Online Supplementary Material
Supplementary figure legends
Figure S1. Gating strategy for Side Population analysis (Related to Fig. 1-7)
A. The step by step gating strategy for SP analysis is shown for the intracranial T16 xenograft in
eGFP+ NOD/SCID mice. The resulting percentages of cell populations obtained are indicated for
each gate. The same strategy was used for all subsequent experiments to isolate single viable
cells, with exclusion of cell debris and erythrocytes. (1) Cells were distinguished from debris on
the flow cytometric profile based on the Forward Scatter (FSC) and Side Scatter (SSC). (2) Cell
doublets and aggregates were gated out based on their properties displayed on the SSC area
(SSC-A) versus height (SSC-H) dot plot. (3) Dead cells were recognized by their strong
positivity for the dead cell discrimination marker. (4) For cell suspensions from primary tissues
and tumors, erythrocytes were excluded by applying a ‘Hoechst’ gate on the ‘Hoechst
Red’/’Hoechst Blue’ dot plot in the linear scale. (5) In xenografts, human tumor cells were
recognized as the eGFP negative population compared to the eGFP positive mouse stromal host
cells. (6) Tumor (‘black’) and host (‘green’) populations displayed on the Hoechst dot plot show
that tumor cells can display different levels of ploidy. SP cells were recognized as a dim tail with
decreased Hoechst signal in the two ‘Hoechst’ channels (‘blue’). The appropriate SP gates were
adjusted for the tumor and host populations according to their ploidy and according to the
controls showing the strongest dye efflux inhibition. B. Gating tree.
Figure S2. Side Population analysis in different glioblastoma patient biopsies
(Related to Fig. 1A)
1
All Glioblastoma patient biopsies displayed a well-defined SP. Efflux properties were confirmed
by inhibition controls (250µM Verapamil + 10µM FTC).
Figure S3. Side Population analysis in patient biopsy-derived xenografts (Related to
Fig. 1E)
All patient derived xenografts in eGFP+ NOD/SCID mice (‘grey’) contained a well-defined SP
(n = 3). Discrimination between host stromal (‘green’) and tumor (‘black’) compartment
revealed SP uniquely in the stromal compartment of the xenograft (‘blue’), confirmed by
inhibition controls.
Figure S4. Flow cytometric sorting controls of glioblastoma xenograft and normal
brain populations (Related to Fig. 2C-D, Fig. 4C-E and Fig. 5A)
A. T16 xenografts (n = 8) were used for the SP assay followed by FACS analysis. Since T16
tumor cells display amplification of the EGFR gene (Table S1), these can be easily recognized
by EGFR staining. Human-specific EGFR staining was therefore added to eGFP discrimination
to increase the number of events and the purity of the gates used for sorting. Tumor cells were
characterized as eGFP-EGFR+ main population (MP) events (‘Tumor MP’), whereas stromal host
cells were divided into eGFP+EGFR- SP (‘Stromal SP’) and MP (‘Stromal MP’). B. Sorted
populations were reanalyzed directly after each sorting experiment. The purity of populations
with regard to EGFR/eGFP expression was > 98%. C. SP analysis after sorting showed that
eGFP+EGFR- SP events were >98% pure. eGFP+EGFR- MP events appeared with a slightly
decreased ‘Hoechst Red’ signal, due to additional washing and instability of the Hoechst staining
in this channel. Nevertheless, 99% of events were outside the SP gate. All eGFP -EGFR+ sorted
2
cells were aneuploid and 93-99% of events were present in the Tumor MP gate. Graphs show
representative examples of sorted populations (n = 8). Sorted Stromal SP and MP and Tumor MP
were used for functional assays and gene expression analysis. Any events detected in the Tumor
SP gate during prolonged experiments were sorted, however the number of events was extremely
low (<100 events from 3-5 xenografts) and after reanalysis, the sorted cells were mostly present
outside the SP gate, with ‘dead’ cell-like properties (not shown). D. Normal brain sorting. Single
cell suspension of normal brain was sorted as SP (‘Brain SP’) and MP (‘Brain MP’) fraction. E.
Sorted Brain SP was >94% pure. Similarly to the eGFP+EGFR- Stromal MP, Brain MP appeared
with a decreased ‘Hoechst Red’ signal during reanalysis. Sorted cells were used for functional
assays and gene expression analysis.
Figure S5. Side Population analysis in spheroid and stem-like cell line derived
xenografts (Related to Fig. 2)
A.
Related to Fig. 2A.
