Gleason Score Research Articles

Construction of a cuproptosis‑related lncRNA signature to predict biochemical recurrence of prostate cancer.

Biochemical recurrence (BCR) is common in prostate cancer (PCa), and patients with BCR usually have a poor prognosis. Cuproptosis is a unique type of cell death, and copper homeostasis is crucial to the occurrence and development of malignancies. The present study aimed to explore the prognostic value of cuproptosis-related long non-coding RNAs (lncRNAs; CRLs) in PCa and to develop a predictive signature for forecasting BCR in patients with PCa. Using The Cancer Genome Atlas database, transcriptomic, mutation and clinical data were collected from patients with PCa. A total of 121 CRLs were identified using Pearson's correlation coefficient. Subsequently, a 6-CRL signature consisting of AC087276.2, CNNM3-DT, AC090198.1, AC138207.5, METTL14-DT and LINC01515 was created to predict the BCR of patients with PCa through Cox and least absolute shrinkage and selection operator regression analyses. Kaplan-Meier curve analysis demonstrated that high-risk patients had a low BCR-free survival rate. In addition, there was a substantial difference between the high- and low-risk groups in the immune microenvironment, immune therapy, drug sensitivity and tumor mutational burden. A nomogram integrating the Gleason score, 6-CRL signature and clinical T-stage was established and evaluated. Finally, the expression of signature lncRNAs in PCa cells was verified through reverse transcription-quantitative PCR. In conclusion, the 6-CRL signature may be a potential tool for making predictions regarding BCR in patients with PCa, and the prognostic nomogram may be considered a practical tool for clinical decision-making.

Correlation of Transrectal Ultrasonography Guided Prostate Biopsy Gleason Score Results with Prostate Volume in Patients with Prostate Specific Antigen Level Between 2.5-10 ng/mL

Correlation of Transrectal Ultrasonography Guided Prostate Biopsy Gleason Score Results with Prostate Volume in Patients with Prostate Specific Antigen Level Between 2.5-10 ng/mL

A Multi-Institutional Study of Magnetic Resonance/Ultrasound Fusion-Guided Nanoparticle-Directed Focal Therapy for Prostate Ablation.

Focal therapy aims to provide a durable oncologic treatment option for men with prostate cancer (PCa), while preserving their quality of life. Most focal therapy modalities rely on the direct tissue effect, resulting in a possible nontargeted approach to ablation. Here, we report the results of the first human feasibility trial utilizing nanoparticle-directed focal photothermal ablation for PCa. A prospective, open-label, single-arm, multicenter study of men with localized PCa in Gleason Grade Group 1 to 3 was conducted. Men received a single infusion of gold nanoparticles (AuroShells), followed by magnetic resonance (MR)/ultrasound (US) fusion-guided laser excitation of the target tissue to induce photothermal ablation. MRI was used to assess the effectiveness of prostate tissue ablation at 48 to 96 hours, 3 months, and 12 months post treatment. At 3 months, a targeted fusion biopsy of the lesion(s) was conducted. At 12 months, a targeted fusion biopsy and standard templated biopsy were performed. Treatment success was determined based on a negative MR/US fusion biopsy outcome within the treated area. Forty-six men were enrolled in the study, and 44 men with 45 lesions completed nanoparticle infusion and laser treatment. The mean PSA level at baseline was 9.5 ng/mL, which decreased to 5.9 ng/mL at 3 months and to 4.7 ng/mL at 12 months (P < .0001). The oncologic success rates at 3 and 12 months resulted in 29 (66%) and 32 (73%) of 44 patients, respectively, being successfully treated, confirmed with negative MR/US fusion biopsies within the ablation zone. Among Gleason Grade Group, maximum lesion diameter on MRI, prostate volume, and Prostate Imaging Reporting and Data System scoring, the maximum lesion diameter was significantly associated with the odds of treatment failure at 12 months (P = .046). Nanoparticle-directed focal laser ablation of neoplastic prostate tissue resulted in 73% of patients with successful treatment at 12 months post treatment, confirmed by negative MR/US fusion biopsy of the treated lesion and a systematic biopsy. 02680535.

