Expanding Adipose-Derived Mesenchymal - SSCF · 2016. 6. 15. · 6 8 PD PD Flask Mean 6.378 SEM 0.269 N 4 Quantum Mean 4.420 SEM 0.449 N 4 * * p = 0.0096 0 20 40 60 80 DT (hours)

Expanding Adipose-Derived Mesenchymal

Stem / Stromal Cells In Vitro for Stem Cell Therapies

Christian Caprara, PhD

Swiss Stem Cell Foundation

iCAST 2016

Zürich, 31.05.2016

•  Adipose-derived mesenchymal stem / stromal cells (ASCs)

•  Clinical-grade production of ASCs for cell therapy

•  Cell expansion systems

•  Product characterization and quality controls

•  Quantum Cell Expansion System vs. flasks: yield and quality

•  Conclusions and outlook

Adipose-Derived Mesenchymal Stem / Stromal Cells

(ASCs)

Mesenchymal Stem/Stromal Cells (MSCs)

Wangetal,2014,NatureImmunology

Minimal criteria for defining MSCs:

(Dominici et al, 2006, Cytotherapy)

•  adherence to plastic

•  characteristic immunophenotypic profile

•  trilineage differentiation potential

(adipogenic, osteogenic, chondrogenic)

MSC sources:

•  almost all vascularized tissues

•  bone marrow, umbilical cord, adipose tissue, skin,

dental tissues, peripheral blood, muscle, etc.

ASCs Are Found in the Stromal Vascular Fraction (SVF)

Page 2 of 3

Data Set 2: Lipo 1603_Test1 16032016

00001870[Ungated] FL3 INT

Coun

t0

200

400

Beads Channel100 101 102 103

CAL

Gate Number %Total %GatedAll 64,959 100.00 100.00CAL 13,020 20.04 20.04

Data Set 2: Lipo 1603_Test1 16032016

00001870[CleanSVF]FS INT / SS INT

FS INT0 500 1000

SS IN

T

0

500

1000

Gate Number %Total %GatedAll 17,568 27.04 100.00

Data Set 2: Lipo 1603_Test1 16032016 00001870

[CleanSVF]FL4 INT Log / SS INT Linear

SS IN

T

0

500

1000

7-AAD10-1 100 101 102 103

Vive Morte

Gate Number %Total %GatedAll 17,568 27.04 100.00E3 0 0.00 0.00E4 0 0.00 0.00Morte 3,806 5.86 21.66Vive 13,762 21.19 78.34

Data Set 2: Lipo 1603_Test1 16032016 00001870

[CD45-] FL8 INT / FL2 INT

CD34-APC-A75010-1 100 101 102 103

CD14

6-PE

10-1

100

101

102

103

Pericytes Endothelial

Others ASCs

Gate Number %Total %GatedAll 11,455 17.63 100.00ASCs 6,225 9.58 54.34Endothelial 2,165 3.33 18.90Others 1,719 2.65 15.01Pericytes 1,346 2.07 11.75

Page 3 of 3

Data Set 3: Lipo CL test 2 310315 00001466

[CleanSVF] FL4 INT / SS INT

SS IN

T

0

200

400

600

800

1000

7-AAD10-1 100 101 102 103

Vive Morte




CD34-APC-A75010-1 100 101 102 103

CD14

6-PE

10-1

100

101

102

103


Others ASCs


Data Set 3: Lipo CL test 2 310315 00001466[Ungated] FL3 INT

Coun

t

0

200

400


CAL



[CleanSVF]FS INT / SS INT

FS INT0 500 1000

SS IN

T

0

500

1000


Page 2 of 3

Data Set 2: lipo 240715 t1 00001599

[Ungated] FL3 INT

Coun

t

0

100

200

300


CAL


Data Set 2: lipo 240715 t1 00001599

[CleanSVF]FS INT / SS INT

FS INT0 500 1000

SS IN

T

0

500

1000


Data Set 2: lipo 240715 t1 00001599

[CleanSVF]FL4 INT Log / SS INT Linear

SS IN

T

0

500

1000

7-AAD10-1 100 101 102 103

Vive Morte


Data Set 2: lipo 240715 t1 00001599


CD34-APC-A75010-1 100 101 102 103

CD14

6-PE

10-1

100

101

102

103


Others ASCs


SVF

ENZYMATIC DIGESTION

LIPOASPIRATE Adherent cells:

