ArticleBreast cancer (Tokyo, Japan)2021
A novel immune-related prognostic index for predicting breast cancer overall survival.
Article in Breast cancer (Tokyo, Japan), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 9 citations in OpenAlex.
- Dexmedetomidine and dezocine targets (NR1H3 and ADRB1) are potential prognostic biomarkers for breast cancer.Discover oncology · 2025Article
- Predicting survival and immune status of breast cancer patients based on prognostic features related to PANoptosis.Discover oncology · 2025Article
- Article
- Identification of a 5-gene-risk score model for predicting luminal A-invasive lobular breast cancer survival.Genetica · 2022Article
- Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis.Human genomics · 2022Article
- Low expression of NR1H3 correlates with macrophage infiltration and indicates worse survival in breast cancer.Frontiers in genetics · 2022Article
- Identification and Verification of Immune-Related Genes Prognostic Signature Based on ssGSEA for Adrenocortical Carcinoma (ACC).International journal of general medicine · 2022Article
- Integrated Analysis of Copy Number Variation, Microsatellite Instability, and Tumor Mutation Burden Identifies an 11-Gene Signature Predicting Survival in Breast Cancer.Frontiers in cell and developmental biology · 2021Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
purposeTo find immune-related genes with prognostic value in breast cancer, and construct a prognostic risk assessment model to make a more accurate assessment. Moreover, looking for potential immune markers for breast cancer immunotherapy.
methodsThe breast cancer (BC) data were retrieved from The Cancer Genome Atlas (TCGA) database as a training set. Through the Weighted gene co-expression network analysis (WGCNA), Kaplan-Meier (KM) analysis, lasso regression analysis and stepwise backward Cox regression analysis, screening for prognosis-related immune genes, a prognostic index was built, and external validation with two data sets of Gene Expression Omnibus (GEO) database was performed. Transcription factor (TF) regulatory network was constructed to identify key transcription factors that regulate prognostic immune genes. Gene set enrichment analysis (GSEA) was used to explore the signal pathways differences between high and low-risk groups, estimate package and TIMER database were used to evaluate the relationship between risk score and tumor immune microenvironment.
resultsWe obtained 10 prognosis-related immune genes, and the index showed accurate prognostic value. We also identified 7 prognostic transcription factors. Multiple signaling pathways that inhibit tumor progression were enriched in the low-risk group, and risk score was significantly negatively related to the degree of immune infiltration and the expression level of immune checkpoint genes.
conclusionWe successfully constructed an independent prognostic index, which not only has a stronger predictive ability than the tumor pathological stage, but also can reflect the immune infiltration of breast cancer patients.
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