All respective patient derived xenografts contained SP (‘blue’)
exclusively in the stromal compartment (‘green’). Tumor cells (‘black’) were deprived of SP,
regardless of tumor cell ploidy (T16 displayed diploid and aneuploid tumor cells, P3 and P8 were
purely diploid tumors (n = 3)). B. CD133 and CD15 expression of tumor cells in patient derived
xenografts. CD133+ and CD15+ cells are present at varying levels in the tumor population of
respective xenografts (‘black’) and the expression level strongly varies between tumors.
Expression levels are displayed compared to negative controls (‘grey dotted’). C. SP profiles of
tumor and stromal cells in T16 xenografts were unchanged upon TMZ treatment of the mice. D.
Related to Fig. 2B. CD133 and CD15 expression in NCH glioblastoma stem-like cell lines.
Expression levels (‘grey’) are displayed compared to negative controls (‘grey dotted’). E.
3
NCH421k cell line did not possess efflux properties in vitro (n = 5). Tumor/host discrimination
in the NCH421k xenograft in eGFP+ NOD/SCID mice revealed that the SP (‘blue’) is
exclusively present in the stromal compartment (‘green’). NCH421k cells (‘black’) were
aneuploid and the SP tumor gate was adjusted accordingly (n = 3).
Figure S6. Side Population phenotyping in glioblastoma patient biopsies (Related to
Fig. 3)
A. CD31/CD105 phenotyping. CD31+ SP cells co-expressed CD105 in patient biopsies,
indicating their endothelial nature. A low number of tumor cells that were either CD31+ or
CD105+ were detected in the respective xenograft. However the level of expression of CD31 was
10-100 times lower compared to endothelial cells in patient biopsies and these cells were never
CD31/CD105 double positive. B. EGFR/A2B5 phenotyping. All SP events, including A2B5+SP
were EGFR-. C. CD45/CD31 phenotyping. SP events were enriched in CD31+ cells, no CD45+
hematopoietic SP events were observed. The respective xenografts contained <0.1% of CD31+
and CD45+ tumor cells, at a background detection level.
Figure S7. Multicolor Side Population phenotyping in stromal compartment of the
xenograft (Related to Fig. 4 and Fig. 5A)
A. Related to Fig 4. CD105/CD44 phenotyping. SP was enriched in CD105+CD44- cells,
whereas CD105+CD44+ cells were only in MP. Less than 0.3% SP was CD105-CD44+. B.
CD90/CD44 phenotyping. SP was enriched in CD90+CD44- cells, whereas CD90+CD44+ cells
were only in MP. Less than 0.1% SP was CD90-CD44+. The CD90 expression level detected by
flow cytometry was not strong enough for accurate discrimination and was therefore not
4
included in our calculations C. CD15/CD133 phenotyping. CD15+CD133+ and CD15+CD133NSC/NPC-like cells were only in MP, whereas SP was enriched in CD15-CD133+ cells,
confirming their EC origin. D. A2B5+ cells in the
mouse brain can be detected in close
proximity to CD31+ endothelial cells reminiscent of perivascular astrocytes. The arrow points at
a putative ‘end-feet’-like structure. E. Gene expression profile of Nestin and Vimentin in sorted
SP and MP populations of stromal compartment of the xenograft and in normal brain further
confirmed the endothelial nature of the SP. Both Nestin and Vimentin could not be used as
unique NSC/NPC markers as they are expressed by a number of other cell types in the brain,
including endothelial cells (see Table S2). F. Related to Fig. 5A. Gene expression analysis of the
ABC transporter family members. ABCBC1, ABCC2, ABCC3 and ABCC5 transporters were not
enriched in the SP, indicating a lack of direct involvement of these transporters in the dye efflux
properties in the brain and gliomas.
5
Supplementary tables
Table S1. Clinical patient data and chromosomal aberrations of corresponding
human glioblastoma biopsies
Modifications in genome structure as identified by aCGH are shown for each patient tumor and
glioblastoma stem-like cell line. [++ = amplification (Log2 Ratio>2), + = gain (Log2 Ratio
>0.35), - = loss (Log2 Ratio < -0.35), -- = deletion (Log2 Ratio < -1)]. The last column
indicates the experiment for which the patient biopsies were used. For xenografts the mean time
to sacrifice (days +/- SEM) and the number of mice (n) are indicated.
