PhD Scientific Days 2024

Poster Session J - Pathological and Oncological Sciences 1.

Modelling of a precision oncology program on a breast cancer cell line panel in vitro

Előadó neve

Dr. Makkos, András, PhD

Neptun code

olwgb8

Előadó munkahelye

Semmelweis University, Department of Pharmacology and Pharmacotherapy

Előadó telefonszáma

06703707325

Előadó e-mail címe

makkos.andras@semmelweis.hu

Az előadás címe

Modelling of a precision oncology program on a breast cancer cell line panel in vitro

Szerző(k) neve és munkahelye

András Makkos¹, Orsolya Somogyi¹, Anikó Görbe¹, Ákos Takács², Róbert Dóczi³, Péter Ferdinandy¹, István Peták³

1: Semmelweis University, Department of Pharmacology and Pharmacotherapy
2: Genomate Health Inc.
3: Genomate Health Inc., Oncompass Medicine Ltd.

Bemutatás módja

Poszter

Szekció

Poster Session J - Pathological and Oncological Sciences 1.

Language of the presentation

Hungarian

Preferred session

Pathological and Oncological Sciences

Összefoglaló szövege

Optimal cancer treatment selection can be challenging due to the complex pathogenetics of tumors. Precision oncology aims to personalize the treatment based on the molecular profile of the tumor. Digital drug assignment (DDA) systems can help to select the appropriate tumor therapy by analyzing the molecular profile of the tumor. The complexity of these systems requires preclinical testing of their performance.
Here we aim to model a precision oncology program incorporating a DDA system on breast cancer cell lines with known molecular patterns.
8 widely used breast cancer cell lines were involved in our study. The molecular profile of the cell lines was determined by gene sequencing and receptor expression measurements. Subsequently, the molecular profile was used to score and rank oncological agents by the DDA system. From a list of treatment options, 10 agents (afatinib, neratinib, olaparib, talazoparib, rucaparib, niraparib, crizotinib, palbociclib, tamoxifen, vorinostat) were selected for further in vitro testing representing various mechanisms of action and DDA score values. The inhibitory concentration 50 (IC50) was determined for all cell lines for these agents. Finally, the relationship between IC50 values and DDA score was analyzed.
The molecular profiling determined the mutation and copy number alterations of 591 genes and the expression of hormone receptors. The selected 8 cell lines were classified into three main groups: BRCA mutant (CAL-85-1, MDA-MB- 436), HER-2 overexpressing (HCC-1954, SKBR3, MDA-MB-361), and BRCA mutant and HER-2 protein overexpressing cell lines (JIMT-1, BT-474, HCC-1569). Subsequently, based on the molecular profile of the cell lines, DDA scores of the selected drugs were calculated and IC50 values were determined. Correlation of the measured IC50 values and DDA scores showed a weak correlation for all IC50-DTA score pairs altogether. However, for DDA scores with absolute values above 500, the correlation was above 0.6, whereas, for DDA scores with absolute values above 1000, the correlation was above 0.8.
In our work, we demonstrate for the first time the in vitro modeling of a DDA-based precision oncology program on a breast cancer cell line panel. The correlation between the scores calculated with DDA and the measured IC50 values underscores that the DDA system can support precision oncology decision-making.

University

Semmelweis University

Supervisor

Anikó Göbe, MD, PhD

Publication of my abstract

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

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

1293

Start

16:15

End

16:18