Profiling and functional analysis of exosomal circRNAs from EBV-associated gastric carcinoma CSCs

Profiling and functional analysis of exosomal circRNAs from EBV-associated gastric carcinoma CSCs | 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 Research Article Profiling and functional analysis of exosomal circRNAs from EBV-associated gastric carcinoma CSCs Li-ping Gong, Yi-ting Shao, Yu Du, Li-ping Sun, Lu-ying Tang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6704451/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Jan, 2026 Read the published version in Journal of Cancer Research and Clinical Oncology → Version 1 posted 8 You are reading this latest preprint version Abstract Recent studies have found that Epstein-Barr virus (EBV) encodes circular RNAs (ebv-circRNAs) that are involved in tumorigenesis process in EBV-associated gastric carcinoma (EBVaGC). Since little is known whether circRNAs can be enriched into exosomes and their functions in EBVaGC, the aim of our work was to investigate the expression pattern of circRNAs in exosomes derived from EBVaGC cancer stem cells (CSCs). Here, we found two circRNAs, ebv-circLMP2A and hsa-circRNF13 were enriched in EBVaGC CSCs derived exosomes and positively associated with EBVaGC patients with metastasis. Bioinformatics analysis predicted that miR-5683 is the most likely potential target for hsa-circRNF13, and lower miR-5683 expression was positively correlated with microvessel density and Ki67 expression in clinical samples of EBVaGC. Cytology experiments showed that EBVaGC CSCs derived exosomes significantly promoted the invasive growth of EBVaGC cells. Our findings suggest that exosomal circRNAs could be a promising diagnostic and therapeutic target for EBVaGC. EBVaGC Cancer stem cells Exosomes Circular RNAs Bioinformatics analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Epstein-Barr virus (EBV), recognized as the most prevalent cancer-causing virus in humans, establishes a lifelong latent infection that persists in more than 90% of the global adult population[ 1 ]. Latent infections caused by EBV have been linked to the development of lymphomas and epithelial cancers, including Burkitt's lymphoma (BL), Hodgkin's lymphoma (HL), nasopharyngeal carcinoma (NPC), and gastric carcinoma (GC)[ 2 ]. In particular, EBV-associated gastric carcinoma (EBVaGC) stands out as one of the leading causes of mortality related to EBV, with an estimated 75,000 to 90,000 new cases annually[ 3 ]. This subtype constitutes around 10% of all gastric cancer cases and is characterized by unique genomic, molecular, and clinicopathological traits[ 4 ]. As we know, tumor cells are hierarchically organized and sustained by a subpopulation of cells, known as cancer stem cells (CSCs), which possess stem-like functional properties such as strong self-renewal, differentiation, tumorigenesis and drug resistance[ 5 ]. In our previous study, we have established a method to enrich EBVaGC CSCs using a successive xenograft model under chemotherapy pressure and have demonstrated that EBV-encoded circLMP2A (ebv-circLMP2A) could induce stem like properties in vitro and in vivo [ 6 ]. Exosomes are nanoscale membrane vesicles released by diverse cell types, typically measuring 50–200nm in diameter[ 7 ]. Mounting evidences have indicated that exosomes can remodel the biological behaviors of recipient cell which was involved in tumor initiation, progression and metastasis by transferring specific cargos including protein, mRNA and microRNA[ 8 ]. Recent studies have revealed that CSCs also release exosomes to tumor microenvironment (TME) and promote tumor growth, metastasis and immune escape by influencing their surrounding niche. For example, exosomal 5′-triphosphate RNA secreted by colorectal CSCs could stimulate neutrophils and further promote tumorigenesis of colorectal cancer cells through inducing the expression of IL-1β[ 9 ]. Clear cell renal cell carcinoma (CCRCC) CSCs derived exosomes significantly promoted proliferation and metastasis of CCRCC cells by transporting miR-19b-3p into CCRCC cells[ 10 ]. Although with the in-depth research of EBV-associated malignancies, increasing studies have shown that EBV-infected tumor cells continuously release exosomes containing viral components in EBV-positive NPC and transformed lymphoblastoid cell lines, their functions in the recipient cells were not explored until recently. For example, LMP1-positive exosomes increased the migration and invasiveness of the recipient nasopharyngeal cell lines[ 11 ]. Gallo et al. found that EBV BART and BHRF1 miRNAs are loaded into the exosomes secreted from LCLs and can be internalized by co-cultured dendritic cells[ 12 ]. Recently, Hinata M et al. discovered that EBVaGC derived exosomes could suppress the maturation of dendritic cells[ 13 ]. These studies indicated that exosomes from EBV-associated malignancies provide a new insight into the biological mechanisms of these diseases. CircRNAs are newly discovered covalently closed circular RNAs that regulate gene expression at both transcriptional and posttranscriptional levels[ 14 ]. A growing number of studies have discovered that circRNAs have cancer-specific expression pattern and are involved in cancer progression and metastasis[ 15 ]. Moreover, recent studies have shown that circRNAs are enriched and stable in exosomes which play vital roles in the progression of cancer and could be a promising biomarker for cancer diagnosis and prognosis [ 16 , 17 ]. Our previous studies and other reports have proved that EBV can encode multiple circRNAs (ebv-circRNAs), and further functional analysis has shown that these ebv-circRNAs regulate EBV-driven cancer phenotypes, and ebv-circLMP2A specifically controls cancer stem cells and angiogenesis in EBVaGC[ 6 , 18 ]. Ebv-circRPMS1 promoted the proliferation and metastasis of NPC cells and EBVaGC cells[ 19 , 20 ]. However, whether circRNAs are packaged into EBVaGC derived exosomes and their potential functions are still left to be explored. In this study, we explored the alterations of both ebv-circRNAs and human circRNAs expression in exosomes from EBVaGC CSCs and elucidate their functional relevance. These findings will provide a novel perspective on mechanisms by which exosomal circRNAs participate in EBVaGC progression. 2. Materials and Methods 2.1 Cell culture EBVaGC cell lines SNU719 (RRID: CVCL_5086, authenticated by Short Tandem Repeat (STR) profiling within the last 3 years by Guangzhou Cellcook Biotech Co., Ltd) was purchased from Korean Cell Line Bank. EBVaGC cell line SNU4th with properties of CSCs was constructed by our previous study[6], STR profiling confirmed SNU4th originated from SNU719. EBVaGC cell line YCCEL1 (RRID: CVCL_l440, authenticated by STR profiling within the last 3 years by Guangzhou Cellcook Biotech Co., Ltd) was provided by Dr. Qian Tao from the State Key Laboratory of Oncology at the Chinese University of Hong Kong. SNU719 and YCCEL1 cell lines were cultured in RPMI-1640 medium (Gibco, Carlsbad, CA, USA) with 10% FBS (Gibco). SNU4th cell line was cultured as spheres in serum-free medium containing RPMI-1640, B27 supplement (Life Technologies, Carlsbad, CA, USA), 10 ng/mL fibroblast growth factor (Miltenyi Biotec, Bergisch Gladbach, Germany), 10 ng/mL epidermal growth factor (Miltenyi Biotec), 50 μg/ml insulin (Life Technologies) and 1% penicillin/streptomycin (Life Technologies) in a T75 cm 2 ultralow attachment flask (Corning, New York, NY, USA). All cells were cultured under standard conditions (37°C, 5% CO2, humidified atmosphere), mycoplasma-tested cells were used for all experiments. 2.2 Xenografts and patient samples The xenograft model under chemotherapy pressure to enrich EBVaGC CSCs was established in previous experiment[6]. Briefly, SNU719 cells were subcutaneously injected (2×10⁶ cells/mouse) into 4-week-old female NOD/SCID mice (Model Animal Research Center of Nanjing University). Mice received weekly tail vein injections of 5-Fu (20 mg/kg, Selleck). Tumors were harvested when reaching 1.5cm diameter, digested with collagenase to generate single-cell suspensions, and passage through 5-Fu-treated mice for three generations. Tumor tissues were paraffin-embedded for analysis, while peripheral blood collected via retro-orbital bleeding was processed to isolate serum by sequential centrifugation (500×g 10min, 3000×g 20min) for exosomal RNA extraction. Sixty-nine paraffin-embedded EBVaGC samples were obtained from the Third Affiliated Hospital of Sun Yat-Sen University between January 2006 and June 2012. Inclusion criteria followed those previously defined by Du et al[18], with all cases staged according to the 8th AJCC TNM Classification for Gastric Cancer. 2.3 Exosomes isolation and characterization Exosomes from cells were isolated according to differential ultracentrifugation method described in the literature[21]. Briefly, cells were serum-starved for 24 hours before conditioned medium was collected. Successive centrifugation (500×g 5min, 2000×g 10min, 5000×g 20min at 4°C) removed cellular debris. Supernatant was then ultracentrifuged at 120,000×g for 70min at 4°C using a Beckman ultracentrifuge. For xenograft serum, exosomes were isolated using a Total Exosome Isolation Kit (Invitrogen) per manufacturer's instructions. Isolated exosomes were resuspended in PBS for immediate use or cryopreserved at -80°C. Exosome characterization: Transmission electron microscopy (TEM, Philips CM120) was used to analyze morphology and size. Exosome suspension was applied to carbon-coated formvar grids for 10min, stained with 1% phosphotungstic acid (pH 6.8) for 5 min, and imaged under TEM at 10,000–200,000× magnification. Nanoparticle tracking analysis (NTA, NanoSight NS300 instrument, Malvern, UK): Exosome size distribution and concentration were determined using a NanoSight NS300 instrument. The samples were prepared by diluting 10 μL exosome suspension 1:10 with distilled water, loaded into the sample chamber, and analyzed in triplicate. The instrument was calibrated to capture 50–100 particles per frame, with size distribution and concentration data automatically generated and exported as PDF reports. Western blot (WB) analysis: Exosomal markers (CD63, TSG101, CD9, CD81) were detected using WB. Exosome/cell lysates were prepared with a BCA Protein Assay Kit (Life Technologies) for quantification. Proteins were separated by 10% SDS-PAGE, transferred to 0.22μm PVDF membranes (Millipore), blocked with 5% skim milk, probed with primary/secondary antibodies, and visualized using an Immobilon ECL kit (Millipore).The sources of primary antibodies and dilutions used were as follows: rabbit anti-CD63 (Abcam, Cat No. ab134045, 1:1000 dilution), rabbit anti-TSG101 (Abcam, Cat No. ab125011, 1:1000 dilution), rabbit anti-CD9 (Abcam, Cat No. ab92726, 1:2000 dilution), rabbit anti- CD81 (Abcam, Cat No. ab109201, 1:1000 dilution), and rabbit anti-β-actin (Cell Signaling Technology, Cat No. #4970, 1:1000 dilution), which was used as an internal control. 2.4 RNA preparation and RNase R treatment Total RNA was extracted from cultured cells and exosomes using TRIzol reagent (Invitrogen) according to the manufacturer’s instruction. Total RNA from paraffin-embedded EBVaGC tissues was purified using the Rneasy FFPE Kit (Qiagen) according to the manufacturer’s instruction. For RNA quantification and quality control: RNA integrity was evaluated using a NanoPhotometer N60 (Implen, Munich, Germany) via OD260/280 and OD260/230 ratios alongside agarose gel electrophoresis. For RNase R treatment: Purified RNA was incubated with 2 U/μg RNase R (Epicentre) at 37°C for 20 minutes. 2.5 cDNA synthesis, reverse transcription-polymerase chain reaction (RT–PCR) and quantitative real-time polymerase chain reaction (qRT-PCR) We conducted cDNA synthesis following the manufacturers' protocols. For mRNAs, we used the Evo M - MLV RT Kit with gDNA Clean from AG (Changsha, China), and for miRNAs, the Mir - X miRNA First - Strand Synthesis Kit from Takara (Dalian, China). For RT - PCR, we employed the SYBR Green Premix Pro Taq HS qPCR Kit from AG to amplify the cDNAs. The RT - PCR products were then separated by electrophoresis on a 1.8% agarose gel stained with 0.4 mg/ml ethidium bromide and visualized under UV light. For qRT - PCR, we utilized the SYBR Premix Ex TaqTM II Kit from Takara on an ABI 7500 FAST Real - Time PCR System (Applied Biosystems, USA). We selected GAPDH and U6 as internal controls for mRNAs and miRNAs respectively. Each sample was run in triplicate, and the data were analyzed using the 2−ΔΔCq relative quantification method. The primers used in this study are detailed in Table 1. Table 1. Primer sequences used in this study Primers Sequence ebv-circLMP2A Forward: GCGTCACTGATTTTGGGC Reverse: TGGGTCCTCAATCCTCCA LMP2A Forward: CTACTCTCCACGGGATGACTC Reverse: AGGTAGGGCGCAACAATTAC ebv-circBHLF1 Forward: GCCCATTCGAACCCTACC Reverse: TGGTCCTGGAGCTCATCC ebv-circRPMS1 Forward: GGGACGCTAGTGCTGCAT Reverse: GTGTGTCCGGTAAACGCC hsa-circPRKD3 Forward: CTGCAAATTGGCCTCACA Reverse: TGAATGGGTCCATCGAGAA hsa-circMEMO1 Forward: GACAGGAATGTTTGAACGCA Reverse: TAAGCATGGGCAGCACAA hsa-circRNF13 Forward: TGGGCATCTGTCTCATCTTG Reverse: TGACAGCATGAGCATCCC RNF13 Forward: AAGTGTGTAGATCCCTGGCTAA Reverse: GTCCGAGTCACCTTGGGAAG hsa-circWDR43 Forward: CTCATCTTGACAGCCTCTGCT Reverse: CCTGTCTGGGCATTCCAC hsa-circSFMBT2 Forward: CGACCAGTTGGTTGGTGTC Reverse: ACCTTCCAGGAGGTTGGC hsa-circHIPK3 Forward: TAGACTTTGGGTCGGCCA Reverse: CCAAGACTTGTGAGGCCA hsa-circDYM Forward: TTGCTGTGCTGTTTGATGC Reverse: GCATTGTGTGTCTGCCAAA GAPDH Forward: AGCCACATCGCTCAGACA Reverse: GCCCAATACGACCAAATCC hsa-miR-4779 Forward: Mir-X miRNA First-Strand Synthesis Kit provided Reverse: AGGAGGGAATAGTAAAAGCAG hsa-miR-5683 Forward: TACAGATGCAGATTCTCTGACTTC Universal: GCGAGCACAGAATTAATACG AC U6 Forward: CTCGCTTCGGCAGCACA Reverse: AACGCTT CACGAATTTGCGT 2.6 CircRNA sequencing and analysis Transcriptome sequencing and bioinformatics analysis were conducted by Cloud-Seq Biotech (Shanghai, China). Total RNA underwent rRNA depletion using Ribo-Zero kits (Illumina), followed by library construction with the TruSeq Stranded Total RNA Kit (Illumina). Library quality was validated via Agilent BioAnalyzer 2100, with 10 pM libraries denatured, cluster-amplified on Illumina flow cells, and sequenced (150 cycles paired-end) on HiSeq instruments. CircRNA annotation utilized GRCh38/hg38 (UCSC) and EBV genome (NC_007605.1, NCBI), with back-spliced junction reads quantifying circRNA abundance. Host genes were assigned based on RefSeq annotations of mapped genomic regions. Differential expression analysis: Student’s t-test identified exosomal circRNAs with ≥2-fold changes and p<0.05 between SNU719 and SNU4th cells. GO and KEGG pathway enrichment analyses were performed on host genes of these circRNAs. The top 10 significantly enriched pathways for upregulated/downregulated circRNAs were selected to construct pathway networks. miRNA binding sites were predicted using Arraystar software (TargetScan/miRanda algorithms). 