Skip to main content
Download PDF
Download ePub

Plasma-derived extracellular vesicles miR-335–5p as potential diagnostic biomarkers for fusion-positive rhabdomyosarcoma

Journal of Experimental & Clinical Cancer Research volume 43, Article number: 282 (2024) Cite this article

Abstract

Background

Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma, with embryonal (ERMS) and alveolar (ARMS) representing the two most common histological subtypes. ARMS shows poor prognosis, being often metastatic at diagnosis. Thus, the discovery of novel biomarkers predictive of tumor aggressiveness represents one of the most important challenges to overcome and may help the development of tailored therapies. In the last years, miRNAs carried in extracellular vesicles (EVs), small vesicles of endocytic origin, have emerged as ideal candidate biomarkers due to their stability in plasma and their tissue specificity.

Methods

EVs miRNAs were isolated from plasma of 21 patients affected by RMS and 13 healthy childrens (HC). We performed a miRNA profile using the Serum/Plasma Focus microRNA PCR panels (Qiagen), and RT-qPCR for validation analysis. Statistically significant (p < 0.05) miRNAs were obtained by ANOVA test.

Results

We identified nine EVs miRNAs (miR-483-5p, miR-132-3p, miR-766-3p, miR-454-3p miR-197-3p, miR-335-3p, miR-17-5p, miR-486-5p and miR-484) highly upregulated in RMS patients compared to HCs. Interestingly, 4 miRNAs (miR-335-5p, miR-17-5p, miR-486-5p and miR-484) were significantly upregulated in ARMS samples compared to ERMS. In the validation analysis performed in a larger group of patients only three miRNAs (miR-483-5p, miR-335-5p and miR-484) were differentially significantly expressed in RMS patients compared to HC. Among these, mir-335-5p was significant also when compared ARMS to ERMS patients. MiR-335-5p was upregulated in RMS tumor tissues respect to normal tissues (p = 0.00202) and upregulated significantly between ARMS and ERMS (p = 0.04). Furthermore, the miRNA expression correlated with the Intergroup Rhabdomyosarcoma Study (IRS) grouping system, (p = 0.0234), and survival (OS, p = 0.044; PFS, p = 0.025). By performing in situ hybridization, we observed that miR-335-5p signal was exclusively in the cytoplasm of cancer cells.

Conclusion

We identified miR-335-5p as significantly upregulated in plasma derived EVs and tumor tissue of patients affected by ARMS. Its expression correlates to stage and survival in patients. Future studies are needed to validate miR-335-5p as prognostic biomarker and to deeply elucidate its biological role.

Background

Rhabdomyosarcoma (RMS) is the most common type of soft tissue sarcoma in children and young adults, accounting for up to 3–4% of childhood cancer and approximately 50% of all sarcomas [1, 2]. Embryonal (ERMS) and alveolar (ARMS) RMS represent the two most common histological subtypes. ARMS is associated with two chromosomal translocations, t(2;13) (q35;q14) and t(1;13) (p36;q14) resulting respectively in the PAX3–FOXO1 and PAX7–FOXO1 fusion proteins [3]. Various studies have demonstrated that PAX3-7-FOXO1 fusion oncoprotein enhances RMS growth and metastasis by targeting genes involved in proliferation, migration and invasion [4]. Patients affected by ARMS shows a poor prognosis, being often metastatic at diagnosis.

Although, during the last three decades, the use of combination therapies has substantially improved the prognosis of localized RMS, the clinical outcomes for children with metastatic RMS remains very poor even with a multimodal approach, with a 5-year event free survival (EFS) and overall survival (OS) of 17.3% and 21.3% respectively [5, 6]. Thus, the discovery of novel biomarkers predictive of tumor aggressiveness may help the development of tailored therapies and represents one of the most important objectives to achieve in this disease.

Liquid biopsy allows to identify tumor secreted factor circulating in the body fluids, such as plasma or serum, with the advantage of being minimally invasive and reflecting tumor burden in patients [7]. This approach enables the detection of circulating tumor cells, cell-free DNA (cfDNA), circulating microRNAs (miRNAs), proteins and tumor cell-derived extracellular vesicles (EVs) [8]. EVs are cell membrane-derived nanovesicles (30 nm -10 μm) released by eukaryotic cells and abundantly by aggressive tumor cells, carrying lipids, soluble and transmembrane proteins, mRNAs, miRNAs and double-stranded DNA. EVs play a role in intercellular communication by transferring molecules to the surrounding cells and may have significant contribution to tumor progression [9, 10]. Consequently theyare promising candidates as specific cancer biomarkers. MiRNAs within extracellular vesicles (EVs-miRNAs) are particularly stable as they are protected from RNAses, providing an enriched and ideal source for tumor biomarkers detection [11, 12]. Tumor-secreted EVs-miRNAs can be transferred to target cells, influencing their gene expression and impacting tumor biology [13,14,15]. In RMS, several functional studies have demonstrated that different miRNAs could act both as tumor suppressor and oncomiRs regulating cancer cell proliferation, invasion, and apoptosis [16,17,18,19,20,21,22,23]. The study of miRNAs, particularly those encapsulated in EVs, provides unique insights due to their stability, resistance to degradation. Compared to studying mRNA derived from cfRNA, miRNAs offer complementary information as they regulate gene expression and could help to identify the mechanism involved in RMS aggressiveness. Notably, it has been observed that EVs derived from RMS cell lines are enriched in miRNAs, which are implicated in inducing angiogenesis, tumor growth and metastasis [24].

Herein, we report an exploratory study on EVs-miRNAs derived from the plasma of RMS patients, with the purpose of identifying predictive diagnostic and prognostic biomarkers. We found that among the significantly dysregulated miRNAs, miR-335-5p correlates with ARMS subtype and with prognosis in RMS patients. To our knowledge, this is the first study reporting a potential interest of miR-335-5p as novel biomarker in RMS patients.

