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Record W3048255749 · doi:10.1158/1538-7445.pedca19-b69

Abstract B69: Epigenomics and single-cell sequencing define a developmental hierarchy in Langerhans cell histiocytosis

2020· article· en· W3048255749 on OpenAlexaboutno aff
Florian Halbritter, Matthias Farlik, Raphaela Schwentner, Gunhild Jug, Nikolaus Fortelny, Ingrid Simonitsch‐Klupp, Wolfgang Bauer, Christoph Bock, Caroline Hutter

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicHistiocytic Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsLangerhans cell histiocytosisBiologyLineage markersChromatinEpigenomicsPhenotypeCancer researchGeneticsPathologyGene expressionGeneDiseaseDNA methylationMedicine

Abstract

fetched live from OpenAlex

Abstract Langerhans cell histiocytosis (LCH) is a rare neoplasm predominantly affecting children. It occupies a characteristic hybrid position between cancer and inflammatory disease, which makes it an attractive model for studying cancer development. Constitutive activation of the ERK signaling pathway is a common feature of LCH, but its pathogenesis remains unclear. To explore the molecular mechanisms underlying the pathophysiology of LCH and the mechanisms that might cause the characteristic clinical heterogeneity of this disease, we investigated cellular heterogeneity in primary LCH lesions. We used a multilayered approach employing immunohistochemistry, flow cytometry, single-cell RNA-sequencing, and ATAC-sequencing of biopsies obtained from different patients with LCH. Based on the single-cell RNA expression data, we identified different LCH cell populations within LCH lesions that display distinct pathway signatures, including a stem cell-like, proliferative state and different subsets with a more differentiated phenotype, including subsets similar to maturing antigen-presenting cells and a subset that could contribute to tissue destruction in LCH. Computational analysis discovered a hierarchy between these cells that suggests a directed developmental program in each tumor. We confirmed the presence of these distinct subsets using immunohistochemical analysis of different biopsies. Furthermore, using chromatin accessibility profiling in prospectively purified LCH cell subsets in combination with single-cell RNA-seq data and integrative bioinformatic analysis, we analyzed the transcription factors and gene regulatory networks that may underlie the observed developmental hierarchy in LCH lesions. This analysis reveals an intricate interplay of immune-regulatory (including JAK-STAT, AP-1, and NF-κB signaling) and developmental regulators (including epigenetic modifiers such as EP300 or KDMs) that may shape LCH cell development. Together, this study sketches a molecular portrait of LCH lesions and enables new, unprecedented insight into this disease. Moreover, it demonstrates the power of combining single-cell RNA-sequencing and epigenome profiling for dissecting complex developmental hierarchies and their regulatory underpinnings, and thus can serve as a template for the analysis of tumorigenesis beyond LCH. Citation Format: Florian Halbritter, Matthias Farlik, Raphaela Schwentner, Gunhild Jug, Nikolaus Fortelny, Ingrid Simonitsch-Klupp, Wolfgang Bauer, Christoph Bock, Caroline Hutter. Epigenomics and single-cell sequencing define a developmental hierarchy in Langerhans cell histiocytosis [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B69.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.155
GPT teacher head0.346
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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