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

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).

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).

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).

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).

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).

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.