Clonal barcoding of endogenous adult hematopoietic stem cells reveals a spectrum of lineage contributions.

The hierarchical model of hematopoiesis posits that self-renewing, multipotent hematopoietic stem cells (HSCs) give rise to all blood cell lineages. While this model accounts for hematopoiesis in transplant settings, its applicability to steady-state hematopoiesis remains to be clarified. Here, we used inducible clonal DNA barcoding of endogenous adult HSCs to trace their contribution to major hematopoietic cell lineages in unmanipulated animals. While the majority of barcodes were unique to a single lineage, we also observed frequent barcode sharing between multiple lineages, specifically between lymphocytes and myeloid cells. These results suggest that both single-lineage and multilineage contributions by HSCs collectively drive continuous hematopoiesis, and highlight a close relationship of myeloid and lymphoid development.

Transitional dendritic cells are distinct from conventional DC2 precursors and mediate proinflammatory antiviral responses.

High-dimensional approaches have revealed heterogeneity amongst dendritic cells (DCs), including a population of transitional DCs (tDCs) in mice and humans. However, the origin and relationship of tDCs to other DC subsets has been unclear. Here we show that tDCs are distinct from other well-characterized DCs and conventional DC precursors (pre-cDCs). We demonstrate that tDCs originate from bone marrow progenitors shared with plasmacytoid DCs (pDCs). In the periphery, tDCs contribute to the pool of ESAM+ type 2 DCs (DC2s), and these DC2s have pDC-related developmental features. Different from pre-cDCs, tDCs have less turnover, capture antigen, respond to stimuli and activate antigen-specific naïve T cells, all characteristics of differentiated DCs. Different from pDCs, viral sensing by tDCs results in IL-1ß secretion and fatal immune pathology in a murine coronavirus model. Our findings suggest that tDCs are a distinct pDC-related subset with a DC2 differentiation potential and unique proinflammatory function during viral infections.

Haplodeficiency of the 9p21 tumor suppressor locus causes myeloid disorders driven by the bone marrow microenvironment.

The chromosome 9p21 locus comprises several tumor suppressor genes including MTAP, CDKN2A, and CDKN2B, and its homo- or heterozygous deletion is associated with reduced survival in multiple cancer types. We report that mice with germ line monoallelic deletion or induced biallelic deletion of the 9p21-syntenic locus (9p21s) developed a fatal myelodysplastic syndrome/myeloproliferative neoplasm (MDS/MPN)-like disease associated with aberrant trabecular bone formation and/or fibrosis in the bone marrow (BM). Reciprocal BM transfers and conditional targeting of 9p21s suggested that the disease originates in the BM stroma. Single-cell analysis of 9p21s-deficient BM stroma revealed the expansion of chondrocyte and osteogenic precursors, reflected in increased osteogenic differentiation in vitro. It also showed reduced expression of factors maintaining hematopoietic stem/progenitor cells, including Cxcl12. Accordingly, 9p21s-deficient mice showed reduced levels of circulating Cxcl12 and concomitant upregulation of the profibrotic chemokine Cxcl13 and the osteogenesis- and fibrosis-related multifunctional glycoprotein osteopontin/Spp1. Our study highlights the potential of mutations in the BM microenvironment to drive MDS/MPN-like disease.

Stem cell decoupling underlies impaired lymphoid development during aging.

Mammalian aging is associated with multiple defects of hematopoiesis, most prominently with the impaired development of T and B lymphocytes. This defect is thought to originate in hematopoietic stem cells (HSCs) of the bone marrow, specifically due to the age-dependent accumulation of HSCs with preferential megakaryocytic and/or myeloid potential ("myeloid bias"). Here, we tested this notion using inducible genetic labeling and tracing of HSCs in unmanipulated animals. We found that the endogenous HSC population in old mice shows reduced differentiation into all lineages including lymphoid, myeloid, and megakaryocytic. Single-cell RNA sequencing and immunophenotyping (CITE-Seq) showed that HSC progeny in old animals comprised balanced lineage spectrum including lymphoid progenitors. Lineage tracing using the aging-induced HSC marker Aldh1a1 confirmed the low contribution of old HSCs across all lineages. Competitive transplantations of total bone marrow cells with genetically marked HSCs revealed that the contribution of old HSCs was reduced, but compensated by other donor cells in myeloid cells but not in lymphocytes. Thus, the HSC population in old animals becomes globally decoupled from hematopoiesis, which cannot be compensated in lymphoid lineages. We propose that this partially compensated decoupling, rather than myeloid bias, is the primary cause of the selective impairment of lymphopoiesis in older mice.

Deep Learning and Pathomics Analyses Reveal Cell Nuclei as Important Features for Mutation Prediction of BRAF-Mutated Melanomas.

Image-based analysis as a method for mutation detection can be advantageous in settings when tumor tissue is limited or unavailable for direct testing. In this study, we utilize two distinct and complementary machine-learning methods of analyzing whole-slide images for predicting mutated BRAF. In the first method, whole-slide images of melanomas from 256 patients were used to train a deep convolutional neural network to develop a fully automated model that first selects for tumor-rich areas (area under the curve = 0.96) and then predicts for mutated BRAF (area under the curve = 0.71). Saliency mapping was performed and revealed that pixels corresponding to nuclei were the most relevant to network learning. In the second method, whole-slide images were analyzed using a pathomics pipeline that first annotates nuclei and then quantifies nuclear features, showing that mutated BRAF nuclei were significantly larger and rounder than BRAF‒wild-type nuclei. Finally, we developed a model that combines clinical information, deep learning, and pathomics that improves the predictive performance for mutated BRAF to an area under the curve of 0.89. Not only does this provide additional insights on how BRAF mutations affect tumor structural characteristics, but machine learning‒based analysis of whole-slide images also has the potential to be integrated into higher-order models for understanding tumor biology.

Tumor immunogenomic signatures improve a prognostic model of melanoma survival.

BACKGROUND: Tumor mutation burden (TMB) has been associated with melanoma immunotherapy (IT) outcomes, including survival. We explored whether combining TMB with immunogenomic signatures recently identified by The Cancer Genome Atlas (TCGA) can refine melanoma prognostic models of overall survival (OS) in patients not treated by IT. METHODS: Cox proportional-hazards (Cox PH) analysis was performed on 278 metastatic melanomas from TCGA not treated by IT. In a discovery and two validation cohorts Cox PH models assessed the interaction between TMB and 53 melanoma immunogenomic features to refine prediction of melanoma OS. RESULTS: Interferon-γ response (IFNγRes) and macrophage regulation gene signatures (MacReg) combined with TMB significantly associated with OS (p = 8.80E-14). We observed that patients with high TMB, high IFNγRes and high MacReg had significantly better OS compared to high TMB, low IFNγRes and low MacReg (HR = 2.8, p = 3.55E-08). This association was not observed in low TMB patients. CONCLUSIONS: We report a model combining TMB and tumor immune features that significantly improves prediction of melanoma OS, independent of IT. Our analysis revealed that patients with high TMB, high levels of IFNγRes and MacReg had significantly more favorable OS compared to high TMB patients with low IFNγRes and low MacReg. These findings may substantially improve current melanoma prognostic models.