Evidence map›Paper›PMID 39770551›Full record

ArticlePharmaceuticals (Basel, Switzerland)2024

Single-Cell RNA Sequencing, Cell Communication, and Network Pharmacology Reveal the Potential Mechanism of

Jiayi Jiang, Haitao Wu, Xikun Jiang, Qing Ou, Zhanpeng Gan, Fangfang Han, Yongming Cai

Abstract read
In one paragraph

Article in Pharmaceuticals (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Flavonoid Extract ofNutrients · 2025
    Article
  5. 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

7 authors.

Jiayi JiangSchool of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China.ORCID 0009-0009-6618-7596
Haitao WuSchool of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China.
Xikun JiangSchool of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China.ORCID 0009-0006-1130-9283
Qing OuSchool of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China.
Zhanpeng GanSchool of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China.
Fangfang HanSchool of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China.
Yongming CaiSchool of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China.

Funding

Guangdong Medical Products Administration 2024ZDZ10
6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC), a prevalent form of primary liver malignancy, arises from liver-specific hepatocytes.

methodsActive ingredients of Climbing senecio were collected from four online databases and mapped to relevant target databases to obtain predicted targets. After recognizing the key pathways through which Climbing senecio acts in HCC. Gene expression data from GSE54238 Underwent differential expression and weighted gene correlation network analyses to identify HCC-related genes. The "Climbing senecio-Hepatocellular Carcinoma Targets" network was constructed using Cytoscape 3.10.1 software, followed by topology analysis to identify core genes. The expression and distribution of key targets were evaluated, and the differential expression of each key target between normal and diseased samples was calculated. Moreover, single-cell data from the Gene Expression Omnibus (GSE202642) were used to assess the distribution of Climbing senecio's bioactive targets within major HCC clusters. An intersection analysis of these clusters with pharmacological targets and HCC-related genes identified Climbing senecio's primary targets for this disease. Cell communication, receiver operating characteristic (ROC)analysis, survival analysis, immune filtration analysis, and molecular docking studies were conducted for detailed characterization.

resultsEleven components of Climbing senecio were identified, along with 520 relevant targets, 300 differentially expressed genes, and 3765 co-expression module genes associated with HCC.

conclusionsThis study revealed that Climbing senecio may target multiple pathways and genes in the process of regulating HCC and exert potential drug effects through a multi-target mechanism, which provides a new idea for the treatment of HCC. However, the research is predicated on network database analysis and bioinformatics, offering insights into HCC therapeutic potential while emphasizing the need for further validation.

Indexed as

FOShepatocellular carcinomanetwork pharmacologySenecio Scandens Buch.-HamSRC

Identifiers

PMID39770551
PMCPMC11676315

What OpenQuestion holds

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LicenceCC BY
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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.