Survival In Prostate Cancer Patients Research Articles

Androgen receptor, PARP signaling, and tumor microenvironment: the 'perfect triad' in prostate cancer?

Aberrations in the homologous recombination repair (HRR) pathway in prostate cancer (PCa) provide a unique opportunity to develop therapeutic strategies that take advantage of the reduced tumor ability to repair DNA damage. Poly-ADP-ribose polymerase (PARP) inhibitors (PARPi) have been shown to prolong the survival of PCa patients with HRR defects, particularly in those with Breast Cancer type 1 susceptibility protein/Breast Cancer type 2 susceptibility protein alterations. To expand the benefit of PARPi to patients without detectable HRR alterations, multiple preclinical and clinical studies are addressing potential synergies between PARPi and androgen receptor signaling inhibitors, and these strategies are also being evaluated in combination with other drugs such as immune checkpoint inhibitors. However, the effectiveness of these combining therapies could be hindered by multiple mechanisms of resistance, including also the role played by the immunosuppressive tumor microenvironment. In this review, we summarize the use of PARPi in PCa and the potential synergies with different molecular pathways. However, numerous unanswered questions remain, including the identification of the patient population that could benefit most from PARPi, determining whether to use PARPi as monotherapy or in combination, and finding the optimal timing of PARPi, expanding the use of genomic tests, and optimizing combination therapies.

Development and validation of two nomograms for predicting overall survival and Cancer-specific survival in prostate cancer patients with bone metastases: a population-based study

BackgroundProstate cancer with bone metastasis has significant invasiveness and markedly poorer prognosis. The purpose of this study is to establish two nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of prostate cancer patients with bone metastasis.MethodsFrom January 2000 to December 2018, a total of 2683 prostate adenocarcinoma with bone metastasis patients were identified from the Surveillance, Epidemiology, and End Results Program (SEER) database. These patients were then divided into a training cohort and a validation cohort, with OS and CSS as the study endpoints. Correlation analyses were employed to assess the relationship between variables. Univariate and multivariate Cox analyses were utilized to ascertain the independent prognostic factors. Calibration curves and the area under the time-dependent receiver operating characteristic curve (time-dependent AUC) were employed to evaluate discrimination and calibration of the nomogram. DCA was applied to examine accuracy and clinical benefits. The clinical utility of the nomogram and the AJCC Stage System was compared using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Lastly, the risk stratifications of the nomogram and the AJCC Stage System were compared.ResultsThere was no collinearity among the variables that were screened. The results of multivariate Cox regression analysis showed that seven variables (age, surgery, brain metastasis, liver metastasis, lung metastasis, Gleason score, marital status) and six variables (age, surgery, lung metastasis, liver metastasis, Gleason score, marital status) were identified to establish the nomogram for OS and CSS, respectively. The calibration curves, time-dependent AUC curves, and DCA revealed that both nomograms had pleasant predictive power. Furthermore, NRI and IDI confirmed that the nomogram outperformed the AJCC Stage System.ConclusionBoth nomograms had satisfactory accuracy and were validated to assist clinicians in evaluating the prognosis of PABM patients.

O03 - Complete biochemical response below 0.1 ng/ml predicts long-term therapy-free survival of prostate cancer patients treated with salvage lymph node dissection via PSMA-radioguided surgery

O03 - Complete biochemical response below 0.1 ng/ml predicts long-term therapy-free survival of prostate cancer patients treated with salvage lymph node dissection via PSMA-radioguided surgery

Fanconi anemia pathway regulation by FANCI in prostate cancer.

Prostate cancer is one of the leading causes of death among men worldwide, and thus, research on the genetic factors enabling the formation of treatment-resistant cancer cells is crucial for improving patient outcomes. Here, we report a cell line-specific dependence on FANCI and related signaling pathways to counteract the effects of DNA-damaging chemotherapy in prostate cancer. Our results reveal that FANCI depletion results in significant downregulation of Fanconi anemia (FA) pathway members in prostate cancer cells, indicating that FANCI is an important regulator of the FA pathway. Furthermore, we found that FANCI silencing reduces proliferation in p53-expressing prostate cancer cells. This extends the evidence that inactivation of FANCI may convert cancer cells from a resistant state to an eradicable state under the stress of DNA-damaging chemotherapy. Our results also indicate that high expression of FA pathway genes correlates with poorer survival in prostate cancer patients. Moreover, genomic alterations of FA pathway members are prevalent in prostate adenocarcinoma patients; mutation and copy number information for the FA pathway genes in seven patient cohorts (N = 1,732 total tumor samples) reveals that 1,025 (59.2%) tumor samples have an alteration in at least one of the FA pathway genes, suggesting that genomic alteration of the pathway is a prominent feature in patients with the disease.