Materials and methods

Patients and sample collection

Plasma was collected from 21 RMS patients at diagnosis and 13 healthy children (HC) at Pediatric Haematology/Oncology and Cell and Gene Therapy Department, Bambino Gesù Children’s Hospital. Among the RMS patients 9 were diagnosed with fusion positive ARMS and 12 with ERMS, 8 were females and 13 males; their median age was 49 months (range: 5–188 months). Among HC, 8 were males and 5 females, their median age was 74,9 months (range: 6–207 months). Patients’ clinical information is shown in Supplementary Table 1. Written informed consent was signed by all parents and the study was approved by our Institutional Ethics Committee (protocol number 1189_OPBG_2016).

Whole blood was collected in EDTA tubes (BD Vacutainer, Reading, UK) and processed within 2 h. The samples were first centrifugated at 500 × g for 10 min, and then supernatants were collected and centrifuged at 3000 × g and then at 12,000 × g for 20 min each. All the centrifugation steps were performed at 4 degrees. The plasma was collected and stored at -80◦C until EVs isolation.

Isolation of extracellular vesicles from plasma

EVs isolation from plasma was performed using the commercial kit miRCURY™ Exosome isolation kit-serum and plasma (Qiagen) according to the manufacturer’s protocol. Briefly, 3 UI of Thrombin was added to 0.6 ml of plasma and incubated for 5 min at room temperature (RT) and centrifuged for 5 min at 10,000 × g. An amount of 0.5 ml of supernatant was collected, 200 μl of precipitation buffer A was added, resuspended by vortexing for 5 s to mix and incubated for 60 min at 4 °C. After incubation, samples were centrifuged for 5 min at 500 g at RT and the supernatants were removed and discarded. Pellets were re-suspended by vortex in 270 μl resuspension buffer. The isolated EVs were characterized following the recommendations of “Minimal Information for Studies of Extracellular Vesicles” (MISEV) 2023, (Supplementary Methods) [25]. Transmission Electron Microscopy (TEM) confirmed the presence of EVs with homogeneous morphology, occasionally clustered, with a size ranging from 30 to 200 nm (Supplementary Fig. 1A). NanoSight analysis showed a mean vesicle diameter ranging from 105 to 146 nm (Supplementary Fig. 1B). Western Blot revealed an enrichment of the EVs-specific protein Tumor Susceptibility Gene 101 (TSG101), CD9, and CD63 in nanovesicles samples compared to Hela cells lysate; furthermore, the absence of endoplasmic reticulum protein Calnexin demonstrate that no cell debris were present in our preparation’s lysate (Supplementary Fig. 1C). The purified EVs samples were then processed for RNA extraction.

RNA isolation from plasma extracellular vesicles

RNA from plasma EVs was isolated using miRCURY RNA isolation kit-biofluids (Qiagen) according to the manufacturer’s protocol. Briefly, 300 μl of resuspended EVs were mixed with 90 μl Lysis solution biofluids (BF), vortexed for 5 s and incubated for 10 min at RT. 1 μl of RNA spike-in template mixture (miRCURY LNA™ Universal RT microRNA PCR, RNA spike-in kit) was added to each sample for downstream PCR analysis. Then, 30 μl Protein precipitation solution BF was added to samples and vortexed, incubated for 1 min at RT and centrifuged for 3 min at 11,000 g. The supernatants, after addition of 400 μl isopropanol, were vortexed for 5 s and then loaded in miRNA mini spin column BF. Columns were incubated for 2 min at RT, centrifuged for 30 s at 10,000 g, washed with Wash solution 1 BF and twice with Wash solution BF 2. Columns were centrifuged for 2 min at 11,000 g to dry membranes and RNA was eluted adding 30 μl RNase free H2O directly onto the membrane of the spin columns BF. Columns were incubated for 1 min at RT and then centrifuged for 1 min at 11,000 g. The purified RNA samples were stored at -80 °C.

qPCR assessment of extracellular vesicles miRNAs

Total RNA extracted from plasma exosomes was mixed with two artificial RNAs (RNA spike-ins as RT controls) and the final mixture (10 μl) was reverse transcribed at 42 °C for 60 min using the miRCURY LNA™ Universal RT cDNA Synthesis Kit (Qiagen) following the manufacturer’s instruction. The expression level of plasma EVs-miRNAs was evaluated by Serum/Plasma Focus microRNA PCR panels (Qiagen). The amplification curves were filtered (Ct < 36), imported into the GenEx software (ver.5, Qiagen) and normalized by global mean. The expression level (fold change [FC]) was calculated by taking the mean of individual Cq values for each group (HC, ERMS and ARMS patients). To validate the significant EVs-miRNAs in the plasma of an independent cohort of patients, we individually assayed mature miR-486-5p (cat.no. 339306-YP00204001), miR-17-5p (cat.no. 339306-YP02119304), miR-197-3p (cat.no. 339306-YP00204380), miR-483-5p (cat.no. 339306-YP00205693), miR-766-3p (cat.no. 339306-YP00204499), hsa-miR-132-3p (cat.no. 339306-YP00206035), hsa-miR-454-3p (cat.no. 339306-YP00205663), hsa-miR-484 (cat.no. 339306-YP00205636) and hsa-miR-335-5p (cat.no. 339306-YP02119293), by employing two endogenous miRNAs, namely miR-23a-3p (cat.no. 339306-YP00204772) and miR-320a (cat.no. 339306-YP00206042) that were selected by running Genorm and NormFinder analysis tools. QuantStudio 12 K Flex Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA) was employed for all the qPCR quantifications and the fold change was calculated by the 2−ΔΔCt method [26]. At least two independent amplifications were performed for each probe on triplicate samples. The raw Cq values from amplification curves (Serum/Plasma plates) were normalized by global mean using the GenEx qPCR analysis software (Exiqon ver 5), individual assays were normalized by taking miR-23a-3p and miR-320a as endogenous controls. Statistically significant (p < 0.05) miRNAs were obtained by ANOVA test (ERMS patients and ARMS patients versus controls). MiRNAs with a FC lower than -2 (FC < -2) and greater than 2 (FC > 2) in RMS patients and with a p-value lower than 0.05 compared to controls were considered highly dysregulated and retained for further bioinformatics analysis.