Prostate cancer treatment recommendation study based on machine learning and SHAP interpreter.

This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different machine learning algorithms were applied to develop treatment options for predicting patients with prostate cancer, differentiating between surgical and non-surgical treatments. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value. The Shapley Additive Explanations (SHAP) method was employed to investigate the key factors influencing the prediction process. Survival analysis methods were used to compare the survival rates of different treatment options. The CatBoost model yielded the best results (AUC = 0.939, sensitivity = 0.877, accuracy = 0.877). SHAP interpreters revealed that the T stage, cancer stage, age, cores positive percentage, prostate-specific antigen, and Gleason score were the most critical factors in predicting treatment options. The study found that surgery significantly improved survival rates, with patients undergoing surgery experiencing a 20.36% increase in 10-year survival rates compared with those receiving non-surgical treatments. Among surgical options, radical prostatectomy had the highest 10-year survival rate at 89.2%. This study successfully developed a predictive model to guide treatment decisions for prostate cancer. Moreover, the model enhanced the transparency of the decision-making process, providing clinicians with a reference for formulating personalized treatment plans.

Application of proton density fat fraction imaging in risk stratification of prostate cancer.

Prostate cancer (PCa) as one of the most prevalent malignancies in men. We introduced a non-invasive quantitative measurement of intraprostatic fat content based on magnetic resonance proton density fat fraction (PDFF) imaging. The study aims to determine the fat fraction (FF) of PCa using proton density magnetic resonance imaging (MRI), gather clinical and routine MRI characteristics, and identify risk factors for high-risk PCa through multifactorial logistic regression. Clinical and imaging data from 191 pathologically confirmed PCa patients were collected. Patients were stratified based on Gleason score (GS), with 63 in the intermediate- and low-risk group (GS =3+3, 3+4) and 128 in the high-risk group (GS ≥4+3). All patients underwent routine prostate MRI and FF imaging. Clinical and imaging data related to PCa were analyzed, including age, body mass index (BMI), prostate volume (PV) measured by MRI, smoking history, alcohol history, diabetes history, serum prostate-specific antigen (PSA) level, apparent diffusion coefficient (ADC) value, T2 signal intensity (T2SI), Prostate Imaging Reporting and Data System 2.1 (PI-RADS 2.1) score, GS, lesion FF, whole gland FF, periprostatic fat thickness (PPFT), and subcutaneous fat thickness (SFT). Independent risk factors for stratifying PCa risk were identified through multivariate logistic regression analysis, and a predictive model was established. Receiver operating characteristic (ROC) curve analysis was conducted for visual analysis. Significant differences were found in BMI, PV, PSA, tumor ADC value, standard T2SI, PI-RADS score, lesion FF, and PPFT between low- and medium-risk and high-risk groups (P<0.05). No significant differences were observed in age, smoking history, drinking history, diabetes history, and SFT between the two groups (P>0.05). GS correlated significantly with FF (ρ=0.6, P<0.001), PSA (ρ=0.432, P<0.001), ADC value (ρ=-0.379, P<0.001), and PI-RADS (ρ=0.366, P<0.001). Multiple logistic regression analysis revealed that an increase in FF, a PI-RADS score increase of 5 points, and a decrease in ADC value and PV were independent predictors of high-risk PCa (P<0.05). The ROC curve showed that the best cut-off value for the model was 0.67, with an area under the curve (AUC) of 0.907, sensitivity of 78.1%, and specificity of 88.9%. The FF of PCa determined by proton density MRI is significantly associated with GS, serving as an independent predictor of high-risk PCa.

