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Supplementary Materials and Methods
Reagents
AG490 was purchased from Sigma-Aldrich (St. Louis, USA), LOX-1 from Scivax
(Tokyo, Japan), Rhodamine-Phalloidin and DAPI from Invitrogen, STAT, p-STAT,
p-ERK and ERK antibodies from Cell Signaling Technology (Danvers, USA), CD44,
EpCAM antibodies from Abcam (Cambridge, UK), GAPDH, EGFR, E-Cadherin,
HSP70 and HIF1-antibodies from Santa Cruz (Dallas, USA).
Immuno-blotting
Spheroids were cultured in a Lipidure-coat 12 well plate (NOF, Tokyo, Japan) and
harvested on the indicated days. Spheroids were disrupted into single cells by
sonication and then lysed on ice with M-PER (Pierce, Rockford, USA) that contained
a protease inhibitor cocktail (Calbiochem, San Diego, USA) for 30 min. After
centrifugation, the protein concentration was determined by Bradford assay (Bio-Rad,
Hercules, USA). Equal amount of proteins was loaded to SDS-PAGE and transferred
to PVDF membrane for immune-blotting with specific antibodies.
Immunofluorescence on frozen sections
Spheroid were washed with PBS and fixed in 4% formalin (Sigma-Aldrich, St. Louis,
USA) for 2 h. After fixation, spheroids were embedded in optimal cutting temperature
(OCT, Sakura Finetek, Torrance, USA) compound and then frozen by using liquid
nitrogen. Frozen sections (10 m) were attached to the slides for immunofluorescence
staining. The sections were blocked with CAS blocker (Invitrogen, Carlsbad, USA),
and incubated with Rhodamine-Phalloidin (Invitrogen, Carlsbad, USA) for 2 h. DAPI
was used to stain nucleic acid. The sections were mounted and analyzed by confocal
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microscopy (Nikon A1, Tokyo, Japan). The observations were based on examination
of 3 sections and each experiment was repeated 3 times.
qRT-PCR assay
Spheroids were harvested and washed with PBS. The RNA of the spheroids was
extracted by using RNeasy mini kit (QIAGEN, Valencia, USA). cDNA was
synthesized using maxima first strand cDNA synthesis kit (ThermoScientific,
Lafayette, USA) according to the manufacturer’s instruction. Using specific primers,
HIF-1; 5’-GAA AGC GCA CTT CAA AG-3’ (forward), 5’-TGG GTA GGA GAT
GGA GAT GC-3’ (reverse), VEGF; 5’-TTC ATG GAT GTC TAT CAG CGC A-3’
(forward), 5’-CCG CAT AAT CTG CAT GGT GA-3’ (reverse), GAPDH; 5’-AAG
GTG AAG GTC GGA GTC AA-3’ (forward), 5’-GGG GTC ATT GAT GGC AAC
AA-3’, qRT-PCR was performed with Maxima SYBR Green/ROX qPCR master mix
(ThermoScientific, Lafayette, USA) on Thermal Cycler DiceTM Real Time system
(Takara, Shiga, Japan) according to the manufacturer’s instruction. The relative gene
expression levels were determined after normalizing with GAPDH.
Cytotoxicity and Cell viability assay
Cells (2,000 cells/well) were seeded and cultivated for 4 days in a Lipidure-coat 96
well plate. The spheroids were treated with DMSO-dissolved four anti-tumor drugs
(5-FU (99%, Sigma-Aldrich, St. Louis, USA), SN-38 (97%, Sigma-Aldrich, St. Louis,
USA), sorafenib (99%, Selleckchem, Houston, USA), 17-AAG (99%, Selleckchem,
Houston, USA)). After 3 days of incubation, spheroid and media were harvested and
the lactate deghydrogenase (LDH) activity was determined to check cell viability and
cytotoxicity. The LDH activity was measured using LDH-cytotoxicity assay kit
(BioVision, Milpitas, USA), following the manufacturer’s instruction. To determine
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cell viability of 2D cultured cells, the cell lysates were extracted from drug-treated
cells and the LDH activity was measured as above.
Selection of molecular signatures contributing to the separation of the four
spheroid types.
