The Tumour Microenvironment in Paediatric Rhabdomyosarcomas: A Systematic Review

The Tumour Microenvironment in Paediatric Rhabdomyosarcomas: A Systematic Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review The Tumour Microenvironment in Paediatric Rhabdomyosarcomas: A Systematic Review Megan Richards, Christina Putnam, Timothy J Underwood, Zoe S Walters This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7796884/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Rhabdomyosarcoma (RMS) is a predominantly paediatric cancer that is classified by the presence or absence of a PAX-FOXO1 fusion gene, which is associated with a worse prognosis. Previous classification was based on histology, Alveolar RMS (ARMS) or Embryonal RMS (ERMS). In other paediatric cancers, fusion gene status has been shown to associate with differences in the tumour microenvironment. However, comprehensive understanding of the TME in RMS and how it may differ between subtypes is lacking. This systematic review aimed to identify differences in the TME between FP-RMS and FN-RMS, to better understand how the fusion gene drives malignancy. The Web of Science, MEDLINE (Ovid) and EMBASE (Ovid) were searched to identify relevant studies investigating the TME in RMS. A total of 17 studies met the inclusion criteria and were included in the review, but only three studies specified fusion status in their sample data. Nine studies investigated the extracellular matrix (ECM) and stroma, and another nine investigated the immune microenvironment. Significant differences in CD163 + macrophages, matrix metalloproteinases (MMPs) and stromal platelet derived growth factor receptors (PDGFRɑ/ß) were observed between ARMS and ERMS. Regarding fusion status, there were differences in the prevalence of T cell dysfunction, NECTIN-3 expression, and genes related to PD-1 signalling and interferon (IFN) response. This review highlights a definite need for further research of the TME in each fusion subtype. This will improve our understanding of how the fusion gene drives malignancy and ultimately aids in the development of novel treatment strategies. Oncology General Cell Biology & Physiology Rhabdomyosarcoma tumour microenvironment PAX-FOXO1 fusion gene immune microenvironment extracellular matrix Figures Figure 1 Figure 2 1 Introduction 1.1 Paediatric Rhabdomyosarcoma Rhabdomyosarcoma (RMS) is the most common type of soft tissue sarcoma (STS) in children, with an incidence of 4.3 cases per million a year worldwide [1]. Tumours express myogenic regulatory transcription factors (MRFs), which suggest they are of myogenic origin and occur because of abnormal skeletal muscle differentiation [2–4]. Historically, RMS has been divided into alveolar, embryonal, pleomorphic and sclerosing subtypes, based on histological features. Embryonal (ERMS) and Alveolar (ARMS) subtypes are the most common in children [4]. However, more recently, RMS has been defined by molecular characterisation. Up to 80% of ARMS are fusion positive, characterised by a chromosomal translocation between FOXO1 on chromosome 13 and either PAX3 on chromosome 2 (t(2;13)(q35;q14) [5], or PAX7 on chromosome 1 (t(1;13)(p36;q14) [6]. This results in the expression of more potent transcription factors PAX3-FOXO1 (in 55% of ARMS) or PAX7-FOXO1 (in 22% of ARMS) [7], leading to the classification of either fusion positive RMS (FP-RMS) or fusion negative RMS (FN-RMS). The presence of the PAX-FOXO1 fusion is now known to have a primary role in RMS progression and drives an unfavourable outcome for children [8, 9]. FP-RMS have a significantly poorer overall survival, event free survival, and a higher frequency of metastasis compared to FN-RMS [8], making it more clinically aggressive. The fusion gene is also associated with disease recurrence, which decreases patient survival rate from 70%, after current multimodal therapy, to 20% [10, 11]. This highlights the need for novel and improved treatment strategies for FP-RMS patients. Histology was traditionally used to predict prognosis, as the International Classification of Rhabdomyosarcoma (ICR) identified ARMS as having a poorer prognosis compared to ERMS [9]. But recent evidence has shown that fusion negative ARMS (FN-ARMS) is molecularly and clinically indistinguishable from ERMS [8]. Therefore, classifying RMS based on fusion status, rather than histology, may be more prognostically significant. 1.2 The Tumour Microenvironment The tumour microenvironment (TME) plays a crucial role in tumour initiation, progression and metastasis [12, 13]. It consists of cancerous cells, as well as non-malignant host cells, including stromal cells (fibroblasts, endothelial cells, and pericytes), immune cells (CD8 + T cells, natural killer (NK) cells, dendritic cells (DCs) and macrophages) and the extracellular matrix (ECM); a non-cellular component, which comprises of a complex mixture of collagens, laminins, glycoproteins and proteoglycans [14, 15]. Cancer cells communicate with the surrounding non-malignant components of the TME, stimulating changes in their function that promote tumour progression [15, 16]. The stroma is essential for maintaining the integrity of normal tissues, however, malignancy is associated with changes in the stroma, leading to tumour growth, invasion and metastasis [17]. Furthermore, the immune microenvironment has a critical role in the surveillance and elimination of tumours, however, interactions between tumour cells and components of the immune TME can lead to immunosuppression and immune escape [18]. The immune TME can be grouped into pro-tumour and anti-tumour components (Fig. 1). Anti-tumour immune cells include CD8 + T cells, NK cells, DCs and M1 polarised macrophages, which are associated with improved patient outcome in a variety of cancers [18–22]. Pro-tumour immune cells include regulatory T cells (T-regs), myeloid derived suppressor cells (MDSCs) and M2 polarised macrophages, which are associated with tumour progression, invasion and metastasis, resulting in poor patient prognosis [18, 23–28]. Advanced understanding of the TME has shifted the treatment of cancer, from direct targeting of tumour cells, to targeting the TME [12]. Previous studies have identified differences in the TME between cancer subtypes, which may shape their prognostic differences [13]. For example, HER2-positive breast cancer is associated with a higher immune score and immune infiltration compared to luminal A and luminal B subtypes [29]. The intensity of collagen type III staining has also been reported to vary between histological STS subtypes [30]. It was thus suggested that these differences in the TME between cancer subtypes may reflect their prognostic differences. In sarcomas, differences in the TME can be attributed to the presence of a fusion gene. For example, by comparing Myxoid Liposarcoma cells with or without the FUS::DDIT3 fusion protein, Ranji et al. [31] identified FUS::DDIT3 regulated genes involved in cell-cell and cell-ECM interactions, including those involved in ECM organisation. There is a lack of understanding of how the presence of the PAX-FOXO1 fusion protein contributes to tumorigenesis and increased clinical aggression in the FP-RMS subtype [32]. Previous studies using genome wide screens have reported PAX-FOXO1 to exert oncogenic effects by the altered transcription of PAX3 target genes, which are involved in cell survival, myogenic differentiation and mesodermal development [32, 33]. While these studies have attempted to identify these individual genes, many still require validation and further study for their role in FPRMS progression [32]. In addition, these studies were also confounded by the inclusion of RMS with unknown fusion status [32]. It has also been concluded that PAX-FOXO1 alone is not sufficient to cause transformation [32]. Therefore, further work is required to precisely define the mechanisms underlying how the PAX-FOXO1 fusion proteins contribute to tumorigenesis. Since the TME has a crucial role in tumour progression, identifying differences between FP-RMS and FN-RMS may help to determine whether the TME contributes to more malignant behaviour in FP-RMS. This may in turn help identify novel targets for development of more effective treatment strategies for this FP-RMS patients. 1.3 Hypothesis, Aims and Objectives This systematic review asked whether there were differences in the TME between paediatric FP-RMS and FN-RMS. Histological subtype was investigated to infer differences in the TME between fusion subtypes as histology has historically been used to classify RMS subtypes, rather than fusion status. Additionally, since the majority (around 80%) of ARMS are fusion positive, analysing TME differences between ERMS (which are fusion negative) and ARMS, could offer surrogate insights into differences between FP-RMS and FN-RMS. The aim of this systematic review was to identify and evaluate current literature investigating the TME in patient-derived, pediatric FP-RMS and FN-RMS/ ARMS and ERMS, to identify any differences in the stromal, immune, and ECM components between FP-RMS and FN-RMS. Since the TME influences tumor aggression [34], we hypothesized that, after synthesizing existing data from all available relevant studies of patient-derived samples, there would be a difference in the expression, proportion, number, type, and composition of immune, stromal, and ECM components between pediatric FNRMS and the more clinically aggressive FPRMS. 2 Methods 2.1 Search Strategy A systematic search of the literature (between 1994 and 2023) was conducted on three main databases: The Web of Science, MEDLINE (Ovid) and EMBASE (Ovid), with the help of a librarian at the University of Southampton. The Web of Science was searched using only free text terms, whereas EMBASE and MEDLINE were searched using both free text terms and subject heading terms. The search terms used across each database is presented in Table 1 . Searches were limited to English language publications across all databases. In the Web of Science, searches were additionally restricted to published articles and in EMBASE, pre-print records were removed. This systematic review followed the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA). Table 1 Search strategy used for the systematic search of the literature Database (platform) Search Strategy Web of Science (microenvironment OR matrix OR niche OR "tum*r microenvironment" OR "immune cell $ " OR stroma OR "extracellular matrix" OR "cancer associated fibroblast $ " OR "tum*r infiltrating lymphocyte $ " OR "immune microenvironment" OR immune OR "tum*r immunology") AND (rhabdomyosarcoma*) AND (paediatric* OR pediatric* OR child* OR infant* OR adolescen*) MEDLINE (Ovid) microenvironment or matrix or niche or "tumo?r microenvironment" or "immune cell $ " or stroma or "extracellular matrix" or "cancer associated fibroblast $ " or "tumo?r infiltrating lymphocyte $ " or "immune microenvironment" or immune or "tumo?r immunology" or tumor microenvironment/ or fibroblasts/ or cancer-associated fibroblasts/ or myofibroblasts/ or macrophages/ or tumor-associated macrophages/ or stromal cells/ or extracellular matrix/ or cancer-associated fibroblasts/ or -lymphocytes/ or lymphocytes, tumor-infiltrating/ or immune evasion/ or immune checkpoint inhibitors/ or immune system/ or immunotherapy/) AND (rhabdomyosarcoma* or exp rhabdomyosarcoma/) AND (paediatric* or pediatric* or child* or infant* or adolescen*.mp. or infant/ or child/ or adolescent/ or pediatrics/) EMBASE (Ovid) (microenvironment or matrix or niche or "tumo?r microenvironment" or "immune cell $ " or stroma or "extracellular matrix" or "cancer associated fibroblast $ " or "tumo?r infiltrating lymphocyte $ " or "immune microenvironment" or immune or "tumo?r immunology" or tumor microenvironment/ or exp stroma cell/ or stroma cell/ or bone marrow stroma cell/ or stroma/ or mesenchymal stroma cell/ or extracellular matrix/ or cancer associated fibroblast/ or exp tumor associated leukocyte/ or tumor microenvironment/ or immune evasion/ or immune system/ or immune dysregulation/ or immune signaling/ or immune response/ or immune checkpoint inhibitor/ or exp tumor immunology/) AND (rhabdomyosarcoma* or rhabdomyosarcoma/ or alveolar rhabdomyosarcoma/ or embryonal rhabdomyosarcoma/) AND (paediatric* or pediatric* or child* or infant* or adolescen* or pediatrics/ or child/ or hospitalized child/ or child hospitalization/ or adolescent disease/ or adolescent/ or hospitalized adolescent/) 2.2 Inclusion and Exclusion Criteria Inclusion and exclusion criteria were developed based on the PICO framework (Table 2 ). Studies were included if they met the following criteria: a) reported patient-derived data from paediatric ARMS or ERMS/FP-RMS or FN-RMS (patient-derived data included patient-derived cell culture, patient-derived organoids and patient-derived tissue slice cultures) b) characterised a component(s) of the TME. Histological subtype and fusion subtype were included, as many studies still rely on histology to classify RMS. Paediatric was defined as children and young adults up to the age of 21. Studies were excluded if they: a) reported data from adult RMS; b) reported data from animal models, cell lines, or patient-derived xenograft models; c) did not characterise a component of the TME (or were not relevant to the TME); d) reported data from pleomorphic or sclerosing subtypes. If studies did not specify the subtype of RMS, or whether samples were paediatric or adult in their abstracts, they were retained at the abstract screening stage. If not specified in their full text, they were excluded. Adult RMS was excluded, as it is much rarer and has a different prognosis compared to its paediatric counterparts [35]. Table 2 PICO framework and inclusion and exclusion criteria used for screening PICO framework Inclusion criteria Exclusion criteria Population Paediatric a RMS paediatric ARMS or ERMS/FPRMS or FNRMS patient-derived data which includes: - Patient-derived cell culture - Patient-derived organoids - Patient-derived tissue slice cultures Adult RMS Animal and cell line models Patient-derived xenografts Studies that don’t separate RMS results from other sarcoma results. If study doesn’t specify whether the samples are from paediatric or adult patients, exclude at full text screening stage. Intervention The TME Data that characterises a component(s) of the TME Studies that do not describe the TME Comparator The TME in FPRMS versus FNRMS or ERMS versus ARMS. Data from either ARMS or ERMS/FPRMS FNRMS Studies that do not specify the subtype of RMS to be excluded only at the full text screening stage. Studies that group results from multiple subtypes together, to be excluded at the full text stage only. Pleomorphic or sclerosing subtypes. Outcome Differences in the TME between subtypes. Expression, number, proportion, type and composition of immune, stromal and ECM components of the TME. Other Meeting abstracts Reviews Not full text articles a Paediatric includes children and young adults up to the age of 21. RMS , Rhabdomyosarcoma; TME , Tumour microenvironment; FPRMS , fusion-positive rhabdomyosarcoma; FNRMS , fusion-negative rhabdomyosarcoma; ARMS , alveolar rhabdomyosarcoma; ERMS , embryonal rhabdomyosarcoma. 2.3 The Selection Process References identified from the search were exported to Rayyan ( http://rayyan.qcri.org/ ) and de-duplicated. Rayyan was used to screen all titles and abstracts against the inclusion and exclusion criteria as stated in Table 2 , to identify those that were potentially relevant. A random selection of 22 titles and abstracts were independently screened by a second reviewer. Any discrepancies were discussed and resolved. Full text papers were obtained using Endnote or manually searched for using the Web of Science, MEDLINE (Ovid) or EMBASE (Ovid). Some were not obtained due to the University not having access. Full texts were further screened against the inclusion and exclusion criteria to assess their relevance. 2.4 Data Extraction Data extracted from the included studies included: a) first author and year; b) study aims; c) tissue processing technique; d) histological subtype and the number of samples of each; e) fusion status and the number of samples of each; f) patient age; g) the experimental method(s) used; h) the component(s) of the TME analysed; i) the key findings. In Chen et al’s [36] study, key findings regarding their ARMS samples were not extracted, as not all samples were paediatric. Data extraction was conducted by one independent reviewer. Due to the heterogeneity in the methods used and the results reported among the studies, a meta-analysis could not be conducted, so the results were reported descriptively. 