ASCs

CELL CULTURE

FLOW CYTOMETRY

Cell Therapy with MSCs

Tam and Pera, 2013. Bioessays

Injury Healing

liver cirrhosis

liver failure

periodontal tissue defects

diabetic critical limb ischemia

bone damage caused by osteonecrosis

burn-induced skin defects

myocardial infarction

cornea damage

brain and spinal chord injury

Immune Disorder Therapy

graft-versus-host disease

systemic lupus erythematosus

Crohn's disease

multiple system atrophy

multiple sclerosis

amyotrophic lateral sclerosis

Clinical-grade Production of ASCs for Cell Therapy

Cell Expansion Principles

•  Clinical needs: 0.5 to 5 x 106 ASCs/Kg body weight

(30 – 400 x 106 ASCs)

•  40 population doublings before entering senescence

•  maximum 20 population doublings for cell therapy (Prockop et al. 2010 Cytotherapy; Sensebe et al. 2011. Hum Gen Ther)

Ø safety and efficacy = functional ASCs that are safe

and retain their therapeutic properties

Ø develop a bioprocess in a well-defined environment

ASCs

Yield and Quality

(Stromal vs. Stem)

SVF

cell composition and ASC subtypes

Proliferation

ability

Donor age,

harvest site,

clinical history

Medium

composition

Seeding density

Culture microenvironment

Cell confluence

Cell viability

Cell senescence

(genomic stability)

Oxygen tension

Cryopreservation

GMP consistentproduc:onand

controlaccordingtoquality

standards

•  Major challenge: to develop scalable manufacturing

process while maintaining critical quality parameters

•  Applying GMP to the manufacture of living biological

drugs is not straightforward

•  GMP guidelines were designed for chemical

manufacturing

•  Cell culture-based protocols are more complex than

small molecule synthesis

Ø Product definition is more complicated

Product Characterization and Quality Controls

Identity

•  The product

contains the

intended cellular

components

•  Immuno-

phenotyping

• CFU-F

• Morphological

appearance

Purity

•  The product does

not contain

contaminant cell

types or process

reagents

•  Immuno-

phenotyping

Safety

•  The product is not

contaminated with

microbes and

does not have

tumorigenic

potential

• Sterility

• Non-pyrogenic

•  Tumorigenicity/

Genomic

stability

(karyotiping)

Potency

•  The product

possesses

biological

functions relevant

to treating the

intended clinical

indication

• Differentiation

•  Immuno-

supression

• Release of

bioactive

molecules

Product Characterization and Quality Controls

Cell Culture Systems

•  “Classic” T-flasks

+  cost-effective

+  good gas exchange

−  labor-intensive

−  low yield per flask (max 300 cm2)

−  not fully closed (class A cabinet required)

•  Multilayer vessels such as Cell STACKS (Corning)

or Cell Factory (Thermo Fisher)

+  less labor-intensive than T-flasks

+  high yield possible (up to 25’280 cm2)

− monitoring and harvest difficulties

−  not fully closed (class A cabinet required)

Cell Culture Systems

•  Closed automated devices

+  large ratio of surface area to volume

+  safer: closed system

+  simpler: automated inoculation and harvesting, automated control of

culture parameters

+  allows expansion in class C room

−  can be more expensive for “small scale”

•  Bioreactors

•  Multiplate (e.g. Pall Life Sciences), up to 122,400 cm2

•  Hollow-fiber (e.g. Terumo BCT), up to 21’000 cm2

•  Microcarrier (e.g. GE Lifesciences)

Quantum Cell Expansion System (Terumo BCT)

•  Hollow-fiber bioreactor

•  11,500 hollow fibers, 2.1 m2 cell culture surface area

•  equivalent to the surface area of 120 T175 flasks

•  Closed system

•  Automated inoculation, harvesting, and control of

temperature

•  Perfusion system: cell feeding and waste removal

•  Normoxic or hypoxic cell culture

Lactate Monitoring for Cell Number Prediction

•  Within the bioreactor it is not possible to visualize cells

•  Cell number prediction though (daily) measurements of lactate

concentration

•  lactate production is proportional to cell number

•  Experimental determination (in flask culture) of the maximal lactate

production (mmol) per cell per day (reference value for cell number

prediction)

7 days 0.98 mmol/L

11 days: 1.22 mmol/L

13 days: 4.42 mmol/L

Quantum vs. Flasks

Yield

Lactate Measurements for Cell Number Prediction

•  Seeded 9.6 x 106 ASCs

•  5% human platelet lysate (hPL) in IMDM:F12

•  21% O2

0 5 10 150.0

5.0×107

1.0×108

1.5×108

2.0×108

2.5×108

Days

Cells

2.32 x 108

2.07 x 108

Predicted

Real

Donor-dependant Yield Variability

SVF (p=0)

