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Novel Methods for Analysis of Heterogeneous Protein-Cell Interactions: Resolving How the Epidermal Growth Factor Binds to Its Receptor
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Biomedical Radiation Sciences.
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cells are complex biological units with advanced signalling systems, a dynamic capacity to adapt to its environment, and the ability to divide and grow. In fact, they are of such high level of complexity that it has deemed extremely difficult or even impossible to completely understand cells as complete units. The search for comprehending the cell has instead been divided into small, relatively isolated research fields, in which simplified models are used to explain cell biology. The result produced through these reductionistic investigations is integral for our current description of biology. However, there comes a time when it is possible to go beyond such simplifications and investigate cell biology at a higher level of complexity. That time is now.

This thesis describes the development of mathematical tools to investigate intricate biological systems, with focus on heterogeneous protein interactions. By the use of simulations, real-time measurements and kinetic fits, standard assays for specificity measurements and receptor quantification were scrutinized in order to find optimal experimental settings and reduce labour time as well as reagent cost. A novel analysis platform, called Interaction Map, was characterized and applied on several types of interactions. Interaction Map decomposes a time-resolved binding curve and presents information on the kinetics and magnitude of each interaction that contributed to the curve. This provides a greater understanding of parallel interactions involved in the same biological system, such as a cell. The heterogeneity of the epidermal growth factor receptor (EGFR) system was investigated with Interaction Map applied on data from the instrument LigandTracer, together with complementing manual assays. By further introducing disturbances to the system, such as tyrosine kinase inhibitors and variation in temperature, information was obtained about dimerization, internalization and degradation rates.

In the long term, analysis of binding kinetics and combinations of parallel interactions can improve the understanding of complex biomolecular mechanisms in cells and may explain some of the differences observed between cell lines, medical treatments and groups of patients.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2013. , 65 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 854
Keyword [en]
Heterogeneity, Kinetics, EGFR, HER2, LigandTracer, Interaction Map, Internalization, Specificity
National Category
Medical Biotechnology Cell and Molecular Biology
Research subject
Medical Science
Identifiers
URN: urn:nbn:se:uu:diva-183872ISBN: 978-91-554-8570-2 (print)OAI: oai:DiVA.org:uu-183872DiVA: diva2:574810
Public defence
2013-02-15, Rudbeck Hall, Rudbeck Laboratory, Dag Hammarskjöldsväg 20, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2013-01-24 Created: 2012-11-05 Last updated: 2013-02-11Bibliographically approved
List of papers
1. Avoiding false negative results in specificity analysis of protein-protein interactions
Open this publication in new window or tab >>Avoiding false negative results in specificity analysis of protein-protein interactions
2011 (English)In: Journal of Molecular Recognition, ISSN 0952-3499, E-ISSN 1099-1352, Vol. 24, no 1, 81-89 p.Article in journal (Refereed) Published
Abstract [en]

The competition measurement using simultaneous incubation of labeled and unlabeled Ligand is a common method to assess the specificity of a biomolecular interaction. In this paper we show that invalid assumptions about the interactions may lead to improper experimental setups which in turn can result in inaccurate conclusions about the specificity. To improve understanding of competition measurements, simulations in MATLAB as well as real-time interaction analysis using LigandTracer have been performed. We show that use of a concentration of unlabeled Ligand of at least 10 × K(D) is necessary for assay accuracy. Increasing the incubation time to assure equilibrium, adding a pre-incubation phase, and a general understanding of the reversibility of an interaction may also improve the reliability of the measurement and the conclusions drawn about specificity. These findings may lower the risk of false negative results as well as reducing the amount of reagent needed.

Keyword
specificity, affinity, kinetics, competition assay
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-147025 (URN)10.1002/jmr.1026 (DOI)000289781900008 ()21194119 (PubMedID)
Available from: 2011-02-23 Created: 2011-02-23 Last updated: 2017-12-11Bibliographically approved
2. Circumventing the requirement of binding saturation for receptor quantification using interaction kinetic extrapolation
Open this publication in new window or tab >>Circumventing the requirement of binding saturation for receptor quantification using interaction kinetic extrapolation
2011 (English)In: Nuclear medicine communications, ISSN 0143-3636, E-ISSN 1473-5628, Vol. 32, no 9, 863-867 p.Article in journal (Refereed) Published
Abstract [en]