2.5 Quality Assessment To assess the quality of each included study, the Risk of Bias in Non-randomised Studies of Interventions (ROBINS-I) tool was used, which included seven domains of bias: confounding bias, selection bias, information bias, performance bias, detection bias, reporting bias and bias due to missing data. The Cochrane Online Handbook for Systematic Reviews [37] was also used to help further clarify bias definitions. Studies were scored with either a low, moderate, serious or critical risk of bias. Results of the quality assessment are presented in Supplementary Table S1. 3 Results 3.1 Study Selection The initial database search identified 1,287 references in line with the initial search strategy. Of these, 211 were identified from the Web of Science, 321 from MEDLINE (Ovid) and 755 from EMBASE (Ovid). Following exportation to Rayyan, 431 duplicate records were removed, yielding a total of 856 references to be screened. The titles and abstracts were screened against the inclusion and exclusion criteria, which resulted in the exclusion of 727 references. Of the remaining 129, nine full text papers could not be retrieved, leaving 120 full texts to which inclusion criteria was applied. Full text screening resulted in 103 references being excluded. Full texts were excluded due to not meeting either the population criteria (n = 36), the intervention criteria (n = 15), the comparator criteria (n = 11) or were not full text articles (n = 41). Following study selection, 17 studies were included in this systematic review. The PRISMA flowchart of this selection process is presented in Fig. 2. The study characteristics of these included studies are summarised in Table 3 and the key findings are summarised in Table 4 . 3.2 Study Characteristics The 17 included studies were published between 1994 and 2023. Of these studies, only three included fusion status [4, 36, 38], the rest included only histological subtype (ERMS and ARMS). Nine studies investigated the ECM and the stroma [39–47], another nine investigated the immune microenvironment [4, 36, 38, 39, 48–52], and one study investigated both aspects [39]. The most frequently used sample type was Formalin-Fixed, Paraffin-Embedded (FFPE) tissue, which was used by just over half of the studies (56%) [36, 38, 40, 41, 45, 47, 48, 51, 52]. Only one study used patient-derived organoids [4]. Data from patient-derived samples, rather than cell lines or animal models, were included for this review, as these better recapitulate the heterogeneity, complexity and pathophysiology of patient tumours and their TMEs [53]. A variety of different methods were used for analysis, with immunohistochemistry (IHC) being the most common (used in 64.7% of studies) [36, 38, 40, 41, 45, 47–52]. The mean number and the total number of samples per histological subtype and fusion subtype is presented in Table 5 . Three studies were excluded from the mean calculation for ERMS due to missing sample size data [4, 50, 51]. Five studies were excluded from the mean calculation for ARMS due to three having missing sample size data [4, 50, 51], and two studies not including ARMS samples [36, 39]. Table 3 Key characteristics of the studies included in the review First author, year Reference Study Aims Tissue processing technique Histological subtype (number of samples) Fusion status (number of samples) Age of Patients Methods used for analysis Component(s) of TME investigated Chen et al. 2020 [36] Perform an in-depth interrogation of the tumour immune microenvironment of STS to identify immunotherapy agents. FFPE tumour tissue ERMS (27) FP (50) FN (63) ERMS: range = 0.02-22 mean = 7 IHC RNA sequencing gene expression analysis Immune microenvironment Bertolini et al. 2018 [38] Further describe the immune microenvironment of RMS by evaluating PD-L1 expression. FFPE RMS tissue ERMS (13) ARMS (11) FP (7) FN (18) N/A IHC Immune microenvironment PD-L1 Xu et al. 2022 [39] Delineate the testicular ERMS intra-tumoral heterogeneity and TME. Analyse the role of each subpopulation of cells in the progression of testicular ERMS. Analyse the relationship between macrophages and ERMS tumour cells. Fresh tumour tissue ERMS (1) N/A 16 years Single cell RNA sequencing Macrophages Myoid cells Endothelial cells Fibroblasts Xia et al. 2021 [48] Evaluate potential indicators of TME status changes. Correlate immune infiltration with low and high expression of MD2L1 and CCNB2 expressing populations in RMS samples. Paraffin embedded RMS samples. ERMS (14) ARMS (12) N/A Study from which the dataset was from: mean = 7 range = 0–20 Bioinformatics IHC Immune infiltration MD2L1 CCNB2 Saxon et al. 1997 [40] Investigate the presence of adhesion factors laminin, fibronectin, tenascin, thrombospondin and CD44 in paediatric RMS Paraffin embedded samples ERMS (6) ARMS (5) N/A ARMS: average = 11.6 years. Range = 6-15.4 years. ERMS: average = 6 years range = 2.4–8.2 years. IHC Adhesion molecules: Laminin Fibronectin Tenascin Thrombospondin CD44 Gabrych et al. 2019 [49] Assess PD-L1 and PD-1 expression in paediatric RMS and to investigate their clinicopathological associations. Biopsy samples ERMS (19) ARMS (12) N/A Range = 1 day-18 years. Median = 7.4 years. IHC PD-L1 and PD-1 expression Vela et al. 2019 [41] Analysed CXCR4 expression in tumour samples from paediatric RMS patients. Used an orthotopic model of ARMS to evaluate the complementary antitumoral and antimetastatic effects of combined NKAE + MDX1338 immunotherapy in vivo. FFPE tumour samples. ERMS (15) ARMS (5) N/A ERMS: mean = 5.1 range = 0.2-13 ARMS: mean = 9.8 range = 7.5–11.1 IHC CXCR4 expression Masola et al. 2009 [42] Analyse HPSE expression and activity in ARMS and ERMS and investigate the relationship of the different metastatic phenotypes of ARMS and ERMS with expression and activity of HPSE. Plasma and tumour RNA collected from RMS patients. ERMS (10) ARMS (5) N/A Mean = 6.3 years Range = 1–15 years HPSE mRNA expression was evaluated by real time PCR. HPSE activity determined by ELISA method. Plasma assay HPSE Peng et al. 2015 [50] N/A N/A ERMS (N/A) ARMS (N/A) N/A N/A Morphology and number of TAMs examined by IHC. TAMs APN DeMartino et al. 2023 [4] Compile a single cell transcriptomic atlas comprising both FPRMS and FNRMS and to find distinct differences in cellular composition and differentiation states which relate to clinical outcomes. Viably frozen primary RMS tumour samples Patient-derived tumour organoid models N/A FP (13) FN (13) 15 samples were 10 years Single cell mRNA sequencing Immune microenvironment Martin et al. 2007 [43] Analyse dystroglycan expression and glycosylation in paediatric solid tumours and demonstrate alterations in ɑ-dystrogycan in paediatric RMS (and others). Snap frozen unfixed tumour samples Immunoblot: ERMS (2) ARMS (1) Immunostaining: ERMS (23) ARMS (14) N/A Table 1 : ERMS: mean = 4.5 years (5 + 4) ARMS: age = 9 Immunoblot for dystroglycan expression. Immunostaining on tissue microarrays. Glycosylated dystroglycan Thakur et al. 2022 [51] Investigate the immune microenvironment of five major paediatric cancers: Ewing sarcoma, osteosarcoma, RMS, medulloblastoma, neuroblastoma, and correlated with overall survival. FFPE sections ERMS (N/A) ARMS (N/A) N/A 0–17 Gene expression analysis IHC Immune microenvironment Strahm et al. 2008 [44] To investigate the role of the bone marrow microenvironment on RMS signalling and behaviour through the CXCR4/SDF-1ɑ pathway. Patient RNA samples ERMS (7) ARMS (5) N/A N/A RT-PCR Bone marrow stroma - CXCR4/SDF-1ɑ metastatic signalling Stracca-Pansa et al. 1994 [45] Understand ECM elements in small round cell tumour tissue and to investigate the detection of these elements by IHC on tumours from patients. FFPE tissue ERMS (15) ARMS (9) N/A Range = 0.5–23 Mean = 7.5 IHC ECM: - Laminin - Type IV collagen - Fibronectin Ehnman et al. 2013 [46] Identify biological activities linked to PDGF signalling in RMS models and human sample collections. N/A ERMS (261) ARMS (50) N/A Microarray analysis on 3 x tissue microarrays PDGFRɑ and PDGFRβ Diomedi-camassei et al. 2004 [47] To assess the expression of MMPs in RMS and to evaluate the correlation with clinicopathologic parameters. FFPE tissue ERMS (21) ARMS (12) N/A Mean = 85+/- 54 months Range = 2-175 months IHC MMPs Chowdhury et al. 2015 [52] Report the frequency of PD-L1 expression in paediatric malignancies and to assess the frequency of tumour infiltrating CD8 + cytotoxic T-lymphocytes and their levels of PD-1 expression. FFPE primary tumour samples. ERMS (18) ARMS (15) N/A ERMS: median = 6.5 range = 1.3-16.2 ARMS: median = 6.0 range = 1.2–12.8 IHC PD-1/PD-L1 expression CD8 + cytotoxic T cells FFPE , formalin-fixed paraffin embedded; IHC , immunohistochemistry; N/A , data not provided; TME , tumour microenvironment; RMS , rhabdomyosarcoma; ARMS , alveolar rhabdomyosarcoma; ERMS , embryonal rhabdomyosarcoma; ELISA , enzyme-linked immunosorbent assay; TAM , tumour associated macrophages; ECM , extracellular matrix; MMP , matrix metalloproteinase; FP , fusion positive rhabdomyosarcoma; FN , fusion negative rhabdomyosarcoma; STS , soft tissue sarcoma; RT-PCR , reverse transcription polymerase chain reaction; PDGF , platelet derived growth factor; PDGFRɑ/β , platelet derived growth factor receptor-ɑ/β 3.3 Study results 3.3.1 The Immune Microenvironment Of the studies investigating the immune microenvironment, macrophages (n = 5) [36, 38, 39, 48, 50] and CD8 + T cells (n = 4) [4, 36, 51] were investigated the most frequently. Other immune components were also investigated, such as B cells [36], CD4 + T cells [4, 36], monocytes [4], NK cells [4], DCs [4] and T-regs [4]. Three studies investigated the immune microenvironment in FP-RMS and FN-RMS [4, 36, 38]. Data across studies could not be averaged due to heterogeneity in their methods and results reported. Tumour associated macrophages (TAMS), particularly M2-like TAMs, are an immunosuppressive immune cell of the TME [54]. Two studies investigated the difference in macrophages between the histological subtypes and fusion subtypes [4, 50]. DeMartino et al. [4] reported no difference in the proportion of macrophages between FPRMS and FNRMS, and reported that they existed predominantly in the M2 polarisation state in both fusion subtypes. In contrast, Peng et al. [50] identified a difference in the expression of CD163, a marker specific for M2 macrophages, between ERMS and ARMS, with expression levels being significantly increased in ARMS. The latter study did not provide information regarding fusion status. Cytotoxic CD8 + T cells are the primary effector cells of the anti-tumour immune response [55]. Thakur et al. [51] characterised CD8 expression and reported no significant difference between ERMS and ARMS. However, results presented by Chowdhury et al. [52] show a higher mean total CD8 + tumour infiltrating lymphocyte (TIL) count in ERMS compared to ARMS, although the significance was not reported. DeMartino et al. [4] reported that interferon (IFN) stimulated CD4 + T helper cells (ISG+) were found almost exclusively in FN-RMS tumours, which were enriched for gene signatures related to IFN response and stimulation. They also reported that T cell dysfunction was more prevalent in FPRMS tumours, with CD8 + T cells enriched for genes related to PD-1 signalling and T cell exhaustion [4]. In addition, they reported NECTIN-3 to be upregulated on FP-RMS cells, whose interaction with TIGIT on T cells induces T cell dysfunction [56]. Chen et al. [36] found a difference in CD4 + memory T cells between fusion subtypes, with a significant increase in FNRMS compared to FPRMS. DeMartino et al. [4] also reported that the proportion of non-malignant cell types, which included T cells, NK cells, DCs, monocytes, and B cells, did not differ significantly based on fusion status. The immune checkpoint molecules PD-L1, expressed on antigen-presenting cells and tumour cells, and PD-1, expressed on TILs, interact to inhibit T cell activation, which allows cancer cells to evade immunosurveillance [57]. Bertolini et al. [38] and Gabrych et al. [49] reported PD-L1 expression to be restricted to the immune contexture in their RMS samples, which had no correlation with histological subtype [49], or fusion status [38]. However, Chowdhury et al. [52] reported PD-L1 expression on the tumour cells, with 86% of ARMS being PD-L1 positive, compared to 50% of ERMS. But the statistical significance of this difference was not measured and information regarding fusion status was not provided. Table 4 Key findings of the studies included in the review Reference Key Findings [36] ERMS • CD3 + and TAMs (CD163+) in close proximity to endothelial cells - majority of T cells and TAMs are found within 20-40um of endothelial cells. • TAMs predominated the immune microenvironment in all sarcomas. • Majority of CD3 + and CD8 + T cells in aggregates with B cells forming TLS, which were the main source of PD-L1 expression. • B cells found in TLS and not elsewhere. • The common predominant immune signature was myeloid cells in RMS. Results from their analysis of publicly available gene expression datasets: • There was a significantly higher number of resting CD4 + memory T cells in FN-RMS compared to FP-RMS (0.256+/-0.134 in FN-RMS compared to 0.185+/-0.118 in FP-RMS). [38] • PD-L1 expression was heterogenous (not present at all in tumour cells) in both ARMS and ERMS. • PD-L1 expression was found in the immune contexture in: - 6/11 ARMS - 9/14 ERMS. • PDL1 staining does not correlate with fusion status. • PDL1 expression colocalised with CD3 + T lymphocytes and CD68 + macrophages. [39] ERMS • Myeoid cells showed downregulation of genes associated with ECM organisation compared to the ERMS tumour cells (differentially expressed genes between tumour and normal were closely related to cell adhesion and ECM signalling pathways). • Tumour cells included M1 and M2 macrophages, normal tissue contained M3. • All macrophages (M1, M2 and M3) expressed immune checkpoint molecules, however M2 had a higher immune activity. - M1 = FGL1 and IDO1 - M2 = CD101 - HAVCR2. M3 = CD86 • E1 (34.41%), E2 (29.96%) and E3 (35.63%) endothelial cell subtypes expressed in tumour cells, normal tissues mainly expressed E2 (66.7%). • E1 and E2 subgroups transform into E3 subgroup during progression to promote tumour progression. • Macrophages were closely related to collagen and ECM pathway. [48] Bioinformatics analysis: ERMS: • 7 showed low MAD2L1 expression (50%) and 7 showed high expression (50%). • 5 showed low CCNB2 expression (35.7%) and 9 showed high expression (64.3%). ARMS: • 3 showed low MD2L1 expression (25%) and 9 showed high expression (75%). • 5 showed low CCNB2 expression (41.7%) and 7 showed high expression (58.3%). IHC analysis: • Expression rate of MAD2L1 in RMS samples was 90.9% (30/33) - no expression in 11 control skeletal muscle tissue. • Expression rate of CCNB2 was 100% (33/33) - no expression in control. • No statistical difference in expression of MD2L1 or CCNB2 expression between ERMS and ARMS. [40] • All samples expressed tenascin and thrombospondin regardless of subtype (5/5 ARMS, 6/6 ERMS). • Fibronectin was expressed by all ARMS (5/5). • Fibronectin not expressed in all ERMS (4/6). • Laminin expressed in 3/5 ARMS and 2/6 ERMS. • CD44 was not expressed by any ARMS but was expressed by half of ERMS (3/6). [49] • The positive PD-L1 staining in RMS samples was restricted to tumour associated immune cells in all cases, with no reactivity in tumour cells. • No correlation between PD-L1 expression and RMS histological subtype (p = 0.451). - ERMS PD-L1 + in 11/19 (57.89%). - ARMS PD-L1 + 9/12 ARMS (75.00%). [41] • No difference in CXCR4 expression between ERMS and ARMS (for diagnostic samples) (p = 0.59). [42] • Plasma from ARMS patients showed higher activity levels of HPSE compared to ERMS but not statistically significant (data not shown). • HPSE mRNA expression was significantly higher in both ERMS and ARMS compared to control. [50] • CD163 + TAMs and APN + expressed at much higher levels in ARMS compared to ERMS (TAMs p < 0.05, APN p < 0.001) [4] • The proportion of each non-malignant cell types did not differ significantly by fusion status. o Non-malignant cell types included T cells (CD4 T cells, T-regs, CD8 + T cells), NK cells, B cells, monocytes and macrophages (M1 and M2). o These non-malignant cell types were grouped into clusters – T/NK cell cluster, myeloid cluster, B cell cluster and endothelial cell cluster, whose proportions didn’t differ based on fusion status. • IFN stimulated CD4 + T helper cells (ISG+) were found almost exclusively in FNRMS. • Dysfunction of CD8 + T cells was more prevalent in FP-RMS samples - CD8 + T cells were enriched for genes related to PD-1 signalling, OXPHOS and T cell exhaustion. • Cells from FN-RMS tumours were enriched for gene signatures relating to IFN response and stimulation. • Interaction between NECTIN3 on malignant cells and TIGIT receptor on T-regs and CD8 + T cells was specific to FP-RMS tumours due to significantly higher expression of NECTIN-3 on FP-RMS, whilst there was no difference in expression of TIGIT on CD8 + T cells between subtypes [43] Immunoblot results: • All 5 RMS samples had reduced or absent expression of native ɑ-dystroglycan. • β-dystroglycan present in all RMS