Serum Long Non-Coding RNA SCARNA10 Serves As A Potential Diagnostic Biomarker For Hepatocellular Carcinoma

Serum Long Non-Coding RNA SCARNA10 Serves As A Potential Diagnostic Biomarker For Hepatocellular Carcinoma | 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 Serum Long Non-Coding RNA SCARNA10 Serves As A Potential Diagnostic Biomarker For Hepatocellular Carcinoma Yawei Han, Wenna Jiang, Yu Wang, Meng Zhao, Yueguo Li, Li Ren This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-757014/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Apr, 2022 Read the published version in BMC Cancer → Version 2 posted 12 You are reading this latest preprint version Show more versions Abstract Background: Circulating long non-coding RNAs (lncRNAs) have been demonstrated to serve as diagnostic or prognosis biomarkers for various disease. We aimed to elucidate the diagnostic efficacy of serum lncRNA SCARNA10 for the hepatocellular carcinoma (HCC). Methods: In this study, a total of 127 patients with HCC, 55 patients with benign liver disease (BLD), and 99 healthy controls (HC) were enrolled in this study. According to different classifications, the levels of serum SCARNA10 were assessed by quantitative real-time polymerase chain reaction (qPCR). The correlations between serum SCARNA10 and clinicopathological charcaterisstics were further analyzed. The receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to estimate the diagnostic capacity of serum SCARNA10 and its combination with AFP for HCC. Results: The results demonstrated that the levels of serum SCARNA10 were significantly higher in HCC patients than in patients with BLD and healthy controls, and significantly increased in HCC patients with hepatitis B or C infection, or with liver cirrhosis. Furthermore, positive correlations were noted between serum SCARNA10 level and some clinicopathological characteristics, including tumor size, differentiation degrees, tumor stage, vascular invasion, tumor metastasis and complications. ROC analysis revealed that SCARNA10 had a significantly predictive value for HCC, the combination of SCARNA10 and AFP gained the higher accuracy. SCARNA10 retained significant diagnosis capabilities for AFP-negative HCC patients. Conclusions: In summary, lncRNA SCARNA10 may serve as a novel and non-invasive biomarker with relatively high sensitivity and specificity for HCC diagnosis. Cancer Biology Oncology hepatocellular carcinoma long non-coding RNA SCARNA10 biomarker Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally with relatively high morbidity and mortality [ 1 , 2 ]. Although great progresses made in HCC therapy in recent years, the prognosis of HCC patients still remains poor due to being diagnosed at an advanced stage and high rate of recurrence [ 1 , 3 ]. Currently, histological examination of the tumor tissue serves as the standard procedure for difinitive diagnosis of HCC, and imaging examinations including ultrasound, computer tomography (CT) and magnetic resonance imaging (MRI) are the common supplement procedures [ 4 ]. However, their application has been limited due to invasiveness, insensitivity to small tumors, and high cost [ 5 ]. For serum biomarkers, alpha fetoprotein (AFP) is one of the most widely used biomarkers for HCC diagnosis clinically. Nevertheless, the sensitivity and specificity of AFP are unsatisfactory, especially for patients with early-stage HCC. In addition, AFP may be elevated in some benign liver diseases, such as chronic hepatitis and cirrhosis [ 6 , 7 ]. Therefore, it is of great value to detect convenient, non-invasive, inexpensive and repeatable serum biomarkers in the HCC diagnosis. Long non-coding RNAs (lncRNAs) are a class of non-coding RNA, which is longer than 200 nucleotides in length [ 8 ]. Accumulating evidence has demonstrated that lncRNAs play important roles in various physiological and pathological processes [ 9 , 10 ]. LncRNAs have been proved to play important roles as oncogenes or tumor suppressor genes in differernt cancer types [ 11 ]. Current researches have found that lncRNA abnormal expression profile has close relationships with HCC developments [ 12 ]. Several circulating lncRNAs have been implied to be promising markers with high accuracies and efficiencies for the diagnosis and prognosis of HCC, for instance, HULC, MALAT1 and UCA1 [ 13 – 17 ]. However, the diagnostic value of many lncRNAs for HCC reported by different researchers remains controversial and needs further investigation. Moreover, the diagnostic efficacy of only a small number of circulating lncRNAs has been confirmed. The majority of circulating lncRNAs involved in HCC still remains largely unclear. Previously, we identified lncRNA Small Cajal body-specific RNA 10 (SCARNA10) is up-regulated in the serum and liver tissue samples from patients with advanced hepatic fibrosis, which promotes liver fibrosis both in vitro and in vivo through inducing HCs apoptosis and HSCs activation [ 18 ]. It has been reported that SCARNA10 is one of the highest expressed in 615 differentially expressed lncRNAs of breast cancer [ 19 ]. SCARNA10 has also been reported to play important potential functions in small-cell lung cancer (SCLC) [ 20 ]. Although the function of SCARNA10 in liver tissues are beginnig to be understood, its roles in serum of HCC patients require further study. Here, we initially found that serum SCARNA10 level is higher in HCC than in healthy controls, SCARNA10 level was correlated with tumor differentiation degrees, size, stage, vascular invasion, lymph node metastasis, distant metastasis and complications. Combined detection of SCARNA10 and AFP was more effective for the diagnosis of HCC. SCARNA10 may serve as a potential diagnostic biomarker for HCC. Methods And Materials Patients and specimens This study analyzed a total of 281 serum samples obtained from 127 patients diagnosed with HCC, 55 patients diagnosed with benign liver disease and 99 healthy controls at Tianjin Medical University Cancer Institute and Hospital (Tianjin, China) between October 2019 and March 2021. Patients with hemorrhagic or thrombotic diseases and those who have taken anticoagulant agents such as warfarin and similar drugs or vitamin K within 6 months of enrollment were excluded. Venous blood were collected from the participants before treatment, centrifuged at 3000 rpm for 20 minutes, transferred the supernatant to EP tube, and quickly forzen to -80 ℃ for later use, avoiding freezing and thawing cycles. Clinicopathological feature data including age, sex, tumor size and number, stage, lymph node and distant metastasis, vascular invasion, differentiation degree and complicatons were collected. RNA extraction and quantitative RT-PCR Total RNA was extracted from equal volume of serum samples with TRIzol LS reagent (Invitrogen, Carlsbad, CA, USA) as described in the manufacturer’s protocol. cDNA was generated using the First-strand cDNA synthesize kit (#1622, Thermo Fisher Scientific, Waltham, MA, USA) in accordance with the manufacturer’s instructions. The synthesized cDNA templates were further amplified by SYBR Green master kit (Takara, Shiga-ken, Japan), and the expression of β-actin was used as the internal control. We calculated the relative expression values by comparing the normalized cycle threshold (Ct). The sequences of primers were as follows: SCARNA10 (forward): 5’-GTTTGGCTAAGCCCAGGGAC-3’, (reverse): 5’-GTTGGTCTGCCCTTACAGTGA-3’; β-actin (forward): 5’-GCCGGGACCTGACTGACTAC-3’, (reverse): 5’-TTCTCCTTAATGTCACGCACGAT-3’. Quantification of serum AFP levels using electrochemiluminescence immunoasssays Serum AFP levels were measured using the Roche Cobas E601 electrochemical immunoluminescence analyzer (Roche Diagnostics, Mannheim, Germany) equipped with Roche dedicated reagents following the instructions provided by the manufacturer. Statistical analysis The Wilcoxon signed-rank test was used to compare two groups, and the Friedman rank sum test was used