1078-0432.CCR-19-0725.Full-Text.Pdf

Author Manuscript Published OnlineFirst on August 2, 2019; DOI: 10.1158/1078-0432.CCR-19-0725 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

1 Research Article

2 Genetic Characterization and Prognostic Relevance of Acquired Uniparental Disomies in

3 Cytogenetically Normal Acute Myeloid Leukemia

4 Christopher J. Walker1, Jessica Kohlschmidt1,2, Ann-Kathrin Eisfeld1, Krzysztof Mrózek1,

5 Sandya Liyanarachchi1, Chi Song3, Deedra Nicolet1,2, James S. Blachly1, Marius Bill1,

6 Dimitrios Papaioannou1, Christopher C. Oakes1, Brain Giacopelli1, Luke K. Genutis1,

7 Sophia E. Maharry1, Shelley Orwick1, Kellie J. Archer1,3, Bayard L. Powell4, Jonathan E. Kolitz5,

8 Geoffrey L. Uy6, Eunice S. Wang7, Andrew J. Carroll8, Richard M. Stone9, John C. Byrd1,

9 Albert de la Chapelle1, and Clara D. Bloomfield1

10 1The Ohio State University Comprehensive Cancer Center, Columbus, Ohio

11 2Alliance Statistics and Data Center, The Ohio State University Comprehensive Cancer Center,

12 Columbus, Ohio

13 3The Ohio State University Division of Biostatistics, Columbus, Ohio

14 4Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, North Carolina

15 5Monter Cancer Center, Zucker School of Medicine at Hofstra/Northwell, Lake Success, New

16 York

17 6Washington University School of Medicine in St. Louis, Siteman Cancer Center, St. Louis,

18 Missouri

19 7Roswell Park Comprehensive Cancer Center, Buffalo, New York

20 8University of Alabama at Birmingham, Birmingham, Alabama

21 9Dana-Farber Cancer Institute, Boston, Massachusetts

22 Short title: UPDs, mutations, and outcome in CN-AML

23 Scientific section: Precision Medicine

Downloaded from clincancerres.aacrjournals.org on September 25, 2021. © 2019 American Association for Cancer Research. Author Manuscript Published OnlineFirst on August 2, 2019; DOI: 10.1158/1078-0432.CCR-19-0725 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

24 Correspondence: Christopher J. Walker, The Ohio State University Comprehensive Cancer

25 Center, 460 W 12th Ave. 894 BRT, Columbus, OH, 43210, USA; phone 614-688-4463, fax: 614-

26 685-0211; e-mail [email protected] or Dr. Clara D. Bloomfield, The Ohio State

27 University Comprehensive Cancer Center, C933 James Cancer Hospital, 460 West 10th

28 Avenue, Columbus, OH 43210-1228, phone: 614-293-7518, fax: 614-366-1637, e-mail:

29 [email protected].

30 Support: Research reported in this publication was supported by the National Cancer Institute

31 for the National Institutes of Health under Award Numbers U10CA180821, U10CA180882, and

32 U24CA196171 (to the Alliance for Clinical Trials in Oncology); P30CA016058, U10CA180833,

33 U10CA180850, U10CA180861, U10CA180866, U10CA180867, and UG1CA233338; the

34 Leukemia Clinical Research Foundation; the Warren D. Brown Foundation; and by an allocation

35 of computing resources from The Ohio Supercomputer Center. Also supported in part by funds

36 from Novartis (CALGB-10603). The content is solely the responsibility of the authors and does

37 not necessarily represent the official views of the National Institutes of Health.

38 Conflict of Interest Disclosure Statement: The authors declare no potential conflicts of

39 interest.

40 Abstract: 249 words; main text: 2789 words; Tables: 2 Figures: 2

41 Abstract

42 Purpose: Uniparental disomy UPD is a way cancer cells duplicate a mutated gene causing loss

43 of heterozygosity (LOH). Patients with cytogenetically normal acute myeloid leukemia (CN-AML)

44 do not have microscopically detectable chromosome abnormalities, but can harbor UPDs. We

45 examined the prognostic significance of UPDs and frequency of LOH in CN-AML patients.

