Soft-tissue sarcomas represent a heterogeneous group of cancer, with more than 50 histological subtypes1,2. The clinical presentation of patients with different subtypes is often atypical, and responses to therapies such as immune checkpoint blockade vary widely3,4. To explain this clinical variability, here we study gene expression profiles in 608 tumours across subtypes of soft-tissue sarcoma. We establish an immune-based classification on the basis of the composition of the tumour microenvironment and identify five distinct phenotypes: immune-low (A and B), immune-high (D and E), and highly vascularized (C) groups. In situ analysis of an independent validation cohort shows that class E was characterized by the presence of tertiary lymphoid structures that contain T cells and follicular dendritic cells and are particularly rich in B cells. B cells are the strongest prognostic factor even in the context of high or low CD8+ T cells and cytotoxic contents. The class-E group demonstrated improved survival and a high response rate to PD1 blockade with pembrolizumab in a phase 2 clinical trial. Together, this work confirms the immune subtypes in patients with soft-tissue sarcoma, and unravels the potential of B-cell-rich tertiary lymphoid structures to guide clinical decision-making and treatments, which could have broader applications in other diseases.
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The transcriptomic datasets analysed in this study can be accessed on the GDC Portal (portal.gdc.cancer.gov, cohort TCGA SARC) and the GEO repository under accession numbers GSE21050, GSE21122 and GSE30929. FSG cohort data are publicly available from ArrayExpress for gastrointestinal stromal tumour with accession code E-MTAB-373, and from the GEO for synovial sarcomas with accession number GSE40021. Myxoid liposarcomas from the FSG cohort are available from the corresponding authors upon reasonable request. Immunohistochemistry and gene expression data related to the NTUH cohort (Fig. 3, Extended Data Figs. 7, 8) are available upon reasonable request to W.H.F. (email@example.com). The data that support the findings related to Fig. 4 are available from SARC but restrictions apply to the availability of these data, which were used under license for the study. Data are, however, available from H.A.T. (firstname.lastname@example.org) upon reasonable request and with permission of SARC.
All code used in this study is available from the corresponding author upon reasonable request.
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This work was supported by the Institut National de la Santé et de la Recherche Médicale, the Université de Paris, Sorbonne University, the Programme Cartes d’Identité des Tumeurs (CIT) from the Ligue Nationale Contre le Cancer, grants from Institut National du Cancer (HTE-INSERM plan cancer, C16082DS), Association pour la Recherche sur le Cancer (ARC), Cancer Research for Personalized Medecine programme (CARPEM T8), French Sarcoma Group, the European Connective Tissue Cancer Network (CONTICANET, FP6-018806), ‘FONCER contre le cancer’ programme, Labex Immuno-Oncology (LAXE62_9UMRS972 FRIDMAN), the National Institutes of Health (E.Z.K. is supported by T32CA0095999) and the Moon Shot program at MD Anderson Cancer Center. Grants from the Ministry of Education (NTU-107L9014) and Ministry of Science and Technology (MOST 107-3017-F-002 -002-), Taiwan and from the National Taiwan University (YongLin Chair Grant S-01 and S-03) also supported this study. SARC028 was jointly funded by Merck, Inc., SARC, Sarcoma Foundation of America, and the QuadW Foundation. F.P. supported by CARPEM doctorate fellowship. C.L.R. is recipient of the Paul Calabresi Clinical Oncology Award (K12 CA088084). The slides stained for immunofluorescence were scanned and analysed at the Centre d’Histologie, d’Imagerie et de Cytométrie (CHIC), Centre de Recherche des Cordeliers UMRS1138 (Paris, France). CHIC is a member of the Sorbonne University Flow Cytometry Network (RECYF). We thank C. Klein, K. Garbin and E. Devevre for their support with the imaging. The Nanostring analysis of the NTUH core cohort was performed by the Plateforme Génomique of the Institut Curie (Paris, France). We thank D. Gentien and E. Henry for their support. We acknowledge the help of H. Yan and B. Singh.