to compare three or more groups. Spearman’s correlation test was used to determine the relationship between serum SCARNA10 levels and biochemical parameters. The ROC analysis was performed to obtain the area under the curve (AUC), cutoff values, sensitivity and specificity. p -values < 0.05 was considered to indicate a significant difference. All statistial analyses were performed using SPSS 20.0 (IBM, Armonk, NY, USA). Results The expression level of lncRNA SCARNA10 in serum of HCC patients To determine the significance of lncRNA SCARNA10 in HCC, the expression levels of SCARNA10 in serum of 127 HCC patients, 55 benign liver disease (BLD) and 99 healthy controls (HC) were examined by RT-qPCR analysis. The relative serum levels of SCARNA10 in HCC patients were significantly higher than that in patients diagnosed with BLD and HC (both p < 0.05, Fig. 1 ). Simultaneously, we observed that SCARNA10 expression levels were not significantly difference between patients with BLD and HC (Fig. 1 ). The results suggested that SCARNA10 can be used as a potential diagnostic biomarker for HCC. Subgroup Analysis Of Serum Scarna10 Level In Hcc Patients According to different classification methods, we further found that serum SCARNA10 levels in HCC patients with hepatits B virus or hepatitis C virus infection were significantly higher than those without infection controls (both p < 0.05, Figure 2 a), but there was no significant difference in the expression of SCARNA10 between HCC patients infected with HBV and HCV (Fig. 2 a). Moreover, serum SCARNA10 levels in HCC patients with liver cirrhosis were significantly increased ( p < 0.05, Fig. 2 b). Association between clinicopathologic features and SCARNA10 expression levels in HCC To investigate the clinical significance of SCARNA10 expression in HCC, the relationship between serum SCARNA10 levels and clinicopathological features in HCC patients were summarized in Table 1 . We found that SCARNA10 expression was significantly correlated with tumor size and differentiation degrees (both p < 0.01). Moreover, serum SCARNA10 levels was positively correlated with the tumor stage ( p < 0.01). Serum SCARNA10 levels in HCC patients with vascular invasion, lymph node metastasis and distant metastasis were significantly increased (all p < 0.05). Simultaneously, serum SCARNA10 levels in patients experiencing complications were significantly higher than the levels observed in patients without complications ( p < 0.01). However, there was no significant correlation between the SCARNA10 levels and age, sex, or tumor numbers. Table 1 Correlation of serum SCARNA10 levels with clinipathological parameters in HCC Characteristics Number (%) Serum SCARNA10 levels p -value Low levels ≤ 3.25 (n = 65) High levels >3.25 (n = 62) Age (years) ≤ 55 > 55 58 (45.67) 69 (54.33) 27 38 31 31 0.437 Gender Male Female 81 (63.78) 46 (36.22) 41 24 40 22 0.297 Tumor size ≤5cm >5cm 76 (59.84) 51 (40.16) 47 18 29 33 <0.01 * Tumor number Single Multiple 79 (62.20) 48 (37.80) 40 25 39 23 0.495 Differentiation degrees Well Moderate Poor 48 (37.80) 46 (36.22) 33 (25.98) 34 19 12 14 27 21 <0.01 * Tumor stage 1 2 3 4 49 (38.58) 49 (38.58) 19 (14.96) 10 (7.88) 33 23 6 3 16 26 13 7 <0.01 * Vascular invasion Yes No 58 (45.67) 69 (54.33) 28 37 30 32 <0.01 * Lymph node metastasis Yes No 45 (35.43) 82 (64.57) 19 46 26 36 <0.01 * Distant metastasis Yes No 33 (25.98) 94 (74.02) 18 47 15 47 0.038 * Complications Yes No 47 (37.01) 80 (62.99) 20 45 27 35 <0.01 * The diagnostic value of SCARNA10 in HCC patients To further explore the utility of SCARNA10 as a promising diagnostic molecular marker for HCC, ROC curves of SCARNA10 and AFP were plotted in participants. As shown in Fig. 3 a, b and Table 2 , both markers showed remarkable diagnostic performance in distinguishing HCC from HC, and both markers showed remarkable diagnostic performance when it came to distinguishing HCC from BLD. The AUCs of the combined markers were significantly greater than SCARNA10 or AFP alone in all groups. The sensitivity of the diagnosis of the two combined markers were also increased, respectively. Table 2 Performances of SCARNA10 and AFP for the diagnosis of HCC patients Sensitivity Specificity AUC HCC vs HC SCARNA10 0.66 0.81 0.82 AFP 0.69 0.91 0.83 SCARNA10+AFP 0.88 0.80 0.92 HCC vs BLD SCARNA10 0.66 0.84 0.80 AFP 0.65 0.93 0.82 SCARNA10+AFP 0.89 0.82 0.91 Efficacy of SCARNA10 in the diagnosis of AFP-negative HCC patients To further estimate the complementary role of SCARNA10 for AFP in the diagnosis of HCC, the diagnostic value of SCARNA10 were assessed in HCC patients that were missed by AFP, based on the cutoff values obtained in clinical diagnosis. As shown in Fig. 4 and Table 3 , SCARNA10 showed a significant ability in distinguishing AFP-negative HCC from healthy controls with higher sensitivity and specificity. Table 3 Performance of SCARNA10 for the diagnosis of AFP-negative HCC patients Sensitivity Specificity AUC HCC vs HC 0.73 0.79 0.80 HCC vs BLD 0.82 0.43 0.59 Discussion Currently, the identification of novel potential serum biomarkers for the detection of HCC remains a vital goal, particularly for the diagnosis of early-stage HCC. Nevertheless, only a few biomarker candidates have been translated to clinical applications due to the limited study cohorts or diagnostic performance. For instance, so far, there is still only AFP as the most commonly used biomarker for HCC patients, despite its unsatisfactory sensitivity and specificity [ 7 ]. Several HCC-related lncRNAs can be present in the body fluid, as is the case lncRNAs UCA1, WRAP53, PVT1, ATB and uc002mbe.2 [ 17 , 21 – 23 ]. The representative lncRNA HULC is detectable in blood sample and can be easily quantified by conventional qPCR [ 24 ]. These findings have suggested a non-invasive approach for HCC diagnosis through circulating lncRNA measurement. Our study is the first to examine the potential diagnostic utility of serum SCARNA10 in HCC patients. As previously researches, a large number of lncRNAs are aberrantly expressed in HCC compared with normal liver tissue, which is useful to distinguish HCC patients from healthy cohorts [ 25 ]. However, some of those lncRNAs are also shown abbrrant expression patterns in other cancer types or non-cancerous situations such as cirrhosis or liver injury, resulting in reduced reliability. Thus, lncRNAs combined with other molecules, especially known HCC biomarker AFP, is more likely to be a desirable HCC diagnosis method instead of evaluating lncRNAs alone. For example, the combination of two lncRNAs UCA1 and WRAP53 with AFP achieves sensitivity up to 100% [ 21 ]. Similarly, the combination of another two lncRNAs PVT1 and uc002mbe.2 with AFP have been also shown to perform much better than AFP alone in HCC diagnosis [ 22 ]. Besides AFP, other molecules including miRNAs or mRNAs can also predict HCC in combination with lncRNAs [ 26 ]. In this study, for the first time, we found that the levels of SCARNA10 in HCC patients were significantly higher than that in BLD patients and healthy controls. Moreover, the SCARNA10 levels were not notable divergence between BLD patients and HC. These demonstrated that serum SCARNA10 levels can clearly distinguish benign and malignant liver tumors. In addition, the ROC analysis suggested that the AUCs of the combined SCARNA10 and AFP were greater than themself alone in distinguishing HCC from BLD and HCC from HC. The sensitivity of the two combined markers were also increased. Finally, in AFP-negative HCC, SCARNA10 also showed a significant ability with higher sensitivity and specificity. All these findings indicated that SCARNA10 can serve as a potential diagnostic biomarker for HCC. HBV infection is the major risk factor for HCC development. Worldwide, >50% of HCC cases are associated with HBV infection [ 2 , 27 ]. Several lines of evidence have supported the direct involvement of HBV in driving hepatocarcinogenesis. For example, the HBV genome can