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Record W3083171017 · doi:10.1158/1538-7445.am2020-685

Abstract 685: Sortilin receptor-mediated novel cancer therapy: A targeted approach to inhibit vasculogenic mimicry in ovarian and breast cancers

2020· article· en· W3083171017 on OpenAlexaff
Jean-Christophe Currie, Michel Demeule, Alain Zgheib, Richard Béliveau, Christian Marsolais, Borhane Annabi

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversité du Québec à MontréalTheratechnologies (Canada)
Fundersnot available
KeywordsVasculogenic mimicryOvarian cancerCancer researchDoxorubicinMatrigelTriple-negative breast cancerCancerBreast cancerDocetaxelCancer cellCancer stem cellMedicineBiologyChemistryInternal medicineMetastasisChemotherapyAngiogenesis

Abstract

fetched live from OpenAlex

Abstract Rational: Vasculogenic mimicry (VM) is defined as the formation of microvascular channels by aggressive, metastatic and genetically deregulated tumor cells. This microcirculation system, independent of endothelial cells, provides oxygen and nutrients to tumor cells. Such system contributes, in part, to current chemoresistance and facilitates tumor progression as well as dissemination of cancer metastases. VM is a process associated with aggressive ovarian cancer and triple-negative breast cancer (TNBC) and is shown to correlate with decreased overall cancer patient survival. Procedures: Targeting VM in ovarian and TNBC tumors, in addition to targeting tumor cells, may thus help circumvent chemoresistance and contribute to more efficient cancer treatments. Sortilin receptor (SORT1) is essential for VM in ovarian and TNBC tumors and high expression of SORT1 in many types of cancers has been associated with their invasion and progression. Results: SORT1 was detected in 3D-tubular structures of ES-2 ovarian cancer and MDA-MB-231 TNBC cells when grown on Matrigel. Peptide-drug conjugates targeting SORT1 significantly decreased the formation of new 3D-structures by 50% (IC50) at low nM concentrations (5-10 nM). In fact, the Doxorubicin-peptide conjugate (TH1904) abolished the formation of 3D-tubular structures of ovarian cancer cells in an in vitro model, whereas unconjugated Doxorubicin or liposomal Doxorubicin (up to 20 µM) had no effect on the formation of the VM structure. Moreover, a Docetaxel-peptide conjugate (TH1902) also showed very potent in vitro activity against the formation of VM in TNBC. IC50 values for VM 3D-tubular structures inhibition was about 30 pM for TH1902 compared to 0.5 nM for Docetaxel. Conclusion: Our results provide insight into future potent ovarian and TNBC therapeutic treatments. Targeting this receptor's functions with peptide-drug conjugates may provide an efficient strategy to increase the binding/internalization of cancer drugs within tumor cells, thereby improving the efficacy of standard anticancer treatments. Our results indicate that peptide-drug conjugates targeting SORT1 strongly inhibit the formation of VM, a phenomenon associated with a more aggressive tumor phenotype and poor prognosis in patients with TNBC or ovarian cancer. Citation Format: Jean-Christophe Currie, Michel Demeule, Alain Larocque, Alain Zgheib, Richard Béliveau, Christian Marsolais, Borhane Annabi. Sortilin receptor-mediated novel cancer therapy: A targeted approach to inhibit vasculogenic mimicry in ovarian and breast cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 685.

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 score0.006

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 head0.052
GPT teacher head0.328
Teacher spread0.276 · 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
Published2020
Admission routes1
Has abstractyes

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