Patient
Chromosomal aberrations
Patient
Patient
age
sex
biopsy
T16
++[EGFR , MDM2], +7q, - [Chr6q, Chr10, Chr11, 13q12-
52
F
q32.2], --CDKN2A/B
T101
++[EGFR, MDM2] +Chr7, -[3q, Chr4, Chr10, Chr11,
++EGFR, +Chr7, -10q, --CDKN2A/B
Xenograft (74 +/- 2 ;
n = 16)
60
M
Chr15], --CDKN2A/B
T185
Experiment
Xenograft (91 +/ 0.4 ;
n = 10)
76
F
Xenograft (142 +/0.5; n = 6)
T233
++EGFR, 2q34 +1q21.2-24.2, Chr7, Chr19, Chr20,
43
F
-9p21.3 -21.1, Chr10, --CDKN2A/B
T238
+Chr7, -[6q, 9p-p21.1,Chr10, Chr13]
Xenograft (129 +/10; n = 6)
41
M
Xenograft (139 +/- 1;
n = 3)
T239
+[Chr7, Chr19], -[1p-p35.3, 9p24.2-p23, 9p21.3-p21.1], --
79
M
CDKN2A/B
T251
++EGFR, 2q34, +1q21.2-24.2, Chr7, Chr19, Chr20,
n = 6)
43
F
-9p21.3 -21.1, Chr10, --CDKN2A/B
T316
-[Chr6, 9p, Chr10, 11p, Chr13, Chr14, Chr18, 22q12.3-
Xenograft (140 +/- 6;
Xenograft (103 +/7.5; n = 7)
51
M
FISH analysis
70
M
FISH analysis
84
M
FISH analysis
qter]
T330
++EGFR, +Chr7, -[Chr6, 9p, Chr10, Chr14, 16q, 18p], -CDKN2AB
T331
++EGFR, +[Chr1, Chr7, Chr20],
-[9p, Chr10, Chr22], --PTEN
6
T341
++PDGFRA, 7p21.1, EGFR, 7q21.1-22.2, 17p12, 1Chr7,
75
F
FISH analysis
64
M
Xenograft (37 +/- 4;
Chr16, Chr19, -Chr10, --CDKN2A/B
P3
+ [Chr 7, Chr19, 20q], -[1q42-q43, Chr9, Chr10, 20p]
--[PIK3R , CDKN2A/B]
P8
++EGFR, +[5q31-q35, Chr7, 8q24], -[6q22-q24, Chr10,
n = 8)
64
F
13q13.3-q33.3, 18q21.2-q22.4], --CDKN2A/B
Xenograft (64.5 +/0.5; n = 8)
Cell Line
NCH421k
++[PDGFRA, MYC, CDK4], +[1p31.1-q43, 5q1-q22.2,
N/A
M
16p], -[2q, 3p-q13.31, 8p, 9p, Chr10, 13q]
NCH644
++MYC, +[5q34-qter, EGFR, 8p, 8q-8q22.3, 20q11.23-qter,
Chr21, Chr22], -[5q32.2-q34, 12q24.12-q24.32, 13q-q31.1,
Xenograft (71 +/0.8; n = 21)
N/A
F
Xenograft (31.5 +/1; n = 14)
18q, Chr19]
7
Table S2. List of lineage-specific markers used in the study
NSC: neural stem cells, NPC: neural progenitor cells, EC: endothelial cells, EPC: endothelial
progenitor cells, HSC: hematopoietic stem cells; MSC: mesenchymal stem cell
Protein
A2B5
Full/alternative name
Lineage specificity in normal brain
c-series gangliosides,
Neural and glial precursors, late oligodendrocyte precursors,
immature astrocytes,
Aif1
Allograft inflammatory factor 1, IBA1,
Ionized
calcium
binding
microglia, macrophages
adaptor
molecule 1
CD11c
Integrin alfa X, p150/90
microglia, macrophages/monocytes, myeloid cells, granulocytes
CD15
sialyl Lewis X, (LeX ), Stage-Specific
NSCs, NPCs, neurons
Embryonic Antigen-1 (SSEA-1)
CD31
CD44
CD45
Platelet
endothelial
cell
adhesion
ECs,
lymphocytes,
platelets,
macrophages,
T/NK
cells,
molecule-1 (PECAM1)
granulocytes, neutrophils
Heparan sulfate proteoglycan receptor,
glial precursors and glial cells, microglia/macrophages, MSCs,
Pgp-1
hematopoietic cells
Protein tyrosine phosphatase, receptor
macrophages, hematopoietic cells
type, C (PTPRC)
CD90
Thy-1 cell surface antigen
ECs, neurons, MSCs, fibroblasts
CD133
Prominin-1 (PROM1)
NSCs, NPCs, ECs, EPCs, HSCs
CD105
Endoglin
ECs, mesenchymal cells, MSCs, fibroblasts
Desmin
GFAP
pericytes, MSC, fibroblasts, smooth muscle cells
Glial fibrillary acidic protein
NSCs, NPCs, astrocytes
Nestin
NG2
Olig2
NSCs, NPCs , pericytes, ECs
Neuron-Glial
2
chondroitin
sulfate
pericytes, macrophages , glial progenitor cells, oligodendrocyte
proteoglycan
precursors,
Oligodendrocyte transcription factor 2
motor neurons, oligodendrocyte progenitors
Vimentin
