Evidence map›Paper›PMID 36313358›Full record

ArticleFrontiers in pharmacology2022

Integrated network pharmacology and experimental analysis unveil multi-targeted effect of 18α- glycyrrhetinic acid against non-small cell lung cancer.

Rasha Irshad, Nafis Raj, Gamal A Gabr, Nikhat Manzoor, Mohammad Husain

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Review
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  3. The role of TIGIT-CD226-PVR axis in mediating T cell exhaustion and apoptosis in NSCLC.Apoptosis : an international journal on programmed cell death · 2025
    Article
  4. Article
  5. Article
  6. Review
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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

5 authors.

Rasha IrshadVirology and Oncology Lab, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India.
Nafis RajMedical Mycology Lab, Department of Biosciences, Jamia Millia Islamia, New Delhi, India.
Gamal A GabrDepartment of Pharmacology and Toxicology, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al- Kharj, Saudi Arabia.
Nikhat ManzoorMedical Mycology Lab, Department of Biosciences, Jamia Millia Islamia, New Delhi, India.
Mohammad HusainVirology and Oncology Lab, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-small cell lung cancer (NSCLC) is one of the most malignant types of cancer with soaring incidence rates worldwide, attributed to its heterogeneity and complex etiology. Evidently, alternative anti-cancer therapies comprising traditional medicines and natural products have gained attention for their ability to act as chemopreventive agents with minimal toxicities, either alone or in combination. Accumulating studies have substantiated the inevitability of network pharmacology studies for effectively mapping molecular targets of natural products against multifaceted diseases, including cancer. The 18α-Glycyrrhetinic acid (18α-GA), a triterpenoid found in licorice plants, has shown promising medicinal properties, although, its mechanism of action against NSCLC yet remains elusive. The present study was conducted to explore the anti- NSCLC potential of 18α-GA, employing integrative network pharmacology, molecular docking, and experimental research. Initially, network analysis revealed 181 common targets of 18α-GA in NSCLC as shown in the "compound-target- disease" network employing

Indexed as

18α-Glycyrrhetinic acidapoptosisEGFR-PI3K/AKT pathwaynetwork pharmacologyNSCLCsurvival analysistriterpenoid

Identifiers

PMID36313358
PMCPMC9596789

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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.