The interaction between microRNA-152 and DNA methyltransferase-1 as an epigenetic prognostic biomarker in HCV-induced liver cirrhosis and HCC patients
Authors: Mona M Zoheiry
Rady E El-Araby
Raafat A Ibrahim
Manal Y Zahran
Faiza M Essawy
Mohamed I Rady
Mohamed D El-Talkawy
Mahmoud A Khalifa
Journal: Cancer Gene Therapy (2020)
Discipline: CLINICAL MEDICINE
Keywords: hepatocellular carcinoma; HCV genotype 4; miRNA-152; DNMT-1; chronic liver disease
Affiliations: Assistant Researcher of Molecular Biology, Central Lab, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt. ., Assistant Prof. of Molecular Biology, Zoology Department, Faculty of Science, Al-Azhar University, Cairo, Egypt., Prof. of Clinical pathology (Immunology), Immunology Research Department, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt., Prof. of Hematology, Clinical Laboratory, Research Department, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt., Prof. of Cytochemistry and Histochemistry, Zoology Department, Faculty of Science, Al-Azhar University, Cairo, Egypt., Prof. of Hepatoastroenterology, Hepatoastroenterology Department, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt.

Abstract:  The necessity for early detection and hence improving the outcome of treatment of hepatocellular carcinoma (HCC) is critical especially in Hepatitis C virus (HCV)-Genotype 4 induced cases. In our current work, we examined the miRNA-152 and DNMT-1 expression in chronic liver disease (CLD) due to HCV genotype 4 infection with/without cirrhosis and HCC patients as an attempt to evaluate the potential benefits of these new circulating, noninvasive, prognostic, epigenetic markers for liver cirrhosis and carcinogenesis of Egyptian patients. Eighty subjects were included in this study, divided into two groups; group I (40 patients) were classified into subgroup Ia (CLD without cirrhosis, n = 18) and subgroup Ib (CLD with cirrhosis, n = 22), group II (CLD patients with HCC, n = 20), and control (Healthy volunteer, n = 20). The expression of miRNA-152 and DNMT-1 genes were analyzed using Real-Time PCR. MiRNA-152 showed a persistent and significant downregulation in all diseased groups, which was in consistence with the progression of the disease toward the HCC stage. DNMT-1 showed upregulation in all diseased groups when compared to control and subgroup Ia. The miRNA-152 was shown to correlate inversely with DNMT-1 in subgroup Ia, Ib and group II (r = -0.557, p &lt; 0.01), (r = -0.850, p &lt; 0.001) and (r = -0.544, p &lt; 0.02) respectively. In addition, miRNA-152 and DNMT-1 showed a diagnostic ability to discriminate between cases of cirrhosis and HCC against CLD without cirrhosis (p &lt; 0.01), while DNMT-1 did not, except between HCC and cirrhotic cases. Furthermore, both genes can be considered as predictor and prognostic parameters for cirrhosis (OR = 1.041, p = 0.043) and (OR = 1.039, p = 0.04) respectively, while miRNA-152 alone is proved as a prognostic marker for HCC (OR = 1.003, p = 0.044). Finally, the persistent reverse correlation between miRNA-152 with DNMT-1 prompts their use as noninvasive prognostic biomarkers for HCV induced liver cirrhosis and HCC in HCV Genotype 4 patients. 

