High levels of ecto-5′-nucleotidase (CD73) have been implicated in immune suppression and tumor progression, and have also been observed in cancer patients who progress on anti–PD-1 immunotherapy. Although regulatory T cells can express CD73 and inhibit T cell responses via the production of adenosine, less is known about CD73 expression in other immune cell populations. We found that tumor-infiltrating NK cells upregulate CD73 expression and the frequency of these CD73-positive NK cells correlated with larger tumor size in breast cancer patients. In addition, the expression of multiple alternative immune checkpoint receptors including LAG-3, VISTA, PD-1, and PD-L1 was significantly higher in CD73-positive NK cells than in CD73-negative NK cells. Mechanistically, NK cells transport CD73 in intracellular vesicles to the cell surface and the extracellular space via actin polymerization–dependent exocytosis upon engagement of 4-1BBL on tumor cells. These CD73-positive NK cells undergo transcriptional reprogramming and upregulate IL-10 production via STAT3 transcriptional activity, suppressing CD4-positive T cell proliferation and IFN-γ production. Taken together, our results support the notion that tumors can hijack NK cells as a means to escape immunity and that CD73 expression defines an inducible population of NK cells with immunoregulatory properties within the tumor microenvironment.

Introduction: The cancer stem cell model implies a hierarchical organization within breast tumors maintained by cancer stem-like cells (CSCs). Accordingly, CSCs are a subpopulation of cancer cells with capacity for self-renewal, differentiation and tumor initiation. These cells can be isolated through the phenotypic markers CD44+/CD24-, expression of ALDH1 and an ability to form nonadherent, multicellular spheres in vitro. However, controversies to describe the stem cell model exist; it is unclear whether the tumorigenicity of CSCs in vivo is solely a proxy for a certain genotype. Moreover, in vivo evidence is lacking to fully define the reversibility of CSC differentiation. Methods: In order to answer these questions, we undertook exome sequencing of CSCs from 12 breast cancer patients, along with paired primary tumor samples. As suggested by stem classical cell biology, we assumed that the number of mutations in the CSC subpopulation should be lower and distinct compared to the differentiated tumor cells with higher proliferation. Results: Our analysis revealed that the majority of somatic mutations are shared between CSCs and bulk primary tumor, with similar frequencies in the two. Conclusions: The data presented here exclude the possibility that CSCs are only a phenotypic consequence of certain somatic mutations, that is a distinct and non-reversible population of cells. In addition, our results imply that CSCs must be a population of cells that can dynamically switch from differentiated tumor cells, and vice versa. This finding increases our understanding of CSC function in tumor heterogeneity and the importance of identifying drugs to counter de-differentiation rather than targeting CSCs.

Transcriptomic profiling of breast tumors provides opportunity for subtyping and molecular-based patient stratification. In diagnostic applications the specimen profiled should be representative of the expression profile of the whole tumor and ideally capture properties of the most aggressive part of the tumor. However, breast cancers commonly exhibit intra-tumor heterogeneity at molecular, genomic and in phenotypic level, which can arise during tumor evolution. Currently it is not established to what extent a random sampling approach may influence molecular breast cancer diagnostics. In this study we applied RNA-sequencing to quantify gene expression in 43 pieces (2-5 pieces per tumor) from 12 breast tumors (Cohort 1). We determined molecular subtype and transcriptomic grade for all tumor pieces and analysed to what extent pieces originating from the same tumors are concordant or discordant with each other. Additionally, we validated our finding in an independent cohort consisting of 19 pieces (2-6 pieces per tumor) from 6 breast tumors (Cohort 2) profiled using microarray technique. Exome sequencing was also performed on this cohort, to investigate the extent of intra-tumor genomic heterogeneity versus the intra-tumor molecular subtype classifications. Molecular subtyping was consistent in 11 out of 12 tumors and transcriptomic grade assignments were consistent in 11 out of 12 tumors as well. Molecular subtype predictions revealed consistent subtypes in four out of six patients in this cohort 2. Interestingly, we observed extensive intra-tumor genomic heterogeneity in these tumor pieces but not in their molecular subtype classifications. Our results suggest that macroscopic intra-tumoral transcriptomic heterogeneity is limited and unlikely to have an impact on molecular diagnostics for most patients.