Open AccessIs tumor cell specificity distinct from tumor selectivity in vivo? A quantitative NIR molecular imaging analysis of nanoliposome targeting
Author(s) -
Girgis Obaid,
Kimberley S. Samkoe,
Kenneth M. Tichauer,
Shazia Bano,
Yeonjae Park,
Zachary Silber,
Sassan Hodge,
Susan Callaghan,
Mina Guirguis,
Srivalleesha Mallidi,
Brian W. Pogue,
Tayyaba Hasan
Publication year - 2020
Publication title -
nano research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.536
H-Index - 125
eISSN - 1998-0124
pISSN - 1998-0000
DOI - 10.1007/s12274-020-3178-x
Subject(s) - in vivo , molecular imaging , ex vivo , cancer research , cetuximab , epidermal growth factor receptor , receptor , chemistry , biology , biochemistry , immunology , antibody , microbiology and biotechnology , monoclonal antibody
The significance and ability for receptor targeted nanoliposomes (tNLs) to bind to their molecular targets in solid tumors in vivo has been questioned, particularly as the efficiency of their tumor accumulation and selectivity is not always predictive of their efficacy or molecular specificity. This study presents, for the first time, in situ NIR molecular imaging-based quantitation of the in vivo specificity of tNLs for their target receptors, as opposed to tumor selectivity, which includes influences of enhanced tumor permeability and retention. Results show that neither tumor delivery nor selectivity (tumor-to-normal ratio) of cetuximab and IRDye conjugated tNLs correlate with EGFR expression in U251, U87 and 9L tumors, and in fact underrepresent their imaging-derived molecular specificity by up to 94.2%. Conversely, their in vivo specificity, which we quantify as the concentration of tNL-reported tumor EGFR provided by NIR molecular imaging, correlates positively with EGFR expression levels in vitro and ex vivo (Pearson's r= 0.92 and 0.96, respectively). This study provides a unique opportunity to address the problematic disconnect between tNL synthesis and in vivo specificity. The findings encourage their continued adoption as platforms for precision medicine, and facilitates intelligent synthesis and patient customization in order to improve safety profiles and therapeutic outcomes.