NSCs, NPCs, ECs, pericytes, microglia, fibroblasts, smooth
muscle cells
vWF
von Willebrand factor, VWF
ECs
8
Table S3. List of antibodies used in the study
Epitope
Conjugate
Species reactivity
Clone
Supplier
Concentration
used/test*
A2B5
APC/PE
human, mouse
105-HB29
Miltenyi
10µl/test
ABCB1
PE
human
CD243 UIC-2
Chemicon
1µl/test
ABCG2
APC
human
CD338 5D3
Biolegend
20 µl/test
CD11c
APC
mouse
N418
eBioscience
1.2µl/test
CD11c
PerCP
mouse
N418
Biolegend
2.5µl/test
CD15/SSEA-1
Alexa Fluor 647
human, mouse
MC-480
Biolegend
5µl/test
CD15/SSEA-1
PE
human
MEM-158
Immunotools
10µl/test
CD31
Dy590 (PE-TR)
human
MEM-05
Immunotools
10µl/test
CD31
APC
mouse
MEC 13.3
BD Bioscience
5µl/test
CD31
APC/PE-Cy7
mouse
390
eBioscience
2.5µl/test
CD44
PE-Cy7
human, mouse
IM7
eBioscience
1.2µl/test
CD45
PE
human
MEM-28
Immunotools
10µl/test
CD90
APC
human
5E 10
BD Bioscience
5µl/test
CD90
PE/APC
mouse
G7
Beckman Coulter
2µl/test
CD133
PE /APC
human
293C3/AC133
Miltenyi
10µl/test
CD133
PE/APC
mouse
13A4
eBioscience
5µl/test
CD105
PE
mouse
MJ7/18
eBioscience
2.5µl/test
CD105
APC
human
MEM-226
Immunotools
10µl/test
EGFR
PE
human
EGFR.1
BD Bioscience
20µl/test
NG2
PE
human, mouse
LHM-2
R&D
10µl/test
*Flow cytometry test: 106 cells/100µl
9
Table S4. List of mouse-specific primer sequences used in the study
To avoid false positive signals originating from DNA contamination all PCR primers were
mouse-specific and designed with known amplicon size, and where possible flanking a region
that contains at least one intron.
Target
Primer F
Primer R
ABCB1A
CAAAAGGAAGCTGGAGGTACA
CCACATGACCAAGACAGGAA
ABCB1B
CTGAGGCCGCTGCTTCCATCTT
CGTGCCACCTCCGGGTTTCCTT
ABCC1
CAAAAAGGTGGCGAGCAG
GCCCCAGTGTTACTGGTCA
ABCC2
GATGGCCAAGGAAGCCGGCATT
GCCAACCTGAGCAACAGCAACAAAC
ABCC3
GGAGGCCGCAGAGGGTGAGA
TGGCTGGCTGCTCACGAACG
ABCC4
CGGTGCACACCGAGGTGAAACC
CACCAGAAGAACACGCGCGAG
ABCC5
GCAAGAGCCCTGCTGCGTCA
CTGTGTGCAGGCGATGGGCA
ABCG2
AAATCCGCAGGGTTGTTGTA
GCCTTGGAGTACTTTGCATCA
ACTIN
TCTTGGGTATGGAATCCTGTG
CGGATGTCAACGTCACACTT
AIF1
GGACTGCTGAAGGCCCAGCA
TCCTCGGAGCCACTGGACACC
DESMIN
CAGCCCCGAGCAAAGGGGTTC
TGACAACCTCTCCATCCCGGGT
GAPDH
GAAGACACCAGTAGACTCCACGACA
ATGTTCCAGTATGACTCCACTCAC
GFAP
TGGAGGGCGAAGAAAACCGCATCAC
TTGGCCTTCCCCTTCTTTGGTGC
NESTIN
GCCAGAACCCCCACCTTGGC
AGGGAAGTGGTCCGGCTGCT
OLIG2
AGGTTCTCCTCCGCAGCGAGC
GTTCTGGGGACGATGGGCGAC
VIMENTIN
AACAACGATGCCCTGCGCCA
GCTCCAGGGACTCGTTAGTGCCT
VWF
CACTCCAGGCGCGATGCTGT
TGATGCTGTGGAACCGCGCT
10
Supplementary material and methods
Flow Cytometer settings for SP analysis
The FACS AriaTM SORP cytometer (BD Biosciences), fitted with a 632nm (30mW) red laser, a
355 (60mW) UV laser, a 405nm (50mW) violet laser and a 488nm (100mW) blue laser was
used. The Hoechst dye was excited by the UV laser and fluorescence was collected in two
channels: ‘Hoechst Blue’ 450/50 band-pass (BP) filter and ‘Hoechst Red’ 660/40 long-pass (LP)
filter. A LP635nm dichroic mirror was used to split the emission wavelengths. The flow
cytometer was stabilised for at least 1h before laser alignment and data acquisition. The
Coefficient of Variation of the instrument (%CV) was routinely examined before each
experiment. Routinely a 100µm nozzle and window extension (WE) 5 were used for data
acquisition and sorting. Cell acquisition and sorting were performed at 4°C at a low fluidic
sample speed. Data acquisition and analysis were done with DIVA software (BD Bioscience).
