• Somatic copy number alterations of miRNA genes are uncommon in de novo and secondary AML.

  • MIR223 silencing in AML occurs through both genetic and epigenetic mechanisms.

Altered microRNA (miRNA) expression is frequently observed in acute myelogenous leukemia (AML) and has been implicated in leukemic transformation. Whether somatic copy number alterations (CNAs) are a frequent cause of altered miRNA gene expression is largely unknown. Herein, we used comparative genomic hybridization with a custom high-resolution miRNA-centric array and/or whole-genome sequence data to identify somatic CNAs involving miRNA genes in 113 cases of AML, including 50 cases of de novo AML, 18 cases of relapsed AML, 15 cases of secondary AML following myelodysplastic syndrome, and 30 cases of therapy-related AML. We identified a total of 48 somatic miRNA gene-containing CNAs that were not identified by routine cytogenetics in 20 patients (18%). All these CNAs also included one or more protein coding genes. We identified a single case with a hemizygous deletion of MIR223, resulting in the complete loss of miR-223 expression. Three other cases of AML were identified with very low to absent miR-223 expression, an miRNA gene known to play a key role in myelopoiesis. However, in these cases, no somatic genetic alteration of MIR223 was identified, suggesting epigenetic silencing. These data show that somatic CNAs specifically targeting miRNA genes are uncommon in AML.

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression posttranscriptionally by binding to target messenger RNAs (mRNAs).1  Although miRNAs are frequently dysregulated in acute myelogenous leukemia (AML),2-9  the mechanism of dysregulation remains poorly understood. It is known that the majority of human miRNA genes are present in fragile sites and genomic regions frequently altered in cancer.10  Point mutations of miRNA genes appear to be rare in human cancers. While single nucleotide polymorphisms (SNPs) in miRNAs that affect expression have been reported,11,12  there are only rare examples of recurring somatic point mutations in miRNA genes in human cancer.13,14  Conversely, somatic copy number alterations (CNAs) that include miRNA genes have been reported in several human cancers.15-18  However, whether miRNA genes are frequently and specifically targeted in AML by deletion or amplification is largely unknown. To address this issue, we performed a comprehensive analysis of somatic CNAs involving miRNA genes in 113 cases of AML (50 cases of de novo AML, 18 cases of relapsed AML, 15 cases of secondary AML following myelodysplastic syndrome, and 30 cases of therapy-related AML [t-AML]) by using custom miRNA-specific, high-resolution array-based comparative genomic hybridization (aCGH) and whole-genome sequence data.

Human subjects

All AML samples were obtained from a study at Washington University to identify genetic factors contributing to AML initiation and progression. Approval for these studies was obtained from the Washington University institutional review board. After obtaining written informed consent for the patients in accordance with the Declaration of Helsinki, a bone marrow sample and a 6-mm punch biopsy of skin (for analysis of matched normal cells) were obtained.

aCGH

A custom high-resolution aCGH platform (3×720K array; NimbleGen, Madison, WI) was generated to interrogate CNAs of all known miRNA genes at the time these studies were performed (835 miRNAs [miRBase, version 14.0] for the 30 t-AML samples and 1027 miRNAs [miRBase, version 15.0] for the 18 relapsed AML samples) and 44 miRNA processing genes (Table 1). Each gene and 40 kb of its flanking genome were interrogated with densely tiled probes at either 30 to 40 bp (miRNA genes) or 80 bp (miRNA processing genes). This array also contained dense tiling of probes designed to interrogate 170 DNA repair genes. In addition, probes uniformly spaced throughout the genome at approximately 8600-bp intervals were included. Two micrograms of genomic DNA from unfractionated bone marrow (tumor) and paired normal tissue (skin) was fragmented, labeled, and hybridized to the array as previously described.19  Log2 ratios of fluorescent intensity for tumor/skin were generated for each probe. Abnormal segments (ie, putative regions of CNAs) were identified by using segmentation algorithms from NimbleGen (segments) and Partek (segmentation). Segments generated by segmentation algorithms were prioritized on the basis of the number of probes and the log2 ratio of each segment (score = log10 [number of probes per segment] × log2 ratio) and manually reviewed, as previously described.19  To identify CNAs within miRNA genes and miRNA processing gene loci, plots of log2 values for each probe spanning the locus with 0.5 to 5 Mb flanking DNA were manually reviewed by 4 independent reviewers. Next, we collapsed contiguous segments generated by segmentation algorithms and identified boundaries by using segment boundaries and manual review. For 18 of the 30 t-AML patients, an independent iScan platform was available, and it confirmed 100% of the aCGH calls.

Table 1

miRNA processing genes

GeneChromosomeStartStop
ADAR 152 811 158 152 857 306 
DDX20 112 089 713 112 121 721 
EIF2C1 36 053 645 36 167 440 
ILF2 151 891 138 151 920 103 
LIN28 26 599 856 26 638 806 
PAPD3 52 651 535 52 801 331 
NOP58 202 828 760 202 886 629 
PACT 178 994 395 179 034 110 
TERC 170 955 092 170 975 542 
GAR1 110 946 115 110 975 342 
NPH2 177 499 072 177 523 567 
PAPD4 78 933 999 79 028 227 
RNASEN 31 426 359 31 578 039 
TERT 1 296 287 1 358 162 
XPO5 43 588 047 43 661 790 
EIF2C2 141 600 446 141 724 828 
PIWIL2 22 178 755 22 279 529 
TRIM32 118 479 402 118 513 400 
ADARB2 10 1 208 073 1 779 718 
PAPD1 10 30 628 736 30 688 273 
PIWI4 11 93 930 122 94 004 234 
HNRNPA1 12 52 950 755 52 975 297 
IPO8 12 30 663 189 30 750 018 
PIWI1 12 129 378 567 129 432 826 
RAN 12 129 912 736 129 937 316 
TARBP2 12 52 170 972 52 196 482 
DICER1 14 94 612 318 94 687 808 
NOP10 15 32 411 209 32 432 654 
TNRC6A 16 24 638 550 24 755 048 
DDX5 17 59 914 836 59 942 946 
GEMIN4 17 584 411 612 251 
FBL 19 7 502 445 7 541 588 
HNRNPL 19 45 006 934 45 038 894 
ILF3 19 44 008 868 44 044 819 
KHSRP 19 10 615 937 10 674 093 
PTBP1 19 6 354 119 6 385 822 
UPF1 19 738 392 773 327 
NOP56 20 18 793 744 18 850 039 
DDX17 22 2 571 254 2 597 039 
DGCR8 22 37 199 389 37 242 291 
NHP2L1 22 18 437 834 18 489 400 
PIWI3 22 40 389 883 40 424 859 
DKC1 23 435 001 23 510 683 
FMR1 153 634 225 153 669 157 
GeneChromosomeStartStop
ADAR 152 811 158 152 857 306 
DDX20 112 089 713 112 121 721 
EIF2C1 36 053 645 36 167 440 
ILF2 151 891 138 151 920 103 
LIN28 26 599 856 26 638 806 
PAPD3 52 651 535 52 801 331 
NOP58 202 828 760 202 886 629 
PACT 178 994 395 179 034 110 
TERC 170 955 092 170 975 542 
GAR1 110 946 115 110 975 342 
NPH2 177 499 072 177 523 567 
PAPD4 78 933 999 79 028 227 
RNASEN 31 426 359 31 578 039 
TERT 1 296 287 1 358 162 
XPO5 43 588 047 43 661 790 
EIF2C2 141 600 446 141 724 828 
PIWIL2 22 178 755 22 279 529 
TRIM32 118 479 402 118 513 400 
ADARB2 10 1 208 073 1 779 718 
PAPD1 10 30 628 736 30 688 273 
PIWI4 11 93 930 122 94 004 234 
HNRNPA1 12 52 950 755 52 975 297 
IPO8 12 30 663 189 30 750 018 
PIWI1 12 129 378 567 129 432 826 
RAN 12 129 912 736 129 937 316 
TARBP2 12 52 170 972 52 196 482 
DICER1 14 94 612 318 94 687 808 
NOP10 15 32 411 209 32 432 654 
TNRC6A 16 24 638 550 24 755 048 
DDX5 17 59 914 836 59 942 946 
GEMIN4 17 584 411 612 251 
FBL 19 7 502 445 7 541 588 
HNRNPL 19 45 006 934 45 038 894 
ILF3 19 44 008 868 44 044 819 
KHSRP 19 10 615 937 10 674 093 
PTBP1 19 6 354 119 6 385 822 
UPF1 19 738 392 773 327 
NOP56 20 18 793 744 18 850 039 
DDX17 22 2 571 254 2 597 039 
DGCR8 22 37 199 389 37 242 291 
NHP2L1 22 18 437 834 18 489 400 
PIWI3 22 40 389 883 40 424 859 
DKC1 23 435 001 23 510 683 
FMR1 153 634 225 153 669 157 

