Evidence map›Paper›PMID 33178874›Full record

ArticleReports of biochemistry & molecular biology2020

Long Non-Coding HULC and miRNA-372 as Diagnostic Biomarkers in Hepatocellular Carcinoma.

Olfat Shaker, Hala Mahfouz, Ahmad Salama, Engy Medhat

Open access · goldAbstract read
In one paragraph

Article in Reports of biochemistry & molecular biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.3field-weighted citation impact, top 10% 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

23 citing papers in PubMed, 31 citations in OpenAlex.

  1. Epigenetic Mechanisms Involved in Hcv Infection and Human HCC.International journal of molecular sciences · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Olfat ShakerMedical Biochemistry and Molecular Biology Department, Faculty of Medicine, Cairo University, Egypt.
Hala MahfouzMedical Biochemistry and Molecular Biology Department, Faculty of Medicine, Kafrelsheikh University, Egypt.
Ahmad SalamaTropical Medicine Department, Faculty of Medicine, Cairo University, Egypt.
Engy MedhatMedical Biochemistry and Molecular Biology Department, Faculty of Medicine, Cairo University, Egypt.
Cairo University · EGKafrelsheikh University · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aimed to evaluate the effectiveness of Highly Upregulated in Liver Cancer (HULC) and microRNA-372 (miR-372) as biochemical markers in Hepatocellular carcinoma (HCC) and HCV-infected patients.

methodsThe present study was conducted on 100 Egyptian individuals divided into 3 groups, 40 patients with HCC and HCV infection, 40 patients only HCV-infected, and 20 individuals as normal controls. They were subject to full history taking, full clinical and laboratory examination, and assessment of HULC and miR-372 levels by real-time PCR.

resultsA statistically significant difference was found with p< 0.05 between HCC and each of HCV and control groups as regards HULC level with high mean among HCC followed by HCV patients. Our results also show a statistically significant difference with p< 0.05 between each of HCC and HCV compared to control as regards miR-372 level with low mean among HCC patients.

conclusionHULC could be considered as a potential non-invasive marker for detection and early diagnosis of HCC. Also, it may play an important role in the early prophylaxis and control measures to reduce the incidence of HCC. However, miR-372 cannot be considered as a reliable marker as HULC for early detection of HCC especially in HCV patients.

Indexed as

HCCHCVHULCMiRNA-372

Identifiers

PMID33178874
PMCPMC7603263
OpenAlexW3095137580

What OpenQuestion holds

Textmetadata
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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.