Astana – September 21th, 2018Kazakhstan

Flow Cytometry Workshop

Customized cellular products

Matthias Schiemann

Technische Universität München, Germany

Flow Cytometry units of the Technischen UniversitätMünchen (CyTUM)

Steering Committee

Chair: M. Schiemann

Members: D. Busch, D. Zehn, C. Traidl-Hoffmann

Lehrstuhl für Tierphysiologie und Immunologie

Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt

Flow Cytometry FACS Unit`s – located at MIH, LTI and UNIKA-T

à First University overarching facility in Germany

680 user• 300 (Analysis)• 380 (Cell Sorting)

Instruments:

• 28 Analyzer• 7 Cell Sorter

• 10 employees

CyTUM

Instrumentation of the CyTUM MIH

>200 different cell typesAdherence

Density

Microfluidics

Antibody

Plasma

PBMCs

Erythrocytesc tes

cs

Adherence

Density

Plasma

PBMCs

Erythrocytesc tes

Microfluidicscs

Antibody

Cell separation – an overview

MACS FACS

LaserPOI

Droplet generation

Deflection

Nozzle

Sca ttered light

Fluorescence

Waste

Antibody based cell separation methods

Introduction FACS

LaserPOI

Droplet generation

Deflection

Nozzle

Sca ttered light

Fluorescence

Waste

Scientific Question and considerations

- Sample processing- Cell isolation/preparation- Staining/biological

durability/activation- Temperature

- Sorting parameters- Pressure- Shearing

effects/Acceleration- Decompression/expansion- Laser light- Electrostatic charge- Impact- Energy Dissipation Rate

Varma, S. et al., Analytical chemistry (2017)Richardson, G. M. et al., Cytometry A (2015)Mollet, M. et al., Biotechnology and Bioengineering (2007)

A closer look at some FACS forces

Ge, J. et al., Cytometry A (2013)Catt, S. L. et al., Molecular human reproduction (1997)

Olesen, S. P. et al., Nature (1988)Seidl, J. et al., Cytometry (1999).

Eisinger, J. et al., Biophysical chemistry (1987)

Characterization of cell alterations caused by FACS

In versatile applications FACS is unrivaled to otherpurification methods, thus limited to applications forresearch use only.

In the work of our group we evaluate assays to determinecell fitness, in order to validate current research data.These results might also be useful for other clinical cellprocessing's.

Method – “optimized” cell sorter

We built a modified MoFlo XDPTM cell sorter, for controlling temperature sort

conditions of the whole system, enabling us to evaluate the influence of

temperature. In this approach we used different technologies to evaluate every

single parameter during sorting, like in an equation, with only one variable.

37�C4�C

LLO91-99–specific T cell lineH2-Kd/LLO91-99/mb2m SA-Alexa54645 min staining

FACS Optimizing - Temperature

0

5

10

15

20

25

30 60 90 120 150 180 210 240 270 300 330 360

time [min]

tem

pera

ture

[°C]

roomtemperature

conventionellice cooling

coolingoption

Ice cooling

Centralized cooling solution for all conventionalinstruments

Temperature control on the MoFlo XDPTM fluidic system

Sorting with temperature control:Stable from 7�C up to 30�C

Cell death after temperature storage by propidium iodide (PI) staining

Flow cytometric analysis of cell death after temperature storage by propidium iodide (PI) staining. Graphs show percentages of living cells in a time course for human PBMCs, murine splenocytes and K562 cells.

Phosphorylation of the MAPK p38 signaling pathway

Immunoblot (top left graph) for phosphorylated p38 in ficoled PBMCs from BuffyCoatDonors, with exclusion of Buffer related phosphorylation effects (lower graph). p38 signal strength was determined via ImageJ Software shown as a bar chart (top right graph).

phospho-p38

endogenous-p38

PB

MC

´s u

nsor

ted

PB

MC

´s im

med

iate

afte

r sor

t

0.18 0.54 0.59 0.58 0.45 0.25

PBMC´s incubated after sort time in min

0 5 15 30

Functional Analysis of sorted cells

Two graphs (both left) show the proliferation based thymidine uptake of sorted CD8 positive cells in a mixed lymphocyte reaction (MLR).

Lower graph displays the survival of sorted CD8 cells from whole blood in a time course over two days.

mRNA levels via MicroArray

sorted – 0h

unsorted - 0h

unsorted

4h

resting

unsorted - 0h

sorted – 4h

over time

sorted – 4hsorted – 4h

unsorted - 4h

Conclusion and Discussion

- We were able to observe sorting induced cell alterations in different cell lines, as well as altered cell physiology.