46 Experimental Design: We examined the frequency and prognostic significance of UPDs in a

47 set of 425 adult de novo CN-AML patients who were previously sequenced for 81 genes

48 typically mutated in cancer. Associations of UPDs with outcome were analyzed in the 315 CN-

49 AML patients younger than 60 years.

50 Results: We detected 127 UPDs in 109 patients. Most UPDs were large and typically

51 encompassed all or most of the affected chromosome arm. The most common UPDs occurred

52 on chromosome arms 13q (7.5% of patients), 6p (2.8%) and 11p (2.8%). Many UPDs

53 significantly co-occurred with mutations in genes they encompassed, including 13q UPD with

54 FLT3-internal tandem duplication (FLT3-ITD) (P<0.001), and 11p UPD with WT1 mutations

55 (P=0.02). Among patients younger than 60 years, UPD of 11p was associated with longer

56 overall survival (OS) and 13q UPD with shorter disease-free survival (DFS) and OS. In

57 multivariable models that accounted for known prognostic markers including FLT3-ITD and WT1

58 mutations, UPD of 13q maintained association with shorter DFS, and UPD of 11p maintained

59 association with longer OS.

60 Conclusions: LOH mediated by UPD is a recurrent feature of CN-AML. Detection of UPDs of

61 13q and 11p might be useful for genetic risk stratification of CN-AML patients.

62 Statement of Translational Relevance

63 Acquired uniparental disomy (UPD) is recognized as a common mechanism by which cancer

64 cells can achieve homozygous mutations in oncogenes or tumor suppressor genes. UPDs

65 frequently occur in cytogenetically normal acute myeloid leukemia (CN-AML) patients, and

66 specific UPDs are reportedly associated with patient outcome. Our study reports the largest CN-

67 AML patient set screened for UPDs, to our knowledge. Consistent with previous reports, we

68 found that UPDs often co-occur with mutations in genes they encompass resulting in loss of

69 heterozygosity, including UPD of 13q with FLT3 internal tandem duplication and UPD of 11p

70 with WT1 mutations. In the CN-AML patients younger than 60 years, we found UPD of 13q and

71 UPD of 11p were associated with shorter and longer survival, respectively, even in multivariable

72 models that accounted for known prognostic markers. These results imply that genetic risk

73 stratification of younger CN-AML patients could be improved by the inclusion of UPD testing.

74 Introduction

75 Acute myeloid leukemia (AML) is a genetically heterogeneous disease. The prognosis of AML

76 patients is strongly influenced by chromosomal aberrations and gene mutations, and patients

77 are prognostically stratified based on the results of gene sequencing and cytogenetic analysis

78 (1-3). Although genetic risk stratification of AML patients has been well-studied, there remains

79 room for improvement, especially for the cytogenetically normal (CN) group which comprises

80 40-45% of adult patients. For CN-AML patients, the 2017 European LeukemiaNet (ELN) genetic

81 risk stratification guidelines are determined entirely by gene mutations (i.e. mutation of NPM1,

82 RUNX1, ASXL1 and TP53; bi-allelic CEBPA mutations; and FLT3-internal tandem duplication

83 [ITD] allelic ratio).

84 CN-AML patients by definition do not have chromosomal abnormalities detectable by

85 karyotyping (3), but these patients often harbor acquired uniparental disomies (UPDs, also

86 called copy-neutral loss of heterozygosity) (4-10), which are somatic losses of a chromosome or

87 segment with duplication of the homologous chromosome or segment. In cancer development

88 UPDs have been shown to mediate loss of heterozygosity (LOH) of mutated oncogenes and

89 tumor suppressor genes by duplicating the mutant alleles thus resulting in homozygous

90 mutations.

91 The prognostic relevance of UPD in CN-AML has not been adequately investigated, although

92 there is evidence that specific UPDs can impact AML patient outcome (11-20). To better define

93 the utility of UPDs for prognostic risk stratification of CN-AML patients, we herein screened a

94 large cohort of adult de novo CN-AML patients for UPDs and investigated their associations with

95 patient survival and relationship with recurrent gene mutations.

96 Materials and Methods

97 Patients and cytogenetic analysis

98 Studies were conducted using samples obtained from a cohort of 425 adults with de novo AML

99 aged 17-79 years (median 52 years), with 315 patients younger than 60 years. Patients with

100 acute promyelocytic leukemia, AML secondary to myelodysplastic syndromes, or therapy-

101 related AML, and patients who received allogeneic hematopoietic stem cell transplantation in

102 first complete remission (CR) were not included in the study. This study was limited to patients

103 with CN-AML. Pretreatment cytogenetic analyses of bone marrow samples of all patients were

104 performed by the Cancer and Leukemia Group B (CALGB)-approved institutional laboratories

105 using short-term (24-48 hours) unstimulated cultures, and all karyotypes were centrally

106 reviewed (21). In each case, ≥20 metaphase cells were analyzed and no clonal abnormality was

107 found. All patients were similarly treated on CALGB trials (21-33) and did not die within 30 days

108 (see Supplementary Methods for details). Study protocols were in accordance with the

109 Declaration of Helsinki and approved by the institutional review boards. All individuals in this

110 study provided written informed consent.