Development of machine learning prognostic models for overall survival of prostate cancer patients with lymph node-positive

Prostate cancer (PCa) patients with lymph node involvement (LNI) constitute a single-risk group with varied prognoses. Existing studies on this group have focused solely on those who underwent prostatectomy (RP), using statistical models to predict prognosis. This study aimed to develop an easily accessible individual survival prediction tool based on multiple machine learning (ML) algorithms to predict survival probability for PCa patients with LNI. A total of 3280 PCa patients with LNI were identified from the Surveillance, Epidemiology, and End Results (SEER) database, covering the years 2000–2019. The primary endpoint was overall survival (OS). Gradient Boosting Survival Analysis (GBSA), Random Survival Forest (RSF), and Extra Survival Trees (EST) were used to develop prognosis models, which were compared to Cox regression. Discrimination was evaluated using the time-dependent areas under the receiver operating characteristic curve (time-dependent AUC) and the concordance index (c-index). Calibration was assessed using the time-dependent Brier score (time-dependent BS) and the integrated Brier score (IBS). Moreover, the beeswarm summary plot in SHAP (SHapley Additive exPlanations) was used to display the contribution of variables to the results. The 3280 patients were randomly split into a training cohort (n = 2624) and a validation cohort (n = 656). Nine variables including age at diagnosis, race, marital status, clinical T stage, prostate-specific antigen (PSA) level at diagnosis, Gleason Score (GS), number of positive lymph nodes, radical prostatectomy (RP), and radiotherapy (RT) were used to develop models. The mean time-dependent AUC for GBSA, RSF, and EST was 0.782 (95% confidence interval [CI] 0.779–0.783), 0.779 (95% CI 0.776–0.780), and 0.781 (95% CI 0.778–0.782), respectively, which were higher than the Cox regression model of 0.770 (95% CI 0.769–0.773). Additionally, all models demonstrated almost similar calibration, with low IBS. A web-based prediction tool was developed using the best-performing GBSA, which is accessible at https://pengzihexjtu-pca-n1.streamlit.app/. ML algorithms showed better performance compared with Cox regression and we developed a web-based tool, which may help to guide patient treatment and follow-up.

Immunohistochemistry-Based Biomarkers and Impact on Outcomes Following Salvage Radiotherapy for Prostate Cancer.

Salvage radiation therapy (SRT) is a mainstay of treatment for prostate cancer patients who experience biochemical relapse following radical prostatectomy. We sought to characterize the prognostic impact of previously identified deleterious molecular phenotypes-loss of PTEN, ERG expression, and p53 mutation- upon survival in patients undergoing SRT. We analyzed an institutional database of 320 patients treated with SRT for whom prostatectomy tissue was available; tissue microarrays (TMAs) were constructed and used for genetically validated immunohistochemistry assays for PTEN, ERG, and p53. Chi-squared and Mann-Whitney's tests were used to assess association between molecular expression and clinical risk factors for adverse survival. Uni- and multivariate Cox-proportional hazards models were constructed to determine effects on biochemical (bRFS) and metastasis-free survival (MFS), calculated from end of SRT to event. Loss of PTEN (n = 123, 50%) and ERG expression (n = 118, 39.1%) were common, while p53 overexpression (signifying TP53 missense mutation) was less common (n = 21, 6.6%). On univariate Cox regression, loss of PTEN portended worse bRFS [HR 1.86; 95% CI 1.36-2.57] and MFS [HR 1.89; 1.21-2.94], with homogeneous loss associated with particularly worse MFS [HR 2.47; 1.54-3.95]. Similarly, p53 overexpression predicted worse bRFS [HR 1.95; 1.14-3.32] and MFS [HR 2.79; 1.50-5.19]. ERG expression was associated with only worse MFS [HR 1.6; 1.03-2.48]. On multivariate analysis adjusting for known prognostic features (grade, nodal involvement, pathologic stage, androgen deprivation therapy (ADT), and PSA velocity), homogeneous PTEN loss remained predictive of adverse bRFS [HR 1.73; 1.06-2.82] and MFS [HR 2.35; 1.04-5.34]. PTEN loss identified by immunohistochemistry is an independent adverse prognostic factor for both biochemical and metastasis-free survival in prostate cancer patients treated with SRT. Although clinically validated RNA expression assays also exist which are prognostic for outcomes following SRT, stromal contamination in bulk RNA could mask "loss" signals specific to tumor cells, such as PTEN. Further work is necessary to determine the optimal approach to treating patients with poor molecular prognostic features in a salvage setting.