Bioinformatics analysis of Gene Expression Omnibus (GEO) dataset

A survey on the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/gds) repository was made to identify the publicly available miRNA expression datasets associated with RMS patients. The miRNA microarray-based expression data matrix from a cohort of 49 RMS Formalin-fixed paraffin-embedded tissues (primary not pre-treated tumors) collected at Fondazione IRCCS Istituto Nazionale dei Tumori (Milan, Italy) was retrieved for further analysis (ID: GSE135518). In this dataset, miRNA profile was performed using a SurePrint G3 Human miRNA r21 microarrays (Agilent) designed on miRBase 21.0 (miRNA). GSE135518 includes 27 pediatric RMS (0–14 years) and 22 AYA RMS (15- + 30 years)] as well as 13 normal tissue counterparts (CTRL) [27]. Primary data were collected using Agilent’s Feature Extraction software v10.7 (Agilent Technologies), background corrected, and quantile normalized using Bioconductor limma implementation in R. Differentially expressed miRNAs in the tissue sample between ARMS, ERMS and CTRL were identified imposing log2|FC|> 2 and adjusted p < 0.05 by using the GEO2R bioinformatics tool. Expression of miR-335-5p was retrieved from the data matrix and median expression was used to stratify patients for Kaplan–Meier analysis having overall survival as clinical endpoint. Patients’ clinical information’s are shown in Supplementary Table 2.

Bioinformatics target prediction of miR-335-5p and gene ontology

Target prediction of the miR-335-5p, was carried out by already reported procedure [28] that integrates the predictions of three different algorithms (i.e., TargetScan, MiRanda, and PITA). The list of target genes predicted in all databases were used for bioinformatics analysis. Gene Ontology (GO), KEGG pathway enrichment analysis, and annotation by DAVID bioinformatics tool [29] were performed, to determine the biological processes and signaling pathways in which the predicted targets of miR-335-5p were involved.

In situ hybridization (ISH)

Tumor sample paraffin embedded from 16 patients (10 ERMS and 6 ARMS) were obtained from the archives of Operative Unit of Pathology at Bambino Gesù Children’s Hospital. Formalin-fixed paraffin-embedded tumor samples were cut in RNAse-free environment at 5 µm thick, mounted on positive-charged slides. MiRNA in situ hybridization was performed as previously described [15]. Slides were analyzed by light microscopy with (Eclipse E600, Nikon). Each slide was scored by 2 independent, qualified observers, blinded on patient’s clinical information’s. miR-335-5p expression was semi-quantitatively evaluated based on staining intensity and distribution using a total score as follows: intensity score × proportional score. The intensity score (IS) was predefined as follows: 0, negative; 1, weak; 2, moderate and 3, strong. The proportional score (PS) was defined as follows: 0, negative; 1, < 10%; 2, 10%–50%; 3, > 50% positive cells [30].

Results

Profiling of extracellular vesicles miRNAs in plasma of RMS patients

We first analyzed EVs-miRNAs differentially expressed in the comparison between 10 RMS patients’ group (5 ARMS and 5 ERMS) and 4 HCs. A total of (171) miRNAs were expressed in RMS patients and (180) in HC. Among commonly expressed miRNAs, we focused on the EVs-miRNAs expressed in the 80% of RMS samples and HCs (116). A total of 41 miRNAs were significantly (p < 0.05) up or down regulated in one of the two groups (i.e., ERMS and ARMS), (Fig. 1, Supplementary Table 3).

Fig. 1
figure 1

Heatmap of the 41 statistically dysregulated EVs-miRNAs in ERMS and ARMS patients compared to HC. Upregulated and downregulated miRNAs are represented in red and green, respectively, P-value < 0.05

Full size image

Nine miRNAs (miR-483-5p, miR-132-3p, miR-766-3p, miR-454-3p miR-197-3p, miR-335-3p, miR-17-5p, miR-486-5p and miR-484) were highly upregulated in RMS patients compared to HCs, whereas no significant downregulated miRNAs were observed (Table 1).

Table 1 Highly dysregulated and statistically significant miRNAs (-2 > FC > 2; p-value < 0.05) detected in RMS patients compared to HCs, in ERMS and ARMS patients compared to HCs and in ARMS patients compared to ERMS patients
Full size table

Performing the analysis by histology, 5 miRNAs (miR-483-5p, miR-132-3p, miR-766-3p, miR-454-3p and miR-197-3p) were significantly upregulated in both ERMS and ARMS patients compared to HCs. Interestingly, 4 miRNAs (miR-335-5p, miR-17-5p, miR-486-5p and miR-484) were significantly upregulated in ARMS samples compared to ERMS patients (Table 1).

Validation of selected extracellular vesicles miRNAs from plasma by RT-qPCR

In order to validate the results obtained in our previous discovery analysis (Table 1), the expression level of the nine EVs-miRNAs (miR-483-5p, miR-132-3p, miR-766-3p, miR-454-3p and miR-197-3p, miR-335-5p, miR-17-5p, miR-486-5p and miR-484), found to be significantly upregulated in RMS were validated in additional samples by using real-time qPCR. In total, 12 ERMS, 9 ARMS and 13 HC were used in the validation analysis (Supplementary Table 1). The results, obtained by ANOVA test, showed that only miR-483-5p (p = 0.029), miR-484 (p = 0.007) and miR-335-5p (p = 0.003) resulted statistically significant between groups (Fig. 2). Interestingly, the three miRNAs were significantly upregulated in ARMS patients compared to HC and only mir-335-5p was significantly upregulated also compared to ERMS (Fig. 2). This suggest that miR-335-5p could be specifically related to ARMS histotype.