Coordinates are based on NCCI36/HG18 assembly.

Analysis of whole-genome sequencing data

We recently reported the sequence of 50 de novo AML genomes20  and 15 genomes of patients with secondary AML following myelodysplastic syndrome.21,22  The sequence data were analyzed to identify potential somatic CNAs as previously described.20  However, there is a high false-positive rate with CNAs identified in this fashion.21  Thus, we also performed aCGH by using the Affymetrix 6.0 SNP array to independently call somatic CNAs in all cases. We included for further analysis only those CNAs that were identified by both platforms.

Real time RT-PCR

Total RNA was reverse transcribed by using the TaqMan microRNA Reverse Transcription Kit per manufacturer’s instructions (Applied Biosystems). Real time reverse transcription-polymerase chain reaction (RT-PCR) for the indicated miRNA and RNU48 (as a control) were performed by using the relevant TaqMan MicroRNA assay.

Quantitative genomic PCR

Quantitative PCR was performed by using SYBR Green Master Mix (Applied Biosystems) and 50 ng of genomic DNA. PCR primers were designed to amplify MIR223 and MIR181b. MIR181b was included as a diploid gene copy number control, since no somatic CNAs of this gene were identified in any of the samples. MIR223 primers were 5′-CTTTACCTGCTTATCTTCAGGATCTCT-3′ and 5′-CGTACGCGCCCCCATCAGCACTCT-3′. MIR181b primers were 5′-GTCTCCCATCCCCTTCAGAT-3′ and 5′-TTTGCCTTTTCTAAAACATGCTC-3′. Technical triplicates were performed for each sample.

A total of 113 patients with AML were studied, including 50 cases of de novo AML (Table 2), 18 cases of relapsed de novo AML (Table 2), 15 cases of secondary AML following myelodysplastic syndrome (Table 3), and 30 cases of t-AML (Table 4). The median age of the de novo AML patients was 54.5 years (range, 21 to 82 years), and the median blast percentage was 75% (range, 35% to 100%). A normal karyotype was identified in 37 (74%) of 50 patients. The median age of the relapsed AML patients was 57.5 years (range, 24 to 77 years). The median blast percentage was 59% (range, 12% to 95%). A normal karyotype was identified in 6 (40%) of 15 patients with relapsed AML. The patients with secondary AML were older, with a median age of 66 years (range, 26 to 77 years). The median time to progression from myelodysplastic syndrome to AML was 400 days (range, 28 to 1751 days), and the median blast percentage in the bone marrow was 43% (range, 21% to 89%). A normal karyotype was identified in 43% of cases, and abnormalities involving chromosome 5 or 7 were observed in 43%. The median age of patients with t-AML was 59 years (range, 26 to 80 years). Twelve of the t-AML patients (40%) were treated for breast cancer, 6 (20%) for non-Hodgkin lymphoma, 2 (6.7%) for Hodgkin lymphoma, 2 (6.7%) for multiple myeloma, and 8 (20%) for other diseases. Most of the t-AML patients (76.7%) were treated for their primary cancer with a combination of chemotherapy that included topoisomerase inhibitors and/or alkylating agents. The median blast percentage in the bone marrow was 76% (range, 31% to 95%). Cytogenetic analysis revealed −5/−5q and/or −7 in seven patients (23%), translocations involving chromosome 11q23 (MLL gene rearrangement) in 6 patients (20.0%), and a normal karyotype in 6 patients (20%).