samples, molecular weight in tumour sample was similar to normal muscle controls. • Laminin binding was significantly reduced in all 5 RMS samples compared to controls. Immunostaining of tissue microarrays results: • Both ERMS and ARMS had significant reduction in ɑ-dystroglycan staining relative to normal skeletal muscle and relative to β-dystroglycan. • Laminin expression was significantly reduced relative to β-dystroglycan in both RMS subtypes. • ɑ-dystroglycan staining occurred primarily in tumour vasculature in both ERMS and ARMS. • β-dystroglycan staining was abundant in all tumour samples of both tumour types - no tumour types received a score of 1 (no staining) for β-dysrtroglycan). • For ɑ-dystroglycan, 67% (for VIA4-1) and 55% (for IIH6) ERMS had a score of 1, and 43% (for VIA4-1) and 33% (for IIH6) of ARMS had a score of 1. • ERMS (23): * between tumour sample and control βDG = 2.91 ± 0.21 VIA4-1 (ɑDG) = 1.46 ± 0.11*** IIH6 (ɑDG) = 1.70 ± 0.15*** LN-1 (laminin) = 1.66 ± 0.21* • ARMS (14): * between tumour sample and control βDG = 2.89 ± 0.07 VIA4-1 (ɑDG) = 1.55 ± 0.16** IIH6 (ɑDG) = 1.90 ± 0.19* LN-1 (laminin) = 1.80 ± 0.13* [51] • CD8 by IHC and gene expression was comparable in ARMS and ERMS. • 30% of RMS samples were positive for PD-L1–4 samples had PD-L1 positivity in tumour cells, 2 samples were PD-L1 positive in immune cells. [44] • CXCR4 expression was statistically increased in ARMS primary samples relative to ERMS and control skeletal muscle (p = 0.004). • No statistical difference in expression of CXCR4 between ERMS and control skeletal muscle. • All BMS cultures expressed increased SDF-1ɑ. • CXCR4- SDF-1ɑ signalling axis may be involved in RMS metastasis to bone marrow. [45] • ERMS: - Laminin (93%) - Fibronectin (87%) - Type IV collagen (54%) • ARMS: rarely expressed any of the extracellular matrix proteins - Laminin (22%) - Fibronectin (22%) - Type IV collagen (14%) [46] • PDGFRβ was significantly over expressed in both ARMS and ERMS. • PDGFRβ protein levels were rarely detected in tumour cells, expression was associated with stroma in ARMS subtype. - PDGFRβ stromal staining was positively associated with ARMS (p < 0.0001). • PDGFRɑ expression was observed in both the tumour cell and stroma and was associated with ERMS. - PDGFRɑ stromal staining was positively associated with ERMS (p = 0.0329). [47] • ARMS cells stained diffusely and strongly for MMP-2 and MMP-9. • MMP-1 positive in: - 11/12 ARMS - 11/21 ERMS • MMP-2 positive in: - 12/12 ARMS - 9/21 ERMS • MMP7 expressed in 26/33 tumour samples: - 11/12 ARMS - 15/21 ERMS • MMP-3 was negative in almost all RMS samples (28/32). • MMP-3 positive in: - 2/12 ARMS - 3/21 ERMS • MMP-9 was positive in perivascular ECM and in vascular structures of tumours • Positive in: - 12/12 ARMS - 11/21 ERMS • Statistically significant difference between ARMS and ERMS: MMP-1 (P = 0.006) MMP-2 (P = 0.0001) MMP-9 (P = 0.0001) [52] • 86% of ARMS were PD-L1 positive. • 50% of ERMS were PD-L1 positive. • Figure 3e shows ERMS having a higher mean total number of CD8 + TILs compared to ARMS (significance wasn’t reported). TAM , tumour associated macrophages; TLS , tertiary lymphoid structure; RMS , rhabdomyosarcoma; ERMS , embryonal rhabdomyosarcoma; ARMS , alveolar rhabdomyosarcoma; FN , fusion negative; FP , fusion positive; ECM , extracellular matrix; APN , adiponectin; NK cells , natural killer cells; IHC , immunohistochemistry; BMS , bone marrow stroma; FN-RMS , fusion negative rhabdomyosarcoma; FP-RMS , fusion positive rhabdomyosarcoma; OXPHOS , oxidative phosphorylation; T-regs , regulatory T cells; MMP , matrix metalloproteinase; TIL , tumour infiltrating lymphocytes; PDGFRɑ/β , platelet derived growth factor receptor-ɑ/β; SDF-1 , stromal cell-derived factor 1; βDG , β-dystroglycan; ɑDG, ɑ-dystroglycan. Table 5 The total number and the mean number of samples for each RMS subtype Subtype Mean Total FP-RMS 23 70 FN-RMS 31 94 ERMS 32 452 ARMS 13 156 FP-RMS , fusion positive rhabdomyosarcoma; FN-RMS , fusion negative rhabdomyosarcoma; ERMS , embryonal rhabdomyosarcoma; ARMS , alveolar rhabdomyosarcoma. 3.3.2 The Extracellular Matrix and the Tumour Stroma Nine studies investigated a component of the ECM in RMS [39–47], which included adhesion factors [40, 45], Chemokine Receptor 4 (CXCR4) signalling [41, 44], ECM enzymes [42], ECM receptors [43], matrix metalloproteinases (MMPs), [47] platelet derived growth factor receptor (PDGFR) signalling [46], laminin and fibronectin [40, 45], and type IV collagen [45]. No studies investigated these components in FP-RMS or FN-RMS specifically. Laminin and fibronectin are major proteins involved in establishing the architecture of the ECM [58]. Two studies investigated laminin and fibronectin expression in ERMS and ARMS and found opposing results [40, 45]. Saxon et al. [40] reported laminin and fibronectin to be expressed by a higher percentage of ARMS compared to ERMS, whereas Stracca-Pansa et al. [45] reported laminin and fibronectin to be expressed by a higher percentage of ERMS compared to ARMS. Again, the significance of these differences was not reported, and fusion status was not provided. CXCR4 is commonly expressed on tumour cells [59]. Binding to its ligand, stromal cell-derived factor 1 (SDF-1), in the TME, promotes angiogenesis, survival and proliferation of tumour cells and recruitment of immune cells [60, 61]. Vela et al. [41] and Strahm et al [44] investigated CXCR4 expression in ERMS and ARMS and found opposing results. Vela et al. [41] observed CXCR4 staining in 68% of their specimens but reported no difference in CXCR4 expression between ERMS and ARMS. However, Strahm et al. [44] observed a statistically significant increase in CXCR4 expression in ARMS compared to ERMS. Data from across these two studies could not be averaged due to differences in tissue processing techniques and experimental methods. Again, no fusion status was provided. Heparanase, ɑ- and β-dystroglycan, tenascin and thrombospondin, and type IV collagen are all ECM components, known to be important in cancer progression [62–65]. They were investigated by four studies using different methods [40, 42, 43, 45]. None of the studies reported information regarding fusion status. It was reported that there were no differences in the expression of heparanase [42], ɑ- and β-dystroglycan [43], or tenascin and thrombospondin [40], between ERMS and ARMS. However, Martin et al. [43] reported that both subtypes had a significant reduction in ɑ-dystroglycan and laminin binding relative to the control. Type IV collagen, an ECM protein, was expressed in only 14% of ARMS compared to 54% of ERMS [45] and CD44 was expressed in 50% of ERMS, but not at all in ARMS samples [40]. The significance of these results was not reported. MMPs promote tumour cell invasion and metastasis by degrading the surrounding ECM [66]. Diomedi-Camassei et al. [47] reported a significant increase in the expression of MMP-1, MMP-2 and MMP-9 in ARMS compared to ERMS, but no difference in the expression of MMP-3 or MMP-7. Platelet derived growth factors (PDGFs) and their receptors, PDGFRs, are expressed on tumour and stromal cells [67]. Ehnman et al. [46] reported a positive association between PDGFRß stromal staining and ARMS, and a positive association between PDGFRɑ stromal staining and ERMS. Interestingly, they also showed that stromal PDGFRɑ was negatively associated with metastasis, whereas PDGFRß was positively associated with metastasis, reflective of the more aggressive behaviour observed in ARMS. 4 Discussion The composition of the TME plays a crucial role in supporting tumour survival and metastasis and has previously been shown to differ between aggressive and less aggressive cancer subtypes [15, 16]. The role of the PAX-FOXO1 fusion proteins in tumorigenesis lacks understanding, but FP-RMS is associated with a much more aggressive and metastatic nature compared to FN-RMS [8], which could be linked to differences in their TMEs. Therefore, the aim of this systematic review was to use systematic review methodology to identify and evaluate current literature investigating the TME in patient-derived, paediatric FP-RMS, FN-RMS/ERMS and ARMS in order to identify potential differences in the TME between the fusion subtypes. This review identified significant differences in CD163 + macrophages [53], MMPs [50] and stromal PDGFRɑ/ß [49] between ARMS and ERMS. An increase in T cell dysfunction and NECTIN-3 expression was reported in FP-RMS, with an increase in gene sets relating to PD-1 signalling and T cell exhaustion [4]. Genes relating to IFN response were enriched in FN-RMS samples [4]. There were no differences in the expression of ɑ/β-dystroglycan, thrombospondin, tenascin or heparanase expression between ERMS and ARMS [43, 45, 46, 48]. There were also no differences identified in the proportion of T cells, NK cells, myeloid cells or B cells based on fusion status [4]. PD-L1 expression [41, 52, 55], CXCR4 expression [44, 47], laminin and fibronectin [43, 48] expression were variable between studies. 4.1 The Immune Microenvironment The immune microenvironment plays a crucial role in the elimination of tumours, however, tumours can evade the immune response by mechanisms such as immunosuppression and inducing T cell dysfunction [68]. TAMs are an immunosuppressive immune cell and have a direct role in the proliferation, invasion and metastasis of tumours [69]. Previous studies have shown that an increased infiltration of CD163 + TAMs, associated with an M2 phenotype, is associated with more advanced tumours with poorer prognosis [70].Consistent with the literature, this review found that the expression of CD163 + TAMs was significantly increased in ARMS compared to ERMS [50], suggestive of a more immunosuppressive TME in ARMS. This difference may be driven by the PAX-FOXO1 fusion protein, present in the ARMS subtype. DeMartino et al. [4] reported no difference in the proportion of macrophages based on fusion status [4]. Current literature has shown that cancer subtypes with more favourable prognosis are associated with a higher infiltration of CD8 + T cells [71]. In contrast to this, Thakur et al. [51] reported no significant difference in CD8 expression between ARMS and ERMS. But, since a small proportion of ARMS are fusion negative and are biologically and clinically indistinct from ERMS, these results could be confounded by the presence of FN-ARMS. This highlights the limitation of missing fusion status data. Despite an infiltration of cytotoxic CD8 + T cells, tumours can evade the immune response by inducing T cell dysfunction [72]. T cell dysfunction was more prevalent in FP-RMS, and correlated with an enrichment of genes related to T cell exhaustion and PD-1 signalling, as well as an upregulation of NECTIN-3 on FP-RMS cells [4]. These results suggest a reduction in the activity of cytotoxic T cells in FP-RMS, which may be contributing to its poor prognosis. This is reflective of current knowledge that immune evasion is a crucial mechanism contributing to tumour progression and metastasis [73]. Similar to DeMatino et al’s [4] study reporting an increase in PD-1 signalling in FP-RMS, Chowdhury et al’s [52] study showed PD-L1 to be expressed by a higher percentage of ARMS cells compared to ERMS cells. This suggests an increase in PD-L1 expression associated with the presence of the fusion gene, potentially contributing to the aggressive and metastatic nature of FP-RMS. This correlates with previous research showing PD-L1 expression to be increased in metastatic tumours compared to primary tumours [74]. However, the significance of Chowdhury et al’s [52] findings were not reported. DeMartino et al’s [4] study found that cells of FN-RMS tumours were enriched with IFN response and stimulation gene signatures, indicative of an IFN response in these tumours, which may be contributing to the better prognosis observed in FN-RMS patients. IFNs are potent drivers of the anti-tumour immune response and play a critical role in shaping the TME [75]. DeMartino et al. [4] identified that IFN stimulated CD4 + T helper cells (ISG+) were found almost exclusively in FN-RMS tumours, reflective of IFNs role in promoting a Th1 phenotype of CD4 + T cells [4, 75]. Future research should further investigate IFN activity and the resulting impacts it has on the immune cells of the TME between fusion subtypes. This could provide insight into how distinct immune responses contribute to differences in prognosis between FP-RMS and FN-RMS. 4.2 The Extracellular Matrix and the Tumour Stroma Paediatric sarcomas have previously been characterised by high levels of MMPs, which are secreted by various cells of the TME to promote tumour cell migration, invasion and eventually metastasis by degrading the surrounding ECM [76, 77]. Consistent with this, Diomedi-Camassei et al. [47] identified that MMP-1, MMP-2 and MMP-9 were significantly increased in ARMS compared to ERMS, which reflects previous evidence showing that PAX3-FOXO1 may promote a metastatic phenotype by increasing MMP-2 activity [33, 78]. Degradation of the ECM by MMPs involves the loss of basement membrane architecture, of which type IV collagen is a major component [79]. The reduced expression of type IV collagen in ARMS compared to ERMS [45] may therefore be reflective of the increase in MMPs in ARMS/FP-RMS. The interaction of these TME components may therefore be contributing to the more aggressive and metastatic nature of FP-RMS and should be an area of focus for future research. Compared to the immune microenvironment, studies investigating the stromal component of the TME in RMS are lacking. The most abundant component of the tumour stroma are cancer associated fibroblasts (CAFs), however these are largely understudied in many STSs due to a shared mesenchymal origin, making it challenging to distinguish CAFs from malignant mesenchymal cells [80]. However, the tumour stroma, including CAFs, has a role in promoting tumour development, metastasis, and recurrence, and has been correlated with phenotypes of tumour aggression in solid tumours [81]. Therefore, further understanding of the tumour stroma in paediatric RMS may provide valuable information regarding the mechanism of RMS progression, which could provide novel targets for treatment. Thus, future research should aim to overcome the challenges of investigating CAFs, to better characterise the tumour stroma in FP-RMS and FN-RMS. 4.3 Strengths and Limitations The methodology of this review allowed the aim of identifying and evaluating relevant literature to identify differences in the TME between FP-RMS and FN-RMS, to be achieved. The screening of a random selection of titles and abstracts by a second independent reviewer highlighted some discrepancies, which allowed clearer inclusion and exclusion criteria to be developed. For instance, it was decided that studies that did not specify the subtype, or whether samples were paediatric or adult in the abstract, were to be retained for screening of the full text. This ensured that all relevant studies were included. The data extraction was carried out by only one reviewer; however, the data that was extracted was double checked and additional information added during the quality assessment stage, which ensured that all relevant findings were included. In addition, a comprehensive search strategy was developed and translated appropriately between databases to ensure that all possible relevant literature were identified. Furthermore, multiple databases were used to search for literature, which is recommended to capture all relevant studies [82]. The three databases used (MEDLINE (Ovid), EMBASE (Ovid), and the Web of Science) were recommended by Barmer et al. [82] to be used for adequate recall, precision and number of references. These steps ensured that all relevant literature were identified and included in the review. However, there were also some notable limitations. Firstly, the majority of included studies had small sample sizes, attributed to the rarity of this cancer type. This meant that they lacked statistical power [83], which may explain the lack of difference identified in some TME components between subtypes. Some studies also failed to report if statistical significance was measured, making it difficult to draw conclusions based on their results. Smaller sample sizes also increase the chance of random variations in results [84], which could explain the contrasting results found between CXCR4 expression [41, 44], and laminin and fibronectin [40, 45] between studies. This review looked at both histology and fusion status in order to identify differences in the TME between FP-RMS and FN-RMS. This approach was chosen as many studies still rely on RMS histology, which has historically been used to classify RMS. Additionally, since the majority of ARMS are fusion positive, and all ERMS are fusion negative, analysing differences in the TME between ERMS and ARMS could offer insights into differences between FP-RMS and FN-RMS. However, the absence of fusion status information in the included studies was a major limitation of this approach as it could not be determined whether differences in the TME between ERMS and ARMS were driven by the presence of the fusion gene in the ARMS samples. Absence of fusion status information could also contribute to the reporting of no difference in the TME between ERMS and ARMS, which could be confounded by the potential presence of FN-ARMS. Furthermore, a third subtype of RMS, known as spindle cell/sclerosing RMS (SS-RMS) has only recently been separated from the ERMS subtype, defined as a separate pathologic entity in the WHO 2013 classification of soft tissue and bone tumours [85, 86]. SS-RMS can be further classified by the presence of a MYOD1 mutation, associated with a highly lethal outcome and unfavourable behaviour, which is comparable to ARMS [85]. Therefore, the possible presence of this RMS subtype in the ERMS samples, particularly in the older studies, may have contributed to a lack of difference in the TME reported between ERMS and ARMS. This review also highlighted a lack of standardisation of methods used to analyse some components of the TME, contributing to variability in results and preventing data from multiple studies being averaged. For instance, Bertolini et al. [38] and Gabrych et al. [49] detected PD-L1 expression only on tumour associated immune cells, while Chowdhury et al. [52] detected it on ARMS and ERMS tumour cells. Similar inconsistencies regarding PD-L1 expression have been found in previous research, which has been attributed to the use of different antibodies across studies [74]. Bertolini et al. [38] and Gabrych et al [49] used SP142 antibody and 22C3 clone to detect PD-L1 expression, whereas Chowdhury et al. [52] used anti-CD274. To draw more reliable conclusions, more standardised methods should be used across studies. 