Circulating miR-184 and miR-206 as Predictive Biomarkers for Early Recurrence in HBV- Related Hepatocellular Carcinoma: A Prospective Study

Circulating miR-184 and miR-206 as Predictive Biomarkers for Early Recurrence in HBV- Related Hepatocellular Carcinoma: A Prospective Study | 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 Circulating miR-184 and miR-206 as Predictive Biomarkers for Early Recurrence in HBV- Related Hepatocellular Carcinoma: A Prospective Study Sang-Hoon Kim, Ryunjin Lee, Eunyoung Tak, Ki-Hun Kim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9024910/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: Early recurrence after curative resection remains a major challenge in hepatocellular carcinoma (HCC), particularly in hepatitis B virus (HBV)-related cases. Liquid biopsy using circulating microRNAs (miRNAs) offers a non-invasive approach to identify molecular markers predictive of recurrence. Methods: We prospectively enrolled 30 individuals with HBV-related HCC presenting with a single tumor (<5 cm) and no vascular invasion or metastasis. Blood samples were collected preoperatively and on postoperative day 7. Expression of 20 selected miRNAs from circulating cell-free DNA/RNA and exosomes was analyzed. Participants were categorized into early recurrence (within 1 year, n=6) and non-recurrence (n=24) groups. Differentially expressed miRNAs were identified, and target genes of significant miRNAs were retrieved from miRTarBase. Protein–protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape. Enrichment analysis was performed using Gene Ontology and KEGG pathway databases. Results: On postoperative day 7, expression of miR-184 and miR-206 was significantly lower in the early recurrence group than in the non-recurrence group (p < 0.05). Other miRNAs showed no significant differences. Target gene analysis revealed 16 key hub proteins—CCND1, CCND2, KLF4, NOTCH3, BDNF, MET, CDK4, BCL2, AKT2, IGF1R, MYC, HDAC4, ESR1, KRAS, SMARCB1, and AGO2—enriched in cancer-related pathways and involved in HCC progression. Conclusion: Reduced postoperative expression of miR-184 and miR-206 may predict early recurrence in individuals with HBV-related HCC. Their associated regulatory networks suggest possible mechanisms of recurrence and represent potential biomarkers for postoperative surveillance. Further studies are needed to validate their prognostic value. Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide, particularly in East Asia, where chronic hepatitis B virus (HBV) infection remains highly prevalent. In Korea, HBV is the predominant cause of HCC, accounting for approximately 60–75% of cases. 1 , 2 Although curative resection is feasible in early-stage disease, especially in individuals with a solitary tumor smaller than 5 cm, early recurrence within one year after surgery continues to significantly impact long-term survival. Liquid biopsy, which involves analyzing circulating biomarkers such as cell-free DNA, RNA, and exosomal miRNAs, has emerged as a promising non-invasive tool to detect minimal residual disease and predict recurrence risk. 3 – 6 Recent studies have demonstrated the potential of circulating miRNAs and cell-free DNA as diagnostic and prognostic biomarkers for HCC. However, many of these investigations are retrospective and involve heterogeneous populations, with variability in tumor size, stage, and underlying etiology. 7 Prospective studies specifically targeting individuals with HBV-related HCC and small solitary tumors—those considered ideal candidates for curative resection—remain limited. Furthermore, few studies have examined the biological relevance of these circulating biomarkers in the context of early tumor recurrence. 8 We conducted a prospective study in individuals with HBV-related HCC and solitary tumors < 5 cm, analyzing perioperative changes in circulating miRNAs to identify biomarkers associated with early recurrence within one year after surgery. Our aim was to identify non-invasive prognostic markers and improve understanding of the molecular mechanisms underlying postoperative recurrence in this population. MATERIALS AND METHODS Ethical considerations All study procedures, including the collection of informed consent, were conducted in accordance with the ethical standards of the Institutional Review Board of Asan Medical Center and the principles of the 1975 Declaration of Helsinki. The study protocol was reviewed and approved by the Institutional Review Board of Asan Medical Center, Seoul, Korea (IRB No. 2023-0048). Written informed consent was obtained from all participants for the use of anonymized data in this research. The study also adheres to the STROBE reporting guidelines, as detailed in Supplementary Table 1. Study population This prospective observational study was conducted at Asan Medical Center in Seoul, Korea. From June 2023 to February 2024, we enrolled 30 individuals with HCC who underwent curative surgical resection and 10 healthy individuals who underwent living donor right hepatectomy as the control group. Final follow-up data were collected on June 30, 2025. Participants in the HCC group were included if they met all of the following criteria: (1) chronic HBV infection; (2) a single primary tumor smaller than 5 cm; (3) no evidence of preoperative metastasis; (4) no vascular or biliary invasion before surgery; and (5) open curative anatomical resection. Exclusion criteria included: (1) tumor recurrence; (2) a history of other malignancies before surgery; (3) combined liver disease unrelated to HBV, such as hepatitis C or alcoholic liver disease; or (4) minimally invasive surgery. Healthy living donors in the control group were eligible if they met the following conditions: (1) no history of malignancy; (2) age over 20 years; and (3) no underlying liver disease. Sample collection and processing This study included individuals with HCC and healthy living liver donors. Peripheral blood samples (10 mL) were collected in EDTA tubes at two time points: on the day of surgery before the operation and seven days after surgery. Samples were de-identified, assigned study numbers, and processed within two hours of collection. Plasma was separated by centrifugation at 820 × g for 10 minutes at 4 °C, followed by a second centrifugation at 1,450 × g for 10 minutes to remove residual cells. The supernatant was aliquoted into labeled Eppendorf tubes and stored at −80 °C or in liquid nitrogen tanks. Remaining samples were discarded after the study period according to institutional guidelines. Extraction of circulating cell-free DNA and RNA Circulating cell-free DNA (ccfDNA) and RNA (ccfRNA) were isolated from 1.0–4.0 mL of thawed plasma using the QIAamp® ccfDNA/RNA Kit (Qiagen, Cat. No. 55184) according to the manufacturer’s protocol. Briefly, nucleic acids were extracted following proteinase K digestion and column-based purification and eluted in 20 µL of RNase-free water. The concentration and purity of the isolated nucleic acids were assessed using a NanoDrop spectrophotometer. Exosome precipitation and RNA isolation Exosomes were isolated from 0.5–1.0 mL of thawed plasma using the Exodisc device (LabSpinner™, Cat. No. EX-D1001), following the manufacturer’s instructions. Plasma samples were applied to the Exodisc unit and subjected to tangential flow filtration through a series of nano-sized filters. This process enabled selective capture of extracellular vesicles, which were subsequently recovered through gentle elution for downstream analyses. Exosomal RNA was extracted using the miRNeasy Micro Kit (Qiagen, Cat. No. 217084). Exosome suspensions were mixed with 700 µL of QIAzol lysis reagent and processed according to the manufacturer’s protocol. The RNA was eluted in 14 µL of RNase-free water and stored at −80 °C until further analysis. Exosome tracking analysis To analyze exosomes isolated from plasma, extracellular vesicles were purified using the Exodisc device (LabSpinner™, Cat. No. EX-D1001) and characterized by nanoparticle tracking analysis (NTA) using the NanoSight NS300 system. Western blot analysis Protein concentrations were determined using the BCA Assay