Evidence map›Paper›PMID 33414839›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2020

The Shuganhuazheng Formula in Triple-Negative Breast Cancer: A Study Based on Network Pharmacology and In Vivo Experiments.

Bo Wang, Rui Fei, Yan Yang, Niancai Jing, Yi Lu, Hongyu Xiao, Jili Yang, Yue Zhang

Abstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

8 authors.

Bo WangChangchun University of Chinese Medicine, Changchun, Jilin 130117, China.
Rui FeiCell Biology Department, School of Basic Medicine, Jilin University, Changchun, Jilin 130021, China.
Yan YangDepartment of Integrated Chinese and Western Medicine, Jilin Cancer Hospital, Changchun, Jilin 130000, China.
Niancai JingDepartment of Integrated Chinese and Western Medicine, Jilin Cancer Hospital, Changchun, Jilin 130000, China.
Yi LuDepartment of Integrated Chinese and Western Medicine, Jilin Cancer Hospital, Changchun, Jilin 130000, China.
Hongyu XiaoDepartment of Integrated Chinese and Western Medicine, Jilin Cancer Hospital, Changchun, Jilin 130000, China.
Jili YangDepartment of Integrated Chinese and Western Medicine, Jilin Cancer Hospital, Changchun, Jilin 130000, China.
Yue ZhangDepartment of Integrated Chinese and Western Medicine, Jilin Cancer Hospital, Changchun, Jilin 130000, China.ORCID https://orcid.org/0000-0001-8737-2373

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is the most common cancer in women. Among breast cancer subtypes, triple-negative breast cancer (TNBC) has the highest degree of malignancy and the worst prognosis. The Shuganhuazheng formula (SGHZF) is a traditional Chinese herbal formula for the treatment of TNBC, but the mechanism of SGHZF in the treatment of TNBC remains unclear. In this study, the therapeutic effect and mechanism of SGHZF against TNBC were preliminarily determined based on in vivo experimental verification and network pharmacology. In terms of therapeutic effects, the antitumour effect was verified by measuring and calculating tumour volume, and the expression of proto-oncogene c-Myc was verified by PCR. In terms of the mechanism, potential therapeutic targets were identified by overlapping the SGHZF-related and TNBC-related targets. After comprehensively analysing the results of the protein-protein interaction (PPI), gene ontology (GO) function, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, Akt and HIF-1

Identifiers

PMID33414839
PMCPMC7752265

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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.