5 Conclusion This systematic review has highlighted that research regarding the TME in FP-RMS and FN-RMS is still in its infancy, with single-cell studies, such as DeMartino et al’s [4] study, only beginning to highlight potential differences between these fusion subtypes. Because of this, there was insufficient evidence to draw robust conclusions about differences in the TME between FP-RMS and FN-RMS specifically. Findings based on histological subtypes suggest there may be differences linked to fusion status. But due to the fusion status being unknown in the majority of studies, further research is needed to confirm this. Future research should therefore prioritise investigating fusion subtypes over histological subtypes, since fusion status is now recognised to classify RMS and predict prognosis more accurately. It can also be recommended that an updated version of this systematic review be conducted as more data on the TME in FP-RMS and FN-RMS becomes available. Since the TME plays a crucial role in tumour progression, understanding it’s composition, in relation to fusion status, will improve our knowledge of how the PAX-FOXO1 fusion gene contributes to tumorigenesis and a poorer prognosis seen in FP-RMS patients. Ultimately, this could identify novel targets and aid in the development of novel treatment strategies to improve patient outcomes. Declarations Funding: Open access funding provided by University of Southampton Library. ZSW has funding from Children with Cancer UK and the CRIS Cancer Foundation, CP is funded by University of Southampton. Author contributions: Conceptualization, M.R. and Z.S.W.; methodology, M.R., C.P. and Z.S.W.; investigation, M.R.; resources, M.R., C.P., T.J.U., and Z.S.W.; writing—original draft preparation, M.R.; writing—review and editing, M.R., C.P., T.J.U., and Z.S.W.; visualisation, M.R. and Z.S.W.; supervision, C.P. and Z.S.W.; project administration, M.R. and Z.S.W. All authors have read and agreed to the published version of the manuscript. Acknowledgements: ZSW has funding from Children with Cancer UK and the CRIS Cancer Foundation, CP is funded by University of Southampton References Hawkins DS, Spunt SL, Skapek SX. Children's Oncology Group's 2013 blueprint for research: Soft tissue sarcomas. Pediatr Blood Cancer. 2013;60(6):1001-8. Tenente IM, Hayes MN, Ignatius MS, McCarthy K, Yohe M, Sindiri S, et al. Myogenic regulatory transcription factors regulate growth in rhabdomyosarcoma. Elife. 2017;6. Ciesla M, Dulak J, Józkowicz A. 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2","display":"","copyAsset":false,"role":"figure","size":23385,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7796884/v1/92585bf5320c3dd3cdb65936.png"},{"id":93151545,"identity":"329e58f3-9939-47ad-9dd6-1d9460f7dac9","added_by":"auto","created_at":"2025-10-09 14:50:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1418273,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7796884/v1/fb79cca0-aaaf-4ab2-afdf-82cff72c6d17.pdf"},{"id":93148151,"identity":"d09b7019-187f-46ad-9de2-9ea20d459f6e","added_by":"auto","created_at":"2025-10-09 14:18:39","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":62116,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7796884/v1/1f280320cc1f02a935dee3eb.png"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eThe Tumour Microenvironment in Paediatric Rhabdomyosarcomas: A Systematic Review\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1 Paediatric Rhabdomyosarcoma\u003c/h2\u003e\u003cp\u003eRhabdomyosarcoma (RMS) is the most common type of soft tissue sarcoma (STS) in children, with an incidence of 4.3 cases per million a year worldwide [1]. Tumours express myogenic regulatory transcription factors (MRFs), which suggest they are of myogenic origin and occur because of abnormal skeletal muscle differentiation [2\u0026ndash;4].\u003c/p\u003e\u003cp\u003eHistorically, RMS has been divided into alveolar, embryonal, pleomorphic and sclerosing subtypes, based on histological features. Embryonal (ERMS) and Alveolar (ARMS) subtypes are the most common in children [4]. However, more recently, RMS has been defined by molecular characterisation. Up to 80% of ARMS are fusion positive, characterised by a chromosomal translocation between FOXO1 on chromosome 13 and either PAX3 on chromosome 2 (t(2;13)(q35;q14) [5], or PAX7 on chromosome 1 (t(1;13)(p36;q14) [6]. This results in the expression of more potent transcription factors PAX3-FOXO1 (in 55% of ARMS) or PAX7-FOXO1 (in 22% of ARMS) [7], leading to the classification of either fusion positive RMS (FP-RMS) or fusion negative RMS (FN-RMS). The presence of the PAX-FOXO1 fusion is now known to have a primary role in RMS progression and drives an unfavourable outcome for children [8, 9]. FP-RMS have a significantly poorer overall survival, event free survival, and a higher frequency of metastasis compared to FN-RMS [8], making it more clinically aggressive. The fusion gene is also associated with disease recurrence, which decreases patient survival rate from 70%, after current multimodal therapy, to 20% [10, 11]. This highlights the need for novel and improved treatment strategies for FP-RMS patients.\u003c/p\u003e\u003cp\u003eHistology was traditionally used to predict prognosis, as the International Classification of Rhabdomyosarcoma (ICR) identified ARMS as having a poorer prognosis compared to ERMS [9]. But recent evidence has shown that fusion negative ARMS (FN-ARMS) is molecularly and clinically indistinguishable from ERMS [8]. Therefore, classifying RMS based on fusion status, rather than histology, may be more prognostically significant.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2 The Tumour Microenvironment\u003c/h2\u003e\u003cp\u003eThe tumour microenvironment (TME) plays a crucial role in tumour initiation, progression and metastasis [12, 13]. It consists of cancerous cells, as well as non-malignant host cells, including stromal cells (fibroblasts, endothelial cells, and pericytes), immune cells (CD8\u0026thinsp;+\u0026thinsp;T cells, natural killer (NK) cells, dendritic cells (DCs) and macrophages) and the extracellular matrix (ECM); a non-cellular component, which comprises of a complex mixture of collagens, laminins, glycoproteins and proteoglycans [14, 15].\u003c/p\u003e\u003cp\u003eCancer cells communicate with the surrounding non-malignant components of the TME, stimulating changes in their function that promote tumour progression [15, 16]. The stroma is essential for maintaining the integrity of normal tissues, however, malignancy is associated with changes in the stroma, leading to tumour growth, invasion and metastasis [17]. Furthermore, the immune microenvironment has a critical role in the surveillance and elimination of tumours, however, interactions between tumour cells and components of the immune TME can lead to immunosuppression and immune escape [18].\u003c/p\u003e\u003cp\u003eThe immune TME can be grouped into pro-tumour and anti-tumour components (Fig.\u0026nbsp;1). Anti-tumour immune cells include CD8\u0026thinsp;+\u0026thinsp;T cells, NK cells, DCs and M1 polarised macrophages, which are associated with improved patient outcome in a variety of cancers [18\u0026ndash;22]. Pro-tumour immune cells include regulatory T cells (T-regs), myeloid derived suppressor cells (MDSCs) and M2 polarised macrophages, which are associated with tumour progression, invasion and metastasis, resulting in poor patient prognosis [18, 23\u0026ndash;28]. Advanced understanding of the TME has shifted the treatment of cancer, from direct targeting of tumour cells, to targeting the TME [12].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePrevious studies have identified differences in the TME between cancer subtypes, which may shape their prognostic differences [13]. For example, HER2-positive breast cancer is associated with a higher immune score and immune infiltration compared to luminal A and luminal B subtypes [29]. The intensity of collagen type III staining has also been reported to vary between histological STS subtypes [30]. It was thus suggested that these differences in the TME between cancer subtypes may reflect their prognostic differences. In sarcomas, differences in the TME can be attributed to the presence of a fusion gene. For example, by comparing Myxoid Liposarcoma cells with or without the FUS::DDIT3 fusion protein, Ranji et al. [31] identified FUS::DDIT3 regulated genes involved in cell-cell and cell-ECM interactions, including those involved in ECM organisation.\u003c/p\u003e\u003cp\u003eThere is a lack of understanding of how the presence of the PAX-FOXO1 fusion protein contributes to tumorigenesis and increased clinical aggression in the FP-RMS subtype [32]. Previous studies using genome wide screens have reported PAX-FOXO1 to exert oncogenic effects by the altered transcription of PAX3 target genes, which are involved in cell survival, myogenic differentiation and mesodermal development [32, 33]. While these studies have attempted to identify these individual genes, many still require validation and further study for their role in FPRMS progression [32]. In addition, these studies were also confounded by the inclusion of RMS with unknown fusion status [32]. It has also been concluded that PAX-FOXO1 alone is not sufficient to cause transformation [32]. Therefore, further work is required to precisely define the mechanisms underlying how the PAX-FOXO1 fusion proteins contribute to tumorigenesis. Since the TME has a crucial role in tumour progression, identifying differences between FP-RMS and FN-RMS may help to determine whether the TME contributes to more malignant behaviour in FP-RMS. This may in turn help identify novel targets for development of more effective treatment strategies for this FP-RMS patients.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e1.3 Hypothesis, Aims and Objectives\u003c/h2\u003e\u003cp\u003eThis systematic review asked whether there were differences in the TME between paediatric FP-RMS and FN-RMS. Histological subtype was investigated to infer differences in the TME between fusion subtypes as histology has historically been used to classify RMS subtypes, rather than fusion status. Additionally, since the majority (around 80%) of ARMS are fusion positive, analysing TME differences between ERMS (which are fusion negative) and ARMS, could offer surrogate insights into differences between FP-RMS and FN-RMS.\u003c/p\u003e\u003cp\u003eThe aim of this systematic review was to identify and evaluate current literature investigating the TME in patient-derived, pediatric FP-RMS and FN-RMS/ ARMS and ERMS, to identify any differences in the stromal, immune, and ECM components between FP-RMS and FN-RMS. Since the TME influences tumor aggression [34], we hypothesized that, after synthesizing existing data from all available relevant studies of patient-derived samples, there would be a difference in the expression, proportion, number, type, and composition of immune, stromal, and ECM components between pediatric FNRMS and the more clinically aggressive FPRMS.\u003c/p\u003e\u003c/div\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Search Strategy\u003c/h2\u003e\u003cp\u003eA systematic search of the literature (between 1994 and 2023) was conducted on three main databases: The Web of Science, MEDLINE (Ovid) and EMBASE (Ovid), with the help of a librarian at the University of Southampton. The Web of Science was searched using only free text terms, whereas EMBASE and MEDLINE were searched using both free text terms and subject heading terms. The search terms used across each database is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Searches were limited to English language publications across all databases. In the Web of Science, searches were additionally restricted to published articles and in EMBASE, pre-print records were removed. This systematic review followed the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSearch strategy used for the systematic search of the literature\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDatabase (platform)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSearch Strategy\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeb of Science\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(microenvironment OR matrix OR niche OR \"tum*r microenvironment\" OR \"immune cell\u003cspan\u003e$\u003c/span\u003e\" OR stroma OR \"extracellular matrix\" OR \"cancer associated fibroblast\u003cspan\u003e$\u003c/span\u003e\" OR \"tum*r infiltrating lymphocyte\u003cspan\u003e$\u003c/span\u003e\" OR \"immune microenvironment\" OR immune OR \"tum*r immunology\")\u0026nbsp;AND (rhabdomyosarcoma*) AND (paediatric* OR pediatric* OR child* OR infant* OR adolescen*)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMEDLINE (Ovid)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emicroenvironment or matrix or niche or \"tumo?r microenvironment\" or \"immune cell\u003cspan\u003e$\u003c/span\u003e\" or stroma or \"extracellular matrix\" or \"cancer associated fibroblast\u003cspan\u003e$\u003c/span\u003e\" or \"tumo?r infiltrating lymphocyte\u003cspan\u003e$\u003c/span\u003e\" or \"immune microenvironment\" or immune or \"tumo?r immunology\" or tumor microenvironment/ or fibroblasts/ or cancer-associated fibroblasts/ or myofibroblasts/ or macrophages/ or tumor-associated macrophages/ or stromal cells/ or extracellular matrix/ or cancer-associated fibroblasts/ or -lymphocytes/ or lymphocytes, tumor-infiltrating/ or immune evasion/ or immune checkpoint inhibitors/ or immune system/ or immunotherapy/) AND (rhabdomyosarcoma* or exp rhabdomyosarcoma/) AND (paediatric* or pediatric* or child* or infant* or adolescen*.mp. or infant/ or child/ or adolescent/ or pediatrics/)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEMBASE (Ovid)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(microenvironment or matrix or niche or \"tumo?r microenvironment\" or \"immune cell\u003cspan\u003e$\u003c/span\u003e\" or stroma or \"extracellular matrix\" or \"cancer associated fibroblast\u003cspan\u003e$\u003c/span\u003e\" or \"tumo?r infiltrating lymphocyte\u003cspan\u003e$\u003c/span\u003e\" or \"immune microenvironment\" or immune or \"tumo?r immunology\" or tumor microenvironment/ or exp stroma cell/ or stroma cell/ or bone marrow stroma cell/ or stroma/ or mesenchymal stroma cell/ or extracellular matrix/ or cancer associated fibroblast/ or exp tumor associated leukocyte/ or tumor microenvironment/ or immune evasion/ or immune system/ or immune dysregulation/ or immune signaling/ or immune response/ or immune checkpoint inhibitor/ or exp tumor immunology/) AND (rhabdomyosarcoma* or rhabdomyosarcoma/ or alveolar rhabdomyosarcoma/ or embryonal rhabdomyosarcoma/) AND (paediatric* or pediatric* or child* or infant* or adolescen* or pediatrics/ or child/ or hospitalized child/ or child hospitalization/ or adolescent disease/ or adolescent/ or hospitalized adolescent/)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Inclusion and Exclusion Criteria\u003c/h2\u003e\u003cp\u003eInclusion and exclusion criteria were developed based on the PICO framework (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Studies were included if they met the following criteria: a) reported patient-derived data from paediatric ARMS or ERMS/FP-RMS or FN-RMS (patient-derived data included patient-derived cell culture, patient-derived organoids and patient-derived tissue slice cultures) b) characterised a component(s) of the TME. Histological subtype and fusion subtype were included, as many studies still rely on histology to classify RMS. Paediatric was defined as children and young adults up to the age of 21.