BackgroundBody composition has a significant impact on the prognosis of cancer patients. However, little is known about its impact on the efficacy and safety of antibody–drug conjugates (ADCs), despite the need for accurate patient profiling to ensure reliable safety data and early signals of activity.MethodsAll patients treated with ADCs in early-phase clinical trials between March 2015 and March 2023 in our institution were retrospectively included in the analysis. Pre-treatment injected CT scans were acquired for all patients. A deep learning software, Anthropometer3DNet, automatically quantified anthropometric parameters in three dimensions (3D) on the acquired CT scans: skeletal muscle mass (SMM), total adipose tissue (TAT), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and lean body mass (LBM). The effect of these anthropometric parameters on progression-free survival (PFS), overall survival (OS), and time in protocol (TIP) was analyzed.ResultsA total of 136 patients were included. The median age, Eastern Cooperative Oncology Group Performance Status (ECOG PS), albumin, and number of previous lines of treatment were respectively 60.8 years (30 to 85), 1 (0–2), 42 g/L [interquartile range (IQR): 39–44], and 3 (IQR: 0–2). The median PFS and OS were 2.6 and 7.9 months, respectively; 90 (66%) patients had experienced toxicity (of which 46 were grade 3–5). Univariate analyses showed that higher SAT [hazard ratio (HR) = 0.67, p = 0.03] and TAT (HR = 0.60, p = 0.01) were significantly associated with longer PFS [median PFS (mPFS) = 2.76 vs. 2.3 and 2.76 vs. 1.9, respectively]. Higher SAT (HR = 0.66, p = 0.04) and higher VAT (HR = 0.65, p = 0.04) were significantly associated with longer OS [median OS (mOS) = 9.34 vs. 7.43 months and 9.27 vs. 6.08 months, respectively]. Higher TAT was associated with longer TIP in both univariate and multivariate analyses (HR = 0.56, p = 0.006). A Royal Marsden Hospital (RMH) prognostic score of 2 or more was associated with PFS, OS, and TIP in both univariate and multivariate analyses (HR = 1.78, 1.89, and 1.74, respectively). All anthropometric parameters were significantly associated with all-grade toxicity in the univariate analysis but not in the multivariate analysis.ConclusionsAutomatic extraction of body composition parameters using artificial intelligence (AI) may help in anticipating the benefits of ADCs in patients included in early-phase clinical trials. Combining anthropomorphic data with clinical and biological data may lead to more refined patient selection.

BACKGROUND:Alveolar soft part sarcoma (ASPS) is an ultra-rare sarcoma with limited chemotherapy sensitivity affecting mostly young patients. Tyrosine kinase inhibitors (TKIs) and immunotherapy are therapeutic advances with promising results in this disease. The aim of this study was to describe the characteristics, management and survival of patients with ASPS in France. PATIENTS AND METHODS:The French NETSARC+ database was screened for all adult patients with ASPS managed in French sarcoma centers between 2010 and 2023. RESULTS:Sixty-four patients from 18 centers were analyzed. The 5-year overall survival (OS) of the entire cohort was 87.3 % (95 % CI, 75.0-93.8 %). Fifty-six percent of patients had localized tumors at diagnosis; all were treated surgically, and 47 % received perioperative radiotherapy. With a median follow-up of 91 months, their 5-year OS was 96.3 % (95 % CI, 76.5-99.5 %). Half of the patients experienced metastatic recurrence with a median metastasis-free survival of 87.9 months (95 % CI, 29.6-NE). In patients with metastases, the first-line systemic treatment yielded an overall response rate of 7 %, 26 %, and 40 % for chemotherapy, TKIs, and immunotherapy, respectively. The 5-year OS after metastasis diagnosis was 67.7 % (95 % CI: 50.5-80.0 %). CONCLUSION:Our cohort reinforces existing data on clinical characteristics and demonstrated prolonged survival in both localized and metastatic stages. Among systemic treatments, immunotherapy achieved the highest response rates. We confirmed that ASPS may follow an indolent course in some cases and highlighted recent advances in its management, driven by standardized local treatments in reference centers and innovative systemic therapies.

Supplementary File containing methods, figures and uncropped membranes.

