MétaCan
Menu
Back to cohort
Record W2560940828 · doi:10.1158/1538-7445.am2015-4991

Abstract 4991: RET and integrins cooperate in cell-microenvironment response

2015· article· en· W2560940828 on OpenAlexaff
Eric Lian, Mathieu J. F. Crupi, Jessica Cockburn, Simona Wagner, Anirudh Goel, Lois M. Mulligan

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsQueen's University
Fundersnot available
KeywordsGlial cell line-derived neurotrophic factorIntegrinCell biologyBiologyCell adhesionGDNF family of ligandsExtracellular matrixCell migrationNeural crestReceptor tyrosine kinaseCell adhesion moleculeNeurotrophic factorsSignal transductionNeural cell adhesion moleculeCellReceptorGeneticsEmbryo

Abstract

fetched live from OpenAlex

Abstract The RET receptor tyrosine kinase is expressed in neural crest-derived cell types, where it is activated by soluble ligands of the Glial Cell-derived Neurotrophic Factor (GDNF) family and signals through multiple downstream pathways, contributing to cell growth, survival, and migration during embryonic development. In addition to its normal developmental roles, oncogenic mutations or aberrant expression of RET are also linked to tumour spread and metastasis in multiple human tumour types. Thus, a consistent feature of RET involvement in these disease processes is its contribution to directional cell motility. We have previously shown that RET-mediated cell-adhesion and migration requires multiple members of the integrin family of cell adhesion molecules, including integrin β1 (ITGB1) and β3 (ITGB3) subunits, however the regulation of cell migration and invasion by RET and integrins has not been explored. In this study, we showed that GDNF-mediated RET activation induced rapid ITGB1 and ITGB3 activation with transiently increased cell adhesion, followed by enhanced cell protrusion formation and reduced adhesion typical of more migratory cells. In addition, we showed that directional cell migration in response to GDNF requires the presence of both extracellular matrix and a GDNF concentration gradient. Our data also suggest that ITGB1 and ITGB3 play complementary but non-compensatory roles in the initiation of RET-mediated cell migration and invasion, and that the inhibition of either ITGB1 or ITGB3 resulted in impaired migration and invasion in both 2D and 3D culture conditions. We have also shown that multiple signaling pathways downstream of RET are involved in these processes and that these pathways contribute differently to migration in 2D vs 3D microenvironments. These data highlight the ability of tumour cells to leverage different signaling pathways to mediate cell migration and invasion downstream of RET, and reveal ways in which cooperation between RET and integrins might affect aspects of tumour progression. Our data, together with other studies which have shown combination therapy targeting integrins and RTKs to be more effective than monotherapy, suggest that adjuvant treatment with agents targeting integrin function may further enhance therapeutic options for tumours where RET is expressed. Citation Format: Eric Lian, Mathieu J.F. Crupi, Jessica G. Cockburn, Simona M. Wagner, Anirudh Goel, Lois M. Mulligan. RET and integrins cooperate in cell-microenvironment response. [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 4991. doi:10.1158/1538-7445.AM2015-4991

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0050.002

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 head0.061
GPT teacher head0.363
Teacher spread0.302 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicProtein Degradation and InhibitorsFrench-language works237,207