Department of Pathology, Yale School of Medicine, New Haven, Connecticut.
Navigate BioPharma Services, Inc., Carlsbad, California.
Clin Cancer Res. 2021 Apr 1;27(7):1987-1996. doi: 10.1158/1078-0432.CCR-20-3340. Epub 2021 Jan 27.
Imaging mass cytometry (IMC) is among the first tools with the capacity for multiplex analysis of more than 40 targets, which provides a novel approach to biomarker discovery. Here, we used IMC to characterize the tumor microenvironment of patients with metastatic melanoma who received immunotherapy in efforts to find indicative factors of treatment response. In spite of the new power of IMC, the image analysis aspects are still limited by the challenges of cell segmentation.
Here, rather than segment, we performed image analysis using a newly designed version of the AQUA software to measure marker intensity in molecularly defined compartments: tumor cells, stroma, T cells, B cells, and macrophages. IMC data were compared with quantitative immunofluorescence (QIF) and digital spatial profiling.
Validation of IMC results for immune markers was confirmed by regression with additional multiplexing methods and outcome assessment. Multivariable analyses by each compartment revealed significant associations of 12 markers for progression-free survival and seven markers for overall survival (OS). The most compelling indicative biomarker, beta2-microglobulin (B2M), was confirmed by correlation with OS by QIF in the discovery cohort and validated in an independent published cohort profiled by mRNA expression.
Using digital image analysis based on pixel colocalization to assess IMC data allowed us to quantitively measure 25 markers simultaneously on formalin-fixed, paraffin-embedded tissue microarray samples. In addition to showing high concordance with other multiplexing technologies, we identified a series of potentially indicative biomarkers for immunotherapy in metastatic melanoma, including B2M.
成像质谱流式细胞术（IMC）是首批能够对 40 多个靶标进行多重分析的工具之一，为生物标志物的发现提供了一种新方法。在这里，我们使用 IMC 对接受免疫治疗的转移性黑色素瘤患者的肿瘤微环境进行了特征分析，以寻找治疗反应的指示性因素。尽管 IMC 具有新的功能，但图像分析方面仍然受到细胞分割挑战的限制。
在这里，我们没有进行分割，而是使用新设计的 AQUA 软件版本进行图像分析，以测量分子定义的隔室中的标记强度：肿瘤细胞、基质、T 细胞、B 细胞和巨噬细胞。将 IMC 数据与定量免疫荧光（QIF）和数字空间分析进行了比较。
通过与其他多重分析方法和结果评估的回归验证了免疫标志物的 IMC 结果的验证。通过每个隔室的多变量分析发现，12 个标志物与无进展生存期相关，7 个标志物与总生存期（OS）相关。最引人注目的指示性生物标志物β2-微球蛋白（B2M）通过与发现队列中 QIF 的 OS 进行相关性得到了证实，并在独立发表的通过 mRNA 表达进行分析的队列中得到了验证。
使用基于像素共定位的数字图像分析来评估 IMC 数据，使我们能够在福尔马林固定、石蜡包埋的组织微阵列样本上同时定量测量 25 个标志物。除了与其他多重分析技术具有高度一致性外，我们还确定了一系列潜在的转移性黑色素瘤免疫治疗指示性生物标志物，包括 B2M。
