF-PSM) was associated with a significantly increased risk of BCR. In addition, pT >2 was associated with a significantly increased risk of BCR compared to pT2. Notably, the findings were found to be reliable based on the sensitivity and subgroup analyses. PGG at the PSM, length of PSM, number of PSMs, and pathological stage of the primary tumor in patients with PCa were found to be associated with a significantly increased risk of BCR. Thus, patients with these factors should be treated differently in terms of receiving adjunct treatment and more frequent monitoring. Large-scale, well-designed prospective studies with longer follow-up periods are needed to validate the efficacy of these risk factors and their effects on patient responses to adjuvant and salvage therapies and other oncological outcomes.

Influence of Tumor Characteristics and Time to Metastatic Disease on Oncological Outcomes in Metachronous Metastatic Prostate Cancer Patients

IntroductionMetachronous metastatic prostate cancer (mmPCa) patients harbor different characteristics and outcomes, relative to DeNovo metastatic PCa patients. Onset of metastatic disease might be influenced by primary PCa characteristics such as Gleason score (GS) or cancer stage, as well as overall survival (OS) by timing of metastatic onset. Patients and MethodsWe relied on an institutional tertiary-care database to identify mmPCa patients. Kaplan Meier and Cox Regression models tested for onset of metastases and OS, stratified according to GS, pathological stage and time to mmPCa. ResultsOf 341 mmPCa patients, 8% harbored GS6 versus 41% versus 51% GS7 and GS8-10. Median time to onset of metastatic disease was 79 versus 54 versus 41 months for GS6 versus GS7 versus GS8-10 (P = .01). Moreover, median time to onset of metastases was 64 versus 44 months for pT1-2 versus pT3-4 mmPCa patients undergoing radical prostatectomy (P = .027). In multivariable Cox regression models, higher GS and pT-stage was associated with earlier onset of metastases. Additionally, significant OS differences could be observed for time interval of < 24 versus 24-60 versus 60-120 versus ≥ 120 months between primary PCa diagnosis and onset of mmPCa. Specifically, median OS was 56 versus 69 versus 97 months versus not reached (P < .01) for these categories. In multivariable Cox regression, shorter time to metastatic onset was associated with shorter OS. ConclusionTiming of mmPCa is strongly influenced by grading and pT-stage in real-life setting. OS benefits can be observed with longer time interval between primary PCa diagnosis and onset of mmPCa.

SERPINH1 modulates apoptosis by inhibiting P62 ubiquitination degradation to promote bone metastasis of prostate cancer

SERPINH1 modulates apoptosis by inhibiting P62 ubiquitination degradation to promote bone metastasis of prostate cancer

Bone Pain and Survival Among Patients With Metastatic, Hormone-Sensitive Prostate Cancer

