Despite significant advances in the treatment of multiple myeloma (MM), most patients succumb to disease progression. One of the major immunosuppressive mechanisms that is believed to play a role in myeloma progression is the expansion of regulatory T cells (Tregs). In this study, we demonstrate that myeloma cells drive Treg expansion and activation by secreting type 1 interferon (IFN). Blocking IFN α and β receptor 1 (IFNAR1) on Tregs significantly decreases both myeloma-associated Treg immunosuppressive function and myeloma progression. Using syngeneic transplantable murine myeloma models and bone marrow (BM) aspirates of MM patients, we found that Tregs were expanded and activated in the BM microenvironment at early stages of myeloma development. Selective depletion of Tregs led to a complete remission and prolonged survival in mice injected with myeloma cells. Further analysis of the interaction between myeloma cells and Tregs using gene sequencing and enrichment analysis uncovered a feedback loop, wherein myeloma-cell-secreted type 1 IFN induced proliferation and expansion of Tregs. By using IFNAR1-blocking antibody treatment and IFNAR1-knockout Tregs, we demonstrated a significant decrease in myeloma-associated Treg proliferation, which was associated with longer survival of myeloma-injected mice. Our results thus suggest that blocking type 1 IFN signaling represents a potential strategy to target immunosuppressive Treg function in MM.
Yawara Kawano, Oksana Zavidij, Jihye Park, Michele Moschetta, Katsutoshi Kokubun, Tarek H. Mouhieddine, Salomon Manier, Yuji Mishima, Naoka Murakami, Mark Bustoros, Romanos Sklavenitis Pistofidis, Mairead Reidy, Yu J. Shen, Mahshid Rahmat, Pavlo Lukyanchykov, Esilida Sula Karreci, Shokichi Tsukamoto, Jiantao Shi, Satoshi Takagi, Daisy Huynh, Antonio Sacco, Yu-Tzu Tai, Marta Chesi, P. Leif Bergsagel, Aldo M. Roccaro, Jamil Azzi, Irene M. Ghobrial
Usage data is cumulative from October 2019 through October 2020.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.