Cancer immune therapy using engineered ‛tail-flipping' nanoliposomes targeting alternatively activated macrophages.
Praneeth R KunintyKarin Binnemars-PostmaAhmed JarrayKunal P PednekarMarcel Alexander HeinrichHelen J PijffersHetty Ten HoopenGert StormPeter van HoogevestWouter K den OtterJai PrakashPublished in: Nature communications (2022)
Alternatively-activated, M2-like tumor-associated macrophages (TAM) strongly contribute to tumor growth, invasiveness and metastasis. Technologies to disable the pro-tumorigenic function of these TAMs are of high interest to immunotherapy research. Here we show that by designing engineered nanoliposomes bio-mimicking peroxidated phospholipids that are recognised and internalised by scavenger receptors, TAMs can be targeted. Incorporation of phospholipids possessing a terminal carboxylate group at the sn-2 position into nanoliposome bilayers drives their uptake by M2 macrophages with high specificity. Molecular dynamics simulation of the lipid bilayer predicts flipping of the sn-2 tail towards the aqueous phase, while molecular docking data indicates interaction of the tail with Scavenger Receptor Class B type 1 (SR-B1). In vivo, the engineered nanoliposomes are distributed specifically to M2-like macrophages and, upon delivery of the STAT6 inhibitor (AS1517499), zoledronic acid or muramyl tripeptide, these cells promote reduction of the premetastatic niche and/or tumor growth. Altogether, we demonstrate the efficiency and versatility of our engineered "tail-flipping" nanoliposomes in a pre-clinical model, which paves the way to their development as cancer immunotherapeutics in humans.
Keyphrases
- molecular dynamics simulations
- molecular docking
- papillary thyroid
- squamous cell
- induced apoptosis
- fatty acid
- cancer therapy
- squamous cell carcinoma
- cell cycle arrest
- electronic health record
- lymph node metastasis
- cell death
- childhood cancer
- cell proliferation
- young adults
- anti inflammatory
- machine learning
- endoplasmic reticulum stress
- ionic liquid
- artificial intelligence
- pi k akt