Multiparameteranalytik von Immunzellen

Transkript

1 Multiparameteranalytik von Immunzellen Hans-Dieter Volk Institute of Medical Immunology, Charité, Berlin & Berlin-Brandenburg Center of Regenerative Therapies (BCRT) Charité, Berlin & Immunology Labor Berlin GmbH

2 Need for Personalized Medicine => Need for biomarkers guiding preventive and therapeutic approaches - enhanced knowledge on (patho)physiology = risk / disease subtypes - availability of new therapeutic tools selectively targeting particular pathways - health-economic pressure Need for biomarkers - to identify the right patient and the right time point for a particular preventive / therapeutic approach - to predict the individual safety / success / failure of the approach - to identify novel targets by deeper analysis of patients where the therapy failed Personalized Medicine

3 Entwicklung personalisierter Therapien Traditionelle Therapie Personalisierte Therapie One size fits all Strategie Stratifizierung der Patientenpopulation Individualisierte Therapie + einfach umzusetzen - viele partielle oder komplette Therapieversager - schlechtes Verhältnis Kosten / Nutzen - Biomarker notwendig + hohe Erfolgsrate + sehr gutes Verhältnis Kosten / Nutzen - Biomarker notwendig + neue Therapien möglich + sehr hohe Erfolgsrate + gutes Verhältnis Kosten / Nutzen

4 Long Way to Biomarker-guided Prevention / Therapy Selection of a promising biomarker (set) Methodical validation PoC study to verify the putative clinical usefulness of the marker Extensive methodical validation (incl. interlab comparison) Clinical validation - learning set of data for set-up of cut-off s etc. - confirmation set using predefined cut-off s etc. Biomarker-guided studies (approval studies) Clinical routine use

5 Applications of Immunological Biomarkers - Novel immune therapeutics (phase I/IIa studies) - safety (no over-immunosuppression, cytokine release, immunogenicity) - pharmacodynamics (sufficient suppression of the target) - efficacy (response / failure markers) - Personalized immunotherapy of immune-related disease - preselection of responder / non-responder to a particular therapy - minimizing adverse effects - early detection of response / failure - disease progression - Measuring the success of regeneration - Measuring the success of prevention

6 Key Multiparameter Methods in Immunology - Multicolor Flowcytometry quantification of extra/intracellular cell markers - Multiplex Ligand Assays quantification of soluble mediators / antibodies - Multiplex RT-PCR quantification of (immune) gene expression - NGS (gene expression, mutations, methylation...) => Core Research Units at BCRT and Inst.Med.Immunol. => certified (DACH/FDA) clinical study lab at Inst.Med.Immunology (5-10 phase I/a) => certified (DACH) routine lab at Labor Berlin GmbH (>4,000 patients/a)

7 One Key Method: Multiparameter Flowcytometry Differential automatic multiparameter flowcytometry blood smear blood cell counts >4 >10 >100 parameters about 100 1,000-10,000 >100,000 analyzed cells/sample minutes seconds seconds/minutes Identification / Quantification of cell subsets their history their activation level their ex vivo responsiveness

8 Opportunities / Problems - rising number of lasers (5) = many colors in parallel - rising number of surface /intracellular markers (>500) = complex analysis - limited number of fluorescence dyes with distinct emmission spectrum - alternatives - tandem dyes (e.g. PE-Cy5, PE-Cy7 etc.) - synthetic nano particles (e.g. QDots) - replacement of fluorescence dyes (CyTOF)

9 Opportunities / Problems challenges by using tandem dyes - incomplete energy transfer from carrier to emmission dye - one laser two ranges of emmission overlap with carrier-dye emmission => need for compensation! new options: QDots (broad absorption spectrum distinct emmission)

10 Applications: Immune Status ( Advanced differential blood smear )

11 Beispiel Immunstatus : Zusammensetzung Immunzellpopulationen FL1 CD16 FL2 CD56 FL3 CD19 FL4 leer FL5 CD14 FL6 CD4 FL7 CD8 FL8 CD3 FL9 CD64 FL10 CD45

12 Beispiel T-Zellsubsets: History = naive/memory/effektor T-Zellen FL1 CD127 FL2 CCR7 FL3 CD62L FL4 leer FL5 CD25 FL6 CD4 FL7 CD8 FL8 CD3 FL9 CD45RA FL10 CD45

13 Beispiel T-Zellen: in vivo akute und chronische Aktivierung FL1 CD57 FL2 CD28 FL3 HLA-DR FL4 leer FL5 CD27 FL6 CD4 FL7 CD8 FL8 CD3 FL9 CD45RA FL10 CD45

14 Entwicklung personalisierter Regenerativer Therapien Patienten mit Knochenbruch Stratifizierung Patienten in Risikogruppen stratifizierte Therapie Immun- Biomarker gezielte supportive Therapie für High-Risk Patienten one-size-fits all Therapie

15 Example I: Prediction of delayed bone fracture healing and identifying putative new targets for supporting bone fractur healing Charité / BCRT - Dr. S. Reinke - Prof. G. Duda - Prof. N. Haas - Prof. P. Reinke - Dr. Chr. Meisel - Dr. K. Jülke etc.

