Departments of Global Pathology and Investigative Toxicology, Pfizer, Inc., San Diego, California.
Drug Safety Statistics, Drug Safety Research and Development, Pfizer, Inc., San Diego, California.
Am J Pathol. 2021 Dec;191(12):2133-2146. doi: 10.1016/j.ajpath.2021.07.012. Epub 2021 Aug 21.
Murine tumors are indispensable model systems in preclinical immuno-oncology research. While immunologic heterogeneity is well-known to be an important factor that can influence treatment outcome, there is a severe paucity of data concerning the nature of this heterogeneity in murine tumor models. Using serial sectioning methodology combined with IHC analysis and whole-slide image analysis, the depth-dependent variation in immune-cell abundance in tumor specimens was investigated at single-cell resolution. Specifically, intra- and intertumor variability in cell density of nine immune-cell biomarkers was quantified in multiple murine tumor models. The analysis showed that intertumor variability was typically the dominant source of variation in measurements of immune-cell densities. Statistical power analysis revealed the effect of group size and variance in immune-cell density on the predictive power of detecting a statistically meaningful fold-change in immune-cell density. Intertumor variability in the ratio of immune-cell densities showed distinct patterns in select tumor models and revealed the existence of strong correlations between select biomarker pairs. Furthermore, the relative proportion of immune cells at different depths across tumor samples was preserved in some but not all tumor models, thereby revealing the existence of compositional heterogeneity. Taken together, these results reveal novel insights into the nature of immunologic heterogeneity, which is not accessible through typical omics approaches.
鼠类肿瘤是临床前肿瘤免疫学研究中不可或缺的模型系统。虽然免疫异质性是一个重要的影响治疗结果的因素,但在鼠类肿瘤模型中,关于这种异质性的本质的数据却严重匮乏。本研究采用连续切片方法结合免疫组化分析和全切片图像分析,以单细胞分辨率研究了肿瘤标本中免疫细胞丰度的深度依赖性变化。具体而言,在多个鼠类肿瘤模型中,定量分析了 9 种免疫细胞标志物的细胞密度的肿瘤内和肿瘤间变异性。分析表明,肿瘤间变异性通常是免疫细胞密度测量中变异性的主要来源。统计功效分析揭示了组大小和免疫细胞密度方差对检测免疫细胞密度统计学上有意义的倍数变化的预测能力的影响。在某些肿瘤模型中,免疫细胞密度比的肿瘤间变异性呈现出独特的模式,并揭示了选择生物标志物对之间存在强烈相关性。此外,在一些但不是所有肿瘤模型中,肿瘤样本中不同深度的免疫细胞的相对比例是保持不变的,从而揭示了组成异质性的存在。总之,这些结果揭示了免疫异质性的本质的新见解,这是通过典型的组学方法无法获得的。