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A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer.

ABSTRACT: Breast cancer is a heterogeneous disease. Tumor cells and associated healthy cells form ecosystems that determine disease progression and response to therapy. To characterize features of breast cancer ecosystems and their associations with clinical data, we analyzed 144 human breast tumor and 50 non-tumor tissue samples using mass cytometry. The expression of 73 proteins in 26 million cells was evaluated using tumor and immune cell-centric antibody panels. Tumors displayed individuality in tumor cell composition, including phenotypic abnormalities and phenotype dominance. Relationship analyses between tumor and immune cells revealed characteristics of ecosystems related to immunosuppression and poor prognosis. High frequencies of PD-L1⁺ tumor-associated macrophages and exhausted T cells were found in high-grade ER⁺ and ER^- tumors. This large-scale, single-cell atlas deepens our understanding of breast tumor ecosystems and suggests that ecosystem-based patient classification will facilitate identification of individuals for precision medicine approaches targeting the tumor and its immunoenvironment.

SUBMITTER: Wagner J

PROVIDER: S-EPMC6526772 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer.

Wagner Johanna J Rapsomaniki Maria Anna MA Chevrier Stéphane S Anzeneder Tobias T Langwieder Claus C Dykgers August A Rees Martin M Ramaswamy Annette A Muenst Simone S Soysal Savas Deniz SD Jacobs Andrea A Windhager Jonas J Silina Karina K van den Broek Maries M Dedes Konstantin Johannes KJ Rodríguez Martínez Maria M Weber Walter Paul WP Bodenmiller Bernd B

Cell 20190411 5

Breast cancer is a heterogeneous disease. Tumor cells and associated healthy cells form ecosystems that determine disease progression and response to therapy. To characterize features of breast cancer ecosystems and their associations with clinical data, we analyzed 144 human breast tumor and 50 non-tumor tissue samples using mass cytometry. The expression of 73 proteins in 26 million cells was evaluated using tumor and immune cell-centric antibody panels. Tumors displayed individuality in tumor ...[more]

PMID: 30982598

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Project description:BackgroundThe internal heterogeneity of breast cancer, notably the tumor microenvironment (TME) consisting of malignant and non-malignant cells, has been extensively explored in recent years. The cells in this complex cellular ecosystem activate or suppress tumor immunity through phenotypic changes, secretion of metabolites and cell-cell communication networks. Macrophages, as the most abundant immune cells within the TME, are recruited by malignant cells and undergo phenotypic remodeling. Tumor-associated macrophages (TAMs) exhibit a variety of subtypes and functions, playing significant roles in impacting tumor immunity. However, their precise subtype delineation and specific function remain inadequately defined.MethodsThe publicly available single-cell transcriptomes of 49,141 cells from eight breast cancer patients with different molecular subtypes and stages were incorporated into our study. Unsupervised clustering and manual cell annotation were employed to accurately classify TAM subtypes. We then conducted functional analysis and constructed a developmental trajectory for TAM subtypes. Subsequently, the roles of TAM subtypes in cell-cell communication networks within the TME were explored using endothelial cells (ECs) and T cells as key nodes. Finally, analyses were repeated in another independent publish scRNA datasets to validate our findings for TAM characterization.ResultsTAMs are accurately classified into 7 subtypes, displaying anti-tumor or pro-tumor roles. For the first time, we identified a new TAM subtype capable of proliferation and expansion in breast cancer-TUBA1B+ TAMs playing a crucial role in TAMs diversity and tumor progression. The developmental trajectory illustrates how TAMs are remodeled within the TME and undergo phenotypic and functional changes, with TUBA1B+ TAMs at the initial point. Notably, the predominant TAM subtypes varied across different molecular subtypes and stages of breast cancer. Additionally, our research on cell-cell communication networks shows that TAMs exert effects by directly modulating intrinsic immunity, indirectly regulating adaptive immunity through T cells, as well as influencing tumor angiogenesis and lymphangiogenesis through ECs.ConclusionsOur study establishes a precise single-cell atlas of breast cancer TAMs, shedding light on their multifaceted roles in tumor biology and providing resources for targeting TAMs in breast cancer immunotherapy.

