Abstract A112: Mapping the impact of proteasome inhibitor therapy on the antigenic landscape of multiple myeloma: Identifying robust targets for T cell immunotherapy

Author(s):  
Daniel J. Kowalewski ◽  
Simon Walz ◽  
Linus Backert ◽  
Heiko Schuster ◽  
Oliver Kohlbacher ◽  
...  
Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3001-3001
Author(s):  
Daniel Johannes Kowalewski ◽  
Simon D. Walz ◽  
Linus Backert ◽  
Heiko Schuster ◽  
Susanne M. Rittig ◽  
...  

Abstract Recent studies underscore that multiple myeloma is an immunogenic disease and suggest that it can be effectively treated by T cell based immunotherapy via immunomodulation. This strategy might be synergistically complemented by therapeutic vaccination, which may help induce and guide specific anti-cancer T cell responses. We have recently conducted a study which directly characterized the antigenic landscape of myeloma by mass spectrometric analysis of naturally presented HLA ligands and identified a panel of T cell epitopes characterized by exquisite myeloma-association (Walz, Stickel et. al., Blood 2015). As standard of care in myeloma includes proteasome inhibitor therapy and the proteasome plays a central role in the generation of MHC-presented peptides, it is of great importance to thoroughly characterize and take into account the effects of this treatment on the antigenic landscape of myeloma cells and implement only robustly presented targets for peptide vaccine design. This is even more important Here we present a mass spectrometry-based study, which longitudinally and semi-quantitatively maps the effects of treatment with the 2nd generation proteasome inhibitor carfilzomib in an in vitro model of multiple myeloma. We observed considerable plasticity of the HLA class I ligandome of MM.1S cells after treatment with carfilzomib with 17.9±1.1.% (mean of 3 biological replicates ± SD) of HLA ligands showing significant modulation (fold change ≥ 4, P ≤ 0.01) at t24h compared to mock-treated controls (down-modulated: 11.5±1.1%, up-modulated: 6.3±0.6%). We were able to longitudinally tracke the abundance of 28 previously defined myeloma antigens, confirming robust (16/28, 57.1%) or even increased presentation (8/28, 28.6%) under treatment for the majority of these peptides. However, - importantly - we observed highly distortive effects of carfilzomib treatment on the HLA allotype distribution of target cells, which manifested as a marked reduction of HLA ligands restricted by HLA-A*23:01 and A*24:02 (-62.5±1.8% and -57.0±0.6%, respectively, at t=24h after treatment). These findings indicate strong allotype-specific effects of carfilzomib on the antigenic landscape of myeloma cells, which we interpret to be a direct reflection of the mechanism of action of this drug. As a significant proportion of the U.S. population are carriers of the affected alleles (A*23:01: 8.2%; A*24:02: 22.6%), these findings could have broad implications for the design or implementation of antigen-specific therapies in patients under proteasome inhibitor treatment. Furthermore, these findings might indicate the possibility of altered cancer immunosurveillance as a consequence of proteasome inhibitor therapy. Disclosures Weisel: Amgen: Consultancy, Honoraria, Other: Travel Support; Onyx: Consultancy, Honoraria; Novartis: Other: Travel Support; Janssen Pharmaceuticals: Consultancy, Honoraria, Other: Travel Support, Research Funding; Noxxon: Consultancy; Celgene: Consultancy, Honoraria, Other: Travel Support, Research Funding; BMS: Consultancy, Honoraria, Other: Travel Support.


Oncotarget ◽  
2018 ◽  
Vol 9 (40) ◽  
pp. 25764-25780 ◽  
Author(s):  
De-Xiu Bu ◽  
Reshma Singh ◽  
Eugene E. Choi ◽  
Marco Ruella ◽  
Selene Nunez-Cruz ◽  
...  

Cancers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2941
Author(s):  
Luciana R. C. Barros ◽  
Emanuelle A. Paixão ◽  
Andrea M. P. Valli ◽  
Gustavo T. Naozuka ◽  
Artur C. Fassoni ◽  
...  

Immunotherapy has gained great momentum with chimeric antigen receptor T cell (CAR-T) therapy, in which patient’s T lymphocytes are genetically manipulated to recognize tumor-specific antigens, increasing tumor elimination efficiency. In recent years, CAR-T cell immunotherapy for hematological malignancies achieved a great response rate in patients and is a very promising therapy for several other malignancies. Each new CAR design requires a preclinical proof-of-concept experiment using immunodeficient mouse models. The absence of a functional immune system in these mice makes them simple and suitable for use as mathematical models. In this work, we develop a three-population mathematical model to describe tumor response to CAR-T cell immunotherapy in immunodeficient mouse models, encompassing interactions between a non-solid tumor and CAR-T cells (effector and long-term memory). We account for several phenomena, such as tumor-induced immunosuppression, memory pool formation, and conversion of memory into effector CAR-T cells in the presence of new tumor cells. Individual donor and tumor specificities are considered uncertainties in the model parameters. Our model is able to reproduce several CAR-T cell immunotherapy scenarios, with different CAR receptors and tumor targets reported in the literature. We found that therapy effectiveness mostly depends on specific parameters such as the differentiation of effector to memory CAR-T cells, CAR-T cytotoxic capacity, tumor growth rate, and tumor-induced immunosuppression. In summary, our model can contribute to reducing and optimizing the number of in vivo experiments with in silico tests to select specific scenarios that could be tested in experimental research. Such an in silico laboratory is an easy-to-run open-source simulator, built on a Shiny R-based platform called CARTmath. It contains the results of this manuscript as examples and documentation. The developed model together with the CARTmath platform have potential use in assessing different CAR-T cell immunotherapy protocols and its associated efficacy, becoming an accessory for in silico trials.


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