MiRNA-122 association with TNF-α in some liver diseases of Egyptian patients

: Background: Due to the high frequency of HCC, ongoing research is needed to find precise, non-invasive biomarkers for early identification and follow-up that will improve prognostic results. Patients and methods: this study was conducted on 90 patients with liver diseases and 25 healthy control G1, patients divided into 4 groups, (G2) 25 patients with HCV infection, (G3) 25 HCC+HCV infection, (G4) 25 patients with HBV infection, (G5) 15 patients with HCC + HBV. Results: Serum miR-122 and TNF-α levels were increased in HCV and HBV infection significantly with p-value >0.001 * compared to the control group, and their levels decreased when developed into HCC but still higher than the healthy subjects significantly with p-value >0.001. For discriminating HCV from HCV+HCC the cut-off for miR-122 was >7.1 at sensitivity 100%, specificity 100%, and the AUC was 1.0 (Excellent) P-value <0.001, also the sensitivity and specificity for TNF-α 72%, and 60% respectively with cut off >12.1 and AUC of 0.745 (Good) p-value 0.003. For discriminating HBV from HBV+HCC the cut-off for miR-122 was ≤6.4 at a sensitivity of 86.67% and specificity of 96%, and the AUC of miR-122 was 0.99 (Excellent) P-value <0.001, also the sensitivity and specificity for TNF-α 93.33%, and 48.0% respectively with cut-off ≤15.73, TNF-α has AUC of 0.527 (fair) it was not significant p-value 0.780.

Liver cancer is one of the most prevalent malignancies in the world, with significant rates of morbidity and death.The most prevalent primary liver cancer, hepatocellular carcinoma (HCC), accounts for 75-85% of all liver cancer cases (3).The most frequent causes of HCC are chronic liver infection from hepatitis B or C virus (HBV or HCV, respectively) and alcohol addiction (4), It has been evident that hepatitis B is a common condition and that more than 2 billion individuals worldwide have been exposed to HBV.According to estimates from the World Health Organization (WHO), 296 million persons worldwide had chronic HBV infection in 2019. (https://www.who.int/news-room/factsheets/detail/hepatitis-b).
Hepatitis C Virus (HCV) infection is one of the major causes of morbidity and mortality globally and in developing countries HCV is a major contributor to chronic liver disease, HCC, and liver transplantation

(5).
With 58 million chronically infected individuals and 1.5 million new infections annually, HCV has a large worldwide impact, WHO estimated that approximately 290,000 people died from hepatitis C in 2019, mostly from cirrhosis and hepatocellular carcinoma.WHO set ambitious goals to eradicate viral hepatitis B and C as a public health threat by 2030 (WHO June 2022

Report) (6).
To reduce the prevalence of HCC, HBV, and HCV, the two main risk factors, must be prevented and treated (7).For the early diagnosis of HCC, alpha-fetoprotein (AFP) screening and ultrasonography are frequently employed.However, there are certain limitations with AFP and ultrasonography in HCC early detection (8).
The majority of patients with primary HCC are detected at late stages, which is linked to a poor prognosis and a low survival rate of the illness.
Currently, there are no viable biomarkers for early identification of primary HCC.Therefore, it is crucial to find more accurate and reliable markers for the early diagnosis of primary HCC, and many efforts have been undertaken in this direction over the past few decades.
The discovery of short noncoding regulatory RNAs called microRNAs (miRNAs) is an evolutionarily conserved gene class (9).Noncoding RNAs of the family known as microRNAs (miRNAs) range in length from 17 to 22 nucleotides and play a crucial role in posttranscriptional gene regulation.These master regulators are also sensitive to post-transcriptional and transcriptional control (10).The most prevalent liverspecific miRNA, MicroRNA-122 (miR-122), constitutes around 70% of the overall miRNA population in the adult liver (11).
According to Boutz DR and colleagues (2011), miRNA-122 controls several genes in the liver that modify the cell cycle, differentiation, proliferation, and apoptosis.This suggests that miRNA -122 can be a reliable and predictive blood marker for alcohol, viral, and chemical-induced liver injury because the change in miRNA-122 levels in the blood is a well-known indicator of liver disease and is prominent early before the increase in liver aminotransferase activity (12).
In all phases of HCC development, miRNA-122 is markedly down-regulated and exhibits tumorsuppressive properties (13).miRNA 122 is involved in the control of TNFα expression (14).A significant inflammatory cytokine in the progression of liver disease is tumor necrosis factor (TNF-α).This cytokine has the potential to damage the liver, induce cirrhosis, and ultimately lead to hepatocellular cancer

(15)
High production of TNF is associated with the increase of pro-inflammatory cytokine secretion, the activation of proto-oncogenes, and several genes related to cell growth, invasion, and metastasis of cancer cells (16).
This study aims to detect the unclear association between miRNA-122 and TNF-α in liver diseases of Egyptian patients, and the validity of miRNA-122 and TNF-α in early diagnosis of HCC associated with HCV and HBV infection.