Fig. 2
figure 2

Significant EVs-miRNAs expression in the validation analysis evaluated by RT-qPCR. ** p < 0,01 (miRNA-484, miRNA-483-5p, miRNA-335-5p)

Full size image

Time-course analysis of miR-335-5p in two patients during treatment

We also analyzed EVs miR-335-5p expression during different treatment timepoints in two patients (ARMS 1 and ERMS 2), (Supplementary Fig. 2).

ARMS 1 was a 9 months old boy diagnosed with a parameningeal ARMS with bone and lymph nodes metastasis [2]. At the end of maintenance treatment with vinorelbine and cyclophosphamide, he presented a local relapse of disease. He received second line of treatment with vincristine, irinotecan and temodal [31]. The patients died after 2 cycles of VIT for further progression disease (PD). The expression of EVs miR-335-5p reduced during maintenance treatment but increased close to the end of maintenance and at the relapse.

ERMS 2 was a 8 years old girl diagnosed with a localized parameningeal ERMS (size more than 5 cm diameter, IRS III, N1, M0). She received chemotherapy according to EpSSG RMS 05 protocol, HR group. After the first 3 cycles of chemotherapy, she showed a partial response. She continued scheduled chemotherapy, and she received radiotherapy on the tumor and lymph nodes. For local PD, she was treated with a second line chemotherapy with vincristine, irinotecan and pazopanib [32]. The expression of EVs miR-335-5p reduced after the third cycle of chemotherapy, but increased again after the 4th cycle and at the diagnosis of local PD. She is still alive after 6 years of treatment stop.

Prediction of target genes and hub genes of Kegg pathway network of miR-335-5p

By following our bioinformatics approach, we obtained a list of 1292 target genes predicted for miR-335-5p. By GO enrichment analysis (http://amigo.geneontology.org) we found that the most enriched items with a p-value < 0.001 are: positive regulation of transcription from RNA polymerase II promoter (GO:0045944); cell division (GO:0051301); cellular response to insulin stimulus (GO:0032869); regulation of alternative mRNA splicing, via spliceosome (GO:0000381); corticospinal tract morphogenesis (GO:0021957), (Fig. 3A). The KEGG pathways analysis showed an enrichment in target genes with a p-value < 0.01 implicated in: Ras signaling pathway (hsa04014) [33]; Cell cycle (hsa04110); Endocrine and other factor-regulated calcium reabsorption (hsa04961), (Fig. 3B).

Fig. 3
figure 3

Bioinformatic analysis of predicted targets of miR-335-5p. A GO enrichment analysis; B KEGG Pathways; C Cytoscape interaction network

Full size image

Finally, we carried out a bioinformatic analysis to identify the target genes of miR-335-5p involved in biological processes that contribute to metastatic behavior such as cell migration (GO:0016477), cell motility (GO:0048870), and cytoskeleton organization (GO0007010). In GO biological processes, 257 genes belong to cell migration, 31 to cell motility, 134 to cytoskeleton organization and 35 genes were in common in all of the three pathways. We extracted the intersection of these lists and the connections between miR-335-5p, and its target genes were visualized in Fig. 3C as an interaction network (by Cytoscape).

MiR-335-5p is upregulated in RMS tissues

In order to investigate if miR-335-5p was expressed also in RMS tissues, we used the dataset GSE135518 obtained from the GEO database (https://www.ncbi.nlm.nih.gov/gds/). We observed that miR-335-5p was upregulated in RMS tumor tissues (49 patients) with respect to normal tissues (13 subjects), (p = 0.00202), and upregulated significantly between ARMS and ERMS (p = 0.04), (Fig. 4A). Furthermore, the miRNA expression correlated with the Intergroup Rhabdomyosarcoma Study (IRS) grouping system, (p = 0.0234), (Fig. 4B) and patients with high miR-335-5p expression had a lower Overall- (OS, p = 0.044) and Progression Free-survival (PFS, p = 0.025), (Fig. 4C, D).

Fig. 4
figure 4

Bioinformatics analysis of expression of miR-335-5p, from GSE135518 database in RMS tissues compared to normal tissue. A Comparison between miR-335-5p expression and histology B Comparison between miR-335-5p and IRS; C Correlation between miR-335-5p and OS and (D) PFS**** p < 0,0001; ** p < 0,01; * p < 0,05

Full size image

To explore miR-335-5p expression in tumor cells and microenvironment, ISH was performed on paraffin-embedded RMS tumor samples of 6 ARMS and 10 ERMS patients. MiR-335-5p signal was observed exclusively in the cytoplasm of cancer cells. With the limitation of low numbers of samples, we observed a median total score of 3.3 in ARMS and 2.3 in ERMS patients (see Materials and Methods section for the score calculation). Representative pictures are shown in Fig. 5.

Fig. 5
figure 5

Representative miR-335-5p ISH staining images in tissue samples of RMS patients (× 400). The panel shows the presence of miR-335-5p in tumor cells

Full size image

Discussion

The use of liquid biopsy to track tumor-related biomarkers at diagnosis, during treatment or follow-up, represents a very promising tool, especially in the field of pediatric tumors, due to the non-invasive characteristics of this approach.

In this study, we performed a miRNA profile of plasma EVs isolated from patients affected by RMS, to identify specific tumor related biomarkers. MiRNAs have been largely studied in RMS tumors; in particular, they can directly modulate myogenic-regulatory factors thereby regulating RMS development and progression. Muscle-specific miRNAs, termed myomiRs, are indeed important for regulation of cell proliferation and myoblasts differentiation, which are key processes for muscle development. The deregulation of myomiRs expression may inhibit the correct skeletal muscle growth causing the occurrence of muscle-related disorders [34,35,36]. Several myomiRs have been involved in the development of RMS, especially those with tumor suppressive activity.

