Transplantation with autologous hematopoietic progenitors remains an important consolidation treatment for patients with multiple myeloma (MM) and is thought to prolong the disease plateau phase by providing intensive cytoreduction. However, transplantation induces inflammation in the context of profound lymphodepletion that may cause hitherto unexpected immunological effects. We developed preclinical models of bone marrow transplantation (BMT) for MM using Vk*MYC myeloma–bearing recipient mice and donor mice that were myeloma naive or myeloma experienced to simulate autologous transplantation. Surprisingly, we demonstrated broad induction of T cell–dependent myeloma control, most efficiently from memory T cells within myeloma-experienced grafts, but also through priming of naive T cells after BMT. CD8+ T cells from mice with controlled myeloma had a distinct T cell receptor (TCR) repertoire and higher clonotype overlap relative to myeloma-free BMT recipients. Furthermore, T cell–dependent myeloma control could be adoptively transferred to secondary recipients and was myeloma cell clone specific. Interestingly, donor-derived IL-17A acted directly on myeloma cells expressing the IL-17 receptor to induce a transcriptional landscape that promoted tumor growth and immune escape. Conversely, donor IFN-γ secretion and signaling were critical to protective immunity and were profoundly augmented by CD137 agonists. These data provide new insights into the mechanisms of action of transplantation in myeloma and provide rational approaches to improving clinical outcomes.
Slavica Vuckovic, Simone A. Minnie, David Smith, Kate H. Gartlan, Thomas S. Watkins, Kate A. Markey, Pamela Mukhopadhyay, Camille Guillerey, Rachel D. Kuns, Kelly R. Locke, Antonia L. Pritchard, Peter A. Johansson, Antiopi Varelias, Ping Zhang, Nicholas D. Huntington, Nicola Waddell, Marta Chesi, John J. Miles, Mark J. Smyth, Geoffrey R. Hill
Usage data is cumulative from November 2018 through November 2019.
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.