This study evaluated the effect of dietary fat on prostate cancer development by using the Hi-Myc mouse transgenic prostate cancer model. Hi-Myc mice develop murine prostatic intraepithelial neoplasia (mPIN) as early as 2 to 4 weeks and invasive adenocarcinoma between 6 and 9 months due to the overexpression of human c-Myc in the mouse prostate. Three-week-old male Hi-Myc mice were placed on high-fat (HF; 42% Kcal) or low-fat (LF; 12% Kcal) diets, and equal caloric intake was maintained until euthanasia at 7 months. The number of mice that developed invasive adenocarcinoma at 7 months was 27% less in the LF diet group (12/28) compared with the HF diet group (23/33, P < 0.05). Epithelial cells in mPIN lesions in the LF group had a significantly lower proliferative index compared with epithelial cells in the HF group (21.7% versus 28.9%, P < 0.05). During the mPIN phase of carcinogenesis (4 months), the LF group had higher serum insulin-like growth factor (IGF) binding protein-1 levels (21.0 +/- 8.9 ng/mL versus 3.2 +/- 0.8 ng/mL, P < 0.05) relative to the HF group. Akt (Ser(473)) phosphorylation, Akt kinase activity, and phosphorylation of downstream targets of Akt in prostates were significantly reduced in the LF diet group compared with the HF group. We conclude that dietary fat reduction delays transition from mPIN to invasive cancer in this Myc-driven transgenic mouse model, possibly through suppression of the IGF-Akt pathway and decreased proliferation of mPIN epithelial cells.
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http://dx.doi.org/10.1158/0008-5472.CAN-07-5616 | DOI Listing |
Prostate Cancer
December 2024
Department of Histopathology and Cytology, Faculty of Medical Laboratory Sciences, Al-Neelain University, Khartoum, Sudan.
Prostate cancer is the most common noncutaneous malignancy among men worldwide, including in Sudan, where it represents a significant public health challenge. CD147, a transmembrane glycoprotein implicated in tumor progression, invasion, and metastasis, has shown potential as a prognostic biomarker in various cancers. This retrospective case-control study aimed to evaluate CD147 expression in prostate adenocarcinoma among Sudanese men and its association with tumor grade.
View Article and Find Full Text PDFJ West Afr Coll Surg
August 2024
Division of Urology, Department of Surgery, College of Health Sciences, University of Abuja, Abuja, Nigeria.
Background: Prostate cancer (PCa) was the most common noncutaneous cancer among Nigerian men in 2020. Despite this high incidence, documented rates may be an underestimation.
Objectives: This study aimed to determine the hospital incidence rate, trends, and characterise the clinicopathologic features, and treatment outcomes of patients with PCa in our institution.
Oncol Res
December 2024
Department of Rehabilitation, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, 530000, China.
Background: Transmembrane emp24 trafficking protein 3 (TMED3) is associated with the development of several tumors; however, whether TMED3 regulates the progression of prostate cancer remains unclear.
Materials And Methods: Short hairpin RNA was performed to repress TMED3 in prostate cancer cells (DU145 cells) and in a prostate cancer mice model to determine its function in prostate cancer and .
Results: In the present study, we found that TMED3 was highly expressed in prostate cancer cells.
Front Oncol
December 2024
Department of Orthopedics, Chengdu Fifth People's Hospital, Chengdu, China.
Background: Prostate cancer (PCa) ranks as the second leading cause of cancer-related mortality among men. Long non-coding RNAs (lncRNAs) are known to play a regulatory role in the development of various human cancers. LncRNA MAFG-divergent transcript (MAFG-DT) was reported to play a crucial role in tumor progression of multiple human cancers, such as pancreatic cancer, colorectal cancer, bladder cancer, and gastric cancer.
View Article and Find Full Text PDFBioinform Adv
November 2024
Laboratory of Molecular Science and Engineering, Åbo Akademi University, Henrikinkatu 2, Turku 20500, Finland.
Motivation: NMR-based metabolomics is a field driven by technological advancements, necessitating the use of advanced preprocessing tools. Despite this need, there is a remarkable scarcity of comprehensive and user-friendly preprocessing tools in Python. To bridge this gap, we have developed Protomix-a Python package designed for metabolomics research.
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