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Abstract 3801A: Reoxygenation and repopulation of hypoxic cells in a solid tumor after chemotherapy: a cause of treatment failure.

2013· article· en· W2315115823 on OpenAlexaffabout
Jasdeep K. Saggar, Ian F. Tannock

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsHypoxia (environmental)ChemotherapyBone marrowMedicineDoxorubicinCancer researchRadiation therapyPathologyBiologyInternal medicineChemistryOxygen

Abstract

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Abstract Background: Hypoxia occurs in solid tumors: chronic diffusion-limited hypoxia occurs distal from functional blood vessels, while acute hypoxia may occur because of interruptions in blood flow. Well-nourished tumor cells close to blood vessels tend to be rapidly proliferating but hypoxic cells located farther away are slowly-proliferating. Chemotherapy may spare hypoxic cells because of poor drug distribution to them and because most drugs are selectively toxic to proliferating cells. Intervals between administration of chemotherapy allow for recovery of normal tissues (e.g. repopulation of bone marrow) but might allow re-oxygenation and resumed proliferation of formerly hypoxic cells due to better supply of nutrients to them, as is observed during radiotherapy. Here we evaluate these processes in human tumor xenografts Methods: Two specific markers of hypoxic cells (pimonidazole [pimo] and EF5) were injected into mice bearing MCF7 tumor xenografts, and tumor cells labeled with one or both markers were recognized in tumor sections (in relation to DioC7+ve functional tumor blood vessels) using appropriate fluorescence-labeled antibodies and imunohistochemistry. Proliferating cells were identified by an antibody to Ki67. Mice were treated with pimo and then either doxorubicin or saline one hour later; EF5 was given after a variable interval of 24, 48, 72, 96 or 120 hours; mice were killed two hours after the second injection. Changes in the location, proliferation and oxygen status of formerly hypoxic (pimo+ve) cells were quantified by their distance from hypoxia, Ki67 status and uptake of EF5 as a function of time. Results: Following treatment with doxorubicin, the proportion of hypoxic cells in the entire tumor decreased from 1.5% (pimo+ve) prior to injection to 0.7% (EF5+ve) at 24 hours. The percentage of pimo+ve formerly hypoxic cells that are no longer hypoxic (i.e. EF5 - ve) at 24 hours was 90% after docxorubicin compared to 27% in controls, indicating rescue of previous hypoxic cells that would have died in the absence of treatment. Proliferation of these pimo+ve cells that were cycling (Ki67+ve) increased from 7% to 15.0% at 24 Hours and then slowly decreased. Conclusions: Formerly hypoxic cells in MCF7 xenografts undergo re-oxygenation and increase their proliferation following treatment with doxorubicin. Originally hypoxic cells (that may have died in the absence of treatment) can move closer to blood vessels, re-oxygenate and repopulate a tumor. Treatment directed to killing hypoxic cells (e.g. with hypoxia activated pro-drugs) has potential to improve the outcome of chemotherapy. Supported by a research grant from the Canadian Institutes for Health Research. Citation Format: Jasdeep K. Saggar, Ian F. Tannock. Reoxygenation and repopulation of hypoxic cells in a solid tumor after chemotherapy: a cause of treatment failure. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3801A. doi:10.1158/1538-7445.AM2013-3801A

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 score0.003
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 integrity0.0010.000
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 head0.029
GPT teacher head0.342
Teacher spread0.314 · 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
Published2013
Admission routes2
Has abstractyes

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