Prediction of high-risk prostate cancer based on the habitat features of biparametric magnetic resonance and the omics features of contrast-enhanced ultrasound

Rationale and objectivesTo predict high-risk prostate cancer (PCa) by combining the habitat features of biparametric magnetic resonance imaging (bp-MRI) with the omics features of contrast-enhanced ultrasound (CEUS). Materials and methodsThis study retrospectively collected patients with PCa confirmed by histopathology from January 2020 to June 2023. All patients underwent bp-MRI and CEUS of the prostate, followed by a targeted and transrectal systematic prostate biopsy. The cases were divided into the intermediate-low-risk group (Gleason score ≤7, n = 59) and high-risk group (Gleason score ≥8, n = 33). Radiomics prediction models, namely, MRI_habitat, CEUS_intra, and MRI-CEUS models, were developed based on the habitat features of bp-MRI, the omics features of CEUS, and a merge of features of the two, respectively. Predicted probabilities, called radscores, were then obtained. Clinical-radiological indicators were screened to construct clinic models, which generated clinic scores. The omics–clinic model was constructed by combining the radscore of MRI-CEUS and the clinic score. The predictive performance of all the models was evaluated using the receiver operating characteristic curve. ResultsThe area under the curve (AUC) values of the MRI-CEUS model were 0.875 and 0.842 in the training set and test set, respectively, which were higher than those of the MR_habitat (training set: 0.846, test set: 0.813), CEUS_intra (training set: 0.801, test set: 0.743), and clinic models (training set: 0.722, test set: 0.611). The omics–clinic model achieved a higher AUC (train set: 0.986, test set: 0.898). ConclusionsThe combination of the habitat features of bp-MRI and the omics features of CEUS can help predict high-risk PCa.

Prognostic factors in post-prostatectomy salvage radiotherapy setting with and without hormonotherapy: An individual patient data analysis of randomized trials from ICECaP database

BackgroundEarly salvage radiotherapy (SRT) is the standard of care for biochemical recurrence post-prostatectomy but outcomes are heterogeneous. ObjectiveTo develop a risk scoring system based on relevant standard-of-care clinico-pathological prognostic factors for patients treated with SRT with and without hormonal therapy (HT). Design, setting, and participantsThe Intermediate Clinical Endpoints in Cancer of the Prostate (ICECaP) database included three randomized trials (Individual patients’ data from 1647 subjects) assessing SRT (GETUG-AFU-16; NRG/RTOG-9601, and a subset of EORTC-22911). Outcome measurements and statistical analysisOutcomes were clinical progression (CP). metastasis free-survival (MFS) and overall survival (OS). Clinico-pathological factors, including pathological Gleason Score (GS), PSA at SRT start, margin status, persistent PSA post-RP and time from RP to SRT were evaluated by multivariable models stratified by type of treatment. Results and limitationsOn multivariable analysis PSA ≥ 0.5 ng/mL at SRT start, GS ≥ 8 and negative margin status were the three strongest prognostic factors. Three prognostic groups defined by number of these risk features (high risk: 2 or 3; intermediate risk: 1 and low risk: 0) were strongly associated with OS, MFS and CP outcomes with SRT alone or with HT. This prognostic group definition was also relevant for patients with persistent PSA post RP and for patients treated < 1 year from RP to SRT and with and without HT. ConclusionA risk score for patients receiving SRT with or without HT, using three standard-of-care clinico-pathological risk factors provides refined prognostic information for individual patient counselling. Patient summaryBy using a composite score of pathology grading (Gleason Score), PSA at start of salvage radiation and margin status data, physicians can provide patients with more refined information on the risk of a second relapse after receiving radiation to the prostate bed after a prostatectomy for a rising or persistent PSA, both with and without hormonal therapy.

Salvage local treatment for recurrent prostate cancer after focal therapy: A systematic review and meta-analysis