2.7 RNA in situ hybridization (ISH) EBV presence in tumor cells was confirmed via ISH with an EBER-1 probe (PanPath, Amsterdam, the Netherlands), as reported by Chen et al[22]. 2.8 Immunohistochemistry (IHC) Paraffin-embedded xenograft tissues and 69 EBVaGC samples were sectioned into 4-μm-thick slices. Immunohistochemistry was performed using previously described standardized protocols[23]. The sources of antibodies and dilutions used were as follows: Oct4 (Abcam, Cat No. ab181557, 1:1000 dilution), Klf4 (Abcam, Cat No. ab215036, 1:2000 dilution), Sox2 (Abcam, Cat No. ab92494, 1:100 dilution), Mouse anti-CD34 (Cell Signaling Technology, Cat No. #3528, 1:2000 dilution) and Mouse anti-Ki67 (Cell Signaling Technology, Cat No. #9449, 1:2000 dilution). Immunohistochemical staining score was used to evaluate Ki67 IHC staining result by two experienced pathologists. The staining score criteria were performed as follows: the staining intensity was scored as 0 (negative), 1(weak), 2 (moderate), or 3 (strong); the percentage of positive tumor cells was categorized as 0 (80%) positive cells. The final IHC scores of staining ranged from 0 to 12 by multiplying the scores of the intensity of staining and positive staining percentage. Microvessel density (MVD) was assessed via CD34 immunohistochemistry following the method described by Du et al [18]. CD34+ endothelial cell or distinct endothelial cluster separated from adjacent vessels, tumor cells, and stroma was counted as one microvessel. 2.9 Exosomes internalization assay Exosomes internalization assay was conducted to confirm the uptake of labeled exosomes by YCCEL1 cells. First, exosomes from SNU719 or SNU4th cells were labeled with a PKH67 green, fluorescent labeling kit (Sigma-Aldrich, MINI67) according to the manufacturer's protocol. Next, YCCEL1 cells were plated at a density of 3×10⁴ cells/well in 24-well plates and co-incubated with various concentrations of labeled exosomes at 37 °C for 6-24 hours. Finally, the cells were examined under a fluorescence microscope (Excitation: 494 nm; Emission: 521 nm (green); Filter setting: Typical GFP filter set). 2.10 Cell proliferation, migration, invasion assays, and flow cytometry To assess cell proliferation, we seeded cells in 96-well plates at a density of 5×10³ cells per well. We then used the Cell Counting Kit-8 (CCK-8) from Dojindo (Japan) to measure cell viability on days 1, 2, 3, 4, and 5 as per the manufacturer's protocol. An automatic microplate reader (TECAN, Austria) was used to measure the absorbance at 450 nm. A wound healing assay was carried out to evaluate the migratory ability of cells. Cells were seeded in 24-well plates at a density of 5×10⁴ cells per well in 1640 medium containing 10% FBS and incubated for 24h. After that, a wound was created using a 10μl pipette tip. The cells were then washed twice with PBS at 0h and 6h. The closure of the wound was observed under a microscope. To conduct cell migration and invasion assays, we resuspended cells in 200 μL of serum-free RPMI-1640 medium at a density of 5×10⁵ cells/ml. Then, we seeded the cell suspension into the upper chambers of transwell inserts (8 μm pore size, Costar). For the migration assay, the inserts were uncoated, while for the invasion assay, they were pre-coated with Matrigel (BD Biosciences, USA). We added RPMI-1640 medium supplemented with 20% FBS to the bottom chamber as a chemoattractant. The cells were then incubated at 37°C in a 5% CO₂ atmosphere for 24h. After incubation, we removed the non-migrated/invaded cells in the upper chambers using cotton swabs. The cells on the lower surface of the inserts were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet. Finally, we randomly selected five microscopic fields of view for imaging. To analyze apoptosis, we stained the cells with an Annexin V, 633 apoptosis kit from Dojindo (Japan) following the manufacturer's instructions. Then, we used flow cytometry (BD influx, USA) to analyze the stained cells. 2.11 Statistical analysis All experiments were performed in triplicate. Data were analyzed using IBM SPSS 19.0 and GraphPad Prism 6.0, presented as mean ± SD from ≥3 independent experiments. Two-tailed Student’s t-test evaluated group differences (p<0.05 significant). Pearson’s correlation analyzed variable relationships. Median miR-5683 expression defined high/low groups. Overall survival (OS) was calculated from surgery to death/last follow-up. Survival curves were generated via Kaplan–Meier method with log-rank test for significance. 3. Results 3.1 Characterization of exosomes derived from EBVaGC CSCs We previously developed a xenograft model under chemotherapeutic selection to isolate and enrich EBVaGC CSCs[6]. With this model, we obtained SNU4th cells with the properties of CSCs (Fig. 1A). The existence of EBV in successive xenografts was detected by EBER-1 ISH, and compared with the first xenografts, and the expression of stemness makers Oct4, Klf4, Sox2 were obviously increased in the fourth xenografts (Fig. 1B). Next, exosomes in cell culture supernatants from parental SNU719 cells and SNU4th cells were purified by differential ultracentrifugation. As shown in Fig. 1C, the structural features of exosomes were identified by TEM, showing a saucer-like shape morphology and a range of 50-100nm in diameter. The amount and size distribution of exosomes were analyzed by NTA, which shows the higher concentration of SNU4th cells derived exosomes than SNU719 cells derived exosomes（6.86×10 5 particles/mL vs 5.91×10 5 particles/mL）and the diameter of both SNU719 and SNU4th cells derived exosomes were approximately 100-150nm (Fig. 1D). We further confirmed the presence of the exosome associated makers CD63, TSG101, CD9 and CD81 both in the whole cell lysate and isolated exosomes (Fig. 1E). 3.2 Profiling of ebv-circRNAs and human circRNAs in EBVaGC CSCs derived exosomes As an initial exploration into whether ebv-circRNAs exist in exosomes, we separately profiled ebv-circRNAs and human circRNAs by using RNA sequencing analysis of ribosomal RNA-depleted total RNA from SNU719 and SNU4th cells derived exosomes. The ebv-circRNAs sequencing reads of each sample were shown in Fig. 2A. There were only six ebv-circRNAs (at least one backspliced read in each sample) exist in exosomes. Despite the low abundance of these ebv-circRNAs, three of these ebv-circRNAs, including ebv-circLMP2A, ebv-circBHLF1 and ebv-circRPMS1(149580_150348+) were significantly up-regulated in SNU4th cells derived exosomes than SNU719 cells derived exosomes. Besides, a total of 8909 distinct human circRNAs were found in exosomes (Fig. 2B, supplementary Table 1). Of these, approximately 80.10% of the human circRNAs originated from exonic regions, and others derived from intergenic regions, introns, antisense, sense overlapping (Fig. 2C). Analysis of the number of human circRNAs isotypes from their host gene showed that one gene could generate multiple human circRNAs isotypes (Fig. 2D). The cluster heatmap for human circRNAs differentially expressed in SNU719 and SNU4th cells derived exosomes revealed distinct expression pattern in these cells with different biological properties (Fig. 2E). As shown in supplementary Table 2 and 3, we identified 261 significantly differentially expressed exosomal circRNAs, of which 167 were up-regulated （supplementary Table 2）and 94 were down-regulated （supplementary Table 3）in SNU4th cells derived exosomes compared with SNU719 cells derived exosomes. Scatter plot (Fig. 2F) illustrates the variation of exosomal circRNAs expression according to the criteria of exhibiting fold change > 2.0 and p values ≤ 0.05. Circos plots (Fig. 2G) analyzed these differentially expressed exosomal circRNAs and their host gene’s location, suggesting that the expression of circRNAs were not correlated with their corresponding parent genes. 3.3 Bioinformatics analysis of differentially expressed exosomal circRNAs derived host genes GO analysis was used to annotate and speculate the function of these differentially expressed exosomal circRNAs derived host genes (Fig. 3A and B). GO analysis of biological process (BP) revealed that these differentially expressed exosomal circRNAs were mainly involved in regulation of protein modification process, mitotic cell cycle, biological regulation and other biological processes. GO analysis of cellular components (CC) showed that these differentially expressed exosomal circRNAs were significantly associated with regulation of intracellular part, endosome, cell junction, and other cellular components. GO analysis of molecular function (MF) indicated that these differentially expressed exosomal circRNAs took part in protein binding, vascular endothelial growth factor, GTPase inhibitor activity and other molecular functions. KEGG analysis (Fig. 3C and D) was performed to predict the top ten significant enrichment pathways which related to the variation of exosomal circRNAs from EBVaGC CSCs. The top three related pathways including viral carcinogenesis, ubiquitin mediated proteolysis and angiogenesis, suggesting that EBVaGC CSCs derived exosomes may play a key role in tumor progression. 3.4 Detection of circRNAs expression in EBVaGC CSCs derived exosomes To test the reliability of the sequencing data, we selected top 10 differentially expressed circRNAs including three ebv-circRNAs (ebv-circLMP2A, ebv-circBHLF1 and ebv-circRPMS1) and seven human circRNAs (hsa-circDYM, hsa-circMEMO1, hsa-circRNF13, hsa-circSFMBT2, hsa-circPRKD3, hsa-circWDR43 and hsa-circHIPK3) for validation in cells or exosomes of SNU719 and SNU4th cells by qRT-PCR. As shown in Fig. 4A-J, the expressions of ebv-circLMP2A, ebv-circRPMS1, hsa-circDYM, hsa-circMEMO1, hsa-circRNF13, hsa-circSFMBT2, hsa-circWDR43 and hsa-circHIPK3 were significantly up-regulated in SNU4th cells compared with SNU719 cells. What’s more, among these up-regulated circRNAs, the abundance of ebv-circLMP2A and hsa-circRNF13 were significantly higher in exosomes than in cells, indicating that ebv-circLMP2A and hsa-circRNF13 were enriched in SNU4th cells derived exosomes. Next, the presence of ebv-circRNAs and hsa-circRNF13 were further validated by RT–PCR in cells and exosomes of SNU4th cells treated with or without RNase R digestion. As shown in Fig. 4K, the fragments of the linear form of LMP2A and RNF13 were digested with RNase R, whereas ebv-circRNAs and hsa-circRNF13 were resistant to RNase R digestion due to their circular form. 3.5 The expression of ebv- circLMP2A and hsa- circRNF13 in EBVaGC tissues and the clinical relevance between hsa-miR-5683 and ebv- circLMP2A or hsa- circRNF13 To determine whether tumor derived exosomal circRNAs enter the circulation and are measurable for cancer detection, we harvested serum from the previously established four successive generation xenografts, and circulating exosomal ebv-circLMP2A and hsa-circRNF13 were quantified by qRT-PCR. As shown in Fig. 5A and B, abundance of EBVaGC derived exosomal ebv-circLMP2A and hsa-circRNF13 in serum were able to be dectected. More importantly, the expression of exosomal ebv-circLMP2A and hsa-circRNF13 in serum were gradually up-regulated among the successive four generation xenografts, indicating that the abundance of exosomal ebv-circLMP2A and hsa-circRNF13 in serum were correlated with tumor stemness. Furthermore, we also detected the expression of ebv-circLMP2A and hsa-circRNF13 in 69 paraffin-embedded EBVaGC tissues by qRT-PCR. As shown in Fig. 5C and D, EBVaGC patients with metastasis had higher expression levels of ebv-circLMP2A and hsa-circRNF13 than patients without metastasis, suggesting that ebv-circLMP2A and hsa-circRNF13 play an important role in promoting the malignant progression of