Retracted: No

PubPeer comments:
 I found a series of 4 papers. (A) [DOI 10.1186 s43042-020-0048-8] , in Egyptian Journal of Medical Human Genetics. (B) no DOI immediately available, [https link] , in Al-Azhar Journal of Pharmaceutical Sciences. (C) [DOI 10.1038 s41417-019-0123-9] , in Cancer Gene Therapy. (D) [DOI 10.1016 j.genrep.2019.100452] in Gene Reports. (A) and (B) cite the same approval document, (C) and (D) also cite the same approval document, different from (A) and (B). The authors listed for (C) and (D) are the same. For (A) and (B) the author lists are slightly different, and different from (C) and (D), but have a large overlap. Of interest are socdem + lab analyses + ultrasound result tables. The N values are different between (A) and (B) (C) and (D). Moreover, the numbers for cirrhosis splenomegaly ascites patients are different across all tables, suggesting that these studies deal with 4 different samples. However, despite differences, there are many unnaturally repeated values across the tables, which the reader will easily spot. For (B) splenomegaly percentage in group 1a is incorrect: reported 11.11%, correct value per given absolute numbers - 8.00% For (C) numbers of male female members in groups 1a and 2 do not add up to respective N. The same numbers and the same inconsistency are in (D), too. (A) ![file] (B) ![file] (C) ![file] (D) ![file] What happened? , 
 #1 Thank you for your comments, I am Rady El-Araby, 1st author of C and D paper, I would like to indicate that as a response to your inquires, these 4 papers stem from two different projects, but from one laboratory and under one supervisor, which is Prof. Dr. Faiza Esawy. The first project was about LncRNA, from which emerged A and B papers, (A) https: doi.org 10.1186 s43042-020-0048-8 in Egyptian Journal of Medical Human Genetics. (B) https: ajps.journals.ekb.eg article_70241_f50ac92909cde6cf76eb27b44580e9e1.pdf in Al-Azhar Journal of Pharmaceutical Sciences. - While the 2nd one was about miRNAs this is my Ph.D project. from which emerged C and D papers, So I can answer your questions about my project (Paper C and D) only, 1- I didn t do any clinical trials, but the attached approval shows the approval of the Ethics Committee to conduct the research and the possibility of collecting blood samples only from patients after their agreement on a consent form and accordingly we obtain the approval from the Ethical Committee in the Institute. So, you will find this approval in C and D papers. 2- The reason for the similarity between the C and D papers is that as you mentioned, this work was done on the same cases. So you will find all clinical and laboratory data is the same. N.B: If you have any inquires regarding A and B papers, you may ask the corresponding author of those articles  Fawzy Roshdy . 3- I admit that something went wrong, but it was not intended in the gender distribution in the C and D papers. After precise review and return to the source of the research and the collected papers, the following was found: Female(1a) = 10(55.6%); Male(1a) = 8(44.4%); Total N of (1a) = 18. Female(2) = 4(20.0%); Male(2) = 16(80.0%); Total N of (2) = 20. Therefore, I would like to apologize for these results that appeared unintentionally as a result of missing data, especially in the gender column as shown in the attached master sheet. ![file] , 
 Correction 22 Feb 2022. [Link] . --- After publication an error was found in Table 3 of the manuscript in the columns related to gender distribution. After precise review and return to the source of the research and the collected papers, the following was found: Female (1a)u2009=u200910 (55.6%); Male (1a)u2009=u20098 (44.4%); Total N of (1a)u2009=u200918. Female (2)u2009=u20094 (20.0%); Male (2)u2009=u200916 (80.0%); Total N of (2)u2009=u200920. These modifications do not affect the results or the discussion of the manuscript, as age was not an influencing factor in this study or associated with any other parameters in the study. The amended figure accompanies this correction. --- However, this correction is inconsistent with Figure 6. See annotated figure below. The ROCs (Figure 6) suggest the following sizes of groups: * HCV (Ia) - 19 * Cirrhosis (Ib) - 20 * HCC (II) - 18. The same figures are deduced from ROC curves in the companion study (D) - see [PubPeer thread] . The same figures are also obtained if sums of male and female patients in the groups were as reported before correction. To check myself, I calculated AUCs for panels (c) and (d) under assumption that my reading of ROC curves is correct and got exactly the results reported (light green boxed). ![file] , 