ObjectivesTo evaluate the role of salvage local treatment in managing recurrent PCa following FT, focusing on oncological and functional outcomes. MethodsA systematic review and meta-analysis were performed following the PRISMA framework. A comprehensive literature search using the PubMed/MEDLINE and EMBASE databases was performed until July 2023. Eligible studies included patients with clinically localised PCa initially treated with FT, who experienced relapse during surveillance and subsequently underwent salvage radical prostatectomy (sRP), salvage external beam radiation therapy (sEBRT) or salvage focal therapy (sFT). The primary endpoint was the biochemical recurrence rate post-salvage treatment. The secondary endpoints were functional outcomes, including urinary incontinence and erectile dysfunction rates. ResultsIn 26 retrospective studies including 990 patients, the overall pooled biochemical recurrence rate postsalvage treatment was 26%. The subgroup analysis revealed a biochemical recurrence rate of 20%, 22%, and 42% after sRP, sEBRT, and sFT, respectively. The overall pooled rate of urinary incontinence was 20%. Salvage FT had the lowest prevalence of urinary incontinence, followed by sRP and sEBRT. The overall pooled rate of erectile dysfunction was 43%. Salvage RP had the highest prevalence of erectile dysfunction, followed by sFT and sEBRT. Substantial heterogeneity was observed among the studies, primarily due to different sample sizes. Meta-regression analysis revealed no to low contributions of salvage treatment modalities, extent of ablation, age, prostatic specific antigen level before salvage treatment, proportion of patients with Gleason score ≥7 at recurrence, and time between the primary and salvage therapies to heterogeneity. ConclusionSalvage local treatment for recurrent PCa after FT is feasible, and it provides acceptable oncological and functional outcomes. Among all treatment modalities, sRP and sEBRT appeared to have the lowest biochemical recurrence rates, whereas sFT was associated with improved functional outcomes.

Hypofractionated Dose Escalation Radiotherapy for High-Risk Prostate Cancer: the survival analysis of the Prostate Cancer Study-5 (PCS-5), a GROUQ-led phase III trial

Background and objectiveProstate Cancer Study 5 (PCS5) compared conventional fractionated radiotherapy (CFRT) with hypofractionated radiotherapy (HFRT) in high-risk prostate cancer (PCa) patients, hypothesizing similar toxicity and survival outcomes. This report presents the efficacy analysis. MethodsPCS5 is a Canadian multicenter, open-label, phase 3 randomized control trial. Men with histologically proven, clinically localized PCa with one or more high-risk features (T3/T4, Gleason score ≥8, and prostate-specific antigen >20) were eligible. Patients were randomized 1:1 to CFRT (76 Gy/38 fractions [Fx] to the prostate and 46 Gy/23 Fx to the pelvic lymph nodes [PLNs]) or HFRT (68 Gy/25 Fx to the prostate and 45 Gy/25 Fx to the PLNs) and 28 mo of androgen suppression. The primary endpoint was toxicity; secondary endpoints included survival outcomes. Key findings and limitationsOf 329 patients, 164 were randomized to HFRT and 165 to CFRT, with 159 in the HFRT arm and 160 in the CFRT arm included in survival analyses. At the 5-yr median follow-up, there were no significant differences in overall survival (OS; 90.3% vs 89.7%; risk ratio [RR]: 1.01; 95% confidence interval [CI]: 0.93–1.09), PCa-specific survival (PCSS; 97.4% vs 97.5%; RR: 1.00; 95% CI: 0.93–1.07), biochemical recurrence–free survival (BCRFS; 85.2% vs 85.2%; RR: 1.00; 95% CI: 0.91–1.10), or distant metastasis–free survival (DMFS; 87.1% vs 87.1%; RR: 1.00; 95% CI: 0.92–1.09). Hazard ratios were 0.92 (95% CI: 0.56–1.53) for OS, 1.31 (95% CI: 0.46–3.78) for PCSS, 0.85 (95% CI: 0.56–1.30) for BCRFS, and 0.90 (95% CI: 0.56–1.43) for DMFS. Sample size was a limiting factor. Conclusions and clinical implicationsThere were no differences in survival outcomes between HFRT (68 Gy/25 Fx) and CFRT (76 Gy/38 Fx). HFRT, including PLN radiotherapy and long-term androgen deprivation therapy, should be considered a new standard of care for high-risk PCa patients undergoing external beam radiotherapy.