integrate into the human genome, contributing to genomic instability and generation of oncogenic chimeric transcripts [ 28 ]. HBV protein X (HBx) is highly carcinogenic, and 90% of HBx transgenic mice develop HCC [ 29 ]. HCV infection is a major cause of cirrhosis and consequently HCC [ 30 ]. The molecular mechanisms underlying HCV-induced HCC development might differ from those associated with HBV infection. HCV could promote HCC formation by upregulating host miRNAs and deregulating cellular signalling pathways [ 31 , 32 ]. In this study, we found that serum SCARNA10 levels in HCC patients with HBV or HCV infection were significantly higher than those without infection controls, and in HCC patients with liver cirrhosis were also increased. These results demonstrated that SCARNA10 may play a role in HCC by regulating a common pathway in HBV or HCV. All these provide ideas for further research on the function and mechanism of SCARNA10 in HCC in the future. In conclusion, we found the serum SCARNA10 level was increased in HCC patients, and associated with some clinicopathologic features, including tumor size, differentiation degrees, stage, vascular invasion, metastasis and complications. The combined detection of SCARNA10 and AFP significantly imporved the diagnostic sensitivity of HCC. However, the roles of SCARNA10 in HCC need to be elucidated in more detail. In future study, we will further research the definite function and mechnism of SCARNA10 in liver carcinogenesis. Abbreviations lncRNAs: long non-coding RNAs; HCC: hepatocellular carcinoma; BLD: benign liver disease; HC: healthy controls; qPCR: quantitative real-time polymerase chain reaction; ROC: receiver operating characteristic; AUC: area under curve; CT: computer tomography; MRI: magnetic resonance imaging; AFP: alpha fetoprotein; SCARNA10: Small Cajal body-specific RNA 10. Declarations Ethics approval and consent to participate The study has been approved by Institutional Ethics Committee of Tianjin Medical University Cancer Institute and Hospital (No. Ek2020192). The study methodologies were conformed to the standards set by the Declaration of Helsinki. All subjects were over 18 years of age and voluntarily signed informed consent forms. Consent for publication Not applicable. Availability of data and materials The datasets used during the current study are available from the corresponding author on reasonable request. Competing interests The authors have declared that no conflicting interest exists. Funding This work was supported by the Scientific Research Project of Tianjin Education Commission (No. 2020KJ129). Authors’ contributions Y.H, L.R and Y.L conceived and designed the studies. Y.H and W.J performed the majority of the experiments. Y.W collected the clinical samples. Y.H and M.Z analyzed the data. Y.H, Y.L and L.R wrote the manuscript. All authors critically reviewed and approved the final manuscript. Acknowledgments Not applicable. Author details 1 Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin 300060, China. 2 College of Inspection, Tianjin Medical University, Tianjin, China. References Yang JD, Hainaut P, Gores GJ, Amadou A, Plymoth A, Roberts LR. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nat Rev Gastroenterol Hepatol. 2019;16(10):589–604. McGlynn KA, Petrick JL, El-Serag HB. Epidemiology of Hepatocellular Carcinoma. Hepatology. 2021;73 Suppl 1:4–13. Llovet JM, Montal R, Sia D, Finn RS. Molecular therapies and precision medicine for hepatocellular carcinoma. Nat Rev Clin Oncol. 2018;15(10):599–616. Roberts LR, Sirlin CB, Zaiem F, Almasri J, Prokop LJ, Heimbach JK, et al. Imaging for the diagnosis of hepatocellular carcinoma: A systematic review and meta-analysis. Hepatology. 2018;67(1):401–421. Kulik L, El-Serag HB. Epidemiology and Management of Hepatocellular Carcinoma. Gastroenterology. 2019;156(2):477-491 e471. Tzartzeva K, Obi J, Rich NE, Parikh ND, Marrero JA, Yopp A, et al. Surveillance Imaging and Alpha Fetoprotein for Early Detection of Hepatocellular Carcinoma in Patients With Cirrhosis: A Meta-analysis. Gastroenterology. 2018;154(6):1706-1718 e1701. Luo P, Yin P, Hua R, Tan Y, Li Z, Qiu G, et al. A Large-scale, multicenter serum metabolite biomarker identification study for the early detection of hepatocellular carcinoma. Hepatology. 2018;67(2):662–675. Goodall GJ, Wickramasinghe VO. RNA in cancer. Nat Rev Cancer. 2021;21(1):22–36. Kopp F, Mendell JT. Functional Classification and Experimental Dissection of Long Noncoding RNAs. Cell. 2018;172(3):393–407. Gal Z, Gezsi A, Semsei AF, Nagy A, Sultesz M, Csoma Z, et al. Investigation of circulating lncRNAs as potential biomarkers in chronic respiratory diseases. J Transl Med. 2020;18(1):422. Statello L, Guo CJ, Chen LL, Huarte M. Gene regulation by long non-coding RNAs and its biological functions. Nat Rev Mol Cell Biol. 2021;22(2):96–118. Wong CM, Tsang FH, Ng IO. Non-coding RNAs in hepatocellular carcinoma: molecular functions and pathological implications. Nat Rev Gastroenterol Hepatol. 2018;15(3):137–151. Huang J, Zheng Y, Xiao X, Liu C, Lin J, Zheng S, et al. A Circulating Long Noncoding RNA Panel Serves as a Diagnostic Marker for Hepatocellular Carcinoma. Dis Markers. 2020;2020:5417598. Zhang H, Liao Z, Liu F, Su C, Zhu H, Li Y, et al. Long noncoding RNA HULC promotes hepatocellular carcinoma progression. Aging (Albany NY). 2019;11(20):9111–9127. Yao Z, Jia C, Tai Y, Liang H, Zhong Z, Xiong Z, et al. Serum exosomal long noncoding RNAs lnc-FAM72D-3 and lnc-EPC1-4 as diagnostic biomarkers for hepatocellular carcinoma. Aging (Albany NY). 2020;12(12):11843–11863. Sonohara F, Inokawa Y, Hayashi M, Yamada S, Sugimoto H, Fujii T, et al. Prognostic Value of Long Non-Coding RNA HULC and MALAT1 Following the Curative Resection of Hepatocellular Carcinoma. Sci Rep. 2017;7(1):16142. Zheng ZK, Pang C, Yang Y, Duan Q, Zhang J, Liu WC. Serum long noncoding RNA urothelial carcinoma-associated 1: A novel biomarker for diagnosis and prognosis of hepatocellular carcinoma. J Int Med Res. 2018;46(1):348–356. Zhang K, Han Y, Hu Z, Zhang Z, Shao S, Yao Q, et al. SCARNA10, a nuclear-retained long non-coding RNA, promotes liver fibrosis and serves as a potential biomarker. Theranostics. 2019;9(12):3622–3638. Jia Y, Shi L, Yun F, Liu X, Chen Y, Wang M, et al. Transcriptome sequencing profiles reveal lncRNAs may involve in breast cancer (ER/PR positive type) by interaction with RAS associated genes. Pathol Res Pract. 2019;215(6):152405. Lei Y, Shi Y, Duan J, Liu Y, Lv G, Shi R, et al. Identification of alternative splicing and lncRNA genes in pathogenesis of small cell lung cancer based on their RNA sequencing. Adv Clin Exp Med. 2019;28(8):1043–1050. Kamel MM, Matboli M, Sallam M, Montasser IF, Saad AS, El-Tawdi AHF. Investigation of long noncoding RNAs expression profile as potential serum biomarkers in patients with hepatocellular carcinoma. Transl Res. 2016;168:134–145. Yu J, Han J, Zhang J, Li G, Liu H, Cui X, et al. The long noncoding RNAs PVT1 and uc002mbe.2 in sera provide a new supplementary method for hepatocellular carcinoma diagnosis. Medicine (Baltimore). 2016;95(31):e4436. Yuan JH, Yang F, Wang F, Ma JZ, Guo YJ, Tao QF, et al. A long noncoding RNA activated by TGF-beta promotes the invasion-metastasis cascade in hepatocellular carcinoma. Cancer Cell. 2014;25(5):666–681. Panzitt K, Tschernatsch MM, Guelly C, Moustafa T, Stradner M, Strohmaier HM, et al. Characterization of HULC, a novel gene with striking up-regulation in hepatocellular carcinoma, as noncoding RNA. Gastroenterology. 2007;132(1):330–342. Qu L, Cai X, Xu J, Wei X, Qu X, Sun L, et al. Six long noncoding RNAs as potentially biomarkers involved in competitive endogenous RNA of hepatocellular carcinoma. Clin Exp Med. 2020;20(3):437–447. Klingenberg M, Matsuda A, Diederichs S, Patel T. Non-coding RNA in hepatocellular carcinoma: Mechanisms, biomarkers and therapeutic targets. J Hepatol. 2017;67(3):603–618. Parkin DM. The global health burden of infection-associated cancers in the year 2002. Int J Cancer. 