Powered By Bing

Supplementary Information

Supplemental data for classification, subtype discovery and prediction of outcome in pediatric lymphoblastic leukemia by gene expression profiling

Section I: Expanded Methods

RNA extraction, labeling, hybridization, and data analysis

Mononuclear cell suspensions from diagnostic BM aspirates or peripheral blood (PB) samples were prepared from each patient and an aliquot cryopreserved. RNA was extracted using the Trizol reagent (Gibco BRL Life Technologies, Gaithersburg, MD) following the manufacture´s recommended protocol. RNA integrity was assessed by electrophoresis on the Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA).

First and second strand cDNA were synthesized from 5-15 µg of total RNA using the SuperScript Double-Stranded cDNA Synthesis Kit (Gibco Life Technologies) and the oligo-dT24-T7 (5´-GGC CAG TGA ATT GTA ATA CGA CTC ACT ATA GGG AGG CGG-3´) primer according to the manufacturer´s instructions. cRNA was synthesized and labeled with biotinylated UTP and CTP by in vitro transcription using the T7 promoter coupled double stranded cDNA as template and the T7 RNA Transcript Labeling Kit (ENZO Diagnostics Inc., Farmingdale NY). Briefly, double stranded cDNA synthesized from the previous steps was washed twice with 70% ethanol and resuspended in 22 µl RNase-free H2O. The cDNA was incubated with 4 µl of 10X each reaction buffer, 1µl of biotin labeled ribonucleotides, 2 µl of DTT, 1µl of RNase inhibitor mix and 2 µl 20X T7 RNA Polymerase for 5 hr at 37°C. The labeled cRNA was separated from unincorporated ribonucleotides by passing through a CHROMA SPIN-100 column (Clontech, Palo Alto, CA) and precipitated at -20°C for 1 hr to overnight.

The cRNA pellet was resuspended in 10 ml Rnase-free H2O. and 10.0 mg was fragmented by heat and ion-mediated hydrolysis at 95°C for 35 minutes in 200 mM Tris-acetate, pH 8.1, 500 mM KOAc, 150 mM MgOAc. The fragmented cRNA was hybridized for 16 hr at 45°C to HG_U95Av2 oligonucleotide arrays (Affymetrix, Santa Clara, CA) containing 12,600 probe sets from full length annotated genes together with additional probe sets designed to represent EST sequences. Arrays were washed at 25°C with 6 X SSPE (0.9M NaCl, 60 mM NaH2PO4, 6 mM EDTA + 0.01% Tween 20) followed by a stringent wash at 50°C with 100 mM MES, 0.1M NaCl2, 0.01% Tween 20. The arrays were then stained with phycoerythrin conjugated streptavidin (Molecular Probes, Eugene, OR). Arrays were scanned using a laser confoCal scanner (Agilent, Palo Alto, CA) and the expression value for each gene was calculated using Affymetrix Microarray software (MAS 4.0). The signal intensity for each gene was calculated as the average intensity difference (AID), represented by [Σ(PM - MM)/(number of probe pairs)], where PM and MM denote perfect-match and mismatch probes, respectively. Expression values were normalized across the sample set by scaling the average of the fluorescent intensities of all genes on an array to a constant target intensity of 2500, then any AID over 45,000 was capped to a value of 45,000. All AID´s less than 100, including negative values and absent calls were converted to a value of 1. In addition, a variation filter was used that eliminated any probe set in which less than 1% of the samples had a present call, or if the Max AID - Min AID across the sample set was less than 100. The average intensity differences for each of the remaining genes were analyzed. For some metrics the data was log transformed prior to analysis. The minimum quality control values required for inclusion of a sample´s hybridization data in the study were 10% or greater present calls, a GAPDH/Actin 3´ /5´ ´ ratio <5, and use of a scaling factor that was within 3 standard deviations from the mean of the scaling values of all chips analyzed. The average percent present calls for our overall dataset was 29.7%, and for each of the genetic subgroups was BCR-ABL (31.1%), E2A-PBX1 (28.9%), Hyper >50 (31%), MLL (29.8%), T-ALL (29.1%), TEL-AML1 (28.5%), Novel (30.2%), others (31.1%). In addition, we required each sample to have >75% blasts. The average percentage blasts for the overall dataset used to define the genetic subtypes was 93%, and for each genetic subtype was BCR-ABL (92%), E2A-PBX1 (96%), Hyper >50 (93%), MLL (93%), T-ALL (91%), TEL-AML1 (92%), Novel (95%), and others (94%).

