ArticleFrontiers in immunology2024
A new 4-gene-based prognostic model accurately predicts breast cancer prognosis and immunotherapy response by integrating WGCNA and bioinformatics analysis.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed, 16 citations in OpenAlex.
- DNA polymerase theta (Polθ): a novel candidate for targeted cancer therapy.Cancer biology & therapy · 2026Review
- Single-Cell sequencing investigation of endoplasmic reticulum stress-related genes in gastric cancer prognostic models and identification of NOX5 as a novel therapeutic target.Translational oncology · 2026Article
- Identification of a biologically coherent three gene immune signature predictive of immunotherapy benefit in gastric adenocarcinoma.Discover oncology · 2026Article
- Exploration of precise classification and therapeutic targets of breast cancer based on genes related to neuro-cancer crosstalk.Translational oncology · 2026Article
- Identification of NETs and inflammation-related prognostic genes in breast cancer and PCR experimental validation.Frontiers in genetics · 2026Article
- Pan cancer research reveals the role of PTGDS in tumor suppression and immune regulation.NPJ precision oncology · 2025Article
- Identification of a fibroblast-derived gene signature reveals prognostic and therapeutic insights in pancreatic cancer.Clinical and experimental medicine · 2025Article
- Stromal PLAU mediates tumor progression and informs a novel therapeutic target in triple-negative breast cancer.Cancer cell international · 2025Article
- Harnessing single-cell and multi-omics insights: STING pathway-based predictive signature for immunotherapy response in lung adenocarcinoma.Frontiers in immunology · 2025Article
- PLCH1 overexpression promotes breast cancer progression and predicts poor prognosis through the ERK1/2-EGR1 axis.Frontiers in oncology · 2025Article
- Multi-cohort validation of a lipid metabolism and ferroptosis-associated index for prognosis and immunotherapy response prediction in hormone receptor-positive breast cancer.International journal of biological sciences · 2025Article
- Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outcomes.Frontiers in immunology · 2025Article
- Advancing breast cancer biomarkers: a centromere-related gene signature integrated with single-cell analysis for prognostic prediction.Frontiers in immunology · 2025Article
- Cancer-associated fibroblasts gene signature: a novel approach to survival prediction and immunotherapy guidance in colon cancer.Frontiers in immunology · 2025Article
- Article
- AGTR1: a potential biomarker associated with the occurrence and prognosis of lung adenocarcinoma.Frontiers in oncology · 2024Article
- Multi-omics analyses were combined to construct ubiquitination-related features in colon adenocarcinoma and identify ASNS as a novel biomarker.Frontiers in immunology · 2024Article
- Combining single-cell analysis and molecular docking techniques to construct a prognostic model for colon adenocarcinoma and uncovering inhibin subunit βb as a novel therapeutic target.Frontiers in immunology · 2024Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Breast cancer (BRCA) is a common malignancy in women, and its resistance to immunotherapy is a major challenge. Abnormal expression of genes is important in the occurrence and development of BRCA and may also affect the prognosis of patients. Although many BRCA prognosis model scores have been developed, they are only applicable to a limited number of disease subtypes. Our goal is to develop a new prognostic score that is more accurate and applicable to a wider range of BRCA patients. Methods: BRCA patient data from The Cancer Genome Atlas database was used to identify breast cancer-related genes (BRGs). Differential expression analysis of BRGs was performed using the 'limma' package in R. Prognostic BRGs were identified using co-expression and univariate Cox analysis. A predictive model of four BRGs was established using Cox regression and the LASSO algorithm. Model performance was evaluated using K-M survival and receiver operating characteristic curve analysis. The predictive ability of the signature in immune microenvironment and immunotherapy was investigated. Results: Our study identified a four-BRG prognostic signature that outperformed conventional clinicopathological characteristics in predicting survival outcomes in BRCA patients. The signature effectively stratified BRCA patients into high- and low-risk groups and showed potential in predicting the response to immunotherapy. Notably, significant differences were observed in immune cell abundance between the two groups. Conclusion: Our 4-BRG signature has the potential as an independent biomarker for predicting prognosis and treatment response in BRCA patients, complementing existing clinicopathological characteristics.
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