2006;118(12):3030–3044. Gao Q, Zhu H, Dong L, Shi W, Chen R, Song Z, et al. Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma. Cell. 2019;179(2):561-577 e522. Xu QG, Yuan SX, Tao QF, Yu J, Cai J, Yang Y, et al. A novel HBx genotype serves as a preoperative predictor and fails to activate the JAK1/STATs pathway in hepatocellular carcinoma. J Hepatol. 2019;70(5):904–917. Hamdane N, Juhling F, Crouchet E, El Saghire H, Thumann C, Oudot MA, et al. HCV-Induced Epigenetic Changes Associated With Liver Cancer Risk Persist After Sustained Virologic Response. Gastroenterology. 2019;156(8):2313-2329 e2317. Lupberger J, Croonenborghs T, Roca Suarez AA, Van Renne N, Juhling F, Oudot MA, et al. Combined Analysis of Metabolomes, Proteomes, and Transcriptomes of Hepatitis C Virus-Infected Cells and Liver to Identify Pathways Associated With Disease Development. Gastroenterology. 2019;157(2):537–551 e539. Van Renne N, Roca Suarez AA, Duong FHT, Gondeau C, Calabrese D, Fontaine N, et al. miR-135a-5p-mediated downregulation of protein tyrosine phosphatase receptor delta is a candidate driver of HCV-associated hepatocarcinogenesis. Gut. 2018;67(5):953–962. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 20 Apr, 2022 Read the published version in BMC Cancer → Version 2 posted Editorial decision: Major revision 31 Jan, 2022 Reviewers agreed at journal 05 Jan, 2022 Reviewers agreed at journal 14 Dec, 2021 Reviews received at journal 09 Dec, 2021 Reviews received at journal 07 Dec, 2021 Reviewers agreed at journal 07 Dec, 2021 Reviewers agreed at journal 28 Nov, 2021 Reviewers invited by journal 24 Oct, 2021 Editor assigned by journal 18 Oct, 2021 Editor invited by journal 01 Oct, 2021 Submission checks completed at journal 01 Oct, 2021 First submitted to journal 21 Sep, 2021 You are reading this latest preprint version Show more versions 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-757014","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[{"code":1,"date":"2021-08-03 19:38:35","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":56751041,"identity":"3edb7d98-fda4-4c40-bb14-1a568a6e406a","order_by":0,"name":"Yawei Han","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yawei","middleName":"","lastName":"Han","suffix":""},{"id":56751042,"identity":"8936d2aa-0be3-4376-ba98-9d5c39dea72d","order_by":1,"name":"Wenna Jiang","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wenna","middleName":"","lastName":"Jiang","suffix":""},{"id":56751043,"identity":"9b079a01-071e-4000-a810-26118b46f41e","order_by":2,"name":"Yu Wang","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Wang","suffix":""},{"id":56751044,"identity":"809536a3-f9a6-407d-be37-da51ea76d592","order_by":3,"name":"Meng Zhao","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Zhao","suffix":""},{"id":56751045,"identity":"9111c057-683a-42a7-b552-30f92322fe8d","order_by":4,"name":"Yueguo Li","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yueguo","middleName":"","lastName":"Li","suffix":""},{"id":56751046,"identity":"816a0a0e-5fbb-4dcf-9700-dab36ab44517","order_by":5,"name":"Li Ren","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqElEQVRIiWNgGAWjYBACPmYQWQHhSBClhQ2s5YwBKVpABGMbSVrYeR8+Lpz3J9rgAPPB2zwMdnlEOIzd2HjmNoPcDQfYkq15GJKLidDCxibNC9bCYybNw3AgsYEILey/eeeAtPB/I1oLGzNvA9gWNqK1MEvzHDPOnXmYzdhyjkEyYS38/McYP/PUyOX2HW9+eONNhR1hLQgAjlMD4tWPglEwCkbBKMADAHbcLlCDNY4vAAAAAElFTkSuQmCC","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Ren","suffix":""}],"badges":[],"createdAt":"2021-07-28 00:59:18","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-757014/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-757014/v2","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-022-09530-3","type":"published","date":"2022-04-20T13:52:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":14641944,"identity":"d06d4df4-2956-4f86-bbd8-51ca7f7d4211","added_by":"auto","created_at":"2021-10-18 21:51:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":59609,"visible":true,"origin":"","legend":"Serum SCARNA10 levels in participants. The relative levels of SCARNA10 in patients with HCC, benign liver diseases (BLD) and healthy controls (HC) were performed by qPCR. Upper and lower limits of the box plots and the line inside the boxes indicate the 75th and 25th percentiles and the median, respectively. *p\u003c0.05.","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-757014/v2/b9a246e063498d9c0c913d10.png"},{"id":14641947,"identity":"e1981d5b-499f-424d-bb30-d4ca37d47883","added_by":"auto","created_at":"2021-10-18 21:51:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":80652,"visible":true,"origin":"","legend":"Serum SCARNA10 levels in patients with HCC. (A) Serum SCARNA10 levels in HCC patients with hepatitis B virus (HBV) infection, hepatitis C virus (HCV) infection, or hepatitis with neither (Ctrl). (B) Serum SCARNA10 levels in HCC patients with chromic hepatitis or liver cirrhosis were performed by qPCR. Upper and lower limits of the box plots and the line inside the boxes indicate the 75th and 25th percentiles and the median, respectively. *p\u003c0.05.","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-757014/v2/cb57290c137f9bcf974af1c9.png"},{"id":14641945,"identity":"d1566e36-6e98-4cc5-9472-9f1032012204","added_by":"auto","created_at":"2021-10-18 21:51:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":190763,"visible":true,"origin":"","legend":"SCARNA10 and AFP complementation in the diagnosis of HCC. ROC of SCARNA10, AFP, SCARNA10 + AFP to distinguish HCC from HC (A), and BLD (B).","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-757014/v2/d2b8dba813fd66706acdaa5d.png"},{"id":14641976,"identity":"93b6d7b7-2822-4c9e-a7c3-3fa42e6b7f18","added_by":"auto","created_at":"2021-10-18 21:54:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":147902,"visible":true,"origin":"","legend":"Performance of SCARNA10 in the diagnosis of AFP-negative HCC patients. ROC of SCARNA10 to distinguish HCC AFP-negative from HC (A), and BLD (B), respectively.","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-757014/v2/baa0809e06df727e1e13b785.png"},{"id":20604126,"identity":"2b16886b-4b14-4ded-b250-aedda1160f35","added_by":"auto","created_at":"2022-04-21 13:52:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":816346,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-757014/v2/fca74fdd-0283-41f0-b38c-cc0844fcbd34.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eSerum Long Non-Coding RNA SCARNA10 Serves As A Potential Diagnostic Biomarker For Hepatocellular Carcinoma\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHepatocellular carcinoma (HCC) is one of the most common malignant tumors globally with relatively high morbidity and mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although great progresses made in HCC therapy in recent years, the prognosis of HCC patients still remains poor due to being diagnosed at an advanced stage and high rate of recurrence [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Currently, histological examination of the tumor tissue serves as the standard procedure for difinitive diagnosis of HCC, and imaging examinations including ultrasound, computer tomography (CT) and magnetic resonance imaging (MRI) are the common supplement procedures [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, their application has been limited due to invasiveness, insensitivity to small tumors, and high cost [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. For serum biomarkers, alpha fetoprotein (AFP) is one of the most widely used biomarkers for HCC diagnosis clinically. Nevertheless, the sensitivity and specificity of AFP are unsatisfactory, especially for patients with early-stage HCC. In addition, AFP may be elevated in some benign liver diseases, such as chronic hepatitis and cirrhosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, it is of great value to detect convenient, non-invasive, inexpensive and repeatable serum biomarkers in the HCC diagnosis.