Reagent (Cat. No. 23225; Thermo Fisher Scientific). Equivalent amounts of protein from each sample were loaded onto polyacrylamide gels and separated by electrophoresis.The separated proteins were transferred to nitrocellulose membranes (Cat. No. 1704270, Bio-Rad) for 20 minutes. The membranes were then blocked with 5% skim milk dissolved in Tris-buffered saline containing 0.1% Tween-20 (TBST) for 1 hour at room temperature. After washing, the membranes were incubated overnight at 4 °C with specific primary antibodies of interest, diluted in 5% BSA in TBST. Following primary antibody incubation, the membranes were probed with horseradish peroxidase (HRP)-conjugated anti-rabbit IgG antibodies. Exosomal marker ALIX (Recombinant Anti-ALIX antibody, Abcam, ab275377, 1:1,000) was used for 1 hour at room temperature.Protein bands were visualized using ECL SuperSignal West Femto Maximum Sensitivity Substrate (Cat. No. 34095, Thermo Fisher Scientific), and images were captured using the LuminoGraph II system (Cat. No. WSE-6200, ATTO). miRNA analysis Reverse transcription of extracted miRNAs was performed using the miRCURY LNA™ RT Kit (Qiagen, Cat. No. 339340) according to the manufacturer’s instructions. Briefly, RNA templates were incubated at 42 °C for 1 hour, followed by enzyme inactivation at 95 °C for 5 minutes, and then held at 4 °C to complete cDNA synthesis. Quantitative PCR (qPCR) was conducted using the miRCURY LNA™ SYBR Green PCR Kit (Qiagen, Cat. No. 339347) along with miRNA-specific LNA-enhanced primers. The qPCR cycling conditions consisted of an initial denaturation at 95 °C for 2 minutes, followed by 40 cycles of 95 °C for 10 seconds and 56 °C for 1 minute. A melting curve analysis was subsequently performed at 95 °C for 10 seconds, 60 °C for 5 seconds, and a gradual increase to 95 °C with a 0.5 °C/s ramp rate. All reactions were performed in technical duplicates using the Bio-Rad CFX384 Connect Real-Time System. The relative expression levels of target miRNAs were normalized to the endogenous control U6, and data were analyzed using the ΔΔCt method. The study analyzed liver-associated miRNAs related to HCC, including hsa-miR-122-3p, hsa-miR-122-5p, hsa-miR-1247-3p, hsa-miR-148b, hsa-miR-155, hsa-miR-184, hsa-miR-192, hsa-miR-193b, hsa-miR-195, hsa-miR-199a-3p, hsa-miR-199a-5p, hsa-miR-206, hsa-miR-21-3p, hsa-miR-21-5p, hsa-miR-221, hsa-miR-222-3p, hsa-miR-223, hsa-miR-224, hsa-miR-766, and hsa-miR-93, to evaluate expression changes and their association with early recurrence. All primer sequences of the miRNAs used in this study are provided in Supplementary Table 2 . Bioinformatics analysis To investigate the functional roles of predicted target genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the DAVID database ( http://david.ncifcrf.gov ). Enriched terms were classified into biological processes, cellular components, and molecular functions, with a p-value < 0.05 considered significant. Protein–protein interaction (PPI) analysis was performed using the STRING database ( http://www.string-db.org/ ) with a confidence score ≥ 0.4, and the network was visualized using Cytoscape (version 3.10.3). Hub genes were identified and validated through GEPIA ( http://gepia.cancer-pku.cn/ ) based on TCGA and GTEx data. Kaplan–Meier survival analyses were performed to evaluate the prognostic value of hub genes, with groups stratified by median expression. Log-rank tests were used for comparisons, and hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. A p-value < 0.05 was considered statistically significant. Clinical and pathological data Baseline characteristics and clinicopathological factors were prospectively collected from medical records. Demographic and clinical data included age, sex, body mass index, platelet count, prothrombin time, serum creatinine, total bilirubin, aspartate aminotransferase, alanine aminotransferase, and serum albumin. Pathological data included tumor number, maximum tumor diameter, tumor grade, and the presence of microvascular invasion, portal vein invasion, hepatic vein invasion, hepatic artery invasion, bile duct invasion, capsule invasion, lymphovascular invasion, satellite nodules, background liver cirrhosis, and fatty liver. Recurrence within one year after surgery was defined as early recurrence. Statistical analysis All continuous variables are presented as medians with ranges and were compared using the Mann–Whitney U test. Categorical variables are expressed as counts with percentages and were compared using Fisher’s exact test. A total of 20 circulating miRNAs (miR-122-3p, miR-122-5p, miR-1247-3p, miR-148b, miR-155, miR-184, miR-192, miR-193b, miR-195, miR-199a-3p, miR-199a-5p, miR-206, miR-21-3p, miR-21-5p, miR-221, miR-222-3p, miR-223, miR-224, miR-766, and miR-93) were analyzed. Expression levels were compared between the healthy donor group and the HCC group using one-way analysis of variance. Group differences were further evaluated with the Mann–Whitney U test, and differential expression distributions were visualized using heatmaps. A two-sided p-value < 0.05 was considered statistically significant. All statistical analyses were performed using R software (version 4.4.1; R Foundation for Statistical Computing, Vienna, Austria) and Python (version 3.11; Python Software Foundation, Wilmington, DE, USA). RESULTS During the study period, 30 individuals with HCC underwent curative open anatomical liver resection. Their perioperative and pathological outcomes are summarized in Table 1 . Baseline characteristics of 10 healthy living liver donors, included as the normal control group, are presented in Supplementary Table 3 . A flow chart of study inclusion is shown in Figure 1 . Early recurrence Of the 30 individuals with hepatocellular carcinoma, six experienced early recurrence within one year after surgery. The median time to recurrence was 157 days (range, 94–352 days). All recurrences were identified as intrahepatic metastases ( Table 1 ). HCC-specific circulating microRNA expression Compared with preoperative day 1, four miRNAs in the cell-free RNA fraction showed significant changes on postoperative day 7, namely miR-184, miR-21-3p, miR-224, and miR-766 (p < 0.05). In contrast, seven circulating exosomal miRNAs exhibited significant changes: miR-148b, miR-184, miR-192, miR-206, miR-21-5p, miR-224, and miR-93 (p < 0.05). The comparison of circulating cell-free and exosomal microRNA expression between individuals with HCC and healthy donors is summarized in Supplementary Table 4 . A heatmap of differential expression is provided in Supplementary Figure 1 . MicroRNA expression as a biomarker of early recurrence To identify biomarkers associated with early recurrence of HCC within one year, 20 circulating miRNAs were analyzed from blood samples collected preoperatively and on postoperative day 7. Comparison with healthy donors showed no significantly up- or down-regulated miRNAs in either the cell-free RNA fraction or the exosomal fraction at preoperative day 1. However, by postoperative day 7, significant downregulation of miR-184 and miR-206 was observed in the cell-free RNA fraction (p < 0.05). No significant changes were detected in the exosomal fraction. The comparison of circulating cell-free and exosomal microRNA expression between recurrent and non-recurrent HCC cases is summarized in Table 2 , and a heatmap of differential expression is shown in Figure 2 . Notably, reduced postoperative expression of miR-184 and miR-206 was associated with early recurrence, suggesting their potential as prognostic biomarkers following curative resection for HBV-related HCC. ALIX expression in exosomal plasma protein Plasma was separated from participant samples, followed by purification of exosomal miRNAs using the ExoDisc platform ( Figure 3A ). The presence of the exosome biomarker ALIX was confirmed via western blot analysis. ALIX served as a loading control to compare protein loading amounts across samples. We observed a differential expression pattern: ALIX was absent in samples from healthy donors but expressed in those from individuals with HCC ( Figure 3B ). Full-length original membrane