\u003c/p\u003e\u003cp\u003eStudies were excluded if they: a) reported data from adult RMS; b) reported data from animal models, cell lines, or patient-derived xenograft models; c) did not characterise a component of the TME (or were not relevant to the TME); d) reported data from pleomorphic or sclerosing subtypes. If studies did not specify the subtype of RMS, or whether samples were paediatric or adult in their abstracts, they were retained at the abstract screening stage. If not specified in their full text, they were excluded. Adult RMS was excluded, as it is much rarer and has a different prognosis compared to its paediatric counterparts [35].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePICO framework and inclusion and exclusion criteria used for screening\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePICO framework\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInclusion criteria\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExclusion criteria\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePopulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePaediatric\u003csup\u003ea\u003c/sup\u003e RMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003epaediatric ARMS or ERMS/FPRMS or FNRMS patient-derived data which includes:\u003c/p\u003e\u003cp\u003e- Patient-derived cell culture\u003c/p\u003e\u003cp\u003e- Patient-derived organoids\u003c/p\u003e\u003cp\u003e- Patient-derived tissue slice cultures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAdult RMS\u003c/p\u003e\u003cp\u003eAnimal and cell line models\u003c/p\u003e\u003cp\u003ePatient-derived xenografts\u003c/p\u003e\u003cp\u003eStudies that don\u0026rsquo;t separate RMS results from other sarcoma results.\u003c/p\u003e\u003cp\u003eIf study doesn\u0026rsquo;t specify whether the samples are from paediatric or adult patients, exclude at full text screening stage.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe TME\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eData that characterises a component(s) of the TME\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStudies that do not describe the TME\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComparator\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe TME in FPRMS versus FNRMS or ERMS versus ARMS.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eData from either ARMS or ERMS/FPRMS FNRMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStudies that do not specify the subtype of RMS to be excluded only at the full text screening stage.\u003c/p\u003e\u003cp\u003eStudies that group results from multiple subtypes together, to be excluded at the full text stage only.\u003c/p\u003e\u003cp\u003ePleomorphic or sclerosing subtypes.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDifferences in the TME between subtypes.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExpression, number, proportion, type and composition of immune, stromal and ECM components of the TME.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMeeting abstracts\u003c/p\u003e\u003cp\u003eReviews\u003c/p\u003e\u003cp\u003eNot full text articles\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Paediatric includes children and young adults up to the age of 21.\u003c/p\u003e\u003cp\u003e\u003cem\u003eRMS\u003c/em\u003e, Rhabdomyosarcoma; \u003cem\u003eTME\u003c/em\u003e, Tumour microenvironment; \u003cem\u003eFPRMS\u003c/em\u003e, fusion-positive rhabdomyosarcoma; \u003cem\u003eFNRMS\u003c/em\u003e, fusion-negative rhabdomyosarcoma; \u003cem\u003eARMS\u003c/em\u003e, alveolar rhabdomyosarcoma; \u003cem\u003eERMS\u003c/em\u003e, embryonal rhabdomyosarcoma.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.3 The Selection Process\u003c/h2\u003e\u003cp\u003eReferences identified from the search were exported to Rayyan (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://rayyan.qcri.org/\u003c/span\u003e\u003cspan address=\"http://rayyan.qcri.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and de-duplicated. Rayyan was used to screen all titles and abstracts against the inclusion and exclusion criteria as stated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, to identify those that were potentially relevant. A random selection of 22 titles and abstracts were independently screened by a second reviewer. Any discrepancies were discussed and resolved. Full text papers were obtained using Endnote or manually searched for using the Web of Science, MEDLINE (Ovid) or EMBASE (Ovid). Some were not obtained due to the University not having access. Full texts were further screened against the inclusion and exclusion criteria to assess their relevance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Data Extraction\u003c/h2\u003e\u003cp\u003eData extracted from the included studies included: a) first author and year; b) study aims; c) tissue processing technique; d) histological subtype and the number of samples of each; e) fusion status and the number of samples of each; f) patient age; g) the experimental method(s) used; h) the component(s) of the TME analysed; i) the key findings. In Chen et al\u0026rsquo;s [36] study, key findings regarding their ARMS samples were not extracted, as not all samples were paediatric. Data extraction was conducted by one independent reviewer. Due to the heterogeneity in the methods used and the results reported among the studies, a meta-analysis could not be conducted, so the results were reported descriptively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Quality Assessment\u003c/h2\u003e\u003cp\u003eTo assess the quality of each included study, the Risk of Bias in Non-randomised Studies of Interventions (ROBINS-I) tool was used, which included seven domains of bias: confounding bias, selection bias, information bias, performance bias, detection bias, reporting bias and bias due to missing data. The Cochrane Online Handbook for Systematic Reviews [37] was also used to help further clarify bias definitions. Studies were scored with either a low, moderate, serious or critical risk of bias. Results of the quality assessment are presented in Supplementary Table S1.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Study Selection\u003c/h2\u003e\u003cp\u003eThe initial database search identified 1,287 references in line with the initial search strategy. Of these, 211 were identified from the Web of Science, 321 from MEDLINE (Ovid) and 755 from EMBASE (Ovid). Following exportation to Rayyan, 431 duplicate records were removed, yielding a total of 856 references to be screened. The titles and abstracts were screened against the inclusion and exclusion criteria, which resulted in the exclusion of 727 references. Of the remaining 129, nine full text papers could not be retrieved, leaving 120 full texts to which inclusion criteria was applied. Full text screening resulted in 103 references being excluded. Full texts were excluded due to not meeting either the population criteria (n\u0026thinsp;=\u0026thinsp;36), the intervention criteria (n\u0026thinsp;=\u0026thinsp;15), the comparator criteria (n\u0026thinsp;=\u0026thinsp;11) or were not full text articles (n\u0026thinsp;=\u0026thinsp;41). Following study selection, 17 studies were included in this systematic review. The PRISMA flowchart of this selection process is presented in Fig.\u0026nbsp;2. The study characteristics of these included studies are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and the key findings are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Study Characteristics\u003c/h2\u003e\u003cp\u003eThe 17 included studies were published between 1994 and 2023. Of these studies, only three included fusion status [4, 36, 38], the rest included only histological subtype (ERMS and ARMS). Nine studies investigated the ECM and the stroma [39\u0026ndash;47], another nine investigated the immune microenvironment [4, 36, 38, 39, 48\u0026ndash;52], and one study investigated both aspects [39]. The most frequently used sample type was Formalin-Fixed, Paraffin-Embedded (FFPE) tissue, which was used by just over half of the studies (56%) [36, 38, 40, 41, 45, 47, 48, 51, 52]. Only one study used patient-derived organoids [4]. Data from patient-derived samples, rather than cell lines or animal models, were included for this review, as these better recapitulate the heterogeneity, complexity and pathophysiology of patient tumours and their TMEs [53]. A variety of different methods were used for analysis, with immunohistochemistry (IHC) being the most common (used in 64.7% of studies) [36, 38, 40, 41, 45, 47\u0026ndash;52]. The mean number and the total number of samples per histological subtype and fusion subtype is presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Three studies were excluded from the mean calculation for ERMS due to missing sample size data [4, 50, 51]. Five studies were excluded from the mean calculation for ARMS due to three having missing sample size data [4, 50, 51], and two studies not including ARMS samples [36, 39].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKey characteristics of the studies included in the review\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirst author, year\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStudy Aims\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTissue processing technique\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHistological subtype (number of samples)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFusion status (number of samples)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAge of Patients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMethods used for analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eComponent(s) of TME investigated\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChen et al.\u003c/p\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[36]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePerform an in-depth interrogation of the tumour immune microenvironment of STS to identify immunotherapy agents.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE tumour tissue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFP (50)\u003c/p\u003e\u003cp\u003eFN (63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eERMS:\u003c/p\u003e\u003cp\u003erange\u0026thinsp;=\u0026thinsp;0.02-22\u003c/p\u003e\u003cp\u003emean\u0026thinsp;=\u0026thinsp;7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eIHC\u003c/p\u003e\u003cp\u003eRNA sequencing\u003c/p\u003e\u003cp\u003egene expression analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eImmune microenvironment\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBertolini et al.\u003c/p\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[38]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFurther describe the immune microenvironment of RMS by evaluating PD-L1 expression.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE RMS tissue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (13)\u003c/p\u003e\u003cp\u003eARMS (11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFP (7)\u003c/p\u003e\u003cp\u003eFN (18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eIHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eImmune microenvironment \u003c/p\u003e\u003cp\u003ePD-L1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eXu et al.\u003c/p\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[39]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDelineate the testicular ERMS intra-tumoral heterogeneity and TME.\u003c/p\u003e\u003cp\u003eAnalyse the role of each subpopulation of cells in the progression of testicular ERMS.\u003c/p\u003e\u003cp\u003eAnalyse the relationship between macrophages and ERMS tumour cells.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFresh tumour tissue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSingle cell RNA sequencing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eMacrophages\u003c/p\u003e\u003cp\u003eMyoid cells\u003c/p\u003e\u003cp\u003eEndothelial cells\u003c/p\u003e\u003cp\u003eFibroblasts\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eXia et al.\u003c/p\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[48]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEvaluate potential indicators of TME status changes. \u003c/p\u003e\u003cp\u003eCorrelate immune infiltration with low and high expression of MD2L1 and CCNB2 expressing populations in RMS samples.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eParaffin embedded RMS samples.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (14)\u003c/p\u003e\u003cp\u003eARMS (12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eStudy from which the dataset was from:\u003c/p\u003e\u003cp\u003emean\u0026thinsp;=\u0026thinsp;7\u003c/p\u003e\u003cp\u003erange\u0026thinsp;=\u0026thinsp;0\u0026ndash;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eBioinformatics\u003c/p\u003e\u003cp\u003eIHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eImmune infiltration\u003c/p\u003e\u003cp\u003eMD2L1\u003c/p\u003e\u003cp\u003eCCNB2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaxon et al.\u003c/p\u003e\u003cp\u003e1997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[40]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInvestigate the presence of adhesion factors laminin, fibronectin, tenascin, thrombospondin and CD44 in paediatric RMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eParaffin embedded samples\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (6)\u003c/p\u003e\u003cp\u003eARMS (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eARMS:\u003c/p\u003e\u003cp\u003eaverage\u0026thinsp;=\u0026thinsp;11.6 years.\u003c/p\u003e\u003cp\u003eRange\u0026thinsp;=\u0026thinsp;6-15.4 years.\u003c/p\u003e\u003cp\u003eERMS:\u003c/p\u003e\u003cp\u003eaverage\u0026thinsp;=\u0026thinsp;6 years\u003c/p\u003e\u003cp\u003erange\u0026thinsp;=\u0026thinsp;2.4\u0026ndash;8.2 years.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eIHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAdhesion molecules:\u003c/p\u003e\u003cp\u003eLaminin\u003c/p\u003e\u003cp\u003eFibronectin\u003c/p\u003e\u003cp\u003eTenascin\u003c/p\u003e\u003cp\u003eThrombospondin\u003c/p\u003e\u003cp\u003eCD44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGabrych et al.\u003c/p\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[49]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAssess PD-L1 and PD-1 expression in paediatric RMS and to investigate their clinicopathological associations.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiopsy samples\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (19)\u003c/p\u003e\u003cp\u003eARMS (12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eRange\u0026thinsp;=\u0026thinsp;1 day-18 years.\u003c/p\u003e\u003cp\u003eMedian\u0026thinsp;=\u0026thinsp;7.4 years.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eIHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ePD-L1 and PD-1 expression\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVela et al.\u003c/p\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[41]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnalysed CXCR4 expression in tumour samples from paediatric RMS patients.\u003c/p\u003e\u003cp\u003eUsed an orthotopic model of ARMS to evaluate the complementary antitumoral and antimetastatic effects of combined NKAE\u0026thinsp;+\u0026thinsp;MDX1338 immunotherapy in vivo.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE tumour samples.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (15)\u003c/p\u003e\u003cp\u003eARMS (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eERMS:\u003c/p\u003e\u003cp\u003emean\u0026thinsp;=\u0026thinsp;5.1\u003c/p\u003e\u003cp\u003erange\u0026thinsp;=\u0026thinsp;0.2-13\u003c/p\u003e\u003cp\u003eARMS:\u003c/p\u003e\u003cp\u003emean\u0026thinsp;=\u0026thinsp;9.8\u003c/p\u003e\u003cp\u003erange\u0026thinsp;=\u0026thinsp;7.5\u0026ndash;11.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eIHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCXCR4 expression\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMasola et al.\u003c/p\u003e\u003cp\u003e2009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[42]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnalyse HPSE expression and activity in ARMS and ERMS and investigate the relationship of the different metastatic phenotypes of ARMS and ERMS with expression and activity of HPSE.