bioRxivCancer Biology
Immunosuppressive tumor microenvironment of osteosarcoma
A. M. Taylor, J. Sheng, P. K. S. Ng, J. M. Harder, P. Kumar, J. Y. Ahn, Y. Cao, A. M. Dzis, N. L. Jillette, A. Goodspeed, A. Bodlak, Q. Wu, M. S. Isakoff, J. George, J. D. S. Grassman, D. Luo, W. F. Flynn, E. T. Courtois, P. Robson, M. Hayashi, A. T. Paolillo, A. S. Petrilli, S. R. C. de Toledo, F. S. Balarezo, A. D. Lindsay, , C. C. Lau
Abstract
Osteosarcoma is the most common malignant bone tumor in children, characterized by a high degree of genomic instability, resulting in copy-number alterations and genomic rearrangements without disease-defining recurrent mutations. Clinical trials based on molecular characterization have failed to find new effective therapies or improve outcomes over the last 40 years. To better understand the immune microenvironment of osteosarcoma, we performed single-cell RNA sequencing on six tumor biopsy samples, combined with a previously-published cohort of six samples. Additional osteosarcoma samples were profiled using spatial transcriptomics for validation of discovered subtypes and to add spatial context. Analysis revealed immunosuppressive cells, including myeloid-derived suppressor cells (MDSCs), regulatory and exhausted T-cells, and LAMP3+ dendritic cells. Using cell-cell communication modeling, we identified robust interactions between MDSCs and other cells, leading to NF-{kappa}B upregulation and an immunosuppressive microenvironment, as well as interactions involving regulatory T-cells and osteosarcoma cells that promoted tumor progression and a proangiogenic niche. Statement of SignificanceOsteosarcoma patient survival has remained stagnant for several decades due to lack of successful therapy for high-risk patients, including those with metastatic disease. Identifying novel therapeutics including immunotherapies is of great clinical importance. Our study highlights several important immunosuppressive mechanisms within osteosarcoma that should be considered when developing future immunotherapies.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: cell-cell communication
- approach: deep learning
- approach: statistical model
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