Incorporation of mpMRI before prostate biopsy shall be universal or selective: A prospective observational study

Purpose: The aim of this study is to evaluate the role of multiparametric magnetic resonance imaging (mpMRI) as a triage workup in the diagnostic pathway of suspected prostate cancer (PCa) in our population. Material and methods: This prospective observational study was conducted at lesser than details of site are removed for blinded peer review &gt; on biopsy-naive patients from May 2021 to December 2022. We included patients aged 40 to 80 years with clinical suspicion of PCa, prostate-specific antigen (PSA) level &gt;4 ng/mL, abnormal digital rectal examination (DRE), or all the above. All patients first underwent 1.5-T mpMRI and transrectal ultrasound-guided biopsy using the cognitive biopsy technique. Results: A total of 95 patients were included, with the majority of them (64.21%) being ≥66 years old. Of these, 69 patients had abnormal DRE findings, 89 had PSA ≥4 ng/mL, and 64 had both elevated PSA and abnormal DRE findings. PCa was detected in 6.25%, 54.84%, 71.43%, and 96.43% of patients with lesions of Prostate Image Reporting and Data System scores of 2, 3, 4, and 5, respectively. Using Prostate Image Reporting and Data System score of 3 as a biopsy threshold resulted in high sensitivity (98.31%) and low specificity (41.67%) for PCa detection. The proportion of Gleason score of ≥7 cancer-detected cores in the magnetic resonance imaging-guided cognitive biopsy was significantly higher than that in the standard 12-core biopsy (86.54% versus 61.45%; P &lt; 0.001). Conclusion: The incorporation of prebiopsy mpMRI could be used as a diagnostic pathway for suspected PCa before transrectal ultrasound-guided biopsy.

Risk of Biochemical Recurrence and Metastasis in Prostate Cancer Patients Treated with Radical Prostatectomy After a 10-year Disease-free Interval

Background and objectiveProstate-specific antigen (PSA) testing is used to follow up prostate cancer (PCa) patients treated with radical prostatectomy (RP). Research on PSA thresholds for identifying PCa patients with biochemical recurrence (BCR) who are at a higher risk of progression yielded inconclusive results. This study aims to investigate the risk of late BCR in PCa patients treated with RP and long postoperative (120 mo) undetectable PSA follow-up, and to identify prognostic factors for late BCR within this patient cohort. MethodsPCa patients treated with curative RP (1992–2012) and free of BCR during the first 120 mo following RP were retrospectively identified within five European tertiary centers; BCR was defined as two consecutive PSA values of ≥0.2 ng/ml. Kaplan-Meier and Cox regression models tested for an association between BCR and patient or tumor characteristics. Key findings and limitationsThe study cohort consisted of 4639 patients, of whom 243 (5.2%) developed BCR at a medium follow-up of 147 mo. Of those with BCR, 23 (9.5%) subsequently developed metastatic progression. In Kaplan-Meier models, BCR-free survival differed according to advanced tumor status. In multivariable Cox regression models, pT stage (pT3a: hazard ratio [HR]: 1.46; pT3b: HR: 2.42), pathological Gleason score (pGS 3 + 4: HR: 1.71; pGS ≥4 + 3: HR: 2.47), surgical margin (R1/Rx: HR: 1.72), and pNx stage (pNx: HR: 0.72) represented independent predictors for BCR (all p < 0.05). Conversely, age, PSA at diagnosis, and year of surgery failed to achieve independent predictor status for BCR. Conclusions and clinical implicationsAmong PCa patients with an uneventful follow-up of at least 10 yr after RP, still one in 20 patients subsequently develop late BCR. Nevertheless, late BCR and subsequent progression to metastasis (0.3%) rates in patients with pT2 stage and pGS ≤3 + 4 were strikingly low, implicating that abandoning follow-up beyond an uneventful period of 10 yr is justifiable within this cohort of patients. Patient summaryIn this study, prostate cancer patients treated with a radical prostatectomy and at least 10 yr of uneventful prostate-specific antigen testing were identified within five European centers. Relying on these patients, the rate of subsequent late biochemical recurrence was calculated and risk factors were identified for biochemical recurrence following 10 yr of uneventful prostate-specific antigen testing.

