Evidence map›Paper›PMID 32572780›Full record

ArticleChinese journal of integrative medicine2021

Exploring Mechanism of Key Chinese Herbal Medicine on Breast Cancer by Data Mining and Network Pharmacology Methods.

Li-Na Yang, Zhu-Lin Wu, Zhen-Jiang Yang, Shi-Guang Li, Chen-Sheng Ouyang

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Article in Chinese journal of integrative medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 15% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Pooled it
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  11. Integration strategy of network pharmacology in Traditional Chinese Medicine: a narrative review.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2022
    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 at 1 institution in 1 country.

Li-Na YangDepartment of Oncology and Haematology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong Province, 518033, China.
Zhu-Lin WuDepartment of Oncology and Haematology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong Province, 518033, China.
Zhen-Jiang YangDepartment of Oncology and Haematology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong Province, 518033, China.
Shi-Guang LiDepartment of Oncology and Haematology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong Province, 518033, China.
Chen-Sheng OuyangDepartment of Oncology and Haematology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong Province, 518033, China. chensheng_ouyang@126.com.
Guangzhou University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo screen the key Chinese Herbal Medicines (KCHMs) against breast cancer by data mining, and analyze the potential mechanism of KCHMs using network pharmacology method.

methodsClinical prescriptions consisted of CHMs for treating breast cancer were screened, and then Traditional Chinese Medicine Inheritance Support System (TCMISS) was applied to obtain the KCHMs. Subsequently, active ingredients and corresponding target genes of KCHMs were searched by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database, and target genes of breast cancer were collected using OMIM and MalaCards. After that, the overlapping target genes of KCHMs and breast cancer were screened, and the protein-protein interaction (PPI) network was built. In addition, a network of "KCHMs-active ingredients-breast cancer-targets" was constructed by Cytoscape 3.7.1. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis were performed with Database for Annotation, Visualization and Integrated Discovery (DAVID) database to reveal the action mechanism of KCHMs.

resultsA total of 7 KCHMs were identified, whose active ingredients include quercetin, luteolin, nobiletin, kaempferol, isorhamnetin, naringenin, and be-ta-sitosterol, etc. Based on protein-protein interaction analysis, core targets were ESR1, MYC, CCND1, EGFR, CASP3, ERBB2, etc. Several KEGG pathways (e.g, PI3K-Akt, p53, ErbB, and HIF-1 signaling pathways) were found.

conclusionBased on the combination of the data mining method and network pharmacology approach, the therapeutic effect of KCHMs on breast cancer may be realized by acting on target genes and signaling pathways related to the formation and progression of breast cancer.

Indexed as

Breast NeoplasmsDrugs, Chinese HerbalData MiningFemaleHumansMedicine, Chinese TraditionalNetwork PharmacologyPhosphatidylinositol 3-KinasesDrugs, Chinese HerbalPhosphatidylinositol 3-Kinasesbreast cancerChinese herbal medicineChinese medicinepharmacology

Identifiers

PMID32572780
OpenAlexW3036214772

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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.