For example, it has been described that PAX7, which is a gene essential for ARMS cell differentiation and tumor progression, was downregulated by miR-206 [37]. Low miR-206 expression in RMS tissues correlated with poor survival in ERMS and ARMS patients [38]. Among circulating biomarkers, exosomal miRNAs are potentially highly useful since they are stable and have been described to be tumor type-specific [39,40,41]. Concerning RMS, Ghayad and collaborators reported 31 miRNAs commonly deregulated in exosomes released by ARMS and ERMS cell lines [24]. Interestingly, RMS-derived exosomes increased the migration and invasion of normal recipient fibroblasts and endothelial cells in a dose-dependent manner, underlining their putative contribution to the metastatic process [24]. In a separate work, Hanna and colleagues identified miR-486-5p, a downstream target of the PAX3-FOXO1 chimeric protein, as highly expressed in ARMS cell lines-derived exosomes [18]. In a small cohort of RMS patients (6 ERMS and 1 ARMS), miR-486-5p was enriched in serum exosomes and its value was reduced after chemotherapy [42].

In our first analysis, miR-486-5p was significantly upregulated in ARMS patients in comparison to ERMS and HCs (Table 1), however the validation analysis did not confirm this observation.

We identified miR-335-5p, as significantly upregulated in plasma EVs of patients affected by ARMS compared to HCs and ERMS. The analysis of different time points for two RMS patients demonstrated a reduction of EVs-miR-335-5p expression during treatment, but an increase before diagnosis of disease recurrence. MiR-335-5p expression was increased in ARMS tumor compared to ERMS and surrounding healthy muscle as showed in the GEO dataset. The ISH revealed the localization in the tumor cells. Furthermore miR-335-5p expression correlated with IRS, as well as with OS and PFS.

MiR-335-3p is induced during myoblast differentiation and highly expressed during muscle regeneration [43]. Indeed, deregulation of miR-335 is implicated in several muscle-related diseases [44] being involved in multiple cellular processes including proliferation and apoptosis. In cancer miR‐335 presents a dual role, having both oncosuppressor and oncogenic function depending on tumor type and can affect treatment resistance of cancer [45,46,47,48]. Interestingly, exosomes from metastatic colorectal cancer cell lines, carrying miR‐335, promote migration, invasion, and epithelial to mesenchymal transition (EMT) [49]. High levels of miR-335 have been identified in tumors and plasma derived from patients affected by gastric cancer and uterine sarcoma patients with poor prognosis [50, 51]. In this perspective, miR-335 could be considered as a potential prognostic biomarker [52].

Concerning RMS, two teams documented the overexpression of miR-335-5p in RMS tumor samples and in particular in ARMS [53, 54]. Hanna and colleagues observed that silencing of PAX3-FOXO1 in ARMS cell lines induced downregulation of miR-335-3p, while PAX3-FOXO1 overexpression in ERMS cell line determine an upregulation of this miRNA [18].

Conclusion

In our study we observed that miR-335-5p expression is up-regulated in EVs isolated from plasma and in tumor samples of patients affected by ARMS in comparison to ERMS and HCs and miR335-5p expression appears to be associated with stage and survival in RMS patients. Considering the limited number of samples, it was not possible to define in this study if miR-335-5p could be an independent prognostic biomarker or if the worse prognosis is due to the presence of alveolar histology. Therefore, further studies with larger sample sizes are needed to confirm these findings and to deeply elucidate its biological role.

Availability of data and materials

All data generated or analyzed during this study are included in this published article. Datasets are described in the material and methods section and public available (accession number is provided).

Abbreviations

RMS:

Rhabdomyosarcoma

ERMS:

Embryonal Rhabdomyosarcoma

ARMS:

Alveolar Rhabdomyosarcoma

EFS:

Event free survival

OS:

Overall survival

cfDNA:

Circulating free DNA

miRNAs:

MicroRNAs

EVs:

Extracellular vesicles

EVs-miRNAs:

Extracellular Vesicles microRNA

HC:

Healthy children

RT:

Room temperature

MISEV:

Minimal Information for Studies of Extracellular Vesicles

TEM:

Transmission Electron Microscopy

TSG101:

Tumor Susceptibility Gene 101

BF:

Biofluids

FC:

Fold change

GEO:

Gene Expression Omnibus

CTRL:

Normal tissue counterparts

GO:

Gene Ontology

ISH:

In situ hybridization

IS:

Intensity score

PS:

Proportional score

PD:

Progression disease

IRS:

Intergroup Rhabdomyosarcoma Study

EMT:

Epithelial to mesenchymal transition

References

  1. ‘SEER Cancer Statistics Review 1975–2003 - Previous Version - SEER Cancer Statistics’, SEER. Accessed  28  Mar 2024. Available: https://seer.cancer.gov/archive/csr/1975_2003/index.html.

  2. Schoot RA, et al. Metastatic Rhabdomyosarcoma: Results of the European Paediatric Soft Tissue Sarcoma Study Group MTS 2008 Study and Pooled Analysis With the Concurrent BERNIE Study. J Clin Oncol. 2022;40(32):3730–40. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/JCO.21.02981.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Sorensen PHB, et al. PAX3-FKHR and PAX7-FKHR Gene Fusions Are Prognostic Indicators in Alveolar Rhabdomyosarcoma: A Report From the Children’s Oncology Group. J Clin Oncol. 2002;20(11):2672–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/JCO.2002.03.137.

    Article  PubMed  CAS  Google Scholar 

  4. ‘Prognostic Factors and Clinical Outcomes in Children and Adolescents With Metastatic Rhabdomyosarcoma—A Report From the Intergroup Rhabdomyosarcoma Study IV | Journal of Clinical Oncology’. Accessed 28 Mar 2024. .Available: https://ascopubs.org/doi/10.1200/JCO.2003.06.129?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed.

  5. Ferrari A, et al. ‘Metastatic rhabdomyosarcoma: Evidence of the impact of radiotherapy on survival. A retrospective single-center experience.’ Pediatr Blood Cancer. 2022;69:e29853. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/pbc.29853.

