The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survival
Abstract Background 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 co...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-07-01
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| Series: | BMC Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12916-023-02960-1 |
| _version_ | 1797769418620534784 |
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| author | Zi-An Xia Can Lu Can Pan Jia Li Jun Li Yitao Mao Lunquan Sun Jiang He |
| author_facet | Zi-An Xia Can Lu Can Pan Jia Li Jun Li Yitao Mao Lunquan Sun Jiang He |
| author_sort | Zi-An Xia |
| collection | DOAJ |
| description | Abstract Background 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. Methods 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. Results 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. Conclusions 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. |
| first_indexed | 2024-03-12T21:08:45Z |
| format | Article |
| id | doaj.art-285c7edfa62c41228d226bef30b3f707 |
| institution | Directory Open Access Journal |
| issn | 1741-7015 |
| language | English |
| last_indexed | 2024-03-12T21:08:45Z |
| publishDate | 2023-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medicine |
| spelling | doaj.art-285c7edfa62c41228d226bef30b3f7072023-07-30T11:17:30ZengBMCBMC Medicine1741-70152023-07-0121111810.1186/s12916-023-02960-1The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survivalZi-An Xia0Can Lu1Can Pan2Jia Li3Jun Li4Yitao Mao5Lunquan Sun6Jiang He7Department of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South UniversityDepartment of Pathology, Xiangya Hospital, Central South UniversitySchool of Clinical Medicine, Hunan University of Traditional Chinese MedicineDepartment of Emergency, Xiangya Hospital, Central South UniversityDepartment of Nuclear Medicine, Peking University Shenzhen HospitalDepartment of Radiology, Xiangya Hospital, Central South UniversityNational Clinical Research Center for Geriatric Disorders, XiangyaHospital, Central South UniversityNational Clinical Research Center for Geriatric Disorders, XiangyaHospital, Central South UniversityAbstract Background 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. Methods 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. Results 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. Conclusions 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.https://doi.org/10.1186/s12916-023-02960-1Large-scale data analysisTumour-infiltrating lymphocytesCD103LAG3ImmunotherapyChemotherapy |
| spellingShingle | Zi-An Xia Can Lu Can Pan Jia Li Jun Li Yitao Mao Lunquan Sun Jiang He The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survival BMC Medicine Large-scale data analysis Tumour-infiltrating lymphocytes CD103 LAG3 Immunotherapy Chemotherapy |
| title | The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survival |
| title_full | The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survival |
| title_fullStr | The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survival |
| title_full_unstemmed | The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survival |
| title_short | The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survival |
| title_sort | expression profiles of signature genes from cd103 lag3 tumour infiltrating lymphocyte subsets predict breast cancer survival |
| topic | Large-scale data analysis Tumour-infiltrating lymphocytes CD103 LAG3 Immunotherapy Chemotherapy |
| url | https://doi.org/10.1186/s12916-023-02960-1 |
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