Two-staged partial least squares (PLS) analysis was used to select the molecular
signatures. First, multiple partial least squares-discriminant analysis (MPLS-DA) was
performed to identify molecular signatures that contribute to the discrimination of the
four spheroid morphology types as previously demonstrated (1). For the analysis,
gene expression, copy number variation (CNV) and mutation data of 70 cancer cells
were obtained from cancer cell line encyclopedia (CCLE) database. Genes, showing
significant variation (i.e. coefficient of variation larger than 1 in the 70 cancer cells) in
the levels of mRNA expression (18,926 genes), CNV (20,073 genes) and mutation
(1,369 genes) were selected among these data. For these genes, the three X-block data
matrices were generated in the 70 cancer cells (70  18,926 X1-block containing
mRNA expression data, 70  20,073 X3-block containing CNV data, and 70  1,369
X2-block containing mutation data). Then, 70  3 Y-block data matrix containing the
subtypes of the 70 cancer cells (i.e. [1 0 0] for R type, [0 1 0] for M type, [0 0 1] for A
type, and [0 0 0] for N type) was generated. Each of the four data matrices was autoscaled for each column (mRNA expression, CNV, and mutation, in X1-3 blocks and
subtypes in Y-block) to have zero mean and unit standard deviation in the data matrix.
MPLS-DA was applied to the auto-scaled X1-3 and Y blocks (2). After the MPLSDA application, the five PLS latent variables (LVs) were selected and then 2,202
genes, which significantly contribute to the separation of the four spheroid types with
P value of the variable importance in projection (VIP) < 0.05, were identified (1).
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CNV, mutation, and mRNA expression in individual X-blocks were randomly
permuted to compute P values of VIPs and then MPLS-DA was applied to the
permuted data matrices. VIPs were computed in each X-block, and an empirical
distribution of VIPs in each X-block was identified. Finally, for each gene in an Xblock, P value for the VIP of the gene in the X-block was computed by performing a
right-sided statistical test using the empirical distribution of the VIP in the X-block.
Second, a second PLS-DA (3) was applied to the 2,202 genes to further select the
genes whose levels of mRNAs, CNVs, and mutations are predominantly high or low
in individual types of spheroids. For each type of spheroids, PLS-DA was separately
performed for X1-Y, X2-Y, and X3-Y block matrices in which the 70  1 Y-block
matrix contains one when the cancer cell generated the corresponding type of
spheroids. Among the 2,202 genes above, 560 subtype specific genes, which have Pvalues of their VIPs  0.1 for mRNA expression, 0.05 for CNV, and 0.1 for mutation,
was finally identified. The same random permutation of the data matrices was done
for the computation of P values of the VIPs. The P values cutoff values were
determined after manually evaluating the differential expression of mRNA, CNVs,
and mutation levels. We performed PLS-DA using Matlab software (version
7.12.0(R2011a), Math Works Inc., Natick, USA) including the PLS toolbox
(Eigenvector).
Computation of misclassification error rates in the prediction using the MPLSDA model.
Using the selected 560 subtype-specific genes, the prediction performance of MPLSDA model was evaluated by calculating the accuracy and misclassification error rates
from leave-one-out-cross-validations (LOOCVs). To evaluate the accuracy of the
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model, MPLS-DA model was built using the whole data sets (the 70 cancer cells) and
the classes of the 70 cancer cells were predicted by using the model. Then the
accuracy was calculated as the number of the cells correctly classified divided by the
total number of the cells used (i.e. 70). Independently, LOOCVs were performed by
building the MPLS-DA model using the data sets of the 69 cell lines as a training set
and predict the class of the data for the left-out one cell line using the model. This
procedure was repeated until every cell of the 70 cells was used as a test set at least at
once. Misclassification error rate was obtained by the number of the misclassified
cells divided by the total number of the cells.
Reconstruction of a network model describing cellular processes and pathways
associated with the A type spheroid.
