Download Supplementary Materials (doc 54K)

Supplementary Material and References
Histology
Tissue sections from necropsies were fixed in neutral buffered formalin and paraffin sections
stained with hematoxylin and eosin (H&E, Thermo-Scientific, Waltham, MA). Cytospin
preparations of peripheral blood, spleen, and bone marrow were stained with the Hema 3 Stain
Set (Fisher Scientific, Pittsburgh, PA).
Flow cytometry
Primary ALL cells and cells from immunodeficient mouse (‘xenografts’) blood, spleen
(‘splenocytes’), and marrow were analyzed with a FACSCalibur or LSRII flow cytometer (both
from BD Biosciences, Franklin Lakes, NJ) after staining with the following monoclonal
antibodies (Mabs): CD10 APC, CD19 FITC, CD22 PE, CD34 APC, CD34 FITC, CD45 APC,
CD45 PE-Cy5, CD45 PE-Cy7 mouse CD45 FITC, mouse CD45 APC, CD33 PE, CD33 FITC,
CD13 FITC, CD13 PE (all from BD Pharmingen, San Diego, CA) except CD13 FITC (Dako
Cytomation, Copenhagen, Denmark).
Immunoglobulin heavy chain (IgH) gene rearrangements
DNA was extracted from unsorted primary samples or splenocytes from transplanted mice
(xenografts) using the QiaAMP DNA Mini kit (Qiagen, Valencia, CA), for ALL cases#1-5. DNA
aliquots were subjected to PCR using primers for the Ig heavy chain gene VDJ region [FR3a, 5'ACACGGC(C/T)(G/C)TGTATTACTGTG-3'; VLJH, 5'TGACCAGGGT(A/G/C/T)CCTTGGCCCCAG -3'] for 35 cycles. IgH rearrangement was not
detected for ALL case#3 using these primers, but was detected using Tube C from the
InVivoScribe Technologies (San Diego, CA) kit. IgH Gene Clonality Assay kits were used
according to manufacturers’ directions. 1 primer was fluorochorome-labeled in each PCR
reaction. Distilled water and control DNA encoding either a known monoclonal IgH gene
rearrangement or a polyclonal population were used as negative or positive controls, respectively.
PCR amplified products were subjected to capillary electrophoresis on an ABI PRISM 3100
genetic analyzer and evaluated using the Genescan 2.1 software package (Applied Biosystems,
Foster City, CA).
Molecular karyotypes
For ALL cases #1-5, total RNA was isolated from primary ALL samples or splenocytes from
transplanted mice (xenografts) using the RNeasy Mini Kit (Qiagen, Valencia, CA). Common
leukemia translocations (i.e. TEL/AML1, BCR/ABL major and minor, E2A/PBX, MLL/AF4)
were identified using the Signature® LTx ALL and CML kits (Asuragen, Austin, TX). For each
multiplexed assay, total RNA (3 μL) was reverse transcribed into cDNA and amplified by PCR
using biotin-modified primers (35 cycles of 94°C for 30 sec, 55°C for 30 sec, 72°C for 30 sec).
GAPDH transcripts were co-detected in the same reaction as endogenous internal controls. The
PCR products were then sorted on a liquid bead array containing oligonucleotide probes specific
for each of the translocations and detected using the Luminex 200 system (Austin, TX). Mean
fluorescence intensity was analyzed on at least 100 beads for each target. Clinically validated
cutoffs for detecting these translocations were used to determine positivity.
Gene expression microarrays
Thawed cell suspensions from primary ALL samples or splenocytes of transplanted mice
(xenografts) were pelleted, resuspended in cold PBS and lysed in TRIzol Reagent (Invitrogen,
Carlsbad, CA). RNA was isolated using a combined protocol, where the TRIzol extraction
aqueous phase was mixed with an equal volume of 70% ethanol, applied to an RNeasy Midi
column (Qiagen, Valencia, CA) and purified according to manufacturer’s instructions. RNA
integrity was verified on a BioAnalyzer (Agilent, Foster City, CA). cDNA was synthesized by
reverse transcription from 200 ng total RNA. Biotinylated cRNA targets were amplified by in
vitro transcription using the TotalPrep-96 RNA Amplification Kit (Ambion, Austin, TX) and
hybridized to HumanWG-6 v3 Expression BeadChips (Illumina, San Diego, CA) according to
manufacturers’ instructions. Expression values were generated using the Illumina BeadStudio
Gene Expression module (version 3.2.7) and exported for further analysis.