\u003c/p\u003e \u003cp\u003eLong non-coding RNAs (lncRNAs) are a class of non-coding RNA, which is longer than 200 nucleotides in length [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Accumulating evidence has demonstrated that lncRNAs play important roles in various physiological and pathological processes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. LncRNAs have been proved to play important roles as oncogenes or tumor suppressor genes in differernt cancer types [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Current researches have found that lncRNA abnormal expression profile has close relationships with HCC developments [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Several circulating lncRNAs have been implied to be promising markers with high accuracies and efficiencies for the diagnosis and prognosis of HCC, for instance, HULC, MALAT1 and UCA1 [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, the diagnostic value of many lncRNAs for HCC reported by different researchers remains controversial and needs further investigation. Moreover, the diagnostic efficacy of only a small number of circulating lncRNAs has been confirmed. The majority of circulating lncRNAs involved in HCC still remains largely unclear.\u003c/p\u003e \u003cp\u003ePreviously, we identified lncRNA Small Cajal body-specific RNA 10 (SCARNA10) is up-regulated in the serum and liver tissue samples from patients with advanced hepatic fibrosis, which promotes liver fibrosis both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e through inducing HCs apoptosis and HSCs activation [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. It has been reported that SCARNA10 is one of the highest expressed in 615 differentially expressed lncRNAs of breast cancer [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. SCARNA10 has also been reported to play important potential functions in small-cell lung cancer (SCLC) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Although the function of SCARNA10 in liver tissues are beginnig to be understood, its roles in serum of HCC patients require further study.\u003c/p\u003e \u003cp\u003eHere, we initially found that serum SCARNA10 level is higher in HCC than in healthy controls, SCARNA10 level was correlated with tumor differentiation degrees, size, stage, vascular invasion, lymph node metastasis, distant metastasis and complications. Combined detection of SCARNA10 and AFP was more effective for the diagnosis of HCC. SCARNA10 may serve as a potential diagnostic biomarker for HCC.\u003c/p\u003e"},{"header":"Methods And Materials","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003ePatients and specimens\u003c/h2\u003e\n \u003cp\u003eThis study analyzed a total of 281 serum samples obtained from 127 patients diagnosed with HCC, 55 patients diagnosed with benign liver disease and 99 healthy controls at Tianjin Medical University Cancer Institute and Hospital (Tianjin, China) between October 2019 and March 2021. Patients with hemorrhagic or thrombotic diseases and those who have taken anticoagulant agents such as warfarin and similar drugs or vitamin K within 6 months of enrollment were excluded. Venous blood were collected from the participants before treatment, centrifuged at 3000 rpm for 20 minutes, transferred the supernatant to EP tube, and quickly forzen to -80 ℃ for later use, avoiding freezing and thawing cycles. Clinicopathological feature data including age, sex, tumor size and number, stage, lymph node and distant metastasis, vascular invasion, differentiation degree and complicatons were collected.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch2\u003eRNA extraction and quantitative RT-PCR\u003c/h2\u003e\n\u003cp\u003eTotal RNA was extracted from equal volume of serum samples with TRIzol LS reagent (Invitrogen, Carlsbad, CA, USA) as described in the manufacturer\u0026rsquo;s protocol. cDNA was generated using the First-strand cDNA synthesize kit (#1622, Thermo Fisher Scientific, Waltham, MA, USA) in accordance with the manufacturer\u0026rsquo;s instructions. The synthesized cDNA templates were further amplified by SYBR Green master kit (Takara, Shiga-ken, Japan), and the expression of \u0026beta;-actin was used as the internal control. We calculated the relative expression values by comparing the normalized cycle threshold (Ct). The sequences of primers were as follows: SCARNA10 (forward): 5\u0026rsquo;-GTTTGGCTAAGCCCAGGGAC-3\u0026rsquo;, (reverse): 5\u0026rsquo;-GTTGGTCTGCCCTTACAGTGA-3\u0026rsquo;; \u0026beta;-actin (forward): 5\u0026rsquo;-GCCGGGACCTGACTGACTAC-3\u0026rsquo;, (reverse): 5\u0026rsquo;-TTCTCCTTAATGTCACGCACGAT-3\u0026rsquo;.\u003c/p\u003e\n\u003ch2\u003eQuantification of serum AFP levels using electrochemiluminescence immunoasssays\u003c/h2\u003e\n\u003cp\u003eSerum AFP levels were measured using the Roche Cobas E601 electrochemical immunoluminescence analyzer (Roche Diagnostics, Mannheim, Germany) equipped with Roche dedicated reagents following the instructions provided by the manufacturer.\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eThe Wilcoxon signed-rank test was used to compare two groups, and the Friedman rank sum test was used to compare three or more groups. Spearman\u0026rsquo;s correlation test was used to determine the relationship between serum SCARNA10 levels and biochemical parameters. The ROC analysis was performed to obtain the area under the curve (AUC), cutoff values, sensitivity and specificity. \u003cem\u003ep\u003c/em\u003e-values \u0026lt; 0.05 was considered to indicate a significant difference. All statistial analyses were performed using SPSS 20.0 (IBM, Armonk, NY, USA).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eThe expression level of lncRNA SCARNA10 in serum of HCC patients\u003c/h2\u003e\n \u003cp\u003eTo determine the significance of lncRNA SCARNA10 in HCC, the expression levels of SCARNA10 in serum of 127 HCC patients, 55 benign liver disease (BLD) and 99 healthy controls (HC) were examined by RT-qPCR analysis. The relative serum levels of SCARNA10 in HCC patients were significantly higher than that in patients diagnosed with BLD and HC (both \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Simultaneously, we observed that SCARNA10 expression levels were not significantly difference between patients with BLD and HC (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The results suggested that SCARNA10 can be used as a potential diagnostic biomarker for HCC.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch2\u003eSubgroup Analysis Of Serum Scarna10 Level In Hcc Patients\u003c/h2\u003e\n\u003cp\u003eAccording to different classification methods, we further found that serum SCARNA10 levels in HCC patients with hepatits B virus or hepatitis C virus infection were significantly higher than those without infection controls (both \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea), but there was no significant difference in the expression of SCARNA10 between HCC patients infected with HBV and HCV (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea). Moreover, serum SCARNA10 levels in HCC patients with liver cirrhosis were significantly increased (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation between clinicopathologic features and SCARNA10 expression levels in HCC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the clinical significance of SCARNA10 expression in HCC, the relationship between serum SCARNA10 levels and clinicopathological features in HCC patients were summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. We found that SCARNA10 expression was significantly correlated with tumor size and differentiation degrees (both \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). Moreover, serum SCARNA10 levels was positively correlated with the tumor stage (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). Serum SCARNA10 levels in HCC patients with vascular invasion, lymph node metastasis and distant metastasis were significantly increased (all \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Simultaneously, serum SCARNA10 levels in patients experiencing complications were significantly higher than the levels observed in patients without complications (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). However, there was no significant correlation between the SCARNA10 levels and age, sex, or tumor numbers.