Time-resolved interaction analysis on living cells: Comprehensive data generates new knowledge and better decisions

Transcription

1 Time-resolved interaction analysis on living cells: Comprehensive data generates new knowledge and better decisions Karl Andersson CEO

2 Karl Andersson, PhD Ridgeview Instruments AB Molecular interactions on living cells Founder, inventor, CEO Uppsala University Associate professor & senior lecturer Dpt of Immunology, Genetics and Pathology In the past Biacore R&D ( ) PhD bioinformatics MSc scientific computing

3 The first contact between drug and cell

4 The first contact between drug and cell Number of drugs bound to target

5 Technology background 3 simulated binding traces Same affinity 1 nm Different interaction dynamics First 2 h 10 nm Then 7 h wash-out % occupied target h

6 Technology background Fast on - fast off requires continuous supply 100 % occupied target Slow on - slow off will occupy fraction of targets for a long time h

7 Technology background Frequent administration of low concentration. 100 % occupied target Rare administration of high concentration h Affinity alone cannot provide this information

8 Technology background Curve shape may be indicative of mode-of-action 100 % occupied target Relative signal may reflect receptor abundance h Affinity alone cannot provide this information

9 Binding kinetics in context Drug discovery: effort to relate in vitro binding kinetics to in vivo effects Local concentration of drug Ligand + Target k on k off LT complex Downstream biological processes Pharmacokinetics Binding Kinetics Pharmacodynamics

10 Our solution: LigandTracer Measure interactions Often: Protein cell Truly: Any Any Label based detection Fluorescence or radioactivity

11 LigandTracer cell based assay Cells in regular Petri dish Rotating, sloping support Detection at drained higher end

12 Signal Detector Time Medium + Ligand Petri dish with cells (T) and background (B) position LigandTracer Output: Background corrected real-time binding curve

13 The first contact between drug and cell Number of drugs bound to target

14 The first contact between drug and cell What can you learn about your molecules? Examples from: Rituximab - CD20 EGF EGFR

15 Rituximab CD20 CD20 Drug target since late 1990 s Challenges for real-time cell-based assays B-cells in suspension = need to anchor them CD20 suggested to form clusters / oligomers = complex framework mab treatment is often conveyed through CDC or ADCC Not too much literature on the CD20 biology

16 Challenge 1: Anchoring Anchoring protocol developed: BAM Verified on a range of different cells and targets Daudi / CD20 A431 / EGFR Jurkat / CD3 BAM Target cells in PBS Cultivate in cell-culture medium Bondza et al, Front. Immunol., 24 April 2017

17 Challenge 2: Clustering Interactions often thought as one-to-one Ligand Glycosphingolipid Monomer Homodimer Heterodimer Oligomer Clustering in microdomains Cholesterol

18 Challenge 2: Clustering Interactions often thought as one-to-one Poor match with the reality on a cell surface... Ligand Glycosphingolipid Monomer Homodimer Heterodimer Oligomer Clustering in microdomains Cholesterol

19 Challenge 2: Clustering - quantification Develop proximity assay to follow cluster (or dimer) formation over time: Bondza et al, Anal Chem Dec 19

20 Challenge 2: Clustering - results Rituximab induces clustering of CD20 CD20 and B-cell receptor co-localize????

21 Challenge 3: Antibody effect issues

22 Challenge 3: Antibody effect issues

23 Challenge 3: Antibody effect issues Is there a relation between anti- CD20 mab interaction and CDC??? C1q binding to Rituximab on a B-cell line 20 nm Fitc- C1q nm unl Rituximab

24 Rituximab CD20 conclusions Confirmed non-1:1 interaction = biology to discover Activities in our lab Clustering and co-localization confirmed and in process of quantification Interaction dependent CDC mechanisms in pipeline to be monitored, on-line Next step: Expand antibody library with plethora of CD20 binders Share findings to enrich literature on the subject

25 Examples from the EGFR family Overexpressed in variety of cancers Used to establish our toolbox of methods Common trait: Comparison of similar states Culturing conditions / cell lines / labels / molecules

26 EGF( 125 I) EGFR multiple conditions and cell lines A431 cells Conditions Red: Regular Blue: Starving Green: Gefitinib Black: Gefitinib + starvation 3 nm 9 nm 0 nm 3 nm 9 nm 0 nm 3 nm 9 nm 0 nm 3 nm 9 nm 0 nm Björkelund H, et al, PLoS One. 2011;6(9):e24739.

27 Comparing cell lines EGFR HER2 A SKOV Conditions Red: Regular conditions Blue: Starvation Green: Gefitinib (Iressa) Black: Gefitinib + starvation Björkelund H, et al, PLoS One. 2011;6(9):e24739.

28 Unlocking results with Interaction Map

29 Quantify drug-induced dimerization Quenching effect increased by 50% with Gefitinib treatment Kinetic parameters did not change significantly Increased quenching due to increase in EGFR-HER2 dimers

30 EGFR finding: Complex dimer biology Dimerization depends on drug and on cell line Altered dimerization pattern affects affinity Functional evaluation of dimerization mechanisms Björkelund H et al, Mol Clin Onc :

31 Extending toolbox beyond EGFR and CD20 Nanoparticles Tissue samples Non-human cell models Virus Bacteria Incubate spot with 6ug/mL of Ab against E.coli membrane compound, 3h. Then wash. Incubate E.coli, OD=1.0, 1h at 37ºC, then block with BSA 1%, 30 min Ready to go.

32 All in all We work with time-resolved molecular interaction analysis on living cells Brings new light on biology Precise & repeatable Ideal for comparisons Advanced assays and data evaluation Simple technology with low running costs Available in all aspects; hardware, software

33 But one challenge remains Exploring Biophysical principles in Cell biology: Different way of thinking Different constraints New types of results

34 But one challenge remains Exploring Biophysical principles in Cell biology: Different way of thinking Different constraints New types of results So: Educate Arrange courses (new) Embed learning package in software

35 Courses Courses arranged by us Advanced level; WHY, not how Small group, genuine experts as teachers SPR-focus May 2018 Cell-based focus Fall 2018 On-site training using us Multiple universities embed our courses Dedicated training on-site at pharma companies (SPR and/or cell-based)

36 Learning package embedded in software More basic type education 1. HOW 2. WHY 3. WHAT 4. TEST Additional lessons in pipeline.

37 All in all We work with time-resolved molecular interaction analysis on living cells Brings new light on biology Precise & repeatable Ideal for comparisons Advanced assays and data evaluation Simple technology with low running costs Available in all aspects; hardware, software Digital learning module included Courses of various types available

38 Acknowledging Fantastic colleagues and collaborators, former and current, far too many to list Karl Andersson, PhD CEO

39 Thank you Karl Andersson, PhD CEO