ArticlePeerJ2021
Establishment and validation of an individualized macrophage-related gene signature to predict overall survival in patients with triple negative breast cancer.
Article in PeerJ, 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, 10 citations in OpenAlex.
- High-dose irradiation promotes macrophage-mediated engulfment of triple-negative breast cancer through M1 polarization via the IKZF1-CCL5 axis.Cell communication and signaling : CCS · 2026Article
- Integration of Single-cell and Bulk Transcriptome Analyses Unravels a Macrophage-based Gene Signature for Prognostication and Treatment in Triple-negative Breast Cancer.International journal of medical sciences · 2026Article
- The role of Phafin proteins in cell signaling pathways and diseases.Open life sciences · 2024Review
- Local administration of liposomal-based Plekhf1 gene therapy attenuates pulmonary fibrosis by modulating macrophage polarization.Science China. Life sciences · 2023Article
- A novel conditional survival nomogram for monitoring real-time prognosis of non-metastatic triple-negative breast cancer.Frontiers in endocrinology · 2023Article
- Overview of triple negative breast cancer prognostic signatures in the context of data science-driven clinico-genomics research.Annals of translational medicine · 2022Article
- Identification of immune-related biomarkers for predicting neoadjuvant chemotherapy sensitivity in HER2 negative breast cancer via bioinformatics analysis.Gland surgery · 2022Article
- Necroptosis-Related LncRNAs Signature and Subtypes for Predicting Prognosis and Revealing the Immune Microenvironment in Breast Cancer.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRecently, researchers have classified highly heterogeneous triple negative breast cancer (TNBC) into different subtypes from different perspectives and investigated the characteristics of different subtypes to pursue individualized treatment. With the increase of immunotherapy and its preliminary application in TNBC treatment, the value of immune-related strategies in the treatment of TNBC has been initially reflected. Based thereon, this study plans to classify and further explore TNBC from the perspective of immune cell infiltration.
methodThe fractions of immune cells of TNBC patients were assessed by six immune component analysis methods in The Cancer Genome Atlas (TCGA) database. Hub genes significantly related to poor prognosis were verified by weighted gene co-expression network analysis (WGCNA) analysis, Lasso analysis, and univariate KM analysis. Two cohorts of TNBC patients with complete prognosis information were collected for validation analysis. Finally, the Genomics of Drug Sensitivity in Cancer (GDSC) database was adopted to ascertain the sensitivity differences of different populations based on hub-gene grouping to different chemotherapy drugs.
resultsFive hub genes (CD79A, CXCL13, IGLL5, LHFPL2, and PLEKHF1) of the key co-expression gene module could divide TNBC patients into two groups (Cluster A and Cluster B) based on consistency cluster analysis. The patients with Cluster A were responsible for significantly worse prognosis than the patients with Cluster B (
conclusionThis study found five hub prognostic genes associated with macrophages, and a prognostic model was established to predict the survival of TNBC patients. Finally, these five genes were related to gemcitabine resistance in TNBC patients.
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