Systemic Delivery of Paclitaxel by Find-Me Nanoparticles Activates Antitumor Immunity and Eliminates Tumors.
Soonbum KwonFanfei MengHassan TamamHytham H GadallaJianping WangBoyang DongAmber S Hopf JannaschTimothy L RatliffYoon YeoPublished in: ACS nano (2024)
Local delivery of immune-activating agents has shown promise in overcoming an immunosuppressive tumor microenvironment (TME) and stimulating antitumor immune responses in tumors. However, systemic therapy is ultimately needed to treat tumors that are not readily locatable or accessible. To enable systemic delivery of immune-activating agents, we employ poly(lactic- co -glycolide) (PLGA) nanoparticles (NPs) with a track record in systemic application. The surface of PLGA NPs is decorated with adenosine triphosphate (ATP), a damage-associated molecular pattern to recruit antigen-presenting cells (APCs). The ATP-conjugated PLGA NPs (NP pD -ATP) are loaded with paclitaxel (PTX), a chemotherapeutic agent inducing immunogenic cell death to generate tumor antigens in situ . We show that the NP pD -ATP retains ATP activity in hostile TME and provides a stable "find-me" signal to recruit APCs. Therefore, the PTX-loaded NP pD -ATP helps populate antitumor immune cells in TME and attenuate the growth of CT26 and B16F10 tumors better than a mixture of PTX-loaded NP pD and ATP. Combined with anti-PD-1 antibody, PTX-loaded NP pD -ATP achieves complete regression of CT26 tumors followed by antitumor immune memory. This study demonstrates the feasibility of systemic immunotherapy using a PLGA NP formulation that delivers ICD-inducing chemotherapy and an immunostimulatory signal.
Keyphrases
- drug delivery
- cell death
- cancer therapy
- immune response
- computed tomography
- signaling pathway
- squamous cell carcinoma
- induced apoptosis
- cell cycle arrest
- machine learning
- magnetic resonance imaging
- oxidative stress
- photodynamic therapy
- case report
- contrast enhanced
- working memory
- toll like receptor
- locally advanced
- dual energy
- endoplasmic reticulum stress
- drug induced
- deep learning
- bone marrow
- mesenchymal stem cells
- positron emission tomography
- quantum dots
- reduced graphene oxide
- smoking cessation