Langerhans cell histiocytosis (LCH) is characterized by inflammatory lesions containing pathologic CD207 dendritic cells with constitutively activated ERK. Mutually exclusive somatic mutations in MAPK pathway genes have been identified in ∼75% of LCH cases, including recurrent BRAF-V600E and MAP2K1 mutations. To elucidate mechanisms of ERK activation in the remaining 25% of patients, we performed whole-exome sequencing (WES, n = 6), targeted BRAF sequencing (n = 19), and/or whole-transcriptome sequencing (RNA-seq, n = 6) on 24 LCH patient samples lacking BRAF-V600E or MAP2K1 mutations. WES and BRAF sequencing identified in-frame BRAF deletions in the β3-αC loop in 6 lesions. RNA-seq revealed one case with an in-frame FAM73A-BRAF fusion lacking the BRAF autoinhibitory regulatory domain but retaining an intact kinase domain. High levels of phospho-ERK were detected in vitro in cells overexpressing either BRAF fusion or deletion constructs and ex vivo in CD207 cells from lesions. ERK activation was resistant to BRAF-V600E inhibition, but responsive to both a second-generation BRAF inhibitor and a MEK inhibitor. These results support an emerging model of universal ERK-activating genetic alterations driving pathogenesis in LCH. A personalized approach in which patient-specific alterations are identified may be necessary to maximize benefit from targeted therapies for patients with LCH.

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BACKGROUND: Central nervous system Langerhans cell histiocytosis (CNS-LCH) brain involvement may include mass lesions and/or a neurodegenerative disease (LCH-ND) of unknown etiology. The goal of this study was to define the mechanisms of pathogenesis that drive CNS-LCH. METHODS: Cerebrospinal fluid (CSF) biomarkers including CSF proteins and extracellular BRAFV600E DNA were analyzed in CSF from patients with CNS-LCH lesions compared with patients with brain tumors and other neurodegenerative conditions. Additionally, the presence of BRAFV600E was tested in peripheral mononuclear blood cells (PBMCs) as well as brain biopsies from LCH-ND patients, and the response to BRAF-V600E inhibitor was evaluated in 4 patients with progressive disease. RESULTS: Osteopontin was the only consistently elevated CSF protein in patients with CNS-LCH compared with patients with other brain pathologies. BRAFV600E DNA was detected in CSF of only 2/20 (10%) cases, both with LCH-ND and active lesions outside the CNS. However, BRAFV600E+ PBMCs were detected with significantly higher frequency at all stages of therapy in LCH patients who developed LCH-ND. Brain biopsies of patients with LCH-ND demonstrated diffuse perivascular infiltration by BRAFV600E+ cells with monocyte phenotype (CD14+CD33+CD163+P2RY12−) and associated osteopontin expression. Three of 4 patients with LCH-ND treated with BRAF-V600E inhibitor experienced significant clinical and radiologic improvement. CONCLUSION: In LCH-ND patients, BRAFV600E+ cells in PBMCs and infiltrating myeloid/monocytic cells in the brain is consistent with LCH-ND as an active demyelinating process arising from a mutated hematopoietic precursor from which LCH lesion CD207+ cells are also derived. Therapy directed against myeloid precursors with activated MAPK signaling may be effective for LCH-ND.

In a recent paper by Hellerstein [15], a tight relationship was conjectured between the number of strata of a Datalog ¬ program and the number of "coordination stages" required for its distributed computation. Indeed, Ameloot et al. [9] showed that a query can be computed by a coordinationfree relational transducer network iff it is monotone, thus answering in the affirmative a variant of Hellerstein's CALM conjecture, based on a particular definition of coordinationfree computation. In this paper, we present three additional models for declarative networking. In these variants, relational transducers have limited access to the way data is distributed. This variation allows transducer networks to compute more queries in a coordination-free manner: e.g., a transducer can check whether a ground atom A over the input schema is in the "scope" of the local node, and then send either A or ¬A to other nodes.We show the surprising result that the query given by the well-founded semantics of the unstratifiable win-move program is coordination-free in some of the models we consider. We also show that the original transducer network model [9] and our variants form a strict hierarchy of classes of coordination-free queries. Finally, we identify different syntactic fragments of Datalog ¬¬ ∀ , called semi-monotone programs, which can be used as declarative network programming languages, whose distributed computation is guaranteed to be eventually consistent and coordination-free.

Key Points Transcriptional profile of LCH CD1a+CD207+ DCs is most closely related to that of CD1c+ mDCs in the blood. Lineage tracing with BRAFV600E and HLA-DQB2 expression supports CD1c+ mDCs as precursors to LCH CD1a+CD207+ DCs.

Abstract. We propose a new model of provenance, based on a game-theoretic approach to query evaluation. First, we study games G in their own right, and ask how to explain that a position x in G is won, lost, or drawn. The resulting notion of game provenance is closely related to winning strategies, and excludes from provenance all "bad moves", i.e., those which unnecessarily allow the opponent to improve the outcome of a play. In this way, the value of a position is determined by its game provenance. We then define provenance games by viewing the evaluation of a first-order query as a game between two players who argue whether a tuple is in the query answer. For RA + queries, we show that game provenance is equivalent to the most general semiring of provenance polynomials N[X]. Variants of our game yield other known semirings. However, unlike semiring provenance, game provenance also provides a "built-in" way to handle negation and thus to answer why-not questions: In (provenance) games, the reason why x is not won, is the same as why x is lost or drawn (the latter is possible for games with draws). Since first-order provenance games are draw-free, they yield a new provenance model that combines how-and why-not provenance.

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