W.H.F. is a consultant for AstraZeneca, Novartis, Servier and Pierre Fabre. A.I. serves in the advisory board of Bayer, Daiichy, Epizyme, Lilly, Novartis, Roche and Springworks, and received research funding from Astra Zeneca, Bayer, Chugai, Merck, MSD, Novartis and Pharmamar. J.A. is a consultant for AstraZeneca, Bayer, BMS, MSD and Roche and received research funding from MSD, Pfizer and Pierre Fabre. J.A.W. participated on advisory boards for Merck, BMS, Novartis, Astra Zeneca, Roche Genentech and Illumina. M.A.B. is a consultant for EMD Serono, Immune Design, Eisai. H.A.T. serves on advisory boards and receives consulting fees from BMS, Merck and Genentech, and received research funding from BMS, Merck, Celgene, GSK, and Genentech. T.W.-W.C. participated in advisory boards for Eisai and Lilly and received research funds from Eisai. C.L.R. received research funding from BMS. The other authors declare no conflict of interest.
Peer review information Nature thanks Naiyer Rizvi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data figures and tables
a, Repartition of the SICs in various histologies of TCGA SARC and GSE21050 (LMS, UPS and DDLPS), and FSG cohort (synovial sarcoma, myxoid liposarcoma, gastrointestinal stromal tumour (GIST)). b, Survival of patients from the FSG cohort (n = 136) according to SIC classification. Patients with synovial sarcoma, myxoid liposarcoma and gastrointestinal stromal tumour were pooled. Analysis was performed with Kaplan–Meier estimates and two-sided log-rank tests.
This figure refers to the GSE21050 cohort (n = 283). a, Composition of the GSE21050 cohort by SIC, histology and site of disease. b, Composition of the TME by SIC as defined by the MCP-counter Z-scores. c, Expression of gene signatures related to the functional orientation of the immune TME by SIC. d, Expression of genes related to immune checkpoints by SIC. Adjusted P values are obtained from Benjamini–Hochberg correction of two-sided Kruskal–Wallis test P values. These observations stand for cohorts GSE21122 and GSE30929 (not shown).
a–e, MCP-counter scores in TCGA SARC (n = 213) (a, c, e) and GSE21050 (n = 283) (b, d, e), for CD8+ T cells (a, b), cytotoxic lymphocytes (c, d) and B lineage cells (e, f). The blue line indicates the density curve. The red dotted line indicates the cut-off chosen to segregate high or low values, set at the median for CD8+ T cells and at the third quartile for cytotoxic lymphocytes and B lineage, in each cohort. These values were chosen because the CD8 T cells scores present a normal distribution, whereas the cytotoxic lymphocytes and B lineage scores distribution exhibit a long right tail.
This figure refers to TCGA SARC and GSE21050 pooled cohorts (n = 496). a, Overall survival of patients with STS according to MCP-counter scores for cytotoxic lymphocytes. b, Overall survival of patients based on the infiltration level of their tumours by B lineage cells and cytotoxic lymphocytes. c–e, Overall survival of patients based on degree of tumour infiltration by B lineage cells and expression of PDCD1 (c), CD274 (d) and FOXP3 (e). The analyses were performed with the Kaplan–Meier estimates and two-sided log-rank tests. Tumours were considered high for expression of PDCD1, CD274 and FOXP3 if their expression was above median, and high for B lineage and cytotoxic lymphocytes if the MCP-counter score was above the third quartile.
Extended Data Fig. 6 The mutational landscape of STS tumours does not vary significantly between SICs.
This figure refers to the TCGA SARC cohort (n = 213). a, Mutational burden according to the SIC of the tumours, expressed in number of non-silent mutations. P value was computed with a Kruskal–Wallis test. Box plots as in Fig. 3d. b, Mutation frequency of all genes that are mutated in greater than 2.5% of tumours. c, Mutation frequency for genes that are mutated in more than 5% of tumours, according to SICs in the TCGA SARC cohort. The dashed lines indicate the overall mutation frequency. P values were obtained through one-sample two-sided t-tests, corrected for multiple testing with the Bonferroni method. This was applied only to samples that had mutations on the considered genes (TP53: n = 75; ATRX: n = 34; TTN: n = 21; RB1: n = 19; MUC16, n = 17; PCLO, n = 13; DNAH5, MUC17 and USH2A: n = 11, PTEN, n = 6; KRAS, n = 2; BRAF, n = 1).
