Silver Dimolybdate Nanorods: In Vitro Anticancer Activity Against Breast and Prostate Tumors and In Vivo...

Background: The development of nanostructured materials for cancer therapy has garnered significant interest due to their unique physicochemical properties, including enhanced surface area and tunable electronic structures, which can facilitate targeted drug delivery and oxidative stress modulation. This study investigates the anticancer potential of monoclinic silver dimolybdate nanorods (m-Ag₂Mo₂O₇) against aggressive breast (MDA-MB-231) and prostate (PC-3) cancer cells and explores their in vivo pharmacokinetic behavior. Methods: m-Ag₂Mo₂O₇ nanorods were synthesized via a hydrothermal method and characterized using XRD, SEM, Raman, and FTIR spectroscopy. In vitro cytotoxicity was evaluated using MTT assays on MDA-MB-231 and PC-3 cell lines across concentrations ranging from 1.56 to 100 µg/mL. In vivo biodistribution and radiopharmacokinetics were assessed using technetium-99m-labeled nanorods in male Swiss rats, with gamma counting employed for tissue uptake analysis and pharmacokinetic parameter determination. Results: m-Ag₂Mo₂O₇ nanorods exhibited a modest cytotoxic effect on MDA-MB-231 cells, with 50 µg/mL reducing cell viability by 23.5% (p < 0.05), while no significant cytotoxicity was observed in PC-3 cells. In vivo studies revealed predominant accumulation in the stomach, liver, spleen, and bladder, indicating reticuloendothelial system uptake and renal clearance. Pharmacokinetic analysis showed a rapid systemic clearance (half-life ~6.76 h) and a low volume of distribution (0.0786 L), suggesting primary retention in circulation with minimal off-target diffusion. Conclusions: While m-Ag₂Mo₂O₇ nanorods display limited standalone cytotoxicity, their ability to induce oxidative stress and favorable pharmacokinetic profile support their potential as adjuvant agents in cancer therapy, particularly for chemoresistant breast cancers. Further studies are warranted to elucidate their molecular mechanisms, optimize combinatorial treatment strategies, and assess long-term safety in preclinical models.