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Updated: Jul 26, 2026
Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
A bioinformatic analysis found low expression and clinical significance of ATF4 in breast cancer
Lujing Shao1, Zhounan Zhu1, Xinyan Jia2
1Department of Oncology, East Hospital Affiliated to Tongji University, Tongji University School of Medicine, Tongji University, Shanghai, 200092, PR China.
Background:
Activating Transcription Factor 4 (ATF4) expression exhibits differential patterns across different types of tumors. Besides, the pathogenesis of breast cancer is complex, and the exact relationship between ATF4 and ATF4 remains uncertain.
Methods:
The analysis of ATF4 expression was conducted by utilizing The Cancer Genome Atlas (TCGA) pan-cancer data, while the gene expression profile of breast cancer was checked by the comprehensive database-Gene Expression Omnibus database. In order to gain a more comprehensive understanding of the specific cell types that exhibit ATF4 expression within the microenvironment of breast cancer, we conducted a single-cell analysis of ATF4 using two distinct datasets of human breast cancer (GSE114717 and GSE11088, respectively). The spatial distribution of ATF4 within a tissue was demonstrated based on datasets obtained from the Human Protein Atlas (HPA) and SpatialDB. The clinical prognostic significance of ATF4 was assessed by analyzing clinical survival data obtained from TCGA, GSE4830, and GSE25055 datasets. We used the R package clusterProfiler to carry out an enrichment analysis of ATF4. We assessed how ATF4 impacts the growth and movement of breast cancer cell lines. We manipulated ATF4 levels using plasmid transfection techniques.
Results:
The expression of ATF4 was found to be suboptimal and demonstrated a significant correlation with enhanced disease-specific survival (p = 0.012) and overall survival (p = 0.032) in breast cancer as well as other malignancies. We conducted an analysis to investigate the interaction between the infiltration level of immune cells and the expression of ATF4, using samples obtained from TCGA with known immune cell infiltration scores. Furthermore, a notable positive correlation exists between the elevated expression of ATF4 and immune-related genomes, specifically those associated with chemokine as well as immunity. Subsequent examination revealed a notable augmentation in the cytodifferentiation of T cells into regulatory T (Treg) cells within tissues exhibiting elevated levels of ATF4 expression. ATF4 exhibits notable upregulation in the MDA-MB-231 cell, thereby exerting a substantial impact on cell proliferation and migration upon its knockdown. Conversely, the overexpression of ATF4 in the MCF7 Luminal A breast cancer cell line can also modulate cellular function.
Conclusions:
Our study suggests that ATF4 helps T cells differentiate into Treg cells in breast cancer. ATF4 can represent a clinically useful biomarker to predict the overall survival rate, especially in patients with different subtypes of breast cancer. Provide certain guidance value for the development of targeted drugs or inhibitors targeting ATF4.
Insights
Activating Transcription Factor 4 (ATF4) expression is linked to better survival in breast cancer patients. This protein influences T cell differentiation and may serve as a biomarker for targeted therapies.
Area of Science:
- Oncology
- Immunology
- Molecular Biology
Background:
- Activating Transcription Factor 4 (ATF4) shows varied expression across tumor types, but its role in breast cancer pathogenesis is unclear.
- The complex nature of breast cancer necessitates a deeper understanding of ATF4's function and interactions within the tumor microenvironment.
Purpose of the Study:
- To investigate the expression patterns and prognostic significance of ATF4 in breast cancer.
- To explore the relationship between ATF4, immune cell infiltration, and T cell differentiation in breast cancer.
- To assess the impact of ATF4 on breast cancer cell proliferation and migration.
Main Methods:
- Utilized The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases for ATF4 expression analysis.
- Performed single-cell analysis on human breast cancer datasets (GSE114717, GSE11088) to identify ATF4-expressing cell types.
- Assessed ATF4's spatial distribution using Human Protein Atlas (HPA) and SpatialDB data.
- Analyzed clinical survival data from TCGA and other datasets (GSE4830, GSE25055) to determine prognostic value.
- Conducted enrichment analysis, immune cell infiltration analysis, and in vitro experiments manipulating ATF4 levels in breast cancer cell lines.
Main Results:
- Lower ATF4 expression correlated with poorer survival, while higher expression was linked to enhanced disease-specific and overall survival in breast cancer and other malignancies.
- Elevated ATF4 expression showed a positive correlation with immune-related genes and promoted T cell differentiation into regulatory T (Treg) cells.
- ATF4 significantly impacted proliferation and migration in MDA-MB-231 cells upon knockdown and modulated cellular function in MCF7 cells upon overexpression.
Conclusions:
- ATF4 plays a role in T cell differentiation into Treg cells within the breast cancer microenvironment.
- ATF4 serves as a potential prognostic biomarker for predicting overall survival in breast cancer patients across different subtypes.
- Findings provide a basis for developing targeted therapies or inhibitors focused on ATF4.
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