Table 2

Clinical characteristics of the patients with de novo or relapsed AML

UPNAML diagnosisFAB subtypeSexAge, y*% BM blastCytogenetics
933124 De novo M1 57 100 46,XX[20] 
807970 De novo M1 38 86 46,XY[20] 
123172 De novo M1 56 90 46, XY[20] 
831711 De novo M1 57 64 46, XX[19] 
849660 De novo M1 22 71 46,XY[30] 
808642 De novo M1 61 49 46,XY[20] 
509754 De novo M1 21 91 46, XX[20] 
327733 De novo M1 32 94 46, XX[20] 
709968 De novo M3 25 91 46,XY,t(15;17)(q22;q21)[20] 
863018 De novo M3 62 82 46,XY,t(15;17)(q22:q21)[11]/46,XY[9] 
478908 De novo M3 50 74 46,XY,t(15;17)(q22;q21)[20] 
344551 De novo M3 48 65 46,XY,t(15;17)(q22:q21)[11]/46,XY[8] 
673778 De novo M3 53 42 46,XY,t(15;17)(q22;q21)[19]/46,XY[1] 
321258 De novo M3 31 40 46,XX,t(15;17)(q22;q21)[11]/46,XX[9] 
758168 De novo M3 25 93 46,XX,t(15;17)(q22;q21)[20] 
455499 De novo M3 29 85 46,XX,t(15;17)(q22;q21)[12]/46,XX[8] 
103342 De novo M2 61 43 46, XX[20] 
113971 De novo M2 57 43 46, XX[15] 
142074 De novo M4 60 89 46, XY[15] 
179223 De novo M2 82 53 46, XX[20] 
224143 De novo M1 67 76 46, XX[20] 
225373 De novo M2 71 70 46, XX[14] 
246634 De novo M4 79 58 46,XY[20] 
254137 De novo M2 31 63 46, XX[20] 
273919 De novo M2 25 56 46, XY[20] 
335640 De novo M5 67 85 46, XX[20] 
400220 De novo M4 34 71 46, XX[20] 
426980 De novo M2 68 64 46, XY[20] 
440422 De novo M0 69 82 46, XY[20] 
445045 De novo M2 75 63 46, XY[20] 
452198 De novo M5 55 97 46, XY[15] 
456892 De novo M4 58 58 46, XY[18] 
545259 De novo M1 30 86 46, XX[20] 
548327 De novo M1 51 85 46, XY[20] 
573988 De novo M4 67 75 46, XX[16] 
700717 De novo M0 45 75 46,XY[20] 
702808 De novo M5 75 41 46,XX[18] 
753374 De novo M2 29 45 46,XY,15pstk+[20] 
775109 De novo M5 45 81 46,XY[20] 
804168 De novo M1 53 86 46,XY[20] 
816067 De novo M5 35 87 46, XX[20] 
817156 De novo M2 54 67 46,XY[19] 
869586 De novo M4 23 51 46,XY[20] 
906708 De novo M4 76 91 46,XX[20] 
907786 De novo M5 81 53 46,XX[20] 
991612 De novo M2 63 35 46,XY[20] 
202127 De novo M3 68 85 46,XX,t(15;17)(q22;q21)[20] 
529205 De novo M3 59 79 46,XY,t(15;17)(q22;q21)[20] 
501944 De novo M3 40 90 46,XX,t(15;17)(q22;q21.1)[19]/47,idem,+8 [1] 
943309 De novo M3 35 90 47,XY,del(7)(q22),+8,t(15;17)(q22;q21)[18]/46,XY,del(7)(q22),t(15;17)(q22;q21)[2] 
142074 Relapsed M4 61 65 46, XY[15] 
255108 Relapsed M0 62 80 47,XY,+8 [19] 
375182 Relapsed M5 57 79 Not available 
387919 Relapsed M1 58 20 46, XY, +3 [3], 46,XY [17] 
400220 Relapsed M4 35 60 46, XX[20] 
426980 Relapsed M2 71 12 46, XY[20] 
452198 Relapsed M5 57 20 46, XY[15] 
573988 Relapsed M4 68 54 Failed 
593890 Relapsed M2 36 95 47,XY,+21 [6]/46,XY[13] 
708512 Relapsed M4 65 38 50 XX, +4,+6,+8, +19 [4]/ 47 XX, + i4(q10)[12]. 
758168 Relapsed M3 27 92 46,XX,t(15;17)(q22;q21)[20] 
804168 Relapsed M1 54 81 46,Y,t(X;6)(q22;q23)?t(1;12;7;3)(p36.1;q13;p11.2;p21)[17],46,XY[3],ish,der3,t(3,;17)(p53+),de(12)t(1;12)(1pter+) 
817156 Relapsed M2 55 58 46,XY[19] 
869586 Relapsed M4 24 54 Failed 
869922 Relapsed M2 56 50 46,XX[20] 
923966 Relapsed M5 61 79 47,XY,t(9;11)(p22;q23),+8[7]/45,XY,t(9;11)(p22;q23),-8[7]/46,XY[4] 
962561 Relapsed M4 77 32 46,XX,+13,-21[3],46,XX[17] 
972783 Relapsed M0 72 66 46,XY,der(15)t(15;17)(p11.2q11.2),der(17)t(15;17)del(17)p(1.3)[3]/47,idem,+mar[1] 
UPNAML diagnosisFAB subtypeSexAge, y*% BM blastCytogenetics
933124 De novo M1 57 100 46,XX[20] 
807970 De novo M1 38 86 46,XY[20] 
123172 De novo M1 56 90 46, XY[20] 
831711 De novo M1 57 64 46, XX[19] 
849660 De novo M1 22 71 46,XY[30] 
808642 De novo M1 61 49 46,XY[20] 
509754 De novo M1 21 91 46, XX[20] 
327733 De novo M1 32 94 46, XX[20] 
709968 De novo M3 25 91 46,XY,t(15;17)(q22;q21)[20] 
863018 De novo M3 62 82 46,XY,t(15;17)(q22:q21)[11]/46,XY[9] 
478908 De novo M3 50 74 46,XY,t(15;17)(q22;q21)[20] 
344551 De novo M3 48 65 46,XY,t(15;17)(q22:q21)[11]/46,XY[8] 
673778 De novo M3 53 42 46,XY,t(15;17)(q22;q21)[19]/46,XY[1] 
321258 De novo M3 31 40 46,XX,t(15;17)(q22;q21)[11]/46,XX[9] 
758168 De novo M3 25 93 46,XX,t(15;17)(q22;q21)[20] 
455499 De novo M3 29 85 46,XX,t(15;17)(q22;q21)[12]/46,XX[8] 
103342 De novo M2 61 43 46, XX[20] 
113971 De novo M2 57 43 46, XX[15] 
142074 De novo M4 60 89 46, XY[15] 
179223 De novo M2 82 53 46, XX[20] 
224143 De novo M1 67 76 46, XX[20] 
225373 De novo M2 71 70 46, XX[14] 
246634 De novo M4 79 58 46,XY[20] 
254137 De novo M2 31 63 46, XX[20] 
273919 De novo M2 25 56 46, XY[20] 
335640 De novo M5 67 85 46, XX[20] 
400220 De novo M4 34 71 46, XX[20] 
426980 De novo M2 68 64 46, XY[20] 
440422 De novo M0 69 82 46, XY[20] 
445045 De novo M2 75 63 46, XY[20] 
452198 De novo M5 55 97 46, XY[15] 
456892 De novo M4 58 58 46, XY[18] 
545259 De novo M1 30 86 46, XX[20] 
548327 De novo M1 51 85 46, XY[20] 
573988 De novo M4 67 75 46, XX[16] 
700717 De novo M0 45 75 46,XY[20] 
702808 De novo M5 75 41 46,XX[18] 
753374 De novo M2 29 45 46,XY,15pstk+[20] 
775109 De novo M5 45 81 46,XY[20] 
804168 De novo M1 53 86 46,XY[20] 
816067 De novo M5 35 87 46, XX[20] 
817156 De novo M2 54 67 46,XY[19] 
869586 De novo M4 23 51 46,XY[20] 
906708 De novo M4 76 91 46,XX[20] 
907786 De novo M5 81 53 46,XX[20] 
991612 De novo M2 63 35 46,XY[20] 
202127 De novo M3 68 85 46,XX,t(15;17)(q22;q21)[20] 
529205 De novo M3 59 79 46,XY,t(15;17)(q22;q21)[20] 
501944 De novo M3 40 90 46,XX,t(15;17)(q22;q21.1)[19]/47,idem,+8 [1] 
943309 De novo M3 35 90 47,XY,del(7)(q22),+8,t(15;17)(q22;q21)[18]/46,XY,del(7)(q22),t(15;17)(q22;q21)[2] 
142074 Relapsed M4 61 65 46, XY[15] 
255108 Relapsed M0 62 80 47,XY,+8 [19] 
375182 Relapsed M5 57 79 Not available 
387919 Relapsed M1 58 20 46, XY, +3 [3], 46,XY [17] 
400220 Relapsed M4 35 60 46, XX[20] 
426980 Relapsed M2 71 12 46, XY[20] 
452198 Relapsed M5 57 20 46, XY[15] 
573988 Relapsed M4 68 54 Failed 
593890 Relapsed M2 36 95 47,XY,+21 [6]/46,XY[13] 
708512 Relapsed M4 65 38 50 XX, +4,+6,+8, +19 [4]/ 47 XX, + i4(q10)[12]. 
758168 Relapsed M3 27 92 46,XX,t(15;17)(q22;q21)[20] 
804168 Relapsed M1 54 81 46,Y,t(X;6)(q22;q23)?t(1;12;7;3)(p36.1;q13;p11.2;p21)[17],46,XY[3],ish,der3,t(3,;17)(p53+),de(12)t(1;12)(1pter+) 
817156 Relapsed M2 55 58 46,XY[19] 
869586 Relapsed M4 24 54 Failed 
869922 Relapsed M2 56 50 46,XX[20] 
923966 Relapsed M5 61 79 47,XY,t(9;11)(p22;q23),+8[7]/45,XY,t(9;11)(p22;q23),-8[7]/46,XY[4] 
962561 Relapsed M4 77 32 46,XX,+13,-21[3],46,XX[17] 
972783 Relapsed M0 72 66 46,XY,der(15)t(15;17)(p11.2q11.2),der(17)t(15;17)del(17)p(1.3)[3]/47,idem,+mar[1] 

BM, bone marrow; F, female; FAB, French-American-British; M, male; UPN, unique patient number.

*

Age at presentation of initial diagnosis of AML.