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePlasma and tumour RNA collected from RMS patients.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (10)\u003c/p\u003e\u003cp\u003eARMS (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;6.3 years\u003c/p\u003e\u003cp\u003eRange\u0026thinsp;=\u0026thinsp;1\u0026ndash;15 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHPSE mRNA expression was evaluated by real time PCR.\u003c/p\u003e\u003cp\u003eHPSE activity determined by ELISA method.\u003c/p\u003e\u003cp\u003ePlasma assay\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eHPSE\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeng et al.\u003c/p\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[50]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (N/A)\u003c/p\u003e\u003cp\u003eARMS (N/A)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMorphology and number of TAMs examined by IHC.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eTAMs\u003c/p\u003e\u003cp\u003eAPN\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeMartino et al.\u003c/p\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[4]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCompile a single cell transcriptomic atlas comprising both FPRMS and FNRMS and to find distinct differences in cellular composition and differentiation states which relate to clinical outcomes.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eViably frozen primary RMS tumour samples\u003c/p\u003e\u003cp\u003ePatient-derived tumour organoid models\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFP (13)\u003c/p\u003e\u003cp\u003eFN (13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15 samples were \u0026lt;\u0026thinsp;10 years\u003c/p\u003e\u003cp\u003e12 samples were \u0026gt;\u0026thinsp;10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eSingle cell mRNA sequencing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eImmune microenvironment\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMartin et al.\u003c/p\u003e\u003cp\u003e2007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[43]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnalyse dystroglycan expression and glycosylation in paediatric solid tumours and demonstrate alterations in ɑ-dystrogycan in paediatric RMS (and others).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSnap frozen unfixed tumour samples\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eImmunoblot:\u003c/p\u003e\u003cp\u003eERMS (2)\u003c/p\u003e\u003cp\u003eARMS (1)\u003c/p\u003e\u003cp\u003eImmunostaining:\u003c/p\u003e\u003cp\u003eERMS (23)\u003c/p\u003e\u003cp\u003eARMS (14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e:\u003c/p\u003e\u003cp\u003eERMS:\u003c/p\u003e\u003cp\u003emean\u0026thinsp;=\u0026thinsp;4.5 years (5\u0026thinsp;+\u0026thinsp;4)\u003c/p\u003e\u003cp\u003eARMS:\u003c/p\u003e\u003cp\u003eage\u0026thinsp;=\u0026thinsp;9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eImmunoblot for dystroglycan expression.\u003c/p\u003e\u003cp\u003eImmunostaining on tissue microarrays.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eGlycosylated dystroglycan\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThakur et al.\u003c/p\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[51]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInvestigate the immune microenvironment of five major paediatric cancers:\u003c/p\u003e\u003cp\u003eEwing sarcoma, osteosarcoma, RMS, medulloblastoma, neuroblastoma, and correlated with overall survival.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE sections\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (N/A)\u003c/p\u003e\u003cp\u003eARMS (N/A)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0\u0026ndash;17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eGene expression analysis\u003c/p\u003e\u003cp\u003eIHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eImmune microenvironment\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStrahm et al.\u003c/p\u003e\u003cp\u003e2008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[44]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTo investigate the role of the bone marrow microenvironment on RMS signalling and behaviour through the CXCR4/SDF-1ɑ pathway.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePatient RNA samples\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (7)\u003c/p\u003e\u003cp\u003eARMS (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRT-PCR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eBone marrow stroma\u003c/p\u003e\u003cp\u003e- CXCR4/SDF-1ɑ metastatic signalling\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStracca-Pansa et al.\u003c/p\u003e\u003cp\u003e1994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[45]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnderstand ECM elements in small round cell tumour tissue and to investigate the detection of these elements by IHC on tumours from patients.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE tissue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (15)\u003c/p\u003e\u003cp\u003e ARMS (9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eRange\u0026thinsp;=\u0026thinsp;0.5\u0026ndash;23\u003c/p\u003e\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;7.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eIHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eECM:\u003c/p\u003e\u003cp\u003e- Laminin\u003c/p\u003e\u003cp\u003e- Type IV collagen\u003c/p\u003e\u003cp\u003e- Fibronectin\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEhnman et al.\u003c/p\u003e\u003cp\u003e2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[46]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIdentify biological activities linked to PDGF signalling in RMS models and human sample collections.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (261)\u003c/p\u003e\u003cp\u003eARMS (50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMicroarray analysis on 3 x tissue microarrays\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ePDGFRɑ and PDGFRβ\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiomedi-camassei et al.\u003c/p\u003e\u003cp\u003e2004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[47]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTo assess the expression of MMPs in RMS and to evaluate the correlation with clinicopathologic parameters.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE tissue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (21)\u003c/p\u003e\u003cp\u003eARMS (12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;85+/- 54 months\u003c/p\u003e\u003cp\u003eRange\u0026thinsp;=\u0026thinsp;2-175 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eIHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eMMPs\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChowdhury et al.\u003c/p\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e[52]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReport the frequency of PD-L1 expression in paediatric malignancies and to assess the frequency of tumour infiltrating CD8\u0026thinsp;+\u0026thinsp;cytotoxic T-lymphocytes and their levels of PD-1 expression.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFPE primary tumour samples.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERMS (18)\u003c/p\u003e\u003cp\u003eARMS (15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eERMS:\u003c/p\u003e\u003cp\u003emedian\u0026thinsp;=\u0026thinsp;6.5\u003c/p\u003e\u003cp\u003erange\u0026thinsp;=\u0026thinsp;1.3-16.2\u003c/p\u003e\u003cp\u003eARMS:\u003c/p\u003e\u003cp\u003emedian\u0026thinsp;=\u0026thinsp;6.0\u003c/p\u003e\u003cp\u003erange\u0026thinsp;=\u0026thinsp;1.2\u0026ndash;12.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eIHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ePD-1/PD-L1 expression\u003c/p\u003e\u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;cytotoxic T cells\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eFFPE\u003c/em\u003e, formalin-fixed paraffin embedded; \u003cem\u003eIHC\u003c/em\u003e, immunohistochemistry; \u003cem\u003eN/A\u003c/em\u003e, data not provided; \u003cem\u003eTME\u003c/em\u003e, tumour microenvironment; \u003cem\u003eRMS\u003c/em\u003e, rhabdomyosarcoma; \u003cem\u003eARMS\u003c/em\u003e, alveolar rhabdomyosarcoma; \u003cem\u003eERMS\u003c/em\u003e, embryonal rhabdomyosarcoma; \u003cem\u003eELISA\u003c/em\u003e, enzyme-linked immunosorbent assay; \u003cem\u003eTAM\u003c/em\u003e, tumour associated macrophages; \u003cem\u003eECM\u003c/em\u003e, extracellular matrix; \u003cem\u003eMMP\u003c/em\u003e, matrix metalloproteinase; \u003cem\u003eFP\u003c/em\u003e, fusion positive rhabdomyosarcoma; \u003cem\u003eFN\u003c/em\u003e, fusion negative rhabdomyosarcoma; \u003cem\u003eSTS\u003c/em\u003e, soft tissue sarcoma; \u003cem\u003eRT-PCR\u003c/em\u003e, reverse transcription polymerase chain reaction; \u003cem\u003ePDGF\u003c/em\u003e, platelet derived growth factor; \u003cem\u003ePDGFRɑ/β\u003c/em\u003e, platelet derived growth factor receptor-ɑ/β\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Study results\u003c/h2\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1 The Immune Microenvironment\u003c/h2\u003e\u003cp\u003eOf the studies investigating the immune microenvironment, macrophages (n\u0026thinsp;=\u0026thinsp;5) [36, 38, 39, 48, 50] and CD8\u0026thinsp;+\u0026thinsp;T cells (n\u0026thinsp;=\u0026thinsp;4) [4, 36, 51] were investigated the most frequently. Other immune components were also investigated, such as B cells [36], CD4\u0026thinsp;+\u0026thinsp;T cells [4, 36], monocytes [4], NK cells [4], DCs [4] and T-regs [4]. Three studies investigated the immune microenvironment in FP-RMS and FN-RMS [4, 36, 38]. Data across studies could not be averaged due to heterogeneity in their methods and results reported.\u003c/p\u003e\u003cp\u003eTumour associated macrophages (TAMS), particularly M2-like TAMs, are an immunosuppressive immune cell of the TME [54]. Two studies investigated the difference in macrophages between the histological subtypes and fusion subtypes [4, 50]. DeMartino et al. [4] reported no difference in the proportion of macrophages between FPRMS and FNRMS, and reported that they existed predominantly in the M2 polarisation state in both fusion subtypes. In contrast, Peng et al. [50] identified a difference in the expression of CD163, a marker specific for M2 macrophages, between ERMS and ARMS, with expression levels being significantly increased in ARMS. The latter study did not provide information regarding fusion status.\u003c/p\u003e\u003cp\u003eCytotoxic CD8\u0026thinsp;+\u0026thinsp;T cells are the primary effector cells of the anti-tumour immune response [55]. Thakur et al. [51] characterised CD8 expression and reported no significant difference between ERMS and ARMS. However, results presented by Chowdhury et al. [52] show a higher mean total CD8\u0026thinsp;+\u0026thinsp;tumour infiltrating lymphocyte (TIL) count in ERMS compared to ARMS, although the significance was not reported. DeMartino et al. [4] reported that interferon (IFN) stimulated CD4\u0026thinsp;+\u0026thinsp;T helper cells (ISG+) were found almost exclusively in FN-RMS tumours, which were enriched for gene signatures related to IFN response and stimulation. They also reported that T cell dysfunction was more prevalent in FPRMS tumours, with CD8\u0026thinsp;+\u0026thinsp;T cells enriched for genes related to PD-1 signalling and T cell exhaustion [4]. In addition, they reported NECTIN-3 to be upregulated on FP-RMS cells, whose interaction with TIGIT on T cells induces T cell dysfunction [56]. Chen et al. [36] found a difference in CD4\u0026thinsp;+\u0026thinsp;memory T cells between fusion subtypes, with a significant increase in FNRMS compared to FPRMS. DeMartino et al. [4] also reported that the proportion of non-malignant cell types, which included T cells, NK cells, DCs, monocytes, and B cells, did not differ significantly based on fusion status.\u003c/p\u003e\u003cp\u003eThe immune checkpoint molecules PD-L1, expressed on antigen-presenting cells and tumour cells, and PD-1, expressed on TILs, interact to inhibit T cell activation, which allows cancer cells to evade immunosurveillance [57]. Bertolini et al. [38] and Gabrych et al. [49] reported PD-L1 expression to be restricted to the immune contexture in their RMS samples, which had no correlation with histological subtype [49], or fusion status [38]. However, Chowdhury et al. [52] reported PD-L1 expression on the tumour cells, with 86% of ARMS being PD-L1 positive, compared to 50% of ERMS. But the statistical significance of this difference was not measured and information regarding fusion status was not provided.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKey findings of the studies included in the review\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKey Findings\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[36]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eERMS\u003c/p\u003e\u003cp\u003e\u0026bull; CD3\u0026thinsp;+\u0026thinsp;and TAMs (CD163+) in close proximity to endothelial cells - majority of T cells and TAMs are found within 20-40um of endothelial cells.\u003c/p\u003e\u003cp\u003e\u0026bull; TAMs predominated the immune microenvironment in all sarcomas.\u003c/p\u003e\u003cp\u003e\u0026bull; Majority of CD3\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells in aggregates with B cells forming TLS, which were the main source of PD-L1 expression.\u003c/p\u003e\u003cp\u003e\u0026bull; B cells found in TLS and not elsewhere.\u003c/p\u003e\u003cp\u003e\u0026bull; The common predominant immune signature was myeloid cells in RMS.\u003c/p\u003e\u003cp\u003eResults from their analysis of publicly available gene expression datasets:\u003c/p\u003e\u003cp\u003e\u0026bull; There was a significantly higher number of resting CD4\u0026thinsp;+\u0026thinsp;memory T cells in FN-RMS compared to FP-RMS (0.256+/-0.134 in FN-RMS compared to 0.185+/-0.118 in FP-RMS).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[38]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; PD-L1 expression was heterogenous (not present at all in tumour cells) in both ARMS and ERMS.\u003c/p\u003e\u003cp\u003e\u0026bull; PD-L1 expression was found in the immune contexture in:\u003c/p\u003e\u003cp\u003e- 6/11 ARMS\u003c/p\u003e\u003cp\u003e- 9/14 ERMS.\u003c/p\u003e\u003cp\u003e\u0026bull; PDL1 staining does not correlate with fusion status.\u003c/p\u003e\u003cp\u003e\u0026bull; PDL1 expression colocalised with CD3\u0026thinsp;+\u0026thinsp;T lymphocytes and CD68\u0026thinsp;+\u0026thinsp;macrophages.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[39]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eERMS\u003c/p\u003e\u003cp\u003e\u0026bull; Myeoid cells showed downregulation of genes associated with ECM organisation compared to the ERMS tumour cells (differentially expressed genes between tumour and normal were closely related to cell adhesion and ECM signalling pathways).\u003c/p\u003e\u003cp\u003e\u0026bull; Tumour cells included M1 and M2 macrophages, normal tissue contained M3.\u003c/p\u003e\u003cp\u003e\u0026bull; All macrophages (M1, M2 and M3) expressed immune checkpoint molecules, however M2 had a higher immune activity.\u003c/p\u003e\u003cp\u003e- M1\u0026thinsp;=\u0026thinsp;FGL1 and IDO1\u003c/p\u003e\u003cp\u003e- M2\u0026thinsp;=\u0026thinsp;CD101\u003c/p\u003e\u003cp\u003e- HAVCR2. M3\u0026thinsp;=\u0026thinsp;CD86\u003c/p\u003e\u003cp\u003e\u0026bull; E1 (34.41%), E2 (29.96%) and E3 (35.63%) endothelial cell subtypes expressed in tumour cells, normal tissues mainly expressed E2 (66.7%).\u003c/p\u003e\u003cp\u003e\u0026bull; E1 and E2 subgroups transform into E3 subgroup during progression to promote tumour progression.\u003c/p\u003e\u003cp\u003e\u0026bull; Macrophages were closely related to collagen and ECM pathway.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[48]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBioinformatics analysis:\u003c/p\u003e\u003cp\u003eERMS:\u003c/p\u003e\u003cp\u003e\u0026bull; 7 showed low MAD2L1 expression (50%) and 7 showed high expression (50%).\u003c/p\u003e\u003cp\u003e\u0026bull; 5 showed low CCNB2 expression (35.7%) and 9 showed high expression (64.3%).\u003c/p\u003e\u003cp\u003eARMS:\u003c/p\u003e\u003cp\u003e\u0026bull; 3 showed low MD2L1 expression (25%) and 9 showed high expression (75%).\u003c/p\u003e\u003cp\u003e\u0026bull; 5 showed low CCNB2 expression (41.7%) and 7 showed high expression (58.3%).\u003c/p\u003e\u003cp\u003eIHC analysis:\u003c/p\u003e\u003cp\u003e\u0026bull; Expression rate of MAD2L1 in RMS samples was 90.9% (30/33) - no expression in 11 control skeletal muscle tissue.\u003c/p\u003e\u003cp\u003e\u0026bull; Expression rate of CCNB2 was 100% (33/33) - no expression in control. \u003c/p\u003e\u003cp\u003e\u0026bull; No statistical difference in expression of MD2L1 or CCNB2 expression between ERMS and ARMS.