Patterns of Immune Infiltration in Breast Cancer and Their Clinical Implications: A Gene-Expression-Based Retrospective Study.
Patterns of Immune Infiltration in Breast Cancer and Their Clinical Implications: A Gene-Expression-Based Retrospective Study.
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乳腺癌中免疫浸润及其临床意义的模式：一项基于基因表达的回顾性研究。
DOI：
10.1371/journal.pmed.1002194
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发表时间：
2016-12
期刊：
影响因子：
15.8
通讯作者：
Caldas C
中科院分区：
文献类型：
--
作者：
Ali HR;Chlon L;Pharoah PD;Markowetz F;Caldas C
乳腺肿瘤的免疫浸润与临床结果相关。然而，过去的工作并没有考虑到构成免疫反应的功能不同的细胞类型的多样性。本研究的目的是确定乳腺肿瘤中免疫浸润细胞组成的差异是否影响生存和治疗反应，以及这些影响是否因分子亚型而异。我们将一种已建立的计算方法（CIBERSORT）应用于近11，000个肿瘤的大量基因表达谱，以推断22个免疫细胞子集的比例。我们研究了每种细胞类型与生存率和化疗反应之间的关系，将细胞比例建模为四分位数。我们发现，根据雌激素受体（ER）状态，几乎没有或没有免疫浸润的肿瘤与不同的生存模式相关。在ER阴性疾病中，缺乏免疫浸润的肿瘤与最差的预后相关，而在ER阳性疾病中，它们与中等预后相关。在研究的细胞亚群中，调节性T细胞和M0和M2巨噬细胞与不良结局的相关性最强，与ER状态无关。在ER阴性肿瘤中，CD 8 + T细胞（风险比[HR] = 0.89，95% CI 0.80-0.98; p = 0.02）和激活的记忆T细胞（HR 0.88，95% CI 0.80-0.97; p = 0.01）与有利的结局相关。T滤泡辅助细胞在ER阴性的疾病中，新辅助化疗的病理完全反应与体液免疫（优势比[OR] = 1.34，95%CI 1.14-1.57; p < 0.001）和记忆B细胞（OR = 1.18，95%CI 1.0-1.39; p = 0.04）相关，提示体液免疫在介导细胞毒性治疗反应中的作用。使用免疫细胞比例的无监督聚类分析显示了8个肿瘤亚组，主要由M0，M1和M2巨噬细胞之间的平衡定义，ER状态和与诊断时患者年龄的相关性具有不同的生存模式。这项研究的主要局限性是使用不同的平台来测量基因表达，包括一些以前没有与CIBERSORT一起使用的平台，以及对不同形式的随访研究的综合分析。乳腺肿瘤中免疫浸润的细胞组成似乎存在很大差异，这些差异可能是预后和治疗反应的重要决定因素。特别是，巨噬细胞成为新疗法的可能靶点。对肿瘤细胞免疫反应的详细分析有可能增强临床预测并确定免疫治疗的候选者。为了研究不同类型的免疫细胞对肿瘤的浸润，H。Raza Ali及其同事研究了来自大型乳腺癌数据集的基因表达谱。先前的研究表明，乳腺肿瘤中存在的某些免疫细胞与复发风险有关。然而，特定的免疫细胞类型是否与更大或更小的复发风险相关，以及这些效应如何因乳腺癌亚型而异，目前尚不清楚。我们对公共领域（10，988例）中可用的乳腺肿瘤基因表达谱进行了大量分析，以获得22种免疫细胞亚群的相对比例估计值，以调查每种细胞类型的比例与疾病复发或对化疗的反应之间的关联。我们发现，某些免疫细胞类型的比例较高与复发风险较高（或化疗反应较大）相关，而其他免疫细胞类型与风险较低相关，并且这些相关性通常根据肿瘤的雌激素受体（ER）状态而不同。在缺乏ER表达的肿瘤中，我们发现CD 8 + T细胞和激活的记忆T细胞的存在与复发风险的降低有关，而具有高比例T滤泡辅助细胞的肿瘤更可能对新辅助化疗有反应。在ER阳性肿瘤中，M0巨噬细胞的存在与预后不良相关。调节性T细胞与ER阳性和ER阴性肿瘤的预后不良相关。这些发现建立了乳腺癌肿瘤内免疫细胞的异质性、肿瘤分子亚型和疾病进展之间的复杂关系。旨在增强对肿瘤的免疫反应的治疗，即，免疫疗法仅在一部分患者中有效，我们的发现可能有助于识别这一患者群体，并为开发新的免疫疗法提出目标。
Immune infiltration of breast tumours is associated with clinical outcome. However, past work has not accounted for the diversity of functionally distinct cell types that make up the immune response. The aim of this study was to determine whether differences in the cellular composition of the immune infiltrate in breast tumours influence survival and treatment response, and whether these effects differ by molecular subtype. We applied an established computational approach (CIBERSORT) to bulk gene expression profiles of almost 11,000 tumours to infer the proportions of 22 subsets of immune cells. We investigated associations between each cell type and survival and response to chemotherapy, modelling cellular proportions as quartiles. We found that tumours with little or no immune infiltration were associated with different survival patterns according to oestrogen receptor (ER) status. In ER-negative disease, tumours lacking immune infiltration were associated with the poorest prognosis, whereas in ER-positive disease, they were associated with intermediate prognosis. Of the cell subsets investigated, T regulatory cells and M0 and M2 macrophages emerged as the most strongly associated with poor outcome, regardless of ER status. Among ER-negative tumours, CD8+ T cells (hazard ratio [HR] = 0.89, 95% CI 0.80–0.98; p = 0.02) and activated memory T cells (HR 0.88, 95% CI 0.80–0.97; p = 0.01) were associated with favourable outcome. T follicular helper cells (odds ratio [OR] = 1.34, 95% CI 1.14–1.57; p < 0.001) and memory B cells (OR = 1.18, 95% CI 1.0–1.39; p = 0.04) were associated with pathological complete response to neoadjuvant chemotherapy in ER-negative disease, suggesting a role for humoral immunity in mediating response to cytotoxic therapy. Unsupervised clustering analysis using immune cell proportions revealed eight subgroups of tumours, largely defined by the balance between M0, M1, and