The data was analyzed using the MAS 4.0 software. Recently, a new version of the Affymetrix software became available (Affymetrix MAS 5.0). Affymetrix reports an overall 94% correlation between data analyzed using these two software programs. We have performed a limited analysis to directly compare the results of our data analyzed with these two different software programs. We took 74 randomly selected cases and reanalyzed the primary data using the MAS 5.0 software. Using the default parameters set by Affymetrix, the average percent present call was lower for the MAS 5.0 analyzed data as compare to the values obtained using MAS 4.0; however, with exceedingly rare exception, all of the 271 Chi-squared genes selected as discriminators of the seven genetic subtypes (see below) remained within the new dataset. Moreover, when we used these 271 in a 2-D hierarchical clustering analysis (as described below), the data looked identical to the results obtained using the MAS 4.0 dataset (data not shown).

Reproducibility of microarray data

The reproducibility of the Affymetrix microarray system was assessed by comparing the gene expression profiles of the following samples: (i) RNA extracted from duplicate cryopreserved diagnostic leukemic samples from 23 patients; (ii) Single RNA samples from 13 patients analyzed on two separate arrays. Results from these analyses are presented in Table 2. As shown, the mean number of probe sets that displayed a >2-fold difference in expression between separately extracted but paired RNA samples was 144, and for single RNA samples analyzed on two separate occasions was 133. Moreover, very few probe sets were found to have a >3-fold difference in expression levels between replicate samples. The observed number of probe sets showing a difference in expression values represents <2% of the total number of probe sets on the microarray, and thus these data suggest that the Affymetrix microarray system has a very high degree of reproducibility.

Table 2. Comparison data from replicate bone marrow sample

  # > 2 fold 2.1-3.0 3.1-4.0 > 4 Chip Extraction  
  42 38 4 0 T-ALL-#3 Different  
  45 43 2 0 BCR-ABL-#7 Different  
  59 53 1 5 E2A-PBX-#7 Different  
  61 55 2 4 T-ALL C25 Different  
  68 61 6 1 Hyperdip47-50-C17 Different  
  69 65 3 1 MLL-C6 Different  
  84 81 1 2 Hyperdip47-50-C18 Different  
  103 99 4 0 Pseudodip-C10 Different  
  107 93 11 3 Pseudodip-C12 Different  
  109 106 3 0 Normal-R1 Different  
  116 106 7 3 TEL-AML1-C33 Different  
  117 109 4 4 TEL-AML1-2M#2 Different  
  126 117 8 1 T-ALL-C3  replicate #1 Different  
  133 122 7 4 Normal-#3 Different  
  153 146 5 2 Hypodip-#4 replicate #1 Different  
  159 117 26 16 Hyperdip47-50-C13 Different  
  163 121 15 27 TEL-AML1-#10 Different  
  166 154 12 0 T-ALL-C3  replicate #2 Different  
  183 168 12 3 Pseudodip-#6 Different  
  187 155 23 9 T-ALL-RR1 Different  
  239 200 19 20 Hypodip-#4 replicate #2 Different  
  256 204 29 23 Hypodip-#4 replicate #3 Different  
  568 295 137 136 Hyperdip>50-R2M1 Different  
  21 19 2 0 T-ALL-#7 Same  
  24 22 2 0 T-ALL-R2 Same  
  34 33 1 0 T-ALL-C3 replicate #3 Same  
  52 52 0 0 TEL-AML1-C29 Same  
  64 58 2 4 Hyperdip>50-C34 Same  
  64 56 5 3 Hyperdip>50-R2M2 Same  
  76 74 1 1 T-ALL-R2M1 Same  
  132 129 1 2 Pseudodip-#7 Same  
  158 147 9 2 Hyperdip>50-C1 Same  
  161 139 19 3 TEL-AML1-C20 Same  
  197 189 6 2 T-ALL-#8 Same  
  210 169 25 16 Normal-C30-N Same  
  539 139 123 277 Pseudodip-C4 Same  

Differences between Different and Same Extraction

    Mean Median Stdev  
Different Extraction   144.0 117.0 109.0  
Same Extraction   133.2 76.0 138.4  


Comparison of microarray data between PB and BM leukemia samples

Matched BM and PB samples that contained >80% leukemic blasts were obtained from 10 patients and the RNA extracted and assessed by microarray analysis. As shown in Table 3, a very high level of correlation was observed for the expression profiles of BM and PB, with only 189 probe sets having a >2-fold difference in expression. More importantly, sample type. These data suggest that there are minimal differences in the gene expression profiles of leukemic blasts obtained from BM or PB, and raise the possibility that diagnostic gene expression profiling might be possible on samples obtained from the PB.

