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Record W2175083747 · doi:10.18632/oncotarget.6046

Suppression of Her2/Neu mammary tumor development in <i>mda-7/IL-24</i> transgenic mice

2015· article· en· W2175083747 on OpenAlexafffundabout
Youjun Li, Guodong Liu, Lei Xia, Xiao Xiao, Jeff C. Liu, Mitchell E. Menezes, Swadesh K. Das, Luni Emdad, Devanand Sarkar, Paul B. Fisher, Michael C. Archer, Eldad Zacksenhaus, Yaacov Ben‐David

Bibliographic record

VenueOncotarget · 2015
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsUniversity Health NetworkUniversity of Toronto
FundersCanadian Cancer Society Research InstituteTerry Fox FoundationNational Natural Science Foundation of ChinaNational Foundation for Cancer ResearchSamuel Waxman Cancer Research Foundation
KeywordsGenetically modified mouseTransgeneCancer researchMedicineHER2/neuMammary tumorBiologyBreast cancerCancerInternal medicineGeneGenetics

Abstract

fetched live from OpenAlex

// You-Jun Li 1,* , Guodong Liu 2,* , Lei Xia 4 , Xiao Xiao 4 , Jeff C. Liu 5 , Mitchell E. Menezes 6 , Swadesh K. Das 6 , Luni Emdad 6 , Devanand Sarkar 6 , Paul B. Fisher 6 , Michael C. Archer 2,3 , Eldad Zacksenhaus 3,5 and Yaacov Ben-David 3,4 1 Department of Anatomy, Norman Bethune College of Medicine, Jilin University, Changchun, Jilin, China 2 Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada 3 Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada 4 Division of Biology, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guiyang, China 5 Toronto General Research Institute - University Health Network, Toronto, Ontario, Canada 6 Department of Human and Molecular Genetics, VCU Institute of Molecular Medicine, VCU Massey Cancer Center, Virginia Commonwealth University, School of Medicine, Richmond, Virginia, USA * These authors have contributed equally to this work Correspondence to: Yaacov Ben-David, email: // Eldad Zacksenhaus, email: // Keywords : mda-7/IL-24, HER2, breast cancer, prevention, mouse model Received : July 06, 2015 Accepted : September 23, 2015 Published : October 09, 2015 Abstract Melanoma differentiation associated gene-7/interleukin-24 ( mda-7/IL-24 ) encodes a tumor suppressor gene implicated in the growth of various tumor types including breast cancer. We previously demonstrated that recombinant adenovirus-mediated mda-7/IL-24 expression in the mammary glands of carcinogen-treated (methylnitrosourea, MNU) rats suppressed mammary tumor development. Since most MNU-induced tumors in rats contain activating mutations in Ha-ras, which arenot frequently detected in humans, we presently examined the effect of MDA-7/IL-24 on Her2/Neu - induced mammary tumors, in which the RAS pathway is induced. We generated tet-inducible MDA-7/IL-24 transgenic mice and crossed them with Her2/Neu transgenic mice. Triple compound transgenic mice treated with doxycycline exhibited a strong inhibition of tumor development, demonstrating tumor suppressor activity by MDA-7/IL-24 in immune-competent mice. MDA-7/IL-24 induction also inhibited growth of tumors generated following injection of Her2/Neu tumor cells isolated from triple compound transgenic mice that had not been treated with doxycycline, into the mammary fat pads of isogenic FVB mice. Despite initial growth suppression, tumors in triple compound transgenic mice lost mda-7/IL-24 expression and grew, albeit after longer latency, indicating that continuous presence of this cytokine within tumor microenvironment is crucial to sustain tumor inhibitory activity. Mechanistically, MDA-7/IL-24 exerted its tumor suppression effect on HER2 + breast cancer cells, at least in part, through PERP, a member of PMP-22 family with growth arrest and apoptosis-inducing capacity. Overall, our results establish mda-7/IL-24 as a suppressor of mammary tumor development and provide a rationale for using this cytokine in the prevention/treatment of human breast cancer.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.037
GPT teacher head0.286
Teacher spread0.249 · 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

Citations17
Published2015
Admission routes3
Has abstractyes

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