Back

Opposing immune and genetic forces shape oncogenic programs in synovial sarcoma

Jerby, L.; Neftel, C.; Shore, M. E.; McBride, M. J.; Haas, B.; Izar, B.; Weissman, H. R.; Volorio, A.; Boulay, G.; Cironi, L.; Richman, A. R.; Broye, L. C.; Gurski, J. M.; Luo, C. C.; Mylvaganam, R.; Nguyen, L.; Mei, S.; Melms, J. c.; Georgescu, C.; Cohen, O.; Buendia-Buendia, J. E.; Cuoco, M. S.; Labes, D.; Zollinger, D. R.; Beechem, J. M.; Nielsen, P.; Chebib, I.; Cote, G.; Choy, E.; Letovanec, I.; Cherix, S.; Wagle, N.; Sorger, P. K.; Haynes, A. B.; Mullen, J. T.; Stamenkovic, I.; Rivera, M. N.; Kadoch, C.; Rozenblatt-Rosen, O.; Suva, M. L.; Riggi, N.; Regev, A.

2019-08-04 cancer biology
10.1101/724302 bioRxiv
Show abstract

Synovial sarcoma is an aggressive mesenchymal neoplasm, driven by the SS18-SSX fusion, and characterized by immunogenic antigens expression and exceptionally low T cell infiltration levels. To study the cancer-immune interplay in this disease, we profiled 16,872 cells from 12 human synovial sarcoma tumors using single-cell RNA-sequencing (scRNA-Seq). Synovial sarcoma manifests antitumor immunity, high cellular plasticity and a core oncogenic program, which is predictive of low immune levels and poor clinical outcomes. Using genetic and pharmacological perturbations, we demonstrate that the program is controlled by the SS18-SSX driver and repressed by cytokines secreted by macrophages and T cells in the tumor microenvironment. Network modeling predicted that SS18-SSX promotes the program through HDAC1 and CDK6. Indeed, the combination of HDAC and CDK4/6 inhibitors represses the program, induces immunogenic cell states, and selectively targets synovial sarcoma cells. Our study demonstrates that immune evasion, cellular plasticity, and cell cycle are co-regulated and can be co-targeted in synovial sarcoma and potentially in other malignancies.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.