Table 3. Comparison of peripheral blood and bone marrow samples

  #  >  2 fold 2.1-3.0 3.1-4.0 >  4 Peripheral Blood Bone Marrow  
  98 90 6 2 E2A-PBX1-C7 PB E2A-PBX1-C7  
  108 93 9 6 Pseudodip-NHR1 PB Pseudodip-NHR1  
  113 105 4 4 BCR-ABL-#1 PB BCR-ABL-#1  
  139 117 18 4 Hyperdip>50-C8 PB Hyperdip>50-C8  
  141 135 6 0 E2A-PBX1-C3 PB E2A-PBX1-C3  
  159 139 16 4 T-ALL-C9 PB T-ALL-C9  
  244 223 14 7 Hyperdip>50-C6 PB Hyperdip>50-C6  
  245 194 33 18 MLL-C3 PB MLL-C3  
  272 246 20 6 MLL-RR3 PB MLL-RR3  
  377 300 50 27 E2A-PBX1-C2 PB E2A-PBX1-C2  

Differences between PB vs BM

        Mean Median Stdev  
        189.6 150.0 91.1  
        133.2 76.0 138.4  


Real-time RT-PCR results

Real-time RT-PCR assays (Taqman; Perkin-Elmer/Applied Biosystems, Foster City, CA) were developed to independently determine the level of mRNA for five genes that were found by microarray analysis to be predictive of either T-lineage ALL (CD3δ, CD3D antigen delta polypeptide TiT3 complex; MAL, mal T-Cell differentiation protein; and PRKCQ, protein kinase C theta) or E2A-PBX1 expressing ALL (MERTK, c-MER proto-oncogene tyrosine kinase and KIAA802). RNA samples analyzed included four samples each of E2A-PBX1 and T-ALL, and two samples each from the remaining subtypes (BCR-ABL, MLL, TEL-AML1, Hyperdiploid >50, Hyperdiploid 47-50, Hypodiploid, Pseudodiploid, and Normal). Whenever possible, the forward and reverse primers were designed in different exons so that DNA contamination would not be a concern. In the case of MAL where this was not clear, the RNA was treated for 15 minutes at room temperature with 1.0 unit of DNase I (Invitrogen, Carlsbad, California) using the Invitrogen protocol to remove any contaminating DNA.

Thirty-three ng of RNA from each sample was reverse transcribed using random hexamers and Multiscribe Reverse Transcriptase (Perkin-Elmer/Applied Biosystems) in a total volume of 10 µl. Real Time PCR was performed on a PE Applied Biosystems 7700 prism using oligonucleotide primers and probes sequences designed using Primer Express. The following primers and probes were used: (1) MERTK, 5´ -GGC GTG CTA ACT GTT CCA GG-3´ (forward primer), 5´ -CCT TTG TCA TTG TGG GCC TC-3´(reverse primer), and 5´-CAA CTG AAG ACC GCC ATC TCC GTC AG-3´(probe); (2) KIAA802, 5´- CCA AGC TGA AGG AGT CGG AC-3´(forward), 5´-AGA TTT CCT TTG TGA TTT TCT TCT TCC-3´(reverse), and 5´-TGC TCG GCC AGT GAG AAT CTC TAC CTG-3´(probe); (3) PRKCQ, 5´-AAG CTG CCA CAA GTT CGA CC-3´(forward), 5´-ATG AAG GAA CTG CAG ACC AAG AA-3´ (reverse), and 5´-CCA GAG CGA CGT TTT ATG CTG CTG AAA TC-3´(probe); (4) MAL, 5´-CCA GTG GCT TCT CGG TCT TC-3´ (forward), 5´-CAG GAG CCA CTC ACA AAC TCA A-3´(reverse), and 5´-CCA CCT TGC CCG ACT TGC TCT TCA-3´(probe); and (5) CD3δ , 5´-TCA ACA GAG CTT GTG TGT CGG-3´(forward), 5´-CAT TGC CAC TCT GCT CCT TG-3(reverse), and 5´-TGT CCA GCA AAG CAG AAG ACT CCC AAA-3´(probe). All probes were labeled at the 5´ end with FAM (6-carboxy-fluroescein) and at the 3´ end with TAMRA (6-carboxy-tetramethyl-rhodamine).

The PCR reactions were performed in a total volume of 50 µl containing 10 µl of the RT product, 300 nm each of the forward and reverse primers, 100 nM of probe, 1X master mix (PE Applied Biosystems) and 1 µl of Taq Gold. Following a 10 minute incubation at 95°C to activate the Taq Gold, samples were denatured at 95°C for 15 seconds, then annealed and extended at 60°C for 1 minute, for a total of 40 cycles. The RNA from each sample was also amplified using primers and probes to RNase P (PE Applied Biosystems) for use in normalization. Appropriate negative controls were included in each run. Standard curves were generated for T-cell markers and RNase P using MOLT4 RNA, a T-cell leukemia cell line, and for the E2A-PBX1 markers and RNase P using a leukemia cell line, 697, that contains an E2A-PBX1 fusion. The expression level of the predictive genes and RNase P were determined in each of the 24 ALL samples (Figures 7-11). A ratio was then calculated by taking the expression value for the specific gene and dividing it by the expression level of RNase P in the sample. These ratios were then compared to the values obtained from the Affymetrix data from the same RNA sample. The raw Affymetrix data were scaled as described and then normalized using the 3´GAPDH value for each sample, yielding a normalized ratio. The Taqman and Affymetrix ratios were then log transformed and compared. Since the markers selected for Taqman analysis were predictors for either E2A-PBX1 or T-ALLs, each gene was expected to have four RNA samples with high and 20 samples with low expression. For each gene evaluated, an average expression value for both the Taqman and Affymetrix data was calculated for all samples in the up-regulated group, and similarly, for the samples in the down-regulated group. These values were then compared against each other as shown in Figure 12.

