Introduction: Radiolabeled peptides play a central role in nuclear medicine as radiotheranostics for targeted imaging and therapy of cancer. We have recently proposed the use of metabolically stabilized GRPR antagonist BBN2 for radiolabeling with F and Ga and subsequent PET imaging of GRPRs in prostate cancer. The present work studied the impact of Sc- and Ga-labeled DOTA complexes attached to GRPR antagonist BBN2 on the in vitro GRPR binding affinity, and their biodistribution and tumor uptake profiles in MCF7 breast and PC3 prostate cancer models.
Methods: DOTA-Ava-BBN2 was radiolabeled with radiometals Ga and Sc. Gastrin-releasing peptide receptor (GRPR) affinities of peptides were assessed in PC3 prostate cancer cells. GRPR expression profiles were studied in human breast cancer tissue samples and MCF7 breast cancer cells. PET imaging of Ga- and Sc-labeled peptides was performed in MCF7 and PC3 xenografts as breast and prostate cancer models.
Results: Radiopeptides [Ga]Ga-DOTA-Ava-BBN2 and [Sc]Sc-DOTA-Ava BBN2 were prepared in radiochemical yields of 70-80% (decay-corrected), respectively. High binding affinities were found for both peptides (IC = 15 nM (Ga) and 5 nM (Sc)). Gene expression microarray analysis revealed high GRPR mRNA expression levels in estrogen receptor (ER)-positive breast cancer, which was further confirmed with Western blot and immunohistochemistry. However, PET imaging showed only low tumor uptake of both radiotracers in MCF7 xenografts ([Ga]Ga-DOTA-BBN2 (SUV 0.27 ± 0.06); [Sc]Sc-DOTA-BBN2 (SUV 0.20 ± 0.03)). In contrast, high tumor uptake and retention were found for both radiopeptides in PC3 tumors ([Ga]Ga-DOTA-BBN2 (SUV 0.46 ± 0.07); [Sc]Sc-DOTA-BBN2 (SUV 0.51 ± 0.11)).
Conclusions: Comparison of Ga- and Sc-labeled DOTA-Ava-BBN2 peptides revealed slight but noticeable differences of the radiometal with an impact on the in vitro GRPR receptor binding properties in PC3 cells. No differences were found in their in vivo biodistribution profiles in MCF7 and PC3 xenografts. Radiopeptides [Ga]Ga-DOTA-Ava-BBN2 and [Sc]Sc-DOTA-Ava-BBN2 displayed comparable tumor uptake and retention profiles with rapid blood and renal clearance profiles in both tumor models.
Advances In Knowledge And Implications For Patient Care: The favorable PET imaging performance of [Sc]Sc-DOTA-Ava-BBN2 in prostate cancer should warrant the development of an [Sc]Sc-DOTA-Ava-BBN2 analog for clinical translation which comes with a main γ-line of much lower energy and intensity compared to Sc.
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http://dx.doi.org/10.1016/j.nucmedbio.2020.10.005 | DOI Listing |
JAMA Netw Open
January 2025
Department of Epidemiology and Biostatistics, University of California, San Francisco.
Importance: Incidence of distant stage prostate cancer is increasing in the United States. Research is needed to understand trends by social and geographic factors.
Objective: To examine trends in prostate cancer incidence and mortality rates in California by stage, age, race and ethnicity, and region.
Endocrine
January 2025
Department of Zoology, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, India.
The word "cancer" evokes myriad emotions, ranging from fear and despair to hope and determination. Cancer is aptly defined as a complex and multifaceted group of diseases that has unapologetically led to the loss of countless lives and affected innumerable families across the globe. The battle with cancer is not only a physical battle, but also an emotional, as well as a psychological skirmish for patients and for their loved ones.
View Article and Find Full Text PDFInvest New Drugs
January 2025
School of Life Sciences, Jilin University, Changchun, China.
Due to the emergence of drug resistance, androgen receptor (AR)-targeted drugs still pose great challenges in the treatment of prostate cancer, and it is urgent to explore an innovative therapeutic strategy. MK-1775, a highly selective WEE1 inhibitor, is shown to have favorable therapeutic benefits in several solid tumor models. Recent evidence suggests that the combination of MK-1775 with DNA-damaging agents could lead to enhanced antitumor efficacy.
View Article and Find Full Text PDFJ Natl Cancer Inst
January 2025
Department of Urology, Vanderbilt University Medical Center, Nashville, TN, United States.
Front Oncol
January 2025
Department of Urology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
The prediction of survival outcomes is a key factor in making decisions for prostate cancer (PCa) treatment. Advances in computer-based technologies have increased the role of machine learning (ML) methods in predicting cancer prognosis. Due to the various effective treatments available for each non-linear landscape of PCa, the integration of ML can help offer tailored treatment strategies and precision medicine approaches, thus improving survival in patients with PCa.
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