Evidence map›Paper›PMID 35041152›Full record

ArticleBreast cancer (Tokyo, Japan)2022

Multi-time scale transcriptomic analysis on the dynamic process of tamoxifen resistance development in breast cancer cell lines.

Qiuhong Zeng, Xiaofang Lin, Huadong Chen, Yixin Yan, Xianlong Wang

Abstract read
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In one paragraph

Article in Breast cancer (Tokyo, Japan), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 9% 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

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4 · The record

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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.

Qiuhong ZengKey Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China.
Xiaofang LinKey Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China.
Huadong ChenKey Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China.
Yixin YanKey Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China.
Xianlong WangKey Laboratory of Medical Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350122, China. wang.xianlong@139.com.ORCID http://orcid.org/0000-0001-8195-2027
Fujian Medical University · CN

Funding

Fujian Medical University XRCZX2017001Natural Science Foundation of Fujian Province 2019J01294
6 · The paper itself

Abstract

backgroundApproximately 30% of breast cancer patients develop endocrine resistance after tamoxifen therapy. There still lacks a comprehensive understanding on the mechanism of tamoxifen resistance. This study aims to explore the dynamic process of ER + breast cancer resistance to tamoxifen through the time course transcriptomic analysis.

methodsThe transcriptome profiles of human breast cancer cell line MCF-7 treated with tamoxifen at different time scales were collected from LINCS, SRA and GEO databases. Differentially expressed genes (DEGs) were identified in the short-term tamoxifen treatment and tamoxifen-resistant cell lines. The time course analysis was used to explore the dynamic development of tamoxifen resistance using the transcriptome profiles of tamoxifen-cultured MCF-7 for 1-12 weeks.

resultsAfter the short-term treatment of MCF-7 with tamoxifen for 6 h or 24 h, the expression level of gene PRSS23 was significantly reduced. However, its expression recovered in the resistant cell lines. The time course analysis identified 9 clusters of the DEGs based on the temporal trend of their expression levels. Gene PRSS23 belongs to cluster 2 in which the expression levels were significantly down-regulated in the first 4 weeks but gradually recovered afterwards. Functional enrichment analysis of the DEGs in cluster 2 showed that they are significantly enriched in DNA replication, mismatch repair and cell cycle pathways. Their specific role in the resistance development needs to be further explored. The protein-protein interaction network analysis indicates that gene PRSS23 participates in the drug resistance by regulating multiple tamoxifen drug targets.

conclusionsThe acquired drug resistance in ER + breast cancer is a complex and dynamic biological process. PRSS23 plays an important role in the development of resistance and is a potential target for overcoming resistance.

Indexed as

Breast NeoplasmsTamoxifenAntineoplastic Agents, HormonalCell LineCell Line, TumorDrug Resistance, NeoplasmFemaleGene Expression Regulation, NeoplasticHumansMCF-7 CellsTranscriptomeAntineoplastic Agents, HormonalTamoxifenDrug resistanceER+ breast cancerGene PRSS23Time course analysis

Identifiers

PMID35041152
OpenAlexW4205621867

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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.