of ALIX (96 kDa) detected in human plasma-derived exosomes was showed in Supplementary Figure 2. Nanoparticle tracking analysis (NTA) was also performed to confirm the presence of exosomes by measuring their size and concentration ( Figure 3C ). Protein–protein interaction network and hub gene identification Using Cytoscape (version 3.10.3) and the STRING database, a PPI network of 28 predicted target genes of miR-184 and miR-206 was constructed. The network consisted of 17 nodes and 30 edges, with an average node degree of 3.53 and an average local clustering coefficient of 0.416 ( Figure 4A ). Topological analysis in Cytoscape identified hub genes based on degree of connectivity. The following 16 hub genes showed the highest degree centrality: CCND1, CCND2, KLF4, NOTCH3, BDNF, MET, CDK4, BCL2, AKT2, IGF1R, MYC, HDAC4, ESR1, KRAS, SMARCB1, and AGO2 ( Figure 4B ). These genes, predicted targets of miR-184 and miR-206, are likely to play central roles in the regulatory network associated with early recurrence of HCC. Functional enrichment and KEGG pathway analyses of these 16 hub genes demonstrated significant involvement in cell cycle regulation, transcriptional control, and multiple cancer-related pathways, including HCC, breast cancer, melanoma, gastric cancer, and miRNAs in cancer. Detailed enrichment terms and associated signaling pathways are summarized in Supplementary Table 5 . Validation of hub genes using the TCGA database Validation of the 16 hub genes targeted by miR-184 and miR-206 using TCGA and GEPIA databases revealed that high CDK4 expression and low ESR1 expression were significantly associated with poor recurrence-free survival and overall survival in HCC ( Supplementary Figures 3 and 4) . DISCUSSION Early recurrence after curative treatment remains a major obstacle to improving long-term outcomes in HCC. 9–11 Many individuals who undergo surgery or liver transplantation experience recurrence within the first year, even when tumors are small and detected early. 12 To more accurately predict this risk, recent studies have explored liquid biopsy techniques using biomarkers such as circulating miRNAs, cell-free DNA, and circulating tumor cells. 10,11 These non-invasive approaches have shown promising potential for identifying individuals with minimal residual disease. For example, changes in circulating miRNA levels 13 , the presence of tumor-specific mutations in plasma 14 , or the persistent detection of circulating tumor cells 15 have all been associated with early recurrence. Liquid biopsy research has gained significant attention because it enables real-time monitoring of tumor dynamics without the need for invasive procedures and may help guide more personalized surveillance and treatment strategies after surgery 11 . In this study, we used a liquid biopsy approach to measure circulating miRNAs as predictors of early recurrence following curative resection in individuals with HBV-related HCC. This method is non-invasive, allows for repeated sampling, and enables real-time monitoring of tumor behavior. 16 Circulating miRNAs are stable in blood and have been widely investigated as diagnostic and prognostic biomarkers in HCC. 17,18 However, their clinical utility remains limited due to technical variability and patient heterogeneity. 19 Most previous studies on miRNAs and HCC recurrence were based on tumor tissue samples, which require invasive sampling and are unsuitable for serial monitoring. 20 Although several recent studies have investigated circulating miRNAs, many focused on preoperative levels or employed multi-miRNA panels without evaluating postoperative changes. In our study, we observed distinct postoperative alterations in circulating miRNA profiles specific to HBV-related HCC. Compared with preoperative levels, four miRNAs from the cell-free RNA fraction (miR-184, miR-21-3p, miR-224, and miR-766) and seven miRNAs from the exosomal fraction (miR-148b, miR-184, miR-192, miR-206, miR-21-5p, miR-224, and miR-93) showed significant up- or downregulation by postoperative day 7. These tumor-associated miRNA alterations hold potential not only as biomarkers for diagnosis and recurrence monitoring but also as a foundation for future studies exploring liquid biopsy–based strategies in the postoperative management of HCC. 21 Regarding biomarkers for early recurrence, specific miRNAs such as miR-2122, miR-26a, miR-221, miR-122, and miR-1246 have previously been identified as recurrence-associated markers, primarily in diagnostic or pre-treatment settings. 7,23,24 In our study, we analyzed 20 candidate miRNAs from plasma samples collected both preoperatively and on postoperative day 7 in individuals with early-stage HCC. We found that miR-184 and miR-206 were significantly downregulated in individuals who experienced early recurrence, suggesting their potential as biomarkers of minimal residual disease and recurrence risk. Unlike prior studies that focused on a single time point, our approach emphasized dynamic changes in the early postoperative phase, which may reflect molecular events preceding clinical recurrence. This postoperative blood-based monitoring approach may aid in the early detection of minimal residual disease and inform surveillance strategies for individuals with early-stage HCC. Larger studies are warranted to validate these findings and clarify the roles of miR-184 and miR-206 in recurrence biology. Our bioinformatics analyses identified 16 hub genes—CCND1, CCND2, KLF4, NOTCH3, BDNF, MET, CDK4, BCL2, AKT2, IGF1R, MYC, HDAC4, ESR1, KRAS, SMARCB1, and AGO2—as potential key regulators in HCC. Analysis of The Cancer Genome Atlas (TCGA) data further confirmed that high CDK4 expression and low ESR1 expression were significantly associated with increased risk of early recurrence and reduced overall survival, underscoring their potential as prognostic biomarkers and therapeutic targets. CDK4, a critical regulator of the G1/S cell cycle transition, is frequently overexpressed in HCC and has been associated with tumor aggressiveness, microvascular invasion, and poor survival outcomes. 25–29 In contrast, ESR1, known for its tumor-suppressive function, is often downregulated in HCC due to promoter hypermethylation, with low expression correlating with early recurrence and unfavorable prognosis. 30–33 This study has several notable strengths. First, it was a well-designed prospective investigation focused exclusively on individuals with early-stage HCC, specifically those with a single tumor smaller than 5 cm. Second, to minimize variation in surgical techniques and perioperative factors, only patients who underwent open hepatic resection were included. Third, all participants had underlying chronic HBV infection, eliminating etiologic heterogeneity and resulting in a more homogeneous study population. Finally, the study integrated clinical outcomes, circulating miRNA expression, protein expression, and bioinformatic analysis, providing a more comprehensive understanding of the potential molecular mechanisms associated with early recurrence after curative resection. This study also has several limitations. First, the sample size was relatively small, which may limit the statistical power and generalizability of the findings. Second, the follow-up duration was insufficient to evaluate long-term outcomes such as late recurrence or overall survival. Third, although postoperative levels of miR-184 and miR-206 were significantly associated with early recurrence, no significant differences in preoperative circulating miRNA levels were observed between the early recurrence and non-recurrence groups, which limits their utility as preoperative predictive markers. Fourth, the study did not assess the relationship between circulating miRNA expression in blood and their corresponding expression levels in tumor tissue, leaving the biological origin and relevance of these circulating biomarkers uncertain. In conclusion, this prospective study highlights the potential of circulating miR-184 and miR-206 as early predictive biomarkers for postoperative recurrence in individuals with HBV-related HCC characterized by a single tumor