Protein microarrays as tool for systems biology

Systems biology aims to generate dynamic models of signal transduction pathways in order to identify key regulatory steps. Established tools for the quantification of signal transduction events are restricted in sensitivity and sample capacity. Therefore challenges of large-scale protein profiling were addressed with the development of quantitative protein microarray applications which are continuously improved to

• increase the antibody panel for protein microarray applications
• increase sensitivity and sample capacity
• improve software tools for the quantitative analysis of protein microarray data
• develop SOPs for automated time-resolved measurements
• develop SOPs for various protein microarray applications.

Protein microarrays are produced through contact-free dispensing. Currently, two robotic instruments are employed for arraying, a BioChipArrayer (Perkin Elmer) and a Sprint Inkjet Arrayer (Arrayjet). RPPA protocols and protein microarray data analysis software were developed in collaboboration with Translational Oncogenomics, and Bioinformatics and Modeling.

Collaborations: A. Tresch (Gene Center Munich), U.Klingmüller (DKFZ Heidelberg)

Breast Cancer

Drugs targeting receptors for estrogen or growth factors are well established targets in breast cancer therapies (examples: Tamoxifen/ERalpha, Herceptin/Her2). Nevertheless, treatment success is frequently limited. For this reason, this project aims to analyze the dynamics of signal transduction through ErbB2, EGFR and Met in different breast cancer cell lines after inhibition with specific anti-tumor drugs, administered either alone or in different combinations. Quantitative protein microarrays will be employed to analyze the activation of downstream signalling pathways (Erk, Akt, Stat), and of key players in the control of apoptosis, proliferation, and migration. The data will feed into quantitative data-driven modelling of network dynamics to identify new points for clinical intervention. This project is performed in collaboration with Integrative Cell Biology, Receptor Tyrosine Kinase Signaling, and Bioinformatics and Modeling.

Collaborations: A. Schneeweiss (University Clinic Heidelberg), J. Timmer (University Freiburg)