Senescence-associated secretory phenotype constructed detrimental and beneficial subtypes and prognostic index for prostate cancer patients undergoing radical prostatectomy

BackgroundCellular senescence is growing in popularity in cancer. A dual function is played by the senescence-associated secretory phenotype (SASP) that senescent cells produce in the development of pro-inflammatory niches, tissue regeneration or destruction, senescence propagation, and malignant transformation. In this study, we conducted thorough bioinformatic analysis and meta-analysis to discover detrimental and beneficial subtypes and prognostic index for prostate cancer (PCa) patients using the experimentally confirmed SASP genes.MethodsWe identified differentially expressed and prognosis-related SASP genes and used them to construct two molecular subtypes and risk score. Another two external cohorts were used to confirm the prognostic effect of the above subtypes and risk score and meta-analysis was further conducted. Additionally, functional analysis, tumor stemness and heterogeneity and tumor microenvironment were also evaluated. We completed analyses using software R 3.6.3 and its suitable packages. Meta-analysis was performed by software Stata 14.0.ResultsThrough multivariate Cox regression analysis and consensus clustering analysis, we used VGF, IGFBP3 and ANG to establish detrimental and beneficial subtypes in the TCGA cohort, which was validated through other two independent cohorts. Meta-analysis showed that detrimental SASP group had significantly higher risk of biochemical recurrence (BCR) than beneficial SASP group (HR: 2.48). Moreover, we also constructed and validated risk score based on these genes to better guide clinical practice. DNA repair, MYC target, oxidative phosphorylation, proteasome and ribosome were highly enriched in detrimental SASP group. Detrimental SASP group had significantly higher levels of B cells, CD8+ T cells, homologous recombination deficiency, loss of heterozygosity, microsatellite instability, purity, tumor mutation burden, mRNAsi, differentially methylated probes and epigenetically regulated RNA expression than beneficial SASP group. The top mutation genes between detrimental and beneficial SASP groups were SPOP, FOXA1, KMT2C, APC, BSN, DNAH17, MYH6, EPPK1, ZNF536 and ZC3H13 with statistical significance.ConclusionsFrom perspective of SASP, we found detrimental and beneficial tumor subtypes which were closely associated with BCR-free survival for PCa patients, which might be important for the furture research in the field of PCa.

Low Alanine Aminotransferase, as a Marker of Sarcopenia and Frailty, Is Associated with Shorter Survival Among Prostate Cancer Patients and Survivors. A Retrospective Cohort Analysis of 4064 Patients

BackgroundSarcopenia is characterized by loss of muscle mass and function and is associated with frailty, a syndrome with higher likelihood of falls, fractures, physical disability, and mortality. Both frailty and sarcopenia are known markers of shorter survival in various cancer patient populations. Low alanine aminotransferase (ALT), reflecting loss of muscle mass (sarcopenia), may be associated with greater frailty and shorter survival in multiple cancers. ObjectiveTo assess the potential association between low ALT and shorter survival among prostate cancer (PCa) patients and survivors. Design, setting, and participantsThis was a retrospective analysis of a historical cohort of PCa patients and survivors. Patients were defined as those still actively receiving PCa treatment, while those no longer receiving such treatment were classified as PCa survivors. Outcome measurements and statistical analysisALT data were obtained from results for basic biochemical blood testing carried out for patients on their first hospital admission. Patients were divided into two groups: those with ALT ≥17 IU/l and those with ALT <17 IU/l. Univariate and multivariable analyses were conducted for between-group survival comparisons. Results and limitationsWe identified 9489 PCa records. The final study cohort with ALT data available included 4064 patients with ALT <40 IU/l. Of this cohort, 536 patients were actively receiving medical anticancer therapy for PCa. The mean age for the entire cohort was 74.6 yr (standard deviation 9.6) and the median ALT level was 19.28 IU/l; 1676 patients (41%) had low ALT (<17 IU/l). On univariate analysis, low ALT was associated with a 78% increase in mortality risk (95% confidence interval [CI] 1.62–1.97; p < 0.001). A sensitivity analysis of the 536 patients actively receiving medical anticancer treatment revealed that low ALT was associated with a 48% increase in mortality risk (95% CI 1.19–1.85; p = 0.001). In a multivariable model controlled for age, kidney disease, history of cerebrovascular event/transient ischemic attack, and baseline prostate-specific antigen, low ALT was still associated with a 35% increase in mortality risk (95% CI 1.12–1.63; p = 0.001). Limitations include the single-center, retrospective design. ConclusionsLow ALT, which is indicative of sarcopenia and frailty, is associated with shorter survival among PCa patients and survivors and could potentially be used for treatment personalization. Patient summaryWe compared survival for prostate cancer patients and survivors according to their blood level of the protein alanine aminotransferase (ALT). Low ALT levels in the general population are associated with loss of muscle mass. We found that in our group of prostate cancer patients and survivors, the risk of death from any cause was higher for those with low ALT levels.

