Cargando…

Extracellular matrix physical properties govern the diffusion of nanoparticles in tumor microenvironment

Nanoparticles (NPs) are confronted with limited and disappointing delivery efficiency in tumors clinically. The tumor extracellular matrix (ECM), whose physical traits have recently been recognized as new hallmarks of cancer, forms a main steric obstacle for NP diffusion, yet the role of tumor ECM p...

Descripción completa

Detalles Bibliográficos
Autores principales: He, Xiaocong, Yang, Yuanyuan, Han, Yulong, Cao, Chunyu, Zhang, Zhongbin, Li, Lingxiao, Xiao, Cailan, Guo, Hui, Wang, Lin, Han, Lichun, Qu, Zhiguo, Liu, Na, Han, Shuang, Xu, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9910605/
https://www.ncbi.nlm.nih.gov/pubmed/36574668
http://dx.doi.org/10.1073/pnas.2209260120
Descripción
Sumario:Nanoparticles (NPs) are confronted with limited and disappointing delivery efficiency in tumors clinically. The tumor extracellular matrix (ECM), whose physical traits have recently been recognized as new hallmarks of cancer, forms a main steric obstacle for NP diffusion, yet the role of tumor ECM physical traits in NP diffusion remains largely unexplored. Here, we characterized the physical properties of clinical gastric tumor samples and observed limited distribution of NPs in decellularized tumor tissues. We also performed molecular dynamics simulations and in vitro hydrogel experiments through single-particle tracking to investigate the diffusion mechanism of NPs and understand the influence of tumor ECM physical properties on NP diffusion both individually and collectively. Furthermore, we developed an estimation matrix model with evaluation scores of NP diffusion efficiency through comprehensive analyses of the data. Thus, beyond finding that loose and soft ECM with aligned structure contribute to efficient diffusion, we now have a systemic model to predict NP diffusion efficiency based on ECM physical traits and provide critical guidance for personalized tumor diagnosis and treatment.