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Islands of CD123highcells have been commonly described in the bone marrow of patients with chronic myelomonocytic leukemia (CMML). Using a multiparameter flow cytometry assay, we detected an excess of CD123+mononucleated cells that are lineage-negative, CD45+, CD11c−, CD33−, HLA-DR+, BDCA-2+, BDCA-4+in the bone marrow of 32/159 (20%) patients. Conventional and electron microscopy, flow cytometry detection of cell surface markers, gene expression analyses, and the ability to synthesize interferon alpha in response to Toll-like receptor agonists identified these cells as bona fide plasmacytoid dendritic cells (pDCs). Whole-exome sequencing of sorted monocytes and pDCs identified somatic mutations in genes of the oncogenic RAS pathway in the two cell types of every patient. CD34+cells could generate high amount of pDCs in the absence of FMS-like tyrosine kinase 3-ligand (FLT3L). Finally, an excess of pDCs correlates with regulatory T cell accumulation and an increased risk of acute leukemia transformation. These results demonstrate the FLT3L-independent accumulation of clonal pDCs in the bone marrow of CMML patients with mutations affecting the RAS pathway, which is associated with a higher risk of disease progression.

The functions and transcriptional profiles of dendritic cells (DCs) result from the interplay between ontogeny and tissue imprinting. How tumors shape human DCs is unknown. Here we used RNA-based next-generation sequencing to systematically analyze the transcriptomes of plasmacytoid pre-DCs (pDCs), cell populations enriched for type 1 conventional DCs (cDC1s), type 2 conventional DCs (cDC2s), CD14+DCs and monocytes-macrophages from human primary luminal breast cancer (LBC) and triple-negative breast cancer (TNBC). By comparing tumor tissue with non-invaded tissue from the same patient, we found that 85% of the genes upregulated in DCs in LBC were specific to each DC subset. However, all DC subsets in TNBC commonly showed enrichment for the interferon pathway, but those in LBC did not. Finally, we defined transcriptional signatures specific for tumor DC subsets with a prognostic effect on their respective breast-cancer subtype. We conclude that the adjustment of DCs to the tumor microenvironment is subset specific and can be used to predict disease outcome. Our work also provides a resource for the identification of potential targets and biomarkers that might improve antitumor therapies.