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Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels T cell-related prognostic risk model and tumor immune microenvironment modulation in triple-negative breast cancer

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机构: [1]School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China [2]National Cancer Center/National Clinical Research Center for Cancer/Chinese Medicine Department of the Caner Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China [3]Department of Medical Oncology, The Fourth Hospital of Hebei Medical University, Hebei Tumor Hospital,Shijiazhuang, 050000, China [4]Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu,610054, China [5]School of Management, Beijing University of Chinese Medicine, Beijing, 100029, China [6]China-Japan Friendship Hospital, Beijing, 100029, China
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关键词: Single-cell RNA sequencing Bulk RNA sequencing Triple negative breast cancer T cells Tumor immune environment Prognostic risk model

摘要:
Triple negative breast cancer (TNBC) is an aggressive and fatal malignancy. The current success of tumor immunotherapy has focused attention on intermediate T-cell subsets and the tumor microenvironment, which are essential for activation of the anti-tumor response. Therefore, both areas require further research to accelerate progress in developing tailored immunotherapeutic approaches for patients with TNBC.We obtained scRNA-seq data of TNBC from the GEO database. A multiplex strategy was used to analyze and identify the T-cell heterogeneity of TNBC. By combining the METABRIC and GEO databases, a prognostic risk model for T-cell marker genes was constructed and validated. In addition, the immune-infiltrating cells of TNBC was analyzed using CIBERSORT, and the association between the risk model and response to immunotherapy was investigated.Based on scRNA-seq data, 25,932 cells were identified for multiple analyzes. T cells were studied with a focus on 2 subtypes, including CD8+ and CD4+. There were also communication relationships between T cells and multiple cell types. The results of the enrichment analysis showed that the T-cell marker genes were focused in pathways related to the immune system. In addition, OPTN, TMEM176A, PKM and HES1 deserve attention as prognostic markers in TNBC. The immune infiltration results showed that the high-risk group had significant immune cell infiltration and immunosuppression status.This study provides a resource for understanding T-cell heterogeneity and the associated prognostic risk model for TNBC. The results show that the model helps predict prognosis and response to treatment in breast cancer.Copyright © 2023. Published by Elsevier Ltd.

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出版当年[2023]版:
大类 | 2 区 医学
小类 | 1 区 生物学 1 区 数学与计算生物学 2 区 计算机:跨学科应用 2 区 工程:生物医学
最新[2025]版:
大类 | 2 区 医学
小类 | 1 区 数学与计算生物学 2 区 生物学 2 区 计算机:跨学科应用 2 区 工程:生物医学
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出版当年[2023]版:
Q1 BIOLOGY Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Q1 ENGINEERING, BIOMEDICAL Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
最新[2023]版:
Q1 BIOLOGY Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Q1 ENGINEERING, BIOMEDICAL Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2023版] 出版当年五年平均 出版前一年[2022版]

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第一作者机构: [1]School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
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