EBVaGC. As we know, circRNAs-miRNAs interaction has been extensively studied and demonstrated to contribute to cancer progression by participating in the regulation of target gene expression. Therefore, it is necessary to identify the interaction between circRNAs and miRNAs. miRNA binding sites (including EBV derived miRNAs and human derived miRNAs) on differentially expressed exosomal ebv-circRNAs based on TargetScan and miRanda are separately listed in supplementary Table 3 and 4, and miRNA binding sites (including EBV derived miRNAs and human derived miRNAs) on differentially expressed human circRNAs are separately listed in supplementary Table 5 and 6. Because ebv-circLMP2A and hsa-circRNF13 were highly enriched in SNU4th cells derived exosomes, they were specifically selected for further analysis of the potential target miRNAs that may be related to EBVaGC progression. The top five potential target human derived miRNAs and top three potential target EBV derived miRNAs for ebv-circLMP2A and hsa-circRNF13 were separately presented in Fig. 5E and F. Interestingly, previous literature reports that hsa-miR-4779, which has a significant anti - cancer effect[24], is the downstream target of ebv-circLMP2A. And hsa-miR-5683 is the downstream target of hsa-circRNF13. Furthermore, we detected the expression of hsa-miR-4779 and hsa-miR-5683 in 69 paraffin-embedded EBVaGC tissues by qRT-PCR and analyzed the clinical correlation between hsa-miR-4779 and ebv-circLMP2A or hsa-miR-5683 and hsa-circRNF13. There is no significant correlation between the expression level of hsa-miR-4779 and ebv-circLMP2A (Fig. 5G), but the expression level of hsa-miR-5683 was negatively correlated with hsa-circRNF13 in EBVaGC tissues (Fig. 5H). Furthermore, we studied the expression of CD34 and Ki67 in 69 paraffin-embedded EBVaGC tissues by IHC. The endothelial cells of blood vessels within the tumor were labeled by CD34 for calculating MVD. We observed that lower hsa-miR-5683 expression was positively correlated with MVD and Ki67 expression in EBVaGC samples (Fig. 5I). And EBVaGC patients with lower hsa-miR-5683 expression had a worse 5-year OS than those with higher hsa-miR-5683 expression (95.3% vs 43.8%, P < 0.001, Fig. 5J). Besides, the pathway relation network of the top 10 significant pathways of differentially expressed exosomal circRNAs showed that the ultimate regulatory effect of EBVaGC CSCs derived exosomes was involved in viral carcinogenesis (Fig. 5K). 3.6 EBVaGC CSCs derived exosomes promoted the invasive growth of EBVaGC cells To further understand the role of EBVaGC CSCs derived exosomes in EBVaGC, exosomes from parental SNU719 cells and SNU4th cells were separately isolated, and EBVaGC cells YCCEL1 were pretreated with above different cells derived exosomes for 24h to investigate the effects of exosomes on the biological behaviors of YCCEL1 cells. Firstly, we used PKH67 to mark the exosomes and observed the existence of PKH67-labeled exosomes in YCCEL1 cells. As shown in Fig. 6A, after incubation with different concentrations of SNU4th cells derived exosomes, the abundance of exosomes absorbed by YCCEL1 cells was significantly increased in a dose and time dependent manner. Moreover, we evaluated the expression of ebv-circLMP2A and hsa-circRNF13 by qRT-PCR after incubation with different concentrations of SNU4th cells derived exosomes in YCCEL1 cells for 24h. As shown in Fig. 6B, the expression of hsa-circRNF13 can be detected in a dose-dependent manner in YCCEL1 cells, while the expression of ebv-circLMP2A was poorly low. Besides, compared with 10% FBS or SNU719 cells derived exosomes treatment, the proliferative ability of YCCEL1 cells was enhanced after SNU4th cells derived exosomes treatment (Fig. 6C). And the migratory and invasive capability of YCCEL1 cells were also promoted after incubation with SNU4th cells derived exosomes (Fig. 6D and E). Meanwhile, SNU4th cells derived exosomes also decreased the rate of apoptosis in YCCEL1 cells (Fig. 6F). Altogether, our results indicated that exosomes from EBVaGC CSCs could be transferred into EBVaGC cells and promoted the invasive growth of EBVaGC cells. 4. Discussion To date, EBV has been studied for decades and was closely associated with kinds of tumors in terms of both epidemiology and molecular biology[ 1 , 25 ]. Products including proteins and nucleic acids encoded by EBV play critical roles in the carcinogenesis of EBV. Emerging evidence supports the notion that exosomes serve as perfect carriers for these viral molecules, protecting them from being degraded by host enzymes and transporting them into surrounding cells to continuously influence the biological behavior of recipient cells[ 26 ]. Ebv-circRNAs is a newly discovered member of the EBV transcriptome and has been found to contribute to the oncogenic phenotype in EBV-associated malignancies[ 6 , 18 , 19 ]. Whether ebv-circRNAs exist in exosomes and their functions are still unknown. Here, we performed a comprehensive expression profile of circRNAs including both ebv-circRNAs and human circRNAs in EBVaGC CSCs derived exosomes and found that two potential cirRNAs, ebv-circLMP2A and hsa-circRNF13, enriched in EBVaGC CSCs derived exosomes, are positively associated with EBVaGC patients with metastasis, which supports the contention of potential functional relevance of tumor phenotype. Moreover, EBVaGC CSCs derived exosomes could be uptaken into EBVaGC cells and promoted the invasive growth of EBVaGC cells, further suggests the potential unique role of CSCs derived exosomes in tumor progression. To the best of our knowledge, this is the first study aiming at identifying circRNAs expression profile in EBVaGC CSCs derived exosomes and providing the first evidence that specific circRNAs are selectively loaded into CSCs derived exosomes which may play an important role in the progression of EBVaGC. Emerging evidence has suggested that exosomes released by cancer cells act as natural vehicles to transfer specific protein, mRNA or miRNA to recipient cells, which further reprograms the surrounding cells and remodels the TME to be suitable for survival[ 27 ]. The role of exosomal circRNAs has gained increasing attention. Although recent studies have manifested that EBV encoded proein LMP1, LMP2A and BART, BHRF1 miRNAs are selectively enriched in exosomes secreted by EBV-infected cells that act on various target cells with various biological functions, whether circRNAs are packaged into exosomes derived from EBV-infected cells and their functions have not been explored. Here, we used the method previously metioned to acquire SNU-4th which possessed clear stemness characteristics and isolated exosomes from parental SNU719 and SNU4th cell culture supernatants. We focused our attention on the alterations of both ebv-circRNAs and human circRNAs between SNU719 and SNU4th cell derived exosomes by high-throughput whole transcriptome sequencing. In this study, we found only six unique ebv-circRNAs exist in exosomes, three of which including, ebv-circLMP2A, ebv-circBHLF1 and ebv-circRPMS1(149580_150348+) were significantly up-regulated in SNU4th cells derived exosomes. Besides, a total of 8909 distinct human circRNAs were found in exosomes, 261 of these human circRNAs were significantly differentially expressed including 167 were up-regulated and 94 were down-regulated in SNU4th cells derived exosomes. As we known, CSCs serve as the “seed” and are the cause and maintainers of tumors, therefore, the change of circRNAs in exosomes derived from EBVaGC CSCs may be involved in the malignant progression of EBVaGC. In addition, we selected the top 10 up-regulated circRNAs including three ebv-circRNAs and seven human circRNAs for validation by qRT-PCR. The experimental results showed great consistency between the qRT-PCR results and sequencing data, which is helpful for further functional analysis of the differentially expressed exosomal circRNAs. What’s more, among the top 10 up-regulated circRNAs, ebv-circLMP2A and hsa-circRNF13 were significantly enriched in EBVaGC CSCs derived exosomes, indicating exosomal ebv-circLMP2A and hsa-circRNF13 may play important roles in the initiation and progression of EBVaGC. It will be necessary to explore the function of ebv-circLMP2A and hsa-circRNF13, which may help to add potential therapeutic targets for EBV-associated malignancies. With the deep research of exosomal circRNAs, increasing experimental evidence suggests that tumor derived exosomal circRNAs can enter the circulation and be measurable for cancer detection. That exosomal circRNAs may distinguish patients with cancer from healthy manifests its important translational potential as a circulating biomarker for cancer diagnosis. Here, we found EBVaGC derived exosomal ebv-circLMP2A and hsa-circRNF13 in serum of xenografted mice were able to be detected, and the abundance of exosomal ebv-circLMP2A and hsa-circRNF13 in serum were gradually up-regulated among the four successive generation xenografts, indicating that the abundance of exosomal ebv-circLMP2A and hsa-circRNF13 in serum correlated with tumor stemness. In the following detection of ebv-circLMP2A and hsa-circRNF13 within the tissue samples, we found that EBVaGC patients with metastasis had higher expression levels of ebv-circLMP2A and hsa-circRNF13 than patients without metastasis, further suggesting that exosomal ebv-circLMP2A and exosomal hsa-circRNF13 could be potential liquid biopsy markers for EBVaGC. Given that circRNAs could act as a miRNAs sponge and play an important role in regulating the biological behaviors of cancer cells by competitively binding to target miRNAs, the predicted circRNAs-miRNAs network can help to understand the potential molecular mechanisms of ebv-circLMP2A and hsa-circRNF13 in EBVaGC. In this study, we found that hsa-miR-4779 is the downstream target of ebv-circLMP2A and hsa-miR-5683 is the downstream target of hsa-circRNF13. However, only the expression level of hsa-miR-5683 was negatively correlated with hsa-circRNF13 in EBVaGC tissues. Further analysis reveals that lower hsa-miR-5683 expression was positively correlated with MVD and Ki67 expression in EBVaGC samples. In addition, we also observed that EBVaGC patients with lower hsa-miR-5683 expression had a worse 5-year OS than those with higher hsa-miR-5683 expression. These clinical data suggest that hsa-miR-5683 may be a tumor suppressor, which is consistent with what previous study has found that miR-5683 suppresses glycolysis and proliferation through targeting PDK4 in gastric cancer[ 28 ]. Notably, the pathway relation network of the top 10 significant pathways of differentially expressed exosomal circRNAs showed that the ultimate regulatory effect of EBVaGC CSCs derived exosomes was involved in viral carcinogenesis. Here, we found that EBVaGC cells YCCEL1 could take up EBVaGC CSCs derived exosomes and acquired invasive growth ability. These results at the cellular level preliminarily confirm our hypothesis that EBVaGC CSCs derived exosomes play an important role in promoting the malignant progression of EBVaGC, suggesting that inhibiting the release of EBVaGC derived exosomes may be serve as a novel therapeutic strategy. Although the specific molecular mechanisms remain unknown, the role of EBVaGC CSCs derived exosomes in EBVaGC deserves further investigation. In summary, this study uncovers a new spectrum of exosomal circRNAs expression pattern in EBVaGC CSCs. The bioinformatics analysis and circRNAs-miRNAs network prediction provide a deep understanding of these differentially expressed exosomal circRNAs which may be related to the malignant progression of EBVaGC. Experiments at the cellular level preliminarily support the hypothesis that EBVaGC CSCs derived exosomes could be transferred into EBVaGC cells to promote the invasive growth of EBVaGC cells. To date, therapies for EBV-associated malignancies have displayed limited effectiveness, our study provides novel therapeutic targets for EBVaGC that focus on EBV derived exosomal circRNAs. Declarations Author Contributions : Li-ping Gong: designation of the study, experiment performer and writing of the manuscript; Yi-ting Shao: data analysis; Yu Du: animal experiment performer; Li-ping Sun: collection of clinical specimens; Lu-ying Tang: IHC Scoring; Jian-ning Chen: interpretation of data and revise of the manuscript. Acknowledgements We sincerely thank Dr. Qian Tao for providing us with YCCEL1 cells. Conflict of interest statement: The authors declare no potential conflicts of interest. Data availability statement: Data is provided within the manuscript or supplementary information files. Consent for publication: All participants gave informed consent to publish the paper. Ethics approval and consent to participate: All animal studies were performed in accordance with the institutional ethics guidelines for the animal experiments approved by the Experimental Animal Ethics Committee of the Third Affiliated Hospital, Sun Yat-sen University. All patient samples were obtained with appropriate informed consent from the patients and approved by the Institute Research Ethics Committee of the Third Affiliated Hospitals of Sun Yat-Sen University (Ethic No. RG2023-111-01). Patient consent for publication: Not applicable. Funding: This work was supported by the National Natural Science Foundation of China (82203679), Medical Research Foundation of Guangdong Province (A2022380), China Postdoctoral Science Foundation (2022M713568). References Young, L.S., Yap, L.F., and Murray, P.G. (2016). Epstein-Barr virus: more than 50 years old and still providing surprises. Nature reviews. Cancer 16 , 789-802. Farrell, P.J. (2019). Epstein-Barr Virus and Cancer. 