Using single-cell RNA-seq, Azizi et al. computationally analyzed 45,000 immune cells from 8 breast cancer carcinomas, along with cells from matched normal breast tissue, blood, and lymph nodes. Despite similarities between tissue-resident and tumor-resident immune cells, there was increased heterogeneity in cell states and expansion of diverse immune populations within the tumor. A continuous spectrum of T cell activation states was observed, likely due to both TCR diversity and exposure to different microenvironments within the tumor. Interestingly, the data did not align with the canonical M1/M2 macrophage polarization model.
Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We profiled 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph nodes, using single-cell RNA-seq. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer. Our results have important implications for characterizing tumor-infiltrating immune cells.