Analysis of CD3δ

The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg).

Figure 7. The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg).

Table 4. Results of Taqman assay for CD3δ and RNase P on twenty-four selected ALL diagnostic bone marrow samples representing the various leukemia subgroups.

  Ct
CD3δ @
Ct
RNP +
Input Log
CD3δ ++
Input
CD3δ%
Input Log
RNP*
Input
RNP**
Input
CD3δ /RNP &
 
E2A-PBX1-#1 28.26 17.05 2.394 247.825 4.454 28452.773 0.0087  
E2A-PBX1-#3 30 16.69 1.868 73.772 4.585 38490.487 0.0019  
E2A-PBX1-#7 28.94 17.36 2.188 154.342 4.341 21934.21 0.0070  
E2A-PBX1-C10 27.53 16.27 2.615 412.030 4.738 54758.77 0.0075  
T-ALL-R3 23.47 19.43 3.843 6963.863 3.587 3859.725 1.8042  
T-ALL-C20 21.76 17.14 4.360 22910.208 4.421 26382.588 0.8684  
T-ALL-R1 24.79 20.06 3.444 2777.311 3.357 2274.605 1.2210  
T-ALL-#3 22.39 18.24 4.170 14773.707 4.020 10479.498 1.4098  
BCR-ABL-R3 29.68 20.38 1.965 92.188 3.240 1738.834 0.0530  
BCR-ABL-#7 25.8 17.51 3.138 1374.537 4.286 19339.415 0.0711  
Hyperdip>50-C36 27.65 17.44 2.579 378.997 4.312 20509.735 0.0185  
Hyperdip>50-#5 30.04 17.36 1.856 71.7455 4.341 21934.21 0.0033  
Hyperdip47-50-C17 30.18 20.08 1.813 65.081 3.350 2236.74 0.0291  
Hyperdip47-50-C8 30.49 17.95 1.7197 52.444 4.126 13367.573 0.0039  
Hypodip-#1 28.75 18.09 2.246 176.176 4.075 11885.546 0.0148  
Hypodip-C4 29.91 18.28 1.895 78.544 4.006 10133.5 0.0078  
MLL-C2 28.53 17.26 2.312 205.345 4.378 23854.727 0.0086  
MLL-2M#2 29.88 17.11 1.904 80.202 4.432 27055.348 0.0030  
Normal-C5 27.34 17.58 2.672 470.319 4.261 18235.876 0.0258  
Normal-C6 31.51 18.79 1.411 25.77523 3.820 6604.684 0.0040  
Pseudodip-#4 28.49 18.73 2.325 211.146 3.842 6945.82 0.0304  
Pseudodip-C16-N 28.21 18.18 2.409 256.606 4.042 11020.77 0.0233  
TEL-AML1-#7 29.05 18.08 2.155 142.960 4.079 11985.727 0.0119  
TEL-AML1-C39 30.89 19.6 1.599 39.693 3.525 3346.472 0.0119  

@Critical threshold value for CD3δ + Critical threshold value for RNase
++ Log of the pg CD3δ   in patient sample calculated from standard curve
% Exponentiated value of log CD3δ
* Log of the pg RNase P in patient sample calculated from standard curve
** Exponentiated value of log RNase P
& Ratio of CD3δ  to RNase P

Analysis of MAL

Figure 8. The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg).

Figure 8. The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg).

Table 5. Results of Taqman assay for MAL and RNase P on twenty-four selected ALL diagnostic bone marrow samples representing the various leukemia subgroups.

  Ct
MAL@
Ct
RNP+
Input Log
MAL++
Input
MAL%
Input Log
RNP*
Input
RNP**
Input
MAL/RNP&
 