To reconstruct a network model, the identified sub-networks were collectively
represented by mRNA, CNV, and mutation data of 2,202 genes selected from the twostaged PLS-DA analysis described above using HotNet algorithm (4). For this HotNet
analysis, the P values of the VIPs were computed using mRNA, CNV, and mutation
data for the 2,202 genes using Stouffer’s method and combined (5). -2log(combined P
values) was used as a heat value for the 2,202 genes. Using the heat values and the
PPI interactome (Human Proteome Reference Database (6)) as the input, the HotNet
algorithm was used to identify tightly linked sub-networks following the parameters;
t=0.1, delta=0.022, number of permutation = 1000. Among the resulting sub-networks,
52 sub-networks, whose size>=3 and P value < 0.027, were selected and 25 subnetworks were further narrowed. Each sub-network should include at least one R
type-specific gene. A network model was reconstructed with a total of 212 genes in
25 sub-networks by combining them. The nodes were linked using PPIs with
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experimental evidence in the three PPI database (HitPredict (7), String (8), and
MetaCoreTM (ver6.7) (9)). Among the 212 genes, 138 were finally included in the
final network model. Of the 138 nodes, 49 belonged to the 186 R type-specific genes.
Also, the 138 nodes include 50 previously reported drug targets, according to the NCI
chemical-gene Index. The 138 nodes were arranged so that those with the same
GOBPs or KEGG pathways were grouped into the same modules. For the detailed
sub-networks, the whole network was divided into the three sub-networks that
describe the major cellular processes, including JAK-STAT signaling pathway cell, Tcell signaling mediated defense response, and DNA replication.
Measurement of drug concentration in spheroids
Drug concentrations were determined by a LC-MS/MS using an API 2000 triple
quadrupole mass spectrometer with an electrospray ionization (ESI) source (AB MDS
Sciex, Concord, USA) coupled to Alliance 2690 HPLC system (Waters, Watford,
UK). To measure drug concentration in the spheroids, the cultured spheroid and
media were put into acetonitrile (Sigma-Aldrich, St. Louis, USA) containing 200
ng/ml of nonivamide (Sigma-Aldrich, St. Lousi, USA) and the mixture was vortexed
for disintegration and deproteinization of the spheroids. Then, the mixture was
injected into the HPLC system. For internal standard, 70:30 v/v mixture with 0.1%
formic acid and nonivamide was used. To calculate the drug concentration in
spheroids, drug standard calibration curves were constructed in the range of 25–1000
nM. The peak area of sample was compared with the calibration curve and drug
concentration was determined.
Bimolecular fluorescence complementation (BiFC)
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FKBP12 and FRB fragment, encoding the human mTOR FRB (2015-2114) domain,
were cloned into BiFC-VN173 (Flag tag) and VC155 (HA tag), respectively. These
plasmids were co-transfected into 2D-cultured 293T. After 12 h incubation, 5,000
cells in the culture overexpressing fusion-proteins were transferred to 3D culture
plates for induction of spheroid formation. To monitor the BiFC signal of FKBP12FRB interaction, spheroid was pre-incubated with or without 150 M AG490 (98%,
Sigma-Aldrich, St. Louis, USA) for 3 days, and then treated with 1 M rapamycin
(95%, Invivogen, San Diego, USA), which induces FKBP12-FRB interaction, for 24
h. BiFC signal was measured by fluorescence microscopy EMCCD (Nikon C1, Tokyo,
Japan).
Mouse xenograft model
The mouse xenograft experiments were performed in accordance with the University
Animal Care and Use Committee guidelines of Seoul National University. H1650
cells (5 x 106) were subcutaneously injected into the flank of 8-week-old BALB/c
nude mice. Tumor growth was monitored by measuring tumor volume (mm3) that was
calculated as length x width2 x 0.5. The drug treatment was initiated when the tumor
volume reached the range of 90-100 mm3. Each group of mice (n=6) was treated with
saline (control), 5-FU (10 mg/kg/day) or AG490 (5 mg/kg/day) alone and both once a
day for 5 days by intraperitoneal injection. On the final day, tumors were isolated and
their weights were measured.
TUNEL assay
After sacrificing mice, xenografted tumors were isolated, embedded in the optimal
cutting temperature (OCT) compound, and immediately frozen by liquid nitrogen.
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The frozen tissues were sectioned in 10 m thickness by cryostat microtome (Thermo
Scientific, Walldorf, German), fixed and permeabilized. Apoptosis was determined by
DeadEnd Fluoremetric TUNEL system (Promega, Madison, USA) following the
manufacturer’s instruction and the images were monitored by confocal microscopy
(Nikon A1, Tokyo, Japan).
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