smaller than 5 cm. Significantly lower expression of miR-184 and miR-206 was associated with early intrahepatic recurrence, indicating their potential utility for risk stratification and postoperative monitoring. Bioinformatic analysis further identified key hub genes—including CCND1, CCND2, KLF4, NOTCH3, BDNF, MET, CDK4, BCL2, AKT2, IGF1R, MYC, HDAC4, ESR1, KRAS, SMARCB1, and AGO2—of which elevated CDK4 expression and reduced ESR1 expression appeared most strongly linked to early recurrence, suggesting their potential role in postoperative tumor progression. Future large-scale, multi-institutional studies are needed to validate these findings and explore potential therapeutic applications targeting these molecular pathways. Declarations Authorship contributions Sang-Hoon Kim : Conceptualization, Investigation, Data Curation, Visualization, Writing – Original Draft, Writing – Review & Editing. Ryunjin Lee : Investigation, Visualization, Data Curation. Eunyoung Tak : Conceptualization, Data Curation, Visualization, Project Administration, Funding Acquisition, Writing – Original Draft, Writing – Review & Editing. Ki-Hun Kim : Conceptualization, Supervision, Funding Acquisition. Funding This study was sponsored by Yuhan (IIT-061). Research funding was provided to support the conduct of this study. Data availability The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate All study procedures, including the collection of informed consent, were conducted in accordance with the ethical standards of the Institutional Review Board of Asan Medical Center and the principles of the 1975 Declaration of Helsinki. The study protocol was reviewed and approved by the Institutional Review Board of Asan Medical Center, Seoul, Korea (IRB No. 2023-0048). Written informed consent was obtained from all participants for the use of anonymized data in this research. Conflict of Interest The authors declare no conflicts of interest related to this study. Consent for publication All participants signed a document of informed consent. References Lim Y. 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Supplementary Files Supplementarydata.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 Apr, 2026 Reviews received at journal 09 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviews received at journal 08 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviewers invited by journal 07 Apr, 2026 Editor assigned by journal 07 Apr, 2026 Editor invited by journal 30 Mar, 2026 Submission checks completed at journal 28 Mar, 2026 First submitted to journal 28 Mar, 2026 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. We do this by developing innovative software and high quality services for the global research community. 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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-9024910","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":620703226,"identity":"40c2949e-0a97-4e7d-b5c2-f7f3820a9747","order_by":0,"name":"Sang-Hoon Kim","email":"","orcid":"","institution":"University of Ulsan College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Sang-Hoon","middleName":"","lastName":"Kim","suffix":""},{"id":620703227,"identity":"502e304a-3437-406a-b7b0-2504483521f1","order_by":1,"name":"Ryunjin Lee","email":"","orcid":"","institution":"Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ryunjin","middleName":"","lastName":"Lee","suffix":""},{"id":620703228,"identity":"8f212d35-cc77-485a-a9fa-a4abb4723dfb","order_by":2,"name":"Eunyoung Tak","email":"","orcid":"","institution":"Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Eunyoung","middleName":"","lastName":"Tak","suffix":""},{"id":620703229,"identity":"10a665e8-fdea-444e-9741-dea897faebf9","order_by":3,"name":"Ki-Hun Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIie3OsWrDMBCA4RMGZzHJeiJFz+CgNfRZfBTUJdo9ChK0Zi30JVoMpqNaQTNUD5A8RMDQ1ZC6gRYCRfHYQf9ww8HHHUAq9Q9DzMFBvSxmv6sJZCNIUIKbn1U2ggDbeFm6sYQ/Wno7mIya3Qd10C9F6SGTdYTMb96d1y85tUE3yKyS34RChAi8N16HglqnW2DG09NAXs1VYpGa7bEF6E/XyRzV8JgtZYnDFcjdmVCM8AdV+VWoBO6PDZK9k9yz9SJGcK/k56o+FbOtfu66/lZMd2vPY+Sy6jzZeJBKpVKpv/sCzIxRQK7/3+gAAAAASUVORK5CYII=","orcid":"","institution":"University of Ulsan College of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Ki-Hun","middleName":"","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2026-03-04 02:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9024910/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9024910/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107241857,"identity":"219a162e-c53d-4561-bcb1-4cfbd2519a34","added_by":"auto","created_at":"2026-04-19 07:18:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":143259,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of study inclusion\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9024910/v1/f024fdd6a55457a0f5015289.png"},{"id":107241859,"identity":"ec16e497-ab2f-4313-9d2e-1b5e4e091d2e","added_by":"auto","created_at":"2026-04-19 07:18:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":139518,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap showing differential expression of circulating cell-free DNA/RNA (A) and exosomal miRNAs (B) between individuals with hepatocellular carcinoma with and without recurrence. All values are presented as log₂-transformed relative ratios (Recurrence/Non-Recurrence). Δ relative ratios indicate the change from preoperative levels to postoperative day 7.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9024910/v1/ebc1f641b848f50e2cbae653.png"},{"id":107484166,"identity":"4e9ca635-579d-49cd-a293-88739a1ae800","added_by":"auto","created_at":"2026-04-22 02:31:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":172386,"visible":true,"origin":"","legend":"\u003cp\u003ePreparation and characterization of plasma-derived exosomes using the ExoDisc platform and assessment of protein expression levels. (A) Schematic overview of exosome isolation from plasma using ExoDisc. (B) Expression patterns of the exosomal biomarker ALIX in samples from healthy donors and individuals with HCC. (C) Nanoparticle tracking analysis of plasma-derived exosomes.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9024910/v1/9765f36a78faede9228b47c0.png"},{"id":107241861,"identity":"2180eadc-1a5d-4527-b804-61dac6d43fc3","added_by":"auto","created_at":"2026-04-19 07:18:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":247994,"visible":true,"origin":"","legend":"\u003cp\u003eProtein–protein interaction networks associated with miR-184 and miR-206. (A) Overall interaction network. (B) Subnetwork highlighting the top sixteen hub genes with the highest degree of connectivity.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9024910/v1/d4166da959bd37edc41bfc1e.png"},{"id":107705164,"identity":"f9daa2e6-83c7-4257-974b-98b5632b2fda","added_by":"auto","created_at":"2026-04-24 09:08:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":827021,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9024910/v1/33228f0c-b5c6-48d1-9f85-125ad68efd39.pdf"},{"id":107484409,"identity":"9de82085-24cd-4582-804a-c1f28396cfb2","added_by":"auto","created_at":"2026-04-22 02:31:54","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3828523,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydata.docx","url":"https://assets-eu.researchsquare.com/files/rs-9024910/v1/221cdf2a4a592bd385c8ddc1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Circulating miR-184 and miR-206 as Predictive Biomarkers for Early Recurrence in HBV- Related Hepatocellular Carcinoma: A Prospective Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide, particularly in East Asia, where chronic hepatitis B virus (HBV) infection remains highly prevalent. In Korea, HBV is the predominant cause of HCC, accounting for approximately 60\u0026ndash;75% of cases.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Although curative resection is feasible in early-stage disease, especially in individuals with a solitary tumor smaller than 5 cm, early recurrence within one year after surgery continues to significantly impact long-term survival.