Evidence map›Paper›PMID 37274057›Full record

ArticleBreast cancer (Dove Medical Press)2023

Transcriptome Profiling Analysis of Breast Cancer Cell MCF-7 Treated by Sesamol.

Jiafa Wu, Dongping Luo, Jiayun Xu

Open access · goldAbstract read
In one paragraph

Article in Breast cancer (Dove Medical Press), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 19% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 1 country.

Jiafa WuSchool of Food and Bioengineering, Henan University of Science and Technology, Luoyang, People's Republic of China.ORCID 0000-0002-7308-6736
Dongping LuoThe First Affiliated Hospital, Henan University of Science and Technology, Luoyang, People's Republic of China.
Jiayun XuThe First Affiliated Hospital, Henan University of Science and Technology, Luoyang, People's Republic of China.
First Affiliated Hospital of Henan University of Science and Technology · CNHenan University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Breast cancer is a highly malignant tumor that affects a large number of women worldwide. Sesamol, a natural compound, has been shown to exhibit inhibitory effects on various tumors, including breast cancer. However, the underlying mechanism of its action has not been fully explored. In this study, we aimed to investigate the effect of sesamol on the transcriptome of MCF-7 breast cancer cells, in order to better understand its potential as an anti-cancer agent. Methods: The transcriptome profiles of MCF-7 breast cancer cells treated with sesamol were analyzed using Illumina deep-sequencing. The differentially expressed genes (DEGs) between the control and sesamol-treated groups were identified, and GO and KEGG pathway analyses of these DEGs were conducted using ClueGO. Protein-protein interaction (PPI) network of DEGs was mapped on STRING database and visualized by Cytoscape software. Hub genes in the network were screened by Cytohubba plugin of Cytoscape. Prognostic values of hub genes were analyses by the online Kaplan-Meier plotter and validated by qRT-PCR in MCF-7 cells. Results: The results of the study showed that sesamol treatment had a significant effect on the transcriptome of MCF-7 cells, with a total of 351 DEGs identified. Functional enrichment analyses of DEGs revealed their involvement in extracellular matrix (ECM) remodeling, fatty acid metabolism and monocyte chemotaxis. The protein-protein interaction (PPI) network analysis of DEGs resulted in the identification of 10 hub genes, namely Conclusion: Sesamol may play important roles in extracellular matrix (ECM) remodeling, fatty acid metabolism and cell cycle of MCF-7.

Indexed as

breast cancer cellsdifferentially expressed genesGO and KEGG pathway analysessesamoltranscriptome

Identifiers

PMID37274057
PMCPMC10238551
OpenAlexW4378716938

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.