E2A-PBX1-#1 30.11 16.69 3.392 2466.058 4.551 35588.466 0.0693  
E2A-PBX1-#3 32.63 16.28 2.653 449.533 4.696 49703.922 0.0090  
E2A-PBX1-#7 32.01 16.46 2.835 683.343 4.633 42923.625 0.0159  
E2A-PBX1-C10 32 18.69 2.838 687.974 3.844 6975.819 0.0986  
T-ALL-R3 31.16 19.91 3.084 1213.350 3.412 2581.604 0.4700  
T-ALL-C20 27.23 17.39 4.237 17252.443 4.304 20119.137 0.8575  
T-ALL-R1 31.11 19.42 3.099 1255.028 3.585 3848.394 0.3261  
T-ALL-#3 26.3 17.5 4.510 32334.48 4.265 18394.376 1.7578  
BCR-ABL-R3 35.47 22.1 1.820 66.0160 2.637 433.454 0.1523  
BCR-ABL-#7 29.43 16.29 3.591 3903.742 4.693 49300.587 0.0792  
Hyperdip>50-C36 31.31 16.54 3.040 1096.437 4. 40214.977 0.0273  
Hyperdip>50-#5 32.3 16.73 2.750 561.781 4.537 34447.284 0.0163  
Hyperdip47-50-C17 33.59 18.56 2.371 235.042 3.890 7755.264 0.0303  
Hyperdip47-50-C8 31.87 17.27 2.876 751.117 4.346 22185.652 0.0339  
Hypodip-#1 31.5 16.93 2.984 964.378 4.466 29267.362 0.0330  
Hypodip-C4 32.47 16.19 2.700 500.839 4.728 53485.713 0.0094  
MLL-C2 31.43 16.58 3.005 1011.071 4.590 38925.441 0.0260  
MLL-2M#2 33.14 16.22 2.503 318.532 4.718 52194.18 0.0061  
Normal-C5 30.09 16.68 3.398 2499.599 4.555 35879.621 0.0697  
Normal-C6 35.59 17.94 1.784 60.876 4.109 12852.511 0.0047  
Pseudodip-#4 32.11 16.99 2.805 638.710 4.445 27870.975 0.0229  
Pseudodip-C16-N 35.14 17.51 1.916 82.500 4.2611 18245.11 0.0045  
TEL-AML1-#7 31.78 17.22 2.902 798.195 4.3638 23108.143 0.0345  
TEL-AML1-C39 33.1 17.21 2.515 327.256 4.3673 23297.194 0.0140  

@Critical threshold value for MAL
+ Critical threshold value for RNase P
++ Log of the pg MAL  in patient sample calculated from standard curve
% Exponentiated value of log MAL
* Log of the pg RNase P in patient sample calculated from standard curve
** Exponentiated value of log RNase P
& Ratio of MAL  to RNase P

Analysis of PRKCQ

Figure 9. The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg).

Figure 9. The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg).

Table 6. Results of Taqman assay for PRKCQ and RNase P on twenty-four selected ALL diagnostic bone marrow samples representing the various leukemia subgroups.

  Ct
PRKCQ@
Ct
RNP+
Input Log
PRKCQ ++
Input
PRKCQ
%
Input Log
RNP*
Input
RNP**
Input
PRKCQ/RNP&
 
E2A-PBX1-#1 27.43 17.05 3.681 4794.330 4.454 28452.773 0.1685  
E2A-PBX1-#3 28.18 16.69 3.467 2929.645 4.585 38490.487 0.0761  
E2A-PBX1-#7 28.5 17.36 3.376 2374.354 4.341 21934.21 0.1082  
E2A-PBX1-C10 28.73 16.27 3.310 2041.482 4.738 54758.77 0.0373  
T-ALL-R3 26.54 19.43 3.935 8601.440 3.587 3859.725 2.2285  
T-ALL-C20 26.3 17.14 4.003 10069.857 4.421 26382.588 0.3817  
T-ALL-R1 27.21 20.06 3.743 5539.565 3.357 2274.605 2.4354  
T-ALL-#3 25.98 18.24 4.094 12424.897 4.020 10479.498 1.1856  
BCR-ABL-R3 32.34 20.38 2.280 190.683 3.240 1738.834 0.1097  
BCR-ABL-#7 27.59 17.51 3.635 4316.116 4.286 19339.415 0.2232  
Hyperdip>50-C36 28.17 17.44 3.470 2948.948 4.312 20509.735 0.1438  
Hyperdip>50-#5 28.57 17.36 3.356 2267.672 4.341 21934.21 0.1033  
Hyperdip47-50-C17 29.84 20.08 2.993 984.815 3.350 2236.740 0.4403  
Hyperdip47-50-C8 28.67 17.95 3.327 2123.531 4.126 13367.573 0.1589  
Hypodip-#1 30.12 18.09 2.913 819.396 4.075 11885.546 0.0689  
Hypodip-C4 28.58 18.28 3.353 2252.828 4.006 10133.5 0.2223  
MLL-C2 27.68 17.26 3.609 4068.399 4.378 23854.727 0.1705  
MLL-2M#2 27.92 17.11 3.541 3475.133 4.432 27055.348 0.1284  
Normal-C5 28.04 17.58 3.507 3211.777 4.261 18235.876 0.1761  
Normal-C6 31.68 18.79 2.469 294.1405 3.820 6604.683 0.0445  
Pseudodip-#4 30.01 18.73 2.945 880.780 3.842 6945.819 0.1268  
Pseudodip-C16-N 30.02 18.18 2.942 875.015 4.042 11020.77 0.0794  
TEL-AML1-#7 29.18 18.08 3.182 1519.14 4.079 11985.727 0.1267  
TEL-AML1-C39 35.32 19.6 1.430 26.938 3.525 3346.472 0.0080  

@Critical threshold value for PRKCQ
+ Critical threshold value for RNase P
++ Log of the pg PRKCQ in patient sample calculated from standard curve
% Exponentiated value of log PRKCQ* Log of the pg RNase P in patient sample calculated from standard curve
** Exponentiated value of log RNase P
& Ratio of PRKCQ to RNase P

Analysis of KIAA802

Figure 10. The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg).