 Thank you for your comment. I am with you on this, but I confirm that the ROC curve is correct and the settings that were made are correct. But everything in the matter was that the difference was in the gender column, where there were unwritten cases, but they were modified in the previous amendment, and all the rest of the parameters in the study were prepared exactly. , 
 Figure 3, datapoints for group Ia. At least 19 points are visible, versus 18 claimed in the correction. ![file] , 
 Figure 4, datapoints for group Ib. It looks rather like 20 points, versus 22 claimed in the correction. ![file] , 
 Figure 5, datapoints for group II. It looks rather like 18 or 19 points (depending on whether the cluster at miRNA-152 0.7 level consists of 2 or 3 points). However, 20 points are claimed in the correction. (Given the other data, I am inclined to believe there are 18 points in Figure 5.) ![file] , 
 In light of comments #3 and #5 - #7 could the authors please share the minimal raw data needed to reconstruct Figures 3, 4, 5 and 6? These would be three two-column tables (one table corresponding to each of the groups Ia, Ib and II) and showing miRNA-152 and DNMT-1 expression for each patient in the group. , 
 Thank you for your comments, The reason behind the difference in the number of points on the figures and the total number of the studied groups is the occurrence of overlapped points on top of each other, which makes them appear as one point.u00a0 The entire data of the analysed genes for the studied groups can be found in the table below. Best regards, , 
 ![file] , 
 #10 Which proves that the correction is misleading. $N(text{HCV}) = 19  eq 18$ $N(text{Cirrhosis}) = 20  eq 22$ $N(text{HCC}) = 18  eq 20$ I attach an annotated image from #10 so that everyone could easily verify my objection. ![file] , 
 Dear Friend The modifications were not misleading at all! The point is simply that this data is the original data. All in a nutshell is that the first group increased by one case because we worked on HCV genotype 4, but the case of No. 12 had a genotype 2  yellow highlited case in the attached table in comment No. 2. Therefore, it was necessary to completely remove her from all relationships. So I admit that it is necessary to restore relations without this case in the first group of HCV  Ia . Regarding groups  Ib and  2, each group had two cases. We did not get their RT-PCR readings well, so they were not recorded, but they had all the data related to the rest of the studied parameters.u00a0 Best regards, , 
 Therefore, it was necessary to completely remove her from all relationships. Are you planning to submit yet another correction for this? If you do, go ahead and let us see where it goes. Regarding groups  Ib and  2, each group had two cases. We did not get their RT-PCR readings well, so they were not recorded, but they had all the data related to the rest of the studied parameters. Got it. High-quality clinical trials and accurate reporting of data obtained. Just as we deserve. --- P.S. Could any knowledgeable reader step in and check the following: * whether the accuracy of 5 decimal digits is customary to reporting the expression of miRNA-152 and DNMT-1 * how likely it is to have two repeated values with this precision in a group of 20 (i.e., group Ib)? , 
 Dear Editor Kindly find the corrected graph regarding coment 5# Fig. 3 Correlation between DNMT-1 and miRNA-152 in Ia group , 
 ![file] , 
 Regarding the comments 6 and 7 which about figurs 4 and 5, They are correct, as I explained to you before the groups  Ib n= 22 and  2 n= 20, but each group had two cases. We did not get their RT-PCR readings well, so they were not recorded, but they had all the data related to the rest of the studied parameters. , 
 Regarding the comment 3# Kindlly find the corrected figure 6![file] , 
 Because of the change that has occurred, we have to amend the comments for this part in the results as well as in the discussion sections, as will (Table 5) regarding the diagnostic performance of miRNA152 and DNMT-1.u00a0 ![file] , 