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelation of serum SCARNA10 levels with clinipathological parameters in HCC\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSerum SCARNA10 levels\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow levels\u003c/p\u003e\n \u003cp\u003e\u0026le; 3.25\u003c/p\u003e\n \u003cp\u003e(n = 65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh levels\u003c/p\u003e\n \u003cp\u003e\u0026gt;3.25\u003c/p\u003e\n \u003cp\u003e(n = 62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le; 55\u003c/p\u003e\n \u003cp\u003e\u0026gt; 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (45.67)\u003c/p\u003e\n \u003cp\u003e69 (54.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.437\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81 (63.78)\u003c/p\u003e\n \u003cp\u003e46 (36.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;5cm\u003c/p\u003e\n \u003cp\u003e\u0026gt;5cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (59.84)\u003c/p\u003e\n \u003cp\u003e51 (40.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003cp\u003eMultiple\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79 (62.20)\u003c/p\u003e\n \u003cp\u003e48 (37.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.495\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDifferentiation degrees\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWell\u003c/p\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (37.80)\u003c/p\u003e\n \u003cp\u003e46 (36.22)\u003c/p\u003e\n \u003cp\u003e33 (25.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (38.58)\u003c/p\u003e\n \u003cp\u003e49 (38.58)\u003c/p\u003e\n \u003cp\u003e19 (14.96)\u003c/p\u003e\n \u003cp\u003e10 (7.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (45.67)\u003c/p\u003e\n \u003cp\u003e69 (54.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymph node metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (35.43)\u003c/p\u003e\n \u003cp\u003e82 (64.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDistant metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (25.98)\u003c/p\u003e\n \u003cp\u003e94 (74.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.038\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComplications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (37.01)\u003c/p\u003e\n \u003cp\u003e80 (62.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eThe diagnostic value of SCARNA10 in HCC patients\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eTo further explore the utility of SCARNA10 as a promising diagnostic molecular marker for HCC, ROC curves of SCARNA10 and AFP were plotted in participants. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea, b and Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, both markers showed remarkable diagnostic performance in distinguishing HCC from HC, and both markers showed remarkable diagnostic performance when it came to distinguishing HCC from BLD. The AUCs of the combined markers were significantly greater than SCARNA10 or AFP alone in all groups. The sensitivity of the diagnosis of the two combined markers were also increased, respectively.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePerformances of SCARNA10 and AFP for the diagnosis of HCC patients\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHCC vs HC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCARNA10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCARNA10+AFP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHCC vs BLD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCARNA10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCARNA10+AFP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eEfficacy of SCARNA10 in the diagnosis of AFP-negative HCC patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further estimate the complementary role of SCARNA10 for AFP in the diagnosis of HCC, the diagnostic value of SCARNA10 were assessed in HCC patients that were missed by AFP, based on the cutoff values obtained in clinical diagnosis. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, SCARNA10 showed a significant ability in distinguishing AFP-negative HCC from healthy controls with higher sensitivity and specificity.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePerformance of SCARNA10 for the diagnosis of AFP-negative HCC patients\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHCC vs HC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHCC vs BLD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCurrently, the identification of novel potential serum biomarkers for the detection of HCC remains a vital goal, particularly for the diagnosis of early-stage HCC. Nevertheless, only a few biomarker candidates have been translated to clinical applications due to the limited study cohorts or diagnostic performance. For instance, so far, there is still only AFP as the most commonly used biomarker for HCC patients, despite its unsatisfactory sensitivity and specificity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Several HCC-related lncRNAs can be present in the body fluid, as is the case lncRNAs UCA1, WRAP53, PVT1, ATB and uc002mbe.2 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The representative lncRNA HULC is detectable in blood sample and can be easily quantified by conventional qPCR [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These findings have suggested a non-invasive approach for HCC diagnosis through circulating lncRNA measurement. Our study is the first to examine the potential diagnostic utility of serum SCARNA10 in HCC patients.\u003c/p\u003e \u003cp\u003eAs previously researches, a large number of lncRNAs are aberrantly expressed in HCC compared with normal liver tissue, which is useful to distinguish HCC patients from healthy cohorts [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, some of those lncRNAs are also shown abbrrant expression patterns in other cancer types or non-cancerous situations such as cirrhosis or liver injury, resulting in reduced reliability. Thus, lncRNAs combined with other molecules, especially known HCC biomarker AFP, is more likely to be a desirable HCC diagnosis method instead of evaluating lncRNAs alone. For example, the combination of two lncRNAs UCA1 and WRAP53 with AFP achieves sensitivity up to 100% [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Similarly, the combination of another two lncRNAs PVT1 and uc002mbe.2 with AFP have been also shown to perform much better than AFP alone in HCC diagnosis [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Besides AFP, other molecules including miRNAs or mRNAs can also predict HCC in combination with lncRNAs [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this study, for the first time, we found that the levels of SCARNA10 in HCC patients were significantly higher than that in BLD patients and healthy controls. Moreover, the SCARNA10 levels were not notable divergence between BLD patients and HC. These demonstrated that serum SCARNA10 levels can clearly distinguish benign and malignant liver tumors. In addition, the ROC analysis suggested that the AUCs of the combined SCARNA10 and AFP were greater than themself alone in distinguishing HCC from BLD and HCC from HC. The sensitivity of the two combined markers were also increased. Finally, in AFP-negative HCC, SCARNA10 also showed a significant ability with higher sensitivity and specificity. All these findings indicated that SCARNA10 can serve as a potential diagnostic biomarker for HCC.