ArticleScientific reports2022
Role of androgen receptor signaling pathway-related lncRNAs in the prognosis and immune infiltration of breast cancer.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 14 citations in OpenAlex.
- The role of long non-coding RNAs in NK cell biology and diseases.Genes & diseases · 2026Review
- Integrative Genomic Analysis Identifies MAGT1 as a Key Regulator of Proliferation and Poor Prognosis in Breast Cancer.Human mutation · 2026Article
- Network Pharmacology and Molecular Dynamics Identified Potential Androgen Receptor-Targeted Metabolites inInternational journal of molecular sciences · 2025Article
- Regulation of Stromal Cells by Sex Steroid Hormones in the Breast Cancer Microenvironment.Cancers · 2024Review
- Long Non-Coding RNAs, Nuclear Receptors and Their Cross-Talks in Cancer-Implications and Perspectives.Cancers · 2024Review
- Prognostic model development and clinical correlation of eight key genes in skin cutaneous melanoma.Heliyon · 2024Article
- Predicting prostate cancer progression with a Multi-lncRNA expression-based risk score and nomogram integrating ISUP grading.Non-coding RNA research · 2024Article
- Deciphering the dual roles of PHD finger proteins from oncogenic drivers to tumor suppressors.Frontiers in cell and developmental biology · 2024Review
- Endocrine nuclear receptors and long non‑coding RNAs reciprocal regulation in cancer (Review).International journal of oncology · 2024Review
- The current advances of lncRNAs in breast cancer immunobiology research.Frontiers in immunology · 2023Review
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Androgen receptor (AR) is strong association with breast cancer (BRCA). We aimed to investigate the effect of the androgen receptor signaling pathway-related long non-coding RNAs (ARSP-related lncRNAs) on the process of subtype classification and the tumor microenvironment (TME) of breast cancer (BRCA). Our study screen ARSP-related lncRNAs for the construction of a risk model. The single-sample gene set enrichment analysis (ssGSEA) method was used to detect the differences between the immune responses generated by the patients belonging to the low- and high-risk groups. The relationship between the ARSP-related lncRNAs and TME was explored following the process of cluster analysis. The univariate Cox analysis and the Lasso regression analysis method was used to screen nine of these lncRNAs to develop a risk model. It was observed that risk score could function as an independent prognostic factor, affecting the prognoses of patients suffering from BRCA. The validity of the model was assessed by analyzing the generated calibration curves and a nomogram. Additionally, the effect of the risk score on the extent of immune cell infiltration realized in TME was explored. M2 macrophages correlated positively, whereas NK cells, CD4+ T cells, and naive B cells correlated negatively with the risk score. Results obtained using the cluster analysis indicated that immune scores correlated with clustered subtypes. Finally, the risk score and cluster subtypes were analyzed to study the sensitivity of the patients toward different drugs to identify the appropriate therapeutic agents. The prognoses of patients suffering from BRCA can be accurately predicted by ARSP-related lncRNAs.
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