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Record W4205787518 · doi:10.21203/rs.3.rs-1233380/v1

Spatial and molecular profiling of the classic Hodgkin lymphoma microenvironment reveals an immunosuppressive mononuclear phagocyte network

2022· preprint· en· W4205787518 on OpenAlexfundno aff
Benjamin J. Stewart, Martin Fergie, Matthew D. Young, Claire Jones, Ashwin Sachdeva, Alex E. Blain, Chris M. Bacon, Vikki Rand, John R. Ferdinand, Kylie R. James, Krishnaa T. Mahbubani, Liz Hook, Nicolaas Jonas, Nicholas Coleman, Kourosh Saeb‐Parsy, Matthew Collin, Menna R. Clatworthy, Sam Behjati, Christopher D. Carey

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsnot available
FundersMedical Research CouncilCenters for Disease Control and PreventionNewcastle UniversityUniversity of British ColumbiaWellcome TrustJGW Patterson Foundation
KeywordsMononuclear phagocyte systemPhagocyteProfiling (computer programming)LymphomaHodgkin lymphomaTumor microenvironmentBiologyComputational biologyImmunologyComputer scienceImmune system

Abstract

fetched live from OpenAlex

Abstract Although a lymph node infiltrated by classic Hodgkin lymphoma is mostly composed of non-neoplastic immune cells, the malignant Hodgkin Reed-Sternberg cells (HRSC) successfully suppress an anti-tumor immune response, to create a cancer-permissive microenvironment. Accordingly, unleashing the dormant immune cells, for example by checkpoint inhibition, has been a central focus of recent therapeutic advances for this disease. Here, we profiled the global immune cell composition of normal and diseased lymph nodes by single-cell RNA sequencing, as a basis for interrogating the immediate vicinity of HRSC, first regionally and then at cellular resolution. Our analyses revealed specific immune cells and functional states associated with HRSC. Most prominently, we discovered a non-random spatial association of immunoregulatory mononuclear phagocytes positioned around HRSC, which express the immune checkpoints PD-L1, TIM-3, and the tryptophan-catabolizing protein IDO1. These findings provide a basis for rational targeting and activation of the anti-tumor immune response in classic Hodgkin lymphoma.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.003
Research integrity0.0000.001
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 head0.026
GPT teacher head0.302
Teacher spread0.276 · 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.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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