Cell-based Oncology
The Reaction Oncology Platform

Cell-based Oncology

Phenotypic cellular assays allow the examination of the effects of drug treatment on cells. Reaction Biology offers a large suite of assays including 2D, 3D, or co-culture setups.

Killing basics
Is your drug cytotoxic on tumor cells?
Which tumor cell lines are sensitive to your drug?
Which tumor types are mostly affected by your drug?
Which drug combinations increase the efficacy of your drug?

Killing insight
What is your drug’s kinetics?, or: How fast does your drug kill?
Does your drug induce cell cycle arrest?
Does your drug kill both, tumor and stroma cells?

Tumor cell-specific treatment effects
Is your drug effective on cellular 3D spheroids?
Does your drug inhibit tumor cell migration, a prerequisite of metastasis?
Does your drug stop tumor cells from invading neighboring tissue?

Tumor-specific treatment effects
Does your drug inhibit new blood vessel formation?

Large cell panel screen for identification of responsive tumor cell lines


ProliFiler – Cell Panel Screen on 140 Human Tumor Cell Lines


To perform studies with an MDM2 antagonist in cellular and animal models we needed to determine which tumor cell lines and which tumor origins are affected by drug treatment.


We ran the ProliFiler cell panel screen with the drug for IC50 value determination on 140 human cell lines with the cellular proliferation assay based on CellTiter-Glo readout.

The resulting IC50 values were plotted in a graphic based on the tumor type revealing blood cancers (LE_AML… Acute Myeloid Leukemia) as the most susceptible cancer type. The best performing cell lines were MV4-11 and MOLM-13.


Boost the potency of a drug by a combination drug approach


Analysis of the combinatorial therapy with a Raf and a MEK1 inhibitor


Drug combination therapy, the use of multiple drugs for treatment of a complex disease such as cancer, offers higher efficacies; or lower adverse affects due to lower individual doses. In a large cell panel screening we aimed to identify cell lines susceptible to combinatorial treatment against Raf and MEK1. We were also interested in a common genomic signature of susceptible cell lines.


We tested the anti-proliferative effects of Raf and MEK1 in a two-sided approach with a checkerboard setup on 120 human tumor cell lines. The comparison of the dose-response curves of the two compounds via Bliss-Factor calculation revealed cell lines with mere additive effects, synergistic effects, or antagonistic effects of combination treatment.

In 8 cell lines we found mutual synergy with higher efficacies of 20 to 500-fold.

In 2 cell lines we found one-sided synergy of MEK inhibition significantly increasing the efficacy of Raf inhibition.

In 8 cell lines we found moderate synergy of about 3-fold at sub-optimal drug concentrations.

A pharmacogenomic analysis revealed that cells showing the one-sided synergy effects bear activating KRAS Q61 mutations. Cell lines with synergies at sub-optimal concentrations were mostly expressing an activating Raf V600E mutation.

Analysis of the combinatorial anti-proliferative effect of pan-RAF inhibitor AZ-628 and MEK1 inhibitor AZD-6244 (Selumetinib) on a large panel of tumor cell lines