M6A-modified circABCC4 promotes stemness and metastasis of prostate cancer by recruiting IGF2BP2 to increase stability of CCAR1.

Prostate cancer (PCa) is a malignant tumor of the urinary system. CircABCC4 has been demonstrated to promote the development of PCa; however, its regulatory mechanisms in PCa progression remain largely unknown. We found that circABCC4 was highly expressed in PCa tissues and cells, and elevated circABCC4 level indicated a poor overall survival of PCa patients. METTL3 overexpression increased circABCC4 expression via m6A modification in PCa cells. Functionally, knockdown of circABCC4 or METTL3 repressed PCa cell stemness, migration, and invasion in vitro and delayed PCa cancer growth and metastasis in vivo. circABCC4 knockdown-mediated inhibition in PCa cell stemness and metastasis could be counteracted by overexpression of wild-type circABCC4 with m6A sites. Mechanistically, circABCC4 recruited IGF2BP2 protein to CCAR1 mRNA, thereby enhancing CCAR1 mRNA stability and subsequent activation of the Wnt/β-catenin pathway. Overexpression of CCAR1 counteracted the inhibitory effect of circABCC4 silencing on PCa cell stemness and metastasis. These results revealed that m6A-modified circABCC4 by METTL3 facilitated PCa cell stemness and metastasis by interacting with IGF2BP2 to increase the stability and expression of CCAR and subsequent expression of Wnt/β-catenin target genes. Our findings suggest circABCC4 as a promising therapeutic target for PCa.

Development and external validation of a novel prognostic nomogram for overall survival in prostate cancer patients with bone metastatic: a retrospective study of the SEER-based and a single Chinese center.

Prostate cancer (PCa) patients with bone metastases (BM) often face a poor prognosis, a leading contributor to mortality within this group. This study aims to develop a novel prognostic nomogram to predict overall survival for them. We retrospectively analyzed PCa patients with BM from Surveillance, Epidemiology, and End Results (SEER) database and our hospital. Independent prognostic factors were identified using univariate and multivariate Cox regression analyses for the creation of a nomogram. Calibration curves and receiver operating characteristic (ROC) curves, along with the concordance index (C-index) and decision curve analysis (DCA), were employed to evaluate the performance of the constructed nomogram. A total of 12,344 PCa patients with BM, derived from 2010 to 2019 SEER database, were randomly allocated into a training cohort (n = 8640) and an internal validation cohort (n = 3704). Additionally, an external validation cohort (n = 126) from our hospital. The novel nomogram integrates multiple factors: age, race, histopathology, organ metastasis, chemotherapy, Gleason score, and prostate-specific antigen (PSA). C-index for the training, internal validation, and external validation cohorts were 0.770 (0.766-0.774), 0.756 (0.749-0.763), and 0.751 (0.745-0.757) respectively. Similarly, the area under the curve (AUC) for each cohort exhibited comparable results (training cohort-3-year: 0.682, 6-year: 0.775, 9-year: 0.824; internal validation cohort-3-year: 0.681, 6-year: 0.750, 9-year: 0.806; external validation cohort-2-year: 0.667, 3-year: 0.744, 4-year: 0.800), indicating that the nomogram possesses robust discriminative ability. Calibration curve and DCA curve further proved the reliability and accuracy of the prognostic nomogram. This study determined the independent risk factors for prostate cancer (PCa) patients with bone metastasis (BM) and subsequently developed a robust prognostic nomogram to predict overall survival (OS). This tool can serve to guide precise clinical treatment strategies for these patients.

