Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment

Abstract

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.

CD163+ tumor‐associated macrophage accumulation in breast cancer patients reflects both local differentiation signals and systemic skewing of monocytes

“…We identified about 25% of total immune cells infiltrating BCs as CD14 + TAMs that express variable levels of CD163, underlying the phenotypic heterogeneity in TAMs. Through high‐dimensional analysis approaches, several recent reports have uncovered TAM heterogeneity at the single‐cell level in distinct tumor types, including BC, clear cell renal cell carcinoma, melanoma and lung adenocarcinoma . These studies revealed a great variety of distinct phenotypic TAM subsets that co‐exist by sharing the expression of well‐established M1 and M2 markers.…”

“…M1‐MΦ are recognised as classically activated MΦ endowed with anti‐tumoral properties, while M2‐MΦ contribute to tumor development because of their immunosuppressive and pro‐angiogenic features . The use of large‐scale single‐cell analyses has recently revealed a new level of diversity in TAM populations according to their ontogeny and functional state that extends beyond the M1‐ and M2‐like phenotypes . However, the mechanisms and tumor‐derived factors responsible for educating monocytes to TAMs with different phenotypes by tumor‐derived factors remain poorly characterised in humans.…”

Monocyte heterogeneity and functions in cancer

“…The cues that govern monocyte fate decisions between remaining a monocyte, differentiation into a Mϕ or DC, or undergoing programmed cell‐death remain are not fully understood. In a recent study of human breast cancer intratumoral heterogeneity using scRNA‐Seq, the authors inferred a monocytic activation gene signature that reflected a trajectory from blood monocytes to intratumoral monocytes, and from that to other myeloid compartments such as DCs and TAMs . Similar types of analyses in both mouse models and human cancers will be critical for improving our understanding of monocyte fates within tumors.…”

The Unmixing Problem: A Guide to Applying Single-Cell RNA Sequencing to Bone

“…These issues can be further complicated if differences in transcript sampling among cellular populations lead to different detection thresholds in each cluster. Computational strategies to address this issue include MAGIC (Markov affinity‐based graph imputation of cells), which infers values for gene expression data missing due to sampling issues in each cell based on gene expression in similar cells . Alternatively, where feasible, cellular isolation followed by bulk RNA‐sequencing offers perhaps the most straightforward method to experimentally validate gene expression changes observed by scRNA‐seq.…”