5% hPL in IMDM:F12

pre-selected ASCs (p>1)

5% hPL in IMDM:F12

0 2 4 6 80

1×108

2×108

3×108

4×108

5×108

Days

Ce

lls

1 x 108

Donor 1 (P2)

Donor 2 (P1)

4.84 x 108

0 5 10 150.0

5.0×107

1.0×108

1.5×108

2.0×108

2.5×108

Days

Ce

lls

Donor 3 (SVF)

Donor 2 (SVF) 2.32 x 108

7.51 x 107

Seed Harvest CultureDura/on(days) PD(cumula/ve)

Donor2(SVF) 9.60x106 2.32x108 11.90 5.18

Donor3(SVF) 1.05x107 7.51x107 13.80 3.43

Donor2(ASC,P1) 2.00x107 4.84x108 5.83 10.36

Donor1(ASC,P2) 1.00x107 1.00x108 6.90 6.76

Higher ASC Proliferation in Flasks

0

2

4

6

8

PD

PD

Flask

Mean

6.378

SEM

0.269

N

4

Quantum

Mean

4.420

SEM

0.449

N

4

* *

p = 0.0096

0

20

40

60

80

DT

(h

ou

rs)

Flask

Quantum

DT

Flask

Mean

34.360

SEM

5.006

N

4

Quantum

Mean

55.735

SEM

14.706

N

4

Population Doublings Doubling Time

Medium and Feeding Rate Optimization

0 2 4 6 80

2×108

4×108

6×108

8×108

Days

Cells

normal feeding rate

high feeding rate

0 2 4 6 80

2×108

4×108

6×108

8×108

Days

Cells

5% hPL

5% hPL + bFGF

High feeding rate + bFGF

Quantum vs. Flasks

Quality

Immunophenotyping

ASC 2 Analysis - overlays

Page 2

CD31CD31-FITCIgG1-FITC

%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD31-FITC100 101 102 103

CD31+

1.65 %

Marker Number %Total %Gated X-Med X-AMeanAll 80,663 66.02 100.00 0.29 0.40All 98,932 81.93 100.00 0.25 0.28CD31+ 1,333 1.09 1.65 0.90 5.71CD31+ 1,033 0.86 1.04 0.87 1.09

CD45CD45-KrOIgG1-KrO

%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD45-KrO10-1 100 101 102 103

CD45+

0.56 %

Marker Number %Total %Gated X-Med X-AMeanAll 86,121 64.50 100.00 0.43 0.49All 98,932 81.93 100.00 0.62 0.71CD45+ 482 0.36 0.56 2.23 2.60CD45+ 1,227 1.02 1.24 2.23 2.51


Page 2


%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD31-FITC100 101 102 103

CD31+

1.65 %


CD45CD45-KrOIgG1-KrO

%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD45-KrO10-1 100 101 102 103

CD45+

0.56 %

Marker Number %Total %Gated X-Med X-AMeanAll 86,121 64.50 100.00 0.43 0.49All 98,932 81.93 100.00 0.62 0.71CD45+ 482 0.36 0.56 2.23 2.60CD45+ 1,227 1.02 1.24 2.23 2.51


Page 3

CD11bCD11b-APCIgG1-APC

%Gat

ed

0

0.1

0.2

0.3

0.4

0.5

CD11b-APC10-2 10-1 100 101 102 103

CD11b+

0.04 %

Marker Number %Total %Gated X-Med X-AMeanAll 86,121 64.50 100.00 0.00 -12.38All 98,932 81.93 100.00 0.03 0.03CD11b+ 37 0.03 0.04 1.03 17.48CD11b+ 1,054 0.87 1.07 0.33 0.63


%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD73-FITC100 101 102 103

CD73+

99.71 %



Page 3

CD11bCD11b-APCIgG1-APC

%Gat

ed

0

0.1

0.2

0.3

0.4

0.5

CD11b-APC10-2 10-1 100 101 102 103

CD11b+

0.04 %

Marker Number %Total %Gated X-Med X-AMeanAll 86,121 64.50 100.00 0.00 -12.38All 98,932 81.93 100.00 0.03 0.03CD11b+ 37 0.03 0.04 1.03 17.48CD11b+ 1,054 0.87 1.07 0.33 0.63