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(2022). ebv-circRPMS1 promotes the progression of EBV-associated gastric carcinoma via Sam68-dependent activation of METTL3. Cancer letters 535 , 215646. Liu, Q., Shuai, M., and Xia, Y. (2019). Knockdown of EBV-encoded circRNA circRPMS1 suppresses nasopharyngeal carcinoma cell proliferation and metastasis through sponging multiple miRNAs. Cancer management and research 11 , 8023-8031. Zhu, L., Sun, H.T., Wang, S., Huang, S.L., Zheng, Y., Wang, C.Q., Hu, B.Y., Qin, W., Zou, T.T., Fu, Y., et al. (2020). Isolation and characterization of exosomes for cancer research. Journal of hematology & oncology 13 , 152. Chen, J.N., Ding, Y.G., Feng, Z.Y., Li, H.G., He, D., Du, H., Wu, B., and Shao, C.K. (2010). Association of distinctive Epstein-Barr virus variants with gastric carcinoma in Guangzhou, southern China. Journal of medical virology 82 , 658-667. Gong, L.P., Chen, J.N., Xiao, L., He, Q., Feng, Z.Y., Zhang, Z.G., Liu, J.P., Wei, H.B., and Shao, C.K. (2019). The implication of tumor-infiltrating lymphocytes in Epstein-Barr virus-associated gastric carcinoma. Human pathology 85 , 82-91. Koo, K.H., and Kwon, H. (2018). MicroRNA miR-4779 suppresses tumor growth by inducing apoptosis and cell cycle arrest through direct targeting of PAK2 and CCND3. Cell Death Dis 9 , 77. Fukayama, M., Abe, H., Kunita, A., Shinozaki-Ushiku, A., Matsusaka, K., Ushiku, T., and Kaneda, A. (2020). Thirty years of Epstein-Barr virus-associated gastric carcinoma. Virchows Archiv : an international journal of pathology 476 , 353-365. Chen, W., Xie, Y., Wang, T., and Wang, L. (2022). New insights into Epstein‑Barr virus‑associated tumors: Exosomes (Review). Oncology reports 47 . Wortzel, I., Dror, S., Kenific, C.M., and Lyden, D. (2019). Exosome-Mediated Metastasis: Communication from a Distance. Developmental cell 49 , 347-360. Miao, Y., Li, Q., Sun, G., Wang, L., Zhang, D., Xu, H., and Xu, Z. (2020). MiR-5683 suppresses glycolysis and proliferation through targeting pyruvate dehydrogenase kinase 4 in gastric cancer. Cancer medicine 9 , 7231-7243. Additional Declarations No competing interests reported. Supplementary Files Table.S1.xlsx Table. S1. Human CircRNA Expression Profiling. Table.S2.xlsx Table. S2. Human-Differentially Expressed circRNAs. Table.S3.xlsx Table. S3. EBV-circRNA--EBV-miRNA Binding Sites prediction. Table.S4.xlsx Table. S4. EBV-circRNA--Hsa-miRNA Binding Sites prediction. Table.S5.xlsx Table. S5. Hsa-circRNA-- EBV-miRNA Binding Sites prediction. Table.S6.xlsx Table. S6. Hsa-circRNA -- Hsa-miRNA Binding Sites predicti Cite Share Download PDF Status: Published Journal Publication published 08 Jan, 2026 Read the published version in Journal of Cancer Research and Clinical Oncology → Version 1 posted Editorial decision: Revision requested 17 Sep, 2025 Reviews received at journal 16 Sep, 2025 Reviewers agreed at journal 12 Aug, 2025 Reviewers agreed at journal 29 Jun, 2025 Reviewers invited by journal 10 Jun, 2025 Editor assigned by journal 20 May, 2025 Submission checks completed at journal 20 May, 2025 First submitted to journal 20 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6704451","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":468978276,"identity":"7944f51a-6a70-4fa2-88d7-05ed71eac95a","order_by":0,"name":"Li-ping Gong","email":"","orcid":"","institution":"Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Li-ping","middleName":"","lastName":"Gong","suffix":""},{"id":468978277,"identity":"c0c8bb8c-9ca0-4730-8306-3c85ee1e0e8b","order_by":1,"name":"Yi-ting Shao","email":"","orcid":"","institution":"Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Yi-ting","middleName":"","lastName":"Shao","suffix":""},{"id":468978278,"identity":"aec21e58-a1ae-4b82-bf31-4c5e764f087e","order_by":2,"name":"Yu Du","email":"","orcid":"","institution":"Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Du","suffix":""},{"id":468978279,"identity":"7686ebd1-6022-4e17-99b8-66e3b346bbf9","order_by":3,"name":"Li-ping Sun","email":"","orcid":"","institution":"Sixth Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Li-ping","middleName":"","lastName":"Sun","suffix":""},{"id":468978280,"identity":"f25527f1-6988-466c-9f88-ab00cd67de7a","order_by":4,"name":"Lu-ying Tang","email":"","orcid":"","institution":"Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Lu-ying","middleName":"","lastName":"Tang","suffix":""},{"id":468978281,"identity":"e4ffe1d1-e854-43fc-815a-76c3b62b99e9","order_by":5,"name":"Jian-ning Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYDACCYYEIGSQY2BgbDyAECRCizFQSwPRWsAgsQFIEKeFf3bDswcPd9Smr20/DLTlz2F7gwPMB2/zMNjl4bTkzoF0g8Qzx3O3nUlsOMDYdjhxwwG2ZGsehuRiXFoMJBLSJBLbjuVuOwDS0nA4weAAj5k0D8MBsFPxaUk3O/8Q5jD+b8RoqUkwuwG0hYHtMOOGAzxseLVI3ABrOWC47QbQlsS29MSZh9mMLecYJOPUwj8jJ03yZ1udvNn59IcPPvyxtuc73vzwxpsKO5xaGBh4EoDEYQg7gaGZgYEZ7GCc6oGA/QCQqIPx6nArHAWjYBSMghELAF9YYVrG7VROAAAAAElFTkSuQmCC","orcid":"","institution":"Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":true,"prefix":"","firstName":"Jian-ning","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-05-20 06:38:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6704451/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6704451/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00432-025-06414-4","type":"published","date":"2026-01-08T15:58:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84450596,"identity":"b6f3d3cb-aa0c-42fd-9238-21cd3c61897a","added_by":"auto","created_at":"2025-06-12 06:45:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":747552,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDetection of exosomes from EBVaGC CSCs. \u003c/strong\u003e(A) Schematic illustration of the EBVaGC CSCs acquisition process. (B) Representative images presented HE staining, EBER-1 ISH staining, and IHC staining (Oct4, Klf4, Sox2, and Ki67) in the first and fourth generation xenografts. Scale bar = 50μm. (C) Representative TEM images of isolated exsomes from SNU719 and SNU4th cells which showing a saucer-like shape by lipid bilayer; Scale bar = 100 nm. (D) NTA analysis of the concentration and size distribution of exosomes derived from SNU719 and SNU4th cells. The red line shows the number of exosomes with a diameter of 150nm. (E) Western blot analysis of exosomal makers CD63, TSG101, CD9, CD81, and β-actin expression in both the whole cell lysate and isolated exosomes.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/c4818c478b2084ac03adc564.png"},{"id":84451125,"identity":"17e67f32-7d12-4b81-9042-43592f158e84","added_by":"auto","created_at":"2025-06-12 06:53:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":380904,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential expression of ebv-circRNAs and human circRNAs between SNU719 and SNU4th cell derived exosomes.\u003c/strong\u003e (A) The backspliced reads of ebv-circRNAs identified in SNU719 and SNU4th cells derived exosomes. Exo1 = Exosomal sample1, Exo2 = Exosomal sample 2, Exo3 = Exosomal sample3, n = 3 biological replicates. (B) Quantification of human circRNAs and backspliced reads in SNU719/SNU4th-derived exosomes. (C) Genomic origin of human circRNAs. (D) Circular RNA (circRNA) isoform multiplicity describes the phenomenon where a single gene generates multiple circRNA isoforms. (E-G) Clustered heatmap (E), Scatter plot (F) and Circos plots (G) analysis of the differentially expressed human circRNAs between SNU719 and SNU4th cells derived exosomes. Red colour represents up-regulated circRNAs, and green colour represents down-regulated circRNAs. The top line 1 and below the bottom line 3 indicated more than a 2.0-fold change of human circRNAs. n = 3 biological replicates.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/205a81c57ae75de772d03ccf.png"},{"id":84451147,"identity":"983eee75-a59e-439f-98c8-a20873e1b889","added_by":"auto","created_at":"2025-06-12 06:53:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":256348,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGO and KEGG pathway analysis of differentially expressed exosomal circRNAs with top 10 enrichment score.\u003c/strong\u003e (A-B) GO analysis of up-regulated circRNAs (A) and down-regulated circRNAs (B). The horizontal axis was the enrichment score for the GO terms, and the vertical axis is the GO terms. The enrichment score was calculated as -log10 (\u003cem\u003ep\u003c/em\u003e-value). (C-D) KEGG pathway analysis of up-regulated circRNAs (C) and down-regulated circRNAs (D). Enrichment scores were calculated as -log10(\u003cem\u003ep\u003c/em\u003e-values). Selection counts denote the number of differentially expressed circRNAs directly associated with each pathway term.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/63c64ca1b05bebb3c05418be.png"},{"id":84450632,"identity":"258877cb-8769-4447-b1da-77c4d58a1286","added_by":"auto","created_at":"2025-06-12 06:45:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":264765,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eValidation of differentially expressed circRNAs in SNU719 and SNU4th cells derived exosomes. \u003c/strong\u003e(A-C) The relative expressions of selected ebv-circRNAs in cells or exosomes derived from SNU719 and SNU4th cells were measured by qRT-PCR. (D-J) The relative expressions of selected human circRNAs in cells or exosomes derived from SNU719 and SNU4th cells were measured by qRT-PCR. (K) The existence of ebv-circLMP2A and hsa-circRNF13 were validated by RT–PCR in cells or exosomes derived from SNU4th cells treated with or without RNase R digestion. Results are presented as the mean ± SD, n = 3 biological replicates, ns = no significance, *\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001(Student’s t-test).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/b942747bdf557f7f31d33238.png"},{"id":84450627,"identity":"18f7e1aa-47a3-4820-ae1a-f7baaa715ea2","added_by":"auto","created_at":"2025-06-12 06:45:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":490198,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe expression of ebv-circLMP2A and hsa-circRNF13 in EBVaGC tissues and the clinical relevance between miR-5683 and hsa-circRNF13.\u003c/strong\u003e (A-B) The relative expression of ebv-circLMP2A (A) and hsa-circRNF13 (B) in serum exosomes fromsuccessive four generation xenografts. Exo-circLMP2A = Exosomal circLMP2A, Exo-circRNF13 = Exosomal circRNF13, n = 12. (C-D) The relative expression of ebv-circLMP2A (C) and hsa-circRNF13 (D) in EBVaGC patients with or without metastasis. n = 69. (E-F) The top 5 most likely potenial target human miRNAs and top 3 most likely potenial target EBV miRNAs for ebv-circLMP2A (E) and hsa-circRNF13 (F). (G-H) The correlation between the expression levels of miR-4779 and ebv-circLMP2A (G) or miR-5683 and hsa-circRNF13 \u0026nbsp;(H) by performing qRT-PCR on 69 EBVaGC tissues. n = 69. (I) Representative IHC images (left panel) showing CD34 and Ki67 expression in EBVaGC tissues. The images for HE and CD34 were derived from consecutive slices of the same tissue sample. The microvessel density determined by CD34, and Ki67 IHC staining is summarized in the right panel. Scale bar = 100 μm, n = 69. (J) KM survival curves for the overall survival of 69 EBVaGC patients according to the relative expression of miR-5683. n = 69. (K) Pathway relation network analysis of the top 10 significant pathways of up-regulated circRNAs and down-regulated circRNAs. The error bars indicate SEM, ns = no significance, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001(Student’s t-test).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/5cd492e9b9c57b447986c307.png"},{"id":84450641,"identity":"969e0b66-3b19-4830-a963-d17c0d4035f9","added_by":"auto","created_at":"2025-06-12 06:45:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":585916,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSNU4th cell derived exosomes promotes the invasive growth of EBVaGCcells.\u003c/strong\u003e (A) EBVaGC cells YCCEL1 were cultured bySNU4th cells derived PKH67-labeled exosomes for 6h or 24h. Light microscope showed that SNU4th cells derived exosomes were taken up by YCCEL cells. SNU4th-exoPKH67+ = PKH67-labeledSNU4th cells derived exosomes. (B) The expression of ebv-circLMP2A and hsa-circRNF13 by qRT-PCR after incubation with different concentrations of SNU4th cells derived exosomes in YCCEL1 cells for 24h. (C-F) CCK8 assay, wound-healing assay, transwell assays and flow cytometric were used to analyze the effects ofSNU4th cells derived exosomes, compared with treatment withSNU719 cells derived exosomes or 10% FBS on YCCEL1 cellsfor the following characteristics: proliferative ability (C), migratory and invasive capability(D-F), and apoptosis (F). SNU719-Exo = SNU719cells derived exosomes, SNU4th-Exo = SNU4th cells derived exosomes. Results are presented as the mean ± SD, n = 3 biological replicates, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 (Student’s t-test),Scale bar = 50 μm.