Table 3

Clinical characteristics of patients with secondary AML

UPNSexAge, yMDS FABTime to AML, days% BM blastCytogenetics
461282 70 RAEB 1751 69 45,XY,del(5)(q22q33),-17, del(20)(q11.2)[14]/46,XY[4] 
667720 67 RAEB 644 Not done 46,XX[19]/45,XX,-7[1] 
859640 64 RA 252 25 47,XX,+13[3]/46,XX[17] 
610184 46 RA 314 38 41-44,XX,add(1)(p36.3),del(5)(q13q33),-7,-13,dic(16;21)(p13.3;p11.2),add(17)(p13), −18, −22, +mar[cp17]/84,idemx2[cp2]/44,XX,-17, −22[1] 
182896 77 RA 1047 51 47,XY,add(4)(p16),del(5)(q15q33), −7,+8,del(9)(q22),+22,+2mar[1]/54,XY,+3,+8,+8,+9,-12,+15,+19,+20,-21,+22,+2-3mar[cp11]/46,XY[8] 
266395 64 RAEB 75 66 46,XY[17] 
288033 30 RAEB 28 43 46,XX[20] 
298273 26 RAEB-T 131 35 46,XY[20] 
689147 69 RAEB 421 Not done 48,XX,+1,del(5)(q15;q33),+11,i(22)(q10)[20] 
891669 66 RA 323 75 46,XY,inv(3)(q21q26.2)[20] 
169510 58 RAEB 796 28 46,XY[20] 
989382 69 RA 1332 89 Unknown 
178647 61 RA 368 23 46,XY[20] 
759134 67 RA 400 21 46,XY[20] 
838538 67 RAEB 437 51 40∼46,XY,add(X)(p22.1),-2,del(5)(q22q35), del(7)(q22),+8,-12,-16,+mar[19]/46,XY[1] 
UPNSexAge, yMDS FABTime to AML, days% BM blastCytogenetics
461282 70 RAEB 1751 69 45,XY,del(5)(q22q33),-17, del(20)(q11.2)[14]/46,XY[4] 
667720 67 RAEB 644 Not done 46,XX[19]/45,XX,-7[1] 
859640 64 RA 252 25 47,XX,+13[3]/46,XX[17] 
610184 46 RA 314 38 41-44,XX,add(1)(p36.3),del(5)(q13q33),-7,-13,dic(16;21)(p13.3;p11.2),add(17)(p13), −18, −22, +mar[cp17]/84,idemx2[cp2]/44,XX,-17, −22[1] 
182896 77 RA 1047 51 47,XY,add(4)(p16),del(5)(q15q33), −7,+8,del(9)(q22),+22,+2mar[1]/54,XY,+3,+8,+8,+9,-12,+15,+19,+20,-21,+22,+2-3mar[cp11]/46,XY[8] 
266395 64 RAEB 75 66 46,XY[17] 
288033 30 RAEB 28 43 46,XX[20] 
298273 26 RAEB-T 131 35 46,XY[20] 
689147 69 RAEB 421 Not done 48,XX,+1,del(5)(q15;q33),+11,i(22)(q10)[20] 
891669 66 RA 323 75 46,XY,inv(3)(q21q26.2)[20] 
169510 58 RAEB 796 28 46,XY[20] 
989382 69 RA 1332 89 Unknown 
178647 61 RA 368 23 46,XY[20] 
759134 67 RA 400 21 46,XY[20] 
838538 67 RAEB 437 51 40∼46,XY,add(X)(p22.1),-2,del(5)(q22q35), del(7)(q22),+8,-12,-16,+mar[19]/46,XY[1] 

FAB, French-American-British; MDS, myelodysplastic syndrome; RA, refractory anemia; RAEB, refractory anemia with excess blasts; RAEB-T, refractory anemia with excess blasts in transformation.