\u003c/p\u003e \u003cp\u003eLiquid biopsy, which involves analyzing circulating biomarkers such as cell-free DNA, RNA, and exosomal miRNAs, has emerged as a promising non-invasive tool to detect minimal residual disease and predict recurrence risk.\u003csup\u003e\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRecent studies have demonstrated the potential of circulating miRNAs and cell-free DNA as diagnostic and prognostic biomarkers for HCC. However, many of these investigations are retrospective and involve heterogeneous populations, with variability in tumor size, stage, and underlying etiology.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Prospective studies specifically targeting individuals with HBV-related HCC and small solitary tumors\u0026mdash;those considered ideal candidates for curative resection\u0026mdash;remain limited. Furthermore, few studies have examined the biological relevance of these circulating biomarkers in the context of early tumor recurrence.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWe conducted a prospective study in individuals with HBV-related HCC and solitary tumors\u0026thinsp;\u0026lt;\u0026thinsp;5 cm, analyzing perioperative changes in circulating miRNAs to identify biomarkers associated with early recurrence within one year after surgery. Our aim was to identify non-invasive prognostic markers and improve understanding of the molecular mechanisms underlying postoperative recurrence in this population.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical considerations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study procedures, including the collection of informed consent, were conducted in accordance with the ethical standards of the Institutional Review Board of Asan Medical Center and the principles of the 1975 Declaration of Helsinki. The study protocol was reviewed and approved by the Institutional Review Board of Asan Medical Center, Seoul, Korea (IRB No. 2023-0048). Written informed consent was obtained from all participants for the use of anonymized data in this research. The study also adheres to the STROBE reporting guidelines, as detailed in \u003cstrong\u003eSupplementary Table 1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy population\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis prospective observational study was conducted at Asan Medical Center in Seoul, Korea. From June 2023 to February 2024, we enrolled 30 individuals with HCC who underwent curative surgical resection and 10 healthy individuals who underwent living donor right hepatectomy as the control group. Final follow-up data were collected on June 30, 2025.\u003c/p\u003e\n\u003cp\u003eParticipants in the HCC group were included if they met all of the following criteria: (1) chronic HBV infection; (2) a single primary tumor smaller than 5 cm; (3) no evidence of preoperative metastasis; (4) no vascular or biliary invasion before surgery; and (5) open curative anatomical resection. Exclusion criteria included: (1) tumor recurrence; (2) a history of other malignancies before surgery; (3) combined liver disease unrelated to HBV, such as hepatitis C or alcoholic liver disease; or (4) minimally invasive surgery.\u003c/p\u003e\n\u003cp\u003eHealthy living donors in the control group were eligible if they met the following conditions: (1) no history of malignancy; (2) age over 20 years; and (3) no underlying liver disease.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSample collection and processing\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included individuals with HCC and healthy living liver donors. Peripheral blood samples (10 mL) were collected in EDTA tubes at two time points: on the day of surgery before the operation and seven days after surgery. Samples were de-identified, assigned study numbers, and processed within two hours of collection. Plasma was separated by centrifugation at 820 × g for 10 minutes at 4 °C, followed by a second centrifugation at 1,450 × g for 10 minutes to remove residual cells. The supernatant was aliquoted into labeled Eppendorf tubes and stored at −80 °C or in liquid nitrogen tanks. Remaining samples were discarded after the study period according to institutional guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eExtraction of circulating cell-free DNA and RNA\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCirculating cell-free DNA (ccfDNA) and RNA (ccfRNA) were isolated from 1.0–4.0 mL of thawed plasma using the QIAamp® ccfDNA/RNA Kit (Qiagen, Cat. No. 55184) according to the manufacturer’s protocol. Briefly, nucleic acids were extracted following proteinase K digestion and column-based purification and eluted in 20 µL of RNase-free water. The concentration and purity of the isolated nucleic acids were assessed using a NanoDrop spectrophotometer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eExosome precipitation and RNA isolation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExosomes were isolated from 0.5–1.0 mL of thawed plasma using the Exodisc device (LabSpinner™, Cat. No. EX-D1001), following the manufacturer’s instructions. Plasma samples were applied to the Exodisc unit and subjected to tangential flow filtration through a series of nano-sized filters. This process enabled selective capture of extracellular vesicles, which were subsequently recovered through gentle elution for downstream analyses. Exosomal RNA was extracted using the miRNeasy Micro Kit (Qiagen, Cat. No. 217084). Exosome suspensions were mixed with 700 µL of QIAzol lysis reagent and processed according to the manufacturer’s protocol. The RNA was eluted in 14 µL of RNase-free water and stored at −80 °C until further analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eExosome tracking analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo analyze exosomes isolated from plasma, extracellular vesicles were purified using the Exodisc device (LabSpinner™, Cat. No. EX-D1001) and characterized by nanoparticle tracking analysis (NTA) using the NanoSight NS300 system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eWestern blot analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProtein concentrations were determined using the BCA Assay Reagent (Cat. No. 23225; Thermo Fisher Scientific). Equivalent amounts of protein from each sample were loaded onto polyacrylamide gels and separated by electrophoresis.The separated proteins were transferred to nitrocellulose membranes (Cat. No. 1704270, Bio-Rad) for 20 minutes. The membranes were then blocked with 5% skim milk dissolved in Tris-buffered saline containing 0.1% Tween-20 (TBST) for 1 hour at room temperature. After washing, the membranes were incubated overnight at 4 °C with specific primary antibodies of interest, diluted in 5% BSA in TBST. Following primary antibody incubation, the membranes were probed with horseradish peroxidase (HRP)-conjugated anti-rabbit IgG antibodies. Exosomal marker ALIX (Recombinant Anti-ALIX antibody, Abcam, ab275377, 1:1,000) was used for 1 hour at room temperature.Protein bands were visualized using ECL SuperSignal West Femto Maximum Sensitivity Substrate (Cat. No. 34095, Thermo Fisher Scientific), and images were captured using the LuminoGraph II system (Cat. No. WSE-6200, ATTO).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003emiRNA analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReverse transcription of extracted miRNAs was performed using the miRCURY LNA™ RT Kit (Qiagen, Cat. No. 339340) according to the manufacturer’s instructions. Briefly, RNA templates were incubated at 42 °C for 1 hour, followed by enzyme inactivation at 95 °C for 5 minutes, and then held at 4 °C to complete cDNA synthesis. Quantitative PCR (qPCR) was conducted using the miRCURY LNA™ SYBR Green PCR Kit (Qiagen, Cat. No. 339347) along with miRNA-specific LNA-enhanced primers. The qPCR cycling conditions consisted of an initial denaturation at 95 °C for 2 minutes, followed by 40 cycles of 95 °C for 10 seconds and 56 °C for 1 minute. A melting curve analysis was subsequently performed at 95 °C for 10 seconds, 60 °C for 5 seconds, and a gradual increase to 95 °C with a 0.5 °C/s ramp rate.