 Results section: Diagnostic performance of different genes expression as markers of subgroup (Ib) and group II at different cutoff points using (ROC) curve. The calculated sensitivity, specificity, and diagnostic accuracies for studied parameters to discriminate subgroup (Ib) from subgroup (Ia) (Table 5). For discrimination of subgroup (Ib) versus subgroup (Ia), For discrimination of subgroup (Ib) versus subgroup (Ia), regarding miRNA-152, the AUC= 69.2% with (95% CI 52.4%u201386.0%, p value= 0.025) and for DNMT-1, the AUC = 73.9% with (95% CI 58.0%u201389.8%, p value 0.003) Fig. 6a, b. While in case group II versus subgroup (Ia), the miRNA-152 showed AUC of 82.7% (95% CI 69.0% - 96.4%, p value 0.0001) and for DNMT-1, the AUC was of 71.3% (95% CI 53.3% - 89.3%, p value= 0.02) (Fig 6c, d). On discrimination between group II versus subgroup (Ib), the results indicated that miRNA-152 could be considered as a diagnostic parameter with weak significant results or in borderline, AUC = 68.9% for miRNA-152 (95% CI 48.1%u201385.8%, p value = 0.05). But there were no significant difference between the two groups regarding DNMT-1 Fig. 6e, f. We demonstrated that AUC for miRNA-152 = 74.4% (95% CI 61.3% - 87.5%, p value 0.001). But there were a significant results, AUC = 65.1% for DNMT-1 (95% CI 46.9% - 83.2%, p value = 0.05). These results indicated that miRNA-152 could be considered as a diagnostic parameter with a significant results and could be used for discrimination between group II versus group I. , 
 Discussion section: The diagnostic performance of both genes expression as markers in cirrhotic patients at different cutoff points using ROC curve (AUC = 69.2% for miRNA-152 (95% CI 52.4% - 86.0%, p value = 0.025), sensitivity (95.0%), specificity (38.9%) with accuracy (68.4%). In the case of group II (AUC = 82.7% (95% CI 69.0% - 96.4%, p value 0.001), sensitivity (94.4%), specificity (72.2%) with accuracy (83.3%). While there are (AUC = 66.9% (95% CI 48.1%u201385.8%, p value = 0.05), sensitivity (88.9%), specificity (55.0%) with accuracy (71.1%) regarding group II when compared to Ib subgroup. This could be explained due to the relatively small sample size. Evidently, there are (AUC = 74.4% (95% CI 61.3% - 87.5%, p value 0.001), sensitivity (94.4%), specificity (57.9%) with accuracy (69.6%) regarding group II than CLD patients as one group. Stratification of the prognostic values, deduced from the ROC curve, as a biomarker for disease progression showed a gradual decline of miRNA-152 gene expression with disease progression. This can be categorized from CLD without cirrhosis, CLD with cirrhosis and HCC (0.448, p value = 0.025), (0.17, p value 0.001) and (0.11, p value 0.05) respectively. On the contrary, DNMT-1 gene expression increased with disease progression in a disparate process (28.443, p value 0.003), (10.411, p value= 0.02) and (54.57, p value 0.3) respectively. , 
 **Retraction**, June 22, 2022. Retraction notice is available [here] . It reads, The Editor-in-Chief has retracted this Article. After publication, concerns were raised regarding the numbers of patients in various groups in Table 3, which the Authors addressed via Correction [1]. However, further similar issues have been identified in Figs. 3u20136, which affect the results and conclusions of this study. The numbers of data points in these figures do not match the group descriptions in the Materials and methods. Additionally, the Authorsu2019 subsequent study [2] appears to report the same patient recruitment period from the same institution as well as the same inclusion and exclusion criteria, but contains a higher number of patients than this Article. The Authors have been unable to sufficiently explain these discrepancies. Mahmoud A. Khalifa, Mona M. Zoheiry, Manal Y. Zahran, Mohamed I. Rady, Raafat A. Ibrahim, Mohamed D. El-Talkawy and Faiza M. Essawy do not agree to this retraction. Rady E. El-Araby has not explicitly stated whether they agree to this retraction notice. **References:** 1. El-Araby RE, Khalifa MA, Zoheiry MM, Zahran MY, Rady MI, Ibrahim RA, et al. Correction: the interaction between microRNA-152 and DNA methyltransferase-1 as an epigenetic prognostic biomarker in HCV-induced liver cirrhosis and HCC patients. Cancer Gene Ther. 2022. https: doi.org 10.1038 s41417-022-00440-x 2. Roshdy F, Farag MMS, El-Ahwany E, Mahmoud O, Mousa AA, El Talkawy M, et al. Long non-coding RNA HOTAIR and HOTTIP as potential biomarkers for hepatitis C virus genotype 4-induced hepatocellular carcinoma. Egypt J Med Hum Genet. 2020;21:7 https: doi.org 10.1186 s43042-020-0048-8 ,