Table 4

Clinical characteristics of patients with t-AML

UPNSexAge, yPrior disease or cancerAlkXRTTopoOther chemoLatency (years)*% BM blastCytogenetics
180365 54 AML ∼7.8 83 47,XX,+8[18]/46,XX[2] 
180866 66 Multiple myeloma 3.2 Not done 47,XY,+i(8)(q10)[3] / 47,XY,+8[17] 
189941 42 Ovarian/breast 5.6 76 45, XX,add(3)(q27),del(3)(q12),-4,del(5)(q12q33),-7,+add(18)(p11.1),+mar,+mar1[cp19]/46,XX[1] 
205133 59 Breast 7.0 36 46,XX[30] 
266608 80 Renal cell carcinoma 6.4 33 46,XY[20] 
317821 42 Non-Hodgkin lymphoma 1.1 80 36-46,XX,+der(1;7)(p10;q10),add(1)(q42),del(7)(q11.2),der(?)t(?;7)(?::7q11.2->7qter)[cp10] 
377512 74 Non-Hodgkin lymphoma 2.4 31 38-51,XX,add(1)(p13),del(1)(p36.1),del(1)(q12),der(2)t(2;15)(q37;q11.2), add(3)(q29)-5,del(7)(q31),add(8)(p23),r(8)(?p22q24),add(13)(p11.2), iso(13)(q10),add(19)(q13.4),add(20)(p?13),iso(21)(q10)[cp20] 
458613 28 Hodgkin lymphoma 1.5 90 46,XY,inv(16)(p13.1q22)[18] / 46,XY[2] 
476081 68 Breast 1.6 66 46,XX[20] 
476204 51 Breast 6.8 87 46,XX[20] 
482711 57 Breast 11.8 44 44-45,XX,der(4)t(4;?)(q22;?)[3],-5[10],add(6)(q13)[6, del(7)(q22)[10], del(12)(p11.2)[4],-17[6],+mar[4],+2mar[3],add(19)(q13)[4] / 46,XX[10] 
501254 67 Breast 1.4 95 46,XX,t(11;19)(q23;p13)[16] / 47,idem,+8[4] 
514901 63 Breast 1.15 95 46,XX,t(6;11)(q27;q23)[20]/46,XX[7] 
530447 43 Hodgkin lymphoma 12.8 40 44,XY,-3,-5,-7,add(9)(p21),add(17)(q25),+mar1[8] / 45,sl,+mar2[11]/48,sdl1,+21,+22,+r[1] 
548417 77 Breast 7.3 95 46,XX[20] 
557772 60 Multiple myeloma 3.3 47 49,XY,-5,+8,+11,-17,-17,+21,+22,+2mar[19] / 50,idem,+mar[1] 
572162 59 Breast 4.75 79 46,XX,t(3;12)(p13;p13)[5]/46,XX[15] 
644242 56 Breast 4.0 62 46,XX,t(8;21)(q22;q22)[19] 
658208 50 Multiple sclerosis 2.8 94 45,X,-Y,t(8;21)(q22;q22)[19] 
706395 45 Lung 1.9 90 46,XX,t(9;11)(p21;q23)[16] / 46,idem,der(1)(t(1;?)(p13;?)[2] / 46,XX[2] 
751407 74 Rheumatoid arthritis 1.5 61 85,XXY,-Y,-2,-5,-7,-16,-17,-18 [10]/46,XY[10] 
779828 79 Prostate 2.1 76 46,XY[20] 
811184 26 Non-Hodgkin lymphoma NK 56 42∼46, XY, der(11)t(11;15)(p11.2;q11.1), t(11;19)(q23;p13), del(13)(q22), −15, add(22)(q11.1)[cp7]/46,XY[6] 
856024 26 Non-Hodgkin lymphoma 1.1 90 46,XY,der(12)t(1;12)(q25;p13),add(12)(q24.2)[18] / 46,XY[2] 
860923 71 Non-Hodgkin lymphoma 6.9 71 92,XXXX[6] / 46,XX[14] 
864484 39 Testicular 1.1 92 42-48,XY,-2,inv(7)(p15q11.2),-11,-13,del(13)(q12q21),-17,der(19)t(?;19)(?;p13.1),+mar1,+mar2,+mar3,+mar4,+mar5[cp20] 
925964 58 Uterine 2.2 38 46,XX,inv(11)(p15q22∼23)[19] / 46,XX[1] 
942008 69 Non-Hodgkin lymphoma 13.3 67 45,der(X)t(X;16)(p22.1;p13.2),add(X)(q26),Y,t(3;9)(p13;q34),del(5)(q13q31),inv(6)(p21.1q25),der(7)(7pter->q21∼q22;?),der(16)t(X;16)(p22.1;p13.2)[2] / 92,der(X)t(X;16)(p22.1;p13.2),add(X)(q26)x2,Y,t(3;9)(p13;q34)x2,del(5)(q13q31)x2,inv(6)(p21.1q25)x2,der(7)(7pter->q21∼q22;?)x2,der(16)t(X;16)(p22.1;p13.2)x2[1] / 46,XY[27] 
982895 47 Breast ∼3 93 46,XX,t(9;11)(p22;q23)[7]/47, idem, +8[13] 
983545 61 Breast 1.4 41 49,XX,ins(6)(?q13?),+8,+8,t(9;11)(p22;q23),+der(9)t(9;11)(p22;q23),del(13)(q12q14)[7] / 49,XX,idem,+del(13)(q12q14)[7] / 46,XX[5] 
UPNSexAge, yPrior disease or cancerAlkXRTTopoOther chemoLatency (years)*% BM blastCytogenetics
180365 54 AML ∼7.8 83 47,XX,+8[18]/46,XX[2] 
180866 66 Multiple myeloma 3.2 Not done 47,XY,+i(8)(q10)[3] / 47,XY,+8[17] 
189941 42 Ovarian/breast 5.6 76 45, XX,add(3)(q27),del(3)(q12),-4,del(5)(q12q33),-7,+add(18)(p11.1),+mar,+mar1[cp19]/46,XX[1] 
205133 59 Breast 7.0 36 46,XX[30] 
266608 80 Renal cell carcinoma 6.4 33 46,XY[20] 
317821 42 Non-Hodgkin lymphoma 1.1 80 36-46,XX,+der(1;7)(p10;q10),add(1)(q42),del(7)(q11.2),der(?)t(?;7)(?::7q11.2->7qter)[cp10] 
377512 74 Non-Hodgkin lymphoma 2.4 31 38-51,XX,add(1)(p13),del(1)(p36.1),del(1)(q12),der(2)t(2;15)(q37;q11.2), add(3)(q29)-5,del(7)(q31),add(8)(p23),r(8)(?p22q24),add(13)(p11.2), iso(13)(q10),add(19)(q13.4),add(20)(p?13),iso(21)(q10)[cp20] 
458613 28 Hodgkin lymphoma 1.5 90 46,XY,inv(16)(p13.1q22)[18] / 46,XY[2] 
476081 68 Breast 1.6 66 46,XX[20] 
476204 51 Breast 6.8 87 46,XX[20] 
482711 57 Breast 11.8 44 44-45,XX,der(4)t(4;?)(q22;?)[3],-5[10],add(6)(q13)[6, del(7)(q22)[10], del(12)(p11.2)[4],-17[6],+mar[4],+2mar[3],add(19)(q13)[4] / 46,XX[10] 
501254 67 Breast 1.4 95 46,XX,t(11;19)(q23;p13)[16] / 47,idem,+8[4] 
514901 63 Breast 1.15 95 46,XX,t(6;11)(q27;q23)[20]/46,XX[7] 
530447 43 Hodgkin lymphoma 12.8 40 44,XY,-3,-5,-7,add(9)(p21),add(17)(q25),+mar1[8] / 45,sl,+mar2[11]/48,sdl1,+21,+22,+r[1] 
548417 77 Breast 7.3 95 46,XX[20] 
557772 60 Multiple myeloma 3.3 47 49,XY,-5,+8,+11,-17,-17,+21,+22,+2mar[19] / 50,idem,+mar[1] 
572162 59 Breast 4.75 79 46,XX,t(3;12)(p13;p13)[5]/46,XX[15] 
644242 56 Breast 4.0 62 46,XX,t(8;21)(q22;q22)[19] 
658208 50 Multiple sclerosis 2.8 94 45,X,-Y,t(8;21)(q22;q22)[19] 
706395 45 Lung 1.9 90 46,XX,t(9;11)(p21;q23)[16] / 46,idem,der(1)(t(1;?)(p13;?)[2] / 46,XX[2] 
751407 74 Rheumatoid arthritis 1.5 61 85,XXY,-Y,-2,-5,-7,-16,-17,-18 [10]/46,XY[10] 
779828 79 Prostate 2.1 76 46,XY[20] 
811184 26 Non-Hodgkin lymphoma NK 56 42∼46, XY, der(11)t(11;15)(p11.2;q11.1), t(11;19)(q23;p13), del(13)(q22), −15, add(22)(q11.1)[cp7]/46,XY[6] 
856024 26 Non-Hodgkin lymphoma 1.1 90 46,XY,der(12)t(1;12)(q25;p13),add(12)(q24.2)[18] / 46,XY[2] 
860923 71 Non-Hodgkin lymphoma 6.9 71 92,XXXX[6] / 46,XX[14] 
864484 39 Testicular 1.1 92 42-48,XY,-2,inv(7)(p15q11.2),-11,-13,del(13)(q12q21),-17,der(19)t(?;19)(?;p13.1),+mar1,+mar2,+mar3,+mar4,+mar5[cp20] 
925964 58 Uterine 2.2 38 46,XX,inv(11)(p15q22∼23)[19] / 46,XX[1] 
942008 69 Non-Hodgkin lymphoma 13.3 67 45,der(X)t(X;16)(p22.1;p13.2),add(X)(q26),Y,t(3;9)(p13;q34),del(5)(q13q31),inv(6)(p21.1q25),der(7)(7pter->q21∼q22;?),der(16)t(X;16)(p22.1;p13.2)[2] / 92,der(X)t(X;16)(p22.1;p13.2),add(X)(q26)x2,Y,t(3;9)(p13;q34)x2,del(5)(q13q31)x2,inv(6)(p21.1q25)x2,der(7)(7pter->q21∼q22;?)x2,der(16)t(X;16)(p22.1;p13.2)x2[1] / 46,XY[27] 
982895 47 Breast ∼3 93 46,XX,t(9;11)(p22;q23)[7]/47, idem, +8[13] 
983545 61 Breast 1.4 41 49,XX,ins(6)(?q13?),+8,+8,t(9;11)(p22;q23),+der(9)t(9;11)(p22;q23),del(13)(q12q14)[7] / 49,XX,idem,+del(13)(q12q14)[7] / 46,XX[5] 

Alk, alkylator chemotherapy; chemo, chemotherapy; N, no; Topo, topoisomerase chemotherapy; XRT, radiation therapy; Y, yes.

*

Latency, time (years) from treatment of original cancer.

We interrogated paired tumor/normal samples for somatic CNAs by using aCGH or whole-genome sequencing data. The t-AML and relapsed AML cases were analyzed by using a custom CGH array that contained densely spaced oligomers (every 30 to 40 bp spacing) for all miRNA genes that were identified in miRBase at the time this study was performed (835 miRNAs in miRBase, version 14.0, were included in the arrays for the 30 t-AML samples and 1027 miRNAs in miRBase, version 15.0, for the 18 relapsed de novo AML samples). A total of 40 kb of genomic DNA flanking the miRNA precursor gene was targeted. We also included probes for 44 genes involved in miRNA processing (Table 1). In each case, genomic DNA isolated from a skin biopsy was used to distinguish inherited CNAs from somatic CNAs. To call a somatic CNA, we required that a minimum of 25 contiguous probes show differential hybridization. Thus, for miRNA genes, we theoretically should be able to identify somatic CNAs of approximately 1 kb. A total of 64 CNAs that were not apparent by routine cytogenetics were identified in 14 patients (all with t-AML). CNAs were judged to be cytogenetically apparent if any part of the contiguous segment was contained within a chromosomal loss, gain, or interstitial chromosomal deletion identified by routine metaphase cytogenetics. For interstitial deletions, coordinates of the cytogenetic banding were estimated by using National Center for Biotechnology Information (NCBI) Map Viewer, Build 36. Twenty-six of these somatic CNAs, identified in 11 of the 48 patients, contained one or more miRNA genes (Table 5). No cytogenetically unapparent somatic CNAs involving miRNA processing genes were identified in any case.