    Article  PubMed  CAS  Google Scholar 

  6. McDowell HP, Foot ABM, Ellershaw C, Machin D, Giraud C, Bergeron C. Outcomes in paediatric metastatic rhabdomyosarcoma: Results of The International Society of Paediatric Oncology (SIOP) study MMT-98. Eur J Cancer. 2010;46(9):1588–95. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ejca.2010.02.051.

    Article  PubMed  Google Scholar 

  7. Reimers N, Pantel K. Liquid biopsy: novel technologies and clinical applications. Clin Chem Lab Med CCLM. 2019;57(3):312–6. https://doiorg.publicaciones.saludcastillayleon.es/10.1515/cclm-2018-0610.

    Article  PubMed  CAS  Google Scholar 

  8. Gold B, Cankovic M, Furtado LV, Meier F, Gocke CD. Do Circulating Tumor Cells, Exosomes, and Circulating Tumor Nucleic Acids Have Clinical Utility?: A Report of the Association for Molecular Pathology. J Mol Diagn. 2015;17(3):209–24. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jmoldx.2015.02.001.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Mathivanan S, Ji H, Simpson RJ. Exosomes: Extracellular organelles important in intercellular communication. J Proteomics. 2010;73(10):1907–20. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jprot.2010.06.006.

    Article  PubMed  CAS  Google Scholar 

  10. Azmi AS, Bao B, Sarkar FH. ‘Exosomes in Cancer Development, Metastasis and Drug Resistance: A Comprehensive Review.’ Cancer Metastasis Rev. 2013;32:623–42. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10555-013-9441-9.

    Article  PubMed  CAS  Google Scholar 

  11. Ge Q, Zhou Y, Lu J, Bai Y, Xie X, Lu Z. miRNA in Plasma Exosome is Stable under Different Storage Conditions. Molecules. 2014;19(2):1568–75. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/molecules19021568.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Cheng L, Sharples RA, Scicluna BJ, Hill AF. Exosomes provide a protective and enriched source of miRNA for biomarker profiling compared to intracellular and cell-free blood. J Extracell Vesicles. 2014;3. https://doiorg.publicaciones.saludcastillayleon.es/10.3402/jev.v3.23743.

  13. Kosaka N, Iguchi H, Ochiya T. Circulating microRNA in body fluid: a new potential biomarker for cancer diagnosis and prognosis. Cancer Sci. 2010;101(10):2087–92. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1349-7006.2010.01650.x.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Galardi A, et al. Exosomal MiRNAs in Pediatric Cancers. Int J Mol Sci. 2019;20(18):4600. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/ijms20184600.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Colletti M, et al. Neuroblastoma-secreted exosomes carrying miR-375 promote osteogenic differentiation of bone-marrow mesenchymal stromal cells. J Extracell Vesicles. 2020;9(1):1774144. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/20013078.2020.1774144.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Sarver AL, Li L, Subramanian S. MicroRNA miR-183 Functions as an Oncogene by Targeting the Transcription Factor EGR1 and Promoting Tumor Cell Migration. Cancer Res. 2010;70(23):9570–80. https://doiorg.publicaciones.saludcastillayleon.es/10.1158/0008-5472.CAN-10-2074.

    Article  PubMed  CAS  Google Scholar 

  17. Tombolan L, Zampini M, Casara S, Boldrin E, Zin A, Bisogno G, Rosolen A, De Pittà C, Lanfranchi G. MicroRNA-27a Contributes to Rhabdomyosarcoma Cell Proliferation by Suppressing RARA and RXRA. PloS one. 2015;10(4):e0125171. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pone.0125171.

  18. Hanna JA, et al. PAX3-FOXO1 drives miR-486-5p and represses miR-221 contributing to pathogenesis of alveolar rhabdomyosarcoma. Oncogene. 2018;37(15):1991–2007. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41388-017-0081-3.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Tombolan L, et al. Circulating miR-26a as Potential Prognostic Biomarkers in Pediatric Rhabdomyosarcoma. Front Genet. Dec.2020;11: 606274. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fgene.2020.606274.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Molist C, et al. miRNA-7 and miRNA-324-5p regulate alpha9-Integrin expression and exert anti-oncogenic effects in rhabdomyosarcoma. Cancer Lett. May2020;477:49–59. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.canlet.2020.02.035.

    Article  PubMed  CAS  Google Scholar 

  21. Wang Y, et al. MicroRNA-29 family inhibits rhabdomyosarcoma formation and progression by regulating GEFT function. Am J Transl Res. 2020;12(3):1136.

    PubMed  PubMed Central  CAS  Google Scholar 

  22. Pan Y, et al. Down-Regulated miR-130a/b Attenuates Rhabdomyosarcoma Proliferation via PPARG. Front Mol Biosci. Feb.2022;8: 766887. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fmolb.2021.766887.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Casanova M, et al. MiR-223 Exclusively Impairs In Vitro Tumor Growth through IGF1R Modulation in Rhabdomyosarcoma of Adolescents and Young Adults. Int J Mol Sci. Nov.2022;23(22):13989. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/ijms232213989.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Ghayad SE, et al. Exosomes derived from embryonal and alveolar rhabdomyosarcoma carry differential miRNA cargo and promote invasion of recipient fibroblasts. Sci Rep. Nov.2016;6:37088. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/srep37088.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Welsh JA, et al. Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches. J Extracell Vesicles. Feb.2024;13(2): e12404. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/jev2.12404.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Livak KJ, Schmittgen TD. Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method. Methods. Dec.2001;25(4):402–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1006/meth.2001.1262.

    Article  PubMed  CAS  Google Scholar 

  27. P. Gasparini et al., ‘Age-Related Alterations in Immune Contexture Are Associated with Aggressiveness in Rhabdomyosarcoma’, Cancers, vol. 11, no. 9, Art. no. 9, Sep. 2019, https://doiorg.publicaciones.saludcastillayleon.es/10.3390/cancers11091380.