16 Immunological Biomarkers and Bone Healing Why immunological biomarkers in bone healing process? Background: - Blocking inflammation, e.g. by corticosteroids, diminishes wound healing and bone repair - mice deficient for adaptive immunity (scid mice) surprisingly expressed improved bone healing (Toben et al., J Bone Miner Res., infiltration by CD8+ T cells into bone fracture hematoma in a sheep model is associated with poor outcome (Schell/Schmidt-Blek 2011) evidence for a differentiated impact of immune reactivity on bone fractur healing

17 Immunological Biomarkers and Bone Healing Pilot Study: - Proximal Tibia fracture - 18 patients (10 men/ 8 women) - 18 weeks folow-up - Based on the X-ray analyses: - delayed healing patients (n=7) - resorption zone, incomplete callus formation, incomplete bridging at wk 12 (Gollwitzer/Runkel/Schmidmaier) - normal healing patients (n=11). - both groups were similar in age and gender -Immune biomarkers in peripheral blood - immune subsets by FACS - ex vivo stimulation of immune cells => cytokine secretion

18 AO41 B3 tibia fracture pre-surgery (w, years 48, smoker) Hypertrophic delayed healing 6 month after surgery in a AO41 B3 tibia fracture (w, years 48, smoker) Fig. 9a Fig. 9b Type Moore II tibia fracture pre-surgery (w, years 25, smoker) Normal healing of a tibia fracture type Moore II 12 weeks after surgery (w, years 25, smoker) Fig. 9c Fig. 9d

19 % body weight Fig. 2a Fig. 2b Calori Score * maximum force ** * delayed healing patients normal healing patients 0 delayed healing patients normal healing patients 0 6. wk 12. wk 18. wk Fig. 2c * * *

20 Immunological Biomarkers and Bone Healing Higher frequency of CD11a++CD8+T-cell in delayed healing patients indicates an expansion of memory/effector CD8+ T cells This expansion seems not to be a (post) operative fracture reaction but rather a pre-disposition. * = p < 0.05 Which kind of memory/effector CD8+ T cells? - central-memory - effector/memory - terminally differentiated effector (TEMRA)

21 Immunological Biomarkers and Bone Healing Higher frequency of CD11a++CD T-cells in delayed healing patients indicates an expansion of CD8+ TEMRA. This expansion seems not to be a (post) operative fracture reaction but rather a pre-disposition. * = p < 0.05 Expansion of TEMRA = poor bone fracture healing - fast migration into inflamed tissue - bystander activation (no antigen necessary) - undesired over -inflammation - targeting possible (e.g. p38-i)

22 Targeting CD8+ T cells improves bone fracture healing in mice Fig. 8a Fig. 8b Fig. 8c Fig. 8d wt 21d 200µm 200µm Fig. 8e Fig. 8f Fig. 8g Fig. 8h CD8+ depletetion 21d 200µm 200µm

23 Entwicklung personalisierter Regenerativer Therapien Transplantationspatienten Stratifizierung toleranter Patienten stratifizierte Therapie Toleranz- Biomarker gezielte Minimisierung Immunsuppression one-size-fits all Immunsuppression Selektion mit Biomarkern (Hochrisiko Patienten) autologe T-Zellen autologe T-Zellen individualisierte Therapie

24 state of the art Technologien in der klinischen Diagnostik / Prognostik und Forschung Durchflußzytometrie Massenspektrometrie Einzelzellanalytik Geschwindigkeit > X Parameter Trennschärfe

25 ein Mass-Cytometer = CyTOFF verbindet von beiden Technologien die Vorteile Mass-Cytometer > X Parameter Trennschärfe Einzelzellanalytik Geschwindigkeit

26 Funktionsprinzip - Mass Cytometer B) Markierung mit Metall -markierten Antikörpern C) Aufnahme mit CyTOF (1000 Zellen/s) D) Analyse A) Probe (Blut, Biopsie, Zellkultur,...) klassische Analyse (dot plot) 100 Parameter = Signaturen -> Bioinformatik

27 CD45RA CD45RA Vergleich Fluorescence - Mass Cytometry CD4 + T Zellen fluorescence mass CD4 CD4

28 31 Parameter -> 496 biaxial Plots neue Auswertetools und Bioinformatik sind heute bereits für klassische Zytometrie essentiell! und werden angewendet!

29 neue Analyse- und Auswertetools KG1a THP-1 patient X

30 neue Analyse- und Auswertetools ein Proband CD8 + T cell CD4 + T cell B cell Monocyte Granulocyte subset 1 NK cells RBC T cell subset 1 Granulocyte subset II T cell subset II multiple Probanden

31 SPADE: Spanning-tree Progression Analysis of Density-normalized Events (MST = minimum spanning tree) Bendall et al., Science (May 6, 2011)

32 SPADE: Spanning-tree Progression Analysis of Density-normalized Events SPADE identifies a continuum of 280 hematopoietic cell populations Bendall et al., Science (May 6, 2011)

33 Potential Zytometrie bis 2011 state of the art now Diagnostik, Prognostik, Grundlagenforschung, direkte Korrelation Genotyp - Phänotyp - Funktion Benoist & Hacohen Science (May 6, 2011)

34 Fazit theoretisch kann jede Art von Target (Oberflächenmoleküle, intrazelluläre phosphorylierte Proteine, RNA,...) quantitativ markiert und auf Einzelzellbasis analysiert werden Diagnostik, Prognostik, Grundlagenforschung, direkte Korrelation Genotyp - Phänotyp - Funktion Benoist & Hacohen Science (May 6, 2011)

35 Thank you! Nephrology/ BCRT Petra Reinke Cardiology/BCRT Carsten Tschoepe Immunology /BCRT: Birgit Sawitzki Christa Liebenthal Christian Meisel Andreas Thiel Desiree Kunkel special thanks to clinicians, patients and nurses JWI/BCRT: Simon Reinke Georg Duda Hanna Schell Katharina Schmidt-Bleek HLA Lab Konstanze Schoenemann Support: BCRT/BMBF