Driver mutations in major lung cancer oncogenes can be analyzed in Drosophila models

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Judith Bossen
Karin Uliczka
Line Steen
Pia Neugebauer
Mandy Mong-Quyen Mai
Christine Fink
Frank Stracke
Holger Heine
Thomas Roeder

Abstract

Lung cancer remains the leading cause of cancer-associated mortality. Despite recent promising achievements, the overall prognosis remains very poor. In order to integrate the advantages of adapted, transgenic animal models with a high-throughput procedure on the one hand and compliance with the 3R principles on the other hand, we have established and evaluated appropriate Drosophila models. To achieve this goal, we ectopically expressed oncogenes representing the most important driver mutations exclusively in the airway system. These oncogenes were either the human oncogenes or the corresponding Drosophila orthologs. We concentrated on two complementary read-out systems, 1) early larval lethality and 2) quantification of concurrently expressed GFP as a proxy for tumor mass. We could show that ectopic expression of EgfrCA, RasV12, Raf, Rolled (MAPK), PI3K92E, Alk, Akt and Arm can induce early lethality. Thus, they can be used in a straight-forward high-throughput screening approach and can replace mouse models to a considerable extent. Moreover, we could also show that measurement of tumor mass by a concurrently expressed marker (GFP) can be used to detect positive treatment results. Our results show that our Drosophila system provides a superb in vivo inver­tebrate screening system amenable to high-throughput approaches and thus effectively complements the toolbox for the development of novel anti-lung cancer treatments, while complying with the 3R principles.

Article Details

How to Cite
Bossen, J., Uliczka, K., Steen, L., Neugebauer, P., Mai, M. M.-Q., Fink, C., Stracke, F., Heine, H. and Roeder, T. (2021) “Driver mutations in major lung cancer oncogenes can be analyzed in Drosophila models”, ALTEX - Alternatives to animal experimentation, 38(2), pp. 235-244. doi: 10.14573/altex.1912131.
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