The presence of bone pain is significantly associated with worse overall survival (OS) in patients with castration-resistant prostate cancer. However, there are few data regarding bone pain and survival outcomes in the context of metastatic, hormone-sensitive prostate cancer (MHSPC). To compare survival outcomes among patients with MHSPC by presence or absence of baseline bone pain at diagnosis. This post hoc secondary analysis, conducted from September 1 to December 31, 2023, used patient-level data from SWOG-1216, a phase 3, prospective randomized clinical trial that enrolled patients with newly diagnosed MHSPC from 248 academic and community centers across the US from March 1, 2013, to July 15, 2017. All patients in the intention-to-treat population who had available bone pain status were eligible and included in this secondary analysis. In the SWOG-1216 trial, patients were randomized (1:1) to receive either androgen deprivation therapy (ADT) with orteronel, 300 mg orally twice daily (experimental group), or ADT with bicalutamide, 50 mg orally daily (control group), until disease progression, unacceptable toxic effects, or patient withdrawal. Overall survival was the primary end point; progression-free survival (PFS) and prostate-specific antigen (PSA) response were secondary end points. Cox proportional hazards regression models were used for both univariable and multivariable analyses adjusting for age, treatment type, Gleason score, disease volume, Zubrod performance status, and PSA level. Of the 1279 male study participants, 301 (23.5%) had baseline bone pain at MHSPC diagnosis and 896 (70.1%) did not. Bone pain status was unavailable in 82 patients (6.4%). The median age of the 1197 patients eligible and included in this secondary analysis was 67.6 years (IQR, 61.8-73.6 years). Compared with patients who did not experience bone pain, those with baseline bone pain were younger (median age, 66.0 [IQR, 60.1-73.4] years vs 68.2 [IQR, 62.4-73.7] years; P = .02) and had a higher incidence of high-volume disease (212 [70.4%] vs 373 [41.6%]; P < .001). After adjustment, bone pain was associated with shorter PFS and OS. At a median follow-up of 4.0 years (IQR, 2.5-5.4 years), patients with bone pain had median PFS of 1.3 years (95% CI, 1.1-1.7 years) vs 3.7 years (95% CI, 3.3-4.2 years) in patients without initial bone pain (adjusted hazard ratio [AHR], 1.46; 95% CI, 1.22-1.74; P < .001) and OS of 3.9 years (95% CI, 3.3-4.8 years) vs not reached (NR) (95% CI, 6.6 years to NR) in patients without initial bone pain (AHR, 1.66; 95% CI, 1.34-2.05; P < .001). In this post hoc secondary analysis of the SWOG-1216 randomized clinical trial, patients with baseline bone pain at MHSPC diagnosis had worse survival outcomes than those without bone pain. These data suggest prioritizing these patients for enrollment in clinical trials, may aid patient counseling, and indicate that the inclusion of bone pain in prognostic models of MHSPC may be warranted. ClinicalTrials.gov Identifier: NCT01809691.

Physiological biodistribution on Ga68-PSMA PET/CT and the factors effecting biodistribution

AimThe study aims to determine the physiological and pathophysiological distribution of the radiopharmaceutical (Ga68-PSMA-617) and investigate whether there are differences in distribution according to the laboratory, histopathological and clinical findings that can affect image evaluation. Also, we aimed to determine cut-off values to distinguish physiological and pathological uptake in prostate, bone, and lymph nodes.Materials and Methods229 prostate cancer patients who underwent Ga68-PSMA PET/CT at our department were retrospectively analyzed. The patients were grouped according to PET/CT results, Gleason scores, PSA values, received treatments, metastatic status and other laboratory values. The SUV values of the organs, tissues, and pathological lesions of the patients in these subgroups were compared among themselves.ResultsNo significant difference was detected in the physiological uptake of lymph nodes and bone between the groups. In the group with patients that received androgen deprivation therapy (ADT), the bone metastasis SUV values were found to be higher and the SUV values of the submandibular gland and renal cortex were found to be lower (Mann–Whitney U, p = 0.043; 0.004; 0.01, respectively). In the group with patients who received radiotherapy, the normal prostate tissue SUV values were determined to be higher (Mann–Whitney U, p = 0.009). The SUV values of the submandibular gland, muscle, liver, and blood pool were found to be lower in the group of patients with high serum LDH values. The cut-off SUVmax value was determined to be 6.945 (sensitivity 89.6%, specificity 98.1%) for primary prostate lesion; 4.72 for lymph node metastasis; 4.25 for bone metastasis. The serum PSA cut-off value to distinguish the negative/positive groups was found to be 1,505 (sensitivity 79.7%, specificity 77.3%).ConclusionIn conclusion, PSMA-617 demonstrates a similar biodistribution with other PSMA ligands. The physiological uptake of lymph nodes and bone which are mostly metastasized in prostate cancer, are not affected by the factors we examined. It should be kept in mind that the normal prostate tissue uptake may increase in patients receiving radiotherapy, and the physiological/pathological uptake of the organs may differ due to the changes in PSMA expression in patients receiving ADT, tumor burden, and kidney function may affect the biodistribution.

Non-alcoholic fatty liver disease increases the risk of biochemical recurrence in high-grade metastatic prostate cancer patients.

