In castration-resistant prostate cancer (CRPC), clinical response to androgen receptor (AR) antagonists is limited mainly due to AR-variants expression and restored AR signaling. The metabolite spermine is most abundant in prostate and it decreases as prostate cancer progresses, but its functions remain poorly understood. Here, we show spermine inhibits full-length androgen receptor (AR-FL) and androgen receptor splice variant 7 (AR-V7) signaling and suppresses CRPC cell proliferation by directly binding and inhibiting protein arginine methyltransferase PRMT1. Spermine reduces H4R3me2a modification at the AR locus and suppresses AR binding as well as H3K27ac modification levels at AR target genes. Spermine supplementation restrains CRPC growth in vivo. PRMT1 inhibition also suppresses AR-FL and AR-V7 signaling and reduces CRPC growth. Collectively, we demonstrate spermine as an anticancer metabolite by inhibiting PRMT1 to transcriptionally inhibit AR-FL and AR-V7 signaling in CRPC, and we indicate spermine and PRMT1 inhibition as powerful strategies overcoming limitations of current AR-based therapies in CRPC.
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http://dx.doi.org/10.1016/j.celrep.2023.112798 | DOI Listing |
Prostate
January 2025
Department of Urology, Istanbul University-Cerrahpaşa, Cerrahpaşa Faculty of Medicine, Istanbul, Turkey.
Background: Metastatic castration resistance prostate cancer (mCRPC) is a challenging disease with a significant burden of mortality and morbidity. Most of the patients attain resistance to the available treatments, necessitating further novel therapies in this clinical setting. Actinium 225 (Ac) prostate-specific membrane antigen (PSMA) radioligand therapy has emerged as a promising option and has been utilized for the last decade.
View Article and Find Full Text PDFBMC Urol
January 2025
The School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian Province, 350122, China.
Background: In recent years, many studies have illustrated that the neutrophil-to-lymphocyte ratio (NLR) is a prognostic factor of metastatic castration-resistant prostate cancer (mCRPC), but their conclusions are controversial. The aim of this study was to assess the prognostic value of the NLR in patients with mCRPC treated with docetaxel-based chemotherapy.
Methods: Database searches were conducted in PubMed, EMBASE and the Cochrane Library to retrieve relevant published English-language literature up to 20 February 2023.
Eur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha, Hunan, 410008, P.R. China.
Purpose: To develop and validate a prostate-specific membrane antigen (PSMA) PET/CT based multimodal deep learning model for predicting pathological lymph node invasion (LNI) in prostate cancer (PCa) patients identified as candidates for extended pelvic lymph node dissection (ePLND) by preoperative nomograms.
Methods: [Ga]Ga-PSMA-617 PET/CT scan of 116 eligible PCa patients (82 in the training cohort and 34 in the test cohort) who underwent radical prostatectomy with ePLND were analyzed in our study. The Med3D deep learning network was utilized to extract discriminative features from the entire prostate volume of interest on the PET/CT images.
Cell Death Dis
January 2025
Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France.
Prostate cancer is a heterogeneous disease with a slow progression and a highly variable clinical outcome. The tumor suppressor genes PTEN and TP53 are frequently mutated in prostate cancer and are predictive of early metastatic dissemination and unfavorable patient outcomes. The progression of solid tumors to metastasis is often associated with increased cell plasticity, but the complex events underlying TP53-loss-induced disease aggressiveness remain incompletely understood.
View Article and Find Full Text PDFBiochemistry (Mosc)
December 2024
Moscow Institute of Physics and Technology, Dolgoprudny, 141701, Russia.
Activation of the p38 mitogen-activated protein kinase (MAPK) pathways is vital in regulating cell growth, differentiation, apoptosis, and stress response, significantly affecting tumorigenesis and cancer progression. We developed a bioinformatic technique to construct an interactome network-based molecular pathways for genes of interest and quantify their activation levels using high-throughput gene expression data. This study is focused on the p38α, p38β, p38γ, and p38δ kinases, examining their activation levels (PALs) based on transcriptomic data and their associations with survival and drug responsiveness across various cancer types.
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