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Gold Nanoparticles Disrupt the IGFBP2/mTOR/PTEN Axis to Inhibit Ovarian Cancer Growth
Author(s) -
Hossen Md. Nazir,
Wang Lin,
Dwivedi Shailendra Kumar Dhar,
Zhang Yushan,
Rao Geeta,
Elechalwar Chandra Kumar,
Sheth Vinit,
Dey Anindya,
Asfa Sima,
Gulla Suresh Kumar,
Xu Chao,
Fung KarMing,
Robertson J. David,
Bieniasz Magdalena,
Wilhelm Stefan,
Bhattacharya Resham,
Mukherjee Priyabrata
Publication year - 2022
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.202200491
Subject(s) - pten , ovarian cancer , pi3k/akt/mtor pathway , cancer research , serous fluid , medicine , growth inhibition , biodistribution , ovarian tumor , cancer , chemistry , pharmacology , cell growth , signal transduction , in vitro , biochemistry
Abstract By exploiting the self‐therapeutic properties of gold nanoparticles (GNPs) a molecular axis that promotes the growth of high‐grade serous ovarian cancer (HGSOC), one of the deadliest gynecologic malignancies with poorly understood underlying molecular mechanisms, has been identified. The biodistribution and toxicity of GNPs administered by intravenous or intraperitoneal injection, both as a single dose or by repeated dosing over two weeks are first assessed; no biochemical or histological toxicity to vital organs is found. Using an orthotopic patient‐derived xenograft (PDX) model of HGSOC, the authors then show that GNP treatment robustly inhibits tumor growth. Investigating the molecular mechanisms underlying the GNP efficacy reveals that GNPs downregulate insulin growth factor binding protein 2 (IGFBP2) by disrupting its autoregulation via the IGFBP2/mTOR/PTEN axis. This mechanism is validated by treating a cell line‐based human xenograft tumor with GNPs and an mTOR dual‐kinase inhibitor (PI‐103), either individually or in combination with GNPs; GNP and PI‐103 combination therapy inhibit ovarian tumor growth similarly to GNPs alone. This report illustrates how the self‐therapeutic properties of GNPs can be exploited as a discovery tool to identify a critical signaling axis responsible for poor prognosis in ovarian cancer and provides an opportunity to interrogate the axis to improve patient outcomes.

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