Division of Cancer Sciences, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
Manchester Cancer Research Centre, Wilmslow Road, Manchester, M20 4QL, UK.
Cancer Immunol Immunother. 2021 Dec;70(12):3573-3585. doi: 10.1007/s00262-021-02945-0. Epub 2021 Apr 30.
Follicular lymphoma (FL) prognosis is influenced by the composition of the tumour microenvironment. We tested an automated approach to quantitatively assess the phenotypic and spatial immune infiltrate diversity as a prognostic biomarker for FL patients.
Diagnostic biopsies were collected from 127 FL patients initially treated with rituximab-based therapy (52%), radiotherapy (28%), or active surveillance (20%). Tissue microarrays were constructed and stained using multiplex immunofluorescence (CD4, CD8, FOXP3, CD21, PD-1, CD68, and DAPI). Subsequently, sections underwent automated cell scoring and analysis of spatial interactions, defined as cells co-occurring within 30 μm. Shannon's entropy, a metric describing species biodiversity in ecological habitats, was applied to quantify immune infiltrate diversity of cell types and spatial interactions. Immune infiltrate diversity indices were tested in multivariable Cox regression and Kaplan-Meier analysis for overall (OS) and progression-free survival (PFS).
Increased diversity of cell types (HR = 0.19 95% CI 0.06-0.65, p = 0.008) and cell spatial interactions (HR = 0.39, 95% CI 0.20-0.75, p = 0.005) was associated with favourable OS, independent of the Follicular Lymphoma International Prognostic Index. In the rituximab-treated subset, the favourable trend between diversity and PFS did not reach statistical significance.
Multiplex immunofluorescence and Shannon's entropy can objectively quantify immune infiltrate diversity and generate prognostic information in FL. This automated approach warrants validation in additional FL cohorts, and its applicability as a pre-treatment biomarker to identify high-risk patients should be further explored. The multiplex image dataset generated by this study is shared publicly to encourage further research on the FL microenvironment.
滤泡性淋巴瘤（FL）的预后受肿瘤微环境组成的影响。我们测试了一种自动方法，以定量评估表型和空间免疫浸润多样性作为 FL 患者的预后生物标志物。
从 127 例最初接受利妥昔单抗为基础的治疗（52%）、放疗（28%）或主动监测（20%）的 FL 患者中采集诊断性活检。构建组织微阵列并使用多重免疫荧光（CD4、CD8、FOXP3、CD21、PD-1、CD68 和 DAPI）进行染色。随后，对切片进行自动细胞评分和空间相互作用分析，定义为细胞在 30μm 内共定位。香农熵（Shannon's entropy）是一种用于描述生态生境中物种多样性的度量标准，用于量化细胞类型和空间相互作用的免疫浸润多样性。在多变量 Cox 回归和 Kaplan-Meier 分析中，对免疫浸润多样性指数进行了总体生存（OS）和无进展生存（PFS）的测试。
细胞类型多样性（HR=0.19，95%CI 0.06-0.65，p=0.008）和细胞空间相互作用多样性（HR=0.39，95%CI 0.20-0.75，p=0.005）增加与 OS 有利相关，与滤泡性淋巴瘤国际预后指数无关。在利妥昔单抗治疗亚组中，多样性与 PFS 之间的有利趋势没有达到统计学意义。
多重免疫荧光和香农熵可以客观地量化免疫浸润多样性，并为 FL 提供预后信息。这种自动方法需要在更多的 FL 队列中进行验证，并且应该进一步探索其作为预测高危患者的治疗前生物标志物的适用性。本研究生成的多重图像数据集公开共享，以鼓励对 FL 微环境的进一步研究。