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/ea5b5de258996e70b8bcff32.png"},{"id":100069613,"identity":"795907e6-3dde-401b-9d4c-64f6699c1f32","added_by":"auto","created_at":"2026-01-12 16:15:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3885029,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/c60c9924-bc30-42e3-9733-818c5a8c239d.pdf"},{"id":84450645,"identity":"f9274cf9-d6e4-4b43-8a31-86150dbe4d00","added_by":"auto","created_at":"2025-06-12 06:45:16","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1040354,"visible":true,"origin":"","legend":"\u003cp\u003eTable. S1. Human CircRNA Expression Profiling.\u003c/p\u003e","description":"","filename":"Table.S1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/5618bc7cfe18d0a7484006a9.xlsx"},{"id":84451135,"identity":"d953844f-23da-4c8b-b347-463e63794405","added_by":"auto","created_at":"2025-06-12 06:53:15","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":44617,"visible":true,"origin":"","legend":"\u003cp\u003eTable. S2. Human-Differentially Expressed circRNAs.\u003c/p\u003e","description":"","filename":"Table.S2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/57c621adf0ad0c38a8cdd84e.xlsx"},{"id":84450595,"identity":"d6f0f0b4-119a-4e4a-a3fe-d2ff7d6db7bc","added_by":"auto","created_at":"2025-06-12 06:45:14","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":11425,"visible":true,"origin":"","legend":"\u003cp\u003eTable. S3. EBV-circRNA--EBV-miRNA Binding Sites prediction.\u003c/p\u003e","description":"","filename":"Table.S3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/71553c91f33d8497ca1f5162.xlsx"},{"id":84452196,"identity":"cce1c2bb-1aeb-4ab7-ae22-1f2e1bb178e3","added_by":"auto","created_at":"2025-06-12 07:01:15","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":125342,"visible":true,"origin":"","legend":"\u003cp\u003eTable. S4. EBV-circRNA--Hsa-miRNA Binding Sites prediction.\u003c/p\u003e","description":"","filename":"Table.S4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/9882a95f4582247246856261.xlsx"},{"id":84451143,"identity":"cafc106b-4332-45fa-90b2-3bf05509398e","added_by":"auto","created_at":"2025-06-12 06:53:15","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":12766,"visible":true,"origin":"","legend":"\u003cp\u003eTable. S5. Hsa-circRNA-- EBV-miRNA Binding Sites prediction.\u003c/p\u003e","description":"","filename":"Table.S5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/afe84b5be8619120ed4b245c.xlsx"},{"id":84450601,"identity":"91d94171-a446-4088-b83c-3d092f30e32e","added_by":"auto","created_at":"2025-06-12 06:45:15","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":119845,"visible":true,"origin":"","legend":"\u003cp\u003eTable. S6. Hsa-circRNA -- Hsa-miRNA Binding Sites predicti\u003c/p\u003e","description":"","filename":"Table.S6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6704451/v1/9240f3f9db189ee5621d538e.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Profiling and functional analysis of exosomal circRNAs from EBV-associated gastric carcinoma CSCs","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEpstein-Barr virus (EBV), recognized as the most prevalent cancer-causing virus in humans, establishes a lifelong latent infection that persists in more than 90% of the global adult population[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Latent infections caused by EBV have been linked to the development of lymphomas and epithelial cancers, including Burkitt's lymphoma (BL), Hodgkin's lymphoma (HL), nasopharyngeal carcinoma (NPC), and gastric carcinoma (GC)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In particular, EBV-associated gastric carcinoma (EBVaGC) stands out as one of the leading causes of mortality related to EBV, with an estimated 75,000 to 90,000 new cases annually[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This subtype constitutes around 10% of all gastric cancer cases and is characterized by unique genomic, molecular, and clinicopathological traits[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs we know, tumor cells are hierarchically organized and sustained by a subpopulation of cells, known as cancer stem cells (CSCs), which possess stem-like functional properties such as strong self-renewal, differentiation, tumorigenesis and drug resistance[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In our previous study, we have established a method to enrich EBVaGC CSCs using a successive xenograft model under chemotherapy pressure and have demonstrated that EBV-encoded circLMP2A (ebv-circLMP2A) could induce stem like properties \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExosomes are nanoscale membrane vesicles released by diverse cell types, typically measuring 50\u0026ndash;200nm in diameter[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Mounting evidences have indicated that exosomes can remodel the biological behaviors of recipient cell which was involved in tumor initiation, progression and metastasis by transferring specific cargos including protein, mRNA and microRNA[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Recent studies have revealed that CSCs also release exosomes to tumor microenvironment (TME) and promote tumor growth, metastasis and immune escape by influencing their surrounding niche. For example, exosomal 5\u0026prime;-triphosphate RNA secreted by colorectal CSCs could stimulate neutrophils and further promote tumorigenesis of colorectal cancer cells through inducing the expression of IL-1β[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Clear cell renal cell carcinoma (CCRCC) CSCs derived exosomes significantly promoted proliferation and metastasis of CCRCC cells by transporting miR-19b-3p into CCRCC cells[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough with the in-depth research of EBV-associated malignancies, increasing studies have shown that EBV-infected tumor cells continuously release exosomes containing viral components in EBV-positive NPC and transformed lymphoblastoid cell lines, their functions in the recipient cells were not explored until recently. For example, LMP1-positive exosomes increased the migration and invasiveness of the recipient nasopharyngeal cell lines[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Gallo et al. found that EBV BART and BHRF1 miRNAs are loaded into the exosomes secreted from LCLs and can be internalized by co-cultured dendritic cells[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Recently, Hinata M et al. discovered that EBVaGC derived exosomes could suppress the maturation of dendritic cells[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These studies indicated that exosomes from EBV-associated malignancies provide a new insight into the biological mechanisms of these diseases.\u003c/p\u003e \u003cp\u003eCircRNAs are newly discovered covalently closed circular RNAs that regulate gene expression at both transcriptional and posttranscriptional levels[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A growing number of studies have discovered that circRNAs have cancer-specific expression pattern and are involved in cancer progression and metastasis[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Moreover, recent studies have shown that circRNAs are enriched and stable in exosomes which play vital roles in the progression of cancer and could be a promising biomarker for cancer diagnosis and prognosis [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur previous studies and other reports have proved that EBV can encode multiple circRNAs (ebv-circRNAs), and further functional analysis has shown that these ebv-circRNAs regulate EBV-driven cancer phenotypes, and ebv-circLMP2A specifically controls cancer stem cells and angiogenesis in EBVaGC[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Ebv-circRPMS1 promoted the proliferation and metastasis of NPC cells and EBVaGC cells[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, whether circRNAs are packaged into EBVaGC derived exosomes and their potential functions are still left to be explored.\u003c/p\u003e \u003cp\u003eIn this study, we explored the alterations of both ebv-circRNAs and human circRNAs expression in exosomes from EBVaGC CSCs and elucidate their functional relevance. These findings will provide a novel perspective on mechanisms by which exosomal circRNAs participate in EBVaGC progression.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Cell culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEBVaGC cell lines SNU719 (RRID: CVCL_5086, authenticated by Short Tandem Repeat (STR) profiling within the last 3 years by Guangzhou Cellcook Biotech Co., Ltd) was purchased from Korean Cell Line Bank. EBVaGC cell line SNU4th with properties of CSCs was constructed by our previous study[6], STR profiling confirmed SNU4th originated from SNU719. EBVaGC cell line YCCEL1 (RRID: CVCL_l440, authenticated by STR profiling within the last 3 years by Guangzhou Cellcook Biotech Co., Ltd) was provided by Dr. Qian Tao from the State Key Laboratory of Oncology at the Chinese University of Hong Kong.\u003c/p\u003e\n\u003cp\u003eSNU719 and YCCEL1 cell lines were cultured in RPMI-1640 medium (Gibco, Carlsbad, CA, USA) with 10% FBS (Gibco). SNU4th cell line was cultured as spheres in serum-free medium containing RPMI-1640, B27 supplement (Life Technologies, Carlsbad, CA, USA), 10 ng/mL fibroblast growth factor (Miltenyi Biotec, Bergisch Gladbach, Germany), 10 ng/mL epidermal growth factor (Miltenyi Biotec), 50 \u0026mu;g/ml insulin (Life Technologies) and 1% penicillin/streptomycin (Life Technologies) in a T75 cm\u003csup\u003e2\u003c/sup\u003e ultralow attachment flask (Corning, New York, NY, USA). All cells were cultured under standard conditions (37\u0026deg;C, 5% CO2, humidified atmosphere), mycoplasma-tested cells were used for all experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Xenografts and patient samples\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe xenograft model under chemotherapy pressure to enrich EBVaGC CSCs was established in previous experiment[6]. Briefly, SNU719 cells were subcutaneously injected (2\u0026times;10⁶ cells/mouse) into 4-week-old female NOD/SCID mice (Model Animal Research Center of Nanjing University). Mice received weekly tail vein injections of 5-Fu (20 mg/kg, Selleck). Tumors were harvested when reaching 1.5cm diameter, digested with collagenase to generate single-cell suspensions, and passage through 5-Fu-treated mice for three generations. Tumor tissues were paraffin-embedded for analysis, while peripheral blood collected via retro-orbital bleeding was processed to isolate serum by sequential centrifugation (500\u0026times;g 10min, 3000\u0026times;g 20min) for exosomal RNA extraction.\u003c/p\u003e\n\u003cp\u003eSixty-nine paraffin-embedded EBVaGC samples were obtained from the Third Affiliated Hospital of Sun Yat-Sen University between January 2006 and June 2012. Inclusion criteria followed those previously defined by Du et al[18], with all cases staged according to the 8th AJCC TNM Classification for Gastric Cancer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Exosomes isolation and characterization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExosomes from cells were isolated according to differential ultracentrifugation method described in the literature[21]. Briefly, cells were serum-starved for 24 hours before conditioned medium was collected. Successive centrifugation (500\u0026times;g 5min, 2000\u0026times;g 10min, 5000\u0026times;g 20min at 4\u0026deg;C) removed cellular debris. Supernatant was then ultracentrifuged at 120,000\u0026times;g for 70min at 4\u0026deg;C using a Beckman ultracentrifuge. For xenograft serum, exosomes were isolated using a Total Exosome Isolation Kit (Invitrogen) per manufacturer\u0026apos;s instructions. Isolated exosomes were resuspended in PBS for immediate use or cryopreserved at -80\u0026deg;C.\u003c/p\u003e\n\u003cp\u003eExosome characterization: Transmission electron microscopy (TEM, Philips CM120) was used to analyze morphology and size. Exosome suspension was applied to carbon-coated formvar grids for 10min, stained with 1% phosphotungstic acid (pH 6.8) for 5 min, and imaged under TEM at 10,000\u0026ndash;200,000\u0026times; magnification.\u003c/p\u003e\n\u003cp\u003eNanoparticle tracking analysis (NTA, NanoSight NS300 instrument, Malvern, UK): Exosome size distribution and concentration were determined using a NanoSight NS300 instrument. The samples were prepared by diluting 10 \u0026mu;L exosome suspension 1:10 with distilled water, loaded into the sample chamber, and analyzed in triplicate. The instrument was calibrated to capture 50\u0026ndash;100 particles per frame, with size distribution and concentration data automatically generated and exported as PDF reports.