Self-Splittable Transcytosis Nanoraspberry for NIR-II Photo-Immunometabolic Cancer Therapy in Deep Tumor Tissue.
Li WangWei JiangYanhong SuMeixiao ZhanShaojun PengHang LiuLigong LuPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2022)
Cancer photo-immunotherapy (CPIT) as an ideal strategy can rapidly release hostile signals by appropriate dosage of focal laser irradiation to unmask primary tumor immunogenicity and can activate adaptive immunity to control distant metastases. However, many factors, including disordered immunometabolism, poor penetration of photothermal agents and immuno-regulators, inadequate laser penetration into the deep tumor region, restrict the therapeutic outcomes of CPIT. Here, a second near-infrared window (NIR-II) photo-immunometabolic cancer therapy (PICT) by a programmed raspberry-structured nanoadjuvant (PRN MT ) is presented that can potentiates efficient immunogenic cell death (ICD) in deep tumor tissue and alleviates immunometabolic disorder. The PRN MT is architected through self-assembly of indoleamine 2,3-dioxygenase 1 (IDO-1) inhibitor modified small-sized CuS nanoparticles (CuS 5 ) and tumor microenvironment (TME) responsive cationized polymeric matrix. The TME can trigger the splitting and surface cationization of PRN MT into small cationized CuS 5 that feature high transcytosis potential and TME immunometabolic regulation. Upon NIR-II irradiation, CuS 5 induce homogeneous ICD and release immunometabolic regulator in deep tumor tissues, which ameliorates IDO-1 mediated immunometabolic disorder and further suppresses regulatory T cells infiltration. PRN MT mediated PICT effectively delays the primary murine mammary carcinoma 4T1 tumor growth and inhibits the lethal pulmonary metastasis in combination with programmed cell death protein 1 (PD1) blockade.
Keyphrases
- cancer therapy
- regulatory t cells
- drug delivery
- cell death
- photodynamic therapy
- drug release
- blood brain barrier
- transcription factor
- dendritic cells
- fluorescence imaging
- machine learning
- lymph node
- squamous cell carcinoma
- adipose tissue
- risk assessment
- deep learning
- type diabetes
- radiation therapy
- small molecule
- insulin resistance
- radiation induced