Poly (ADP-ribose) polymerase inhibitors (PARPi) have immunomodulatory properties that may potentiate anti-PD-L1 therapy. The academic phase 2 basket trial ARIANES evaluated the PARPi rucaparib (R) and anti-PD-L1 atezolizumab (A) in selected patients (pts). We performed single-cell RNA + T-cell receptor sequencing (scRNA+TCR-Seq) and bulk RNA-Seq on sequential tumor biopsies, concomitant plasma proteomics, and whole exome sequencing in a pt subset. ARIANES included 4 molecularly selected DNA damage response deficient (DDRd), 3 platinum-sensitive, and 2 unselected cohorts of pts with non-breast non-ovarian cancers. R was administered for 3 weeks followed by R+A. Primary endpoint was overall response rate (ORR) by RECISTv1.1 at 12 weeks per cohort. Bulk and scRNA+TCR-Seq were performed on biopsies collected at baseline (B), on R, and on R + A in the same lesion. We used partial least squares discriminant analysis to integrate multi-omics and identify pathways associated with response. We tracked the evolution over time of tumor and microenvironment cells, differentially expressed genes and signatures within each cell population, and TCR clonal dynamics. ARIANES enrolled 130 pts, including 27 DDRd mCRPC pts. In the latter, ORR was 22% (6/27) by PCWG3-mRECISTv1.1, and mPFS (modified Progression Free Survival) 6.7 months (95% CI 2.7 - 11.1) at data cut-off. High-quality profiling data were obtained for 41 samples (17 pts) and 16 samples (6 pts) by bulk and scRNA+TCR-Seq, respectively. When focusing on bulk RNA-Seq data of pts with clinical benefit (CB, i.e. response or PFS > 6 months; n = 4, 3, 3 at B, on R, on R+A, respectively) vs pts with no CB (NCB, n = 10, 8, 12 at B, on R, on R+A, respectively), we found that 7/23 pathways significantly enriched on R+A were related to innate immunity (including IL6_JAK_STAT3 and INFa signaling), whereas DNA_REPAIR and MITOTIC_SPINDLE were significantly downregulated. At the gene level, FANCA, HJURP and RAD54L were downregulated on R+A, whereas ZBP1 was downregulated on R and R+A. scRNA-Seq of a BRCA2-mutant mCRPC pt with prolonged PR (Partial Response) consistently showed gradual increase on R and R+A of cGAS-STING innate immune sensing and JAK/STAT pathways activation, both in tumor and immune cells, together with CCL5 expression; scTCR-Seq revealed the expansion of specific T-cell clonotypes on R + A. This was not observed in progressing patients. Multi-omics analysis on sequential pts samples reveals that R displays immunomodulatory properties in pt tumors and confirms the potential of (i) R to activate innate immune pathways in tumor cells, and (ii) R + A to induce T-cell activation and clonal expansion. To our knowledge, this is the first study providing a longitudinal and multi-omics bulk/sc resolution analysis of evolution of tumor and immune cells in pts on PARPi and PARPi + anti-PD-L1. Thibault Thomas-Bonafos, Julien Vibert, Arnaud Pagès, Léo Colmet-Daage, Roman Chabanon, Aurore Jeanson, Lambros Tselikas, Marlène Garrido, Clémence Hénon, Aurélien Parpaleix, Marianne Chasseriaud, Alice Bernard-Tessier, Nicolas Dorvault, Baptiste Bonnet, Clémence Astier, Anas Gazzah, Ronan Flippot, Natacha Naoun, Anna Patrikidou, Pernelle Lavaud, Aline Fuerea, Laurence Albiges, Yohann Loriot, Stéphane Champiat, Capucine Baldini, Fanny Bouquet, Nathalie Droin, Karim Fizazi, Damien Vasseur, Christophe Massard, Etienne Rouleau, Patricia Martin-Romano, Kaissa Ouali, Sophie Postel-Vinay. Clinical and translational results of the academic ARIANES Phase 2 basket study: Longitudinal bulk and single-cell RNAseq analyses of patient tumors identify biological correlates of response to PARP inhibitors and anti-PD-L1 therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr CT089.

PARPi and ATRi have synergistic cytotoxic effects in models of DSRCT with high PARP1 expression. A and B, PARP1 expression (A) and PARylation levels (B) as assessed by IHC in a cohort of 16 DSRCT samples, compared with those of the JN1 and R cell lines (PARP1 and PAR expression levels are shown as H-scores). Representative cases (PARP1-high vs. PARP1-low tumors; PAR-high vs. PAR-low tumors) are shown to the right, compared with JN1 and R cells. C and D, Surface plots of Bliss independence scores calculated for the talazoparib–M4344 combination in JN1 (C) and R (D) cell lines at 7 days. E, The GR_13-PDX-O model was established from the primary peritoneal tumor of a patient with DSRCT, with confirmation of EWSR1::WT1 fusion by FISH and WT1-Cter IHC (Supplementary Fig. S8). F, Surface plot of Bliss independence scores calculated for the talazoparib–M4344 combination in the GR_13 PDX-O at 7 days. Mean ± SD; n = 3. Surface plots: the x-axis and y-axis values indicate drug concentrations, and the z-axis values indicate the associated synergy score; score < −10, antagonistic interaction; score = 0, absence of interaction; score > 10, synergistic interaction. G, Schematic illustration of an in vivo therapeutic experiment performed to evaluate the antitumor effect of PARPi talazoparib and ATRi M1774 in NSG mice engrafted with JN1 xenografts. H, Therapeutic responses to drug treatment in mice harboring JN1 xenografts. Mean tumor volume ± SD; two-way ANOVA and post hoc Dunnett test. I, Tumor volume at the time of mice sacrifice. Mean ± SD; one-way ANOVA and post hoc Šídák test. *, P < 0.01; ns, not significant. Tala, talazoparib.

