Introduction: PACE4 plays an important role in prostate cancer (PCa) proliferation and aggression, which might provide a useful target against prostate cancer. In this study, we had strived to find some key miRNAs to decrease malignancy and invasiveness of PCa through regulating PACE4 expression.
Methods: Clinically pathological analysis of immunohistochemistry/in situ hybridization was carried out to detect the relationship between PACE4 expression/miRNAs and the malignancy of prostate mass. Prostate cell lines (DU145, C4-2, and BPH-1) were cultured for growth curve, immunocytochemistry analysis, colony formation, Matrigel invasion, and transcriptional/translational expression assay of PACE4-related signaling molecules for confirming the relationship. MiRNAs targeting PACE4 were predicted, validated and further-corroborated using bio-software, real-time PCR, luciferase reporter assay and transfection of miRNA mimics and inhibitor.
Results: It was suggested that PACE4 might reflect the pathological malignancy of prostate lesion from pathology analysis. Moreover, DU145 cells, the highest PACE4-level and related TF expression indicated of the strongest malignancy and invasiveness. It was significantly found that miR-124 was presented with the biggest odd to target PACE4-3'UTR, the capability of decreasing PACE expression and slowing down cell growth and cell invasion.
Conclusions: It was clear that PACE4 level was closely associated with malignancy and invasiveness of PCa in vivo or in vitro MiR-124, played a crucial role inhibiting PACE4 transcription thus exhibiting obvious effects of antiproliferation and antiaggression of PCa.
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http://dx.doi.org/10.1002/pros.22822 | DOI Listing |
J Med Internet Res
January 2025
Cancer Rehabilitation and Survivorship, Department of Supportive Care, Princess Margaret Cancer Centre, Toronto, ON, Canada.
Background: Virtual follow-up (VFU) has the potential to enhance cancer survivorship care. However, a greater understanding is needed of how VFU can be optimized.
Objective: This study aims to examine how, for whom, and in what contexts VFU works for cancer survivorship care.
PLoS One
January 2025
Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom.
Epithelial cancers are typically heterogeneous with primary prostate cancer being a typical example of histological and genomic variation. Prior studies of primary prostate cancer tumour genetics revealed extensive inter and intra-patient genomic tumour heterogeneity. Recent advances in machine learning have enabled the inference of ground-truth genomic single-nucleotide and copy number variant status from transcript data.
View Article and Find Full Text PDFEndocr Relat Cancer
January 2025
S Dehm, Masonic Cancer Center, University of Minnesota, Minneapolis, United States.
Treatment for castration-resistant prostate cancer (CRPC) primarily involves the suppression of androgen receptor (AR) activity using androgen receptor signaling inhibitors (ARSIs). While ARSIs have extended patient survival, resistance inevitably develops. Mechanisms of resistance include genomic aberrations at the AR locus that reactivate AR signaling, or lineage plasticity that drives emergence of AR-independent phenotypes.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Ahmanson Translational Theranostics Division, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles.
Importance: The phase 3 randomized EMBARK trial evaluated enzalutamide with or without leuprolide in high-risk nonmetastatic hormone-sensitive prostate cancer. Eligibility relied on conventional imaging, which underdetects metastatic disease compared with prostate-specific membrane antigen-positron emission tomography (PSMA-PET).
Objective: To describe the staging information obtained by PSMA-PET/computed tomography (PSMA-PET/CT) in a patient cohort eligible for the EMBARK trial.
Int Urol Nephrol
January 2025
Faculty of Medical Sciences, Pharmacology and Toxicology Department, University of Kragujevac, Kragujevac, Serbia.
Purposes: Intermediate-risk prostate cancer (IR PCa) is the most common risk group for localized prostate cancer. This study aimed to develop a machine learning (ML) model that utilizes biopsy predictors to estimate the probability of IR PCa and assess its performance compared to the traditional clinical model.
Methods: Between January 2017 and December 2022, patients with prostate-specific antigen (PSA) values of ≤ 20 ng/mL underwent transrectal ultrasonography-guided prostate biopsies.
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