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Record W4205273857 · doi:10.1126/sciadv.abj9513

O-linked α2,3 sialylation defines stem cell populations in breast cancer

2022· article· en· W4205273857 on OpenAlexaff
Melanie R. Walker, Hira Lal Goel, Dimpi Mukhopadhyay, Peter Chhoy, Emmet R. Karner, Jennifer L. Clark, Haibo Liu, Rui Li, Lihua Julie Zhu, Shuhui Chen, Lara K. Mahal, Barbara A. Bensing, Arthur M. Mercurio

Bibliographic record

VenueScience Advances · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of Alberta
FundersNational Institute of Dental and Craniofacial ResearchNational Cancer Institute
KeywordsBreast cancerStem cellComputational biologyCancerCancer stem cellBiologyComputer scienceGenetics

Abstract

fetched live from OpenAlex

We pursued the hypothesis that specific glycans can be used to distinguish breast cancer stem cells (CSCs) and influence their function. Comparison of CSCs and non-CSCs from multiple breast cancer models revealed that CSCs are distinguished by expression of α2,3 sialylated core2 O-linked glycans. We identified a lectin, SLBR-N, which binds to O-linked α2,3 sialic acids, that was able to enrich for CSCs in vitro and in vivo. This O-glycan is expressed on CD44 and promotes its interaction with hyaluronic acid, facilitating CD44 signaling and CSC properties. In contrast, FUT3, which contributes to sialyl Lewis X (sLeX) production, is preferentially expressed in the non-CSC population, and it antagonizes CSC function. Collectively, our data indicate that SLBR-N can be more efficient at enriching for CSCs than CD44 itself because its use avoids the issues of CD44 splicing and glycan status. These data also reveal how differential glycosylation influences CSC fate.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.041
GPT teacher head0.337
Teacher spread0.296 · 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 designObservational
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

Citations30
Published2022
Admission routes1
Has abstractyes

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