Martin Sos - A 11

Genomic and molecular characterization of the evolutionary process of drug resistance in EGFR-mutant lung cancer

Despite major improvements in targeted therapies in the last years, lung cancer still remains one of the deadliest cancers worldwide. Targeted drugs that inhibit mutant EGFR in lung adenocarcinoma has dramatically prolonged the overall survival of these patients. However, the development of resistance remains inevitable. In this project, we aim for understanding the molecular drivers that shape the evolutionary process of resistance in EGFR-mutant lung tumors. 


Lung cancer is the leading cause of cancer death in men and women in developed countries. Over the last decade novel techniques like next-generation sequencing and high-throughput analyses have enabled us and other groups to systematically classify lung tumors on a genomic level and to develop novel, targeted therapies for genetically defined subgroups of lung cancer patients. 

The central dogma in precision cancer medicine is that an oncogene-addicted tumor can be effectively treated with a targeted drug. For example, EGFR inhibition by targeted inhibitors significantly improves survival in patients with activating EGFR mutations. However, the targeted treatment of EGFR-mutant tumors inevitably leads to the selection of resistant clones and the recurrence of disease. This is not too surprising considering the genomic complexity of cancer and the dynamic evolution of unique cell clones that contribute to the heterogeneity of individual tumors.

In our project, we aim to characterize the genomic and molecular dynamics of clonal evolution in EGFR-driven lung tumors and their implication for therapeutic responses to targeted drugs. For this purpose, we combine systematic in vitro modelling of tumor resistance development and the analysis of patient cohorts with several complementary genomic and transcriptomic approaches to evaluate tumor heterogeneity and clonal evolution. This approach provides important insights into the molecular processes that drive resistance to targeted inhibition of EGFR signalling and may help to further improve the treatment options for patients with EGFR-activated lung cancer.

Aim 1: Systematic characterization of the genomic and transcriptomic architecture of EGFR-mutant tumors

During our work with patient samples from a study investigating the effectiveness of third-generation EGFR inhibitors, we have shown the potential to elucidate the diversity of occurring resistance patterns (Ortiz-Cuaran et al., 2016).

Within this project part, we systematically extend this approach to samples obtained before and after treatment with different EGFR inhibitors. One of the currently investigated routes is the characterization of a novel resistance mutation within EGFR that arises as a subclone in EGFR TKI treated patients. This novel mechanism shifts the sensitivity from the class of third-generation EGFR inhibitors to second-generation EGFR inhibitors (Fassunke J*, Müller F*. et al. under revision).

Furthermore, we expect that our genomic and transcriptomic analyses combined with bioinformatics analyses will allow us to determine tumor heterogeneity and architecture as well as re-wiring of transcriptional networks and signalling pathways.

Aim 2: Functionally linking the subclonal evolution of EGFR-driven lung tumors with their vulnerability to targeted drugs

We and others have shown that the spectrum of resistance mechanisms after treatment with third-generation inhibitors significantly differs from that of first-generation inhibitors. Furthermore, it is known that cell lines driven by the same genetic aberration in EGFR and challenged by the same inhibitor can give rise to distinct resistance mechanisms. 

In this project part, we use cellular models as well as patient-derived cell lines to assess the impact of the subclonal architecture (analyzed in Aim 1) on response to targeted drugs in EGFR-mutant lung cancer. Furthermore, we explore a genomic framework to predict the clonal evolution of druggable resistance mechanisms that may arise in these tumors. Performing these experiments will allow a thorough estimation of the diversity and the relative frequency of resistance mechanisms occurring in different genetic backgrounds. By this means, we aim to identify markers for prediction of a most likely resistance mechanism before start of the treatment of patients.


Our project will strongly foster the basic understanding of tumor evolution, but will also offer insights that may rapidly be translated into clinical applications, such as improved therapies for patients with EGFR-mutant lung cancer.

Selected publications

Ortiz-Cuaran S, Scheffler M, Plenker D, Dahmen L, Scheel AH, Fernandez-Cuesta  L, Meder L, Lovly CM, Persigehl T, Merkelbach-Bruse S, Bos M, Michels S, Fischer  R, Albus K, König K, Schildhaus HU, Fassunke J, Ihle MA, Pasternack H, Heydt C, Becker C, Altmüller J, Ji H, Müller C, Florin A, Heuckmann JM, Nuernberg P, Ansén S, Heukamp LC, Berg J, Pao W, Peifer M, Buettner R, Wolf J, Thomas RK, Sos ML (2016). Heterogeneous Mechanisms of Primary and Acquired Resistance to Third Generation EGFR Inhibitors. Clin Cancer Res. 22(19), 4837-4847.

Prof. Dr. Martin Sos

Institute for Pathology / Dept. of Translational Genomics

Prof. Dr. Martin Sos

Principal Investigator A 11

Work +49 221 478 96175

Institute for Pathology
Weyertal 115b
50931 Cologne

Publications - Martin Sos

Link to PubMed

Group Members

Katia Garbert (Project Coordination)
Johannes Brägelmann (Postdoc)
Niloufar Monhasery (Postdoc)
Armin Khonsari (Postdoc)
Stefanie Lennartz (technician)
Marcel Dammert (PhD student)
Alena Heimsoeth (PhD student)
Hannah Tumbrink (PhD student)
Carina Lorenz (MD student)
David Ast (MD student)
Thorben Scholz (BSc student)
Fatma Parmaksiz (student assistant)

Figure 1

CMMC Research Sos