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.
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Processed scRNA-seq data is available via the Gene Expression Omnibus (GEO), accession number GSE131309 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE131309). Processed scRNA-seq data and interactive plots generated for this study are also provided through the Single Cell Portal at https://portals.broadinstitute.org/single_cell/study/synovial-sarcoma. Raw scRNA-Seq data are deposited in the controlled access repository DUOS (https://duos.broadinstitute.org/#/hom) accession: DUOS-000123 (via the data catalog https://duos.broadinstitute.org/dataset_catalog).
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We thank L. Gaffney and A. Hupalowska for help with artwork and L. Gaffney for help in figure preparation. We thank K. Itoh, N. Naka and S. Takenaka (Osaka University, Japan) for providing the Aska cell lines, and Akira Kawai (National Cancer Center Hospital, Japan) for providing the SYO1 cell line. We thank M. Brown for help with CNA visualization. L.J.-A. is a Chan Zuckerberg Biohub investigator and holds a Career Award at the Scientific Interface from BWF. L.J.-A. was a fellow of the Eric and Wendy Schmidt postdoctoral program and a CRI Irvington Fellow supported by the CRI. A.R. is an HHMI Investigator. Work was supported by the Klarman Cell Observatory, STARR cancer consortium, NCI grants 1U24CA180922, R33-CA202820, the Koch Institute NCI Support (core) grant P30-CA14051, Ludwig Centers at Harvard and MIT, AMRF and the Broad Institute (A.R.). Work was also supported by grants from the Howard Goodman Fellowship at MGH (M.L.S.), the Merkin Institute Fellowship at the Broad Institute of MIT and Harvard (M.L.S.), R37CA245523 (M.L.S.), the Swiss National Science Foundation Sinergia grant CRSII5_177266 (M.L.S. and I.S.). Imaging CyCIF work was supported by a grant (CA225088) from the Center for Cancer Systems Pharmacology at Harvard Medical School (P.K.S.), K08CA222663 (B.I.), Burroughs Wellcome Fund Career Award for Medical Scientists (B.I.), Louis V. Gerstner, Jr. Scholars Program (B.I.) and the Velocity Fellow Program (B.I.). N.R. is supported by the Swiss National Science Foundation Professorship grant (PP00P3-157468/1 and PP00P3_183724), the Swiss Cancer League grant KFS-3973-08-2016, the Fond’Action Contre le Cancer grant and the FORCE grant. N.D.M. was supported by a postdoctoral fellowship from the American Cancer Society (PF-17-042-01-LIB) and the NIH education loan repayment program funded by the NCI (L30 CA231679-01). M.N.R. is supported by the Thomas and Diana Ryan MGH Research Scholar Award. Processed scRNA-seq data are available at https://portals.broadinstitute.org/single_cell/study/synovial-sarcoma and GEO GSE131309. Raw scRNA-seq data is deposited in the controlled access repository DUOS (https://duos.broadinstitute.org/#/hom) accession: DUOS-000123 (via the data catalog https://duos.broadinstitute.org/dataset_catalog).
A.R. is a founder of and equity holder in Celsius Therapeutics, an equity holder in Immunitas Therapeutics, and was a scientific advisory board member for Thermo Fisher Scientific, Syros Pharmaceuticals and Neogene Therapeutics until 1 August 2020. From 1 August 2020, A.R. is an employee of Genentech. M.L.S. is an equity holder, scientific cofounder and advisory board member of Immunitas Therapeutics. K.W.W. serves on the scientific advisory board of TCR2 Therapeutics, T-Scan Therapeutics, SQZ Biotech, Nextechinvest and receives sponsored research funding from Novartis. He is a cofounder of Immunitas Therapeutics. L.J.A, N.R., M.L.S. and A.R. are coinventors on US patent application filed by the Broad Institute relating to synovial sarcoma. O.R.-R. is an employee of Genentech and a coinventor on patent applications filed by the Broad Institute for inventions relating to single cell genomics, such as in PCT/US2018/060860 and US provisional application no. 62/745,259. D.R.Z., N.O. and J.M.B. are employees of Nanostring which developed GeoMx. C.K. is the scientific founder, fiduciary board of directors member, scientific advisory board member, shareholder and consultant for foghorn therapeutics. E.C. reports support paid to his institution for the conduct of clinical trials from Amgen, Astra Zeneca, Novartis, Bayer, Merck, Exelixis, GSK, Adaptimmune and Iterion. G.M.C. reports advisory board fees and support paid to his institution for the conduct of clinical trials from Agios, Epizyme, PharmaMar, Eisai; support paid to his institution for the conduct of clinical trials from Macrogenics, Boston Biomedical, Plexxicon, Merck KGaA / EMD Serono Research and Development Institute, CBA, SpringWorks Therapeutics, Bavarian-Nordic; compound for preclinical research and support paid to his institution for the conduct of clinical trials from Bayer. P.K.S. is a member of the SAB or Board of Directors of Applied Biomath, Glencoe Software and RareCyte and has equity in these companies. In the last five years the Sorger lab has received research funding from Novartis and Merck. The authors declare that these activities are not related to the research reported in this publication and have not influenced the conclusions in this manuscript. B.I. is a consultant for Merck and Volastra Therapeutics. N.W. is an equity holder and scientific advisory board member of Relay Therapeutics, a paid advisor to Eli Lilly and Co, and receives grant support from Puma Biotechnology. N.D.M. serves as a scientific advisor to Immunitas Therapeutics. C.N., M.E.S., H.R.W, M.J.M, B.H., B.I, A.V, G.B., L.C., A.R.Ri, L.C.B., J.M.G., C.C.L, R.M., L.N., S.M., J.C.M., C.G., O.C., J.E.B.-B., A.S., M.S., M.S.C, D.L., S.G., G. P.N., I.C., T.N.-N, M.M., E.C., I.L., S.C., A.B.H., J.T.M., I.S. and M.N.R declare no competing interests.
