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Record W2305209678

Activity of signaling pathways in hypoxic pancreatic and cervical tumor xenografts

2007· article· en· W2305209678 on OpenAlexaff
Nhu‐An Pham, Joao Magalhaes, Trevor Do, Joerg Schwock, Rićhard P. Hill, David W. Hedley

Bibliographic record

VenueMolecular Cancer Therapeutics · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsAngiogenesisIn vivoMetastasisHypoxia (environmental)Cancer researchImmunofluorescencePancreatic cancerTumor hypoxiaBiologyPathologyChemistryCancerAntibodyInternal medicineImmunologyMedicineRadiation therapy
DOInot available

Abstract

fetched live from OpenAlex

B193 Tumor hypoxia is widespread in different cancer types and has been associated with poor prognosis. Current monolayer cell culture models suggest that signaling pathways including Src, STAT3 and AKT influence the transcription activity of hypoxia inducible factor-1α (HIF-1α) which affects biological processes including tumor angiogenesis, metastasis and survival. We determined the activity of these signaling proteins in hypoxic tumor regions compared to non-hypoxic regions as well as global tumor response to continuous in vivo hypoxia. Tumor hypoxia was measured based on the histological distribution of the fluorescently labeled 2-nitroimidazole agent EF5 in four murine xenograft models. In air exposed mice, the percent of hypoxic EF5-stained tumor regions ranged from a mean of 14% (BxPC-3) to 48% (PANC-1) for subcutaneously grown pancreatic xenografts, and 20% (ME180) to 27% (SiHa) for orthotopically grown cervical xenografts. A doubling of EF5-stained regions was achieved in BxPC-3 tumors with continuous exposure of mice to 7% O 2 for 3 hours compared to air control. Individual EF5-stained serial tissue sections were co-labeled with single antibodies against signaling proteins. Immunofluorescence image analysis (labeled percent area x intensity) showed a significant increase in the level of total Src protein in EF5 tumor regions compared to non-EF5 regions in all four tumor models (p≤0.05, Wilcoxon test). Additionally, the levels of total and activated Src (Y419) doubled (p=0.03) in EF5 tumor regions compared to non-EF5 regions of mice exposed to low O 2 levels, suggesting that levels of Src protein and activity are hypoxia inducible. There was a strong co-localization of activated Src and focal adhesion kinase (Y861-FAK) in EF5-stained regions of BxPC-3 tumors (r=0.74, p=0.006) in mice exposed either to air or 7% O 2 . This suggests that the cellular adhesion substrate FAK is important in Src-mediated hypoxia signaling in vivo . In contrast, BxPC-3 tumor xenografts of mice exposed to 7% O 2 showed a decrease in levels of STAT3 (S727) activity (p=0.004, Mann-Whitney test) despite no changes in total STAT3 levels in the entire tumor area. The continuous exposure to 7% O 2 did not affect levels of AKT (S473) activity. These results suggest an important role of Src in hypoxia-responsive signaling in vivo . The increased expression and enhanced activity of Src family tyrosine kinases have been associated with carcinogenesis in different tumor types. Also, Src is a common substrate of oncogenic signaling downstream of several growth factor receptors including EGFR, PDGFR and Met, and impacts on tumor cell adhesion, migration and invasion. A therapeutic strategy involving the use of Src inhibitors might be successful at targeting tumor growth as well as hypoxia-induced processes which lead to increased tumor aggressiveness.

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 score0.007

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)0.0020.000

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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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
Published2007
Admission routes1
Has abstractyes

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