PhD Scientific Days 2026

Poster Session 1.D - Pathological and Oncological Sciences

Metabolic differences across 2D and 3D breast cancer models

Előadó neve

Dr. Moldvai, Dorottya, PhD

Neptune code

JQCZNN

Előadó munkahelye

Semmelweis University, Department of Pathology and Experimental Cancer Research

Előadó telefonszáma

06203291961

Előadó e-mail címe

moldvai.dorottya@gmail.com

Az előadás címe

Metabolic differences across 2D and 3D breast cancer models

Szerző(k) neve és munkahelye

Dorottya Moldvai¹, Péter Sasvári², Fanni Bugyi³, Ildikó Krencz¹, Risa Miyaura¹, Viktória Varga¹, Fatime Szalai¹, Zsófia Gábriel¹, Gábor Barna¹, Anna Sebestyén¹

1: Semmelweis University, Department of Pathology and Experimental Cancer Research
2: Semmelweis University, Department of Physiology
3: HUN-REN Research Centre, MS Proteomics Research Group

Bemutatás módja

Poszter

Szekció

Poster Session 1.D - Pathological and Oncological Sciences

Language of the presentation

Hungarian

Preferred session

Pathological and Oncological Sciences

Összefoglaló szövege

Introduction
Modernization efforts by the European Medicines Agency (EMA) and the U.S. Food and Drug Administration (FDA) aim to reduce animal experimentation in drug development by 2030. This shift increases the demand for alternative preclinical systems. However, current models remain limited: animal models often fail to replicate human biology, while 2D cultures lack tissue complexity.

Aims
This study aims to compare different experimental breast cancer models and evaluate how dimensionality and microenvironment influence cellular behavior, metabolism, and drug sensitivity.

Methods
ZR75.1 breast cancer cell line was used to establish 2D monolayers, 3D spheroids, and 3D bioprinted tissue-mimetic structures (TMSs), alongside xenograft tumors in SCID mice. Proteomic profiling was performed by LC-MS, followed by clustering and enrichment analyses. Protein expression, cell-cycle distribution, and responses to ACAT1 inhibitor (ATR-101; in vitro: 10 uM; in vivo: 3 mg/kg/day, 3x/week) and chemotherapy (doxorubicin; in vitro: 50 ng/ml; in vivo: 2 mg/kg/day, 1x/week) were also assessed among different model systems.

Results
Distinct proteomic profiles were identified across all models, emerging that dimensionality changes the metabolism of different model systems. The 3D bioprinted TMSs showed cell-cycle patterns similar to xenografts, including G₁ phase accumulation. Compared to 2D cultures, these systems displayed reduced sensitivity to ATR-101 and combination (ATR-101+doxorubicin) therapy, while long-term treatments eradicate these effects, similarly as in case of xenograft tumors.

Conclusion
Model dimensionality and extracellular context significantly affect tumor cell behavior and drug response. These findings underline the demand of the development of more physiologically relevant preclinical models.

Fundings: EKÖP-2025-00014, NKFIH-142799

email: moldvai.dorottya@gmail.com
University: Semmelweis University
Supervisor: Anna Sebestyén

University

Semmelweis University

Supervisor

Anna Sebestyén

Publication of my abstract

I do not give consent to the publication of my abstract on the website of the congress.

phd.section.field

after finishing doctoral studies with absolutorium (PhD)

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

6117

Start

16:36

End

16:39