Anti-Quail Dendritic Cells Monoclonal antibody, clone TAP1

Nasopharyngeal carcinoma (NPC) is an aggressive malignancy with extremely skewed ethnic and geographic distributions. Increasing evidence indicates that targeting the tumor microenvironment (TME) represents a promising therapeutic approach in NPC, highlighting an urgent need to deepen the understanding of the complex NPC TME. Here, we generated single-cell transcriptome profiles for 7581 malignant cells and 40,285 immune cells from fifteen primary NPC tumors and one normal sample. We revealed malignant signatures capturing intratumoral transcriptional heterogeneity and predicting aggressiveness of malignant cells. Diverse immune cell subtypes were identified, including novel subtypes such asCLEC9A(+)dendritic cells (DCs). We further revealed transcriptional regulators underlying immune cell diversity, and cell-cell interaction analyses highlighted promising immunotherapeutic targets in NPC. Moreover, we established the immune subtype-specific signatures, and demonstrated that the signatures of macrophages, plasmacytoid dendritic cells (pDCs),CLEC9A(+)DCs, natural killer (NK) cells, and plasma cells were significantly associated with improved survival outcomes in NPC. Taken together, our findings represent a unique resource providing in-depth insights into the cellular heterogeneity of NPC TME and highlight potential biomarkers for anticancer treatment and risk stratification, laying a new foundation for precision therapies in NPC.

The mononuclear phagocyte system (MPS) is a family of cells including progenitors, circulating blood monocytes, resident tissue macrophages, and dendritic cells (DCs) present in every tissue in the body. To test the relationships between markers and transcriptomic diversity in the MPS, we collected from National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO) a total of 466 quality RNA sequencing (RNA-seq) data sets generated from mouse MPS cells isolated from bone marrow, blood, and multiple tissues. The primary data were randomly downsized to a depth of 10 million reads and requantified. The resulting data set was clustered using the network analysis toolBioLayout. A sample-to-sample matrix revealed that MPS populations could be separated based upon tissue of origin. Cells identified as classical DC subsets, cDC1s and cDC2s, and lackingFcgr1(encoding the protein CD64) were contained within the MPS cluster, no more distinct than other MPS cells. A gene-to-gene correlation matrix identified large generic coexpression clusters associated with MPS maturation and innate immune function. Smaller coexpression gene clusters, including the transcription factors that drive them, showed higher expression within defined isolated cells, including monocytes, macrophages, and DCs isolated from specific tissues. They include a cluster containingLyve1that implies a function in endothelial cell (EC) homeostasis, a cluster of transcripts enriched in intestinal macrophages, and a generic lymphoid tissue cDC cluster associated withCcr7. However, transcripts encodingAdgre1,Itgax,Itgam,Clec9a,Cd163,Mertk,Mrc1,Retnla, andH2-a/e(encoding class II major histocompatibility complex [MHC] proteins) and many other proposed macrophage subset and DC lineage markers each had idiosyncratic expression profiles. Coexpression of immediate early genes (for example,Egr1,Fos,Dusp1) and inflammatory cytokines and chemokines (tumour necrosis factor [Tnf],Il1b,Ccl3/4) indicated that all tissue disaggregation and separation protocols activate MPS cells. Tissue-specific expression clusters indicated that all cell isolation procedures also co-purify other unrelated cell types that may interact with MPS cells in vivo. Comparative analysis of RNA-seq and single-cell RNA-seq (scRNA-seq) data from the same lung cell populations indicated that MPS heterogeneity implied by global cluster analysis may be even greater at a single-cell level. This analysis highlights the power of large data sets to identify the diversity of MPS cellular phenotypes and the limited predictive value of surface markers to define lineages, functions, or subpopulations.