SUPPLEMENTARY MATERIALS AND METHODS
Analysis of gene expression following tissue culture passage
Expression data for serum-free tissue culture passaged glioma cells was obtained from
the Lee Dataset1 available through Oncomine (Compendia Biosciences). Expression of
ROS-related genes was compared between human tumor specimens (n = 17), freshly
dissociated xenograft cells (n = 6), or cells that had been passed in serum-free culture
containing bFGF and EGF for 5 (n = 4), 8 (n = 3), 13 (n = 5), or 35 (n = 4) passages.
Expression data was obtained using Affymetrix HG-U133a arrays. Reporters shown are
GCLM 203925_at; GSS 201415_at; EPAS1 200878_at; HIF1A 200989_at; FOXO1
202724_s_at; FOXO4 205451_at.
ATP and ssDNA quantification
ATP was measured using CellTiter-Glo Luminescent Cell Viability Assay (Promega). 24
hours after plating acutely dissociated and CD133-MACS sorted GBM cells (6,000 cells
per well of a 96 well plate) in growth-factor free medium (Neurobasal A medium
supplemented with B27 minus vitamin A). Signal intensity was read on a luminometer
(Perkin-Elmer). An ATP standard curve was generated using ATP solutions ranging
from 1 µM to 10 nM with 100 µl of 1 µM ATP solution containing 10-10 moles ATP and
absorbance readings from experimental samples were fit into this curve to generate moles
ATP. Quantification of ssDNA was measured as described previously.2,
3
Briefly, for
ssDNA quantification: matched GICs and non-GICs from xenografted patient specimens
were grown on GelTrex (Gibco, Invitrogen)-coated cover slips and labeled with 10 µM
BrDU in growth factor free Neurobasal A medium supplemented with B27 for 24 hours.
Quantification of ssDNA by measuring mean intensity of BrdU foci staining
(incorporated BrdU detected under non-denaturing conditions with an antibody to BrdU;
BD Pharmingen; 1:300) was performed by The Olympus Scan^R Screening Station and
analyzed using Scan^R Analysis software (Olympus).
Alkaline comet assay
Single-cell gel electrophoresis under alkaline conditions was performed using
manufacturer’s instructions (Trevigen, Gaithersburg, MD). Briefly, GICs or non-GICs
were harvested into a single-cell suspension of 1.5 x 105 cells/ml in 1X PBS (Ca++ and
Mg++ free), mixed with LMAgarose and pipetted onto CometSlides (Trevigen,
Gaithersburg, MD). Cells were lysed overnight then run in alkaline electrophoresis
solution for 2 hours. DNA was stained using SYBR Green I (Molecular Probes, Eugene,
OR). Images were acquired by epifluorescence microscopy using a a Leica DMR upright
microscope (Heidelberg, Germany), a 10X objective, FITC fluorescence filter, and a
Retiga 2000R CCD digital camera (Q-Imaging, Burnaby, B.C., Canada). Image
acquisition was fully automated for up to 8 slides using an 8-slide, linearly-encoded X, Y,
Z-motorized stage (Prior Scientific, Rockland, MA) managed by Objective Imaging’s
Oasis 4i controller (Kansasville, MI), TurboScan software (Objective Imaging) and
Image-Pro 7.0 (Media Cybernetics, Silver Spring, MD).
During acquisition, high
magnification (auto-focused) image fields were acquired across the entire slide and
stitched together to form a single high resolution, large field-of-view (FOV) image 0.74
um/pixel). Each image field was background corrected prior to stitching to ensure
continuity and minimize chromatic variability. Quantitative comet analysis in each large
field-of-view image was subsequently performed in Image-Pro Plus 7.0 using fully
automated, customized algorithms. Briefly, s spectral filter was applied to each image to
enhance signal intensity followed by a fixed threshold to segment each comet. The
resultant binary mask was then multiplied with the original image to generate a new
image in which background signal around each comet was set to zero. Again in a fully
automated fashion, the mean directional angle for the comets was determined and the
entire image was rotated such that comets were oriented vertically (head to tail). Across
each comet a medial line was placed from head to tail (full length of segmented comet)
and a minima search for an intensity drop was performed across the length of the line to
determine head to tail separation. Once this separation point was found, the length of the
tail was calculated along with its mean intensity. Tail lengths and respective intensities
were exported to Excel for each comet analyzed. Statistical significance was calculated
with GraphPad Prism Software utilizing a Student’s t-test (GraphPad Software Inc.).