Automatic prediction model of overall survival in prostate cancer patients with bone metastasis using deep neural networks

Abstract Objectives Bone is the most common site of metastasis in prostate cancer (PCa) patients and is correlated with poor prognosis and increasing economic burden. Few studies have analyzed the prognostic prediction for metastatic PCa patients with the assistance of neural networks. Methods Four convolutional neural network (CNN) models are developed and evaluated to predict the overall survival (OS) of PCa patients with bone metastasis. All the CNN models are first trained with 64 samples and evaluated with 10 samples; two models use only bone scan images and two models use both bone scan images and clinical parameters (CPs). The predictions of the best models are compared with those by two urology surgeons on 20 test samples. Results Our best models can predict OS of PCa patients with bone metastasis with AUC=0.8022 by using only bone scan images and AUC=0.8132 by using both bone scan images and CPs on 20 test samples. The best Youden indexes of the two models are 0.6263 and 0.7142, respectively, which are 0.3077 and 0.3131 higher than that of the urologists’ average Youden index, which indicate that CNN models exhibit significant advantages. Conclusions CNN models are suitable to predict OS in PCa patients with bone metastasis using bone scan images and CPs. Our models show better performance in terms of accuracy and stability than urology surgeons.

Abstract A031: A fat lot of good: A novel monounsaturated fatty acid promotes prostate cancer growth and survival

Abstract Advanced prostate cancer (PCa) is currently incurable, and development of novel treatments requires a greater understanding of key pathways that are altered during PCa progression. We have focussed on fatty acid metabolism, as the major source of energy for PCa cells, and have implicated a monounsaturated fatty acid (MUFA), cis-vaccenic acid (cVA), as a critical regulator of PCa cell homeostasis. Production of cVA requires stearoyl-CoA desaturase 1 (SCD1), the enzyme attributed to general MUFA production, and whose activity is important in a range of cancer types. Nonetheless, the specific role of cVA has not previously been studied, in PCa nor cancer more generally. To elucidate the role of cVA in PCa more precisely, we used SCD1 inhibition to study PCa responses to broad MUFA depletion and specific MUFA supplementation, comparing the responses of cVA with its more common structural isomer oleate. To accomplish these aims, we utilised cell line models of PCa (LNCaP, MR49F and V16D) and a benign prostate cell line (PNT1A) to perform cell viability, lipidomic and flow cytometric assays. In addition, responses in clinically-relevant patient-derived tumor explants were measured by proliferative (Ki67) and cell death (CC3) marker staining. Pharmacological SCD1 inhibition (SCDi; A939572) decreased cell viability and increased cell death in PCa cell lines and patient-derived tumor explants, while only minimally affecting the benign prostate cell line PNT1A. Phenotypically, analysis of mitochondrial function and lipidomic changes under SCDi suggested a role for MUFAs in regulating mitochondrial membrane composition via cardiolipins, and oxidative stress levels. This in turn has the potential to regulate cell death, control tumor burden, and influence overall PCa patient survival. Supplementation of cVA or oleate under SCDi demonstrated that only cVA was successful at rescuing cell viability, and cVA, but not oleate, could rescue changes observed in mitochondrial-related lipids, suggesting that cVA regulation of mitochondrial function was a major determinant of its effect on cell viability. Additionally, cVA alone dose-dependently increased PCa cell viability, implicating cVA as an important oncogenic factor. Together, these data identify cVA as a novel substrate required for PCa cell viability, likely via regulation of mitochondrial homeostasis and associated cell death pathways. In summary, this research has revealed more precise insights into the oncogenic effects of an overlooked MUFA, cVA, in PCa, and may uncover new druggable targets that are more selective, to improve treatment options for advanced PCa. Citation Format: Julia S. Scott, Reuben Young, Swati Irani, Jonas Dehairs, Stephen Blanksby, Johannes V. Swinnen, Zeyad D. Nassar, Lisa M. Butler. A fat lot of good: A novel monounsaturated fatty acid promotes prostate cancer growth and survival [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A031.

