MétaCan
Menu
Back to cohort
Record W2563676032 · doi:10.1158/1538-7445.am2015-1018

Abstract 1018: Role of Stat3 vs Stat5 in the differentiation of HC11, mouse breast epithelial cells

2015· article· en· W2563676032 on OpenAlexaff
Jamaica Cass, Maximilian Niit, Rozanne Arulanandam, Bruce E. Elliott, Leda Raptis

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsQueen's University
Fundersnot available
KeywordsSTAT3Cancer researchSTAT proteinSTAT5BiologyRAC1Transcription factorCell biologySignal transduction

Abstract

fetched live from OpenAlex

Abstract The Signal Transducer and Activator of Transcription (Stat)3 and Stat5 are transcription factors involved in normal breast development, and are hyperactivated in 30-50% of breast cancers. Stat5 is required for breast epithelial cell differentiation and is over-expressed in breast cancers with a more differentiated phenotype. On the other hand, constitutive over-activation of Stat3 can drive expression of genes involved in survival, migration and angiogenesis, while mutationally activated Stat3 (Stat3C) can transform cultured cells, indicating that Stat3 may play an important role in cancer etiology. Following activation of a number of growth factor or cytokine receptors such as interleukin-6 or expression of oncogenes such as Src, Stat3 is phosphorylated at tyr-705, dimerizes and migrates to the nucleus where it activates transcription from a number of genes involved in cell division and survival, such as survivin, Bcl-xL, Mcl1 and myc, while it downregulates expresssion of the tumor suppressor p53. We recently discovered a novel pathway of activation of Stat3: Engagement of cadherins (E-, N-cadherin or cadherin-11), cell to cell adhesion proteins induces a dramatic increase in the levels of the Rac1 and Cdc42 small GTPases, and this leads to interleukin-6 transcription, hence Stat3 activation. The differentiation of HC11, nonneoplastic mouse breast epithelial cells requires prolactin, hydrocortisone and insulin, added at confluence. Since confluence activates Stat3, we examined the role of Stat3 upon breast epithelial cell differentiation, measured by cellular morphology and expression of the milk proteins, β-casein or whey acidic protein. Through pharmacological inhibition with CPA7 or S3I-201, our results demonstrate that Stat3 is, in fact, required for HC11 cell differentiation. In contrast, constitutive expression of mutationally activated Rac1 was found to block differentiation while inducing transformation. In sharp contrast, our results indicate that Stat5 is upregulated by the differentiation cocktail but is unaffected by cell density, while expression of activated Stat5 promotes a more differentiated phenotype. Taken together, our results demonstrate that Stat3 and Stat5 may constitute independent prognostic markers as well as treatment targets for breast cancer. Citation Format: Jamaica Cass, Maximilian Niit, Rozanne Arulanandam, Bruce Elliott, Leda Raptis. Role of Stat3 vs Stat5 in the differentiation of HC11, mouse breast epithelial cells. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1018. doi:10.1158/1538-7445.AM2015-1018

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.036
GPT teacher head0.344
Teacher spread0.308 · 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 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

Citations1
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicNutrition, Genetics, and DiseaseFrench-language works237,207