\u003c/p\u003e \u003cp\u003eHBV infection is the major risk factor for HCC development. Worldwide, \u0026gt;50% of HCC cases are associated with HBV infection [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Several lines of evidence have supported the direct involvement of HBV in driving hepatocarcinogenesis. For example, the HBV genome can integrate into the human genome, contributing to genomic instability and generation of oncogenic chimeric transcripts [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. HBV protein X (HBx) is highly carcinogenic, and 90% of HBx transgenic mice develop HCC [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. HCV infection is a major cause of cirrhosis and consequently HCC [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The molecular mechanisms underlying HCV-induced HCC development might differ from those associated with HBV infection. HCV could promote HCC formation by upregulating host miRNAs and deregulating cellular signalling pathways [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In this study, we found that serum SCARNA10 levels in HCC patients with HBV or HCV infection were significantly higher than those without infection controls, and in HCC patients with liver cirrhosis were also increased. These results demonstrated that SCARNA10 may play a role in HCC by regulating a common pathway in HBV or HCV. All these provide ideas for further research on the function and mechanism of SCARNA10 in HCC in the future.\u003c/p\u003e \u003cp\u003eIn conclusion, we found the serum SCARNA10 level was increased in HCC patients, and associated with some clinicopathologic features, including tumor size, differentiation degrees, stage, vascular invasion, metastasis and complications. The combined detection of SCARNA10 and AFP significantly imporved the diagnostic sensitivity of HCC. However, the roles of SCARNA10 in HCC need to be elucidated in more detail. In future study, we will further research the definite function and mechnism of SCARNA10 in liver carcinogenesis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003elncRNAs: long non-coding RNAs; HCC: hepatocellular carcinoma; BLD: benign liver disease; HC: healthy controls; qPCR: quantitative real-time polymerase chain reaction; ROC: receiver operating characteristic; AUC: area under curve; CT: computer tomography; MRI: magnetic resonance imaging; AFP: alpha fetoprotein; SCARNA10: Small Cajal body-specific RNA 10.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has been approved by Institutional Ethics Committee of Tianjin Medical University Cancer Institute and Hospital (No. Ek2020192). The study methodologies were conformed to the standards set by the Declaration of Helsinki. All subjects were over 18 years of age and voluntarily signed informed consent forms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that no conflicting interest exists.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Scientific Research Project of Tianjin Education Commission (No. 2020KJ129).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.H, L.R and Y.L conceived and designed the studies. Y.H and W.J performed the majority of the experiments. Y.W collected the clinical samples. Y.H and M.Z analyzed the data. Y.H, Y.L and L.R wrote the manuscript. All authors critically reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin\u0026rsquo;s Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin 300060, China. \u003csup\u003e2\u0026nbsp;\u003c/sup\u003eCollege of Inspection, Tianjin Medical University, Tianjin, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYang JD, Hainaut P, Gores GJ, Amadou A, Plymoth A, Roberts LR. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nat Rev Gastroenterol Hepatol. 2019;16(10):589\u0026ndash;604.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGlynn KA, Petrick JL, El-Serag HB. Epidemiology of Hepatocellular Carcinoma. Hepatology. 2021;73 Suppl 1:4\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLlovet JM, Montal R, Sia D, Finn RS. Molecular therapies and precision medicine for hepatocellular carcinoma. Nat Rev Clin Oncol. 2018;15(10):599\u0026ndash;616.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoberts LR, Sirlin CB, Zaiem F, Almasri J, Prokop LJ, Heimbach JK, et al. Imaging for the diagnosis of hepatocellular carcinoma: A systematic review and meta-analysis. Hepatology. 2018;67(1):401\u0026ndash;421.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKulik L, El-Serag HB. Epidemiology and Management of Hepatocellular Carcinoma. Gastroenterology. 2019;156(2):477-491 e471.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTzartzeva K, Obi J, Rich NE, Parikh ND, Marrero JA, Yopp A, et al. Surveillance Imaging and Alpha Fetoprotein for Early Detection of Hepatocellular Carcinoma in Patients With Cirrhosis: A Meta-analysis. Gastroenterology. 2018;154(6):1706-1718 e1701.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo P, Yin P, Hua R, Tan Y, Li Z, Qiu G, et al. A Large-scale, multicenter serum metabolite biomarker identification study for the early detection of hepatocellular carcinoma. Hepatology. 2018;67(2):662\u0026ndash;675.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoodall GJ, Wickramasinghe VO. RNA in cancer. Nat Rev Cancer. 2021;21(1):22\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKopp F, Mendell JT. Functional Classification and Experimental Dissection of Long Noncoding RNAs. Cell. 2018;172(3):393\u0026ndash;407.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGal Z, Gezsi A, Semsei AF, Nagy A, Sultesz M, Csoma Z, et al. Investigation of circulating lncRNAs as potential biomarkers in chronic respiratory diseases. J Transl Med. 2020;18(1):422.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStatello L, Guo CJ, Chen LL, Huarte M. Gene regulation by long non-coding RNAs and its biological functions. Nat Rev Mol Cell Biol. 2021;22(2):96\u0026ndash;118.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong CM, Tsang FH, Ng IO. Non-coding RNAs in hepatocellular carcinoma: molecular functions and pathological implications. Nat Rev Gastroenterol Hepatol. 2018;15(3):137\u0026ndash;151.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang J, Zheng Y, Xiao X, Liu C, Lin J, Zheng S, et al. A Circulating Long Noncoding RNA Panel Serves as a Diagnostic Marker for Hepatocellular Carcinoma. Dis Markers. 2020;2020:5417598.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang H, Liao Z, Liu F, Su C, Zhu H, Li Y, et al. Long noncoding RNA HULC promotes hepatocellular carcinoma progression. Aging (Albany NY). 2019;11(20):9111\u0026ndash;9127.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYao Z, Jia C, Tai Y, Liang H, Zhong Z, Xiong Z, et al. Serum exosomal long noncoding RNAs lnc-FAM72D-3 and lnc-EPC1-4 as diagnostic biomarkers for hepatocellular carcinoma. Aging (Albany NY). 2020;12(12):11843\u0026ndash;11863.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSonohara F, Inokawa Y, Hayashi M, Yamada S, Sugimoto H, Fujii T, et al. Prognostic Value of Long Non-Coding RNA HULC and MALAT1 Following the Curative Resection of Hepatocellular Carcinoma. Sci Rep. 2017;7(1):16142.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng ZK, Pang C, Yang Y, Duan Q, Zhang J, Liu WC. Serum long noncoding RNA urothelial carcinoma-associated 1: A novel biomarker for diagnosis and prognosis of hepatocellular carcinoma. J Int Med Res. 2018;46(1):348\u0026ndash;356.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang K, Han Y, Hu Z, Zhang Z, Shao S, Yao Q, et al. SCARNA10, a nuclear-retained long non-coding RNA, promotes liver fibrosis and serves as a potential biomarker. Theranostics. 2019;9(12):3622\u0026ndash;3638.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJia Y, Shi L, Yun F, Liu X, Chen Y, Wang M, et al. Transcriptome sequencing profiles reveal lncRNAs may involve in breast cancer (ER/PR positive type) by interaction with RAS associated genes. Pathol Res Pract. 