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[40]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; All samples expressed tenascin and thrombospondin regardless of subtype (5/5 ARMS, 6/6 ERMS).\u003c/p\u003e\u003cp\u003e\u0026bull; Fibronectin was expressed by all ARMS (5/5).\u003c/p\u003e\u003cp\u003e\u0026bull; Fibronectin not expressed in all ERMS (4/6).\u003c/p\u003e\u003cp\u003e\u0026bull; Laminin expressed in 3/5 ARMS and 2/6 ERMS.\u003c/p\u003e\u003cp\u003e\u0026bull; CD44 was not expressed by any ARMS but was expressed by half of ERMS (3/6).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[49]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; The positive PD-L1 staining in RMS samples was restricted to tumour associated immune cells in all cases, with no reactivity in tumour cells.\u003c/p\u003e\u003cp\u003e\u0026bull; No correlation between PD-L1 expression and RMS histological subtype (p\u0026thinsp;=\u0026thinsp;0.451).\u003c/p\u003e\u003cp\u003e- ERMS PD-L1\u0026thinsp;+\u0026thinsp;in 11/19 (57.89%).\u003c/p\u003e\u003cp\u003e- ARMS PD-L1\u0026thinsp;+\u0026thinsp;9/12 ARMS (75.00%).\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[41]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; No difference in CXCR4 expression between ERMS and ARMS (for diagnostic samples) (p\u0026thinsp;=\u0026thinsp;0.59).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[42]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; Plasma from ARMS patients showed higher activity levels of HPSE compared to ERMS but not statistically significant (data not shown).\u003c/p\u003e\u003cp\u003e\u0026bull; HPSE mRNA expression was significantly higher in both ERMS and ARMS compared to control.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[50]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; CD163\u0026thinsp;+\u0026thinsp;TAMs and APN\u0026thinsp;+\u0026thinsp;expressed at much higher levels in ARMS compared to ERMS (TAMs p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, APN p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[4]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; The proportion of each non-malignant cell types did not differ significantly by fusion status.\u003c/p\u003e\u003cp\u003eo Non-malignant cell types included T cells (CD4 T cells, T-regs, CD8\u0026thinsp;+\u0026thinsp;T cells), NK cells, B cells, monocytes and macrophages (M1 and M2).\u003c/p\u003e\u003cp\u003eo These non-malignant cell types were grouped into clusters \u0026ndash; T/NK cell cluster, myeloid cluster, B cell cluster and endothelial cell cluster, whose proportions didn\u0026rsquo;t differ based on fusion status.\u003c/p\u003e\u003cp\u003e\u0026bull; IFN stimulated CD4\u0026thinsp;+\u0026thinsp;T helper cells (ISG+) were found almost exclusively in FNRMS.\u003c/p\u003e\u003cp\u003e\u0026bull; Dysfunction of CD8\u0026thinsp;+\u0026thinsp;T cells was more prevalent in FP-RMS samples - CD8\u0026thinsp;+\u0026thinsp;T cells were enriched for genes related to PD-1 signalling, OXPHOS and T cell exhaustion.\u003c/p\u003e\u003cp\u003e\u0026bull; Cells from FN-RMS tumours were enriched for gene signatures relating to IFN response and stimulation.\u003c/p\u003e\u003cp\u003e\u0026bull; Interaction between NECTIN3 on malignant cells and TIGIT receptor on T-regs and CD8\u0026thinsp;+\u0026thinsp;T cells was specific to FP-RMS tumours due to significantly higher expression of NECTIN-3 on FP-RMS, whilst there was no difference in expression of TIGIT on CD8\u0026thinsp;+\u0026thinsp;T cells between subtypes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[43]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eImmunoblot results:\u003c/p\u003e\u003cp\u003e\u0026bull; All 5 RMS samples had reduced or absent expression of native ɑ-dystroglycan.\u003c/p\u003e\u003cp\u003e\u0026bull; β-dystroglycan present in all RMS samples, molecular weight in tumour sample was similar to normal muscle controls.\u003c/p\u003e\u003cp\u003e\u0026bull; Laminin binding was significantly reduced in all 5 RMS samples compared to controls.\u003c/p\u003e\u003cp\u003eImmunostaining of tissue microarrays results:\u003c/p\u003e\u003cp\u003e\u0026bull; Both ERMS and ARMS had significant reduction in ɑ-dystroglycan staining relative to normal skeletal muscle and relative to β-dystroglycan.\u003c/p\u003e\u003cp\u003e\u0026bull; Laminin expression was significantly reduced relative to β-dystroglycan in both RMS subtypes.\u003c/p\u003e\u003cp\u003e\u0026bull; ɑ-dystroglycan staining occurred primarily in tumour vasculature in both ERMS and ARMS.\u003c/p\u003e\u003cp\u003e\u0026bull; β-dystroglycan staining was abundant in all tumour samples of both tumour types - no tumour types received a score of 1 (no staining) for β-dysrtroglycan).\u003c/p\u003e \u003cp\u003e\u0026bull; For ɑ-dystroglycan, 67% (for VIA4-1) and 55% (for IIH6) ERMS had a score of 1, and 43% (for VIA4-1) and 33% (for IIH6) of ARMS had a score of 1.\u003c/p\u003e\u003cp\u003e\u0026bull; ERMS (23): * between tumour sample and control\u003c/p\u003e\u003cp\u003eβDG\u0026thinsp;=\u0026thinsp;2.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\u003cp\u003eVIA4-1 (ɑDG)\u0026thinsp;=\u0026thinsp;1.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11***\u003c/p\u003e\u003cp\u003eIIH6 (ɑDG)\u0026thinsp;=\u0026thinsp;1.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15***\u003c/p\u003e\u003cp\u003eLN-1 (laminin)\u0026thinsp;=\u0026thinsp;1.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21*\u003c/p\u003e\u003cp\u003e\u0026bull; ARMS (14): * between tumour sample and control\u003c/p\u003e\u003cp\u003eβDG\u0026thinsp;=\u0026thinsp;2.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\u003cp\u003eVIA4-1 (ɑDG)\u0026thinsp;=\u0026thinsp;1.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16**\u003c/p\u003e\u003cp\u003eIIH6 (ɑDG)\u0026thinsp;=\u0026thinsp;1.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19*\u003c/p\u003e\u003cp\u003eLN-1 (laminin)\u0026thinsp;=\u0026thinsp;1.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[51]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; CD8 by IHC and gene expression was comparable in ARMS and ERMS.\u003c/p\u003e\u003cp\u003e\u0026bull; 30% of RMS samples were positive for PD-L1\u0026ndash;4 samples had PD-L1 positivity in tumour cells, 2 samples were PD-L1 positive in immune cells.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[44]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; CXCR4 expression was statistically increased in ARMS primary samples relative to ERMS and control skeletal muscle (p\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e\u003cp\u003e\u0026bull; No statistical difference in expression of CXCR4 between ERMS and control skeletal muscle.\u003c/p\u003e\u003cp\u003e\u0026bull; All BMS cultures expressed increased SDF-1ɑ.\u003c/p\u003e\u003cp\u003e\u0026bull; CXCR4- SDF-1ɑ signalling axis may be involved in RMS metastasis to bone marrow.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[45]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; ERMS:\u003c/p\u003e\u003cp\u003e- Laminin (93%)\u003c/p\u003e\u003cp\u003e- Fibronectin (87%)\u003c/p\u003e\u003cp\u003e- Type IV collagen (54%)\u003c/p\u003e\u003cp\u003e\u0026bull; ARMS:\u003c/p\u003e\u003cp\u003erarely expressed any of the extracellular matrix proteins\u003c/p\u003e\u003cp\u003e- Laminin (22%)\u003c/p\u003e\u003cp\u003e- Fibronectin (22%)\u003c/p\u003e\u003cp\u003e- Type IV collagen (14%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[46]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; PDGFRβ was significantly over expressed in both ARMS and ERMS.\u003c/p\u003e\u003cp\u003e\u0026bull; PDGFRβ protein levels were rarely detected in tumour cells, expression was associated with stroma in ARMS subtype.\u003c/p\u003e\u003cp\u003e- PDGFRβ stromal staining was positively associated with ARMS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e\u003cp\u003e\u0026bull; PDGFRɑ expression was observed in both the tumour cell and stroma and was associated with ERMS.\u003c/p\u003e\u003cp\u003e- PDGFRɑ stromal staining was positively associated with ERMS (p\u0026thinsp;=\u0026thinsp;0.0329).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[47]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; ARMS cells stained diffusely and strongly for MMP-2 and MMP-9.\u003c/p\u003e\u003cp\u003e\u0026bull; MMP-1 positive in:\u003c/p\u003e\u003cp\u003e- 11/12 ARMS\u003c/p\u003e\u003cp\u003e- 11/21 ERMS\u003c/p\u003e\u003cp\u003e\u0026bull; MMP-2 positive in:\u003c/p\u003e\u003cp\u003e- 12/12 ARMS\u003c/p\u003e\u003cp\u003e- 9/21 ERMS\u003c/p\u003e\u003cp\u003e\u0026bull; MMP7 expressed in 26/33 tumour samples:\u003c/p\u003e\u003cp\u003e- 11/12 ARMS\u003c/p\u003e\u003cp\u003e- 15/21 ERMS\u003c/p\u003e\u003cp\u003e\u0026bull; MMP-3 was negative in almost all RMS samples (28/32).\u003c/p\u003e\u003cp\u003e\u0026bull; MMP-3 positive in:\u003c/p\u003e\u003cp\u003e- 2/12 ARMS\u003c/p\u003e\u003cp\u003e- 3/21 ERMS\u003c/p\u003e\u003cp\u003e\u0026bull; MMP-9 was positive in perivascular ECM and in vascular structures of tumours\u003c/p\u003e\u003cp\u003e\u0026bull; Positive in:\u003c/p\u003e\u003cp\u003e- 12/12 ARMS\u003c/p\u003e\u003cp\u003e- 11/21 ERMS\u003c/p\u003e\u003cp\u003e\u0026bull; Statistically significant difference between ARMS and ERMS:\u003c/p\u003e\u003cp\u003eMMP-1 (P\u0026thinsp;=\u0026thinsp;0.006)\u003c/p\u003e\u003cp\u003eMMP-2 (P\u0026thinsp;=\u0026thinsp;0.0001)\u003c/p\u003e\u003cp\u003eMMP-9 (P\u0026thinsp;=\u0026thinsp;0.0001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e[52]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; 86% of ARMS were PD-L1 positive.\u003c/p\u003e\u003cp\u003e\u0026bull; 50% of ERMS were PD-L1 positive.\u003c/p\u003e\u003cp\u003e\u0026bull; Figure 3e shows ERMS having a higher mean total number of CD8\u0026thinsp;+\u0026thinsp;TILs compared to ARMS (significance wasn\u0026rsquo;t reported).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eTAM\u003c/em\u003e, tumour associated macrophages; \u003cem\u003eTLS\u003c/em\u003e, tertiary lymphoid structure; \u003cem\u003eRMS\u003c/em\u003e, rhabdomyosarcoma; \u003cem\u003eERMS\u003c/em\u003e, embryonal rhabdomyosarcoma; \u003cem\u003eARMS\u003c/em\u003e, alveolar rhabdomyosarcoma; \u003cem\u003eFN\u003c/em\u003e, fusion negative; \u003cem\u003eFP\u003c/em\u003e, fusion positive; \u003cem\u003eECM\u003c/em\u003e, extracellular matrix; \u003cem\u003eAPN\u003c/em\u003e, adiponectin; \u003cem\u003eNK cells\u003c/em\u003e, natural killer cells; \u003cem\u003eIHC\u003c/em\u003e, immunohistochemistry; \u003cem\u003eBMS\u003c/em\u003e, bone marrow stroma; \u003cem\u003eFN-RMS\u003c/em\u003e, fusion negative rhabdomyosarcoma; \u003cem\u003eFP-RMS\u003c/em\u003e, fusion positive rhabdomyosarcoma; \u003cem\u003eOXPHOS\u003c/em\u003e, oxidative phosphorylation; \u003cem\u003eT-regs\u003c/em\u003e, regulatory T cells; \u003cem\u003eMMP\u003c/em\u003e, matrix metalloproteinase; \u003cem\u003eTIL\u003c/em\u003e, tumour infiltrating lymphocytes; \u003cem\u003ePDGFRɑ/β\u003c/em\u003e, platelet derived growth factor receptor-ɑ/β; \u003cem\u003eSDF-1\u003c/em\u003e, stromal cell-derived factor 1; \u003cem\u003eβDG\u003c/em\u003e, β-dystroglycan; ɑDG, ɑ-dystroglycan.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e The total number and the mean number of samples for each RMS subtype\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubtype\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFP-RMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFN-RMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eERMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e452\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eARMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e156\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eFP-RMS\u003c/em\u003e, fusion positive rhabdomyosarcoma; \u003cem\u003eFN-RMS\u003c/em\u003e, fusion negative rhabdomyosarcoma; \u003cem\u003eERMS\u003c/em\u003e, embryonal rhabdomyosarcoma; \u003cem\u003eARMS\u003c/em\u003e, alveolar rhabdomyosarcoma.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2 The Extracellular Matrix and the Tumour Stroma\u003c/h2\u003e\u003cp\u003eNine studies investigated a component of the ECM in RMS [39\u0026ndash;47], which included adhesion factors [40, 45], Chemokine Receptor 4 (CXCR4) signalling [41, 44], ECM enzymes [42], ECM receptors [43], matrix metalloproteinases (MMPs), [47] platelet derived growth factor receptor (PDGFR) signalling [46], laminin and fibronectin [40, 45], and type IV collagen [45]. No studies investigated these components in FP-RMS or FN-RMS specifically.\u003c/p\u003e\u003cp\u003eLaminin and fibronectin are major proteins involved in establishing the architecture of the ECM [58]. Two studies investigated laminin and fibronectin expression in ERMS and ARMS and found opposing results [40, 45]. Saxon et al. [40] reported laminin and fibronectin to be expressed by a higher percentage of ARMS compared to ERMS, whereas Stracca-Pansa et al. [45] reported laminin and fibronectin to be expressed by a higher percentage of ERMS compared to ARMS. Again, the significance of these differences was not reported, and fusion status was not provided.\u003c/p\u003e\u003cp\u003eCXCR4 is commonly expressed on tumour cells [59]. Binding to its ligand, stromal cell-derived factor 1 (SDF-1), in the TME, promotes angiogenesis, survival and proliferation of tumour cells and recruitment of immune cells [60, 61]. Vela et al. [41] and Strahm et al [44] investigated CXCR4 expression in ERMS and ARMS and found opposing results. Vela et al. [41] observed CXCR4 staining in 68% of their specimens but reported no difference in CXCR4 expression between ERMS and ARMS. However, Strahm et al. [44] observed a statistically significant increase in CXCR4 expression in ARMS compared to ERMS. Data from across these two studies could not be averaged due to differences in tissue processing techniques and experimental methods. Again, no fusion status was provided.\u003c/p\u003e\u003cp\u003eHeparanase, ɑ- and β-dystroglycan, tenascin and thrombospondin, and type IV collagen are all ECM components, known to be important in cancer progression [62\u0026ndash;65]. They were investigated by four studies using different methods [40, 42, 43, 45]. None of the studies reported information regarding fusion status. It was reported that there were no differences in the expression of heparanase [42], ɑ- and β-dystroglycan [43], or tenascin and thrombospondin [40], between ERMS and ARMS. However, Martin et al. [43] reported that both subtypes had a significant reduction in ɑ-dystroglycan and laminin binding relative to the control. Type IV collagen, an ECM protein, was expressed in only 14% of ARMS compared to 54% of ERMS [45] and CD44 was expressed in 50% of ERMS, but not at all in ARMS samples [40]. The significance of these results was not reported.\u003c/p\u003e\u003cp\u003eMMPs promote tumour cell invasion and metastasis by degrading the surrounding ECM [66]. Diomedi-Camassei et al. [47] reported a significant increase in the expression of MMP-1, MMP-2 and MMP-9 in ARMS compared to ERMS, but no difference in the expression of MMP-3 or MMP-7.\u003c/p\u003e\u003cp\u003ePlatelet derived growth factors (PDGFs) and their receptors, PDGFRs, are expressed on tumour and stromal cells [67]. Ehnman et al. [46] reported a positive association between PDGFR\u0026szlig; stromal staining and ARMS, and a positive association between PDGFRɑ stromal staining and ERMS. Interestingly, they also showed that stromal PDGFRɑ was negatively associated with metastasis, whereas PDGFR\u0026szlig; was positively associated with metastasis, reflective of the more aggressive behaviour observed in ARMS.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe composition of the TME plays a crucial role in supporting tumour survival and metastasis and has previously been shown to differ between aggressive and less aggressive cancer subtypes [15, 16]. The role of the PAX-FOXO1 fusion proteins in tumorigenesis lacks understanding, but FP-RMS is associated with a much more aggressive and metastatic nature compared to FN-RMS [8], which could be linked to differences in their TMEs. Therefore, the aim of this systematic review was to use systematic review methodology to identify and evaluate current literature investigating the TME in patient-derived, paediatric FP-RMS, FN-RMS/ERMS and ARMS in order to identify potential differences in the TME between the fusion subtypes.