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Abstract P5-11-08: SRA/SRAP contributes to TGF-b1 induced cell motility in cancer cells

2013· article· en· W2024533807 on OpenAlexaff
CM Cooper, Yongqing Yan, Weiwei Xu, D Tsuyuki, MK Hamedani, James Davie, Etienne Leygue

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsBiologyTranscriptomeCarcinogenesisGeneRNA interferenceCancer researchEstrogen receptorTranscription factorGene expressionRNABreast cancerCell biologyCancerGenetics

Abstract

fetched live from OpenAlex

Abstract The steroid receptor RNA activator gene (SRA1) is a particularly intriguing genetic system in that both the corresponding RNA (SRA) and protein (SRAP) have been proven to be functional. Accumulated evidence overall suggests that both molecules act as distinct co-regulators of transcription, housed in ribonucleo-protein complexes able to positively or negatively regulate the activity of multiple transcription factors including -but not limited to- several nuclear receptors, MyoD and DAX-1. A role for SRA/SRAP deregulation during breast tumorigenesis has been suggested. Indeed, not only do these molecules regulate the activity of both Estrogen Receptors, these major players in breast cancer etiology, but it has also been shown that SRA RNA is more highly expressed in breast tumors than in normal tissue, and that high levels of SRAP correlated to poorer survival in specific subsets of breast cancer patients. In order to identify the genes and pathways regulated by SRA/SRAP, we performed deep sequencing of transcriptomes from MDA-MB-231 cells depleted of these molecules following RNA interference. The expression of 149 genes was consistently and significantly altered in four independent experiments comparing control RNAi vs SRA RNAi. Interestingly, cluster analysis using Ingenuity software defined a subset of genes (23 out of 149) directly associated with cell movement. Among them figured TGFBR1 (ALK5), a cell surface receptor-kinase mediating TGF-b signalling and a known promoter of cell motility in breast cancer cells. We have now confirmed by quantitative PCR analysis a 40% decrease, upon SRA/SRAP depletion, of TGFBR1 mRNA expression in MDA-MB-231 cells as well as in other breast (MCF7, T5) and non-breast (Hela) cancer cell lines. Consistent with this decrease a drop to 60% of the basal TGFBR1 protein expression is seen by Western blot when MDA-MB-231 cells are depleted of SRA/SRAP. Western blot analyses also revealed that phosphorylation of several SMAD molecules, downstream effectors of TGFBR1 activation by TGF-β1, is impaired in the absence of SRA/SRAP in both MDA-MB-231 and Hela cells. This suggests that SRA/SRAP could potentially regulate TGF beta induced cell motility. Using migration cell assays, we have now confirmed that upon TGF-β1 treatment for 6 hours, SRA/SRAP depleted cells had a significant decrease in migration as compared to control cells. Accordingly, live cell migration assays generated by a time-lapse videomicroscopy system, showed an increased track length and speed in both Hela and 231 cells over-expressed SRAP upon 10 h TGF-β1 treatment. Taken together, these data suggest a cross-talk between SRA/SRAP and TGF-β signalling and induced cell motility. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P5-11-08.

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 score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0080.005

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 head0.072
GPT teacher head0.397
Teacher spread0.325 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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