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Record W2519939644 · doi:10.1002/eji.201646552

Tumor‐secreted products repress B‐cell lymphopoiesis in a murine model of breast cancer

2016· article· en· W2519939644 on OpenAlexafffund
J. Moreau, Michael Mielnik, Alexandra Berger, Caren Furlonger, Christopher J. Paige

Bibliographic record

VenueEuropean Journal of Immunology · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersPrincess Margaret Cancer Foundation
KeywordsBiologyLymphopoiesisCancer researchBreast cancerCancerImmunologyCell biologyHaematopoiesisGeneticsStem cell

Abstract

fetched live from OpenAlex

Growing cancers are known to modify immune responses through suppressive mechanisms manifested within the local tumor microenvironment. Accumulating evidence indicates that secreted tumor products can also influence on distant immunological compartments, including myelopoiesis in the bone marrow. However, it is unknown if a similar effect can occur to regulate B-cell lymphopoiesis in breast cancer. Examining the MMTV-PyMT murine model of breast cancer, we show a complete block in bone marrow B-cell lymphopoiesis, which is dependent on tumor burden. We also observed an increase in the total number of splenic B cells and an elevated frequency of marginal zone B cells. By using in vitro assays of B-cell lymphopoiesis, we show that tumor-secreted molecules directly inhibit B-cell progenitor proliferation and favor maturation. These data demonstrate a profound sensitivity of B-cell lymphopoiesis to the accumulation of ectopically produced molecules during tumor growth in PyMT.

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 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 score0.048
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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

Citations9
Published2016
Admission routes2
Has abstractyes

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