Peer review information Saheli Sadanand was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
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Extended Data Fig. 1 Consistent classification of cells based on expression and genetic features.
a, Converging assignments of cell identity. tSNE of single-cell profiles (dots), colored by (1) tumor sample, (2) inferred cell type, (3) SS18-SSX1/2 and MEOX2-AGMO fusion detection, (4) SSX1/2 gene detection (mRNA level > 0), (5) MEOX2 and AGMO gene detection (mRNA level > 0), (6-12) overall expression of well-established cell type markers (Supplementary Table 2). b, Droplet based scRNA-Seq of SyS. tSNE of single cells (dots), profiled with droplet-based scRNA-seq23, colored according to tumor sample (left) and inferred cell type (right). c, Differential similarity to SyS compared to other sarcomas (Methods) distinguishes malignant (n = 4,371) from non-malignant (n = 2,375) cells. Differential similarity (y axis) to SyS shown for cells in each cell subset (x axis). d, The SyS program distinguishes between SyS and non-SyS cancer types. Distribution of the SyS program Overall Expression (y axis) across BAF driven tumors (left, x axis) and in TCGA (right, x axis; n = 9,128; 253; and 10, for other, sarcoma, and SyS tumors). In (c-d) middle line: median; box edges: 25th and 75th percentiles, whiskers: most extreme points that do not exceed ±IQR*1.5; further outliers are marked individually; P-values: one-sided Wilcoxon-ranksum test; AUC: Area Under the receiver operating characteristic Curve.
Extended Data Fig. 2 Characterizing mesenchymal, epithelial and poorly differentiates malignant cells.
a, Epithelial and mesenchymal program genes. The expression of the top epithelial and mesenchymal program genes (rows) across the malignant cells (columns), with cells sorted according to the difference in epithelial minus mesenchymal OE scores (bottom plot). Topmost Color bar: epithelial vs. non-epithelial cell status, and sample. Canonical markers and immune-related genes are in red and blue, respectively. b, Cell cycle signature. Overall Expression of the G2/M (y axis) and G1/S (x axis) phase signatures in each malignant cell, colored by their cycling status. c, Cycling cells are less differentiated. The distribution of differentiation scores of cycling (red) and non-cycling (grey) malignant cells, across all tumors (top) and within each tumor (bottom; only tumors with at least 10 cycling cells are shown); p-value: mixed-effects test.
Extended Data Fig. 3 The core oncogenic program is detected using different approaches and datasets.
a, Agreement between the core oncogenic program detected by a PCA and an iNMF approach36. Overall Expression (OE) of the core oncogenic program across malignant SyS cells, as identified in the PCA-based approach33 (x axis) and in the iNMF approach36 (y axis) (Methods). (b-c) Program Overall Expression captures inter-tumor variation and the MYC-high cluster in 64 SyS tumors from an independent RNA-Seq cohort16. The tumors were previously classified into two transcriptionally distinct clusters16, denoted here as MYC-high and MYC-low. b, For each tumor (dots), shown is the Overall Expression (OE) of the core oncogenic program (y axis) vs. the projection on the second Principle Component (PC2) of the data. c, Normalized expression (centered log-transformed RPKM) of the core oncogenic program genes (columns) most correlated with PC2 across the tumors (columns). Tumors are sorted by their PC2 projection (bottom bar). d, The fraction of TLE1+LGALS1+ cells out of TLE1+ ones based on ISH of tumors SyS5 and SyS13; Data are presented as mean values ± SD, such that each dot corresponds to one high power field (HPF), with a total of 10 HPF per sample; TLE1 is a SyS cell marker and LGALS1 is a positive marker of the core oncogenic program.