Background:Liposarcomas (LPS) are among the most common sarcomas, but gather a diversity of rare to ultrarare molecular subtypes whose presentations and natural histories are partially characterized. The aim of the work was to describe the presentation and outcome of the different LPS histotypes from the NETSARC+ registry. Methods:NETSARC+ (netsarc.org) is a network of 26 reference sarcoma centers with specialized multidisciplinary tumor boards (MDTB), funded by the French INCA since 2010 aiming to improve the quality of care of sarcoma patients. Patients' characteristics, treatment and outcomes are collected in a nationwide database. This work describes the outcome of all LPS confirmed by central review pathology review and integrated between 2010 and 2023 in the NETSARC+ database. Findings:11,132 liposarcomas are included in the database for an estimated incidence of 11.5/106/y. Median age was 65 (Q1-Q3: 53-74, range 0-97 y), with 6529 males (58.7%), with 4220 (37.9%) dedifferentiated (DDLPS), 1838 (16.5%) well differentiated LPS (WDLPS) & 2424 (21.8%) atypical lipomatous tumours (ALT), 1371 (12.3%) myxoid LPS (MyxLPS), 450 (4.0%) pleomorphic LPS (PLPS), 177 (1.6%) high grade myxoid LPS (HGMLPS), 24 (0.2%) mixed type liposarcomas (MTLPS), 14 (0.1%) myxoid pleomorphic LPS (MPLPS) and 614 (5.5%) non classified LPS (NCLPS). Age, sex and sites differed across histotypes, but overall, all histotypes were represent in all age groups and sites. We report first on a difference in the sex ratio of liposarcoma in different age groups. Women were less frequently affected with liposarcomas after 50, in DDLPS, MyxLPS and HGMLPS. The median overall survival of DDLPS was 144 months, significantly worse than that of MyxLPS (HR: 0.26 [95% CI 0.21-0.33]), PLPS (HR: 0.76 [95% CI 0.59-0.98]), HGMLPS (HR: 0.30 [95% CI 0.18-0.50]), WDLPS (HR: 0.30 [95% CI 0.24-0.37]), unclassified LPS (HR: 0.53 [95% CI 0.37-0.75]). In addition to a lower incidence, women aged >50 had a better relapse free and overall survival than male, while this was not observed in the group aged 50 or under. In multivariate analyses, size and age were independent prognostic factors for the most common subgroups, but specific prognostic parameters were observed in each molecular subgroup. Female >50 was an independent favorable prognostic factor for the largest groups of DDLPS. Interpretation:In this nationwide series of pathology-confirmed LPS, the clinical presentation, management and survival of histotypes are very different with age-related sex differences favoring women >50. DDLPS is the subtype with the worse prognosis. Funding:This work was supported by the following grants: NetSARC+ (INCA), RREPS (INCA), RESOS (INCA), INTERSARC+ (INCA), LabEx DEvweCAN (ANR-10-LABX-0061), LYriCAN+ (INCa-DGOS-INSERM-ITMO cancer_18,003), Ligue Nationale contre le Cancer, Ligue Contre le Cancer (Comité de l'Ain), Fondation ARC, and EURACAN (EU project 739521).

Tenosynovial giant cell tumor is a non-malignant primary locally aggressive articular disease that affects the synovium of joints, tendon sheaths, and bursae. It is characterized by a translocation t (1;2), leading to the overexpression of CSF1 in the tumor microenvironment. CSF1 induces the recruitment of non-malignant cells, mainly macrophages, followed by the differentiation and polarization of these cells into the M2 phenotype. Surgery, particularly total synovectomy, remains the cornerstone of TGCT management. However, recurrence rates vary, reaching 40 to 60% in diffuse disease, often resulting in progressive joint dysfunction, pain, and potential need for joint replacement or limb amputation. Systemic therapy is recommended in recurrent TGCT in patients not amenable to additional surgery. Targeting the CSF1/CSF1R axis has successfully improved tumor responses and enhanced symptomatic function. In this review, we aim to explore contemporary paradigms in inoperable TGCT patients, with a focus on the physiopathology, clinical efficacy, and safety of CSF1 or CSF1R inhibitors.

Desmoplastic small round cell tumor (DSRCT) is an aggressive cancer that predominantly affects adolescents and young adults, typically developing at sites lined by mesothelium [1, 2]. DSRCT is genetically defined by a chromosomal translocation that fuses the N-terminus of EWS RNA binding protein 1 (EWSR1) to the C-terminus of Wilms tumor protein (WT1), forming EWSR1::WT1 [3]. This fusion encodes a potent transcription factor and is the only known driver of oncogenic transformation in DSRCT [4]. The lack of a comprehensive understanding of DSRCT biology parallels its dismal survival rate (5%-20%) [1]. These challenges are exacerbated by the absence of clinical trials, the limited systematic collection and analysis of DSRCT biomaterial [1], and the notable lack of specific diagnostic markers, necessitating resource-intensive molecular testing for an accurate diagnosis. Here we first focused on identifying promising candidates for validation as single, fast, and reliable diagnostic DSRCT markers. For this, we performed differential gene expression (DEG) analysis on datasets comprising patient samples from 32 DSRCT and 20 morphological mimics, identifying 23 genes overexpressed in DSRCT (log2 fold change (log2FC) > 2.5; adjusted P-value (Padj) < 0.01; Figure 1A, Supplementary Figure S1A). Secondly, we analyzed EWSR1::WT1 binding sites derived from chromatin immunoprecipitation followed by sequencing (ChIP-seq) data [5] obtained from the JN-DSRCT-1 cell line, identifying 2,065 genomic loci likely regulated by EWSR1::WT1 (Figure 1A). Third, we established JN-DSRCT-1 and SK-DSRCT2 cell lines expressing doxycycline (DOX)-inducible short hairpin RNA (shRNA)-mediated EWSR1::WT1 