|
乳腺癌是一种异质性疾病，特征不一的肿瘤细胞及其相关健康细胞共同构成决定疾病进展和治疗效果的生态系统。不过，乳腺癌生态系统特征及其与临床数据的相关性尚不明确。 2019年4月11日，全球自然科学三大旗舰期刊之一、美国《细胞》正刊在线发表瑞士苏黎世大学、苏黎世联邦理工学院、IBM苏黎世研究院、巴塞尔大学医院、巴塞尔大学、苏黎世大学医院、德国慕尼黑患者肿瘤银行生物样本库、约瑟夫病理学研究所、马尔堡大学医院的研究报告，通过质量细胞计数法，分析了144例人类乳腺肿瘤和50例非肿瘤组织标本。 该研究利用肿瘤和免疫细胞抗体组，评估了2600万个细胞的73种蛋白质表达。肿瘤的细胞组成特征显著，包括表现型异常和表现型优势。肿瘤与免疫细胞之间的相关性分析表明，某些生态系统特征与免疫抑制和不良预后相关。高分级雌激素受体阳性和雌激素受体阴性肿瘤可见大量PD-L1阳性肿瘤相关巨噬细胞以及被大量消耗的T淋巴细胞。 因此，乳腺癌表现出肿瘤细胞表现型异常和肿瘤个体化，肿瘤与免疫的肿瘤生态系统相关性对于不同患者而不同。该大样本单细胞蛋白质组学分析揭示了肿瘤生态系统的肿瘤与免疫细胞多样性，加深了我们对乳腺肿瘤生态系统的了解，并且表明根据生态系统对患者进行分类，将有助于确定针对肿瘤及其免疫环境的个体化精准治疗方法。 Cell. 2019 Apr 11. [Epub ahead of print] A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer. Johanna Wagner, Maria Anna Rapsomaniki, Stéphane Chevrier, Tobias Anzeneder, Claus Langwieder, August Dykgers, Martin Rees, Annette Ramaswamy, Simone Muenst, Savas Deniz Soysal, Andrea Jacobs, Jonas Windhager, Karina Silina, Maries van den Broek, Konstantin Johannes Dedes, Maria Rodríguez Martínez, Walter Paul Weber, Bernd Bodenmiller. University of Zurich, Zurich, Switzerland; ETH Zurich, Zurich, Switzerland; IBM Research Zurich, Rueschlikon, Switzerland; Patients' Tumor Bank of Hope (PATH) Biobank, Munich, Germany; Institute of Pathology at Josefshaus, Dortmund, Germany; University Hospital Giessen and Marburg, Marburg, Germany; University Hospital Basel and University of Basel, Basel, Switzerland; University Hospital Zurich, Zurich, Switzerland. HIGHLIGHTS
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. KEYWORDS: breast cancer; tumor ecosystem; tumor heterogeneity; immunosuppression; T cell; macrophage; single-cell analysis; mass cytometry DOI: 10.1016/j.cell.2019.03.005
|
|
|
