Quantification of prognostic immune cell markers in colorectal cancer using whole slide imaging tumor maps.

Niels Halama, Inka Zoernig, Anna Spille, Sara Michel, Matthias Kloor, Silke Grauling-Halama, Kathi Westphal, Peter Schirmacher, Dirk Jäger, Niels Grabe
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Abstract

Objective: To analyze intratumoral heterogeneity of immune cells and the resulting impact of heterogeneity on the level of individual patient prediction.

Study design: Using whole slide imaging by virtual microscopy, we present the first spatial quantitative study of immune cells in a set of colorectal cancer primary tumors. We generated "tumor maps" based on cell densities in fields of 1 mm2, visualizing intratumoral heterogeneity. In this example, cutoffs of marker-based cell stains identified by tissue microarray (TMA) led to ambiguous decisions in 11 of the 20 patients studied. Classic TMA analysis can be used in large patient cohorts to generate clinically significant predictors. The transfer of these predictors from large-scale TMA to individualized predictions thus far has not been investigated. In colorectal cancer, TMA-based quantitative immune cell counts using immune cell surface molecules (CD3, CD8, Granzyme B, and CD45RO) have been shown to be potentially better predictors for patient survival than the classical TNM system.

Results: Our results make clear that for individualized prognostic evaluations, whole slide imaging by virtual microscopy is irreplaceable during identification of prognostic markers as well as in their subsequent application.

Conclusion: In the future, spatial marker signatures could contribute to individual patient classifiers.

利用全切片成像肿瘤图定量评价结直肠癌的预后免疫细胞标志物。
目的:分析肿瘤内免疫细胞的异质性及其对个体患者预测水平的影响。研究设计:利用虚拟显微镜的全切片成像技术,我们首次对一组结直肠癌原发肿瘤中的免疫细胞进行了空间定量研究。我们根据1 mm2范围内的细胞密度生成“肿瘤图”,可视化肿瘤内的异质性。在这个例子中,由组织微阵列(TMA)鉴定的基于标记的细胞染色的切断导致了研究的20名患者中的11名患者的模糊决策。经典TMA分析可用于大型患者队列,以产生具有临床意义的预测因子。到目前为止,这些预测因子从大规模TMA到个性化预测的转移尚未得到研究。在结直肠癌中,使用免疫细胞表面分子(CD3、CD8、颗粒酶B和CD45RO)的基于tma的定量免疫细胞计数已被证明是比经典TNM系统更好的患者生存预测指标。结果:我们的研究结果表明,对于个性化的预后评估,虚拟显微镜的全切片成像在预后标志物的识别及其后续应用中是不可替代的。结论:在未来,空间标记特征将有助于个体患者的分类。
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