Table 5

CNAs containing miRNA genes not identified by routine cytogenetics

UPNAML DiagnosisChrBreakpoint startBreakpoint endCallCNA (bp)miRNA genes in the CNA
327733 De novo 16 30 514 514 31 420 587 906 073 4519, 762 
113971 De novo 24 395 064 25 807 518 1 412 454 1301 
869586 De novo 17 26 063 968 27 437 770 1 373 802 4733, 4724, 193a, 4725, 365b 
906708 De novo 81 151 141 87 703 853 6 552 712 7-1 
169510 Secondary 118 096 26 790 111 26 672 015 6720, 4645, 3691, 5683, 5689, 4639, 548a-1 
169510 Secondary 26 790 111 48 691 459 21 901 348 3143, 877, 4640, 4646, 1236, 6721, 3135b, 219-1, 5004, 3934, 1275, 5690, 3925, 4462, 4641, 4647, 4642, 586 
182896 Secondary 12 2 128 232 78 142 425 76 014 193 31 miRNAs 
182896 Secondary 12 79 457 892 87 807 120 8 349 228 617, 618, 4699 
182896 Secondary 12 95 700 444 121 346 369 25 645 925 1251, 135a-2, 4495, 4303, 1827, 3652, 3922, 4496, 619, 4497, 3657, 1302-1,620, 4472-2, 1178, 4498, 4700 
182896 Secondary 12 121 996 058 123 901 827 1 905 769 4304, 3908 
182896 Secondary 17 25 505 826 27 326 775 1 820 949 4733, 4724, 193a, 4725, 365b 
182896 Secondary 21 13 395 102 33 441 194 20 046 092 3156-3, 3118-5, 99a, 7c, 125b-2, 548x, 6130, 155, 4759, 4327 
182896 Secondary 21 36 524 064 46 921 386 10 397 322 6508, 4760, 3197, 5692b, 6070 
182896 Secondary 57 427 648 57 427 648 3690-2, 6089-2 
610184 Secondary 2 784 13 404 817 13 402 033 4261, 4429, 548s, 4262, 3681, 3125 
610184 Secondary 27 745 709 30 891 590 3 145 881 4263 
610184 Secondary 1 273 675 2 400 101 1 126 426 4655 
610184 Secondary 17 526 5 781 507 5 780 981 3183, 22, 132, 212, 1253 
838538 Secondary 61 736 225 115 792 225 054 056 121 miRNAs 
838538 Secondary 17 527 51 162 464 51 161 937 53 miRNAs 
838538 Secondary 17 51 162 465 78 643 088 27 480 623 33 miRNAs 
891669 Secondary 17 26 117 586 27 302 527 1 184 941 4733, 4724, 193a, 4725, 365b 
180365 Therapy-related 123 372 048 132 969 208 9 597 160 663b, 4783, 4784 
180365 Therapy-related 121 883 092 138 624 717 16 741 625 4633, 4460, 3936, 1289-2, 3661, 4461, 5692c-1, 874 
189941 Therapy-related 169 461 120 170 271 699 1 513 091 551b 
189941 Therapy-related 171 702 102 173 816 191 2 114 089 569 
189941 Therapy-related 12 11 708 326 22 796 431 11 088 105 1244-2, 613, 614, 3974 
317821 Therapy-related 120 308 171 220 764 934 100 456 763 3118-1, 3118-2, 3118-3, 6077-1, 5087, 6077-2, 4257, 554, 5698, 190b, 4258, 92b, 555, 9-1, 9-5b, 765, 4259, 5187, 4654, 556, 3658, 921, 1255b-2, 557, 3119-1, 3119-2, 1295, 214, 3120, 199a-2, 488, 4424, 3121, 4426, 1278, 4735, 181b-1, 181a-1, 5191, 1231, 135b, 29c, 29b-2, 205, 4260, 3122, 215, 194-1, 664 
317821 Therapy-related 144 186 839 199 381 715 55 194 876 5186, 3919, 15b, 16-2, 1263, 551b, 569, 4789, 4448, 1224, 5588, 548aq, 1248, 28, 944, 3137, 570, 4797, 922 
377512 Therapy-related 236 856 627 241 034 230 4 177 603 4440, 4441, 4269, 2467, 4786 
377512 Therapy-related 15 18 422 770 22 846 333 4 423 563 3118-4, 5701-1, 3118-6, 5701-2, 1268a, 4509-1, 4508 
482711 Therapy-related 73 561 217 77 720 182 4 158 965 4282, 4463 
482711 Therapy-related 19 7 917 000 8 565 000 648 000 4999 
482711 Therapy-related 19 9 458 030 12 415 444 2 957 414 5589, 4322, 1181, 1238, 638, 4748, 199a-1 
482711 Therapy-related 19 13 331 909 19 078 761 5 746 852 24-2, 27a, 23a, 181c, 181d, 639, 1470, 3188, 3189 
530447 Therapy-related 28 278 165 29 708 951 1 430 786 876, 873 
557772 Therapy-related 21 9 892 286 46 915 712 37 023 426 3156-3, 3118-5, 99a, let-7c, 125b-2, 548x, 6130, 155, 4759, 4327, 6501, 802, 6508, 4760, 3197, 5692b, 6070 
706395 Therapy-related 10 42 100 384 57 162 870 15 062 486 5100, 3156-1, 4294, 605, 548f-1 
811184 Therapy-related 188 612 922 247 171 197 58 558 275 4426, 1278, 4735, 181b-1, 181a-1, 5191, 1231, 135b, 29c, 29b-2, 205, 4260, 3122, 215, 194-1, 664, 320b, 4742, 5008, 3620, 4666a, 1182, 4427, 4671, 4753, 1537, 4428, 3123, 4677, 3916, 3124 
811184 Therapy-related 12 33 393 16 168 160 16 134 767 3649, 200c, 141, 1244-3, 613, 614 
811184 Therapy-related 13 40 292 732 71 225 257 30 932 525 3168, 5006, 3613, 16-1, 15a, 5693, 4703, 759, 1297, 5007, 3169, 548x, 4704 
811184 Therapy-related 17 42 399 786 78 637 123 36 237 337 5089, 152, 1203, 10a, 196a-1, 3185, 6129, 6165, 3614, 142, 4736, 454, 301a, 4729, 21, 4737, 633, 3064, 5047, 6080, 4315-2, 634, 548d-2, 635, 4524a, 3615, 3678, 4738, 636, 4316, 4739, 1268b, 4730, 657, 3065, 338, 1250, 4740, 3186, 4525 
856024 Therapy-related 120 321 638 247 171 198 126 849 560 3118-1, 3118-2, 3118-3, 6077-1, 5087, 6077-2, 4257, 554, 5698, 190b, 4258, 92b, 555, 9-1, 9-5b, 765, 4259, 5187, 4654, 556, 3658, 921, 1255b-2, 557, 3119-1, 3119-2, 1295, 214, 3120, 199a-2, 488, 4424, 3121, 4426, 1278, 4735, 181b-1, 181a-1, 5191, 1231, 135b, 29c, 29b-2, 205, 4260, 3122, 215, 194-1, 664, 320b, 4742, 5008, 3620, 4666a, 1182, 4427, 4671, 4753, 1537, 4428, 3123, 4677, 3916, 3124 
856024 Therapy-related 12 33 393 17 253 192 17 219 799 200c, 141, 1244-3, 613, 614 
856024 Therapy-related 12 120 756 138 132 283 286 11 527 148 4304, 3908, 5188, 4419b, 3612 
856024 Therapy-related 17 44 017 170 78 637 124 34 619 954 196a-1, 3185, 6129, 6165, 3614, 142, 4736, 454, 301a, 4729, 21, 4737, 633, 3064, 5047, 6080, 4315-2, 634, 548d-2, 635, 4524a, 3615, 3678, 4738, 636, 4316, 4739, 1268b, 4730, 657, 3065, 338, 1250, 4740, 3186, 4525 
864484 Therapy-related 14 53 281 577 57 637 143 4 355 566 5580, 4308 
