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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.