knockdown (KD) (Supplementary Figure S1B). Differential protein expression (DEP) analysis of these cells identified 104 proteins consistently regulated across both cell lines (log2FC > 1.0 and Padj < 0.01; Figure 1A, Supplementary Table S1). The intersection of these analyses revealed calcium voltage-gated channel auxiliary subunit alpha2delta 2 (CACNA2D2) and IQ motif containing G (IQCG) as potential DSRCT biomarkers (Figure 1A). CACNA2D2 was selected for validation due to its significantly higher expression in DSRCTs compared to IQCG (P < 0.001; Figure 1A). Indeed, DSRCT exhibited the highest expression of CACNA2D2 among all studied morphological mimics and normal tissues (P < 0.001; Supplementary Figures S1C-D). Further ChIP-seq data and motif analyses of EWSR1::WT1 binding coordinates and histone marks in JN-DSRCT-1 and four DSRCT patient samples [5, 6] suggested a direct regulatory role of EWSR1::WT1 through an enhancer interaction at the CACNA2D2 locus (Figure 1B). Notably, KD of EWSR1::WT1 in JN-DSRCT-1 resulted in a loss of the EWSR1::WT1 signal and Histone H3 lysine 27 acetylation (H3K27ac) enhancer marks at the CACNA2D2 locus (Figure 1B). Additionally, chromatin interaction data [6] revealed 19 loops connecting the EWSR1::WT1 binding site to the transcription start site of CACNA2D2, which were depleted upon KD of EWSR1::WT1 (Figure 1C). Super enhancer (SE) analysis further demonstrated that the EWSR1::WT1-bound enhancer exhibited a characteristic SE H3K27ac profile in JN-DSRCT-1, which was lost upon EWSR1::WT1 KD (Figure 1D, Supplementary Table S2). Post-transcriptional and post-translational KD of EWSR1::WT1 in three DSRCT cell line models expressing different EWSR1::WT1 isoforms (Supplementary Figure S2A) resulted in a significant reduction in CACNA2D2 expression (Figures 1E–F, Supplementary Figure S1B, Supplementary Figures S2B–F). Additionally, ChIP-seq data derived from MeT-5A mesothelial cells [6] – the potential cell of origin of DSRCT [7, 8] – ectopically expressing different EWSR1::WT1 isoforms (-KTS, +KTS, or -KTS/+KTS) suggested direct regulation, as evidenced by the co-occurrence of H3K27ac signals and signals for V5- or HA-tagged EWSR1::WT1 isoforms at the CACNA2D2 enhancer region (Supplementary Figure S2G). Notably, MeT-5A cells transfected with a control vector showed no substantial signal at this locus (Supplementary Figure S2G). Publicly available RNA-sequencing (RNA-seq) data from MeT-5A cells [6] expressing different EWSR1::WT1 isoforms showed that CACNA2D2 was differentially expressed in the presence of EWSR1::WT1 (4.1 ≤ log2FC ≤ 5.9, Padj < 0.001) (Supplementary Figure S2H). Finally, quantitative polymerase chain reaction (qPCR) analysis of MeT-5A cells stably expressing a DOX-inducible ectopic EWSR1::WT1 expression cassette confirmed that upon EWSR1::WT1 induction, CACNA2D2 was significantly and highly overexpressed (Supplementary Figure S2I). Taken together, these results emphasize that EWSR1::WT1 is sufficient to drive CACNA2D2 expression. SE analysis of MeT-5A-derived data strikingly showed that the CACNA2D2 enhancer bound by EWSR1::WT1 became a SE upon ectopic expression of EWSR1::WT1− KTS + KTS (Supplementary Figure S2J). To explore whether CACNA2D2 could serve as a surrogate indicator of oncogenic EWSR1::WT1 transformation, we defined a CACNA2D2 gene set and gene signature by performing a correlation analysis of gene expression data from 32 DSRCT patient samples (Supplementary Figure S3A, Supplementary Tables S3-S4). Next, an EWSR1::WT1 signature was computed by performing a combined DEG analysis of newly generated in vivo and in vitro [4] material derived from three DSRCT cell lines upon EWSR1::WT1 KD (Supplementary Figure S3A, Supplementary Table S4). Notably, fast gene set enrichment analysis (fGSEA) of the CACNA2D2 gene set demonstrated a highly significant (Padj < 0.001) and strong positive enrichment for the EWSR1::WT1 signature (normalized enrichment score, NESEWSR1::WT1 = 3.6). Moreover, single sample gene set enrichment analysis (ssGSEA) of expression data from 32 DSRCT patient samples confirmed that the EWSR1::WT1 signature significantly correlated with that of CACNA2D2 (r = 0.75), highlighting a transcriptional interconnection between CACNA2D2 and EWSR1::WT1 in situ (Figure 1G). These observations were further supported by single-cell (sc)-derived signatures from orthotopically-generated tumors using two DSRCT cell lines with DOX-inducible KD of EWSR1::WT1 at primary (n = 221) and metastatic (n = 221) locations (Figure 1G, Supplementary Table S4). Indeed, ssGSEA of our single-cell data showed highly significant correlation between the NES of our generated EWSR1::WT1 and CACNA2D2 signatures (Figure 1G), regardless of tumor location, implying that CACNA2D2-associated genes are also characteristic features of metastasized DSRCT cells (Supplementary Figure S3B). To delineate the specificity of the interaction between CACNA2D2 and EWSR1::WT1 in DSRCT, we performed ssGSEA using our EWSR1::WT1 and CACNA2D2 signatures on expression data from 20 DSRCT morphological mimics (Figure 1H). Here, non-DSRCT cancer entities showed significantly lower NES and correlation strength for all signatures compared to DSRCT (Supplementary Figures S3C-D). These results further emphasized the high specificity of the CACNA2D2 and EWSR1::WT1 interplay in DSRCT. Moreover, both bulk- and sc-derived CACNA2D2 signatures precisely distinguished DSRCT cell clusters from non-tumor cells in single-cell RNA-sequencing (scRNA-seq) data from four DSRCT patients (n = 11 samples) [9] (Figure 1I, Supplementary Figure S3E). Concordantly, all predicted normal cell types within these tumors exhibited low enrichment of both CACNA2D2 