\u003c/p\u003e\u003cp\u003eThis review identified significant differences in CD163\u0026thinsp;+\u0026thinsp;macrophages [53], MMPs [50] and stromal PDGFRɑ/\u0026szlig; [49] between ARMS and ERMS. An increase in T cell dysfunction and NECTIN-3 expression was reported in FP-RMS, with an increase in gene sets relating to PD-1 signalling and T cell exhaustion [4]. Genes relating to IFN response were enriched in FN-RMS samples [4]. There were no differences in the expression of ɑ/β-dystroglycan, thrombospondin, tenascin or heparanase expression between ERMS and ARMS [43, 45, 46, 48]. There were also no differences identified in the proportion of T cells, NK cells, myeloid cells or B cells based on fusion status [4]. PD-L1 expression [41, 52, 55], CXCR4 expression [44, 47], laminin and fibronectin [43, 48] expression were variable between studies.\u003c/p\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.1 The Immune Microenvironment\u003c/h2\u003e\u003cp\u003eThe immune microenvironment plays a crucial role in the elimination of tumours, however, tumours can evade the immune response by mechanisms such as immunosuppression and inducing T cell dysfunction [68]. TAMs are an immunosuppressive immune cell and have a direct role in the proliferation, invasion and metastasis of tumours [69]. Previous studies have shown that an increased infiltration of CD163\u0026thinsp;+\u0026thinsp;TAMs, associated with an M2 phenotype, is associated with more advanced tumours with poorer prognosis [70].Consistent with the literature, this review found that the expression of CD163\u0026thinsp;+\u0026thinsp;TAMs was significantly increased in ARMS compared to ERMS [50], suggestive of a more immunosuppressive TME in ARMS. This difference may be driven by the PAX-FOXO1 fusion protein, present in the ARMS subtype. DeMartino et al. [4] reported no difference in the proportion of macrophages based on fusion status [4].\u003c/p\u003e\u003cp\u003eCurrent literature has shown that cancer subtypes with more favourable prognosis are associated with a higher infiltration of CD8\u0026thinsp;+\u0026thinsp;T cells [71]. In contrast to this, Thakur et al. [51] reported no significant difference in CD8 expression between ARMS and ERMS. But, since a small proportion of ARMS are fusion negative and are biologically and clinically indistinct from ERMS, these results could be confounded by the presence of FN-ARMS. This highlights the limitation of missing fusion status data.\u003c/p\u003e\u003cp\u003eDespite an infiltration of cytotoxic CD8\u0026thinsp;+\u0026thinsp;T cells, tumours can evade the immune response by inducing T cell dysfunction [72]. T cell dysfunction was more prevalent in FP-RMS, and correlated with an enrichment of genes related to T cell exhaustion and PD-1 signalling, as well as an upregulation of NECTIN-3 on FP-RMS cells [4]. These results suggest a reduction in the activity of cytotoxic T cells in FP-RMS, which may be contributing to its poor prognosis. This is reflective of current knowledge that immune evasion is a crucial mechanism contributing to tumour progression and metastasis [73]. Similar to DeMatino et al\u0026rsquo;s [4] study reporting an increase in PD-1 signalling in FP-RMS, Chowdhury et al\u0026rsquo;s [52] study showed PD-L1 to be expressed by a higher percentage of ARMS cells compared to ERMS cells. This suggests an increase in PD-L1 expression associated with the presence of the fusion gene, potentially contributing to the aggressive and metastatic nature of FP-RMS. This correlates with previous research showing PD-L1 expression to be increased in metastatic tumours compared to primary tumours [74]. However, the significance of Chowdhury et al\u0026rsquo;s [52] findings were not reported.\u003c/p\u003e\u003cp\u003eDeMartino et al\u0026rsquo;s [4] study found that cells of FN-RMS tumours were enriched with IFN response and stimulation gene signatures, indicative of an IFN response in these tumours, which may be contributing to the better prognosis observed in FN-RMS patients. IFNs are potent drivers of the anti-tumour immune response and play a critical role in shaping the TME [75]. DeMartino et al. [4] identified that IFN stimulated CD4\u0026thinsp;+\u0026thinsp;T helper cells (ISG+) were found almost exclusively in FN-RMS tumours, reflective of IFNs role in promoting a Th1 phenotype of CD4\u0026thinsp;+\u0026thinsp;T cells [4, 75]. Future research should further investigate IFN activity and the resulting impacts it has on the immune cells of the TME between fusion subtypes. This could provide insight into how distinct immune responses contribute to differences in prognosis between FP-RMS and FN-RMS.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.2 The Extracellular Matrix and the Tumour Stroma\u003c/h2\u003e\u003cp\u003ePaediatric sarcomas have previously been characterised by high levels of MMPs, which are secreted by various cells of the TME to promote tumour cell migration, invasion and eventually metastasis by degrading the surrounding ECM [76, 77]. Consistent with this, Diomedi-Camassei et al. [47] identified that MMP-1, MMP-2 and MMP-9 were significantly increased in ARMS compared to ERMS, which reflects previous evidence showing that PAX3-FOXO1 may promote a metastatic phenotype by increasing MMP-2 activity [33, 78]. Degradation of the ECM by MMPs involves the loss of basement membrane architecture, of which type IV collagen is a major component [79]. The reduced expression of type IV collagen in ARMS compared to ERMS [45] may therefore be reflective of the increase in MMPs in ARMS/FP-RMS. The interaction of these TME components may therefore be contributing to the more aggressive and metastatic nature of FP-RMS and should be an area of focus for future research.\u003c/p\u003e\u003cp\u003eCompared to the immune microenvironment, studies investigating the stromal component of the TME in RMS are lacking. The most abundant component of the tumour stroma are cancer associated fibroblasts (CAFs), however these are largely understudied in many STSs due to a shared mesenchymal origin, making it challenging to distinguish CAFs from malignant mesenchymal cells [80]. However, the tumour stroma, including CAFs, has a role in promoting tumour development, metastasis, and recurrence, and has been correlated with phenotypes of tumour aggression in solid tumours [81]. Therefore, further understanding of the tumour stroma in paediatric RMS may provide valuable information regarding the mechanism of RMS progression, which could provide novel targets for treatment. Thus, future research should aim to overcome the challenges of investigating CAFs, to better characterise the tumour stroma in FP-RMS and FN-RMS.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Strengths and Limitations\u003c/h2\u003e\u003cp\u003eThe methodology of this review allowed the aim of identifying and evaluating relevant literature to identify differences in the TME between FP-RMS and FN-RMS, to be achieved. The screening of a random selection of titles and abstracts by a second independent reviewer highlighted some discrepancies, which allowed clearer inclusion and exclusion criteria to be developed. For instance, it was decided that studies that did not specify the subtype, or whether samples were paediatric or adult in the abstract, were to be retained for screening of the full text. This ensured that all relevant studies were included. The data extraction was carried out by only one reviewer; however, the data that was extracted was double checked and additional information added during the quality assessment stage, which ensured that all relevant findings were included. In addition, a comprehensive search strategy was developed and translated appropriately between databases to ensure that all possible relevant literature were identified. Furthermore, multiple databases were used to search for literature, which is recommended to capture all relevant studies [82]. The three databases used (MEDLINE (Ovid), EMBASE (Ovid), and the Web of Science) were recommended by Barmer et al. [82] to be used for adequate recall, precision and number of references. These steps ensured that all relevant literature were identified and included in the review.\u003c/p\u003e\u003cp\u003eHowever, there were also some notable limitations. Firstly, the majority of included studies had small sample sizes, attributed to the rarity of this cancer type. This meant that they lacked statistical power [83], which may explain the lack of difference identified in some TME components between subtypes. Some studies also failed to report if statistical significance was measured, making it difficult to draw conclusions based on their results. Smaller sample sizes also increase the chance of random variations in results [84], which could explain the contrasting results found between CXCR4 expression [41, 44], and laminin and fibronectin [40, 45] between studies.\u003c/p\u003e\u003cp\u003eThis review looked at both histology and fusion status in order to identify differences in the TME between FP-RMS and FN-RMS. This approach was chosen as many studies still rely on RMS histology, which has historically been used to classify RMS. Additionally, since the majority of ARMS are fusion positive, and all ERMS are fusion negative, analysing differences in the TME between ERMS and ARMS could offer insights into differences between FP-RMS and FN-RMS. However, the absence of fusion status information in the included studies was a major limitation of this approach as it could not be determined whether differences in the TME between ERMS and ARMS were driven by the presence of the fusion gene in the ARMS samples. Absence of fusion status information could also contribute to the reporting of no difference in the TME between ERMS and ARMS, which could be confounded by the potential presence of FN-ARMS. Furthermore, a third subtype of RMS, known as spindle cell/sclerosing RMS (SS-RMS) has only recently been separated from the ERMS subtype, defined as a separate pathologic entity in the WHO 2013 classification of soft tissue and bone tumours [85, 86]. SS-RMS can be further classified by the presence of a \u003cem\u003eMYOD1\u003c/em\u003e mutation, associated with a highly lethal outcome and unfavourable behaviour, which is comparable to ARMS [85]. Therefore, the possible presence of this RMS subtype in the ERMS samples, particularly in the older studies, may have contributed to a lack of difference in the TME reported between ERMS and ARMS.\u003c/p\u003e\u003cp\u003eThis review also highlighted a lack of standardisation of methods used to analyse some components of the TME, contributing to variability in results and preventing data from multiple studies being averaged. For instance, Bertolini et al. [38] and Gabrych et al. [49] detected PD-L1 expression only on tumour associated immune cells, while Chowdhury et al. [52] detected it on ARMS and ERMS tumour cells. Similar inconsistencies regarding PD-L1 expression have been found in previous research, which has been attributed to the use of different antibodies across studies [74]. Bertolini et al. [38] and Gabrych et al [49] used SP142 antibody and 22C3 clone to detect PD-L1 expression, whereas Chowdhury et al. [52] used anti-CD274. To draw more reliable conclusions, more standardised methods should be used across studies.\u003c/p\u003e\u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis systematic review has highlighted that research regarding the TME in FP-RMS and FN-RMS is still in its infancy, with single-cell studies, such as DeMartino et al\u0026rsquo;s [4] study, only beginning to highlight potential differences between these fusion subtypes. Because of this, there was insufficient evidence to draw robust conclusions about differences in the TME between FP-RMS and FN-RMS specifically. Findings based on histological subtypes suggest there may be differences linked to fusion status. But due to the fusion status being unknown in the majority of studies, further research is needed to confirm this. Future research should therefore prioritise investigating fusion subtypes over histological subtypes, since fusion status is now recognised to classify RMS and predict prognosis more accurately. It can also be recommended that an updated version of this systematic review be conducted as more data on the TME in FP-RMS and FN-RMS becomes available. Since the TME plays a crucial role in tumour progression, understanding it\u0026rsquo;s composition, in relation to fusion status, will improve our knowledge of how the PAX-FOXO1 fusion gene contributes to tumorigenesis and a poorer prognosis seen in FP-RMS patients. Ultimately, this could identify novel targets and aid in the development of novel treatment strategies to improve patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eOpen access funding provided by University of Southampton Library. ZSW has funding from Children with Cancer UK and the CRIS Cancer Foundation, CP is funded by University of Southampton.\u003c/p\u003e\u003ch2\u003eAuthor contributions:\u003c/h2\u003e\u003cp\u003eConceptualization, M.R. and Z.S.W.; methodology, M.R., C.P. and Z.S.W.; investigation, M.R.; resources, M.R., C.P., T.J.U., and Z.S.W.; writing\u0026mdash;original draft preparation, M.R.; writing\u0026mdash;review and editing, M.R., C.P., T.J.U., and Z.S.W.; visualisation, M.R. and Z.S.W.; supervision, C.P. and Z.S.W.; project administration, M.R. and Z.S.W. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\u003cp\u003eZSW has funding from Children with Cancer UK and the CRIS Cancer Foundation, CP is funded by University of Southampton\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHawkins DS, Spunt SL, Skapek SX. Children\u0026apos;s Oncology Group\u0026apos;s 2013 blueprint for research: Soft tissue sarcomas. Pediatr Blood Cancer. 2013;60(6):1001-8.\u003c/li\u003e\n\u003cli\u003eTenente IM, Hayes MN, Ignatius MS, McCarthy K, Yohe M, Sindiri S, et al. Myogenic regulatory transcription factors regulate growth in rhabdomyosarcoma. Elife. 2017;6.\u003c/li\u003e\n\u003cli\u003eCiesla M, Dulak J, J\u0026oacute;zkowicz A. MicroRNAs and epigenetic mechanisms of rhabdomyosarcoma development. 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Evolving classification of rhabdomyosarcoma. Histopathology. 2022;80(1):98-108.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Supplementary Material","content":"\u003cp\u003eSupplementary Table S1 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Southampton","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rhabdomyosarcoma, tumour microenvironment, PAX-FOXO1 fusion gene, immune microenvironment, extracellular matrix","lastPublishedDoi":"10.21203/rs.3.rs-7796884/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7796884/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRhabdomyosarcoma (RMS) is a predominantly paediatric cancer that is classified by the presence or absence of a \u003cem\u003ePAX-FOXO1\u003c/em\u003e fusion gene, which is associated with a worse prognosis. Previous classification was based on histology, Alveolar RMS (ARMS) or Embryonal RMS (ERMS). In other paediatric cancers, fusion gene status has been shown to associate with differences in the tumour microenvironment. However, comprehensive understanding of the TME in RMS and how it may differ between subtypes is lacking. This systematic review aimed to identify differences in the TME between FP-RMS and FN-RMS, to better understand how the fusion gene drives malignancy. The Web of Science, MEDLINE (Ovid) and EMBASE (Ovid) were searched to identify relevant studies investigating the TME in RMS. A total of 17 studies met the inclusion criteria and were included in the review, but only three studies specified fusion status in their sample data. Nine studies investigated the extracellular matrix (ECM) and stroma, and another nine investigated the immune microenvironment. Significant differences in CD163\u0026thinsp;+\u0026thinsp;macrophages, matrix metalloproteinases (MMPs) and stromal platelet derived growth factor receptors (PDGFRɑ/\u0026szlig;) were observed between ARMS and ERMS. Regarding fusion status, there were differences in the prevalence of T cell dysfunction, NECTIN-3 expression, and genes related to PD-1 signalling and interferon (IFN) response. This review highlights a definite need for further research of the TME in each fusion subtype. This will improve our understanding of how the fusion gene drives malignancy and ultimately aids in the development of novel treatment strategies.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e","manuscriptTitle":"The Tumour Microenvironment in Paediatric Rhabdomyosarcomas: A Systematic Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-09 14:18:34","doi":"10.21203/rs.3.rs-7796884/v1","editorialEvents":[{"type":"communityComments","content":1}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"798751bd-244f-4afb-912b-83a92618795e","owner":[],"postedDate":"October 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55877636,"name":"Oncology"},{"id":55877637,"name":"General Cell Biology \u0026 Physiology"}],"tags":[],"updatedAt":"2025-10-09T14:18:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-09 14:18:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7796884","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7796884","identity":"rs-7796884","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}