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Record W2060868558 · doi:10.1158/1538-7445.am2014-4971

Abstract 4971: Splicing factor kinase regulates metastatic dissemination of human prostate cancer

2014· article· en· W2060868558 on OpenAlexaff
David Bond, Konstantin Stoletov, Hon S. Leong, Emma Woolner, Shuhong Liu, Tarek A. Bismar, Andries Zijlstra, John D. Lewis

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsLondon Health Sciences CentreUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMetastasisProstate cancerCancer researchCancerBiologyCancer cellPathologyMedicineGenetics

Abstract

fetched live from OpenAlex

Abstract Metastasis causes the vast majority of cancer-associated deaths. Despite its clinical significance, the molecular mechanisms that regulate this multi-step process are poorly understood. To successfully disseminate a cancer cell must escape the primary tumor, travel to a distant site, arrest, enter the stroma and grow in a new microenvironment. The presence of circulating tumor cells in patients with metastatic disease and experimental animals with metastatic cancers suggests that tumor invasion is a critical, rate-limiting step in the metastatic process. To identify the key molecular determinants that regulate invasive metastatic lesion formation we performed the first whole-genome, in vivo RNAi screen in an avian embryo model using advanced intravital imaging techniques. We identified numerous novel regulators of cancer cell invasion, including JL1, a splicing factor kinase. In secondary assays, we demonstrated that JL1-depletion inhibits migration of several human cancer cell lines with no effect on proliferation or survival. Furthermore, JL1-deficient human cancer cells display diminished metastatic potential in chicken embryo and mouse models of metastasis. Cancer microarray database mining shows that JL1 gene expression is strongly associated with indicators of poor clinical outcome in prostate cancer, including pathological Gleason score and metastasis. To experimentally determine JL1 association with advanced disease we performed histological examinations of prostate cancer tissue and determined that JL1 staining strongly correlates with prostate cancer progression. JL1 kinase regulates alternative splicing of numerous cellular transcripts in response to stress and growth signals. To examine the molecular mechanism behind JL1 regulation of cancer cell metastasis, we performed exon level microarray analysis on JL1-depleted cancer cell lines. Subsequent interactome analysis identified an enrichment of key regulatory proteins in pro-metastatic networks. Therefore, we hypothesize that abrogated JL1 activity directly promotes prostate cancer cell migration and invasion. In summary, JL1 is a novel regulator of cancer cell metastasis that represents a potential pathological marker for prostate cancer progression, and novel drug target to block invasion and metastasis. Citation Format: David J. Bond, Konstantin Stoletov, Hon Sing Leong, Emma Woolner, Shuhong Liu, Tarek Bismar, Andries Zijlstra, John D. Lewis. Splicing factor kinase regulates metastatic dissemination of human prostate cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4971. doi:10.1158/1538-7445.AM2014-4971

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 score0.006

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)0.0020.001

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 head0.042
GPT teacher head0.419
Teacher spread0.377 · 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
Published2014
Admission routes1
Has abstractyes

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