Gleason Grade Restaging After Prostatectomy in Irish Hospitals

Gleason Grade Restaging After Prostatectomy in Irish Hospitals

Consistent predictive ability of prostate-specific antigen density prediction model for clinically significant prostate cancer across age strata.

Prebiopsy prostate-specific antigen density (PSAD) is a well-known predictor of clinically significant prostate cancer (csPCa). Since prostate-specific antigen(PSA) and prostate volume (PV) increase normally with aging, PSAD thresholds may vary. The purpose of the study was to determine if PSAD was predictive of csPCa in different age strata. We retrospectively reviewed our institutional database for patients who underwent multiparametricmagnetic resonance imaging (MRI) between January 2016 and December 2021. We included patients who had post-MRI prostate biopsies. Based on age, we divided our cohort into four subgroups (groups 1-4): <55, 55-64, 65-74, and ≥75 years old. PSAD accuracy was estimated by the area under the curve (AUC) as a predictive model for differentiating csPCa between the groups. CsPCa was defined as a Gleason Grade Group 2 or higher. Three different PSAD thresholds (0.1, 0.15, and 0.2) were tested across the groups for sensitivity, specificity, and positive predictive value (PPV) and negative predictive value(NPV). Chi-square and analysis of variance tests were used for bivariate analysis. All analyswere completed using R 4.3 (R Core Team, 2023). Among 1913 patients, 883 (46.1%) had prostate biopsies. In groups 1, 2, 3, and 4, there were 62 (7%), 321 (36.4%), 404 (45.8%), and 96 (10.9%) patients, respectively. Median PSA was 5.6 (interquartile range 3.4-8.1), 6.2 (4.8-9), 6.8 (5.1-9.7), and 9 (5.6-13), respectively (p < 0.01). Median PV was 42.3 (30-62), 51 (36-77), 55.5 (38-85.9), and 59.3 (42-110) mL, respectively (p < 0.01). No difference was observed in median PSAD between age groups 1-4 (0.1 [0.07-0.16], 0.11 [0.08-0.18], 0.1 [0.07-0.19], and 0.1 [0.07-0.2]), respectively (p = 0.393). CsPCa was diagnosed in 241 (27.3%) patients, of which 10 (16.1%), 65 (20.2%), 121 (30%), and 45 (46.7%) were in groups 1-4, respectively (p < 0.001). For groups 1-4, the PSAD AUC for predicting csPCa was 0.75, 0.68, 0.71, and 0.74. While testing PSAD threshold of 0.15 across the different age groups (1-4), the PPV vs.NPV was 39.1 vs. 93.2, 33.6 vs. 87, 50.9 vs. 80.8, and 66.1 vs. 64.7, respectively. PSAD prediction model was found to be similar among different age groups. In young patients, PSAD had a high NPV but low PPV. With increasing age, the opposite trend was observed, likely due to higher disease prevalence. While PSAD thresholds may be less useful in older patients to rule out higher-grade prostate cancer, the clinical consequences of these diagnoses require a case-by-case evaluation.

Altered expression of vesicular trafficking machinery in prostate cancer affects lysosomal dynamics and provides insight into the underlying biology and disease progression.

This study focuses on the role of lysosomal trafficking in prostate cancer, given the essential role of lysosomes in cellular homoeostasis. Lysosomal motility was evaluated using confocal laser scanning microscopy of LAMP-1-transfected prostate cells and spot-tracking analysis. Expression of lysosomal trafficking machinery was evaluated in patient cohort databases and through immunohistochemistry on tumour samples. The roles of vesicular trafficking machinery were evaluated through over-expression and siRNA. The effects of R1881 treatment on lysosome vesicular trafficking was evaluated by RNA sequencing, protein quantification and fixed- and live-cell microscopy. Altered regulation of lysosomal trafficking genes/proteins was observed in prostate cancer tissue, with significant correlations for co-expression of vesicular trafficking machinery in Gleason patterns. The expression of trafficking machinery was associated with poorer patient outcomes. R1881 treatment induced changes in lysosomal distribution, number, and expression of lysosomal vesicular trafficking machinery in hormone-sensitive prostate cancer cells. Manipulation of genes involved in lysosomal trafficking events induced changes in lysosome positioning and cell phenotype, as well as differential effects on cell migration, in non-malignant and prostate cancer cells. These findings provide novel insights into the altered regulation and functional impact of lysosomal vesicular trafficking in prostate cancer pathogenesis.