\u003cbr\u003e\u0026nbsp;All reactions were performed in technical duplicates using the Bio-Rad CFX384 Connect Real-Time System. The relative expression levels of target miRNAs were normalized to the endogenous control U6, and data were analyzed using the ΔΔCt method.\u003cbr\u003eThe study analyzed liver-associated miRNAs related to HCC, including hsa-miR-122-3p, hsa-miR-122-5p, hsa-miR-1247-3p, hsa-miR-148b, hsa-miR-155, hsa-miR-184, hsa-miR-192, hsa-miR-193b, hsa-miR-195, hsa-miR-199a-3p, hsa-miR-199a-5p, hsa-miR-206, hsa-miR-21-3p, hsa-miR-21-5p, hsa-miR-221, hsa-miR-222-3p, hsa-miR-223, hsa-miR-224, hsa-miR-766, and hsa-miR-93, to evaluate expression changes and their association with early recurrence. All primer sequences of the miRNAs used in this study are provided in \u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBioinformatics analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the functional roles of predicted target genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the DAVID database (\u003cu\u003ehttp://david.ncifcrf.gov\u003c/u\u003e). Enriched terms were classified into biological processes, cellular components, and molecular functions, with a p-value \u0026lt; 0.05 considered significant. Protein–protein interaction (PPI) analysis was performed using the STRING database (\u003cu\u003ehttp://www.string-db.org/\u003c/u\u003e) with a confidence score ≥ 0.4, and the network was visualized using Cytoscape (version 3.10.3). Hub genes were identified and validated through GEPIA (\u003ca href=\"http://gepia.cancer-pku.cn/\"\u003ehttp://gepia.cancer-pku.cn/\u003c/a\u003e) based on TCGA and GTEx data. Kaplan–Meier survival analyses were performed to evaluate the prognostic value of hub genes, with groups stratified by median expression. Log-rank tests were used for comparisons, and hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. A p-value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical and pathological data\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline characteristics and clinicopathological factors were prospectively collected from medical records. Demographic and clinical data included age, sex, body mass index, platelet count, prothrombin time, serum creatinine, total bilirubin, aspartate aminotransferase, alanine aminotransferase, and serum albumin. Pathological data included tumor number, maximum tumor diameter, tumor grade, and the presence of microvascular invasion, portal vein invasion, hepatic vein invasion, hepatic artery invasion, bile duct invasion, capsule invasion, lymphovascular invasion, satellite nodules, background liver cirrhosis, and fatty liver. Recurrence within one year after surgery was defined as early recurrence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll continuous variables are presented as medians with ranges and were compared using the Mann–Whitney U test. Categorical variables are expressed as counts with percentages and were compared using Fisher’s exact test. A total of 20 circulating miRNAs (miR-122-3p, miR-122-5p, miR-1247-3p, miR-148b, miR-155, miR-184, miR-192, miR-193b, miR-195, miR-199a-3p, miR-199a-5p, miR-206, miR-21-3p, miR-21-5p, miR-221, miR-222-3p, miR-223, miR-224, miR-766, and miR-93) were analyzed. Expression levels were compared between the healthy donor group and the HCC group using one-way analysis of variance. Group differences were further evaluated with the Mann–Whitney U test, and differential expression distributions were visualized using heatmaps. A two-sided p-value \u0026lt; 0.05 was considered statistically significant. All statistical analyses were performed using R software (version 4.4.1; R Foundation for Statistical Computing, Vienna, Austria) and Python (version 3.11; Python Software Foundation, Wilmington, DE, USA).\u0026nbsp;\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eDuring the study period, 30 individuals with HCC underwent curative open anatomical liver resection. Their perioperative and pathological outcomes are summarized in \u003cstrong\u003eTable 1\u003c/strong\u003e. Baseline characteristics of 10 healthy living liver donors, included as the normal control group, are presented in \u003cstrong\u003eSupplementary Table 3\u003c/strong\u003e. A flow chart of study inclusion is shown in \u003cstrong\u003eFigure 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEarly recurrence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Of the 30 individuals with hepatocellular carcinoma, six experienced early recurrence within one year after surgery. The median time to recurrence was 157 days (range, 94–352 days). All recurrences were identified as intrahepatic metastases (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHCC-specific circulating microRNA expression\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared with preoperative day 1, four miRNAs in the cell-free RNA fraction showed significant changes on postoperative day 7, namely miR-184, miR-21-3p, miR-224, and miR-766 (p \u0026lt; 0.05). In contrast, seven circulating exosomal miRNAs exhibited significant changes: miR-148b, miR-184, miR-192, miR-206, miR-21-5p, miR-224, and miR-93 (p \u0026lt; 0.05).\u003cbr\u003eThe comparison of circulating cell-free and exosomal microRNA expression between individuals with HCC and healthy donors is summarized in \u003cstrong\u003eSupplementary Table 4\u003c/strong\u003e. A heatmap of differential expression is provided in \u003cstrong\u003eSupplementary Figure 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMicroRNA expression as a biomarker of early recurrence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify biomarkers associated with early recurrence of HCC within one year, 20 circulating miRNAs were analyzed from blood samples collected preoperatively and on postoperative day 7.\u003c/p\u003e\n\u003cp\u003eComparison with healthy donors showed no significantly up- or down-regulated miRNAs in either the cell-free RNA fraction or the exosomal fraction at preoperative day 1. However, by postoperative day 7, significant downregulation of miR-184 and miR-206 was observed in the cell-free RNA fraction (p \u0026lt; 0.05). No significant changes were detected in the exosomal fraction.\u003c/p\u003e\n\u003cp\u003eThe comparison of circulating cell-free and exosomal microRNA expression between recurrent and non-recurrent HCC cases is summarized in \u003cstrong\u003eTable 2\u003c/strong\u003e, and a heatmap of differential expression is shown in \u003cstrong\u003eFigure 2\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNotably, reduced postoperative expression of miR-184 and miR-206 was associated with early recurrence, suggesting their potential as prognostic biomarkers following curative resection for HBV-related HCC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eALIX expression in exosomal plasma protein\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlasma was separated from participant samples, followed by purification of exosomal miRNAs using the ExoDisc platform (\u003cstrong\u003eFigure 3A\u003c/strong\u003e). The presence of the exosome biomarker ALIX was confirmed via western blot analysis. ALIX served as a loading control to compare protein loading amounts across samples. We observed a differential expression pattern: ALIX was absent in samples from healthy donors but expressed in those from individuals with HCC (\u003cstrong\u003eFigure 3B\u003c/strong\u003e). Full-length original membrane of ALIX (96 kDa) detected in human plasma-derived exosomes was showed in\u0026nbsp;\u003cstrong\u003eSupplementary Figure 2.\u0026nbsp;\u003c/strong\u003eNanoparticle tracking analysis (NTA) was also performed to confirm the presence of exosomes by measuring their size and concentration (\u003cstrong\u003eFigure 3C\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eProtein–protein interaction network and hub gene identification\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing Cytoscape (version 3.10.3) and the STRING database, a PPI network of 28 predicted target genes of miR-184 and miR-206 was constructed. The network consisted of 17 nodes and 30 edges, with an average node degree of 3.53 and an average local clustering coefficient of 0.416 (\u003cstrong\u003eFigure 4A\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTopological analysis in Cytoscape identified hub genes based on degree of connectivity. The following 16 hub genes showed the highest degree centrality: CCND1, CCND2, KLF4, NOTCH3, BDNF, MET, CDK4, BCL2, AKT2, IGF1R, MYC, HDAC4, ESR1, KRAS, SMARCB1, and AGO2 (\u003cstrong\u003eFigure 4B\u003c/strong\u003e). These genes, predicted targets of miR-184 and miR-206, are likely to play central roles in the regulatory network associated with early recurrence of HCC.