Figure 10. The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg).

Table 7. Results of Taqman assay for KIAA802 and RNase P on twenty-four selected ALL diagnostic bone marrow samples representing the various leukemia subgroups.

  Ct
KIAA802@
Ct
RNP+
Input Log
KIAA802++
Input
KIAA802%
Input Log
RNP*
Input
RNP**
Input
KIAA802/RNP&
 
E2A-PBX1-#1 24.4 16.999 4.715 51931.756 4.463 29028.716 1.7890  
E2A-PBX1-#3 24.55 16.168 4.672 46983.288 4.763 57945.925 0.8108  
E2A-PBX1-#7 26.05 16.55 4.237 17260.26 4.625 42172.281 0.4093  
E2A-PBX1-C10 26.05 16.985 4.237 17260.26 4.468 29368737 0.5877  
T-ALL-R3 33.72 19.879 2.013 103.10479 3.422 2645.091 0.0390  
T-ALL-C20 31.81 16.86 2.567 369.017 4.513 32586.744 0.0113  
T-ALL-R1 37.045 19.078 1.049 11.201 3.712 5149.894 0.0022  
T-ALL-#3 33.64 17.55 2.036 108.761 4.264 18356.147 0.0059  
BCR-ABL-R3 34.815 20.79 1.696 49.637 3.093 1239.784 0.0400  
BCR-ABL-#7 30.21 17.04 3.031 1073.830 4.448 28055.419 0.0383  
Hyperdip>50-C36 3068 17.04 2.895 784.636 4.448 28055.419 0.0280  
Hyperdip>50-#5 31.135 16.52 2.763 579.095 4.636 43237.887 0.0134  
Hyperdip47-50-C17 31.06 19.19 2.784 608.828 3.672 4691.792 0.1298  
Hyperdip47-50-C8 31.56 17.2 2.640 436.043 4.390 24559.384 0.0178  
Hypodip-#1 31.07 17.02 2.782 604.777 4.455 28526.052 0.0212  
Hypodip-C4 33.397 17.157 2.107 127.916 4.406 25453.706 0.0050  
MLL-C2 30.03 16.74 3.083 1210.941 4.556 36007.29 0.0336  
MLL-2M#2 34.23 16.167 1.865 73.352 4.763 57994.145 0.0013  
Normal-C5 36.1 16.41 1.323 21.050 4.676 47380.7 0.0004  
Normal-C6 33.03 17.24 2.213 163.430 4.376 23755.69 0.0069  
Pseudodip-#4 29.2 17.01 3.324 2107.491 4.459 28764.321 0.0733  
Pseudodip-C16-N 28.51 16.8 3.524 3340.549 4.535 34254.348 0.0975  
TEL-AML1-#7 29.83 16.986 3.141 1383.915 4.468 29344.318 0.0472  
TEL-AML1-C39 30.165 18.187 3.044 1106.579 4.034 10806.078 0.1024  

@Critical threshold value for KIAA802
+Critical threshold value for RNase P 
++Log of the pg KIAA802 in patient sample calculated from standard curve
% Exponentiated value of log KIAA802
* Log of the pg RNase P in patient sample calculated from standard curve
** Exponentiated value of log RNase P

Analysis of MERTK

Figure 11. The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg)

Figure 11. The standard curves of critical threshold values (Ct) versus log of the concentration of RNA in picograms (pg).

Table 8. Results of Taqman assay for MERTK and RNase P on twenty-four selected ALL diagnostic bone marrow samples representing the various leukemia subgroups.

  Ct
MERTK @
Ct
RNP+
Input Log
MERTK++
Input
MERTK%
Input Log
RNP*
Input
RNP**
Input
MERTK/RNP&
 