864484 Therapy-related 64 736 865 65 165 635 428 770 223 
UPNAML DiagnosisChrBreakpoint startBreakpoint endCallCNA (bp)miRNA genes in the CNA
327733 De novo 16 30 514 514 31 420 587 906 073 4519, 762 
113971 De novo 24 395 064 25 807 518 1 412 454 1301 
869586 De novo 17 26 063 968 27 437 770 1 373 802 4733, 4724, 193a, 4725, 365b 
906708 De novo 81 151 141 87 703 853 6 552 712 7-1 
169510 Secondary 118 096 26 790 111 26 672 015 6720, 4645, 3691, 5683, 5689, 4639, 548a-1 
169510 Secondary 26 790 111 48 691 459 21 901 348 3143, 877, 4640, 4646, 1236, 6721, 3135b, 219-1, 5004, 3934, 1275, 5690, 3925, 4462, 4641, 4647, 4642, 586 
182896 Secondary 12 2 128 232 78 142 425 76 014 193 31 miRNAs 
182896 Secondary 12 79 457 892 87 807 120 8 349 228 617, 618, 4699 
182896 Secondary 12 95 700 444 121 346 369 25 645 925 1251, 135a-2, 4495, 4303, 1827, 3652, 3922, 4496, 619, 4497, 3657, 1302-1,620, 4472-2, 1178, 4498, 4700 
182896 Secondary 12 121 996 058 123 901 827 1 905 769 4304, 3908 
182896 Secondary 17 25 505 826 27 326 775 1 820 949 4733, 4724, 193a, 4725, 365b 
182896 Secondary 21 13 395 102 33 441 194 20 046 092 3156-3, 3118-5, 99a, 7c, 125b-2, 548x, 6130, 155, 4759, 4327 
182896 Secondary 21 36 524 064 46 921 386 10 397 322 6508, 4760, 3197, 5692b, 6070 
182896 Secondary 57 427 648 57 427 648 3690-2, 6089-2 
610184 Secondary 2 784 13 404 817 13 402 033 4261, 4429, 548s, 4262, 3681, 3125 
610184 Secondary 27 745 709 30 891 590 3 145 881 4263 
610184 Secondary 1 273 675 2 400 101 1 126 426 4655 
610184 Secondary 17 526 5 781 507 5 780 981 3183, 22, 132, 212, 1253 
838538 Secondary 61 736 225 115 792 225 054 056 121 miRNAs 
838538 Secondary 17 527 51 162 464 51 161 937 53 miRNAs 
838538 Secondary 17 51 162 465 78 643 088 27 480 623 33 miRNAs 
891669 Secondary 17 26 117 586 27 302 527 1 184 941 4733, 4724, 193a, 4725, 365b 
180365 Therapy-related 123 372 048 132 969 208 9 597 160 663b, 4783, 4784 
180365 Therapy-related 121 883 092 138 624 717 16 741 625 4633, 4460, 3936, 1289-2, 3661, 4461, 5692c-1, 874 
189941 Therapy-related 169 461 120 170 271 699 1 513 091 551b 
189941 Therapy-related 171 702 102 173 816 191 2 114 089 569 
189941 Therapy-related 12 11 708 326 22 796 431 11 088 105 1244-2, 613, 614, 3974 
317821 Therapy-related 120 308 171 220 764 934 100 456 763 3118-1, 3118-2, 3118-3, 6077-1, 5087, 6077-2, 4257, 554, 5698, 190b, 4258, 92b, 555, 9-1, 9-5b, 765, 4259, 5187, 4654, 556, 3658, 921, 1255b-2, 557, 3119-1, 3119-2, 1295, 214, 3120, 199a-2, 488, 4424, 3121, 4426, 1278, 4735, 181b-1, 181a-1, 5191, 1231, 135b, 29c, 29b-2, 205, 4260, 3122, 215, 194-1, 664 
317821 Therapy-related 144 186 839 199 381 715 55 194 876 5186, 3919, 15b, 16-2, 1263, 551b, 569, 4789, 4448, 1224, 5588, 548aq, 1248, 28, 944, 3137, 570, 4797, 922 
377512 Therapy-related 236 856 627 241 034 230 4 177 603 4440, 4441, 4269, 2467, 4786 
377512 Therapy-related 15 18 422 770 22 846 333 4 423 563 3118-4, 5701-1, 3118-6, 5701-2, 1268a, 4509-1, 4508 
482711 Therapy-related 73 561 217 77 720 182 4 158 965 4282, 4463 
482711 Therapy-related 19 7 917 000 8 565 000 648 000 4999 
482711 Therapy-related 19 9 458 030 12 415 444 2 957 414 5589, 4322, 1181, 1238, 638, 4748, 199a-1 
482711 Therapy-related 19 13 331 909 19 078 761 5 746 852 24-2, 27a, 23a, 181c, 181d, 639, 1470, 3188, 3189 
530447 Therapy-related 28 278 165 29 708 951 1 430 786 876, 873 
557772 Therapy-related 21 9 892 286 46 915 712 37 023 426 3156-3, 3118-5, 99a, let-7c, 125b-2, 548x, 6130, 155, 4759, 4327, 6501, 802, 6508, 4760, 3197, 5692b, 6070 
706395 Therapy-related 10 42 100 384 57 162 870 15 062 486 5100, 3156-1, 4294, 605, 548f-1 
811184 Therapy-related 188 612 922 247 171 197 58 558 275 4426, 1278, 4735, 181b-1, 181a-1, 5191, 1231, 135b, 29c, 29b-2, 205, 4260, 3122, 215, 194-1, 664, 320b, 4742, 5008, 3620, 4666a, 1182, 4427, 4671, 4753, 1537, 4428, 3123, 4677, 3916, 3124 
811184 Therapy-related 12 33 393 16 168 160 16 134 767 3649, 200c, 141, 1244-3, 613, 614 
811184 Therapy-related 13 40 292 732 71 225 257 30 932 525 3168, 5006, 3613, 16-1, 15a, 5693, 4703, 759, 1297, 5007, 3169, 548x, 4704 
811184 Therapy-related 17 42 399 786 78 637 123 36 237 337 5089, 152, 1203, 10a, 196a-1, 3185, 6129, 6165, 3614, 142, 4736, 454, 301a, 4729, 21, 4737, 633, 3064, 5047, 6080, 4315-2, 634, 548d-2, 635, 4524a, 3615, 3678, 4738, 636, 4316, 4739, 1268b, 4730, 657, 3065, 338, 1250, 4740, 3186, 4525 
856024 Therapy-related 120 321 638 247 171 198 126 849 560 3118-1, 3118-2, 3118-3, 6077-1, 5087, 6077-2, 4257, 554, 5698, 190b, 4258, 92b, 555, 9-1, 9-5b, 765, 4259, 5187, 4654, 556, 3658, 921, 1255b-2, 557, 3119-1, 3119-2, 1295, 214, 3120, 199a-2, 488, 4424, 3121, 4426, 1278, 4735, 181b-1, 181a-1, 5191, 1231, 135b, 29c, 29b-2, 205, 4260, 3122, 215, 194-1, 664, 320b, 4742, 5008, 3620, 4666a, 1182, 4427, 4671, 4753, 1537, 4428, 3123, 4677, 3916, 3124 
856024 Therapy-related 12 33 393 17 253 192 17 219 799 200c, 141, 1244-3, 613, 614 
856024 Therapy-related 12 120 756 138 132 283 286 11 527 148 4304, 3908, 5188, 4419b, 3612 
856024 Therapy-related 17 44 017 170 78 637 124 34 619 954 196a-1, 3185, 6129, 6165, 3614, 142, 4736, 454, 301a, 4729, 21, 4737, 633, 3064, 5047, 6080, 4315-2, 634, 548d-2, 635, 4524a, 3615, 3678, 4738, 636, 4316, 4739, 1268b, 4730, 657, 3065, 338, 1250, 4740, 3186, 4525 
864484 Therapy-related 14 53 281 577 57 637 143 4 355 566 5580, 4308 
864484 Therapy-related 64 736 865 65 165 635 428 770 223 