\u003c/p\u003e\n\u003cp\u003eFunctional enrichment and KEGG pathway analyses of these 16 hub genes demonstrated significant involvement in cell cycle regulation, transcriptional control, and multiple cancer-related pathways, including HCC, breast cancer, melanoma, gastric cancer, and miRNAs in cancer. Detailed enrichment terms and associated signaling pathways are summarized in \u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003eTable 5\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eValidation of hub genes using the TCGA database\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eValidation of the 16 hub genes targeted by miR-184 and miR-206 using TCGA and GEPIA databases revealed that high CDK4 expression and low ESR1 expression were significantly associated with poor recurrence-free survival and overall survival in HCC (\u003cstrong\u003eSupplementary Figures 3 and 4)\u003c/strong\u003e.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eEarly recurrence after curative treatment remains a major obstacle to improving long-term outcomes in HCC.\u003csup\u003e9–11\u003c/sup\u003e Many individuals who undergo surgery or liver transplantation experience recurrence within the first year, even when tumors are small and detected early.\u003csup\u003e12\u003c/sup\u003e To more accurately predict this risk, recent studies have explored liquid biopsy techniques using biomarkers such as circulating miRNAs, cell-free DNA, and circulating tumor cells.\u003csup\u003e10,11\u003c/sup\u003e These non-invasive approaches have shown promising potential for identifying individuals with minimal residual disease. For example, changes in circulating miRNA\u0026nbsp;levels\u003csup\u003e13\u003c/sup\u003e, the presence of tumor-specific mutations in plasma\u003csup\u003e14\u003c/sup\u003e, or the persistent detection of circulating tumor cells\u003csup\u003e15\u003c/sup\u003e have all been associated with early recurrence. Liquid biopsy research has gained significant attention because it enables real-time monitoring of tumor dynamics without the need for invasive procedures and may help guide more personalized surveillance and treatment strategies after\u0026nbsp;surgery\u003csup\u003e11\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn this study, we used a liquid biopsy approach to measure circulating miRNAs as predictors of early recurrence following curative resection in individuals with HBV-related HCC. This method is non-invasive, allows for repeated sampling, and enables real-time monitoring of tumor behavior.\u003csup\u003e16\u003c/sup\u003e Circulating miRNAs are stable in blood and have been widely investigated as diagnostic and prognostic biomarkers in HCC.\u003csup\u003e17,18\u003c/sup\u003e However, their clinical utility remains limited due to technical variability and patient heterogeneity.\u003csup\u003e19\u003c/sup\u003e Most previous studies on miRNAs and HCC recurrence were based on tumor tissue samples, which require invasive sampling and are unsuitable for serial monitoring.\u003csup\u003e20\u003c/sup\u003e Although several recent studies have investigated circulating miRNAs, many focused on preoperative levels or employed multi-miRNA panels without evaluating postoperative changes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn our study, we observed distinct postoperative alterations in circulating miRNA profiles specific to HBV-related HCC. Compared with preoperative levels, four miRNAs from the cell-free RNA fraction (miR-184, miR-21-3p, miR-224, and miR-766) and seven miRNAs from the exosomal fraction (miR-148b, miR-184, miR-192, miR-206, miR-21-5p, miR-224, and miR-93) showed significant up- or downregulation by postoperative day 7. These tumor-associated miRNA alterations hold potential not only as biomarkers for diagnosis and recurrence monitoring but also as a foundation for future studies exploring liquid biopsy–based strategies in the postoperative management of HCC.\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eRegarding biomarkers for early recurrence, specific miRNAs such as miR-2122, miR-26a, miR-221, miR-122, and miR-1246 have previously been identified as recurrence-associated markers, primarily in diagnostic or pre-treatment settings.\u003csup\u003e7,23,24\u003c/sup\u003e In our study, we analyzed 20 candidate miRNAs from plasma samples collected both preoperatively and on postoperative day 7 in individuals with early-stage HCC. We found that miR-184 and miR-206 were significantly downregulated in individuals who experienced early recurrence, suggesting their potential as biomarkers of minimal residual disease and recurrence risk. Unlike prior studies that focused on a single time point, our approach emphasized dynamic changes in the early postoperative phase, which may reflect molecular events preceding clinical recurrence. This postoperative blood-based monitoring approach may aid in the early detection of minimal residual disease and inform surveillance strategies for individuals with early-stage HCC. Larger studies are warranted to validate these findings and clarify the roles of miR-184 and miR-206 in recurrence biology.\u003c/p\u003e\n\u003cp\u003eOur bioinformatics analyses identified 16 hub genes—CCND1, CCND2, KLF4, NOTCH3, BDNF, MET, CDK4, BCL2, AKT2, IGF1R, MYC, HDAC4, ESR1, KRAS, SMARCB1, and AGO2—as potential key regulators in HCC. Analysis of The Cancer Genome Atlas (TCGA) data further confirmed that high CDK4 expression and low ESR1 expression were significantly associated with increased risk of early recurrence and reduced overall survival, underscoring their potential as prognostic biomarkers and therapeutic targets. CDK4, a critical regulator of the G1/S cell cycle transition, is frequently overexpressed in HCC and has been associated with tumor aggressiveness, microvascular invasion, and poor survival outcomes.\u003csup\u003e25–29\u003c/sup\u003e In contrast, ESR1, known for its tumor-suppressive function, is often downregulated in HCC due to promoter hypermethylation, with low expression correlating with early recurrence and unfavorable prognosis.\u003csup\u003e30–33\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several notable strengths. First, it was a well-designed prospective investigation focused exclusively on individuals with early-stage HCC, specifically those with a single tumor smaller than 5 cm. Second, to minimize variation in surgical techniques and perioperative factors, only patients who underwent open hepatic resection were included. Third, all participants had underlying chronic HBV infection, eliminating etiologic heterogeneity and resulting in a more homogeneous study population. Finally, the study integrated clinical outcomes, circulating miRNA expression, protein expression, and bioinformatic analysis, providing a more comprehensive understanding of the potential molecular mechanisms associated with early recurrence after curative resection.\u003c/p\u003e\n\u003cp\u003eThis study also has several limitations. First, the sample size was relatively small, which may limit the statistical power and generalizability of the findings. Second, the follow-up duration was insufficient to evaluate long-term outcomes such as late recurrence or overall survival. Third, although postoperative levels of miR-184 and miR-206 were significantly associated with early recurrence, no significant differences in preoperative circulating miRNA levels were observed between the early recurrence and non-recurrence groups, which limits their utility as preoperative predictive markers. Fourth, the study did not assess the relationship between circulating miRNA expression in blood and their corresponding expression levels in tumor tissue, leaving the biological origin and relevance of these circulating biomarkers uncertain.