Finding the Ideal Seeding Ratio for a Tumor Model

Presenter

Narine Lucia Berberian

Campus

UMass Amherst

Sponsor

Shelly Peyton, Department of Chemical Engineering, UMass Amherst

Schedule

Session 4, 2:30 PM - 3:15 PM [Schedule by Time][Poster Grid for Time/Location]

Location

Poster Board A57, Campus Center Auditorium, Row 3 (A41-A60) [Poster Location Map]

Abstract

Lung cancer is a complicated disease to model. This is due to the abnormal growth rates of lung cancer cells and the drug resistance that can develop over courses of failed treatment. The goal of this project is to find the ideal seeding ratio to produce the most realistic model of lung cancer using spheroids to mimic the cell-cell interactions in a tumor. In order to produce a realistic model, it is important to reproduce the heterogeneous cellular environment that is naturally found in a tumor. I am working under a graduate mentor, Ninette Irakoze, developing a project that branches off of her current research. Ninette’s project focuses on understanding how the extracellular matrix influences drug resistance in lung cancer using a “dual-switch” gene drive therapy. She uses spheroids made of three cell populations in an experiment: an engineered gene drive cell population that constitutes the therapy, a drug-sensitive and a drug (Osimertinib)-resistant cell population. I am trying to determine the best ratio of gene drive cells to drug-resistant cells that can be used when seeding cells to form spheroids using Aggrewell plates and encapsulate them in a 3D collagen gel. I am testing this by using a smaller spheroid size (100-150 cells per spheroid) and running the experiment for a shorter time (7-9 days). With this model, I have found that a low ratio of drug-resistant cells to gene drive cells (about 0.5% to 99.5%) produces the best model with the fewest amount of dead cells. 

Keywords

lung cancer , collagen gel, Aggrewell, cell culture , drug resistance

Research Area

Cancer Studies

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