Non-alcoholic fatty liver disease (NAFLD) has been reported to be helpful to identify high-risk individuals of developing prostate cancer. Our aim is to investigate the relationship between NAFLD and biochemical recurrence in metastatic prostate cancer patients. We retrospectively investigated 602 patients with metastatic prostate cancer receiving the androgen deprivation therapy. Liver fat was estimated with liver-to-spleen ratio by computed tomography (CT) scans. The relationship between NAFLD and biochemical recurrence was investigated with Cox models. The model for biochemical recurrence was adjusted for multiple variables. NAFLD was significantly associated with biochemical recurrence in patients with Gleason score ≥4+3 when adjusting for each of body mass index (hazards ratio [HR]=1.38; 95% confidence interval [CI]=1.08-1.77; p=0.01), visceral adipose tissue (HR=1.36; 95% CI=1.07-1.74; p=0.01), hypertension (HR=1.41; 95% CI=1.10-1.80; p=0.01), and diabetes mellitus (HR=1.42; 95% CI=1.11-1.82; p=0.01), using age and prostate-specific antigen level as potential confounder. The 2-year biochemical recurrence rate in the Gleason score ≥4+3 patients with and without NAFLD was 84.0% (100/119) and 72.2% (130/180), respectively (p=0.018). The median biochemical recurrence free survival of the Gleason score ≥4+3 patients with and without NAFLD were 17 and 21 months, respectively (p=0.005). NAFLD is an independent risk factor for biochemical recurrence in patients with high-grade metastatic prostate cancer. If validated in prospective studies, future research should test whether treatment of NAFLD can lead to better prognosis.

Radical prostatectomy cancer grade and percentage of Gleason pattern 4 estimated by global vs individual tumor grading correlate differently with the risk of biochemical recurrence in Grade Group 2 and 3 cancers.

There are 2 grading approaches to radical prostatectomy (RP) in multifocal cancer: Grade Group (GG) and percentage of Gleason pattern 4 (GP4%). We investigated whether RP GG and GP4% generated by global vs individual tumor grading correlate differently with biochemical recurrence. We reviewed 531 RP specimens with GG2 or GG3 cancer. Each tumor was scored separately with assessment of tumor volume and GP4%. Global grade and GP4% were assigned by combining Gleason pattern 3 and 4 volumes for all tumors. Correlation of GG and GP4% generated by 2 methods with biochemical recurrence was assessed by Cox proportional hazard regression and receiver operating characteristic curves, with optimism adjustment using a bootstrap analysis. Median age was 63 (range, 42-79) years. Median prostate-specific antigen was 6.3 (range, 0.3-62.9) ng/mL. In total, the highest-grade tumor in 371 (36.9%) men was GG2 and in 160 (30.1%) men was GG3. Global grading was downgraded from GG3 to GG2 in 37 of 121 (30.6%) specimens with multifocal disease, and 145 of 404 (35.9%) specimens had GP4% decreased by at least 10%. Ninety-eight men experienced biochemical recurrence within a median of 13 (range, 3-119) months. Men without biochemical recurrence were followed up for a median of 47 (range, 12-205) months. Grade Group, GP4%, and margin status correlated with the risk of biochemical recurrence using highest-grade tumor and global grading, but the degrees of these correlations varied and were statistically significantly different between the 2 grading approaches. Grade Group, GP4%, and margin status derived by global vs individual tumor grading predict postoperative biochemical recurrence statistically significantly differently. This difference has important implications if results derived from cohorts graded using different methods are compared.

Prostate cancer cancer-associated fibroblasts with stable markers post-androgen deprivation therapy associated with tumor progression and castration resistant prostate cancer.

The specificity and clinical relevance of cancer-associated fibroblasts (CAFs) in prostate cancer (PCa), as well as the effect of androgen deprivation therapy (ADT) on CAFs, remain to be fully elucidated. Using cell lineage diversity and weighted gene co-expression network analysis (WGCNA), we pinpointed a unique CAF signature exclusive to PCa. The specificity of this CAF signature was validated through single-cell RNA sequencing (scRNA-seq), cell line RNA sequencing, and immunohistochemistry. This signature associates CAFs with tumor progression, elevated Gleason scores, and the emergence of castration resistant prostate cancer (CRPC). Using scRNA-seq on collected samples, we demonstrated that the CAF-specific signature is not altered by ADT, maintaining its peak signal output. Identifying a PCa-specific CAF signature and observing signaling changes in CAFs after ADT lay essential groundwork for further PCa studies.