%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD73-FITC100 101 102 103

CD73+

99.71 %



Page 4

CD105CD105-PEIgG3-PE

%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD105-PE10-2 10-1 100 101 102 103

CD105+

99.95 %


CD140aCD140a-PEIgG3-PE

%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD140a-PE10-2 10-1 100 101 102 103

CD140a+

0.68 %

Marker Number %Total %Gated X-Med X-AMeanAll 80,663 66.02 100.00 0.00 -0.20All 98,932 81.93 100.00 0.12 0.15CD140a+ 547 0.45 0.68 1.14 1.73CD140a+ 1,149 0.95 1.16 0.78 1.48


Page 5

CD90CD90-PC5IgG1-PC5

%Gat

ed

0

0.2

0.4

0.6

0.8

CD90-PC510-1 100 101 102 103

CD90+

99.98 %



%Gat

ed

0

0.2

0.4

0.6

0.8

CD146-PC510-1 100 101 102 103

CD146+

70.11 %



Page 6


%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD13-PC710-1 100 101 102 103

CD13+

99.95 %


CD44CD44-APCA750IgG1-APCA750

%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD44-APCA75010-1 100 101 102 103

CD44+

99.78 %



Page 6


%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD13-PC710-1 100 101 102 103

CD13+

99.95 %


CD44CD44-APCA750IgG1-APCA750

%Gat

ed

0

0.2

0.4

0.6

0.8

1

CD44-APCA75010-1 100 101 102 103

CD44+

99.78 %


Immunophenotyping

MSC Positive Markers MSC Negative Markers

CD73

CD10

5

CD90

CD13

CD44

90

95

100

% p

os

itiv

e

CD31

CD45

CD11

b

0

1

2

3

4

5

6

% p

os

itiv

e

Quantum (n=5)

Flask (n=5)

Colony-Forming Unit Fibroblast (CFU-F) Assay

•  Acceptance criteria for CFU-F

(Bourin et al. 2013, Cytotherapy)

•  “fresh” SVF: > 1%

•  pre-selected ASCs: > 5%

SVF (CC) SVF (0207) pre-selected ASCs (CC, p1)

pre-selected ASCs (ML, p2)

Before seeding n/a 0.65% 7.80% 1.8%

At harvest (Quantum) 7.80% 14.5% 8.90% 4.05%

At harvest (Flask) 8.20% 17.3% 7.65% 4.15%

Adipogenic Differentiation Potential

Quantum

Osteogenic Differentiation Potential

Quantum

Chondrogenic Differentiation Potential

Courtesy of Prof. Gornati and Prof. Bernardini

DNA Damage/Repair, Apoptosis, Cell Cycle (RT2 Profiler PCR Arrays, Qiagen)

DNA Damage/Repair, Apoptosis, Cell Cycle

Log 10 (Normalized Expression Flask)

Lo

g 1

0 (

No

rma

lize

d E

xp

ress

ion

Qu

an

tum

)


Lo

g 1

0 (

No

rma

lize

d E

xp

ress

ion

Qu

an

tum

)

•  upregulated •  downregulated •  unchanged

DNA Damage/Repair, Apoptosis, Cell Cycle


Lo

g 1

0 (

No

rma

lize

d E

xp

ress

ion

Qu

an

tum

)


Lo

g 1

0 (

No

rma

lize

d E

xp

ress

ion

Qu

an

tum

)

•  upregulated •  downregulated •  unchanged

Conclusions and Outlook

•  ASCs can be expanded in the Quantum

•  Yield variability: donor and culture conditions

•  Bioprocess transition (flask to Quantum) needs optimization

•  The quality of ASCs expanded in the Quantum is comparable to flask-

expanded cells

•  Identity and purity: confirmed

•  Safety: need for further genomic stability testing, tumorigenicity

assay, sterility and endotoxin testing

•  Potency: “classical” differentiation confirmed, need for therapy-

oriented potency assays

Acknowledgments

SSCF

Alessandra Gobbetti

Lina Maciariello

Terumo BCT

Adrian Abbotts

Elise Roy, PhD

Brent Rice, PhD

Università degli Studi dell’Insubria

Prof. Rosalba Gornati, PhD

Prof. Giovanni Bernardini, PhD

Thank You for Your Attention!

Questions?

Documents

Expanding Adipose-Derived Mesenchymal - SSCF · 2016. 6. 15. · 6 8 PD PD Flask Mean 6.378 SEM 0.269 N 4 Quantum Mean 4.420 SEM 0.449 N 4 * * p = 0.0096 0 20 40 60 80 DT (hours)