Evidence map›Paper›PMID 35909589›Full record

ArticleContrast media & molecular imaging2022

Network Pharmacology Integrated Molecular Docking to Explore the Mechanism of Blister Beetle Therapy for Lung Adenocarcinoma.

Shoujun Deng, Ying Mao, Heng Li, Gaofeng Li

Abstract read
In one paragraph

Article in Contrast media & molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Shoujun DengDepartment of Thoracic Surgery II, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming 650118, China.
Ying MaoDepartment of Thyroid Breast Surgery, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, China.
Heng LiDepartment of Thoracic Surgery II, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming 650118, China.
Gaofeng LiDepartment of Thoracic Surgery II, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming 650118, China.ORCID 0000-0002-6685-2172

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) is one of the major causes of cancer death in the world. Studies show that the effective anticancer component in blister beetles is cantharidin, which can improve chemotherapy efficacy, median survival, and prognosis of LUAD. However, the antitumor mechanism of blister beetles has not been fully clarified. This study aimed to identify the key targets of the treatment of LUAD by blister beetles based on the principle of network pharmacology. An integrated approach including network pharmacology and a molecular docking technique was conducted, which mainly comprises target prediction, weighted gene correlation network analysis (WGCNA) analysis, network construction, gene ontology, and pathway enrichment analysis. 35 key targets were obtained and significantly associated with response to external stimuli, collagen binding, cyclin binding, organic acid binding, pyruvate metabolism, glycolysis, and amino acid biosynthesis pathways. Both LASSO regression and the RF model had a high predictive ability, and 9 candidate genes were screened, among which BIRC5 and PLK1 were the key targets for the treatment of LUAD by using blister beetles and showed significant survival significance. Cantharidin exerts its antitumor effects through 8 targets in 32 pathways, while BIRC5 and PLK1 have obvious survival significance.

Indexed as

Adenocarcinoma of LungColeopteraLung NeoplasmsAnimalsCantharidinMolecular Docking SimulationNetwork PharmacologyCantharidin

Identifiers

PMID35909589
PMCPMC9303499

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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.