2019;215(6):152405.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLei Y, Shi Y, Duan J, Liu Y, Lv G, Shi R, et al. Identification of alternative splicing and lncRNA genes in pathogenesis of small cell lung cancer based on their RNA sequencing. Adv Clin Exp Med. 2019;28(8):1043\u0026ndash;1050.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamel MM, Matboli M, Sallam M, Montasser IF, Saad AS, El-Tawdi AHF. Investigation of long noncoding RNAs expression profile as potential serum biomarkers in patients with hepatocellular carcinoma. Transl Res. 2016;168:134\u0026ndash;145.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu J, Han J, Zhang J, Li G, Liu H, Cui X, et al. The long noncoding RNAs PVT1 and uc002mbe.2 in sera provide a new supplementary method for hepatocellular carcinoma diagnosis. Medicine (Baltimore). 2016;95(31):e4436.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuan JH, Yang F, Wang F, Ma JZ, Guo YJ, Tao QF, et al. A long noncoding RNA activated by TGF-beta promotes the invasion-metastasis cascade in hepatocellular carcinoma. Cancer Cell. 2014;25(5):666\u0026ndash;681.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanzitt K, Tschernatsch MM, Guelly C, Moustafa T, Stradner M, Strohmaier HM, et al. Characterization of HULC, a novel gene with striking up-regulation in hepatocellular carcinoma, as noncoding RNA. Gastroenterology. 2007;132(1):330\u0026ndash;342.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQu L, Cai X, Xu J, Wei X, Qu X, Sun L, et al. Six long noncoding RNAs as potentially biomarkers involved in competitive endogenous RNA of hepatocellular carcinoma. Clin Exp Med. 2020;20(3):437\u0026ndash;447.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlingenberg M, Matsuda A, Diederichs S, Patel T. Non-coding RNA in hepatocellular carcinoma: Mechanisms, biomarkers and therapeutic targets. J Hepatol. 2017;67(3):603\u0026ndash;618.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParkin DM. The global health burden of infection-associated cancers in the year 2002. Int J Cancer. 2006;118(12):3030\u0026ndash;3044.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao Q, Zhu H, Dong L, Shi W, Chen R, Song Z, et al. Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma. Cell. 2019;179(2):561-577 e522.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu QG, Yuan SX, Tao QF, Yu J, Cai J, Yang Y, et al. A novel HBx genotype serves as a preoperative predictor and fails to activate the JAK1/STATs pathway in hepatocellular carcinoma. J Hepatol. 2019;70(5):904\u0026ndash;917.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamdane N, Juhling F, Crouchet E, El Saghire H, Thumann C, Oudot MA, et al. HCV-Induced Epigenetic Changes Associated With Liver Cancer Risk Persist After Sustained Virologic Response. Gastroenterology. 2019;156(8):2313-2329 e2317.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLupberger J, Croonenborghs T, Roca Suarez AA, Van Renne N, Juhling F, Oudot MA, et al. Combined Analysis of Metabolomes, Proteomes, and Transcriptomes of Hepatitis C Virus-Infected Cells and Liver to Identify Pathways Associated With Disease Development. Gastroenterology. 2019;157(2):537\u0026ndash;551 e539.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Renne N, Roca Suarez AA, Duong FHT, Gondeau C, Calabrese D, Fontaine N, et al. miR-135a-5p-mediated downregulation of protein tyrosine phosphatase receptor delta is a candidate driver of HCV-associated hepatocarcinogenesis. Gut. 2018;67(5):953\u0026ndash;962.\u003c/span\u003e\u003c/li\u003e\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-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"hepatocellular carcinoma, long non-coding RNA, SCARNA10, biomarker","lastPublishedDoi":"10.21203/rs.3.rs-757014/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-757014/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eCirculating long non-coding RNAs (lncRNAs) have been demonstrated to serve as diagnostic or prognosis biomarkers for various disease. We aimed to elucidate the diagnostic efficacy of serum lncRNA SCARNA10 for the hepatocellular carcinoma (HCC).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eIn this study, a total of 127 patients with HCC, 55 patients with benign liver disease (BLD), and 99 healthy controls (HC) were enrolled in this study. According to different classifications, the levels of serum SCARNA10 were assessed by quantitative real-time polymerase chain reaction (qPCR). The correlations between serum SCARNA10 and clinicopathological charcaterisstics were further analyzed. The receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to estimate the diagnostic capacity of serum SCARNA10 and its combination with AFP for HCC. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe results demonstrated that the levels of serum SCARNA10 were significantly higher in HCC patients than in patients with BLD and healthy controls, and significantly increased in HCC patients with hepatitis B or C infection, or with liver cirrhosis. Furthermore, positive correlations were noted between serum SCARNA10 level and some clinicopathological characteristics, including tumor size, differentiation degrees, tumor stage, vascular invasion, tumor metastasis and complications. ROC analysis revealed that SCARNA10 had a significantly predictive value for HCC, the combination of SCARNA10 and AFP gained the higher accuracy. SCARNA10 retained significant diagnosis capabilities for AFP-negative HCC patients. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eIn summary,\u003cstrong\u003e \u003c/strong\u003elncRNA SCARNA10 may serve as a novel and non-invasive biomarker with relatively high sensitivity and specificity for HCC diagnosis.\u003c/p\u003e","manuscriptTitle":"Serum Long Non-Coding RNA SCARNA10 Serves As A Potential Diagnostic Biomarker For Hepatocellular Carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2021-10-18 21:51:57","doi":"10.21203/rs.3.rs-757014/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-01-31T07:32:45+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"f1cb7d27-0145-4b63-b927-7844735edded","date":"2022-01-06T03:58:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4b0cc1a7-c228-406b-af9e-b82903315572","date":"2021-12-14T19:11:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-12-09T07:15:07+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-12-07T11:43:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"afedd78d-bf1d-4038-b829-7ea890f88c15","date":"2021-12-07T11:05:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"00edbcfb-d1b4-40af-af7f-8203b04b71d1","date":"2021-11-28T22:44:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-10-24T13:35:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-10-19T03:54:17+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-10-01T06:08:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-10-01T06:06:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2021-09-22T01:06:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"424273d1-f759-4fe6-9517-558f790f9c22","owner":[],"postedDate":"October 18th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":7916897,"name":"Cancer Biology"},{"id":7916898,"name":"Oncology"}],"tags":[],"updatedAt":"2022-04-21T13:52:46+00:00","versionOfRecord":{"articleIdentity":"rs-757014","link":"https://doi.org/10.1186/s12885-022-09530-3","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2022-04-20 13:52:46","publishedOnDateReadable":"April 20th, 2022"},"versionCreatedAt":"2021-10-18 21:51:57","video":"","vorDoi":"10.1186/s12885-022-09530-3","vorDoiUrl":"https://doi.org/10.1186/s12885-022-09530-3","workflowStages":[]},"version":"v2","identity":"rs-757014","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-757014","identity":"rs-757014","version":["v2"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}