M2 macrophages, with distinct survival patterns by ER status and associations with patient age at diagnosis. The main limitations of this study are the use of diverse platforms for measuring gene expression, including some not previously used with CIBERSORT, and the combined analysis of different forms of follow-up across studies. Large differences in the cellular composition of the immune infiltrate in breast tumours appear to exist, and these differences are likely to be important determinants of both prognosis and response to treatment. In particular, macrophages emerge as a possible target for novel therapies. Detailed analysis of the cellular immune response in tumours has the potential to enhance clinical prediction and to identify candidates for immunotherapy. To investigate tumor infiltration by different types of immune cells, H. Raza Ali and colleagues study gene expression profiles from large breast cancer datasets. Previous studies have shown that certain immune cells present in breast tumours are associated with risk of relapse. Whether particular immune cell types are associated with a greater or lesser risk of relapse, however, and how these effects differ by breast cancer subtype, remains unclear. We conducted a large analysis of breast tumour gene expression profiles available in the public domain (10,988 cases) to derive estimates of the relative proportions of 22 subsets of immune cells, in order to investigate associations between the proportion of each cell type and disease relapse or response to chemotherapy. We found that higher proportions of some immune cell types were associated with greater risk of relapse (or greater chemotherapy response), whereas others were associated with lesser risk, and that these associations were often different according to the oestrogen receptor (ER) status of the tumour. In tumours lacking expression of ER, we found that the presence of CD8+ T cells and activated memory T cells was associated with a reduction in the risk of relapse, while tumours with high proportions of T follicular helper cells were more likely to respond to neoadjuvant chemotherapy. In ER-positive tumours, the presence of M0 macrophages was associated with poor prognosis. T regulatory cells were associated with poor prognosis in both ER-positive and ER-negative tumours. These findings establish a complex relationship between the heterogeneity of intratumoural immune cells, tumour molecular subtype, and disease progression in breast cancer. Treatments that aim to boost the immune response to tumours, i.e., immunotherapies, are effective in only a subset of patients, and our findings may help to identify this patient group and suggest targets for the development of new immunotherapies.
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影响因子：
50.5
作者：
Ali, H. R.;Glont, S. -E.;Caldas, C.
通讯作者：
Caldas, C.
影响因子：
45.3
作者：
Adams, Sylvia;Gray, Robert J.;Badve, Sunil S.
通讯作者：
Badve, Sunil S.
影响因子：
15.9
作者：
Gu-Trantien, Chunyan;Loi, Sherene;Willard-Gallo, Karen
通讯作者：
Willard-Gallo, Karen
影响因子：
64.8
作者：
Curtis, Christina;Shah, Sohrab P.;Chin, Suet-Feung;Turashvili, Gulisa;Rueda, Oscar M.;Dunning, Mark J.;Speed, Doug;Lynch, Andy G.;Samarajiwa, Shamith;Yuan, Yinyin;Graef, Stefan;Ha, Gavin;Haffari, Gholamreza;Bashashati, Ali;Russell, Roslin;McKinney, Steven;Langerod, Anita;Green, Andrew;Provenzano, Elena;Wishart, Gordon;Pinder, Sarah;Watson, Peter;Markowetz, Florian;Murphy, Leigh;Ellis, Ian;Purushotham, Arnie;Borresen-Dale, Anne-Lise;Brenton, James D.;Tavare, Simon;Caldas, Carlos;Aparicio, Samuel
通讯作者：
Aparicio, Samuel
DOI：
10.1126/science.1246886
发表时间：
2014-01-10
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Joseph CG;Darrah E;Shah AA;Skora AD;Casciola-Rosen LA;Wigley FM;Boin F;Fava A;Thoburn C;Kinde I;Jiao Y;Papadopoulos N;Kinzler KW;Vogelstein B;Rosen A
通讯作者：
Rosen A