Representative images were generated using Adobe Photoshop (San Jose, CA).
Cell viability
To compare the sensitivity of BJ fibroblasts, GICs and non-GICs to PARP inhibition,
acutely dissociated and CD133-MACS sorted GBM cells or BJ fibroblasts (6,000 cells
per well of a 96 well plate, plated in triplicate) were exposed to olaparib (5 µM) in
growth-factor free medium (Neurobasal A medium supplemented with B27 minus
vitamin A) for GICs and non-GICs or in DMEM 10% FBS for BJs and viability was
measured at day 0 and days 1 and 3 post treatment using CellTiter-Glo Luminescent Cell
Viability Assay (Promega, Madison, WI). Results are reported as relative fold change in
ATP with each group internally normalized to the respective vehicle control. For cell
viability via trypan blue exclusion, 2 x 104 GICs were plated per well of a 6 well plate.
Immediately after irradiation (day 0) and on days 1, 3, 5 and 7, cells were harvested,
treated with TrypLE to achieve a single cell suspension and mixed for 2 minutes with
trypan blue (1:1 volume). Live (white) and dead (blue) cells were immediately counted
on a hemocytometer. For long term viability assays, 500 non-GICs per well were plated
in triplicate into 96-well plates containing appropriate growth media. The next day,
vehicle or drug was added to the wells and 2 hours later plates were irradiated. Day 0
readings of ATP levels (CellTiter-Glo Luminescent Cell Viability Assay, Promega) were
taken immediately after irradiation using a luminometer (Perkin-Elmer). ATP levels
were also taken on days 1, 3, 5, 7 and 10 and normalized within each treatment group to
Day 0 readings and reported as a relative fold change in total moles ATP over time.
Immunoblotting
EBC [50 mM Tris pH 8.0, 120 mM NaCl, 0.5 % NP-40, with protease inhibitors (SigmaAldrich) and a PARG inhibitor (Trevigen)] protein extracts from human GBM
xenografted specimens, fetal neural progenitor cells (fNPC; Lonza, Basel, Switzerland),
primary human astrocytes (HA; Clonetics, Walkersville, MD) and immortalized HA4
were separated by 4-12% Novex NuPAGE Bis-Tris Gel System (Invitrogen) and
transferred to PVDF (Millipore). The membranes were blocked with 5% (wt/vol) bovine
serum albumin (BSA) or dry milk in TBS-Tween-20 (0.1% vol/vol) and probed with
primary antibodies against PARP1 (BD Pharmingen; 1:200), Poly (ADP-Ribose) [PAR]
(BD Pharmingen; 1:1000), GFAP (DAKO; 1:10,000), Sox2 (R & D Systems; 1:500),
Olig2 (EMD Millipore; 1:1000) or the loading controls βactin (Sigma-Aldrich; 1:8,000)
or αTubulin (Sigma-Aldrich, 1:500). Secondary detection was accomplished using IRDye
800 and IRDye 680 detected on the Odyssey imaging system (Li-Cor) or by the ECL
detection system according to manufacturer’s instructions (GE Healthcare). For PARP
inhibitor studies, 1 x 106 GICs or non-GICs were plated per 10 cm dish. The next day the
cells were treated with DMSO, or 1, 5 or 10 M olaparib for 6 hours then lysates
generated and analyzed as above.
EdU pulse labeling and cell cycle analysis by FACS
For EdU pulse labeling, matched MACS sorted GICs and non-GICs from acutely
dissociated xenografts were left to attach on GelTrex-coated (Invitrogen) cover-slips
overnight in growth factor free Neurobasal A medium supplemented with B27. Prior to
fixation using 4% paraformaldehyde, cells were pulse-labeled with 10 dU
(Invitrogen) and processed according to manufacturer’s instructions. Quantification of
EdU-positive cells was performed by The Olympus Scan^R Screening Station and
analyzed using Scan^R Analysis software (Olympus).
For cell cycle analysis, acutely dissociated xenografts were MACS sorted within 3 hours
post-dissociation. Immediately after the MACS sort, matched GICs and non-GICs were
stained with PI- staining buffer (10 g/ml propidium iodide, 10 g/ml RNAse A, 0.5%
Triton X-100 in PBS) for 30 minutes at 37°C, spun down and resuspended in PBS.
Samples were acquired with Fortessa (BD Biosciences) and analyzed using FlowJo
software (Tree Star, Inc., Ashland, OR).
