Evidence map›Paper›PMID 35116374›Full record

ArticleTranslational cancer research2021

Identification of key genes involved in tamoxifen-resistant breast cancer using bioinformatics analysis.

Xiaopeng Wang, Shixia Wang

Open access · diamondAbstract read
In one paragraph

Article in Translational cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

12 citing papers in PubMed, 16 citations in OpenAlex.

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  6. ONECUT2 is a druggable driver of luminal to basal breast cancer plasticity.Cellular oncology (Dordrecht, Netherlands) · 2025
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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

2 authors at 1 institution in 1 country.

Xiaopeng WangDepartment of Outpatient and Emergency, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Shixia WangDepartment of Outpatient and Emergency, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Tianjin Medical University Cancer Institute and Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe purpose of the present study was to investigate the molecular mechanisms of tamoxifen resistance in breast cancer and to identify potential targets for antitamoxifen resistance.

methodsDifferentially expressed genes (DEGs) in tamoxifen-resistant and tamoxifen-sensitive breast cancer cells were assessed using the GSE67916 dataset acquired from the Gene Expression Omnibus database. Gene ontology (GO) and pathway enrichment analyses were applied to investigate the functions and pathways of the DEGs. Subsequently, the protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING), and subnetworks were further analyzed by Molecular Complex Detection (MCODE). The PPI network and subnetworks were visualized using Cytoscape software.

resultsIn total, 438 DEGs were identified, of which 300 were upregulated and 138 were downregulated. The DEGs were significantly enriched in the protein binding, cellular response to estradiol stimulus, and immune response GO terms while the most significant pathways included the mitogen-activated protein kinase (MAPK) signaling pathway in cancer. The PPI network of DEGs was constructed with 288 nodes and 629 edges, and 2 subnetworks were screened out from the entire network.

conclusionsA number of significant hub DEGs were identified based on their degree of connectivity in the PPI network, , included

Indexed as

bioinformatics analysisbreast cancerdifferentially expressed genes (DEGs)protein-protein interaction (PPI) networkTamoxifen resistance

Identifiers

PMID35116374
PMCPMC8798269
OpenAlexW3215363264

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.