\u003c/p\u003e\n\u003cp\u003eIn conclusion, this prospective study highlights the potential of circulating miR-184 and miR-206 as early predictive biomarkers for postoperative recurrence in individuals with HBV-related HCC characterized by a single tumor smaller than 5 cm. Significantly lower expression of miR-184 and miR-206 was associated with early intrahepatic recurrence, indicating their potential utility for risk stratification and postoperative monitoring. Bioinformatic analysis further identified key hub genes—including CCND1, CCND2, KLF4, NOTCH3, BDNF, MET, CDK4, BCL2, AKT2, IGF1R, MYC, HDAC4, ESR1, KRAS, SMARCB1, and AGO2—of which elevated CDK4 expression and reduced ESR1 expression appeared most strongly linked to early recurrence, suggesting their potential role in postoperative tumor progression.\u003cbr\u003e\u0026nbsp;Future large-scale, multi-institutional studies are needed to validate these findings and explore potential therapeutic applications targeting these molecular pathways.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthorship contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSang-Hoon Kim\u003c/strong\u003e: Conceptualization, Investigation, Data Curation, Visualization, Writing \u0026ndash; Original Draft, Writing \u0026ndash; Review \u0026amp; Editing.\u003cbr\u003e\u003cstrong\u003eRyunjin Lee\u003c/strong\u003e: Investigation, Visualization, Data Curation.\u003cbr\u003e\u003cstrong\u003eEunyoung Tak\u003c/strong\u003e: Conceptualization, Data Curation, Visualization, Project Administration, Funding Acquisition, Writing \u0026ndash; Original Draft, Writing \u0026ndash; Review \u0026amp; Editing.\u003cbr\u003e\u003cstrong\u003eKi-Hun Kim\u003c/strong\u003e: Conceptualization, Supervision, Funding Acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was sponsored by Yuhan (IIT-061). Research funding was provided to support the conduct of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData availability\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; All study procedures, including the collection of informed consent, were conducted in accordance with the ethical standards of the Institutional Review Board of Asan Medical Center and the principles of the 1975 Declaration of Helsinki. The study protocol was reviewed and approved by the Institutional Review Board of Asan Medical Center, Seoul, Korea (IRB No. 2023-0048). Written informed consent was obtained from all participants for the use of anonymized data in this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflict of Interest\u003cbr\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e The authors declare no conflicts of interest related to this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; All participants signed a document of informed consent.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLim Y. 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Identification of Key Genes and Carcinogenic Pathways in Hepatitis B Virus-associated Hepatocellular Carcinoma through Bioinformatics Analysis. \u003cem\u003eAnn Hepatobiliary Pancreat Surg\u003c/em\u003e. 2022;26:58\u0026ndash;68.\u003c/li\u003e\n \u003cli\u003eMeng F, Henson R, Wehbe-Janek H, et al. MicroRNA-21 Regulates Expression of the PTEN Tumor Suppressor Gene in Human Hepatocellular Cancer. \u003cem\u003eGastroenterology\u003c/em\u003e. 2007;133:647\u0026ndash;658.\u003c/li\u003e\n \u003cli\u003eLiao Q, Han P, Huang Y, et al. Potential role of circulating microRNA-21 for hepatocellular carcinoma diagnosis: A meta-analysis. \u003cem\u003ePLoS One\u003c/em\u003e. 2015;10:1\u0026ndash;11.\u003c/li\u003e\n \u003cli\u003eTomimaru Y, Eguchi H, Nagano H, et al. Circulating microRNA-21 as a novel biomarker for hepatocellular carcinoma. \u003cem\u003eJ Hepatol\u003c/em\u003e. 2012;56:167\u0026ndash;175.\u003c/li\u003e\n \u003cli\u003eNiu Z, Shi Z, Wu G, et al. 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HS1BP3, transcriptionally regulated by ESR1, promotes hepatocellular carcinoma progression. \u003cem\u003eBiochem Biophys Res Commun\u003c/em\u003e. 2022;623:111\u0026ndash;119.\u003c/li\u003e\n \u003cli\u003eWang L, Cui M, Cheng D, et al. miR-9-5p facilitates hepatocellular carcinoma cell proliferation, migration and invasion by targeting ESR1. \u003cem\u003eMol Cell Biochem\u003c/em\u003e. 2021;476:575\u0026ndash;583.\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":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9024910/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9024910/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Early recurrence after curative resection remains a major challenge in hepatocellular carcinoma (HCC), particularly in hepatitis B virus (HBV)-related cases. Liquid biopsy using circulating microRNAs (miRNAs) offers a non-invasive approach to identify molecular markers predictive of recurrence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe prospectively enrolled 30 individuals with HBV-related HCC presenting with a single tumor (\u0026lt;5 cm) and no vascular invasion or metastasis. Blood samples were collected preoperatively and on postoperative day 7. Expression of 20 selected miRNAs from circulating cell-free DNA/RNA and exosomes was analyzed. Participants were categorized into early recurrence (within 1 year, n=6) and non-recurrence (n=24) groups. Differentially expressed miRNAs were identified, and target genes of significant miRNAs were retrieved from miRTarBase. Protein–protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape. Enrichment analysis was performed using Gene Ontology and KEGG pathway databases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOn postoperative day 7, expression of miR-184 and miR-206 was significantly lower in the early recurrence group than in the non-recurrence group (p \u0026lt; 0.05). Other miRNAs showed no significant differences. Target gene analysis revealed 16 key hub proteins—CCND1, CCND2, KLF4, NOTCH3, BDNF, MET, CDK4, BCL2, AKT2, IGF1R, MYC, HDAC4, ESR1, KRAS, SMARCB1, and AGO2—enriched in cancer-related pathways and involved in HCC progression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eReduced postoperative expression of miR-184 and miR-206 may predict early recurrence in individuals with HBV-related HCC. Their associated regulatory networks suggest possible mechanisms of recurrence and represent potential biomarkers for postoperative surveillance. Further studies are needed to validate their prognostic value.\u003c/p\u003e","manuscriptTitle":"Circulating miR-184 and miR-206 as Predictive Biomarkers for Early Recurrence in HBV- Related Hepatocellular Carcinoma: A Prospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 07:18:24","doi":"10.21203/rs.3.rs-9024910/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-10T05:39:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-09T04:24:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296961270647786726230626842590539878048","date":"2026-04-09T03:14:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-08T10:51:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66692726156796033813967374909241385546","date":"2026-04-08T10:24:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-08T03:11:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-08T02:02:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-30T09:33:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-28T07:54:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Gastroenterology","date":"2026-03-28T07:48:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1e93f5a1-f8b5-4216-9918-e4499bdbfb49","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T06:38:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 07:18:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9024910","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9024910","identity":"rs-9024910","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}