MétaCan
Menu
Back to cohort
Record W2394914116 · doi:10.1158/1557-3125.advbc15-a50

Abstract A50: Nonredundant functions of splicing factors in breast-cancer initiation and metastasis

2016· article· en· W2394914116 on OpenAlexaff
Olga Anczuków, Shipra Das, Kuan‐Ting Lin, Jie Wu, Martin Akerman, Senthil K. Muthuswamy, Adrian R. Krainer

Bibliographic record

VenueMolecular Cancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsRNA splicingAlternative splicingBiologyCancer researchMalignant transformationBreast cancerSplicing factorNeoplastic transformationMetastasisCancerContext (archaeology)Cell biologyRNAComputational biologyGeneMessenger RNACarcinogenesisGenetics

Abstract

fetched live from OpenAlex

Abstract Alternative splicing is a key control point in gene expression, whose misregulation contributes to cancer malignancy. Although certain splicing factors (SFs) and their targets are altered in human tumors, the functional significance of these alterations remains unclear. We previously demonstrated that the splicing factor SRSF1 is upregulated in human breast tumors and promotes transformation in vivo and in vitro. SRSF1 is a prototypical member of the SR protein family, composed of 12 structurally related proteins. However, little is known about differences and redundancies in their splicing targets and biological functions. Here, we investigated whether additional SFs also promoted breast cancer, using transformation models that mimic the relevant biological context. In parallel, we used RNA sequencing (RNA-seq) to systematically identify their oncogenic splicing targets. By mining a large collection of human tumors from the TCGA project, we defined the molecular portraits of SFs alterations in breast tumors. We identified five SFs amplified and/or overexpressed in at least 10% of breast tumors. We then used SF-overexpressing human mammary epithelial MCF-10A cells grown in organotypic 3-D culture; these cells form polarized growth-arrested acinar structures, similar to the terminal units of mammary ducts. Various breast-cancer oncogenes are known to disrupt acinar growth and/or architecture. Interestingly, only certain SFs were oncogenic in this context, differentially affecting cell proliferation, apoptosis, or acinar organization, suggesting non-redundant functions. We then characterized the splicing targets relevant for SF-mediated transformation. We developed a bioinformatics pipeline to identify and quantify splicing variation in RNA-seq data. We defined the global repertoire of SF-regulated splicing events in 3-D culture and compared the target specificities of various SR proteins. In addition, we identified splicing targets regulated both in 3-D culture as well as in human breast tumors. Strikingly, SFs that promoted similar phenotypic changes shared a significant number of splicing targets, suggesting that they regulate common genes to promote tumor initiation. Furthermore, specific SFs affected targets previously associated with epithelial to mesenchymal transition, and increased cell migration or invasion. Finally, we uncovered that the splicing regulator TRA2β is required for the maintenance of metastatic properties of human breast-cancer cells in 3-D culture and in mouse orthotopic models. Furthermore, TRA2β levels correlate with increased metastatic incidence in breast cancer patients. Thus TRA2β represent a potential target for therapeutics development. In summary, we gained new insights into the biological functions of SR proteins and identified novel oncogenic SF-regulated splicing events involved in tumor initiation and metastasis. Citation Format: Olga Anczuków, Shipra Das, Kuan-Ting Lin, Jie Wu, Martin Akerman, Senthil K. Muthuswamy, Adrian R. Krainer. Nonredundant functions of splicing factors in breast-cancer initiation and metastasis. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr A50.

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 score0.150
Threshold uncertainty score0.413

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 head0.048
GPT teacher head0.372
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 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueMolecular Cancer ResearchSame topicRNA Research and SplicingFrench-language works237,207