Evidence map›Paper›PMID 34687371›Full record

ArticleMedical oncology (Northwood, London, England)2021

Application of comprehensive bioinformatics approaches to reconnoiter crucial genes and pathways underpinning hepatocellular carcinoma: a drug repurposing endeavor.

Gouri Nair, G N S Hema Sree, Ganesan Rajalekshmi Saraswathy, V Lakshmi Prasanna Marise, T P Krishna Murthy

Abstract read
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In one paragraph

Article in Medical oncology (Northwood, London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
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

5 authors at 1 institution in 1 country.

Gouri NairDepartment of Pharmacology, Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, Karnataka, India. neethugouri@gmail.com.ORCID http://orcid.org/0000-0003-2081-6827
G N S Hema SreeDepartment of Pharmacy Practice, Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, India, Karnataka.
Ganesan Rajalekshmi SaraswathyDepartment of Pharmacy Practice, Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, India, Karnataka.
V Lakshmi Prasanna MariseDepartment of Pharmacy Practice, Faculty of Pharmacy, M. S. Ramaiah University of Applied Sciences, Bangalore, India, Karnataka.
T P Krishna MurthyDepartment of Biotechnology, M. S. Ramaiah Institute of Technology, Bengaluru, Karnataka, 560054, India.
M S Ramaiah University of Applied Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is the fifth most common neoplasm in the world. Chronic inflammation of liver and associated wound healing processes collectively contribute to the development of cirrhosis which further progresses to dysplastic nodule and then to HCC. Etiological mediators and ongoing manipulations at cellular level in HCC are well established; however, key protein interactions and genetic alterations involved in stepwise hepatocarcinogenic pathways are seldom explored. This study aims to unravel novel targets of HCC and repurpose the FDA-approved drugs against the same. Genetic data pertinent to different stages of HCC were retrieved from GSE6764 dataset and analyzed via GEO2R. Subsequently, protein-protein interaction network analysis of differentially expressed genes was performed to identify the hub genes with significant interaction. Hub genes displaying higher interactions were considered as potential HCC targets and were validated thorough UALCAN and GEPIA databases. These targets were screened against FDA-approved drugs through molecular docking and dynamics simulation studies to capture the drugs with potential activity against HCC. Finally, cytotoxicity of the shortlisted drug was confirmed in vitro by MTT assay. CDC20 was identified as potential druggable target. Docking, binding energy calculations, and dynamic studies revealed significant interaction exhibited by Labetalol with CDC20. Further, in MTT assay, Labetalol demonstrated an IC

Indexed as

Drug RepositioningCarcinoma, HepatocellularCdc20 ProteinsComputational BiologyHumansLabetalolLiver CirrhosisLiver NeoplasmsMolecular Docking SimulationProtein Interaction MapsCDC20 protein, humanCdc20 ProteinsLabetalolDrug repurposingHepatocellular carcinomaLabetalolTarget identification

Identifiers

PMID34687371
OpenAlexW3196247731

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.