Extended Data Fig. 4 Antitumor immunity and immune evasion in SyS.
a, CD8 T cell clones, stratified based on clone size (x axis) and tumor (color). b, Overall expression of the T cell expansion program in CD8 T cells with a reconstructed TCR (TCR+), when stratified based on clonality (Clone+ and Clone−, denoting clone size greater or equal to 1, respectively). c, The cancer testis antigens CTAG1A, CTAG1B (encoding for NY-ESO-1), and PRAME are exclusively expressed by SyS malignant (n = 4,371) cells compared to non-malignant ones (n = 2,375). Log-transformed TPM (y axis) in different cell subsets (x axis); p-values: one-sided Mann-Whitney test. d, tSNE of macrophage profiles, colored by M1/M2 polarization scores, according to signatures defined here (Supplementary Table 4). e, M1/M2 polarization scores (y axis) according to previously defined signatures42 in macrophages in our datasets partitioned to M1-like and M2-like subgroups (p-value: two-sided t-test). f, Spearman correlation coefficient (color bar) between each pair of genes from M1 and M2 signatures defined here (top, Supplementary Table 4) or previously42 (bottom) across macrophages in SyS (left) and melanoma30 (right). g, Overall Expression of the immune cell signatures (y axis, Methods) in SyS tumors (orange) and other cancer types (green); p-value: one-sided t-test. (c) and (g) middle line: median; box edges: 25th and 75th percentiles, whiskers: most extreme points that do not exceed ±IQR*1.5; further outliers are marked individually. h, Prognostic value of T cell levels in different tumor types. Kaplan-Meier (KM) curves of survival in melanoma (left; TCGA), sarcoma (middle)21, and SyS20 (right), stratified by high (top 25%, red), low (bottom 25%, blue), or intermediate (remainder, green) levels of inferred T cell infiltration levels; P: COX regression. (i) Protein expression (CyCIF) of core oncogenic program markers in immune-enriched and deprived niches.
Extended Data Fig. 5 Characterizing the transcriptional impact of SS18-SSX inhibition and tumor microenvironment cytokines on SyS cells.
a, The fusion KD induces cell autonomous immune programs. Distribution of Overall Expression scores (y axis) in the pathways most differentially expressed between SyS cells with SS18-SSX (shSSX, grey) vs. control (shCt, blue) shRNA, shown separately for non-cycling and cycling cells (x axis). b, Co-embedding (using PCA and canonical correlation analyses81, Methods) of Aska (top) and SYO1 (bottom) cell profiles (dots), colored by (from left to right): perturbation; or the Overall Expression (colorbar) of the cell cycle, core oncogenic, or mesenchymal differentiation31,32 programs. c, Biological processes regulated in the SS18-SSX program. Gene sets (columns) most enriched (-log10(P-value), hypergeometric test, x axis) in the induced (left) and repressed (right) SS18-SSX program genes, which are either direct (black bars) or indirect (grey bars) targets of SS18-SSX based on ChIP-Seq data16,17 and genetic perturbation. Vertical line denotes statistical significance following multiple hypotheses correction. d, The SS18-SSX program distinguishes SyS from other cancer types and other sarcomas. Overall Expression of the SS18-SSX program (y axis) in either TCGA samples (n = 9,391, top), stratified by cancer types (x axis), or in another independent cohort of sarcoma tumors (n = 164, bottom)58. Middle line: median; box edges: 25th and 75th percentiles, whiskers: most extreme points that do not exceed ±IQR*1.5; further outliers are marked individually. **P < 0.01, ***P < 1*10−3, ****P < 1*10−4, one-sided t-test. e, Repression of the core oncogenic and SS18-SSX programs by short term TNF treatment is not sustained long term. Distribution of Overall Expression scores (y axis) of the core oncogenic program and the direct and indirect SS18-SSX programs (x axis) in control cells (blue) and cells treated with TNF for 4-6 hours (left) or more than 24 hours (right).
Extended Data Fig. 6 HDAC and CDK4/6 inhibitors synergistically repress the core oncogenic program and induce cell autonomous immune responses.
a, The fraction of viable, necrotic, and apoptotic cells, showing four different SyS cell lines. (b-d) Distribution of the expression (y axis) of core oncogenic genes (b), as well as the Overall Expression of TNF (c) and IFN (d) signaling pathways in SyS cells and MSCs (x axis) under different treatments (color legend; n = no. of SYO1, HSSYII, and MSC cells). Middle line: median; box edges: 25th and 75th percentiles, whiskers: most extreme points that do not exceed ±IQR*1.5; further outliers are marked individually. **P < 0.01, ***P < 1*10−3, ****P < 1*10−4, one-sided t-test. e, Workflow of the co-culture CME-1-T-cell experiment. f, HLA-A2 and HLA-E protein levels on the cell surface of CME-1 cells under different treatments. g, Standard, FSC vs. SSC gating was performed followed by strict FSC-width vs. FSC-area criteria to discriminate doublets and gate only single cells. Top: Singlets were gated upon the CD3- population to clearly identify the tumor cell population. The percentage of Zombie-UV+ cells were determined on the CD3- population. Bottom: Singlets were gated upon the Zombie-UV- (live) CD3+ population to identify the viable T cell population.
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Jerby-Arnon, L., Neftel, C., Shore, M.E. et al. Opposing immune and genetic mechanisms shape oncogenic programs in synovial sarcoma. Nat Med 27, 289–300 (2021). https://doi.org/10.1038/s41591-020-01212-6
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