signatures (Supplementary Figures S3F-G). Further, dimensional reduction of CACNA2D2-associated CpG sites in 24 DSRCT patient samples, compared with 192 samples from 13 morphological mimics [10] revealed distinct clustering of all DSRCT samples, which was unique to CACNA2D2 compared to other described EWSR1::WT1-regulated genes or IQCG (Figure 1A, Supplementary Figures S4A-B). Additionally, these CACNA2D2-associated CpG sites exhibited significant (P < 0.001) and specific hypomethylation in DSRCT patient samples, collectively suggesting that the CACNA2D2-associated methylation signature is a distinct and specific feature of DSRCT (Supplementary Figure S4C). To assess the diagnostic utility of CACNA2D2, we optimized a staining protocol for DSRCT cell line xenografts, achieving consistent and robust membranous or cytoplasmatic staining, even uncovering micrometastases (Figure 1J, Supplementary Figure S4D). Finally, we assembled the largest collection of fresh-frozen and paraffin-embedded DSRCT patient samples analyzed to date (n = 61), comprising primary, metastatic, and post-treatment samples, and supplemented it with 249 patient samples from 18 different DSRCT morphological mimics (Supplementary Table S5). CACNA2D2 immunoreactivity was evaluated using a modified Immune Reactive Score (IRS) (Supplementary Material and Methods). Excitingly, DSRCT tumor sections exhibited the highest IRS for CACNA2D2 (IRSmean = 10.5, 6 ≤ IRSDSRCT ≤ 12, P < 0.001) (Supplementary Figure S4E-F), with specificity reaching 98% when applying a cutoff of IRS > 1 (Figure 1K-M, Supplementary Figure S4E). Indeed, even samples derived from CIC- and BCOR-rearranged sarcomas, as well as fusion-positive alveolar rhabdomyosarcomas, showed negligible mean protein expression compared to DSRCT (IRSCIC = 0.21, IRSBCOR = 0, IRSfp-ARMS = 0.56). Furthermore, 100% sensitivity was achieved when applying an IRS cutoff of ≤ 6, implying that DSRCT samples consistently displayed strong staining for CACNA2D2 (Figure 1M). Thus, we recommend a single CACNA2D2 staining for clinically and histologically compatible DSRCT differential diagnosis. If IRSCACNA2D2 ≤ 1, the diagnosis should be reconsidered or re-evaluated using molecular diagnostic procedures (such as fluorescence in situ hybridization, qRT-PCR, or next-generation sequencing), if available (Figure 1N). Conversely, if IRSCACNA2D2 > 1, a diagnosis of DSRCT may be established. Also, CACNA2D2 staining may be used to rule out DSRCT within the broad spectrum of small-round-blue-cell tumors, potentially offering extensive diagnostic utility. Finally, the high, specific, and homogenous membranous expression of CACNA2D2 in DSRCT, combined with the highly specific antibody described here, makes CACNA2D2 an ideal candidate for targeted therapeutic approaches, including drug delivery using antibody-drug conjugates or CAR-T cell therapy. Future studies should investigate the precise role of CACNA2D2 in DSRCT biology, with a focus on its potential contributions in tumor cell fitness, differentiation, and tumorigenic potential. In conclusion, here we developed an extensive toolset for DSRCT research (Supplementary Figure S4G), a validated blueprint for how such resources could be harnessed in other cancer entities, and identified CACNA2D2 as a singular, powerful DSRCT biomarker. Florian Henning Geyer, Florencia Cidre-Aranaz, and Thomas Georg Phillip Grünewald conceived the study. Florian Henning Geyer and Florencia Cidre-Aranaz wrote the paper and drafted all figures and tables. Florian Henning Geyer carried out all in vitro and in vivo experiments and performed all bioinformatic and statistical analyses. Florian Henning Geyer, Alina Ritter, and Thomas Georg Phillip Grünewald performed immunohistochemical evaluation and scoring of tumor samples and TMAs. Florencia Cidre-Aranaz, Roland Imle, and Ana Banito performed and/or coordinated in vivo experiments. Olivier Delattre provided microarray expression data. Seneca Kinn-Gurzo performed in vitro experiments on BER cell lines. Tobias Faehling and Clémence Henon performed single-cell bioinformatic analyses. Karim Aljakouch and Azhar Orynbek performed MassSpec and analyzed MassSpec data. Alina Ritter, Jing Li, Endrit Vinca, Laura Romero-Perez, Martin Sill, and Shunya Ohmura contributed to experimental procedures. Wolfgang Hartmann and Benjamin Friedrich Berthold Mayer provided clinical and/or histological guidance. Enrique De Álava, Juan Díaz-Martín, Stefanie Bertram, Sophie Postel-Vilnay, Martin Ebinger, Monika Sparber-Sauer, Daniel Baumhoer, Carine Ngo, David Horst, Yvonne Versleijen-Jonkers, Armin Jarosch, Sabine Stegmaier, and Thomas Kirchner provided clinical samples. Patrick Joseph Grohar, Thomas Georg Phillip Grünewald, and Jeroen Krijgsveld provided laboratory infrastructure. Florencia Cidre-Aranaz and Thomas Georg Phillip Grünewald supervised the study and data analysis. All authors read and approved the final manuscript. We would like to thank Nadine Gmelin, Stefanie Kutschmann, and Felina Zahnow for their expert technical assistance, and Claudia Schmidt from the Light Microscopy Facility (German Cancer Research Center (DKFZ), Heidelberg, Germany) for her meticulous work in conducting immunohistochemical stainings. We thank the Microarray Core Facility (German Cancer Research Center (DKFZ)) for providing the Gene Expression Arrays and related services. We thank Katharina Bauer, Denise Keitel and Jan-Philipp Mallm from the Single-cell Open Lab (German Cancer Research Center (DKFZ)) for expert support in the preparation of single-cell libraries. We thank the Flow Cytometry Facility team (German Cancer Research Centre (DKFZ)) for their support with cell sorting. We thank Dr. Marc Ladanyi for