  28. Masotti A, Alisi A. Integrated bioinformatics analysis of microRNA expression profiles for an in-depth understanding of pathogenic mechanisms in non-alcoholic fatty liver disease. J Gastroenterol Hepatol. 2012;27(2):187–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1440-1746.2011.07032.x.

    Article  PubMed  CAS  Google Scholar 

  29. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. Jan.2009;4(1):44–57. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nprot.2008.211.

    Article  PubMed  CAS  Google Scholar 

  30. Sato K, Miyamoto M, Takano M, Tsuda H. MicroRNA-21 expression in cancer cells is an independent biomarker of progression-free survival of endometrioid endometrial carcinoma. Virchows Arch. Nov.2021;479(5):883–91. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s00428-021-03171-w.

    Article  PubMed  CAS  Google Scholar 

  31. B. A. Setty et al., ‘VIncristine, irinotecan, and temozolomide in children and adolescents with relapsed rhabdomyosarcoma’, Pediatr. Blood Cancer, vol. 65, no. 1, p. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/pbc.26728, Jan. 2018, https://doiorg.publicaciones.saludcastillayleon.es/10.1002/pbc.26728.

  32. Russo I, et al. A Chart Review on the Feasibility and Safety of the Vincristine Irinotecan Pazopanib (VIPaz) Association in Children and Adolescents With Resistant or Relapsed Sarcomas. Front Oncol. Aug.2020;10:1228. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fonc.2020.01228.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Chiricosta L, et al. Extracellular Vesicles of Human Periodontal Ligament Stem Cells Contain MicroRNAs Associated to Proto-Oncogenes: Implications in Cytokinesis. Front Genet. Jun.2020;11:582. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fgene.2020.00582.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Chen J-F, et al. The role of microRNA-1 and microRNA-133 in skeletal muscle proliferation and differentiation. Nat Genet. Feb.2006;38(2):228–33. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ng1725.

    Article  PubMed  CAS  Google Scholar 

  35. McCarthy JJ. MicroRNA-206: the skeletal muscle-specific myomiR. Biochim Biophys Acta. Nov.2008;1779(11):682–91. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.bbagrm.2008.03.001.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Horak M, Novak J, Bienertova-Vasku J. Muscle-specific microRNAs in skeletal muscle development. Dev Biol. Feb.2016;410(1):1–13. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ydbio.2015.12.013.

    Article  PubMed  CAS  Google Scholar 

  37. Hanna JA, et al. PAX7 is a required target for microRNA-206-induced differentiation of fusion-negative rhabdomyosarcoma. Cell Death Dis. Jun.2016;7(6): e2256. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/cddis.2016.159.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Missiaglia E, et al. MicroRNA-206 expression levels correlate with clinical behaviour of rhabdomyosarcomas. Br J Cancer. Jun.2010;102(12):1769–77. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/sj.bjc.6605684.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Ma J, et al. Exosomal hsa-miR199a-3p Promotes Proliferation and Migration in Neuroblastoma. Front Oncol. Jun.2019;9:459. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fonc.2019.00459.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Yamaoka B, et al. Exosomal miR-214-3p as a potential novel biomarker for rhabdoid tumor of the kidney. Pediatr Surg Int. Dec.2021;37(12):1783–90. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s00383-021-04989-w.

    Article  PubMed  Google Scholar 

  41. Xue P, et al. Exosomal miR-101-3p and miR-423-5p inhibit medulloblastoma tumorigenesis through targeting FOXP4 and EZH2. Cell Death Differ. Jan.2022;29(1):82–95. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41418-021-00838-4.

    Article  PubMed  CAS  Google Scholar 

  42. Ghamloush F, et al. The PAX3-FOXO1 oncogene alters exosome miRNA content and leads to paracrine effects mediated by exosomal miR-486. Sci Rep. Oct.2019;9(1):14242. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41598-019-50592-4.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Greco S, et al. Common micro-RNA signature in skeletal muscle damage and regeneration induced by Duchenne muscular dystrophy and acute ischemia. FASEB J. 2009;23(10):3335–46. https://doiorg.publicaciones.saludcastillayleon.es/10.1096/fj.08-128579.

    Article  PubMed  CAS  Google Scholar 

  44. Huang B, et al. Putative MicroRNA-mRNA Networks Upon Mdfi Overexpression in C2C12 Cell Differentiation and Muscle Fiber Type Transformation. Front Mol Biosci. Oct.2021;8: 675993. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fmolb.2021.675993.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Wang H, et al. Effect of miR-335 upregulation on the apoptosis and invasion of lung cancer cell A549 and H1299. Tumor Biol. Oct.2013;34(5):3101–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s13277-013-0878-9.

    Article  CAS  Google Scholar 

  46. Lu Y, et al. Overexpression of miR-335 confers cell proliferation and tumour growth to colorectal carcinoma cells. Mol Cell Biochem. Jan.2016;412(1):235–45. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s11010-015-2630-9.

    Article  PubMed  CAS  Google Scholar 

  47. Kim Y, Kim H, Park D, Jeoung D. miR-335 Targets SIAH2 and Confers Sensitivity to Anti-Cancer Drugs by Increasing the Expression of HDAC3. Mol Cells. Jun.2015;38(6):562–72. https://doiorg.publicaciones.saludcastillayleon.es/10.14348/molcells.2015.0051.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Hao J, Lai M, Liu C. Expression of miR-335 in triple-negative breast cancer and its effect on chemosensitivity. J BUON Off J Balk Union Oncol. 2019;24(4):1526–31.

    Google Scholar 

  49. Sun X, et al. Exosome-transmitted miRNA-335-5p promotes colorectal cancer invasion and metastasis by facilitating EMT via targeting RASA1. Mol Ther Nucleic Acids. Feb.2021;24:164–74. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.omtn.2021.02.022.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Yan Z, et al. Identification of hsa-miR-335 as a prognostic signature in gastric cancer. PLoS ONE. 2012;7(7): e40037. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pone.0040037.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Gonzalez Dos Anjos L, et al. Could miRNA Signatures be Useful for Predicting Uterine Sarcoma and Carcinosarcoma Prognosis and Treatment? Cancers. Sep.2018;10(9):315. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/cancers10090315.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Ye L, et al. Functions and Targets of miR-335 in Cancer. OncoTargets Ther. 2021;14:3335–49. https://doiorg.publicaciones.saludcastillayleon.es/10.2147/OTT.S305098.

