Advanced prostate cancer

BUD23 promote the cell proliferation ability by affecting the PPAR signaling pathways: evidence from the online dataset and cell experiment

INTRODUCTION

Prostate cancer is a major public health challenge for men worldwide, being the second most common cancer diagnosis and the fifth leading cause of cancer-related deaths among men. The etiology of prostate cancer is multifactorial, with age, genetic predispositions, and lifestyle factors playing critical roles. The role of the peroxisome proliferator-activated receptors (PPARs) in prostate cancer remains complex and not fully elucidated.

METHODS

Transcriptomic data from The Cancer Genome Atlas (TCGA) were utilized for this study. The data were analyzed using single-sample Gene Set Enrichment Analysis (ssGSEA), Gene Ontology (GO) enrichment analysis, KEGG pathway analysis, and Gene Set Enrichment Analysis (GSEA). A prognosis-prediction model was constructed using Cox regression and LASSO analysis. Functional experiments, including Western blotting, quantitative PCR (qPCR), Cell Counting Kit-8 (CCK-8) assays, and EdU incorporation assays, were performed to validate the role of BUD23 in prostate cancer.

RESULTS

Significant differences were observed in the immune microenvironment and HLA gene expression profiles between high and low PPAR expression groups in prostate cancer. The high PPAR group exhibited a less active immune microenvironment with higher fractions of immunosuppressive T regulatory cells (Tregs). A robust prognostic model identified key genes, including BUD23, associated with patient survival. Elevated BUD23 expression was correlated with more aggressive clinical features such as advanced pathological stages, nodal metastasis, and higher Gleason scores. Knockdown of BUD23 in PC-3 and LNCaP prostate cancer cell lines significantly inhibited cell proliferation. Western blotting and qPCR confirmed effective BUD23 knockdown, and CCK-8 and EdU assays demonstrated reduced cell proliferation. BUD23 knockdown resulted in significant reductions in PPAR-α, PPAR-β, and PPAR-γ protein levels, suggesting a regulatory axis between BUD23 and PPARs in prostate cancer.

CONCLUSION

The study highlights the distinct roles of PPARα, PPARβ/δ, and PPARγ in prostate cancer progression and their potential as therapeutic targets. Elevated BUD23 expression is associated with aggressive prostate cancer features and patient survival, making it a potential prognostic biomarker. The knockdown of BUD23 not only inhibited cell proliferation but also reduced the expression of PPAR-related proteins, indicating a potential regulatory axis between BUD23 and PPARs. These findings suggest that targeting BUD23 could modulate PPAR signaling and inhibit tumor growth in prostate cancer.

Develop prediction model to help forecast advanced prostate cancer patients' prognosis after surgery using neural network

Background

The effect of surgery on advanced prostate cancer (PC) is unclear and predictive model for postoperative survival is lacking yet.

Methods

We investigate the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database, to collect clinical features of advanced PC patients. According to clinical experience, age, race, grade, pathology, T, N, M, stage, size, regional nodes positive, regional nodes examined, surgery, radiotherapy, chemotherapy, history of malignancy, clinical Gleason score (composed of needle core biopsy or transurethral resection of the prostate specimens), pathological Gleason score (composed of prostatectomy specimens) and prostate-specific antigen (PSA) are the potential predictive variables. All samples are divided into train cohort (70% of total, for model training) and test cohort (30% of total, for model validation) by random sampling. We then develop neural network to predict advanced PC patients' overall. Area under receiver operating characteristic curve (AUC) is used to evaluate model's performance.

Results

6380 patients, diagnosed with advanced (stage III-IV) prostate cancer and receiving surgery, have been included. The model using all collected clinical features as predictors and based on neural network algorithm performs best, which scores 0.7058 AUC (95% CIs, 0.7021-0.7068) in train cohort and 0.6925 AUC (95% CIs, 0.6906-0.6956) in test cohort. We then package it into a Windows 64-bit software.

Conclusion

Patients with advanced prostate cancer may benefit from surgery. In order to forecast their overall survival, we first build a clinical features-based prognostic model. This model is accuracy and may offer some reference on clinical decision making.

Advanced delivery of leuprorelin acetate for the treatment of prostatic cancer

INTRODUCTION

Androgen-deprivation therapy (ADT) is the main therapy for patients with advanced and metastatic prostate cancer (PCa) and, in combination with radiotherapy, for patients with localized high-risk PCa. Due to its favorable tolerability among different treatments available for ADT, leuprorelin acetate is well established as the leading luteinizing hormone-releasing hormone (LHRH) analog. The development of second-generation leuprorelin acetate (LA) depot formulation (Eligard®, Recordati S.p.A) allowed a consistent and controlled release of leuprorelin between injections and a more efficient reduction of testosterone levels with respect to conventional LHRH agonists.

AREAS COVERED

This work provides a summary of the biological and clinical rationale for using LA to manage PCa and presents the current evidence about the therapeutic activity of the LA gel depot formulation, used as an advanced leuprorelin acetate delivery method.

EXPERT OPINION

Results of the registration studies and post-marketing clinical trials demonstrate that the LA gel depot provides long-term efficacy in the clinical practice and a good degree of tolerability. Overall, collected data suggest that the LA gel depot can represent the ADT reference therapy in advanced PCa.