Our laboratory has previously identified soluble guanylyl cyclase α1 (sGCα1) as a novel androgen-regulated gene essential for prostate cancer cell proliferation. sGCα1 expression is highly elevated in prostate tumors, contrasting with the low expression of sGCβ1, with which sGCα1 dimerizes to mediate nitric oxide (NO) signaling. In studying its mechanism of action, we have discovered that sGCα1 can inhibit the transcriptional activity of p53 in prostate cancer cells independent of either classical mediators of NO signaling or the guanylyl cyclase activity of sGCα1. Interestingly, sGCα1 inhibition of p53-regulated gene expression was gene specific, targeting genes involved in apoptosis/cell survival. Consistent with this, overexpression of sGCα1 makes prostate cancer cells more resistant to etoposide, a chemotherapeutic and apoptosis-inducing drug. Immunoprecipitation and immunocytochemistry assays show a physical and direct interaction between sGCα1 and p53 in prostate cancer cells. Interestingly, sGCα1 induces p53 cytoplasmic sequestration, representing a new mechanism of p53 inactivation in prostate cancer. Analysis of prostate tumors has shown a direct expression correlation between sGCα1 and p53. Collectively, these data suggest that sGCα1 regulation of p53 activity is important in prostate cancer biology and may represent an important mechanism of p53 down-regulation in those prostate cancers that express significant levels of p53.
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http://dx.doi.org/10.1210/me.2010-0394 | DOI Listing |
Eur J Nucl Med Mol Imaging
January 2025
Huashan Hospital and Human Phenome Institute, Fudan University, 220 Handan Road, Shanghai, 200433, China.
Objective: This study aims to conduct a bibliometric analysis to explore research trends, collaboration patterns, and emerging themes in the PET/MR field based on published literature from 2010 to 2024.
Methods: A detailed literature search was performed using the Web of Science Core Collection (WoSCC) database with keywords related to PET/MR. A total of 4,349 publications were retrieved and analyzed using various bibliometric tools, including VOSviewer and CiteSpace.
Aging (Albany NY)
January 2025
Department of Public Health Sciences, University of Chicago, Chicago, IL 60615, USA.
Background: DNA methylation (DNAm) data from human samples has been leveraged to develop "epigenetic clock" algorithms that predict age and other aging-related phenotypes. Some DNAm clocks were trained using DNAm obtained from blood cells, while other clocks were trained using data from diverse tissue/cell types. To assess how DNAm clocks perform across non-blood tissue types, we applied DNAm algorithms to DNAm data generated from 9 different human tissue types.
View Article and Find Full Text PDFBMC Health Serv Res
January 2025
Institute for Health and Nursing Science, Faculty of Medicine, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.
Background: Cancer requires interdisciplinary intersectoral care. The Care Coordination Instrument (CCI) captures patients' perspectives on cancer care coordination. We aimed to translate, adapt, and validate the CCI for Germany (CCI German version).
View Article and Find Full Text PDFRandomized controlled trials (RCTs) evaluating anti-cancer agents often lack generalizability to real-world oncology patients. Although restrictive eligibility criteria contribute to this issue, the role of selection bias related to prognostic risk remains unclear. In this study, we developed TrialTranslator, a framework designed to systematically evaluate the generalizability of RCTs for oncology therapies.
View Article and Find Full Text PDFSci Rep
January 2025
Department of MRI, Zhongshan City People's Hospital, No. 2, Sunwen East Road, Shiqi District, Zhongshan, 528403, Guangdong, China.
To investigate the potential of an MRI-based radiomic model in distinguishing malignant prostate cancer (PCa) nodules from benign prostatic hyperplasia (BPH)-, as well as determining the incremental value of radiomic features to clinical variables, such as prostate-specific antigen (PSA) level and Prostate Imaging Reporting and Data System (PI-RADS) score. A restrospective analysis was performed on a total of 251 patients (training cohort, n = 119; internal validation cohort, n = 52; and external validation cohort, n = 80) with prostatic nodules who underwent biparametric MRI at two hospitals between January 2018 and December 2020. A total of 1130 radiomic features were extracted from each MRI sequence, including shape-based features, gray-level histogram-based features, texture features, and wavelet features.
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