    Article  Google Scholar 

  53. Megiorni F, et al. Deep Sequencing the microRNA profile in rhabdomyosarcoma reveals down-regulation of miR-378 family members. BMC Cancer. Nov.2014;14(1):880. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/1471-2407-14-880.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Bersani F, et al. Deep Sequencing Reveals a Novel miR-22 Regulatory Network with Therapeutic Potential in Rhabdomyosarcoma. Cancer Res. Oct.2016;76(20):6095–106. https://doiorg.publicaciones.saludcastillayleon.es/10.1158/0008-5472.CAN-16-0709.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

We are grateful to “Il sorriso di Costanza” and “Il cuore grande di Flavio” Onlus for their support.

Funding

This research received no external funding.

Author information

Author notes

  1. Giuseppe Maria Milano, Franco Locatelli & Angela Di Giannatale

    Present address: Hematology/Oncology and Cell and Gene Therapy Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy

  2. Giuseppe Maria Milano, Franco Locatelli and Angela Di Giannatale these authors contributed equally to this work (co-last authors).

Authors and Affiliations

  1. Hematology/Oncology and Cell and Gene Therapy Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy

    Virginia Di Paolo, Angela Galardi, Marta Colletti, Silvia Lampis, Evelina Miele, Ida Russo & Valentina Di Ruscio

  2. Multifactorial and Complex Phenotype Research Area, Bambino Gesù Children’s Hospital-IRCCS, Rome, Italy

    Alessandro Paolini & Andrea Masotti

  3. Tumor Genomics Unit, Department of Research, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy

    Patrizia Gasparini

  4. Molecular Mechanisms Unit, Department of Research, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy

    Loris De Cecco

  5. Oncodesign SA, Dijon, 21079, France

    Salvatore Raieli

  6. Research Laboratories, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy

    Cristiano De Stefanis

  7. Pediatric Oncology Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy

    Michela Casanova

  8. Pathology Unit and Predictive Molecular Pathology Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy

    Rita Alaggio

  9. Department of Life Sciences and Public Health, Catholic University of the Sacred Heart, Rome, Italy

    Franco Locatelli

Authors
  1. Virginia Di Paolo
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Alessandro Paolini
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Angela Galardi
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Patrizia Gasparini
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Loris De Cecco
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Marta Colletti
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Silvia Lampis
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Salvatore Raieli
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Cristiano De Stefanis
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Evelina Miele
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Ida Russo
    View author publications

    You can also search for this author inPubMed Google Scholar

  12. Valentina Di Ruscio
    View author publications

    You can also search for this author inPubMed Google Scholar

  13. Michela Casanova
    View author publications

    You can also search for this author inPubMed Google Scholar

  14. Rita Alaggio
    View author publications

    You can also search for this author inPubMed Google Scholar

  15. Andrea Masotti
    View author publications

    You can also search for this author inPubMed Google Scholar

  16. Giuseppe Maria Milano
    View author publications

    You can also search for this author inPubMed Google Scholar

  17. Franco Locatelli
    View author publications

    You can also search for this author inPubMed Google Scholar

  18. Angela Di Giannatale
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

VDP and ADG designing and conceptualization research study; VDP, AP, AG, SL, CDS conducting experiments; VDP, AP, AG, SL, RA acquiring data; VDP, AP, PG, LDC, SR analyzing data; ADG, IR, VDR, RA, GMM providing patient samples; ADG funding acquisition; VDP and ADG writing—original draft preparation; VDP, AP, MC, EM, AM, FL and ADG writing, reviewing and editing the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Angela Di Giannatale.

Ethics declarations

Ethics approval and consent to participate

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of Ospedale Pediatrico Bambino Gesù, IRCCS (protocol code 1189_OPBG_2016; date of approval: 12–08-2016). Informed consent was obtained from all subjects involved in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no potential conflicts of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary Material 1: Supplementary Methods.

13046_2024_3197_MOESM2_ESM.docx

Supplementary Material 2: Supplementary Table 1: Clinical characteristics of the RMS patients involved in the study.  Supplementary Table 2: Clinical characteristics of the RMS patients included in the GEO Dataset (GSE135518).

13046_2024_3197_MOESM3_ESM.pdf

Supplementary Material 3: Supplementary Figure 1:  Characterization of EVs isolated from plasma of HC and RMS patients. (A) Representative TEM images of plasma EVs isolated from HC, ARMS and ERMS patients. Scale bar = 200 nm. (B) Nanoparticle tracking analysis. The calculated size distribution is depicted as mean (black line) with standard error (red shading). (C) Western blot analysis of the typical EVs proteins, TSG101, CD9, CD63 and endoplasmic reticulum protein Calnexin for representative samples. HSP90 was reported as control. 

13046_2024_3197_MOESM4_ESM.pdf

Supplementary Material 4: Supplementary Figure 2: Expression of Evs-miR-335-5p at different time point in one ARMS and one ERMS patients. ARMS t1, t2 and t3:  maintenance treatments; t4: local relapse. ERMS t1: diagnosis; t2: 3rd cycle chemotherapy; t3: 4th cycle chemotherapy; t4: local PD.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Di Paolo, V., Paolini, A., Galardi, A. et al. Plasma-derived extracellular vesicles miR-335–5p as potential diagnostic biomarkers for fusion-positive rhabdomyosarcoma. J Exp Clin Cancer Res 43, 282 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13046-024-03197-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13046-024-03197-3

Keywords

Journal of Experimental & Clinical Cancer Research

ISSN: 1756-9966

Contact us