- Primary cells, specially PBMCs and T-cells seemed very robust und unaffected by the use of FACS.

- The parameters evaluated in this project could also be applied to other clinical cell processing methods.

- mRNA levels via MicroArray

- no activation – more down regulation

General problem: remaining sort-marker

• changes of the cell populationcross linking, activation, cell death, receptor blockade

• clinical issuestoxicity, immunogenicity, allergic reactions

• regulatory/economical aspectsdifficult process for reagent approval

MHC Multimers

MHC dimers

(Schneck)

1 10 100 1000 10000FL2-H: SIIN-dimer 1:20

1

10

100

1000

10000

FL1-

H: C

D8a

20.5 0.47

21.4 57.6

H2-Kb/SIINFEKL dimer

CD

8a

MHC monomer MHC tetramers

(Altman/Davis)

1 10 100 1000 10000FL2-H: SIIN-tet 1:20

1

10

100

1000

10000

FL1-

H: C

D8a

20.7 0.85

1.13 77.3

H2-Kb/SIINFEKL tetramerC

D8a

LLO91-99-specific T cells

MHC Multimers - adoptive Transfer

bact

eria

per s

plee

n

2 x 107 + Multimerno T cells

2 x 107 + T cell line

104

N = 12

105

106

107

T cells

day -1 0 3

Listeria i.v. CFUBacteria spleen / liver

infection after 1 dayBalb/c

2 x 107 + MHC Tetramers

no T cells

2 x 107 + T cell line

LLO91-99-specific T cells

104

MHC Multimers - adoptive Transfer

N = 12

bact

eria

per

spl

een

105

106

107

Reversible MHC Multimers - Streptamers

d-Biotin/Streptactin

KD 10-12 M

d-Biotin

StreptagIII/Streptactin

KD 10-6 M

1 10 100 1000 10000FL2-H: MHC-pily aHSV staining no bio 0

0

20

40

60

80

100

% o

f Max

w/o d-biotincontrol

0

20

40

60

80

100

% o

f Max

+d-biotin

LLO91-99/Kd - Streptamertime 0 min30

% o

f Max

epitope tag staining

Knabel, Franz, Schiemann et al.

Nature Medicine 2002

PE

Alexa 488

*

*

*

*

MHC Streptamers

time[sec]0 200 400 600 800 1000 1200

fluor

esce

nce

inte

nsity

0

10000

20000

30000

40000

50000

60000

koff = -0,0038; t1/2 = 182,41 sec

Regression : y = a * e –koff * t

2 x 107 + MHC Tetramers

no T cells

2 x 107 + T cell line

2 x 107 + MHC Streptamers + d-Biotin

MHC Streptamers and effective adoptive Immunotherapy

** p < 0.001 N = 12

104

Bact

eria

per

spl

een

105

106

107

LLO91-99-specific T cells

CD3

MH

C M

ult

imer

100 101 102 103 104100

101

102

103

104

10

6.22

2.18 81.6

positive fraction

magnetic beads / reversible Multimers

10000

100000

1000000

1x107 1 x 1051x105

PBS

10 mice/group

T cell line ex vivo

prim

ary

T ce

lls

viab

le L

iste

ria

/ sp

leen

Directly ex vivo sorted T cells

• remaining marker (MHC multimers) can alter stained cells

• fully reversible staining with MHC Streptamers

• low numbers of primary T cells for effective adoptive transfer

• identification of highly effective memory subsets for adoptive transfer

Preclinical research summary

• hematopoetic / mesenchymal stem cells

• T cells (antigen-specific T cells, regulatory T cells)

• endothelia, chondrocytes, NK cells …....

Increasing targets and applications

Cell therapy

donor recipient

T cell therapy

donor recipient

4-5 weeks

CD8

B8/IE

1 m

ultim

er

1-2 days

Clinical cell sorting

before sort positive fraction

A2/pp65 -Streptamer-Beads

CliniMACS, MiltenyiCD8

MH

C m

ult

imer

(H

LA-A

2/pp

6549

5-50

3)

100 101 102 103 104100

101

102

103

104

100 101 102 103 104100

101

102

103

104

93.8 %0.45 %

magnetic particle

• MHC Multimer-purification: pp65495-503-specific T cells

• adoptive transfer of 100.000 specific cells

• 14 years, ALL, CMV positive

• stem cell transplantation (father)

• after 2 weeks, CMV reactivation, Ganciclovir resistant Þ Foscarnet

Example: Patient (Utrecht)