Data were analyzed using several packages for the R statistical programming environment
(http://www.r-project.org). Preprocessing, including background correction, variance
stabilization, and quartile normalization was performed using the lumi package1-3. A linear model
controlling for primary (human bone marrow or peripheral blood) or xenograft (splenocyte) cell
origin was fit using the linear models for microarray analysis package4. The residuals from that fit
were then used for hierarchical clustering with Euclidean distance and complete linkage
(Supplementary Figure 4). A second linear model, adding patient as a factor, was used to
determine the genes different between human and xenografts. The David/EASE website5,6 was
used to find enriched gene ontology categories from the gene list that differentiated primary from
xenograft samples (false-discovery-rate 0.05, from the second linear model fit (Supplementary
Table 3 and Supplementary Figure 4). Data and analysis are available for download from NCBI
Gene Expression Omnibus (accession GSE15621) at
http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=bzqtleumgogiqbg&acc=GSE15621
Statistics
LSC frequencies: LSC frequencies were calculated by maximum likelihood estimation
of the Poisson parameter, with the addition of pseudocounts (adding 1 living mouse) at each
endpoint and the next dilution, averaging by least squares to get an overall estimate of LSC
frequency for each cell type. Pseudocounts were added to minimize the effect of small sample
size7. In this analysis, we employed the 1-hit Poisson assumption and then we used a maximum
likelihood expectation to derive the LSC frequency. While the 1-hit assumption has been
critiqued in general8,9, our actual and calculated simulations (Supplementary Tables 5,6) both
support using a lambda of 1 (1-hit model) specifically for our data in these maximum likelihood
expectation calculations.
Trend statistics: Each dilution series was fitted to a log-linear model and the F statistic
was tested for each fit. The times-to-leukemia for each dose of cells injected of the primary ALL
case or cell line (Table 1) were compared to the times-to-leukemia for the corresponding
secondary transplants (Supplementary Table 2, Secondary Transplant 1), using a linear model to
compare the distributions (after confirming that the times-to-leukemia for the secondary
transplants also follows a log-linear model).
Single cell injections: Based on our measurements in the 2 independent single cell
injection simulations (Supplementary Table 5), a statistical simulation was performed to model
the single cell injections for ALL case#3. Sampling with replacement was used (but respecting
the sum of the cells so that the sum could not go above the total number of cells based on the
initial cell counts) to determine whether the mice that eventually developed leukemia were the
recipients of the vast majority of the ALL case#3 cells in the injection solution for all animals, or
if the intended cell numbers were accurate at that low level (Supplementary Table 6).
Supplementary references
1
Du P, Kibbe WA, Lin SM. nuID: a universal naming scheme of oligonucleotides for
illumina, affymetrix, and other microarrays. Biol Direct 2007;2:16.
2
Du P, Kibbe WA, Lin SM. lumi: a pipeline for processing Illumina microarray.
Bioinformatics 2008;24:1547-8.
3
Lin SM, Du P, Huber W, Kibbe WA. Model-based variance-stabilizing transformation
for Illumina microarray data. Nucleic Acids Res 2008;36:e11.
4
Smyth GK, Michaud J, Scott HS. Use of within-array replicate spots for assessing
differential expression in microarray experiments. Bioinformatics 2005;21:2067-75.
5
Dennis G.,Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, et al. DAVID:
Database for Annotation, Visualization, and Integrated Discovery. Genome Bio.
2003;4:P3.
6
Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large
gene lists using DAVID bioinformatics resources. Nat. Protoc. 2009;4:44-57.
7
Taswell C. Limiting dilution assays for the determination of immunocompetent cell
frequencies. I. Data analysis. J Immunol 1981; 126: 1614-1619.
8
Yamazaki J, Mizukami T, Takizawa K, Kuramitsu M, Momose H, Masumi A, et al.
Identification of cancer stem cells in a Tax-transgenic (Tax-Tg) mouse model of adult Tcell leukemia/lymphoma. Blood 2009; 114: 2709-2720.
9
Bonnefoix T, Callanan M. Challenging the adult T-cell leukemia/lymphoma (ATL) stem
cell concept based on limiting dilution transplantation assay. Blood 2010; 115: 21172118.