sharing the SK-DSRCT2 cell line. The authors declare no competing interests. The laboratory of Thomas Georg Phillip Grünewald is supported by grants from the Matthias-Lackas Foundation, the Dr. Leopold und Carmen Ellinger Foundation, the European Research Council (ERC CoG 2023 #101122595), the Deutsche Forschungsgemeinschaft (DFG 458891500), the German Cancer Aid (DKH-70112257, DKH-7011411, DKH-70114278, DKH-70115315), the Dr. Rolf M. Schwiete foundation, the SMARCB1 association, the Ministry of Education and Research (BMBF; SMART-CARE and HEROES-AYA), and the Barbara and Wilfried Mohr foundation. The research team of Florencia Cidre-Aranaz was supported by the German Cancer Aid (DHK-70114111), and the Dr. Rolf M. Schwiete Stiftung (2020-028 and 2022-31). In addition, this work was delivered as part of the PROTECT team supported by the Cancer Grand Challenges partnership funded by Cancer Research UK, the National Cancer Institute, the Scientific Foundation of the Spanish Association Against Cancer And KiKa (Children Cancer Free Foundation). Florian Henning Geyer, Tobias Faehling, Endrit Vinca, and Alina Ritter were supported by the German Academic Scholarship Foundation. In addition, Endrit Vinca was supported by scholarships from the Heinrich F.C. Behr foundation and the Rudolf and Brigitte Zenner foundation, Tobias Faehling by the Heinrich F.C. Behr foundation, and Florian Henning Geyer and Alina Ritter are supported by the German Cancer Aid through the 'Mildred-Scheel-Doctoral Program' (DKH-70114866). This project is co-funded by the European Union (ERC, CANCER-HARAKIRI, 101122595). All views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. In vivo experiments were approved by the government of North Baden and conducted in accordance with ARRIVE guidelines and recommendations of the European Community (86/609/EEC) and UKCCCR (guidelines for the welfare and use of animals in cancer research). Open slides or tissue-microarrays from human formalin-fixed, paraffin-embedded or cryopreserved tissue samples were retrieved from the archives of the Institute of Pathology of the LMU Munich, the Charité Berlin, The Biobank of the Hospital Universitario Virgen del Rocío of Seville, the Hospital Gustave Roussy (Villejuif), the Bone Tumor Reference Center at the University of Basel, the University of Essen, the Cooperative Weichteilsarkom Studiengruppe (CWS) study center, the Klinikum Stuttgart (ethics committee from the Medical Faculty of the Eberhard-Karls University and University Hospital of Tübingen, approval no. 207/2022BO2), the Radboud University Medical Center, the Pathology Institute of the LMU Munich (approval no. 550-16 UE), and the University of Heidelberg (approval no. S-211/2021). The microarray data are deposited at the National Center for Biotechnology Information (NCBI) GEO database with accession codes GSE273438 and GSE273441. All proteomic data is deposited at the PRoteomics IDEntifications database with accession code PXD053786. All other data supporting the findings of this study are available within the article and its supplementary information files, or from the corresponding author upon reasonable request. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Data on the use of antibody drug conjugates (ADCs) in older patients are scarce. The objective was to study the safety and efficacy of ADCs used in early phase clinical trials in patients aged ≥ 65 years compared with younger patients. All patients enrolled in early phase clinical trials (phase I or II) of ADCs for solid tumors in our institution between November 2014 and May 2023 were included in this retrospective monocentric study. Safety and efficacy were compared between patients ≥ 65 and < 65 years old (y.o). A total of 136 patients were included in our study, with 43 (31.6

Desmoplastic small round cell tumor (DSRCT) is an aggressive sarcoma subtype that is driven by the EWS-WT1 chimeric transcription factor. The prognosis for DSRCT is poor, and major advances in treating DSRCT have not occurred for over two decades. To identify effective therapeutic approaches to target DSRCT, we conducted a high-throughput drug sensitivity screen in a DSRCT cell line assessing chemosensitivity profiles for 79 small-molecule inhibitors. DSRCT cells were sensitive to PARP inhibitors (PARPi) and ataxia-telangiectasia and Rad3-related inhibitors (ATRi), as monotherapies and in combination. These effects were recapitulated using multiple clinical PARPi and ATRi in three biologically distinct, clinically relevant models of DSRCT, including cell lines, a patient-derived xenograft-derived organoid model, and a cell line-derived xenograft mouse model. Mechanistically, exposure to a combination of PARPi and ATRi caused increased DNA damage, G2-M checkpoint activation, micronuclei accumulation, replication stress, and R-loop formation. EWS-WT1 silencing abrogated these phenotypes and was epistatic with exogenous expression of the R-loop resolution enzyme RNase H1 in reversing sensitivity to PARPi and ATRi monotherapies. The combination of PARPi and ATRi also induced EWS-WT1-dependent cell-autonomous activation of the cyclic GMP-AMP synthase-stimulator of IFN genes innate immune pathway and cell-surface expression of PD-L1. Taken together, these findings point toward a role for EWS-WT1 in generating R-loop-dependent replication stress that leads to a targetable vulnerability, providing a rationale for the clinical assessment of PARPi and ATRi in DSRCT. Significance: EWS-WT1, the unique oncogenic driver of desmoplastic small round cell tumors, confers sensitivity to PARP and ATR inhibitors, supporting the potential of these drugs in treating patients with this aggressive sarcoma subtype.

