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The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survival

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机构: [1]Department of Integrated Traditional Chinese and Western Medicine, XiangyaHospital, Central South University, Changsha 410008, China [2]National ClinicalResearch Center for Geriatric Disorders, XiangyaHospital, Central South University,Changsha 410008, China [3]Department of Pathology, Xiangya Hospital,Central South University, Changsha 410078, China [4]School of Clinical Medicine,Hunan University of Traditional Chinese Medicine, Changsha 410208,China [5]Department of Emergency, Xiangya Hospital, Central South University,Changsha 410008, China [6]Department of Nuclear Medicine, Peking UniversityShenzhen Hospital, Guangdong 518036, China [7]Department of Radiology,Xiangya Hospital, Central South University, Changsha 410078, China [8]Departmentof Oncology, Xiangya Cancer Center, XiangyaHospital, Central SouthUniversity, Changsha 410008, China [9]Key Laboratory of Molecular RadiationOncology Hunan Province, Changsha 410008, China [10]Hunan InternationalScience and Technology Collaboration Base of Precision Medicine for Cancer,Changsha 410008, China [11]Center for Molecular Imaging of Central, SouthUniversity, Xiangya Hospital, Changsha 410008, China
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关键词: Large-scale data analysis Tumour-infiltrating lymphocytes CD103 LAG3 Immunotherapy Chemotherapy

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Tumour-infiltrating lymphocytes (TILs), including T and B cells, have been demonstrated to be associated with tumour progression. However, the different subpopulations of TILs and their roles in breast cancer remain poorly understood. Large-scale analysis using multiomics data could uncover potential mechanisms and provide promising biomarkers for predicting immunotherapy response.Single-cell transcriptome data for breast cancer samples were analysed to identify unique TIL subsets. Based on the expression profiles of marker genes in these subsets, a TIL-related prognostic model was developed by univariate and multivariate Cox analyses and LASSO regression for the TCGA training cohort containing 1089 breast cancer patients. Multiplex immunohistochemistry was used to confirm the presence of TIL subsets in breast cancer samples. The model was validated with a large-scale transcriptomic dataset for 3619 breast cancer patients, including the METABRIC cohort, six chemotherapy transcriptomic cohorts, and two immunotherapy transcriptomic cohorts.We identified two TIL subsets with high expression of CD103 and LAG3 (CD103+LAG3+), including a CD8+ T-cell subset and a B-cell subset. Based on the expression profiles of marker genes in these two subpopulations, we further developed a CD103+LAG3+ TIL-related prognostic model (CLTRP) based on CXCL13 and BIRC3 genes for predicting the prognosis of breast cancer patients. CLTRP-low patients had a better prognosis than CLTRP-high patients. The comprehensive results showed that a low CLTRP score was associated with a high TP53 mutation rate, high infiltration of CD8 T cells, helper T cells, and CD4 T cells, high sensitivity to chemotherapeutic drugs, and a good response to immunotherapy. In contrast, a high CLTRP score was correlated with a low TP53 mutation rate, high infiltration of M0 and M2 macrophages, low sensitivity to chemotherapeutic drugs, and a poor response to immunotherapy.Our present study showed that the CLTRP score is a promising biomarker for distinguishing prognosis, drug sensitivity, molecular and immune characteristics, and immunotherapy outcomes in breast cancer patients. The CLTRP could serve as a valuable tool for clinical decision making regarding immunotherapy.© 2023. The Author(s).

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大类 | 1 区 医学
小类 | 1 区 医学:内科
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大类 | 1 区 医学
小类 | 1 区 医学:内科
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Q1 MEDICINE, GENERAL & INTERNAL
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Q1 MEDICINE, GENERAL & INTERNAL

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第一作者机构: [1]Department of Integrated Traditional Chinese and Western Medicine, XiangyaHospital, Central South University, Changsha 410008, China [2]National ClinicalResearch Center for Geriatric Disorders, XiangyaHospital, Central South University,Changsha 410008, China
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通讯机构: [2]National ClinicalResearch Center for Geriatric Disorders, XiangyaHospital, Central South University,Changsha 410008, China [8]Departmentof Oncology, Xiangya Cancer Center, XiangyaHospital, Central SouthUniversity, Changsha 410008, China [9]Key Laboratory of Molecular RadiationOncology Hunan Province, Changsha 410008, China [10]Hunan InternationalScience and Technology Collaboration Base of Precision Medicine for Cancer,Changsha 410008, China [11]Center for Molecular Imaging of Central, SouthUniversity, Xiangya Hospital, Changsha 410008, China
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