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Record W2499226924 · doi:10.1158/1538-7445.am2016-5070

Abstract 5070: CD44 alternative splice variants are associated with prostate cancer cell identity and migration

2016· article· en· W2499226924 on OpenAlexaff
David Bond, John D. Lewis

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCD44BiologyAlternative splicingRNA splicingCancer researchProstate cancerMetastasisCancerCancer cellCellCell biologyExonGeneticsGeneRNA

Abstract

fetched live from OpenAlex

Abstract Patient tumors can demonstrate tremendous cell-to-cell genetic heterogeneity while cultured cancer cell lines are often more homogeneous. This fundamental difference can undermine in vitro findings and their application to the more complex in vivo tumor environment. However, it should not be assumed that cultured cells are homogeneous even in well established and widely used cell lines. In my study of CD44 alternative splicing in the prostate cancer cell line PC3, I encountered varying CD44 alternative splicing expression profiles dependent on the origin of the PC3 cell line. CD44 is a cell surface glycoprotein that binds to components of the extracellular matrix, including hyaluronan, and is primarily involved in cell-cell and cell-matrix interactions. CD44 contains 10 variable exons that when combined in particular combinations significantly alter/guide CD44 downstream activities. In the context of cancer biology, alternative splicing of CD44 can control the epithelial to mesenchymal transition (EMT) of cancer cells and is associated with metastasis in many types cancers such as breast and prostate. To determine if cellular heterogeneity was the source of variable CD44 alternative splicing profiles, I isolated PC3 single cell clones. From these clones I identified two cell populations based on colony morphology: a compact colony subset with cells of a epithelial phenotype (PC3-EL), and a diffuse colony subset with cells of a mesenchymal phenotype (PC3-ML). I then performed reverse transcription-PCR (rt-PCR) on cDNA generated from these two populations with primers that specifically amplify the CD44 variable region to generate a fingerprint of CD44 alternative splicing. I found that PC3 cells with an epithelial phenotype express multiple CD44 variant exons (CD44v), including the epithelium-associated CD44v1,v8-10 variant (CD44E). However, phenotypically mesenchymal PC3 cells show a complete loss of CD44 splice variants and primarily express standard CD44v1 (CD44S). These differences in CD44 mRNA alternative spicing are manifested at the protein level as phenotypically epithelial PC3 cells express predominantly high molecular weight CD44 variants. I then monitored the association of CD44v expression on cell migration and determined that PC3 cells that express CD44E are non-motile, while PC3 cells that predominantly express CD44S are highly motile. Acquisition of CD44S over CD44E can signal EMT, an early and critical step in cancer metastasis. These data indicate that the CD44 alternative splice fingerprint may provide a predictive biomarker for EMT and the acquisition of other early pro-metastatic features in prostate cancer cells. Citation Format: David J. Bond, John D. Lewis. CD44 alternative splice variants are associated with prostate cancer cell identity and migration. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5070.

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 score0.004
Threshold uncertainty score0.013

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)0.0040.001

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 head0.038
GPT teacher head0.383
Teacher spread0.345 · 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
Published2016
Admission routes1
Has abstractyes

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