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Record W2317785746 · doi:10.1158/1538-7445.am2011-1973

Abstract 1973: Caveolin-1 promotes cell proliferation, EGFR activation and tumor growth in kidney cancer

2011· article· en· W2317785746 on OpenAlexaff
Chao Xu, Yi Wang, O. Roche, Eduardo H. Moriyama, Michael Ohh

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCaveolin-1 and cellular processes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCancer researchEpidermal growth factor receptorCaveolin 1Cell growthCarcinogenesisBiologyClear cell renal cell carcinomaGene knockdownTumor progressionSignal transductionEpidermal growth factorCancerCell biologyReceptorMedicineCell cultureInternal medicineRenal cell carcinoma

Abstract

fetched live from OpenAlex

Abstract Tumor hypoxia is associated with disease progression, drug resistance and poor prognosis. It has been shown previously that hypoxia prolongs the activation of epidermal growth factor receptor (EGFR) by delaying clathrin-dependent endocytosis-mediated deactivation of receptors. Recently, caveolin (CAV) mediated signaling and trafficking have been reported to be involved in the oncogenesis of many tumours, including clear cell renal cell carcinoma (CCRCC). However, the role of CAV-1 in the tumor progression is unclear. Here, we show that the loss of von Hippel-Lindau (VHL) protein – the principal negative regulator of hypoxia-inducible factor (HIF) – increases the auto-phosphorylation of epidermal growth factor receptor (EGFR), thus attributing to an enhanced ligand-independent cell signaling pathway, majorly Ras-Raf-MEK-ERK pathway, and leading to cell proliferation. The auto-phosphorylation of EGFR is due to the HIF-dependent overexpression of caveolin-1 (CAV-1) at the level of transcription, which enhances the association between EGFR and CAV-1 and the auto-dimerization of EGFR. Primary CCRCC tumors and numerous hypoxia treated tumor cell lines exhibit significantly higher expression of CAV-1 protein. Using a dorsal skin-fold window chamber on SCID mice, shCAV-1 knockdown 786-O tumor cell line exhibits lower growth than that of shscramble counterpart in xenografts. These findings support a model in which tumour hypoxia or oncogenic activation of HIF prolongs ligand-independent RTK signaling through the over-expression of CAV-1. Given the oncogenic role of CAV-1, it should be considered as a future therapeutic target in cancer treatment. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1973. doi:10.1158/1538-7445.AM2011-1973

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 score0.003
Threshold uncertainty score0.011

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)0.0030.001

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 head0.045
GPT teacher head0.329
Teacher spread0.284 · 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
Published2011
Admission routes1
Has abstractyes

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