Evidence map›Paper›PMID 31316135›Full record

ArticleCancer gene therapy2020

The interaction between microRNA-152 and DNA methyltransferase-1 as an epigenetic prognostic biomarker in HCV-induced liver cirrhosis and HCC patients.

Rady E El-Araby, Mahmoud A Khalifa, Mona M Zoheiry, Manal Y Zahran, Mohamed I Rady, Raafat A Ibrahim, Mohamed D El-Talkawy, Faiza M Essawy

RetractedErratum issuedAbstract readRetracted Publication
PubMed Publisher
In one paragraph

Article in Cancer gene therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Rady E El-ArabyAssistant Researcher of Molecular Biology, Central Lab, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt. radyeid.elaraby@gmail.com.ORCID http://orcid.org/0000-0003-4822-5279
Mahmoud A KhalifaAssistant Prof. of Molecular Biology, Zoology Department, Faculty of Science, Al-Azhar University, Cairo, Egypt.ORCID http://orcid.org/0000-0001-7704-1722
Mona M ZoheiryProf. of Clinical pathology (Immunology), Immunology Research Department, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt.
Manal Y ZahranProf. of Hematology, Clinical Laboratory, Research Department, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt.
Mohamed I RadyProf. of Cytochemistry and Histochemistry, Zoology Department, Faculty of Science, Al-Azhar University, Cairo, Egypt.
Raafat A IbrahimProf. of Hepatoastroenterology, Hepatoastroenterology Department, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt.
Mohamed D El-TalkawyProf. of Hepatoastroenterology, Hepatoastroenterology Department, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt.
Faiza M EssawyProf. of Hematology, Clinical Laboratory, Research Department, Theodor Bilharz Research Institute (TBRI), Ministry of Scientific Research, Gizah, Egypt.
Ministry of Higher Education and Scientific Research · EGAl-Azhar University · EGTheodor Bilharz Research Institute · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 < 0.01), (r = -0.850, p < 0.001) and (r = -0.544, p < 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 < 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.

Indexed as

AdolescentAdultBiomarkers, TumorCarcinoma, HepatocellularDNA (Cytosine-5-)-Methyltransferase 1Epigenesis, GeneticFemaleHepacivirusHepatitis C, ChronicHumansLiver CirrhosisLiver NeoplasmsMaleMicroRNAsMiddle AgedPrognosisBiomarkers, TumorDNA (Cytosine-5-)-Methyltransferase 1DNMT1 protein, humanMicroRNAsMIRN152 microRNA, human

Identifiers

PMID31316135
OpenAlexW2959978209

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.