Subjects
This study was carried out on 90 Egyptian hepatic patients and twenty-five healthy subjects.

Group (2):
This group consisted of 25 patients with HCV infection.

Group (3):
This group consisted of 25 patients with hepatocellular carcinoma (HCC) associated with HCV infection.

Group (4):
This group consisted of 25 patients with HBV infection.

Group (5):
This group consisted of 15 patients with hepatocellular carcinoma (HCC) associated with HBV infection.

Blood sample collection and preparation
Five milliliters of venous blood were taken from each patient in all five groups using a vacutainer system and septic venipuncture.The blood sample was separated into two milliliters mixed with sodium citrate for PT-INR and three milliliters for biochemical and molecular analyses.

Liver function tests:
ALT: There is a significant difference between the five groups, when compared to the control group the four patient groups have a significant elevation (0.001) as shown in Table (3) and Figure (1).

AST:
The four patient groups have a statistically significant elevation with the same p-value of 0.001 * for the four groups compared with the control group as shown in Table (3) and Figure (2).
Albumin: compared to the control group all four patient groups have a statistically significant decrease with the same p-value of 0.001 * for the three groups and 0.003 for the HBV group compared with the control group as shown in Table (3) and Figure (3).
Total Protein: Compared to the control group all four patient groups have a statistically significant decrease with the same p-value of 0.001 * for the four groups compared with the control group as shown in Table (3) and Figure (4).
Total bilirubin: compared to the control group all four patient groups have a statistically significant elevation with the same p-value of 0.001 * for the three groups and 0.025 for the HBV group compared with the control group as shown in Table (3) and Figure (5).
Direct bilirubin: compared to the control group the three patient groups have a statistically significant elevation with the same p-value of 0.001 * for the three groups and 0.846 for the HBV group not significant compared with the control group as shown in Table (3) and Figure (6).p2: p-value for comparing between HCV and HCV+HCC.p3: p-value for comparing between HCV and HBV p4: p-value for comparing between HCV and HBV+HCC.p5: p-value for comparing between HCV+HCC and HBV p6: p-value for comparing between HCV+HCC and HBV+HCC.p7: p-value for comparing between HBV and HBV+HCC *: Statistically significant at p ≤ 0.05.

Prothrombin time (PT) (INR)
There was a statistically significant difference between the five groups p value >0.001 * , while compared to the control group, only two groups elevated the group 3 HCV+HCC, and group 5 HBV+HCC had a significant statistical difference with p-value >0.001 * , but HCV and HBV groups have a p-value 0.116 and 0.797 respectively which have not a significant statistically difference compared to the control group as shown in table (4) and figure (7).However, there was no significant difference between (the HCV+HCC) group and (the HBV+HCC) group in the level of Serum miR-122 with a p6-value of 0.673 not significant.as shown in Table (5) and Figure (8).

Association between miR-122 and TNF-α
Compared with the healthy control group, serum miR-122 levels and Tumor necrosis factor-α (TNF-α) were markedly increased in the HCV infection cases group with a significant p-value of>0.001* , and their levels were decreased in the HCV+HCC group but still higher than the healthy control group with a significant p-value of>0.001* for both, miR-122 level decreasing in HCV+HCC group from HCV group with a significant p-value of >0.001 * , and the TNF-α level decreasing in HCV+HCC group from HCV group with a significant p-value of 0.010 * .
In groups, HBV, and HBV+HCC Compared with the healthy control group, serum miR-122 level, and TNFα level were markedly increased in the HBV infection cases group with a significant p-value of>0.001* , and their levels were decreased in HBV+HCC group but still higher than the healthy control group with a significant p-value of>0.001* for both, Serum miR-122 and TNF-α levels were increased in HCV and HBV infection, and their levels decreased when the hepatitis viral infection developed into hepatocellular carcinoma HCC but were still higher than the levels in healthy subjects, miR-122 and TNFα levels have a parallel change as shown in table (6).