E2A-PBX1-#1 23.202 16.999 6.126 1336904.1 4.463 29028.716 46.0545  
E2A-PBX1-#3 23.816 16.168 5.930 851695.74 4.763 57945.925 14.6981  
E2A-PBX1-#7 24.164 16.55 5.819 659630.81 4.625 42172.281 15.6413  
E2A-PBX1-C10 23.198 16.985 6.127 1340836.9 4.468 29368.737 45.6552  
T-ALL-R3 33.649 19.879 2.794 622.819 3.422 2645.091 0.23  
T-ALL-C20 30.594 16.86 3.769 5870.252 4.513 32586.744 0.1801  
T-ALL-R1 28.06 19.078 4.577 37739.445 3.712 5149.894 7.3282  
T-ALL-#3 31.38 17.55 3.518 3295.998 4.264 18356.147 0.1800  
BCR-ABL-R3 34.5 20.79 2.523 333.397 3.093 1239.784 0.2689  
BCR-ABL-#7 28.06 17.04 4.577 37739.445 4.448 28055.419 1.3452  
Hyperdip>50-C36 28.46 17.04 4.449 28133.788 4.448 28055.419 1.0028  
Hyperdip>50-#5 28.43 16.52 4.459 28760.456 4.636 43237.887 0.6652  
Hyperdip47-50-C17 29.767 19.19 4.032 10774.623 3.671 4691.792 2.2965  
Hyperdip47-50-C8 33.36 17.2 2.887 770.068 4.390 24559.384 0.0314  
Hypodip-#1 30.67 17.02 3.744 5551.610 4.455 28526.052 0.1946  
Hypodip-C4 28.88 17.157 4.315 20667.244 4.406 25453.706 0.8120  
MLL-C2 30.415 16.74 3.826 6694.884 4.556 36007.29 0.1859  
MLL-2M#2 33.44 16.167 2.861 726.132 4.763 57994.145 0.0125  
Normal-C5 32.13 16.41 3.279 1900.196 4.676 47380.7 0.0401  
Normal-C6 33.376 17.24 2.881 761.073 4.376 23755.69 0.0320  
Pseudodip-#4 31.98 17.01 3.327 2121.466 4.459 28764.321 0.0738  
Pseudodip-C16-N 28.497 16.8 4.437 27379.672 4.535 34254.348 0.7993  
TEL-AML1-#7 34.15 16.986 2.635 431.105 4.468 29344.318 0.0147  
TEL-AML1-C39 34.3 18.187 2.587 386.141 4.034 10806.078 0.0357  

@Critical threshold value for MERTK
+ Critical threshold value for RNase P
++ Log of the pg MERTK in patient sample calculated from standard curve
% Exponentiated value of log MERTK
* Log of the pg RNase P in patient sample calculated from standard curve
** Exponentiated value of log RNase P
& Ratio of MERTK to RNase P


Comparison of real-time RT-PCR and Affymetrix data

The normalized gene expression ratios for the TaqMan data (TM) (gene/RNase P) and for the Affymetrix microarray data (GC) (AID for a gene/AID for GAPDH) were log transformed and then the average expression values for each gene was calculated in the four samples in which its expression was expected to be up-regulated and separately in the 20 samples in which its expression was expected to be down-regulated. For example, for genes that were expected to be up-regulated in T-ALL (CD3Δ , MAL, and PRKCQ), the log expression ratios in the T-ALL samples were averaged to give the up regulated (Up Reg) values and the log expression ratios of each gene in the non-T-ALL cases were averaged to give the down regulated value (Down Reg).

Table 9. Comparison of real-time RT-PCR and Affymetrix data

    Log ave GC Log ave TM
CD3dδ Up Reg (4) 1.578 0.108
  Down Reg (20) -0.502 -1.958
MAL Up Reg (4) 1.524 -0.159
  Down Reg (20) -0.855 -1.502
PRKCQ Up Reg (4) 0.7521 0.098
  Down Reg (20) -0.136 -0.972
KIAA802 Up Reg (4) 1.16 -0.114
  Down Reg (20) -0.393 -1.772
MERTK (1) Up Reg (4) 0.732 1.42
  Dow Rg (20) -0.934 -0.794
MERTK (2) Up Reg (4) 0.762 1.421
  Down Reg (20) -1.068 -0.792
MERTK (ave) Up Reg (4) 0.747 1.4205
  Down Reg (20) -1.001 -0.793

In the case of MERTK, there were two probe sets on the Affymetrix chip. The normalized log values for each probe sets is shown in Table 9, as well as the average. The average value was used in Figure 12.

Figure 12. The log ratio averages from the up regulated and down regulated genes from the Taqman data plotted against the up regulated and down regulated genes from the microarray data (CG).

Figure 12. The log ratio averages from the up regulated and down regulated genes from the Taqman data plotted against the up regulated and down regulated genes from the microarray data (CG).

In both the Taqman and the microChip array analysis, MERTK and KIAA802, were very highly expressed in the diagnostic samples containing E2A-PBX1, and expressed at low levels in all of the other samples. Likewise, PRKCQ, CD3dδ, and MAL, showed high levels of expression in T cells by both methodologies as compared to non T-cells. The normalized ratios from the Taqman assay were plotted against the normalized ratios from the microChip array for both the up-regulated and down-regulated genes. The correlation between Taqman and the microChip array was 70%, indicating that the same pattern of gene expression was seen in both analyses. The MERTK was extremely high in two of the E2A-PBX1 patient samples by Taqman analysis. It would be necessary to repeat the assay several times to validate the two high figures, but there was not sufficient sample to do so. Removal of the MERTK gene from the analysis resulted in a correlation of 91% between the Taqman and MicroChip array (data not shown).