This figure refers to the NTUH cohort. a, SIC attribution as defined by gene expression using the MCP-counter Z-scores in 73 cases. b, Cell density counts showing the differences in TME composition according to SIC identification of the 73 cases (SIC A: n = 16; SIC C: n = 10; SIC E: n = 11). P values are determined by two-sided Kruskal–Wallis (KW) tests. Pairwise comparisons are derived from the Dunn test. Box plots are as in Fig. 3d. c, Representative images of CD3 (green), CD20 (pink), CD8 (brown) and CD34 (green) expression by immunohistochemistry of SIC A, C and E tumours. The same area of the tumour is represented (0.05 mm2) in each image. Similar results were observed on the other tumours from the same SICs (SIC A: n = 16; SIC C: n = 10; SIC E: n = 11).
a, Pearson correlation between the expression of CXCL13 and the 12-chemokine signature of TLS in TCGA SARC cohort (n = 213). Samples are coloured according to SICs. b, Intratumoural location of TLSs in three different examples from the NTUH cohort—DDLPS, UPS and LMS, respectively. TLSs are observed by the presence of CD20+ B cells aggregates (brown, surrounded by blue shapes). The red line delineates the tumoral zone. Similar findings were observed on the 11 tumours with TLS. c, Definition of peripheral, medium and central zones, accounting for 25%, 25% and 50% of the total tumour area, respectively. d, Distribution of TLSs in the various zones. Each bar represents one tumour. The letters above bars indicate the SIC of the tumour when the sample passed quality control of Nanostring nCounter hybridization. Dots indicate tumours in which SIC could not be determined because of RNA quality control. Similar images were observed for 66 E-TLS, 23 PFL-TLS and 20 SFL-TLS. e, Illustration of diverse degrees of TLS maturation in STS tumours. Consistent with maturation events occurring in secondary lymphoid organs, three maturation steps have been described for TLS: E-TLS (bottom), PFL-TLS (middle) and SFL-TLS (top), which differ in the presence of follicular dendritic cells (FDC) and their markers. E-TLS contain aggregates of CD20+ B cells and CD3+ T cells without FDC, PFL-TLS contain CD21+ FDC (red dotted zones) and SFL-TLS contain a germinal centre, notably visible through the presence of CD21+CD23+ follicular dendritic cells (yellow dotted zone). DAPI staining is shown in white. DAPI-negative green dots correspond to fluorescent erythrocytes. f, Distribution of TLS maturation steps in a subset of tumours. Each bar represents one tumour. Differences between the number of TLSs observed here and in other figures can be explained by use of non-consecutive slides or a different tumour block for some samples.
This figure refers to the four discovery cohorts: TCGA SARC (n = 213), GSE21050 (n = 283), GSE21122 (n = 72) and GSE30929 (n = 40). a–d, Heat map and unsupervised hierarchical clustering of the MCP-counter scores describing the tumour microenvironment. Each of the population is represented by the Z-scores of the signature. a, TCGA SARC. b, GSE21050. c, GSE21122. d, GSE30929. e–h, Evolution of the variance explained by the clusters as a function of the number of clusters. Red dots indicate the number of clusters that was retained in this study. Each graph corresponds to the heat map on its left. i, Heat map of the Pearson correlation of centroids from each SIC class of discovery cohorts (TCGA SARC, GSE21050, GSE21122 and GSE30929, n = 608), with five immune classes and two groups of unclassified samples. j, k, Principal component analysis of samples from the four discovery cohorts (n = 608), based on their normalized and merged MCP-counter scores. j is coloured according to the original classes, k is coloured according to the predicted immune classes, showing a heightened homogeneity within each SIC class. l, m, Composition of the TME with classes defined as in j and k for the four discovery cohorts (n = 608), expressed in cohort-specific row Z-scores.
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Petitprez, F., de Reyniès, A., Keung, E.Z. et al. B cells are associated with survival and immunotherapy response in sarcoma. Nature 577, 556–560 (2020). https://doi.org/10.1038/s41586-019-1906-8
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