\u003c/p\u003e\n\u003cp\u003eWestern blot (WB) analysis: Exosomal markers (CD63, TSG101, CD9, CD81) were detected using WB. Exosome/cell lysates were prepared with a BCA Protein Assay Kit (Life Technologies) for quantification. Proteins were separated by 10% SDS-PAGE, transferred to 0.22\u0026mu;m PVDF membranes (Millipore), blocked with 5% skim milk, probed with primary/secondary antibodies, and visualized using an Immobilon ECL kit (Millipore).The sources of primary antibodies and dilutions used were as follows: rabbit anti-CD63 (Abcam, Cat No. ab134045, 1:1000 dilution), rabbit anti-TSG101 (Abcam, Cat No. ab125011, 1:1000 dilution), rabbit anti-CD9 (Abcam, Cat No. ab92726, 1:2000 dilution), rabbit anti- CD81 (Abcam, Cat No. ab109201, 1:1000 dilution), and rabbit anti-\u0026beta;-actin (Cell Signaling Technology, Cat No. #4970, 1:1000 dilution), which was used as an internal control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eRNA preparation and RNase R treatment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from cultured cells and exosomes using TRIzol reagent (Invitrogen) according to the manufacturer\u0026rsquo;s instruction. Total RNA from paraffin-embedded EBVaGC tissues was purified using the Rneasy FFPE Kit (Qiagen) according to the manufacturer\u0026rsquo;s instruction.\u003c/p\u003e\n\u003cp\u003eFor RNA quantification and quality control: RNA integrity was evaluated using a NanoPhotometer N60 (Implen, Munich, Germany) via OD260/280 and OD260/230 ratios alongside agarose gel electrophoresis.\u003c/p\u003e\n\u003cp\u003eFor RNase R treatment: Purified RNA was incubated with 2 U/\u0026mu;g RNase R (Epicentre) at 37\u0026deg;C for 20 minutes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecDNA synthesis, reverse transcription-polymerase chain reaction (RT\u0026ndash;PCR) and quantitative real-time polymerase chain reaction (qRT-PCR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted cDNA synthesis following the manufacturers\u0026apos; protocols. For mRNAs, we used the Evo M - MLV RT Kit with gDNA Clean from AG (Changsha, China), and for miRNAs, the Mir - X miRNA First - Strand Synthesis Kit from Takara (Dalian, China).\u003c/p\u003e\n\u003cp\u003eFor RT - PCR, we employed the SYBR Green Premix Pro Taq HS qPCR Kit from AG to amplify the cDNAs. The RT - PCR products were then separated by electrophoresis on a 1.8% agarose gel stained with 0.4 mg/ml ethidium bromide and visualized under UV light.\u003c/p\u003e\n\u003cp\u003eFor qRT - PCR, we utilized the SYBR Premix Ex TaqTM II Kit from Takara on an ABI 7500 FAST Real - Time PCR System (Applied Biosystems, USA). We selected GAPDH and U6 as internal controls for mRNAs and miRNAs respectively.\u003c/p\u003e\n\u003cp\u003eEach sample was run in triplicate, and the data were analyzed using the 2\u0026minus;\u0026Delta;\u0026Delta;Cq relative quantification method. The primers used in this study are detailed in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Primer sequences used in this study\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"652\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 248px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSequence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003eebv-circLMP2A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: GCGTCACTGATTTTGGGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: TGGGTCCTCAATCCTCCA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003eLMP2A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: CTACTCTCCACGGGATGACTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: AGGTAGGGCGCAACAATTAC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003eebv-circBHLF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: GCCCATTCGAACCCTACC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: TGGTCCTGGAGCTCATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003eebv-circRPMS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: GGGACGCTAGTGCTGCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: GTGTGTCCGGTAAACGCC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003ehsa-circPRKD3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: CTGCAAATTGGCCTCACA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: TGAATGGGTCCATCGAGAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003ehsa-circMEMO1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: GACAGGAATGTTTGAACGCA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: TAAGCATGGGCAGCACAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003ehsa-circRNF13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: TGGGCATCTGTCTCATCTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: TGACAGCATGAGCATCCC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 248px;\"\u003e\n \u003cp\u003eRNF13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward:\u0026nbsp;AAGTGTGTAGATCCCTGGCTAA\u003c/p\u003e\n \u003cp\u003eReverse: GTCCGAGTCACCTTGGGAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003ehsa-circWDR43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: CTCATCTTGACAGCCTCTGCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: CCTGTCTGGGCATTCCAC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003ehsa-circSFMBT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: CGACCAGTTGGTTGGTGTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: ACCTTCCAGGAGGTTGGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003ehsa-circHIPK3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: TAGACTTTGGGTCGGCCA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: CCAAGACTTGTGAGGCCA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003ehsa-circDYM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: TTGCTGTGCTGTTTGATGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: GCATTGTGTGTCTGCCAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003eGAPDH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: AGCCACATCGCTCAGACA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: GCCCAATACGACCAAATCC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003ehsa-miR-4779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: Mir-X miRNA First-Strand Synthesis Kit provided\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: AGGAGGGAATAGTAAAAGCAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003ehsa-miR-5683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: TACAGATGCAGATTCTCTGACTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eUniversal: GCGAGCACAGAATTAATACG AC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 248px;\"\u003e\n \u003cp\u003eU6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eForward: CTCGCTTCGGCAGCACA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 404px;\"\u003e\n \u003cp\u003eReverse: AACGCTT CACGAATTTGCGT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 CircRNA sequencing and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTranscriptome sequencing and bioinformatics analysis were conducted by Cloud-Seq Biotech (Shanghai, China). Total RNA underwent rRNA depletion using Ribo-Zero kits (Illumina), followed by library construction with the TruSeq Stranded Total RNA Kit (Illumina). Library quality was validated via Agilent BioAnalyzer 2100, with 10 pM libraries denatured, cluster-amplified on Illumina flow cells, and sequenced (150 cycles paired-end) on HiSeq instruments. CircRNA annotation utilized GRCh38/hg38 (UCSC) and EBV genome (NC_007605.1, NCBI), with back-spliced junction reads quantifying circRNA abundance. Host genes were assigned based on RefSeq annotations of mapped genomic regions.\u003c/p\u003e\n\u003cp\u003eDifferential expression analysis: Student\u0026rsquo;s t-test identified exosomal circRNAs with \u0026ge;2-fold changes and p\u0026lt;0.05 between SNU719 and SNU4th cells. GO and KEGG pathway enrichment analyses were performed on host genes of these circRNAs. The top 10 significantly enriched pathways for upregulated/downregulated circRNAs were selected to construct pathway networks. miRNA binding sites were predicted using Arraystar software (TargetScan/miRanda algorithms).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eRNA in situ hybridization (ISH)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEBV presence in tumor cells was confirmed via ISH with an EBER-1 probe (PanPath, Amsterdam, the Netherlands), as reported by Chen et al[22].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8 Immunohistochemistry (IHC)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParaffin-embedded xenograft tissues and 69 EBVaGC samples were sectioned into 4-\u0026mu;m-thick slices. Immunohistochemistry was performed using previously described standardized protocols[23]. The sources of antibodies and dilutions used were as follows: Oct4 (Abcam, Cat No. ab181557, 1:1000 dilution), Klf4 (Abcam, Cat No. ab215036, 1:2000 dilution), Sox2 (Abcam, Cat No. ab92494, 1:100 dilution), Mouse anti-CD34 (Cell Signaling Technology, Cat No. #3528, 1:2000 dilution) and Mouse anti-Ki67 (Cell Signaling Technology, Cat No. #9449, 1:2000 dilution).\u003c/p\u003e\n\u003cp\u003eImmunohistochemical staining score was used to evaluate Ki67 IHC staining result by two experienced pathologists. The staining score criteria were performed as follows: the staining intensity was scored as 0 (negative), 1(weak), 2 (moderate), or 3 (strong); the percentage of positive tumor cells was categorized as 0 (\u0026lt;1%), 1 (1%-10%), 2 (11%-50%), 3 (51%-80%), and 4 (\u0026gt;80%) positive cells. The final IHC scores of staining ranged from 0 to 12 by multiplying the scores of the intensity of staining and positive staining percentage.\u003c/p\u003e\n\u003cp\u003eMicrovessel density (MVD) was assessed via CD34 immunohistochemistry following the method described by Du et al [18]. CD34+ endothelial cell or distinct endothelial cluster separated from adjacent vessels, tumor cells, and stroma was counted as one microvessel.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;2.9\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eExosomes internalization assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExosomes internalization assay was conducted to confirm the uptake of labeled exosomes by YCCEL1 cells. First, exosomes from SNU719 or SNU4th cells were labeled with a PKH67 green, fluorescent labeling kit (Sigma-Aldrich, MINI67) according to the manufacturer\u0026apos;s protocol. Next, YCCEL1 cells were plated at a density of 3\u0026times;10⁴ cells/well in 24-well plates and co-incubated with various concentrations of labeled exosomes at 37 \u0026deg;C for 6-24 hours. Finally, the cells were examined under a fluorescence microscope (Excitation: 494 nm; Emission: 521 nm (green); Filter setting: Typical GFP filter set).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.10 Cell proliferation, migration, invasion assays, and flow cytometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess cell proliferation, we seeded cells in 96-well plates at a density of 5\u0026times;10\u0026sup3; cells per well. We then used the Cell Counting Kit-8 (CCK-8) from Dojindo (Japan) to measure cell viability on days 1, 2, 3, 4, and 5 as per the manufacturer\u0026apos;s protocol. An automatic microplate reader (TECAN, Austria) was used to measure the absorbance at 450 nm.\u003c/p\u003e\n\u003cp\u003eA wound healing assay was carried out to evaluate the migratory ability of cells. Cells were seeded in 24-well plates at a density of 5\u0026times;10⁴ cells per well in 1640 medium containing 10% FBS and incubated for 24h. After that, a wound was created using a 10\u0026mu;l pipette tip. The cells were then washed twice with PBS at 0h and 6h. The closure of the wound was observed under a microscope.\u003c/p\u003e\n\u003cp\u003eTo conduct cell migration and invasion assays, we resuspended cells in 200 \u0026mu;L of serum-free RPMI-1640 medium at a density of 5\u0026times;10⁵ cells/ml. Then, we seeded the cell suspension into the upper chambers of transwell inserts (8 \u0026mu;m pore size, Costar). For the migration assay, the inserts were uncoated, while for the invasion assay, they were pre-coated with Matrigel (BD Biosciences, USA). We added RPMI-1640 medium supplemented with 20% FBS to the bottom chamber as a chemoattractant. The cells were then incubated at 37\u0026deg;C in a 5% CO₂ atmosphere for 24h. After incubation, we removed the non-migrated/invaded cells in the upper chambers using cotton swabs. The cells on the lower surface of the inserts were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet. Finally, we randomly selected five microscopic fields of view for imaging.\u003c/p\u003e\n\u003cp\u003eTo analyze apoptosis, we stained the cells with an Annexin V, 633 apoptosis kit from Dojindo (Japan) following the manufacturer\u0026apos;s instructions. Then, we used flow cytometry (BD influx, USA) to analyze the stained cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.11 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experiments were performed in triplicate. Data were analyzed using IBM SPSS 19.0 and GraphPad Prism 6.0, presented as mean \u0026plusmn; SD from \u0026ge;3 independent experiments. Two-tailed Student\u0026rsquo;s t-test evaluated group differences (p\u0026lt;0.05 significant). Pearson\u0026rsquo;s correlation analyzed variable relationships. Median miR-5683 expression defined high/low groups. Overall survival (OS) was calculated from surgery to death/last follow-up. Survival curves were generated via Kaplan\u0026ndash;Meier method with log-rank test for significance.