Gene Signature for Predicting Metastasis in Prostate Cancer Using Primary Tumor Expression Profiles.

Metastasis is the leading cause of death in patients diagnosed with prostate cancer (PCa), underscoring the need for reliable prediction tools to forecast the risk of metastasis at an early stage. Here, we utilize the gene expression profiles of 1,000 unique primary tumors from patients with localized PCa to develop a gene signature capable of predicting metastasis. Our signature, termed Meta-Score, comprises forty-five genes that can accurately distinguish primary tumor with high propensity for metastasis across different patient cohorts. Notably, Meta-Score maintained its robust predictive performance in an internal validation cohort of comprising primary tumor samples from 239 patients. In addition to its robust predictive performance, Meta-Score demonstrates a significant association with survival, independent of Gleason score in two independent patient cohorts, underscoring its prognostic utility. Taken together, Meta-Score is a robust risk-stratification tool that can be leveraged to identify patients at high-risk of metastasis and unfavorable survival using their primary tumor gene expression profiles.

UQCRB and LBH are correlated with Gleason score progression in prostate cancer: Spatial transcriptomics and experimental validation

Prostate cancer (PCa) is a multifocal disease characterized by genomic and phenotypic heterogeneity within a single gland. In this study, Visium spatial transcriptomics (ST) analysis was applied to PCa tissues with different histological structures to infer the molecular events involved in Gleason score (GS) progression. The spots in tissue sections were classified into various groups using Principal Component Analysis (PCA) and Louvain clustering analysis based on transcriptome data. Anotation of the spots according to GS revealed notable similarities between transcriptomic profiles and histologically identifiable structures. The accuracy of macroscopic GS determination was bioinformatically verified through malignancy-related feature analysis, specifically inferred copy number variation (inferCNV), as well as developmental trajectory analyses, such as diffusion pseudotime (DPT) and partition-based graph abstraction (PAGA). Genes related to GS progression were identified from the differentially expressed genes (DEGs) through pairwise comparisons of groups along a GS gradient. The proteins encoded by the representative oncogenes UQCRB and LBH were found to be highly expressed in advanced-stage PCa tissues. Knockdown of their mRNAs significantly suppressed PCa cell proliferation and invasion. These findings were validated using The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset, as well as through histological and cytological experiments. The results presented here establish a foundation for ST-based evaluation of GS progression and provide valuable insights into the GS progression-related genes UQCRB and LBH.

HLA-DR association with prostate cancer in southwestern Nigeria: A preliminary experience using tissue microarray analysis

Background: Prostate cancer is a disease of gargantuan proportion worldwide. Current therapeutic modalities do not guarantee long survival or cure. Immune-based therapy may be a key solution to the treatment and cure of the disease, despite the limited gain recorded presently. This study aims to determine the association of immune marker HLA-DR with prostate cancer and the usefulness of tissue microarray analysis in small biopsies. Methods: Forty and eight formalin-fixed, paraffin-embedded prostate needle biopsies were processed by tissue microarray analysis and stained with anti HLA-DR monoclonal antibody. The age, Gleason score and Gleason grade groups were noted. Semi-quantitative IHC scoring was done and results analyzed using SPSS version 25. Results: The age range was 54-to 89 years (mean = 68.8; median = 68.0; SD = 7.7). Majority of cases fell into the 60-79 years age group. There was moderate and strong staining with HLA-DR in 18.7% of cases. There was no significant association between HLA-DR and independent variables such as age (r=-0.015, p=0.921) and Gleason score (r=0.226, p=0.123). Conclusions: Prostate cancer is at its peak occurrence in the 60-79 years age group and a proportion of cases express HLA-DR, an expression that is independent of age, Gleason score or Gleason grade group. Contribution of HLA-DR to prostate cancer is probably minimal. Tissue microarray technique on needle biopsies is advocated in low-income countries if tissue loss can be minimized.

