Evidence map›Paper›PMID 38494261›Full record

ArticleJournal, genetic engineering & biotechnology2024

Screening of miRNAs as prognostic biomarkers and their associated hub targets across Hepatocellular carcinoma using survival-based bioinformatics approach.

Prithvi Singh, Rubi Solanki, Alvea Tasneem, Simran Suri, Harleen Kaur, Sapna Ratan Shah, Ravins Dohare

Open access · diamondAbstract read
In one paragraph

Article in Journal, genetic engineering & biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
6.6field-weighted citation impact, top 3% 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

5 citing papers in PubMed, 23 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Prithvi SinghCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India.
Rubi SolankiSchool of Interdisciplinary Sciences and Technology, Jamia Hamdard, New Delhi 110062, India.
Alvea TasneemCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India.
Simran SuriCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India.
Harleen KaurDepartment of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi 110062, India.
Sapna Ratan ShahSchool of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India.
Ravins DohareCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India. Electronic address: ravins@jmi.ac.in.
Jamia Millia Islamia · INJamia Hamdard · INJawaharlal Nehru University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe hepatocellular carcinoma (HCC) incident rate is gradually increasing yearly despite all the research and efforts taken by scientific communities and governing bodies. Approximately 90% of all liver cancer cases belong to HCC. Usually, HCC patients approach the treatment in the late stages of this malignancy which becomes the primary cause of high mortality rate. The knowledge about molecular pathogenesis of HCC is limited and needs more attention from researchers to identify the driver genes and miRNAs, which causes to translate this information into clinical practice. Therefore, the key regulators identification of miRNA-mRNA regulatory network is essential to identify HCC-associated genes. METHODOLOGY: We extracted microRNA (miRNA) and messenger RNA (mRNA) expression datasets of normal and tumor HCC patient samples from UCSC Xena followed by identifying differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs). Univariate and multivariate cox-proportional hazard models were utilized to identify DEMs having significant association with overall survival (OS). Kaplan-Meier (KM) plotter was used to validate the presence of prognostic DEMs. A risk-score model was used to evaluate the effectiveness of KM-plotter validated DEMs combination on risk of samples. Target DEGs of prognostic miRNAs were identified via sources such as miRTargetLink and miRWalk followed by their validation in an external microarray cohort and enrichment analysis.

results562 DEGs and 388 DEMs were identified followed by seven prognostic miRNAs (i.e., miR-19a, miR-19b, miR-30d-5p, miR-424-5p, miR-3677-5p, miR-3913-5p, miR-7705) post univariate, multivariate, risk-score model evaluation and KM-plotter analyses. ANLN, MRO, CPEB3 were their targets and were also validated in GSE84005 dataset.

conclusionsThe findings of this study decipher that most significant miRNAs and their identified target genes have association with apoptosis, inflammation, cell cycle regulation and cancer-related pathways, which appear to contribute to HCC pathogenesis and therefore, the discovery of new targets.

Indexed as

Cox modelHepatocellular carcinomamiRNAPrognosisRisk-score

Identifiers

PMID38494261
PMCPMC11630632
OpenAlexW4391202196

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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 Socratic graph.