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

DOI: https://doi.org/10.21203/rs.3.rs-757014/v2

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.

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 [1317]. 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 2a), but there was no significant difference in the expression of SCARNA10 between HCC patients infected with HBV and HCV (Fig. 2a). Moreover, serum SCARNA10 levels in HCC patients with liver cirrhosis were significantly increased (p < 0.05, Fig. 2b).

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. 3a, 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, 2123]. 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. College of Inspection, Tianjin Medical University, Tianjin, China.

References

  1. 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.
  2. McGlynn KA, Petrick JL, El-Serag HB. Epidemiology of Hepatocellular Carcinoma. Hepatology. 2021;73 Suppl 1:4–13.
  3. 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.
  4. 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.
  5. Kulik L, El-Serag HB. Epidemiology and Management of Hepatocellular Carcinoma. Gastroenterology. 2019;156(2):477-491 e471.
  6. 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.
  7. 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.
  8. Goodall GJ, Wickramasinghe VO. RNA in cancer. Nat Rev Cancer. 2021;21(1):22–36.
  9. Kopp F, Mendell JT. Functional Classification and Experimental Dissection of Long Noncoding RNAs. Cell. 2018;172(3):393–407.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. Parkin DM. The global health burden of infection-associated cancers in the year 2002. Int J Cancer. 2006;118(12):3030–3044.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. 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.