“Giving cancer the flu”
RIG-I in the tumor microenvironment
Strategies to manipulate the tumor immune microenvironment including antibodies targeting immune checkpoints have revolutionized cancer treatment. However, many tumors are immunologically ‘cold’ thereby escaping these immunotherapies. ‘Tricks and tips’ from viruses/bacteria or autoimmune disease have yielded many approaches to enhance immune recognition of tumors. We found that an RNA sensing pathway, Retinoic acid Induced Gene 1 (RIG-I) that serves as a receptor for viral RNA, can be adopted as a robust immune activator across cancer types . A few questions we are investigating currently
What cell types in the tumor benefit from RIG activation - the tumor cells or immune cells?
What makes some tumors sensitive or resistant to RIG activation?
Can we develop small molecule modulators of RIG-I function ?
____________________________________________________________________________________________________
“Endothelial cells orchestrate the cytokine storm during flu. Can we make them do this in cancer?”
Nucleic Acid Sensing and Endothelial Dysfunction
DNA and RNA sensors in endothelial cells (ECs) has been shown to drive inflammation in cancer atherosclerosis and obesity. We previously showed that enhancing DNA sensing by inhibiting three prime exonuclease 1 (TREX1) in ECs led to EC dysfunction. We found that activation of a cytosolic RNA sensor, Retinoic acid Induced Gene 1 (RIG-I) diminishes EC survival, angiogenesis and triggers tissue specific gene expression programs. We have recently discovered a RIG-I dependent gene signature that affects angiogenesis, inflammation and coagulation. We propose that activation of RIG-I pathway in different vascular beds contributes to pathology in different diseases ranging from viral infections to cancer. We are currently testing how these nucleic acid sensors in ECs function across different tissues during development, homeostasis and dysfunction. We are also working to elucidate how these nucleic acid sensors drive EC dysfunction using integrated transcriptomics, proteomics and phosphoproteomics approaches.