Sphere formation
CD133-positive GICs from 3691 and 08-387 xenografted patient specimens were Flow
sorted as described into 96 well plates at a final cell number of 1 cell per well.
Tumorsphere formation was evaluated 10 days after sorting and wells were scored
positive or negative for the presence of at least one tumorsphere.
Dose response curves
Acutely dissociated and CD133-MACS sorted GBM cells were plated at a density of
1,000 cells per well of a 96 well plate, plated in triplicate, in growth-factor free medium
(Neurobasal A medium supplemented with B27 minus vitamin A) for GICs and nonGICs. The next day, cells were exposed to olaparib at 2-fold concentrations ranging from
20 µM down to 0.08 µM diluted in in growth-factor free medium (Neurobasal A medium
supplemented with B27 minus vitamin A). Viability was measured 72 hours post
treatment using CellTiter-Glo Luminescent Cell Viability Assay (Promega, Madison,
WI). Dose response curves and EC50 values were generated using GraphPad Prism
Software (GraphPad Software Inc., San Diego, CA)
SUPPLEMENTARY TITLES AND LEGENDS TO FIGURES
Supplementary Figure 1. Gating strategy for flow cytometry analysis for (a) ROS-FITC
and (b) 8-oxoguanine-FITC from patient xenograft specimen 4121.
Supplementary Figure 2. Glioma cells differentially express ROS-associated genes
upon continual exposure to cell culture conditions.
Changes in transcript levels of the glutathione-related genes, GCLM and GSS, and the
ROS-associated genes, EPAS1, HIF1A, FOXO1 and FOXO4, were evaluated between
RNA isolated from surgical specimens or acutely isolated xenograft cells and the same
xenograft cells following extended tissue culture passage. Expression data was obtained
from the Lee Dataset1 available through Oncomine (Compendia Biosciences).
Supplementary Figure 3. GICs are more metabolically active as compared to nonGICs and contain higher levels of ssDNA.
(a) Moles ATP were measured from GICs (green bars) and non-GICs (black bars) from
4121, 4302, and T564 xenografted patient specimens. n = 3, error bars represent s.d.; NS
= no statistical significance; *, p < 0.05; **, p < 0.01. (b) ssDNA was quantified in
matched GICs (green bars) and non-GICs (black bars) from 4121, 4302 and 3691
xenografted patient specimens by measuring mean intensity of BrdU foci staining
(incorporated BrdU detected under non-denaturing conditions) using the ScanR screening
station. (c) Representative images of 08-387 GICs (top panels) and matched non-GICs
(bottom panels) following the alkaline comet assay. Scatter dot plot for comet tail length
(d) and comet tail DNA content (e) for GICs (green circles) and non-GICs (black
triangles) from 08-387 xenografted patient specimen. n = 391 cells for GICs and n = 396
cells for non-GICs, red line marks mean for each group; error bar represents s.d.; **,
p<0.01; ***, p < 0.001.
Supplementary Figure 4. Differential PARsylation levels and validation of sorting
efficiency for GICs.
(a) PARP levels and PARP-associated activity (PARsylation, PAR) were evaluated by
immunoblot analysis of matched GICs (+) and non-GICs (─) from 08-387 and 3359
xenografted patient specimens. (b) PARP levels and activity (PAR) were evaluated by
immunoblot analysis for matched GICs (+) and non-GICs (─) from 3691 xenografted
patient specimen, fetal neural progenitors cells (fNPC), cycling human astrocytes (HA)
and immortalized HAs (iHA). (c) GFAP (marker of differentiated cells), Sox2 (marker
of stem cells) and Olig2 (marker of stem cells) were used to check for purity of sorted
populations with βactin or αTubulin used as loading controls.
Supplementary Figure 5. Growth kinetics of GICs and non-GICs and increased
sensitivity of neoplastic cells to PARP inhibiton.
(a) EdU pulse labeling of matched MACS-sorted GICs and non-GICs from acutely
dissociated 4121 xenografted patient specimen shows no significant differences in the
fraction of actively proliferating cells.
(b) Representative FACS histograms plots
depicting the cell cycle profiles of matched MACS-sorted GICs and non-GICs (from
acutely dissociated 4121 xenografted patient specimen) exhibit no major differences in
cell cycle phase distribution. (c) Cell viability was measured using an ATP-based assay
on the indicated days for GICs (green line) and non-GICs (black line) from 4121
xenografted patient specimen and BJ fibroblasts (red line) in the presence of 5 M
olaparib (PARPi). n = 3, error bars represent s.d.; ns, no significance, ***, p < 0.001;
****, p < 0.0001 as compared to BJ fibroblasts.
Supplementary Figure 6. Sphere formation of GICs under PARP inhibition.