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Characterization of exosomes\u003c/strong\u003e \u003cstrong\u003ederived\u003c/strong\u003e\u003cstrong\u003e from EBVaGC CSCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe previously developed a xenograft model under chemotherapeutic selection to isolate and enrich EBVaGC CSCs[6]. With this model, we obtained SNU4th cells with the properties of CSCs (Fig. 1A). The existence of EBV in successive xenografts was detected by EBER-1 ISH, and compared with the first xenografts, and the expression of stemness makers Oct4, Klf4, Sox2 were obviously increased in the fourth xenografts (Fig. 1B). Next, exosomes in cell culture supernatants from parental SNU719 cells and SNU4th cells were purified by differential ultracentrifugation. As shown in Fig. 1C, the structural features of exosomes were identified by TEM, showing a saucer-like shape morphology and a range of 50-100nm in diameter. The amount and size distribution of exosomes were analyzed by NTA, which shows the higher concentration of SNU4th cells derived exosomes than SNU719 cells derived exosomes（6.86\u0026times;10\u003csup\u003e5\u003c/sup\u003e particles/mL vs 5.91\u0026times;10\u003csup\u003e5\u003c/sup\u003e particles/mL）and the diameter of both SNU719 and SNU4th cells derived exosomes were approximately 100-150nm (Fig. 1D). We further confirmed the presence of the exosome associated makers CD63, TSG101, CD9 and CD81 both in the whole cell lysate and isolated exosomes (Fig. 1E). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 \u003c/strong\u003e\u003cstrong\u003eProfiling of ebv-circRNAs and human circRNAs in \u003c/strong\u003e\u003cstrong\u003eEBVaGC CSCs\u003c/strong\u003e\u003cstrong\u003e derived\u003c/strong\u003e\u003cstrong\u003e exosomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs an initial exploration into whether ebv-circRNAs exist in exosomes, we separately profiled ebv-circRNAs and human circRNAs by using RNA sequencing analysis of ribosomal RNA-depleted total RNA from SNU719 and SNU4th cells derived exosomes. The ebv-circRNAs sequencing reads of each sample were shown in Fig. 2A. There were only six ebv-circRNAs (at least one backspliced read in each sample) exist in exosomes. Despite the low abundance of these ebv-circRNAs, three of these ebv-circRNAs, including ebv-circLMP2A, ebv-circBHLF1 and ebv-circRPMS1(149580_150348+) were significantly up-regulated in SNU4th cells derived exosomes than SNU719 cells derived exosomes. Besides, a total of 8909 distinct human circRNAs were found in exosomes (Fig. 2B, supplementary Table 1). Of these, approximately 80.10% of the human circRNAs originated from exonic regions, and others derived from intergenic regions, introns, antisense, sense overlapping (Fig. 2C). Analysis of the number of human circRNAs isotypes from their host gene showed that one gene could generate multiple human circRNAs isotypes (Fig. 2D). The cluster heatmap for human circRNAs differentially expressed in SNU719 and SNU4th cells derived exosomes revealed distinct expression pattern in these cells with different biological properties (Fig. 2E). As shown in supplementary Table 2 and 3, we identified 261 significantly differentially expressed exosomal circRNAs, of which 167 were up-regulated （supplementary Table 2）and 94 were down-regulated （supplementary Table 3）in SNU4th cells derived exosomes compared with SNU719 cells derived exosomes. Scatter plot (Fig. 2F) illustrates the variation of exosomal circRNAs expression according to the criteria of exhibiting fold change \u0026gt; 2.0 and \u003cem\u003ep\u003c/em\u003e values \u0026le; 0.05. Circos plots (Fig. 2G) analyzed these differentially expressed exosomal circRNAs and their host gene\u0026rsquo;s location, suggesting that the expression of circRNAs were not correlated with their corresponding parent genes. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Bioinformatics analysis of differentially expressed \u003c/strong\u003e\u003cstrong\u003eexosomal \u003c/strong\u003e\u003cstrong\u003ecircRNAs derived host genes \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGO analysis was used to annotate and speculate the function of these differentially expressed exosomal circRNAs derived host genes (Fig. 3A and B). GO analysis of biological process (BP) revealed that these differentially expressed exosomal circRNAs were mainly involved in regulation of protein modification process, mitotic cell cycle, biological regulation and other biological processes. GO analysis of cellular components (CC) showed that these differentially expressed exosomal circRNAs were significantly associated with regulation of intracellular part, endosome, cell junction, and other cellular components. GO analysis of molecular function (MF) indicated that these differentially expressed exosomal circRNAs took part in protein binding, vascular endothelial growth factor, GTPase inhibitor activity and other molecular functions. KEGG analysis (Fig. 3C and D) was performed to predict the top ten significant enrichment pathways which related to the variation of exosomal circRNAs from EBVaGC CSCs. The top three related pathways including viral carcinogenesis, ubiquitin mediated proteolysis and angiogenesis, suggesting that EBVaGC CSCs derived exosomes may play a key role in tumor progression. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 \u003c/strong\u003e\u003cstrong\u003eDetection \u003c/strong\u003e\u003cstrong\u003eof\u003c/strong\u003e\u003cstrong\u003ecircRNAs \u003c/strong\u003e\u003cstrong\u003eexpression \u003c/strong\u003e\u003cstrong\u003ein \u003c/strong\u003e\u003cstrong\u003eEBVaGC CSCs\u003c/strong\u003e\u003cstrong\u003ederived exosomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo test the reliability of the sequencing data, we selected top 10 differentially expressed circRNAs including three ebv-circRNAs (ebv-circLMP2A, ebv-circBHLF1 and ebv-circRPMS1) and seven human circRNAs (hsa-circDYM, hsa-circMEMO1, hsa-circRNF13, hsa-circSFMBT2, hsa-circPRKD3, hsa-circWDR43 and hsa-circHIPK3) for validation in cells or exosomes of SNU719 and SNU4th cells by qRT-PCR. As shown in Fig. 4A-J, the expressions of ebv-circLMP2A, ebv-circRPMS1, hsa-circDYM, hsa-circMEMO1, hsa-circRNF13, hsa-circSFMBT2, hsa-circWDR43 and hsa-circHIPK3 were significantly up-regulated in SNU4th cells compared with SNU719 cells. What\u0026rsquo;s more, among these up-regulated circRNAs, the abundance of ebv-circLMP2A and hsa-circRNF13 were significantly higher in exosomes than in cells, indicating that ebv-circLMP2A and hsa-circRNF13 were enriched in SNU4th cells derived exosomes. Next, the presence of ebv-circRNAs and hsa-circRNF13 were further validated by RT\u0026ndash;PCR in cells and exosomes of SNU4th cells treated with or without RNase R digestion. As shown in Fig. 4K, the fragments of the linear form of LMP2A and RNF13 were digested with RNase R, whereas ebv-circRNAs and hsa-circRNF13 were resistant to RNase R digestion due to their circular form. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 \u003c/strong\u003e\u003cstrong\u003eThe expression of ebv-\u003c/strong\u003e\u003cstrong\u003ecircLMP2A and \u003c/strong\u003e\u003cstrong\u003ehsa-\u003c/strong\u003e\u003cstrong\u003ecircRNF13\u003c/strong\u003e\u003cstrong\u003e in EBVaGC tissues and\u003c/strong\u003e\u003cstrong\u003e the clinical relevance between \u003c/strong\u003e\u003cstrong\u003ehsa-miR-5683 and ebv-\u003c/strong\u003e\u003cstrong\u003ecircLMP2A or \u003c/strong\u003e\u003cstrong\u003ehsa-\u003c/strong\u003e\u003cstrong\u003ecircRNF13\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo determine whether tumor derived exosomal circRNAs enter the circulation and are measurable for cancer detection, we harvested serum from the previously established four successive generation xenografts, and circulating exosomal ebv-circLMP2A and hsa-circRNF13 were quantified by qRT-PCR. As shown in Fig. 5A and B, abundance of EBVaGC derived exosomal ebv-circLMP2A and hsa-circRNF13 in serum were able to be dectected. More importantly, the expression of exosomal ebv-circLMP2A and hsa-circRNF13 in serum were gradually up-regulated among the successive four generation xenografts, indicating that the abundance of exosomal ebv-circLMP2A and hsa-circRNF13 in serum were correlated with tumor stemness. Furthermore, we also detected the expression of ebv-circLMP2A and hsa-circRNF13 in 69 paraffin-embedded EBVaGC tissues by qRT-PCR. As shown in Fig. 5C and D, EBVaGC patients with metastasis had higher expression levels of ebv-circLMP2A and hsa-circRNF13 than patients without metastasis, suggesting that ebv-circLMP2A and hsa-circRNF13 play an important role in promoting the malignant progression of EBVaGC. \u003c/p\u003e\n\u003cp\u003eAs we know, circRNAs-miRNAs interaction has been extensively studied and demonstrated to contribute to cancer progression by participating in the regulation of target gene expression. Therefore, it is necessary to identify the interaction between circRNAs and miRNAs. miRNA binding sites (including EBV derived miRNAs and human derived miRNAs) on differentially expressed exosomal ebv-circRNAs based on TargetScan and miRanda are separately listed in supplementary Table 3 and 4, and miRNA binding sites (including EBV derived miRNAs and human derived miRNAs) on differentially expressed human circRNAs are separately listed in supplementary Table 5 and 6. \u003c/p\u003e\n\u003cp\u003eBecause ebv-circLMP2A and hsa-circRNF13 were highly enriched in SNU4th cells derived exosomes, they were specifically selected for further analysis of the potential target miRNAs that may be related to EBVaGC progression. The top five potential target human derived miRNAs and top three potential target EBV derived miRNAs for ebv-circLMP2A and hsa-circRNF13 were separately presented in Fig. 5E and F. Interestingly, previous literature reports that hsa-miR-4779, which has a significant anti - cancer effect[24], is the downstream target of ebv-circLMP2A. And hsa-miR-5683 is the downstream target of hsa-circRNF13. \u003c/p\u003e\n\u003cp\u003eFurthermore, we detected the expression of hsa-miR-4779 and hsa-miR-5683 in 69 paraffin-embedded EBVaGC tissues by qRT-PCR and analyzed the clinical correlation between hsa-miR-4779 and ebv-circLMP2A or hsa-miR-5683 and hsa-circRNF13. There is no significant correlation between the expression level of hsa-miR-4779 and ebv-circLMP2A (Fig. 5G), but the expression level of hsa-miR-5683 was negatively correlated with hsa-circRNF13 in EBVaGC tissues (Fig. 5H). Furthermore, we studied the expression of CD34 and Ki67 in 69 paraffin-embedded EBVaGC tissues by IHC. The endothelial cells of blood vessels within the tumor were labeled by CD34 for calculating MVD. We observed that lower hsa-miR-5683 expression was positively correlated with MVD and Ki67 expression in EBVaGC samples (Fig. 5I). And EBVaGC patients with lower hsa-miR-5683 expression had a worse 5-year OS than those with higher hsa-miR-5683 expression (95.3% vs 43.8%, \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001, Fig. 5J). Besides, the pathway relation network of the top 10 significant pathways of differentially expressed exosomal circRNAs showed that the ultimate regulatory effect of EBVaGC CSCs derived exosomes was involved in viral carcinogenesis (Fig. 5K). \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 \u003c/strong\u003e\u003cstrong\u003eEBVaGC CSCs\u003c/strong\u003e\u003cstrong\u003e derived exosomes promoted the invasive growth of \u003c/strong\u003e\u003cstrong\u003eEBVaGC cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further understand the role of EBVaGC CSCs derived exosomes in EBVaGC, exosomes from parental SNU719 cells and SNU4th cells were separately isolated, and EBVaGC cells YCCEL1 were pretreated with above different cells derived exosomes for 24h to investigate the effects of exosomes on the biological behaviors of YCCEL1 cells. Firstly, we used PKH67 to mark the exosomes and observed the existence of PKH67-labeled exosomes in YCCEL1 cells. As shown in Fig. 6A, after incubation with different concentrations of SNU4th cells derived exosomes, the abundance of exosomes absorbed by YCCEL1 cells was significantly increased in a dose and time dependent manner. Moreover, we evaluated the expression of ebv-circLMP2A and hsa-circRNF13 by qRT-PCR after incubation with different concentrations of SNU4th cells derived exosomes in YCCEL1 cells for 24h. As shown in Fig. 6B, the expression of hsa-circRNF13 can be detected in a dose-dependent manner in YCCEL1 cells, while the expression of ebv-circLMP2A was poorly low. Besides, compared with 10% FBS or SNU719 cells derived exosomes treatment, the proliferative ability of YCCEL1 cells was enhanced after SNU4th cells derived exosomes treatment (Fig. 6C). And the migratory and invasive capability of YCCEL1 cells were also promoted after incubation with SNU4th cells derived exosomes (Fig. 6D and E). Meanwhile, SNU4th cells derived exosomes also decreased the rate of apoptosis in YCCEL1 cells (Fig. 6F). \u003c/p\u003e\n\u003cp\u003eAltogether, our results indicated that exosomes from EBVaGC CSCs could be transferred into EBVaGC cells and promoted the invasive growth of EBVaGC cells.