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Record W2035908075 · doi:10.1158/1538-7445.am2012-4652

Abstract 4652: The autophagy-senescence connection in chemotherapy of breast tumor cells; senescence accelerated by autophagy but not dependent on autophagy

2012· article· en· W2035908075 on OpenAlexaff
Rachel W. Goehe, Xu Di, Khushboo Sharma, Molly L. Bristol, Scott C. Henderson, Françis Rodier, Albert R. Davalos, David A. Gewirtz

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAutophagySenescenceATG5Cell biologyBiologyFlow cytometryProgrammed cell deathApoptosisChemistryCancer researchMolecular biologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Introduction: Previous studies from our laboratory have established the capacity of Adriamycin to promote accelerated senescence in MCF-7 cells, while a number of studies have indicated that Adriamycin promotes autophagy. Although senescence and autophagy are considered to be two distinct cellular events in response to genotoxic stress, recent reports have suggested that the two are functionally intertwined. Thus, the current work was designed to determine whether autophagy and senescence were related in response to treatment with Adriamycin (ADR) and Campthothecin (CPT) in MCF-7 cells in vitro. Experimental Procedure: Autophagy induction was measured by acridine orange staining/quantification by flow cytometry and RFP-LC3; autophagic flux was based on p62 western immunoblotting. Autophagy was inhibited pharmacologically using 5µM Chloroquine or 5mM 3-MA and genetically using shRNA against ATG5 and ATG7. Senescence was measured by β-galactosidase staining and C12FDG fluorescence by flow cytometry. To block senescence, shRNA against p21 and 53 were used. The senescence associated markers p21, pRb, and p53 were measured by western immunoblotting. To evaluate common signaling events, 20µM KU55933 or 2mM caffeine were used to downregulate ATM and 20µM N-acetyl cysteine or 20µM Glutathione were used for scavenging ROS. Results: Both ADR and CPT collaterally induced autophagy and senescence in a time-dependent manner. Downregulation of ATM by pharmacological inhibition or genetic ablation collaterally blocked both ADR-induced autophagy and senescence. Suppression of ROS generation collaterally interfered with ADR-induced senescence and autophagy. Moreover, shRNA against either p53 or p21 resulted in a marked reduction in ADR-induced autophagy. In contrast, autophagy blockade with chloroquine, 3-MA, or shRNA against ATG5 and ATG7 only delayed senescence. Finally, tissue and protein analysis from a 4T1 breast tumor model showed that both autophagy and senescence co-exist in vivo in response to ADR. Conclusions: Treatment of MCF-7 cells with either ADR or CPT induced both autophagy and senescence. Interference with ROS generation, ATM activation and induction of p53 or p21 suppressed both autophagy and senescence. However, these observations may indicate only that both responses are mediated by common DNA-damage induced signaling pathways. When autophagy was blocked either pharmacologically or genetically, senescence was temporally delayed, but the overall extent of senescence induced by ADR or CPT was not attenuated. Consequently, although autophagy appears to accelerate and facilitate the senescence process, it is clear that senescence can occur independently of autophagy. Overall, this study provides new insights into the role of autophagy in the senescence process and the signaling events that appear to contribute to both responses. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4652. doi:1538-7445.AM2012-4652

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.013
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.341
Teacher spread0.307 · 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 teacher head, 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

Citations14
Published2012
Admission routes1
Has abstractyes

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