Immune-Monitoring upon T cell transfer

0.65%

8. weeks after transfer

1.09%

5. week

0.38%

3. week

0.08%

1. weekCM

V pp

65 T

etra

mer

APC

CD8 Pacific Blue

before

0.0 %

0.78%

4. week

T cells, virus load

-10 0 10 20 30 40 50 60 70

0.20

0.40

0.60

0.80

1.00

1.20

1.40

virus load

0.0

0.3

0.5

0.8

1.0

1.3

1.5

CD3+CD8+ Multimer+ T cells

days after adoptive transfer

viru

s lo

ad [#

cop

ies

x 10

.000

] Multim

er+ CD3+ lymphocytes [%

]

Identification ofdonor derivedT cells by CDR3specific primers

Bulk sorting of at least5/105 Donor T cell for PCRscreening with V-betaspecific primers

DonorPatient

CD

R-1

CD

R-2

CD

R-3

CD

R-1

CD

R-2

CD

R-3

Donor

Single cell sort on 48 spot slides for CDR3-T cell Tracking in CMV patients

Donor Recipient

Sorting of 1 antigen specific donor T cells per PCR sample

Sorting of 1 antigen specific patient T cells per PCR sample

Patient

Patient (SCID, Tunesia)

• Streptamer-purification: pp65495-503 specific T cells

• adoptive transfer of 30.000 specific cells

• 8 Mo, severe combined immunodeficiency

• stem cell transplantation (father)

• CMV in urine, blood, ascites, trachea, liquor, skin biopsy

• Ganciclovir resistant

A. Borkhardt (Düsseldorf)

CD8 APC-A750

MHC

Mul

timer

PE

7.94

3 weeks after AT

31

4 weeks after AT

0.54

7 weeks after AT

3.89

6 weeks after AT

18.6

5 weeks after AT

0

1 week after AT

0

before AT

0.21

8 weeks after AT

Immunmonitoring upon T cell transfer

Sequence (Patient) V�13N …TGTGCCAGCTTTTTTGGGGGTGGGGATCAAC…

Sequence (Donor) V�13N …TGTGCCAGCTTTTTTGGGGGTGGGGATCAAC…TCRVb13.6 BD2.1 BJ1.2

TUMCells

Core Team: Martin Hildebrandt

Alex SlobodianskiMichael Neuenhahn Nicole Frisch

Julia Albrecht Tanja Rossmann-Bloeck

Products - designed for the production of:

§ Blood cell products

§ Investigational drugs§ Advanced Therapy Medicinal Products (ATMPs), which include:

§ Somatic cell therapy; Gene transfer drugs; Tissue-engineered products (combination products).

Clinical cell processing

Interaction of TCR – MHC Streptamers è only T cells are accessible

• is this principle transferable to other surface molecules / cells ?

è virtually any cell can be addressed (access to cell therapy)

è multiple marker stainings

� recombinant Fab-streptag monomers

� if necessary, affinity modification

unstained8x washing2x washing

CD30 Fab multimer

% o

f Max

Stable binding of aCD30 multimers even after excessive washing

Fab Streptamers

Fully reversible staining with Fab-Streptamers

FL1 - FITC

CD

3 Fa

b-m

ultim

er /

Fab-

mon

omer

64.5

Fab-multimer

0.005

Fab-multimerê

D-biotin

0.018

Fab-multimerê

D-biotin

ê

ST-PE

62.8

Fab-multimerê

D-biotin

ê

Fab-multimer

64.1

FL1 - FITCC

D3

mAb

mAb

Stemberger, Dreher, Tschulik, Schiemann et al.

PloS One 2012

Multiplex Streptamer staning and sorting

Method – “untouched” cells

www.iba-lifesciences.com

Fully reversible staining with Fab-Streptamere

www.iba-lifesciences.com

www.fabian-online.com

Cell selection and expansion:

• FABian® for automated cell selection - with reversible reagents

• PBMCs, T and B cell isolation directly from whole blood withoutmagnetic beads and density gradient centrifugation.

• MHC Streptamers

• Tool for basic research and clinical applications

• Fab Streptamers – transfer of Streptamers to virtually any cell surface

marker

• Reversibility as a standard for clinical cell purification

Summary

From bench to beside - collaboration groups

Schiemann Lab Immunmonitoring

Immanuel Andrä Michael Neuenhahn

Susi Dürr

Lynette Henkel

Busch Lab

Veit Buchholz

Anna HochholzerLothar Germeroth Herbert Stadler

Christian Stemberger

Interdisziplinäres Zentrum für Zelltherapie am Klinikum der Universität München (IZZTKUM)

Martin Hildebrand

Dirk Busch