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Record W2504726256 · doi:10.1158/1538-7445.am2016-941

Abstract 941: Differential roles for membrane-bound and soluble CD109 in breast cancer progression

2016· article· en· W2504726256 on OpenAlexaff
Priyanka Sehgal, Anie Philip

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTGF-β signaling in diseases
Canadian institutionsMcGill University
Fundersnot available
KeywordsBreast cancerCancer researchEpithelial–mesenchymal transitionCancerVimentinBiologyCancer cellSMADMedicineTransforming growth factorImmunologyInternal medicineMetastasisEndocrinologyImmunohistochemistry

Abstract

fetched live from OpenAlex

Abstract Introduction: Our group has recently reported the identification of CD109 (a GPI anchored cell surface glycoprotein) as a TGF-β co-receptor and potent antagonist of TGF-β signaling and responses in human epithelial cells in vitro and in vivo. Proteinase mediated shedding converts CD109 from a membrane-bound coreceptor into a soluble effector capable of binding TGF-β. Our results indicate that CD109 overexpression inhibits TGF-β -induced Epithelial Mesenchymal Transition (EMT) and migration in breast cancer cells in vitro. However, in breast carcinomas, CD109 overexpression correlates with poor prognosis and an aggressive phenotype. Our findings together with the recent report of over expression of CD109 in breast cancer provide compelling reasons to examine whether membrane anchored or soluble CD109 plays an essential role in breast cancer progression and thus represent a molecular target for the treatment of breast cancer. Methods: To investigate the role of CD109 in breast cancer cells that overexpress membrane-anchored (m)CD109 or soluble (s)CD109, or in which endogenous CD109 expression is blocked, or breast cancer cells treated with recombinant CD109 protein, were analysed for SMAD signaling and EMT markers (Fibronectin, PAI, Vimentin, N-cadherin, α-sma, Snail) using immunoblotting. Cell migration and invasion potential in response to TGF-β were assessed using scratch assay and boyden chamber assay, respectively. Results: To determine the role of CD109 in breast cancer progression, human MDA-MB-231 breast cancer cells were transfected with plasmid overexpressing wild-type (WT) which has the potential to shed CD109. Overexpression of WT CD109 decreased TGF-β induced phospho-SMAD signaling, EMT, migration and invasion of breast cancer cells. Conversely, treatment of Hs578T breast cancer cells with CD109 siRNA increased TGF-β induced phospho SMAD signaling, EMT, migration and invasion of cancer cells. In an alternate approach breast cancer cells treated with recombinant CD109 (resembling the shed form of CD109) also showed decreased TGF-β induced EMT, migration and invasion of cancer cells. However overexpression of membrane bound (furinase-mediated shedding resistant) form of CD109 in MDA-MB-231 breast cancer cells showed increased EMT, migration and invasion of cancer cells. Analysis of downstream signaling showed that although both membrane bound and soluble form of CD109 attenuates TGF-β signaling, the membrane bound CD109 promotes tumor aggressiveness. Conclusion: Taken together, these results suggest that membrane anchored and soluble form of CD109 have different role in breast cancer. Both membrane bound and soluble CD109 inhibit TGF-β signaling in breast cancer however the membrane bound form of CD109 can promote cancer progression. Mechanisms underlying the differential effect of these two forms of CD109 in breast cancer need to be deciphered. Citation Format: Priyanka Sehgal, Anie Philip. Differential roles for membrane-bound and soluble CD109 in breast cancer progression. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 941.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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)0.0050.001

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 head0.039
GPT teacher head0.401
Teacher spread0.362 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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