Project description:BackgroundCharacterizing the unique immune microenvironment of each tumor is of great importance for better predicting prognosis and guiding cancer immunotherapy. However, the unique features of the immune microenvironment of triple negative breast cancer (TNBC) compared with other subtypes of breast cancer remain elusive. Therefore, we aimed to depict and compare the immune landscape among TNBC, human epidermal growth factor receptor 2-positive (HER2+ ) breast cancer, and luminal-like breast cancer.MethodsSingle-cell RNA sequencing (scRNA-seq) was performed on CD45+ immune cells isolated from human normal breast tissues and primary breast tumors of various subtypes. By analyzing the scRNA-seq data, immune cell clusters were identified and their proportions as well as transcriptome features were compared among TNBC, human HER2+ breast cancer, and luminal-like breast cancer. Pseudotime and cell-cell communication analyses were also conducted to characterize the immune microenvironment.ResultsScRNA-seq data of 117,958 immune cells were obtained and 31 immune clusters were identified. A unique immunosuppressive microenvironment in TNBC was decoded as compared to that in HER2+ or luminal-like breast cancer, which was characterized by higher proportions of regulatory T cells (Tregs) and exhausted CD8+ T cells and accompanied by more abundant plasma cells. Tregs and exhausted CD8+ T cells in TNBC exhibited increased immunosuppression signature and dysfunctional scores. Pseudotime analyses showed that B cells tended to differentiate to plasma cells in TNBC. Cell-cell communication analyses indicated that these unique features are fostered by the diversified T cell-B cell crosstalk in TNBC. Based on the T cell-B cell crosstalk, a prognostic signature was established that could effectively predict the prognosis status for patients with TNBC. Additionally, it was found that TNBC had a higher proportion of cytotoxic natural killer (NK) cells, whereas HER2+ or luminal-like breast cancer lost this feature, suggesting that HER2+ or luminal-like breast cancer, but not TNBC, may benefit from NK-based immunotherapy.ConclusionsThis study identified a distinct immune feature fostered by T cell-B cell crosstalk in TNBC, which provides better prognostic information and effective therapeutic targets for breast cancer.

Project description:Background: The histological and molecular classification of breast cancer (BC) is being used in the clinical management of this disease. However, subtyping of BC based on the tumor immune microenvironment (TIME) remains insufficiently explored, although such investigation may provide new insights into intratumor heterogeneity in BC and potential clinical implications for BC immunotherapy. Methods: Based on the enrichment scores of 28 immune cell types, we performed clustering analysis of transcriptomic data to identify immune-specific subtypes of BC using six different datasets, including five bulk tumor datasets and one single-cell dataset. We further analyzed the molecular and clinical features of these subtypes. Results: Consistently in the six datasets, we identified three BC subtypes: BC-ImH, BC-ImM, and BC-ImL, which had high, medium, and low immune signature scores, respectively. BC-ImH displayed a significantly better survival prognosis than BC-ImL. Triple-negative BC (TNBC) and human epidermal growth factor receptor-2-positive (HER2+) BC were likely to have the highest proportion in BC-ImH and the lowest proportion in BC-ImL. In contrast, hormone receptor-positive (HR+) BC had the highest proportion in BC-ImL and the lowest proportion in BC-ImH. Furthermore, BC-ImH had the highest tumor mutation burden (TMB) and predicted neoantigens, while BC-ImL had the highest somatic copy number alteration (SCNA) scores. It is consistent with that TMB and SCNA correlate positively and negatively with anti-tumor immune response, respectively. TP53 had the highest mutation rate in BC-ImH and the lowest mutation rate in BC-ImL, supporting that TP53 mutations promote anti-tumor immune response in BC. In contrast, PIK3CA displayed the highest mutation rate in BC-ImM, while GATA3 had the highest mutation rate in BC-ImL. Besides immune pathways, many oncogenic pathways were upregulated in BC-ImH, including ErbB, MAPK, VEGF, and Wnt signaling pathways; the activities of these pathways correlated positively with immune signature scores in BC. Conclusions: The tumors with the strong immune response ("hot" tumors) have better clinical outcomes than the tumors with the weak immune response ("cold" tumors) in BC. TNBC and HER2+ BC are more immunogenic, while HR + BC is less immunogenic. Certain HER2+ or HR + BC patients could be propitious to immunotherapy in addition to TNBC.

Dataset Information

A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer.

Publications

A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer.

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