To preserve the Hoechst profile and cell viability, all sorting experiments were performed
directly after staining and under cold conditions. Although an influence of Hoechst toxicity on
cell survival was observed compared to control sorting using only phenotyping markers, there
was no difference in viability within Hoechst stained populations (not shown).
Hoechst concentration curves with efflux inhibitors were performed in normal brain and
xenograft host (not shown). The inhibition was strongest by simultaneously applying Verapamil
and FTC at a concentration of 10µM and 250µM respectively. Importantly, as the tumor tissue
contains both human and mouse cells, dye efflux behavior was tested after different Hoechst
incubation times, as suggested for different species (Petriz, 2007). Nevertheless, no difference in
the Hoechst staining pattern was detected between 90 and 120min of Hoechst incubation.
11
Immunohistochemistry
Hematoxylin and eosin (H&E) staining and EGFR immunohistochemistry (human-specific antiEGFR antibody; clone E30; DAKO) were performed on formalin-fixed paraffin-embedded
sections (7-10 µm) with standard procedures (Envision kit K4011/K4007, Dako). Direct eGFP
fluorescence was observed on paraformaldehyde-fixed cryostat sections. Immunostaining for
mouse endothelial cells was carried out on fresh-frozen acetone/chloroform-fixed sections with a
rat anti-mouse CD31 antibody (CBL1337, Chemicon), visualized with an anti-rat Alexa Fluor
555 secondary antibody (Invitrogen). A2B5+ astrocytes were detected with a preconjugated anti
human/mouse A2B5-Alexa Fluor 488 antibody (MAB312RX, Chemicon). Sections were
counterstained with 4’,6’-diamidino-2-phenylindole (DAPI). Fluorescent and brightfield images
were obtained using a Leica DMI 6000B microscope and the LAS software (Leica
Microsystems). Vessel number was calculated based on the mouse CD31 staining using ImageJ
software. Vessel counts were computed as a percentage of vessels in treated animals versus
controls.
Array comparative genomic hybridization (aCGH)
Each tumor biopsy was analyzed for chromosomal aberrations using a human-specific aCGH.
Genomic DNA was extracted using the DNAeasy Blood and Tissue Kit (Qiagen). DNA was
fragmented (200-500bp) by DNAse1 (rDNAse1, Ambion) and labelled with the BioPrime aCGH
Genomic labeling Kit (Invitrogen) and Cy3 and Cy5 dyes (GE Healthcare) following standard
protocols for Agilent aCGH. Female DNA pool (Promega) was used as a reference. Labelled
DNA was hybridized to SurePrint G3 Human 2x400k CGH microarrays (Agilent Technologies).
The slides were scanned at 3μm resolution (Agilent High-Resolution Microarray scanner), the
12
image data was extracted using Feature Extraction (Agilent Technologies) and analysed with the
Genomic Workbench software (Agilent Technologies). Aberrations were called using the ADM2
algorithm with a threshold setting of 25, centralization ‘on’ with threshold of 25 and an
aberration filter with a minimal number of probes=5 and a minimal AvgAbsLogRatio=0.45.
Supplementary references
Petriz, J. (2007). Flow cytometry of the side population (SP). Curr Protoc Cytom Chapter 9,
Unit9 23.
13