Department of Dermatology, The Johns Hopkins Hospital, Baltimore, Maryland, USA
Akoya Biosciences, Marlborough, Massachusetts, USA.
J Immunother Cancer. 2021 Jul;9(7). doi: 10.1136/jitc-2020-002197.
Emerging data suggest predictive biomarkers based on the spatial arrangement of cells or coexpression patterns in tissue sections will play an important role in precision immuno-oncology. Multiplexed immunofluorescence (mIF) is ideally suited to such assessments. Standardization and validation of an end-to-end workflow that supports multisite trials and clinical laboratory processes are vital. Six institutions collaborated to: (1) optimize an automated six-plex assay focused on the PD-1/PD-L1 axis, (2) assess intersite and intrasite reproducibility of staining using a locked down image analysis algorithm to measure tumor cell and immune cell (IC) subset densities, %PD-L1 expression on tumor cells (TCs) and ICs, and PD-1/PD-L1 proximity assessments.
A six-plex mIF panel (PD-L1, PD-1, CD8, CD68, FOXP3, and CK) was rigorously optimized as determined by quantitative equivalence to immunohistochemistry (IHC) chromogenic assays. Serial sections from tonsil and breast carcinoma and non-small cell lung cancer (NSCLC) tissue microarrays (TMAs), TSA-Opal fluorescent detection reagents, and antibodies were distributed to the six sites equipped with a Leica Bond Rx autostainer and a Vectra Polaris multispectral imaging platform. Tissue sections were stained and imaged at each site and delivered to a single site for analysis. Intersite and intrasite reproducibility were assessed by linear fits to plots of cell densities, including %PDL1 expression by TCs and ICs in the breast and NSCLC TMAs.
Comparison of the percent positive cells for each marker between mIF and IHC revealed that enhanced amplification in the mIF assay was required to detect low-level expression of PD-1, PD-L1, FoxP3 and CD68. Following optimization, an average equivalence of 90% was achieved between mIF and IHC across all six assay markers. Intersite and intrasite cell density assessments showed an average concordance of R=0.75 (slope=0.92) and R=0.88 (slope=0.93) for breast carcinoma, respectively, and an average concordance of R=0.72 (slope=0.86) and R=0.81 (slope=0.68) for NSCLC. Intersite concordance for %PD-L1+ICs had an average R value of 0.88 and slope of 0.92. Assessments of PD-1/PD-L1 proximity also showed strong concordance (R=0.82; slope=0.75).
Assay optimization yielded highly sensitive, reproducible mIF characterization of the PD-1/PD-L1 axis across multiple sites. High concordance was observed across sites for measures of density of specific IC subsets, measures of coexpression and proximity with single-cell resolution.
新出现的数据表明,基于细胞空间排列或组织切片中共同表达模式的预测生物标志物将在精准免疫肿瘤学中发挥重要作用。多重免疫荧光(mIF)非常适合此类评估。支持多站点试验和临床实验室流程的端到端工作流程的标准化和验证至关重要。六个机构合作:(1)优化针对 PD-1/PD-L1 轴的六重自动化测定,(2)使用锁定的图像分析算法评估染色的站点间和站点内可重复性,以测量肿瘤细胞和免疫细胞(IC)亚群密度、肿瘤细胞(TCs)和 IC 上的 %PD-L1 表达以及 PD-1/PD-L1 接近度评估。
六重 mIF 面板(PD-L1、PD-1、CD8、CD68、FOXP3 和 CK)经过严格优化,通过与免疫组织化学(IHC)显色测定的定量等效性确定。来自扁桃体和乳腺癌以及非小细胞肺癌(NSCLC)组织微阵列(TMA)的连续切片、TSA-Opal 荧光检测试剂和抗体分发给配备 Leica Bond Rx 自动染色机和 Vectra Polaris 多光谱成像平台的六个站点。在每个站点对组织切片进行染色和成像,并将其送到一个站点进行分析。通过线性拟合 TC 和 IC 中 %PDL1 表达的 TMA 中的细胞密度图来评估站点间和站点内的可重复性。
mIF 与 IHC 之间每个标志物的阳性细胞百分比比较表明,需要增强 mIF 测定中的扩增以检测 PD-1、PD-L1、FoxP3 和 CD68 的低水平表达。经过优化,mIF 与所有六种测定标志物的 IHC 之间平均达到 90%的等效性。站点间和站点内细胞密度评估显示,乳腺癌的平均一致性分别为 R=0.75(斜率=0.92)和 R=0.88(斜率=0.93),非小细胞肺癌的平均一致性分别为 R=0.72(斜率=0.86)和 R=0.81(斜率=0.68)。站点间 %PD-L1+ICs 的一致性平均 R 值为 0.88,斜率为 0.92。PD-1/PD-L1 接近度的评估也显示出很强的一致性(R=0.82;斜率=0.75)。
通过优化测定,在多个站点实现了针对 PD-1/PD-L1 轴的高度敏感、可重复的 mIF 特征。观察到站点间特定 IC 亚群密度、共表达和接近度的测量值具有高度一致性,具有单细胞分辨率。