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Record W2594292461 · doi:10.1158/1538-7445.epso16-a18

Abstract A18: A novel 3D co-culture system for the study of adipocyte and extracellular matrix influences on the breast cancer phenotype

2017· article· en· W2594292461 on OpenAlexaff
Nikitha K. Pallegar, Mathepan Mahendralingam, Alicia Viloria‐Petit, Sherri L. Christian

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of GuelphMemorial University of Newfoundland
Fundersnot available
KeywordsBreast cancerCancerExtracellular matrixAdipocyteTumor microenvironmentCancer researchAdipose tissueStromal cellMammary tumorTumor progressionCancer cellBiologyPathologyMedicineInternal medicineCell biology

Abstract

fetched live from OpenAlex

Abstract Breast cancer (BC) is the most common cancer among women worldwide. Among the different subtypes of breast cancer, triple negative breast cancer (TNBC) is the most aggressive disease. The breast tumor microenvironment, which is mainly composed of extracellular matrix (ECM) and stromal cells such as endothelial cells, immune cells and adipocytes, plays a crucial role in cancer progression. The ECM is considered a major regulator of epithelial architecture and function in mammary gland. ECM stiffness correlates with a more malignant breast cancer phenotype. BC progression is also influenced by other conditions of the patient such as obesity. Obesity increases the number of myofibroblasts in mammary adipose tissue which deposits a stiffer ECM and increases the malignant characteristics of mammary epithelial cells. Obese patients with TNBC have a reduced tendency to respond to therapy leading to poor outcome. The density of the mammary gland in terms of adipocyte to ECM ratio also contributes to breast cancer progression. However, the combined contribution of adipocytes and ECM to the phenotype of transformed mammary epithelium and to cancer progression is rather unexplored. The culture models used so far are limited in their relevance to the in vivo interactions among adipocytes, the ECM and breast cancer cells, and the influence of each of these compartments on each other. Whereas, cells in 3-dimensional (3D) culture models exhibit features that are closer to complex in vivo conditions. In this study, we used a 3D co-culture system comprising adipocyte, ECM and BC cells to understand the function of adipocytes in BC aggressiveness. We determined the effect of mature adipocytes and ECM on epithelial-mesenchymal transition markers in breast cancer cells using immunofluorescence and confocal microscopy. In parallel, we determined the effect of the breast cancer cells on lipid morphology and accumulation in mature adipocytes via Bodipy staining of the lipid droplets and morphology analysis under confocal microscope. We found that ECM and the presence of mature adipocytes modified the phenotype of the BC cells. We also found that the BC cells as well as the ECM modified lipid accumulation in adipocytes. These data show that complex physiological interaction between ECM, adipocytes and BC cells affects the breast cancer phenotype. Thus, the co-culture model described here might serve as a valuable tool to address key questions of TNBC biology, including how the microenvironment in obese patients contributes to TNBC progression, and this may lead to improved therapies for this BC subtype. Citation Format: Nikitha Kendyala Pallegar, Mathepan Mahendralingam, Alicia Viloria-Petit, Sherri Christian. A novel 3D co-culture system for the study of adipocyte and extracellular matrix influences on the breast cancer phenotype. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A18.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.124
GPT teacher head0.448
Teacher spread0.324 · 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
Published2017
Admission routes1
Has abstractyes

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