Receiver Operating Characteristics (ROC) Curves analysis:
ROC curve analysis was designed for miR-122, TNFα, and AFP to discriminate HCV-infected patients against HCV+HCC group patients.ROC curve was performed as cut off for disease progression to evaluate the sensitivity and specificity for miR-122 and TNF-α compared with AFP to diagnose HCC from HCV infection.As shown in Figure (10).Prognostic performance for TNF-α, miR-122, and AFP to discriminate HBV from HBV+HCC.Table (8) the results showed that the cut-off for miR-122 was ≤6.4 at a sensitivity of 86.67% and specificity of 96%, the sensitivity and specificity for TNF-α 93.33%, 48.0% respectively with cut-off ≤15.73, while AFP has a cut off >9 with sensitivity 100% and specificity100%, the AUC of miR-122 was 0.99 (Excellent) significant P-value <0.001 * with PPV 92.9% and NPV 92.3%, TNF-α has AUC of 0.527 (fair) it was not significant p-value 0.780, PPV 51.9 and NPV 92.3, while AFP has AUC 1.0 (Excellent) which significant p-value <0.001 * , PPV 100 and NPV 100.

Receiver Operating Characteristics (ROC) Curves analysis:
ROC curve analysis was designed for miR-122, TNF-α, and AFP to discriminate HBV-infected patients against HBV+HCC group patients.ROC curve was performed as cut off for disease progression to evaluate the sensitivity and specificity for miR-122 and TNF-α compared with AFP to diagnose HCC from HCV infection.As shown in figure (11).

Figure ( 1 )
Figure (1): Levels of ALT in all studied five groups.

Figure ( 6 ):
Figure(6): Levels of serum direct bilirubin in all studied five groups.Figure(5): Levels of serum total bilirubin in all studied five groups.

Figure ( 4 )
Figure (4): Levels of serum total Protein in all studied five groups.

Figure ( 7 )
Figure (7): Levels of serum INR in all studied five groups.
. Grps. p2>0.001* ,p3>0.001* ,p4>0.001* ,p5>0.001* ,p6=0.673,p7>0.001* IQR: Inter quartile range SD: Standard deviation.F: F for One-way ANOVA test, Pairwise comparison bet.Each 2 groups were done using a Post Hoc Test (Tukey) H: H for Kruskal Wallis test, Pairwise comparison bet.Each 2 groups were done using a Post Hoc Test (Dunn's for multiple comparisons test) p: p-value for comparing the different studied groups.p1: p-value for comparing between Control and each other groups.p2:p-value for comparing between HCV and HCV+HCC.p3: p-value for comparing between HCV and HBV p4: p-value for comparing between HCV and HBV+HCC.p5: p-value for comparing between HCV+HCC and HBV p6: p-value for comparing between HCV+HCC and HBV+HCC.p7: p-value for comparing between HBV and HBV+HCC.

:
Comparison between the different studied groups according miR-122, TNF-α, and AFP

3.1. Demographic data of the studied groups 3.1.1. Gender
(2)or the four groups compared with the control group as shown in table(2).

Table ( 3): Comparison between the different studied groups according to Liver function
* IQR: Inter quartile range SD: Standard deviation.F: F

for One-way ANOVA test,
Pairwise comparison bet. each 2 groups were done using a Post Hoc Test (Tukey) H: H for Kruskal Wallis test, Pairwise comparison bet.

Figure (11): ROC curve for TNF-α, miR-122, and AFP to discriminate HBV+HCC (n= 15) from HBV (n = 25)
Also, the above results are supported by Enas M et al. -α is primarily generated by activated monocytes, macrophages, endothelial cells, and lymphocytes and has biological action through binding to soluble TNFbinding receptors (TNFR1 and TNFR2) (33).TNF-α has been associated with a poor prognosis in patients with severe acute respiratory syndrome (SARS)‫,و‬ but the serum TNF-α level is not a significant biomarker for diagnosis or prognosis of mild COVID-19 patients Serum TNF-α can be used as a biomarker to differentiate between healthy and infected patients with HCV or HBV and the development of HCC (36).
TNFTNF-α is a powerful pro-inflammatory cytokine in and of itself (37).Necroinflammation in hepatocytes causes mutagenesis and oncogene activation from proto-oncogenes in host cells, resulting in HCC (35).TNF-α is also known to generate HCC via the chronic inflammatory route by activating and differentiating hepatic progenitor cells (38).