2502: Can we predict extraprostatic/metastatic disease on PSMA PET-CT based on PSA, MRI and Gleason grade?

2502: Can we predict extraprostatic/metastatic disease on PSMA PET-CT based on PSA, MRI and Gleason grade?

Traditional Prostate Cancer Risk Assessment Scales Do Not Predict Outcomes from Brain Metastases: A Population-Based Predictive Nomogram.

Brain metastases are an uncommon yet life-limiting manifestation of prostate cancer. However, there is limited insight into the natural progression, therapeutics, and patient outcomes for prostate cancer once metastasized to the brain. This is a retrospective study of 461 patients with metastatic prostate cancer to the brain with a primary outcome of median overall survival (OS). The Surveillance, Epidemiology, and End Results (SEER) database was examined using Cox regression univariate and multivariable analyses, and a corresponding nomogram was developed. The median overall survival was 15 months. In the multivariable analysis, Hispanic patients had significantly increased OS (median OS 17 months, p = 0.005). Patients with tumor sizes greater than three centimeters exhibited significantly reduced OS (median OS 19 months, p = 0.014). Patients with additional metastases to the liver exhibited significantly reduced OS (median OS 3.5 months, p < 0.001). Increased survival was demonstrated in patients treated with chemotherapy or systemic treatment (median OS 19 months, p = 0.039), in addition to radiation and chemotherapy (median OS 25 months, p = 0.002). The nomogram had a C-index of 0.641. For patients with prostate metastases to the brain, median OS is influenced by race, tumor size, presence of additional metastases, and treatment. The lack of an association between traditional prostate cancer prognosis metrics, including Gleason and ISUP grading, and mortality highlights the need for individualized, metastasis-specific prognosis metrics. This prognostic nomogram for prostate metastases to the brain can be used to guide the management of affected patients.

Genomic landscape of early-stage prostate adenocarcinoma in Mexican patients: an exploratory study

BackgroundHealth disparities have been highlighted among patient with prostate adenocarcinoma (PRAD) due to ethnicity. Mexican men present a more aggressive disease than other patients resulting in less favorable treatment outcome. We aimed to identify the mutational landscape which could help to reduce the health disparities among minority groups and generate the first genomics exploratory study of PRAD in Mexican patients.MethodsParaffin-embedded formalin-fixed tumoral tissue from 20 Mexican patients with early-stage PRAD treated at The Instituto Nacional de Cancerología, Mexico City from 2017 to 2019 were analyzed. Tumoral DNA was prepared for whole exome sequencing, the resulting files were mapped against h19 using BWA-MEM. Strelka2 and Lancet packages were used to identify single nucleotide variants (SNV) and insertions or deletions. FACETS was used to determine somatic copy number alterations (SCNA). Cancer Genome Interpreter web interface was used to determine the clinical relevance of variants.ResultsPatients were in an early clinical stage and had a mean age of 59.55 years (standard deviation [SD]: 7.1 years) with 90% of them having a Gleason Score of 7. Follow-up time was 48.50 months (SD: 32.77) with recurrences and progression in 30% and 15% of the patients, respectively. NUP98 (20%), CSMD3 (15%) and FAT1 (15%) were the genes most frequently affected by SNV; ARAF (75%) and ZNF419 (70%) were the most frequently affected by losses and gains SNCA’s. One quarter of the patients had mutations useful as biomarkers for the use of PARP inhibitors, they comprise mutations in BRCA, RAD54L and ATM. SBS05, DBS03 and ID08 were the most common mutational signatures present in this cohort. No associations with recurrence or progression were identified.ConclusionsThis pilot study reveals the mutational landscape of early-stage prostate adenocarcinoma in Mexican men, providing a first approach to understand the mutational patterns and actionable mutations in early prostate cancer can inform personalized treatment approaches and reduce the underrepresentation in genomic cancer studies.