Long-term prospective data on correlation between overall mortality and HADS (Hospital Anxiety and Depression Scale) assessed psychological distress in prostate cancer patients (11 year follow-up data).

12091 Background: We prospectively assessed whether Psychological factors such as anxiety and depression can have a detrimental effect on long term overall survival of prostate cancer patients (pts). Methods: Prostate cancer pts participating in an ethics Committee approved, Prospective study evaluating an Andropause rating scale. All pts had radical radiotherapy with androgen deprivation therapy. Pts completed a baseline HADS questionnaire before any treatment was initiated &amp; at 3mths &amp; after completion of hormone therapy. Patient characteristics: Median age: 69 yrs (50 to 78 yrs). Charlson Comorbidity Index (CCI) prevalence at baseline as follows CCI-I 6.1%; CCI-II: 33.8%; CCI-III: 37.2%; CCI-IV: 14.2%; CCI-V: 6.1% and CCI-VI: 2.7%.; At the survival update in Feb 2023, 49.3% of patients have died [n = 148]; Gleeson grade was Low risk in 7.2%; Intermediate in 53.4% and high risk in 39.2%; Baseline PSA was &lt; 10 ug/L in 45.3%; 10-20 ug/L in 33.1% and &gt; 20 ug/L in 21.6% ; Tumour stage was T1 in 8.1% ; T2 in 63.5% and T3 in 28.4%. Baseline Median serum testosterone was 11.9 nmol/l (min 2.6 and max 26.7). Hormone duration was &lt; 3 mths in 22.3%; 3-6mths in 35.8% ; 6 to &lt; 36mths in 19.6% and &gt; 36mths in 22.3%. Cox regression models estimated hazard ratios (HR) and 95% confidence intervals (CI) of overall mortality, while controlling for the following covariates (Age, T stage, Gleeson risk category, PSA Category, Baseline Serum Testosterone, ADT duration category and Charlson Comorbidity index). Results: Higher anxiety at time of diagnosis had a statistically significant adverse effect on overall survival (table); Higher depression symptoms at baseline did not affect survival but depressive symptoms after completing cancer treatment did affect all-cause mortality in this mature dataset with a median follow up of more than 11 years. Conclusions: Higher anxiety and depression symptoms in prostate cancer patients are associated with significantly higher long-term all-cause mortality. [Table: see text]

GNL3 and PA2G4 as Prognostic Biomarkers in Prostate Cancer.

Prostate cancer is a multifocal and heterogeneous disease common in males and remains the fifth leading cause of cancer-related deaths worldwide. The prognosis of prostate cancer is variable and based on the degree of cancer and its stage at the time of diagnosis. Existing biomarkers for the prognosis of prostate cancer are unreliable and lacks specificity and sensitivity in guiding clinical decision. There is need to search for novel biomarkers having prognostic and predictive capabilities in guiding clinical outcomes. Using a bioinformatics approach, we predicted GNL3 and PA2G4 as biomarkers of prognostic significance in prostate cancer. A progressive increase in the expression of GNL3 and PA2G4 was observed during cancer progression having significant association with poor survival in prostate cancer patients. The Receiver Operating Characteristics of both genes showed improved area under the curve against sensitivity versus specificity in the pooled samples from three different GSE datasets. Overall, our analysis predicted GNL3 and PA2G4 as prognostic biomarkers of clinical significance in prostate cancer.

Management of bone metastasis in prostate cancer.

Progression of bone metastases is the primary cause of death in prostate cancer, and skeletal-related events (SREs), including pathologic fractures, spinal cord compression, radiation, or surgery to bone can impair patients' quality of life. Over the past decade, the development of cytotoxic agents, androgen-receptor-axis-targeted therapies (ARATs), and radioligand therapies has prolonged overall survival of prostate cancer patients with bone metastases and reduced the risk of SREs. The use of bone-modifying agents has also contributed to the reduced risk of SREs. Initial use of a cytotoxic agent, docetaxel, or an ARAT agent with androgen deprivation therapy (ADT) is the current approach to metastatic castration-sensitive prostate cancer. However, there is no consensus on the optimal medication for upfront use in combination with ADT, or on specific patient selection. Recently, next-generation imaging modalities, such as whole-body magnetic resonance imaging and prostate-specific membrane antigen-positron emission tomography have been utilized to detect bone metastases at an early stage. In addition, metastasis-directed therapy, such as stereotactic body radiation therapy, has been attempted. In the future, patients with bone metastatic prostate cancer will be divided into subgroups and their treatment options will be tailored to their specific characteristics.