a, amplification; Chr, chromosome; d, deletion.

To expand our analysis, we next analyzed whole-genome sequencing and aCGH data for 50 cases of de novo AML and 15 cases of secondary AML to identify somatic CNAs. For these samples, the Affymetrix 6.0 SNP array was used. We required that the CNAs be identified by both whole-genome sequencing and by aCGH. Given the lower probe density of the Affymetrix 6.0 SNP array, we estimated that the lower size limit of somatic CNA detection for this approach was approximately 18 kb. Four somatic CNAs involving miRNA genes were identified in 4 de novo AML patients, all with a normal karyotype (Table 5). In the secondary AML cases, we identified 18 somatic CNAs in 5 patients, only one of which had a normal karyotype. In total, we identified cytogenetically unapparent somatic CNAs involving miRNA genes in 18% of patients with AML. In AML with a normal karyotype, somatic CNAs involving miRNA genes were identified in only 5 (9.1%) of 55 cases. The most common recurring somatic CNA (present in 3 cases of AML) is an approximately 1.3-Mb deletion at 17q11.2, which includes MIR4733, MIR4724, MIR193a, MIR4725, and MIR365b (Table 5). However, as is the case for all of the somatic CNAs identified in this study, the 17q11.2 CNA includes several protein coding genes.

The smallest somatic CNA identified in this study is a 429-kb deletion on chromosome X that includes MIR223 and two other genes, MSN and VSIG4 (Figure 1A). It occurred in a male patient with t-AML with complex cytogenetics (Table 4, unique patient number [UPN] 864484). Quantitative PCR of genomic DNA isolated from the bone marrow of this patient confirmed a hemizygous deletion of MIR223 (Figure 1B). As expected, the hemizygous deletion of MIR223 in this patient resulted in the complete loss of miR-223 expression (Figure 1C). miR-223 is one of the most highly expressed miRNAs in human CD34+ cells,23  and its expression increases with myeloid differentiation.24  Accordingly, miR-223 has been implicated in granulocytic differentiation. Fazi et al24  showed that enforced expression of miR-223 in acute promyelocytic leukemic cells induces granulocytic differentiation. Conversely, loss of Mir223 is associated with a myeloproliferative-like phenotype in mice.25 

Figure 1

Hemizygous loss of MIR-223 in a patient with AML. (A) Log2 ratio dot plots of paired tumor and normal DNA from patient UPN 864484 analyzed by using the custom CGH array. A discrete deletion of approximately 429 kb on chromosome X is depicted. Genomic coordinates are based on NCIBI36/HG18 assembly. (B) Quantitative PCR for MIR223 and MIR181b (control gene) was performed by using genomic DNA from the indicated source. Shown is the ratio of MIR223 to MIR181b signal. Data represent the mean ± standard error of the mean of triplicate measurements. (C) miR-223 expression relative to RNU48 is shown for CD34+ cells isolated from healthy donors (CD34) and leukemic bone marrow from patient UPN 864484 or 28 other patients with AML. The 90% confidence interval is shown for CD34+ cells.

Figure 1

Hemizygous loss of MIR-223 in a patient with AML. (A) Log2 ratio dot plots of paired tumor and normal DNA from patient UPN 864484 analyzed by using the custom CGH array. A discrete deletion of approximately 429 kb on chromosome X is depicted. Genomic coordinates are based on NCIBI36/HG18 assembly. (B) Quantitative PCR for MIR223 and MIR181b (control gene) was performed by using genomic DNA from the indicated source. Shown is the ratio of MIR223 to MIR181b signal. Data represent the mean ± standard error of the mean of triplicate measurements. (C) miR-223 expression relative to RNU48 is shown for CD34+ cells isolated from healthy donors (CD34) and leukemic bone marrow from patient UPN 864484 or 28 other patients with AML. The 90% confidence interval is shown for CD34+ cells.

Close modal

To determine whether loss of miR-223 expression was a common occurrence in AML, we performed real-time RT-PCR on bone marrow RNA from an additional 28 cases of AML and from CD34+ cells isolated from 5 healthy donors (Figure 1C). We identified three cases in which miR-223 expression was below the 90% confidence interval based on normal CD34+ cells. Two of these samples (UPN 2_37 and 731274) were from male patients. Quantitative PCR performed on genomic DNA isolated from their leukemic bone marrow showed no deletion of MIR223 (Figure 1B). The third sample with very low miR-223 expression (UPN 189941) was from a female patient. The sequence of her leukemic genome was recently reported and revealed no point mutation or CNA of MIR223.26  Thus, in all of these cases, an epigenetic mechanism is the likely cause of miR-223 silencing. Indeed, UPN 2_37 (a 46-year-old male with M1 AML) had a t(8;21) translocation producing the AML-ETO fusion oncogene, which has been shown to epigenetically silence MIR223.14,27  Our data suggest that the deletion of MIR223 represents another, albeit uncommon, mechanism to decrease miR-223 expression in AML.

Although miRNAs are frequently dysregulated in AML, it appears that genetic alterations in miRNA are relatively rare. Results from whole genome sequencing of 24 cases of de novo AML identified recurring point mutations in a single miRNA gene.21  Specifically, point mutations in MIR142 were identified in 2% of cases of de novo AML. Our study suggests that small somatic CNAs involving miRNA genes that are not apparent by standard cytogenetics are uncommon. Thus, it appears that epigenetic, rather than genetic, mechanisms are responsible for most cases of miRNA dysregulation.

The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

This work was supported by a Translational Research Program Award from the Leukemia & Lymphoma Society (D.C.L.) and by grants RC2 CA1455073 (D.C.L.) and PO1-CA101937 (T.J.L.) from the National Institutes of Health.

Contribution: G.R., M.A.J., M.J.W., and D.C.L. designed the custom comparative genomic hybridization array; G.R., M.A.J., J.S., R.E.D.J.P., D.S., M.T., A.H.G., and M.J.W. contributed to data analysis; T.J.L. provided crucial reagents (acute myelogenous leukemia samples); and D.C.L. was responsible for the overall design and analysis of all studies and edited the final manuscript.

Conflict-of-interest disclosure: The authors declare no competing financial interests.

Correspondence: Daniel C. Link, Division of Oncology, Washington University School of Medicine, Campus Box 8007, 660 South Euclid Ave, St. Louis, MO 63110; e-mail: dlink@dom.wustl.edu.

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Author notes

G.R. and M.A.J. contributed equally to this study.

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