The combination of PARPi and ATRi elicits a cGAS–STING–mediated cell-autonomous immune response. A, Western blots of pTBK1, TBK, pIRF3, and IRF3 in JN1 cells exposed to DMSO control, PARPi talazoparib (Tala), ATRi M4344, or a combination of both for 72 hours. B and C, RT-qPCR analysis of RNA isolated from JN1 cells exposed to DMSO control, PARPi talazoparib, ATRi M4344, or a combination of both for 72 hours. CCL5 (B) and CXCL10 (C) mRNA were analyzed separately relative to RPLP0. Box and whisker plots show arbitrary units of gene expression, normalized to the DMSO condition. Boxes, median and lower and upper quartiles; whiskers, the 5th to 95th percentile range; n = 4; two-way ANOVA and post hoc Dunnett test, relative to the DMSO condition. D, Quantification of PD-L1 cell-surface expression by flow cytometry in JN1 cells exposed to DMSO control, PARPi talazoparib, ATRi M4344, or a combination of both for 72 hours. Scatter plot shows the percentage of PD-L1–positive cells within the DAPI-negative population, normalized to the DMSO condition. Mean ± SD; n = 3. Kruskal–Wallis test and post hoc Dunnett test, relative to the DMSO condition. E, Western blots of pTBK1, TBK, pIRF3, and IRF3 in JN1 cells exposed to DMSO control, PARPi talazoparib, ATRi M4344, or a combination of both for 72 hours, in the presence or absence of siRNA-mediated silencing of EWS–WT1. Appropriate silencing of EWS–WT1 was verified as shown in Fig. 4H. F and G, RT-qPCR analysis of RNA isolated from JN1 cells exposed to DMSO control, PARPi talazoparib, ATRi M4344, or a combination of both for 72 hours, in the presence or absence of siRNA-mediated silencing of EWS–WT1. CCL5 (F) and CXCL10 (G) mRNA were analyzed separately relative to RPLP0. Box and whisker plots show arbitrary units of gene expression, normalized to the siCNTRL DMSO condition. Boxes, median and lower and upper quartiles; whiskers, the 5th to 95th percentile range; n = 4; two-way ANOVA and post hoc Dunnett test, relative to the siCNTRL DMSO condition. H, Quantification of PD-L1 cell-surface expression by flow cytometry in JN1 cells exposed to DMSO control, PARPi talazoparib, ATRi M4344, or a combination of both for 72 hours, in the presence or absence of siRNA-mediated silencing of EWS–WT1. Scatter plot shows the percentage of PD-L1–positive cells within the DAPI-negative population, normalized to the siCNTRL DMSO condition. Mean ± SD; n = 3. Kruskal–Wallis test and post hoc Dunnett test, relative to the siCNTRL DMSO condition. I, Model of EWS–WT1–driven DSRCT sensitivity to PARPi and ATRi. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001; ns, not significant. ISG, IFN-stimulated genes.

EWS–WT1 drives enhanced DNA replication stress and R-loops, which contribute to DSRCT cells’ sensitivity to PARPi and ATRi. A, Assessment of replication fork speed (kb/minute) in JN1 cells subjected to siRNA-mediated silencing of EWS–WT1 or CCND1. A minimum of 50 forks was analyzed per condition. Mean ± SD; each dot represents a single replication fork; n = 2, one-way ANOVA and post hoc Dunnett test. B, Assessment of replication fork speed (kb/minute) in JN1 cells exposed to DMSO control, or a combination of PARPi talazoparib (Tala) and ATRi M4344 for 6 hours, in the presence or absence of siRNA-mediated silencing of EWS–WT1. A minimum of 50 forks was analyzed per condition. Mean ± SD; each dot represents a single replication fork; n = 2; two-way ANOVA and post hoc Šídák test. C and D, DNA:RNA hybrid dot blot of genomic DNA extracted from JN1 (C) or R (D) cells exposed to PARPi talazoparib, ATRi M4344, or a combination of both in the presence or absence of siRNA-mediated silencing of EWS–WT1 as in B. S9.6, RNA:DNA hybrids; ssDNA, loading control. E, Assessment of replication fork speed (kb/minute) in RNase H1–overexpressing JN1 cells subjected to siRNA-mediated silencing of EWS–WT1. Synchronized cells were collected 14 hours after transfection. A minimum of 50 forks was analyzed per condition. Mean ± SD; each dot represents a single replication fork; n = 2; unpaired t test. E, Dose–response survival curves of JN1 cells exposed to PARPi talazoparib (F) or olaparib (G), and ATRi M4344 (H) or AZD6738 (I) for 7 days in the presence or absence of siRNA-mediated silencing of EWS–WT1 and/or RNase H1 overexpression. Mean ± SD; n = 3; two-way ANOVA. *, P < 0.05; ****, P < 0.0001; ns, not significant.