Dihydrotestosterone-based A-ring-fused pyridines: Microwave-assisted synthesis and biological evaluation in prostate cancer cells compared to structurally related quinolines

Dysfunction of the androgen receptor (AR) signalling axis plays a pivotal role in the development and progression of prostate cancer (PCa). Steroidal and non-steroidal AR antagonists can significantly improve the survival of PCa patients by blocking the action of the endogenous ligand through binding to the hormone receptor and preventing its activation. Herein, we report two synthetic strategies, each utilizing the advantages of microwave irradiation, to modify the A-ring of natural androgen 5α-dihydrotestosterone (DHT) with pyridine scaffolds. Treatment of DHT with appropriate Mannich salts led to 1,5-diketones, which were then converted with hydroxylamine to A-ring-fused 6′-substituted pyridines. To extend the compound library with 4′,6′-disubstituted analogues, 2-arylidene derivatives of DHT were subjected to ring closure reactions according to the Kröhnke’s pyridine synthesis. The crystal structure of a monosubstituted pyridine product was determined by single crystal X-ray diffraction. AR transcriptional activity in a reporter cell line was investigated for all novel A-ring-fused pyridines and a number of previously synthesized DHT-based quinolines were included to the biological study to obtain information about the structure-activity relationship. It was shown that several A-ring-fused quinolines acted as AR antagonists, in comparison with the dual or agonist character of the majority of A-ring-fused pyridines. Derivative 1d (A-ring-fused 6′-methoxyquinoline) was studied in detail and showed to be a low-micromolar AR antagonist (IC50 = 10.5 µM), and it suppressed the viability and proliferation of AR-positive PCa cell lines. Moreover, the candidate compound blocked the AR downstream signalling, induced moderate cell-cycle arrest and showed to bind recombinant AR and to target AR in cells. The binding mode and crucial interactions were described using molecular modelling.

Abstract 6486: Single nucleotide polymorphisms that predict serum cholesterol as a prostate cancer prognostic factor - a Mendelian randomization study

Abstract Introduction: Intracellular cholesterol metabolism plays an important role in prostate cancer progression and emergence of treatment resistance. However, it remains unclear whether serum cholesterol and lipoproteins are associated with prostate cancer outcomes. Studies on serum cholesterol and cancer are often confounded by lifestyle factors such as diet and obesity. A possible solution is to use instrumental variables, such as SNPs predicting serum cholesterol. According to the Mendelian randomization theory, germline SNP distribution is unaffected by confounding variables such as diet and lifestyle factors. Objective: To estimate whether SNPs that predict serum cholesterol and lipoproteins also predict mortality among a cohort of men with prostate cancer. Methods: Our study cohort consisted of 3,241 men diagnosed with prostate cancer between 1996-2015, using data collected by the Finnish Randomized Study of Screening for Prostate Cancer. Blood samples were genotyped by PRACTICAL consortium. A UCSC genome browser was utilized for selecting 85 SNPs in lipid metabolism-associated genes. Dates and causes of deaths between 1996-2015 were obtained from the Statistics Finland's statistics on causes of death. Information on serum cholesterol and lipoprotein measurements were obtained from a regional laboratory database.Scores predicting serum cholesterol, LDL, HDL and triglyceride level by SNP genotype were created using linear regression and lasso regression. Risk of prostate cancer death and overall mortality by level of the SNP risk score were evaluated with multivariable-adjusted Cox regression. Follow-up started at prostate cancer diagnosis and continued until death, emigration or common closing date of Dec 31, 2015.Results: SNP score predicting total cholesterol stratified prostate cancer patients both for disease-specific (HR 1.27, 95% CI 0.49-3.28 for highest tertile vs. lowest) and overall survival (HR 1.43, 95% CI 0.94-2.20, p for trend = 0.077), albeit statistical significance was not reached. Similar survival differences were observed for SNP score predicting triglyceride level, but not for scores predicting LDL or HDL.Conclusions: SNPs predicting serum cholesterol and triglycerides are likely prognostic factors for survival of prostate cancer patients. This suggest serum cholesterol and lipoproteins areimportant in prostate cancer progression. Total cholesterol SNP scoreProstate-cancer specific survival Overall survival Citation Format: Sebastian Boele, Aino Siltari, Paavo Raittinen, Johanna Schleutker, Kimmo Taari, Kirsi Talala, Teuvo Tammela, Anssi Auvinen, Teemu J. Murtola. Single nucleotide polymorphisms that predict serum cholesterol as a prostate cancer prognostic factor - a Mendelian randomization study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6486.

