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Record W4206485610 · doi:10.1172/jci149473

ATP11B inhibits breast cancer metastasis in a mouse model by suppressing externalization of nonapoptotic phosphatidylserine

2022· article· en· W4206485610 on OpenAlexaff

Bibliographic record

VenueJournal of Clinical Investigation · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicATP Synthase and ATPases Research
Canadian institutionsHealth Sciences Centre
FundersFundo para o Desenvolvimento das Ciências e da TecnologiaZhejiang UniversityFaculdade de Ciências da Saúde, Universidade de MacauUniversidade de Macau
KeywordsMetastasisBreast cancerCancerCancer cellPhosphatidylserineCytotoxic T cellPhenotypePaclitaxelSuppressor

Abstract

fetched live from OpenAlex

Cancer metastasis is the cause of the majority of cancer-related deaths. In this study, we demonstrated that no expression or low expression of ATP11B in conjunction with high expression of PTDSS2, which was negatively regulated by BRCA1, markedly accelerates tumor metastasis. Further analysis revealed that cells with low ATP11B expression and high PTDSS2 expression (ATP11BloPTDSS2hi cells) were associated with poor prognosis and enhanced metastasis in breast cancer patients in general. Mechanistically, an ATP11BloPTDSS2hi phenotype was associated with increased levels of nonapoptotic phosphatidylserine (PS) on the outer leaflet of the cell membrane. This PS increase serves as a global immunosuppressive signal to promote breast cancer metastasis through an enriched tumor microenvironment with the accumulation of myeloid-derived suppressor cells and reduced activity of cytotoxic T cells. The metastatic processes associated with ATP11BloPTDSS2hi cancer cells can be effectively overcome by changing the expression phenotype to ATP11BhiPTDSS2lo through a combination of anti-PS antibody with either paclitaxel or docetaxel. Thus, blocking the ATP11BloPTDSS2hi axis provides a new selective therapeutic strategy to prevent metastasis in breast cancer patients.

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 score0.056
Threshold uncertainty score0.328

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 science0.0000.000
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 head0.055
GPT teacher head0.389
Teacher spread0.333 · 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

Citations25
Published2022
Admission routes1
Has abstractyes

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