Quantification of the number of receptors per cell (NRPC) is important when assessing whether a tumor surface biomarker is suitable for medical imaging. One common method for NPRC quantification is to use a binding saturation assay, which is time consuming and requires large amounts of reagents. The aim of this study was to evaluate an alternative method based on kinetic extrapolation (KEX) and compare it with the classical manual saturation technique with regard to accuracy as well as time and reagent consumption. Epidermal growth factor receptor (EGFR) and HER2 receptor surface expression were quantified on five tumor cell lines using three (125)I-labeled and (131)I-labeled ligands (cetuximab and EGF for EGFR, trastuzumab for HER2 receptor) for both techniques. The KEX method involved interaction measurements in the LigandTracer, followed by KEX through computerized real-time interaction analysis to correct for nonsaturation on cells. Variability and NRPC estimates of the EGFR and HER2 receptor levels using the KEX method were comparable with the results from the classical saturation technique. However, the ligand consumption for the KEX method was 26-46% of the classical saturation technique. Furthermore, the KEX method reduced the workload radically. From the observations described in this study, we believe that the KEX method enables fast, credible, and easy NRPC quantification with a reduction in reagent consumption.

Keyword
kinetics, ligand-receptor interaction, receptor quantification
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-158879 (URN)10.1097/MNM.0b013e3283483e1c (DOI)000294345300015 ()
Available from: 2011-09-20 Created: 2011-09-19 Last updated: 2017-12-08Bibliographically approved
3. Deciphering complex protein interaction kinetics using Interaction Map
Open this publication in new window or tab >>Deciphering complex protein interaction kinetics using Interaction Map
Show others...
2012 (English)In: Biochemical and Biophysical Research Communications - BBRC, ISSN 0006-291X, E-ISSN 1090-2104, Vol. 428, no 1, 74-79 p.Article in journal (Refereed) Published
Abstract [en]

Cellular receptor systems are expected to present complex ligand interaction patterns that cannot beevaluated assuming a simple one ligand:one receptor interaction model. We have previously evaluatedheterogeneous interactions using an alternative method to regression analysis, called Interaction Map(IM). IM decomposes a time-resolved binding curve into its separate components. By replacing the reductionistic,scalar kinetic association rate constant ka and dissociation rate constant kd with a two-dimensionaldistribution of ka and kd, it is possible to display heterogeneous data as a map where each peakcorresponds to one of the components that contribute to the cumulative binding curve. Here we challengethe Interaction Map approach by artificially generating heterogeneous data from two known interactions,on either LigandTracer or Surface Plasmon Resonance devices. We prove the ability of IM toaccurately decompose these man-made heterogeneous binding curves composed of two different interactions.We conclude that the Interaction Map approach is well suited for the analysis of complex bindingdata and forecast that it has a potential to resolve previously uninterpretable data, in particular thosegenerated in cell-based assays.

Keyword
Real-time analysis, Kinetics, Heterogeneity, LigandTracer, SPR
National Category
Medical and Health Sciences
Research subject
Molecular Biotechnology
Identifiers
urn:nbn:se:uu:diva-183869 (URN)10.1016/j.bbrc.2012.10.008 (DOI)000311523200013 ()
Available from: 2012-11-05 Created: 2012-11-05 Last updated: 2017-12-07Bibliographically approved
4. Comparing the epidermal growth factor interaction with four different cell lines: intriguing effects imply strong dependency of cellular context
Open this publication in new window or tab >>Comparing the epidermal growth factor interaction with four different cell lines: intriguing effects imply strong dependency of cellular context
2011 (English)In: PLoS ONE, ISSN 1932-6203, Vol. 6, no 1, e16536- p.Article in journal (Refereed) Published
Abstract [en]

The interaction of the epidermal growth factor (EGF) with its receptor (EGFR) is known to be complex, and the common over-expression of EGF receptor family members in a multitude of tumors makes it important to decipher this interaction and the following signaling pathways. We have investigated the affinity and kinetics of (125)I-EGF binding to EGFR in four human tumor cell lines, each using four culturing conditions, in real time by use of LigandTracer®.Highly repeatable and precise measurements show that the overall apparent affinity of the (125)I-EGF - EGFR interaction is greatly dependent on cell line at normal culturing conditions, ranging from K(D)≈200 pM on SKBR3 cells to K(D)≈8 nM on A431 cells. The (125)I-EGF - EGFR binding curves (irrespective of cell line) have strong signs of multiple simultaneous interactions. Furthermore, for the cell lines A431 and SKOV3, gefitinib treatment increases the (125)I-EGF - EGFR affinity, in particular when the cells are starved. The (125)I-EGF - EGFR interaction on cell line U343 is sensitive to starvation while as on SKBR3 it is insensitive to gefitinib and starvation.The intriguing pattern of the binding characteristics proves that the cellular context is important when deciphering how EGF interacts with EGFR. From a general perspective, care is advisable when generalizing ligand-receptor interaction results across multiple cell-lines.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-147027 (URN)10.1371/journal.pone.0016536 (DOI)000286834300081 ()21304974 (PubMedID)
Available from: 2011-02-23 Created: 2011-02-23 Last updated: 2013-02-11Bibliographically approved
5. Gefitinib Induces Epidermal Growth Factor Receptor Dimers Which Alters the Interaction Characteristics with (125)I-EGF
Open this publication in new window or tab >>Gefitinib Induces Epidermal Growth Factor Receptor Dimers Which Alters the Interaction Characteristics with (125)I-EGF
Show others...
2011 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 6, no 9, e24739- p.Article in journal (Refereed) Published
Abstract [en]