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTo date, EBV has been studied for decades and was closely associated with kinds of tumors in terms of both epidemiology and molecular biology[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Products including proteins and nucleic acids encoded by EBV play critical roles in the carcinogenesis of EBV. Emerging evidence supports the notion that exosomes serve as perfect carriers for these viral molecules, protecting them from being degraded by host enzymes and transporting them into surrounding cells to continuously influence the biological behavior of recipient cells[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Ebv-circRNAs is a newly discovered member of the EBV transcriptome and has been found to contribute to the oncogenic phenotype in EBV-associated malignancies[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Whether ebv-circRNAs exist in exosomes and their functions are still unknown. Here, we performed a comprehensive expression profile of circRNAs including both ebv-circRNAs and human circRNAs in EBVaGC CSCs derived exosomes and found that two potential cirRNAs, ebv-circLMP2A and hsa-circRNF13, enriched in EBVaGC CSCs derived exosomes, are positively associated with EBVaGC patients with metastasis, which supports the contention of potential functional relevance of tumor phenotype. Moreover, EBVaGC CSCs derived exosomes could be uptaken into EBVaGC cells and promoted the invasive growth of EBVaGC cells, further suggests the potential unique role of CSCs derived exosomes in tumor progression. To the best of our knowledge, this is the first study aiming at identifying circRNAs expression profile in EBVaGC CSCs derived exosomes and providing the first evidence that specific circRNAs are selectively loaded into CSCs derived exosomes which may play an important role in the progression of EBVaGC.\u003c/p\u003e \u003cp\u003eEmerging evidence has suggested that exosomes released by cancer cells act as natural vehicles to transfer specific protein, mRNA or miRNA to recipient cells, which further reprograms the surrounding cells and remodels the TME to be suitable for survival[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The role of exosomal circRNAs has gained increasing attention. Although recent studies have manifested that EBV encoded proein LMP1, LMP2A and BART, BHRF1 miRNAs are selectively enriched in exosomes secreted by EBV-infected cells that act on various target cells with various biological functions, whether circRNAs are packaged into exosomes derived from EBV-infected cells and their functions have not been explored. Here, we used the method previously metioned to acquire SNU-4th which possessed clear stemness characteristics and isolated exosomes from parental SNU719 and SNU4th cell culture supernatants. We focused our attention on the alterations of both ebv-circRNAs and human circRNAs between SNU719 and SNU4th cell derived exosomes by high-throughput whole transcriptome sequencing. In this study, we found only six unique ebv-circRNAs exist in exosomes, three of which including, ebv-circLMP2A, ebv-circBHLF1 and ebv-circRPMS1(149580_150348+) were significantly up-regulated in SNU4th cells derived exosomes. Besides, a total of 8909 distinct human circRNAs were found in exosomes, 261 of these human circRNAs were significantly differentially expressed including 167 were up-regulated and 94 were down-regulated in SNU4th cells derived exosomes. As we known, CSCs serve as the \u0026ldquo;seed\u0026rdquo; and are the cause and maintainers of tumors, therefore, the change of circRNAs in exosomes derived from EBVaGC CSCs may be involved in the malignant progression of EBVaGC.\u003c/p\u003e \u003cp\u003eIn addition, we selected the top 10 up-regulated circRNAs including three ebv-circRNAs and seven human circRNAs for validation by qRT-PCR. The experimental results showed great consistency between the qRT-PCR results and sequencing data, which is helpful for further functional analysis of the differentially expressed exosomal circRNAs. What\u0026rsquo;s more, among the top 10 up-regulated circRNAs, ebv-circLMP2A and hsa-circRNF13 were significantly enriched in EBVaGC CSCs derived exosomes, indicating exosomal ebv-circLMP2A and hsa-circRNF13 may play important roles in the initiation and progression of EBVaGC. It will be necessary to explore the function of ebv-circLMP2A and hsa-circRNF13, which may help to add potential therapeutic targets for EBV-associated malignancies.\u003c/p\u003e \u003cp\u003eWith the deep research of exosomal circRNAs, increasing experimental evidence suggests that tumor derived exosomal circRNAs can enter the circulation and be measurable for cancer detection. That exosomal circRNAs may distinguish patients with cancer from healthy manifests its important translational potential as a circulating biomarker for cancer diagnosis. Here, we found EBVaGC derived exosomal ebv-circLMP2A and hsa-circRNF13 in serum of xenografted mice were able to be detected, and the abundance of exosomal ebv-circLMP2A and hsa-circRNF13 in serum were gradually up-regulated among the four successive generation xenografts, indicating that the abundance of exosomal ebv-circLMP2A and hsa-circRNF13 in serum correlated with tumor stemness. In the following detection of ebv-circLMP2A and hsa-circRNF13 within the tissue samples, we found that EBVaGC patients with metastasis had higher expression levels of ebv-circLMP2A and hsa-circRNF13 than patients without metastasis, further suggesting that exosomal ebv-circLMP2A and exosomal hsa-circRNF13 could be potential liquid biopsy markers for EBVaGC.\u003c/p\u003e \u003cp\u003eGiven that circRNAs could act as a miRNAs sponge and play an important role in regulating the biological behaviors of cancer cells by competitively binding to target miRNAs, the predicted circRNAs-miRNAs network can help to understand the potential molecular mechanisms of ebv-circLMP2A and hsa-circRNF13 in EBVaGC. In this study, we found that hsa-miR-4779 is the downstream target of ebv-circLMP2A and hsa-miR-5683 is the downstream target of hsa-circRNF13. However, only the expression level of hsa-miR-5683 was negatively correlated with hsa-circRNF13 in EBVaGC tissues. Further analysis reveals that lower hsa-miR-5683 expression was positively correlated with MVD and Ki67 expression in EBVaGC samples. In addition, we also observed that EBVaGC patients with lower hsa-miR-5683 expression had a worse 5-year OS than those with higher hsa-miR-5683 expression. These clinical data suggest that hsa-miR-5683 may be a tumor suppressor, which is consistent with what previous study has found that miR-5683 suppresses glycolysis and proliferation through targeting PDK4 in gastric cancer[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNotably, the pathway relation network of the top 10 significant pathways of differentially expressed exosomal circRNAs showed that the ultimate regulatory effect of EBVaGC CSCs derived exosomes was involved in viral carcinogenesis. Here, we found that EBVaGC cells YCCEL1 could take up EBVaGC CSCs derived exosomes and acquired invasive growth ability. These results at the cellular level preliminarily confirm our hypothesis that EBVaGC CSCs derived exosomes play an important role in promoting the malignant progression of EBVaGC, suggesting that inhibiting the release of EBVaGC derived exosomes may be serve as a novel therapeutic strategy. Although the specific molecular mechanisms remain unknown, the role of EBVaGC CSCs derived exosomes in EBVaGC deserves further investigation.\u003c/p\u003e \u003cp\u003eIn summary, this study uncovers a new spectrum of exosomal circRNAs expression pattern in EBVaGC CSCs. The bioinformatics analysis and circRNAs-miRNAs network prediction provide a deep understanding of these differentially expressed exosomal circRNAs which may be related to the malignant progression of EBVaGC. Experiments at the cellular level preliminarily support the hypothesis that EBVaGC CSCs derived exosomes could be transferred into EBVaGC cells to promote the invasive growth of EBVaGC cells. To date, therapies for EBV-associated malignancies have displayed limited effectiveness, our study provides novel therapeutic targets for EBVaGC that focus on EBV derived exosomal circRNAs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLi-ping Gong: designation of the study, experiment performer and writing of the manuscript; Yi-ting Shao: data analysis; Yu Du: animal experiment performer; Li-ping Sun: collection of clinical specimens; Lu-ying Tang: IHC Scoring; Jian-ning Chen: interpretation of data and revise of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank Dr. Qian Tao for providing us with YCCEL1 cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll participants gave informed consent to publish the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal studies were performed in accordance with the institutional ethics guidelines for the animal experiments approved by the Experimental Animal Ethics Committee of the Third Affiliated Hospital, Sun Yat-sen University.\u003c/p\u003e\n\u003cp\u003eAll patient\u0026nbsp;samples were obtained with appropriate informed consent from the patients and approved by the Institute Research Ethics Committee of the Third Affiliated Hospitals of Sun Yat-Sen University (Ethic No. RG2023-111-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (82203679), Medical Research Foundation of Guangdong Province (A2022380), China Postdoctoral Science Foundation (2022M713568).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eYoung, L.S., Yap, L.F., and Murray, P.G. 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Exosome-Mediated Metastasis: Communication from a Distance. Developmental cell \u003cem\u003e49\u003c/em\u003e, 347-360.\u003c/li\u003e\n\u003cli\u003eMiao, Y., Li, Q., Sun, G., Wang, L., Zhang, D., Xu, H., and Xu, Z. (2020). MiR-5683 suppresses glycolysis and proliferation through targeting pyruvate dehydrogenase kinase 4 in gastric cancer. Cancer medicine \u003cem\u003e9\u003c/em\u003e, 7231-7243.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-cancer-research-and-clinical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jocr","sideBox":"Learn more about [Journal of Cancer Research and Clinical Oncology](https://www.springer.com/journal/432)","snPcode":"432","submissionUrl":"https://submission.nature.com/new-submission/432/3","title":"Journal of Cancer Research and Clinical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"EBVaGC, Cancer stem cells, Exosomes, Circular RNAs, Bioinformatics analysis","lastPublishedDoi":"10.21203/rs.3.rs-6704451/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6704451/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRecent studies have found that Epstein-Barr virus (EBV) encodes circular RNAs (ebv-circRNAs) that are involved in tumorigenesis process in EBV-associated gastric carcinoma (EBVaGC). Since little is known whether circRNAs can be enriched into exosomes and their functions in EBVaGC, the aim of our work was to investigate the expression pattern of circRNAs in exosomes derived from EBVaGC cancer stem cells (CSCs). Here, we found two circRNAs, ebv-circLMP2A and hsa-circRNF13 were enriched in EBVaGC CSCs derived exosomes and positively associated with EBVaGC patients with metastasis. Bioinformatics analysis predicted that miR-5683 is the most likely potential target for hsa-circRNF13, and lower miR-5683 expression was positively correlated with microvessel density and Ki67 expression in clinical samples of EBVaGC. Cytology experiments showed that EBVaGC CSCs derived exosomes significantly promoted the invasive growth of EBVaGC cells. Our findings suggest that exosomal circRNAs could be a promising diagnostic and therapeutic target for EBVaGC.\u003c/p\u003e","manuscriptTitle":"Profiling and functional analysis of exosomal circRNAs from EBV-associated gastric carcinoma CSCs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-12 06:45:09","doi":"10.21203/rs.3.rs-6704451/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-18T01:06:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-17T03:29:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"310114144607733054589811808101331854091","date":"2025-08-13T00:19:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"226917854642478908151314284757649095029","date":"2025-06-29T21:30:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-10T05:39:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-20T14:16:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-20T14:12:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Cancer Research and Clinical Oncology","date":"2025-05-20T06:35:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cancer-research-and-clinical-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jocr","sideBox":"Learn more about [Journal of Cancer Research and Clinical Oncology](https://www.springer.com/journal/432)","snPcode":"432","submissionUrl":"https://submission.nature.com/new-submission/432/3","title":"Journal of Cancer Research and Clinical Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7a74cc51-7192-4608-9bde-1d2eef137325","owner":[],"postedDate":"June 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:07:54+00:00","versionOfRecord":{"articleIdentity":"rs-6704451","link":"https://doi.org/10.1007/s00432-025-06414-4","journal":{"identity":"journal-of-cancer-research-and-clinical-oncology","isVorOnly":false,"title":"Journal of Cancer Research and Clinical Oncology"},"publishedOn":"2026-01-08 15:58:01","publishedOnDateReadable":"January 8th, 2026"},"versionCreatedAt":"2025-06-12 06:45:09","video":"","vorDoi":"10.1007/s00432-025-06414-4","vorDoiUrl":"https://doi.org/10.1007/s00432-025-06414-4","workflowStages":[]},"version":"v1","identity":"rs-6704451","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6704451","identity":"rs-6704451","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}