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Record W4362541058 · doi:10.1158/1538-7445.am2023-50

Abstract 50: Tumorigenic properties of uveal melanoma cancer cells cultured in 3D or on a reconstructed extracellular matrix

2023· article· en· W4362541058 on OpenAlexaff
Olivier Chancy, Léo Piquet, Kelly Coutant, Andrew Mitchell, Solange Landreville

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsExtracellular matrixStromal cellFibronectinPathologyMatrigelMetastasisCancer researchHepatic stellate cellMelanomaTumor microenvironmentCell biologyBiologyChemistryAngiogenesisCancerMedicineTumor cells

Abstract

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Abstract Background: Uveal melanoma (UM) is the most common intraocular tumor in adults. It arises from the transformation of melanocytes, and despite the effective treatment of the ocular tumor, hepatic metastases lead to a poor prognosis. Our hypothesis is that the invasive potential and therapeutic resistance of UM cells (UMCs) depend on interactions with stromal cells and properties of the extracellular matrix (ECM). Our study aims to determine the impact of UMCs in stromal cell activation, and to define the role of the ECM produced by choroidal fibroblasts or hepatic stellate cells (HSteCs) on UM cell proliferation and invasion. Methods: Two types of tumor spheroids were generated i) one corresponding to primary melanoma (UMCs from eye tumor + choroidal fibroblasts and endothelial cells) and ii) the other to liver metastasis (UMCs from liver metastasis + HSteCs and sinusoidal endothelial cells). The organization of these mixed spheroids were studied by confocal microscopy using the following markers: Melan-A (UM cells), alpha-smooth muscle actin (aSMA; activated fibroblasts and stellate cells), CD31 (endothelial cells) and Ki67 (proliferation). The viability and invasion capacity of the mixed spheroids were analyzed using an ATP consumption assay, and the measurement of the invasion area in Matrigel. Next, two types of matrices were produced by tissue engineering using the self-assembly approach with choroidal fibroblasts or HSteCs. These matrices were devitalized and characterized by confocal microscopy (collagens, fibronectin), before seeding UMCs to study their morphology, proliferation and ECM remodeling. Results: A higher concentration of alpha-SMA and proliferative cells were observed in the outer layers of the spheroids by immunofluorescence analyses. Choroidal and hepatic matrices were produced in 21 days. These tissue-engineered matrices contained fibronectin and collagen I. These devitalized matrices were seeded with UMCs in monolayer to study their change of morphology, proliferative state and ECM remodeling. Conclusions: We characterized the viability and cellular organization in both choroidal and hepatic spheroid models, and successfully generated tissue-engineered choroidal and hepatic matrices. With the optimization of these 3D models, we will better understand the steps involved in the progression of ocular melanoma to a metastatic stage. These complex models may replace the 2D model using tumor cells in monolayer for future drug screening, which will consider the impact of the microenvironment on UM therapeutic resistance. Citation Format: Olivier Chancy, Léo Piquet, Kelly Coutant, Andrew Mitchell, Solange Landreville. Tumorigenic properties of uveal melanoma cancer cells cultured in 3D or on a reconstructed extracellular matrix [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 50.

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 score0.003
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 head0.122
GPT teacher head0.425
Teacher spread0.303 · 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
Published2023
Admission routes1
Has abstractyes

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