Comparisons of Affymetrix and immunophenotype results

Leukemic blasts at the time of diagnosis were analyzed for expression of lineage restricted cell surface antigens using phycoerythrin- or fluorescein isothioCyanate-conjugated monoClonal antibodies against CD2, CD3ε, CD4, CD5, CD7, CD8, CD10, CD19, and CD22 (Becton Dickinson ImmunoCytometry Systems, San Jose, CA, USA). Data were obtained using a Coulter Epic XL (Beckman Coulter, Miama, Fla, USA), a Coulter Elite, or a FACScalibur flow cytometer (Becton Dickinson, San Jose, CA, USA). The expression patterns for these antigens were then compared to gene expression patterns for the Affymetrix chip sites specified for CD2 (1 probe set, 40738_at), CD3δ (1 probe set, 38319_at), CD3Ε (1 probe set, 36277_at), CD3ζ (1 probe set, 37078_at), CD3γ (1 probe set, 39226_at), CD4 (5 probe sets, 856_at, 1146_at, 35517_at, 34003_at, and 37942_at), CD5 (1probe set, 32953_at), CD7 (1 probe set, 771_s_at), CD8α (1 probe set, 40699_at), CD8β (1 probe set, 39239_at), CD10 (1 probe set, 1389_at), CD19 (2 probe sets, 1096_g_at and 1116_at), and CD22 (2 probe sets, 38521_at and 38522_s_at). As a control, the performance of the Affymetrix microarray probe sets were also assessed using RNA isolated from flow sorted single positive CD4+ and CD8+ thymoCytes, and CD10+/CD19+ bone marrow cells. The results from the microarray analysis are illustrated in Figure 2 in the paper and Figure 13 below. As shown, high RNA expression was observed in T-ALL for the T-lineage restricted genes CD2, CD3δ , ε , and ζ , CD8α , and CD7, and in B-lineage ALLs for the B-cell restricted genes CD19, and CD22. A similar high level of correlation was observed between RNA and protein expression for CD10. The observed low expression levels of T-cell restricted genes in B-cell cases, and B-cell restricted genes in T-ALLs, is consistent with the low level of normal contaminating lymphocytes present in the diagnostic marrow samples analyzed.

Interestingly, in T-lineage ALLs, although high expression was observed for CD3δ , ε , and δ , only trace levels of CD3Γ RNA expression were detected. Verification of the absence of the expression of the encoded protein will require analysis with an antibody specific for this chain.

Although a high correlation was detected between RNA expression by microarray analysis and protein expression by flow cytometry, the absence of RNA expression by microarray analysis did not always correlate with the absence of protein. This resulted from a number of different causes. For example, the Affymetrix probe set for CD5 was able to detect expression in normal thymocytes, but failed to detect expression in T-lineage ALLs, despite the presence of low levels of CD5 protein as assessed by flow cytometry. The most likely interpretation for this observation is that this feature performs poorly under standard hybridization conditions. Thus, high expression levels as seen in normal T-cells can be detected, whereas the lower expression observed in T-ALLs appears to fall below the detection threshold. Two of the five probe sets representing the CD4 gene (1146_at and 35517_at) performed similarly, detecting mRNA in CD4+ thymocytes, but failing to identify the lower CD4 expression levels seen in 23/43 of the T-ALL cases. By contrast, two CD4 probe sets, 856_at (shown) and 37942_at, failed to detect expression in either CD4+ thymocyte or T-ALLs, whereas another probe set (34003_at) detected a transcript that was expressed in the majority of both B- and T-ALLs. A search of the target sequence supplied by Affymetrix against NCBI and CELERA® databases provided some insights into the poor hybridization characteristics of these probe sets. The 34003_at probe set lacked homology to CD4 but demonstrated homology with triosephosphate isomerase 1, and thus represented an unrelated gene. This finding is consistent with recently updated information in the Affymetrix database. The CD4 probe set 856_at had 3 high probability matches, only one that was CD4, however, this sequence was located in an intron. Similarly, the CD8β target sequence was found to localize 3´ of the last exon, and thus the absence of an mRNA able to hybridize to this feature must be cautiously interpreted. Lastly, the CD19 probe set 1116_at was found to have many high probability matches, only one that was homologous to CD19; however, it localized to a region 5´ of exon 1. Taken together, these data suggest that absent or low expression of a gene by microarray analysis must be verified by an alternative method.

Figure 13:B and T cell lineage-associated gene expression in ALL Diagnostic BM. Results are displayed as quantitative values.

Figure 13: B and T cell lineage-associated gene expression in ALL Diagnostic BM. Results are displayed as quantitative values.