Metastatic prostate cancer‐derived extracellular vesicles facilitate osteoclastogenesis by transferring the CDCP1 protein

Bone metastases are still incurable and result in the development of clinical complications and decreased survival for prostate cancer patients. Recently, a number of studies have shown that extracellular vesicles (EVs) play important roles in tumour progression. Here, we show that EVs from metastatic prostate cancer cells promote osteoclast formation in the presence of receptor activator of NF-κB ligand (RANKL). EV characterization followed by functional siRNA screening identified CUB-domain containing protein 1 (CDCP1), a transmembrane protein, as an inducer of osteoclastogenesis. Additionally, CDCP1 expression on plasma-derived EVs was upregulated in bone metastatic prostate cancer patients. Our findings elucidate the effect of EVs from metastatic prostate cancer cells on osteoclast formation, which is promoted by CDCP1 located on EVs. Furthermore, our data suggested that CDCP1 expression on EVs might be useful to detect bone metastasis of prostate cancer.

ARPC1A correlates with poor prognosis in prostate cancer and is up-regulated by glutamine metabolism to promote tumor cell migration, invasion and cytoskeletal changes

ObjectiveThis study aimed to identify potential biomarkers for prostate cancer (PCa) progression and metastasis, and to discern their biological functions.MethodsBioinformatics methods were used to screen for hub genes. The expression level of key hub genes in PCa was determined and their prognostic significance was examined. A series of functional assays were performed to investigate the function of the highest-ranking hub gene.ResultsActin related protein 2/3 complex subunit 1A (ARPC1A) was identified as the hub gene. ARPC1A was highly expressed in PCa tissues and cell lines, and was an independent prognostic factor for predicting biochemical recurrence after radical prostatectomy and overall survival of PCa patients. Knockdown of ARPC1A inhibited PCa cell migration, invasion and cytoskeleton formation, but had no impact on cell proliferation and cell cycle progression. In vivo, ARPC1A overexpression promoted lung metastasis of PCa, but had no efffect on tumor growth. Additionally, glutamine metabolism was identified as an upstream regulator of ARPC1A, and promoted migration, invasion and cytoskeletal changes of PCa cell through ARPC1A.ConclusionThese findings suggested that ARPC1A, which correlates with poor prognosis in PCa, functions downstream of glutamine metabolism to regulate cytoskeletal changes, cellular migration and cellular invasion in this disease.

Glycine Decarboxylase (GLDC) Plays a Crucial Role in Regulating Energy Metabolism, Invasion, Metastasis and Immune Escape for Prostate Cancer.

Glycine decarboxylase (GLDC) is one of the core enzymes for glycine metabolism, and its biological roles in prostate cancer (PCa) are unclear. First, we found that GLDC plays a central role in glycolysis in 540 TCGA PCa patients. Subsequently, a metabolomic microarray showed that GLDC enhanced aerobic glycolysis in PCa cells, and GLDC and its enzyme activity enhanced glucose uptake, lactate production and lactate dehydrogenase (LDH) activity in PCa cells. Next, we found that GLDC was highly expressed in PCa, was directly regulated by hypoxia-inducible factor (HIF1-α) and regulated downstream LDHA expression. In addition, GLDC and its enzyme activity showed a strong ability to promote the migration and invasion of PCa both in vivo and in vitro. Furthermore, we found that the GLDC-high group had a higher TP53 mutation frequency, lower CD8+ T-cell infiltration, higher immune checkpoint expression, and higher immune exclusion scores than the GLDC-low group. Finally, the GLDC-based prognostic risk model by applying LASSO Cox regression also showed good predictive power for the clinical characteristics and survival in PCa patients. This evidence indicates that GLDC plays crucial roles in glycolytic metabolism, invasion and metastasis, and immune escape in PCa, and it is a potential therapeutic target for prostate cancer.