3691 (a) or 08-387 (b) GICs were plated at one cell per well in the presence of vehicle
(DMSO, black bars) or olaparib (PARPi) at 1 M (pink bars) or 10 M (red bars) and
evaluated for the presence of a tumorsphere 10 days later. n = 24, error bars represent
s.d.; **, p < 0.01; ****, p < 0.0001.
Supplementary Figure 7.
PARP inhibition.
Decreased PARsylation in GICs and non-GICs upon
(a) 08-387, 4121, and 3691 GICs and non-GICs were treated with vehicle (DMSO) or
olaparib (PARPi) at 1 M, 5 M or 10 M for 6 hours and then analyzed for PARPassociated activity (PARsylation, PAR) with αTubulin used as a loading control. (b)
Dose response curves were generated for 4121 GICs and non-GICs.
Supplementary Figure 8. PARP inhibition targets GIC growth.
GICs from 3691 xenografted patient specimen were treated with vehicle (DMSO, solid
black line; n = 3), 10 M olaparib (PARPi, solid red line; n = 3), vehicle plus irradiation
(DMSO plus 3 Gy, dashed black line; n = 3), or 10 M olaparib plus irradiation (PARPi
plus 3 Gy, dashed red line; n = 3). Cell growth was measured on the indicated days after
treatment using trypan blue exclusion. The data for each time point was normalized to
the Day 0 readings within each treatment group. Error bars represent s.d. **, p < 0.01;
***, p < 0.001 for DMSO no IR compared to all other treatments.
Supplementary Figure 9. Impact of PARP inhibition and radiotherapy on nonGICs.
(a) Cell viability was measured using an ATP-based assay on the indicated days for nonGICs from 3691 and 08-387 xenografted patient specimens treated with vehicle (DMSO,
black lines), 1 M olaparib (PARPi, pink lines) or 10 M olaparib (PARPi, red lines) and
irradiated with 3 Gray (3 Gy) of ionizing radiation. The data for each time point was
normalized to the Day 0 readings within each treatment group and reported as a relative
fold change in total moles ATP over time. n = 3, error bars represent s.d.; *, p < 0.05; **,
p < 0.01; ****, p <0.0001. (b) Apoptosis was measured 3 days after treatment using an
activated Caspase3/7 based assay for non-GICs from 3691 and 08-387 xenografted
patient specimens treated with vehicle (DMSO), 1 M olaparib (PARPi) or 10 M
olaparib and left unirradiated (black bars) or irradiated with 3 Gray (3 Gy) of ionizing
radiation (red bars). The data was normalized to the unirradiated DMSO-treated control.
n = 3, error bars represent s.d.; ns, no significance; **, p < 0.01. (c) Resolution of DNA
damage was monitored using immunostaining analysis for γH2AX (green; nuclei
counterstained with DAPI, blue) in 3691 non-GICs treated with vehicle (DMSO) or 10
M olaparib (PARPi) and left unirradiated (no IR) or treated with 3 Gray (3 Gy)
irradiation (IR) and fixed at the indicated timepoints. Scale bar equals 5 µm.
REFERENCES
1.
Lee J, Kotliarova S, Kotliarov Y, Li A, Su Q, Donin NM et al. Tumor stem cells
derived from glioblastomas cultured in bFGF and EGF more closely mirror the
phenotype and genotype of primary tumors than do serum-cultured cell lines.
Cancer Cell 2006; 9(5): 391-403.
2.
Bartkova J, Hamerlik P, Stockhausen MT, Ehrmann J, Hlobilkova A, Laursen H
et al. Replication stress and oxidative damage contribute to aberrant constitutive
activation of DNA damage signalling in human gliomas. Oncogene 2010; 29(36):
5095-102.
3.
Groth A, Corpet A, Cook AJ, Roche D, Bartek J, Lukas J et al. Regulation of
replication fork progression through histone supply and demand. Science 2007;
318(5858): 1928-31.
4.
Jeremy N Rich, Chuanhai Guo, Roger E McLendon, Darell D Bigner, Xiao-Fan
Wang, and Christopher M Counter. A Genetically Tractable Model of Human
Glioma Formation. Cancer Research 2001; 61: 3556-60.