High-capacity poly(2-oxazoline) formulation of TLR 7/8 agonist extends survival in a chemo-insensitive, metastatic model of lung adenocarcinoma.
Natasha VinodDuhyeong HwangSalma H AzamAmanda E D Van SwearingenElizabeth WayneSloane Christian FussellMarina Sokolsky-PapkovChad V PecotAlexander V KabanovPublished in: Science advances (2020)
About 40% of patients with non-small cell lung cancer (NSCLC) have stage IV cancer at the time of diagnosis. The only viable treatment options for metastatic disease are systemic chemotherapy and immunotherapy. Nonetheless, chemoresistance remains a major cause of chemotherapy failure. New immunotherapeutic modalities such as anti-PD-1 immune checkpoint blockade have shown promise; however, response to such strategies is highly variable across patients. Here, we show that our unique poly(2-oxazoline)-based nanomicellar formulation (PM) of Resiquimod, an imidazoquinoline Toll-like receptor (TLR) 7/8 agonist, had a superior tumor inhibitory effect in a metastatic model of lung adenocarcinoma, relative to anti-PD-1 therapy or platinum-based chemotherapy. Investigation of the in vivo immune status following Resiquimod PM treatment showed that Resiquimod-based stimulation of antigen-presenting cells in the tumor microenvironment resulted in the mobilization of an antitumor CD8+ immune response. Our study demonstrates the promise of poly(2-oxazoline)-formulated Resiquimod for treating metastatic NSCLC.
Keyphrases
- toll like receptor
- small cell lung cancer
- immune response
- squamous cell carcinoma
- locally advanced
- inflammatory response
- nuclear factor
- air pollution
- particulate matter
- end stage renal disease
- drug delivery
- ejection fraction
- induced apoptosis
- chronic kidney disease
- brain metastases
- newly diagnosed
- papillary thyroid
- prognostic factors
- radiation therapy
- young adults
- combination therapy
- rectal cancer
- risk assessment
- endoplasmic reticulum stress
- dendritic cells
- bone marrow
- water soluble
- stem cells
- cell cycle arrest
- lymph node metastasis
- squamous cell
- deep learning
- machine learning
- childhood cancer
- chemotherapy induced
- replacement therapy