ABSTRACT
Synovial sarcoma (SyS) is an aggressive neoplasm driven by the SS18-SSX fusion, and is characterized by low T cell infiltration. Here, we studied the cancer-immune interplay in SyS using an integrative approach that combines single-cell RNA sequencing (scRNA-seq), spatial profiling and genetic and pharmacological perturbations. scRNA-seq of 16,872 cells from 12 human SyS tumors uncovered a malignant subpopulation that marks immune-deprived niches in situ and is predictive of poor clinical outcomes in two independent cohorts. Functional analyses revealed that this malignant cell state is controlled by the SS18-SSX fusion, is repressed by cytokines secreted by macrophages and T cells, and can be synergistically targeted with a combination of HDAC and CDK4/CDK6 inhibitors. This drug combination enhanced malignant-cell immunogenicity in SyS models, leading to induced T cell reactivity and T cell-mediated killing. Our study provides a blueprint for investigating heterogeneity in fusion-driven malignancies and demonstrates an interplay between immune evasion and oncogenic processes that can be co-targeted in SyS and potentially in other malignancies.
Subject(s)
Carcinogenesis/genetics , Molecular Targeted Therapy , Oncogene Proteins, Fusion/genetics , Sarcoma, Synovial/drug therapy , Cell Line, Tumor , Cyclin-Dependent Kinase 4/antagonists & inhibitors , Histone Deacetylase Inhibitors/therapeutic use , Histone Deacetylases/genetics , Histone Deacetylases/therapeutic use , Humans , Oncogene Proteins, Fusion/antagonists & inhibitors , Oncogenes/genetics , RNA-Seq , Sarcoma, Synovial/genetics , Sarcoma, Synovial/pathology , Single-Cell AnalysisABSTRACT
Accurate orthologue identification is a vital component of bacterial comparative genomic studies, but many popular sequence-similarity-based approaches do not scale well to the large numbers of genomes that are now generated routinely. Furthermore, most approaches do not take gene synteny into account, which is useful information for disentangling paralogues. Here, we present SynerClust, a user-friendly synteny-aware tool based on synergy that can process thousands of genomes. SynerClust was designed to analyse genomes with high levels of local synteny, particularly prokaryotes, which have operon structure. SynerClust's run-time is optimized by selecting cluster representatives at each node in the phylogeny; thus, avoiding the need for exhaustive pairwise similarity searches. In benchmarking against Roary, Hieranoid2, PanX and Reciprocal Best Hit, SynerClust was able to more completely identify sets of core genes for datasets that included diverse strains, while using substantially less memory, and with scalability comparable to the fastest tools. Due to its scalability, ease of installation and use, and suitability for a variety of computing environments, orthogroup clustering using SynerClust will enable many large-scale prokaryotic comparative genomics efforts.
