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Record W2485051841 · doi:10.1158/1538-7445.am2016-3251

Abstract 3251: A Senescence-like phenotype associates with rapid metastasis promotion following antiangiogenic drug resistance and therapy withdrawal

2016· article· en· W2485051841 on OpenAlexaff
Michalis Mastri, Amanda Tracz, Biao Liu, Christina R. Lee, John M.L. Ebos

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAxitinibCancer researchMetastasisStromal cellMelanomaSunitinibIn vivoCancerDrug resistanceAngiogenesisPrimary tumorInternal medicineBiology

Abstract

fetched live from OpenAlex

Abstract Few studies have investigated mechanisms of antiangiogenic drug resistance in mouse models that faithfully recapitulate clinically relevant spontaneous metastatic disease or evaluate the impact of therapy cessation on tumor and stromal cell growth. Generation of such models may be critical to study reported instances of antiangiogenic therapy-induced metastasis in animals that have often proved challenging to confirm in patients. Here we describe the derivation of several human and mouse tumor cell lines obtained from spontaneous metastatic lesions present after surgical removal of primary tumors and following long-term in vivo treatment with sunitinib or axitinib. Selected drug-resistant metastatic (kidney, breast, and melanoma) and non-malignant stromal cell variants (endothelial and fibroblast) were continuously exposed to drug in vitro and then evaluated following both short- and long-term treatment removal (48 hours and 6 months, respectively). Our results show that metastatic drug-resistant cells receiving sustained treatment were re-sensitized to therapy upon orthotopic re-implantation into treatment-naïve animals, suggesting a predominant host-mediated role in therapy failure. However, significant increases in tumor growth and metastatic potential were observed in all models when cells were re-implanted and therapy stopped, suggesting a tumor-dependent pro-metastatic mechanism activated by therapy withdrawal. Whole genome expression analysis for resistant cells on and off treatment revealed reversible and irreversible gene changes implicating a senescence-like phenotype capable of influencing metastatic potential. Senescent-like characteristics included increased cell size, decreased proliferation, cell cycle check-point protein alteration, and therapy-induced SA-β-galactosidase expression, depending on the cell line. Critically, antiangiogenic therapy could induce a senescence associated secretory phenotype (SASP) in both tumor and stroma cells which reversed or persisted following therapy cessation in certain instances. Importantly, we found that interleukin-6 (IL-6) - a major component of the SASP - was upregulated in resistant tumor and stroma cells, but only remained upregulated in stromal cells following therapy withdrawal. These results suggest that antiangiogenic treatment-induced senescence-like changes may contribute to treatment failure and contribute to pro-metastatic growth depending on cell origin (i.e., tumor or stroma) and whether treatment is sustained or stopped. Citation Format: Michalis Mastri, Amanda Tracz, Biao Liu, Christina R. Lee, John ML Ebos. A Senescence-like phenotype associates with rapid metastasis promotion following antiangiogenic drug resistance and therapy withdrawal. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3251.

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 score0.009

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 integrity0.0000.001
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 head0.034
GPT teacher head0.342
Teacher spread0.308 · 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
Published2016
Admission routes1
Has abstractyes

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