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Record W2915165741 · doi:10.1080/15548627.2019.1582951

A novel orally available seleno-purine molecule suppresses triple-negative breast cancer cell proliferation and progression to metastasis by inducing cytostatic autophagy

2019· article· en· W2915165741 on OpenAlexafffund
Chia-Hao Chang, Krikor Bijian, Dominik Wernic, Jie Su, Sabrina Daniela da Silva, Henry Yu, Dinghong Qiu, Mariana Asslan, Moulay A. Alaoui‐Jamali

Bibliographic record

VenueAutophagy · 2019
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsMcGill UniversityJewish General Hospital
FundersFondation du cancer du sein du Québec
KeywordsBiologyAutophagyTriple-negative breast cancerCancer researchBreast cancerMetastasisCancerCell growthPurineCell biologyApoptosisBiochemistryGeneticsEnzyme

Abstract

fetched live from OpenAlex

Patients with triple-negative breast cancer (TNBC) often have a poor prognosis largely due to lack of effective targeted therapy. Using a library of seleno-purines coupled to a high-throughput biochemical enzymatic assays we identified a potent pharmacological enhancer of autophagy (referred herein as SLLN-15) that selectively activated cytostatic macroautophagy/autophagy in TNBC preclinical models. SLLN-15 induced a dose-dependent anti-proliferative activity in the TNBC cell lines MDA-MB-231 and BT-20 via induction of autophagy and autophagic flux. This induction was associated with a selective inhibition of AKT-MTOR signaling. Conversely, rapamycin, a known autophagy inducer and MTOR inhibitor, was unable to duplicate SLLN-15’s effect on TNBC cells. Inhibition of autophagy by siRNA-mediated targeting of the autophagy regulators, BECN1, ATG5 and ATG7 or using 3-methyladenine (3-MA), significantly protected against SLLN-15-induced inhibition of cell viability, further supporting that SLLN-15-induced inhibition of cancer cell proliferation was autophagy-dependent. SLLN-15-induced autophagy in TNBC cells was also associated with decreased AURKA expression, decreased AKT phosphorylation and subsequent blockage of the AKT-MTOR pathway. In vivo, oral SLLN-15 revealed a potent anticancer and anti-metastatic activity in mice bearing TNBC. Altogether, this study describes a novel regulator of mammalian autophagy, with potential utility as an experimental therapeutic for TNBCs.Abbreviations 3-MA: 3-methyladenine; ATG5: autophagy related 5; ATG7: autophagy related 7; AURKA: aurora kinase A; AURKB: aurora kinase B; BECN1: beclin 1; CQ: chloroquine; DMSO: dimethyl sulfoxide; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GFP: green fluorescent protein; ERBB2: erb-b2 receptor tyrosine kinase 2; MAP1LC3B/LC3B: microtubule-associated protein 1 light chain 3 beta; MTOR: mechanistic target of rapamycin kinase; PARP1: poly(ADP-ribose) polymerase 1; PI: propidium iodide; SQSTM1/p62: sequestosome 1; TNBC: triple-negative breast cancer

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.014
GPT teacher head0.273
Teacher spread0.259 · 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

Citations57
Published2019
Admission routes2
Has abstractyes

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