The tyrosine kinase inhibitor gefitinib inhibits growth in some tumor types by targeting the epidermal growth factor receptor (EGFR). Previous studies show that the affinity of the EGF-EGFR interaction varies between hosting cell line, and that gefitinib increases the affinity for some cell lines. In this paper, we investigate possible mechanisms behind these observations. Real-time interaction analysis in LigandTracer (R) Grey revealed that the HER2 dimerization preventing antibody pertuzumab clearly modified the binding of (125)I-EGF to EGFR on HER2 overexpressing SKOV3 cells in the presence of gefitinib. Pertuzumab did not affect the binding on A431 cells, which express low levels of HER2. Cross-linking measurements showed that gefitinib increased the amount of EGFR dimers 3.0-3.8 times in A431 cells in the absence of EGF. In EGF stimulated SKOV3 cells the amount of EGFR dimers increased 1.8-2.2 times by gefitinib, but this effect was cancelled by pertuzumab. Gefitinib treatment did not alter the number of EGFR or HER2 expressed in tumor cell lines A431, U343, SKOV3 and SKBR3. Real-time binding traces were further analyzed in a novel tool, Interaction Map, which deciphered the different components of the measured interaction and supports EGF binding to multiple binding sites. EGFR and HER2 expression affect the levels of EGFR monomers, homodimers and heterodimers and EGF binds to the various monomeric/dimeric forms of EGFR with unique binding properties. Taken together, we conclude that dimerization explains the varying affinity of EGF - EGFR in different cells, and we propose that gefitinib induces EGFR dimmers, which alters the interaction characteristics with (125)I-EGF.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-159470 (URN)10.1371/journal.pone.0024739 (DOI)000294803200045 ()
Available from: 2011-10-04 Created: 2011-10-03 Last updated: 2017-12-08Bibliographically approved
6. Resolving the EGF-EGFR interaction characteristics through a multiple-temperature, multiple-inhibitor, real-time interaction analysis approach
Open this publication in new window or tab >>Resolving the EGF-EGFR interaction characteristics through a multiple-temperature, multiple-inhibitor, real-time interaction analysis approach
2013 (English)In: Molecular and Clinical Oncology, ISSN 2049-9469, Vol. 1, no 2, 343-352 p.Article in journal (Refereed) Published
Abstract [en]

Overexpression and aberrant activity of the epidermal growth factor (EGF) have been observed in various cancer types, rendering it an important target in oncology research. The interaction between EGF and its receptor (EGFR), as well as subsequent internalization, is complex and may be affected by various factors including tyrosine kinase inhibitors (TKIs). By combining real‑time binding curves produced in LigandTracer® with internalization assays conducted at different temperatures and with different TKIs, the processes of ligand binding, internalization and excretion was visualized. SKOV3 cells had a slower excretion rate compared to A431 and U343 cells, and the tested TKIs (gefitinib, lapatinib, AG1478 and erlotinib) reduced the degree of internalization. The kinetic analysis of the binding curves further demonstrated TKI‑dependent balances of EGFR monomer and dimer populations, where lapatinib promoted the monomeric form, while the other TKIs induced dimers. The dimer levels were found to be associated with the apparent affinity of the EGF‑EGFR interaction, with EGF binding stronger to EGFR dimers compared to monomers. This study analyzed how real‑time molecular interaction analysis may be utilized in combination with perturbations in order to understand the kinetics of a ligand‑receptor interaction, as well as some of its associated intracellular processes. Our multiple‑temperature and ‑inhibitor assay setup renders it possible to follow the EGFR monomer, dimer and internalized populations in a detailed manner, allowing for a new perspective of the EGFR biology.

Keyword
epidermal growth factor, tyrosine kinase inhibitors, internalization, kinetics, dimerization, heterogeneity
National Category
Medical and Health Sciences
Research subject
Medicine; Molecular Biotechnology; Medical Cell Biology
Identifiers
urn:nbn:se:uu:diva-183868 (URN)10.3892/mco.2012.37 (DOI)
Available from: 2012-11-05 Created: 2012-11-05 Last updated: 2013-07-24Bibliographically approved

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