Unleashing the Power of NR4A1 Degradation as a Novel Strategy for Cancer Immunotherapy.
Lei WangYufeng XiaoYuewan LuoRohan P MasterJiao MoMyung-Chul KimYi LiuUrvi M PatelXiangming LiDonald ShafferKevin R GuertinEmily MoserKeiran S SmalleyDaohong ZhouGuangrong ZhengWeizhou ZhangPublished in: bioRxiv : the preprint server for biology (2023)
An effective cancer therapy requires both killing cancer cells and targeting tumor-promoting pathways or cell populations within the tumor microenvironment (TME). We purposely search for molecules that are critical for multiple tumor-promoting cell types and identified nuclear receptor subfamily 4 group A member 1 (NR4A1) as one such molecule. NR4A1 has been shown to promote the aggressiveness of cancer cells and maintain the immune suppressive TME. Using genetic and pharmacological approaches, we establish NR4A1 as a valid therapeutic target for cancer therapy. Importantly, we have developed the first-of-its kind proteolysis-targeting chimera (PROTAC, named NR-V04) against NR4A1. NR-V04 effectively degrades NR4A1 within hours of treatment in vitro and sustains for at least 4 days in vivo , exhibiting long-lasting NR4A1-degradation in tumors and an excellent safety profile. NR-V04 leads to robust tumor inhibition and sometimes eradication of established melanoma tumors. At the mechanistic level, we have identified an unexpected novel mechanism via significant induction of tumor-infiltrating (TI) B cells as well as an inhibition of monocytic myeloid derived suppressor cells (m-MDSC), two clinically relevant immune cell populations in human melanomas. Overall, NR-V04-mediated NR4A1 degradation holds promise for enhancing anti- cancer immune responses and offers a new avenue for treating various types of cancer.
Keyphrases
- cancer therapy
- immune response
- drug delivery
- squamous cell carcinoma
- single cell
- stem cells
- induced apoptosis
- oxidative stress
- machine learning
- dna methylation
- inflammatory response
- cell proliferation
- genome wide
- cell therapy
- toll like receptor
- mesenchymal stem cells
- big data
- helicobacter pylori infection
- deep learning
- combination therapy
- genome wide identification