EWS–WT1 is a determinant of DSRCT cells’ sensitivity to PARPi and ATRi. A, Western blot of EWS–WT1 in JN1 and R cells transfected with either siCNTRL or siEWS–WT1. Whole-cell lysates were generated 48 hours after transfection. B–E, Dose–response survival curves of JN1 or R cells exposed to PARPi talazoparib (B and C) or ATRi M4344 (D and E) for 7 days in the presence or absence of siRNA-mediated silencing of EWS–WT1. Mean ± SD; n = 3. F and G, Quantification of γH2AX in JN1 cells exposed to DMSO control, PARPi talazoparib, ATRi M4344, or a combination of both for 72 hours, in the presence or absence of siRNA-mediated silencing of EWS–WT1. Cisplatin was used as the positive control. A minimum of 500 nuclei was analyzed per condition. Violin plots show the absolute number of foci per nucleus. Thick line, median; thin lines, bottom and top quartiles; two-way ANOVA and post hoc Dunn test. H and I, Western blots of pCHK1, CHK1, pRPA2, RPA2, γH2AX, H2AX, and EWS–WT1 in JN1 (H) or R (I) cells exposed to DMSO control, PARPi talazoparib (Tala), ATRi M4344, or a combination of both for 48 hours, in the presence or absence of siRNA-mediated silencing of EWS–WT1. ****, P < 0.0001; ns, not significant.

PARPi and ATRi combination elicits DNA damage, replication stress, and genomic instability in DSRCT cells. A–D, Quantification of γH2AX (A and B) or RAD51 foci (C and D) in JN1 (A and C) or R (B and D) cells exposed to DMSO control, PARPi talazoparib (Tala), ATRi M4344, or a combination of both for 72 hours. Cisplatin was used as the positive control. A minimum of 500 nuclei was analyzed per condition. Violin plots show the absolute number of foci per nucleus. Thick line, median; thin lines, bottom and top quartiles; two-way ANOVA and post hoc Dunn test. E and F, Western blots of pCHK1, CHK1, pRPA2, RPA2, γH2AX, H2AX, and cleaved-PARP1 (cPARP) in JN1 (E) or R (F) cells exposed to DMSO control, PARPi talazoparib or olaparib, ATRi M4344 or AZD6738, or a combination of both for 48 hours. G and H, Representative immunofluorescence images (G) and quantification (H) of micronuclei-positive cells in JN1 cells exposed to DMSO control, PARPi talazoparib, ATRi M4344, or a combination of both for 72 hours. A minimum of 500 cells was analyzed per condition. Mean ± SD; n = 3; one-way ANOVA and post hoc Dunn test. Arrows, micronuclei. Scale bar, 20 μm. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001; ns, not significant.

A small-molecule inhibitor and drug screen identifies PARPi and ATRi as candidate therapies for DSRCT. A, Schematic illustration of the workflow of small-molecule inhibitor and drug screen performed on the JN1 cell line. B, Waterfall plot displaying the difference in AUC between the JN1 cell line (AUCJN1) and the panel of 92 cell lines used for comparison (AUCmedian) for the 79 evaluated small-molecule inhibitors or drugs. Red, PARPi; blue, ATRi; green, conventional cytotoxic. C–F, Dose–response survival curves of the DSRCT cell lines JN1 and R, and the A673 (Ewing sarcoma) and SaOS-2 (osteosarcoma) cell lines exposed to talazoparib (C), olaparib (D), M4344 (E), or AZD6738 (F) for 7 days. Mean ± SD; n = 3. G and H, Violin plots showing the relative sensitivity (log2-fold change of cell viability) of cell lines exposed to the PARPi talazoparib (G) or olaparib (H) after a single-dose exposure at 2.5 μmol/L for 5 days in the DepMap database (PRISM Repurposing 23Q2), in comparison with that of the JN1 and R cell lines. JN1 and R cell line sensitivities were extrapolated from the survival assays presented in C and E; SFs were calculated at 2.5 μmol/L and log2 transformed. Ewing sarcoma cell lines (n = 16): RDES, A673, SKES1, CADOES1, EWS502, MHHES1, EW8, A673STAG2KO16, A673STAG2KO45, A673STAG2NT14, A673STAG2NT23, CBAGPN, CHLA10, SKNEP1, SKPNDW, and TC32; osteosarcoma cell lines (n = 5): G292CLONEA141B1, MG63, U2OS, HOS, and SJSA1; soft-tissue sarcoma cell lines (n = 7): S117, TE617T, HT1080, HS729, RD, RKN, and RH30, including rhabdomyosarcoma (n = 4), leiomyosarcoma (n = 1), fibrosarcoma (n = 1), and NOS sarcoma cell lines (n = 1), respectively. The BRCA1/2-mutant IGROV1 ovarian cancer cell line and BRCA1-mutant MDA-MB-436 breast cancer cell line were used as positive controls for sensitivity to PARPi. **, P < 0.01; ****, P < 0.0001; ns, not significant.

Desmoplastic small round cell tumor (DSRCT) is a rare, aggressive sarcoma driven by the EWSR1::WT1 chimeric transcription factor. Despite this unique oncogenic driver, DSRCT displays a polyphenotypic differentiation of unknown causality. Using single -cell multi-omics on 12 samples from five patients, we find that DSRCT tumor cells cluster into consistent subpopulations with partially overlapping lineage- and metabolism -related transcriptional programs. In vitro modeling shows that high EWSR1::WT1 DNA -binding activity associates with most lineage -related states, in contrast to glycolytic and profibrotic states. Single -cell chromatin accessibility analysis suggests that EWSR1::WT1 binding site variability may drive distinct lineage -related transcriptional programs, supporting some level of cell -intrinsic plasticity. Spatial transcriptomics reveals that glycolytic and profibrotic states specifically localize within hypoxic niches at the periphery of tumor cell islets, suggesting an additional role of tumor cell -extrinsic microenvironmental cues. We finally identify a single -cell transcriptomics-derived epithelial signature associated with improved patient survival, highlighting the clinical relevance of our findings.