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Pre-clinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma

ABSTRACT: Multiple myeloma (MM) is a neoplasia of bone marrow (BM) plasma cells that remains largely incurable with current treatment. Advancing therapeutic discoveries has been hampered by the lack of genetically heterogeneous models of MM. To circumvent this limitation, we engineered fifteen mouse models carrying combinations of eight MM genetic drivers, which fulfilled the pathogenesis of human disease including progression from premalignant states under immune surveillance. Integrative analyses of ⁓500 mice and ⁓1,000 patients revealed a MAPK-MYC genetic pathway that regulates time to progression and immune escape mechanisms across genetically heterogeneous tumors. During progression, MYC-dependent and independent remodeling of the BM microenvironment divided MM into immune categories with predominance of selected T-cell subpopulations, which dictated immunotherapy responses. Experimental targeting of the cytotoxic or immunosuppressive T-cell states observed in refractory MM patients enhanced immunotherapy effectiveness. Our resource enabled characterization of MM cell-intrinsic and immunological traits at unprecedented levels, which will accelerate the translation of personalized immunotherapy.

ORGANISM(S): Mus musculus

PROVIDER: GSE220997 | GEO | 2023/01/31

REPOSITORIES: GEO

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Project description:Background: Anti-tumor immunity is highly heterogeneous between individuals; however, underlying mechanisms remain elusive, despite their potential to improve personalized cancer immunotherapy. Head and neck squamous cell carcinomas (HNSCCs) vary significantly in immune infiltration and therapeutic responses between patients, demanding a mouse model with appropriate heterogeneity to investigate mechanistic differences. Methods: We developed a unique HNSCC mouse model to investigate underlying mechanisms of heterogeneous anti-tumor immunity. This model system may provide a better control for tumor-intrinsic and host-genetic variables, thereby uncovering the contribution of the adaptive immunity to tumor eradication. We employed single-cell T-cell receptor (TCR) sequencing coupled with single-cell RNA sequencing to identify the difference in TCR repertoire of CD8 tumor infiltrating lymphocytes (TILs) and the unique activation states linked with different TCR clonotypes. Results: We discovered that genetically identical wild-type recipient mice responded heterogeneously to the same SCC tumors orthotopically transplanted into the buccal mucosa. While tumors initially grew in 100% of recipients and most developed aggressive tumors, ~25% of recipients reproducibly eradicated tumors without intervention. Heterogeneous anti-tumor responses were dependent on CD8 T cells. Consistently, CD8 TILs in regressing tumors were significantly increased and more activated. Single-cell TCR-sequencing revealed that CD8 TILs from both growing and regressing tumors displayed evidence of clonal expansion compared with splenic controls. However, top TCR clonotypes and TCR specificity groups appear to be mutually exclusive between regressing and growing TILs. Furthermore, many TCRa/TCRb sequences only occur in one recipient. By coupling single-cell transcriptomic analysis with unique TCR clonotypes, we found that top TCR clonotypes clustered in distinct activation states in regressing vs. growing TILs. Intriguingly, the few TCR clonotypes shared between regressors and progressors differed greatly in their activation states, suggesting a more dominant influence from tumor microenvironment than TCR itself on T cell activation status. Conclusions: We reveal that intrinsic differences in the TCR repertoire of TILs and their different transcriptional trajectories may underlie the heterogeneous anti-tumor immune responses in different hosts. We suggest that anti-tumor immune responses are highly individualized and different hosts employ different TCR specificities against the same tumors, which may have important implications for developing personalized cancer immunotherapy.

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Pre-clinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma

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