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Area of Science:

  • Biomedical Engineering
  • Nanotechnology
  • Vascular Biology

Background:

  • Low-permeability (LP) tumor vasculature hinders nanomedicine efficacy.
  • Quantitative understanding of tumor vascular permeability is crucial for drug delivery.
  • Developing strategies to overcome these vascular barriers is essential.

Purpose of the Study:

  • To introduce a deep learning-guided microneedle (MN) platform for precise tumor vasculature modulation.
  • To enhance nanoparticle extravasation into tumors.
  • To quantitatively map vascular remodeling and nanoparticle transport.

Main Methods:

  • Utilized a microneedle (MN) delivery system for localized histamine administration.
  • Integrated the MN system with the nano-ISML 1.1 single-vessel analysis framework.
  • Quantitatively analyzed vascular remodeling and nanoparticle transport in diverse tumor models.

Main Results:

  • Localized histamine delivery via MNs selectively expanded endothelial junctions, increasing interendothelial gaps.
  • Reprogrammed LP tumors to a high-permeability phenotype, enhancing nanoparticle extravasation.
  • Established a size-dependent permeability window, allowing nanoparticles ≤200 nm while excluding >500 nm particles.

Conclusions:

  • The developed MN platform enables controlled modulation of tumor vasculature.
  • This approach overcomes vascular barriers for improved nanomedicine delivery.
  • The interdisciplinary framework offers a mechanistic and predictive paradigm for tumor-targeted nanomedicines.