111 DNA samples from blood of 1,798 non-leukemic individuals recruited in Columbus, Ohio, USA

112 who had never been diagnosed with any cancer, were used as negative controls for somatic

113 UPD detection. All healthy donors provided written informed consent. The ethnicity of the cases

114 and controls were similar as follows: white European, 90% of cases and 91% of controls;

115 African, 6% of cases and 4% of controls; Asian, 2% of cases and 3% of controls; Hispanic, 2%

116 of cases and 1% of controls; Native American, <1% of cases and controls; Native Hawaiian,

117 <1% of cases and controls; and middle-eastern <1% of cases and controls.

118 UPD and copy number alteration (CNA) detection

119 All samples were genotyped with Infinium Omni-1 Quad-bead arrays (Illumina, San Diego, CA)

120 by deCODE Genetics (Reykjavík, Iceland) as previously described (34,35). For quality control,

121 samples with <94% genotyping yield were excluded, and variants were excluded if they had

122 <94% yield, showed significant differences among genotyping batches, or if they significantly

123 (P<10-6) deviated from Hardy-Weinberg equilibrium. GenomeStudio 2.0 software (Illumina) and

124 the cnvPartition plugin (v3.2.0) were used to detect UPDs and CNAs with minimum probe count

125 set to 10. All calls were manually reviewed by examination of LogR ratio and B-allele frequency

126 plots. Nexus Copy Number v10 (BioDiscovery, El Segundo, CA) was used to visualize UPDs.

127 To differentiate between common inherited regions of homozygosity present in germline DNA

128 and somatically acquired UPDs, 1798 non-leukemic control samples were genotyped. Thirty-

129 three different inherited regions of homozygosity, all of which were smaller than 2Mb in size,

130 were present in ≥1% of samples, and were excluded from the UPD analysis (Supplementary

131 Table S1). These non-leukemic samples did not contain any detectable CNAs or large UPDs.

132 DNA sequencing

133 Patient DNA obtained from pretreatment bone marrow or blood samples was sequenced for the

134 following 80 protein coding genes using two separate TruSeq Custom Amplicon panels

135 (Illumina) as described (36): AKT1, ARAF, ASXL1, ATM, AXL, BCL2, BCOR, BCORL1, BRAF,

136 BRD4, BRINP3, BTK, CBL, CCND1, CCND2, CSNK1A1, CTNNB1, DNMT3A, ETV6, EZH2,

137 FBXW7, FLT3, GATA1, GATA2, GSK3B, HIST1H1E, HNRNPK, IDH1, IDH2, IKZF1, IKZF3,

138 IL7R, JAK1, JAK2, JAK3, KIT, KLHL6, KMT2A, KRAS, MAPK1, MAPK3, MED12, MYD88, NF1,

139 NOTCH1, NPM1, NRAS, PHF6, PIK3CD, PIK3CG, PLCG2, PLEKHG5, PRKCB, PRKD3,

140 PTEN, PTPN11, RAD21, RAF1, RUNX1, SAMHD1, SETBP1, SF1, SF3A1, SF3B1, SMARCA2,

141 SMC1A, SMC3, SRSF2, STAG2, SYK, TET2, TGM7, TP53, TYK2, U2AF1, U2AF2, WT1,

142 XPO1, ZMYM3, and ZRSR2. Libraries were prepared according to manufacturer’s instructions,

143 pooled and run on a MiSeq instrument using MiSeq v3 reagent kits (Illumina, San Diego, CA).

144 Sequences were aligned to the hg19 genome build with the Illumina Isis Banded Smith-

145 Waterman aligner. Small indel variants and single nucleotide variants were called using

146 VarScan2 and MuTect, respectively. The Mucor program was used as a baseline for integrative

147 mutation assessment (37). The variant allele fraction (VAF) cut-off was set to 0.1. Variants were

148 considered mutations if they were non-synonymous and not present in the dbSNP v142

149 database or 1000 Genomes database. All called variants underwent visual inspection of the

150 aligned reads using Integrative Genomics Viewer. We excluded variants sequenced with fewer

151 than 15 reads; variants that only occurred in one read direction (if covered by forward and

152 reverse reads); variants in regions marked by low phred-score bases or low-mapping score

153 reads; variants that occurred in all samples; and samples with generally poor quality sequencing

154 for the entire panel. Samples were considered non-evaluable for a specific gene if ≥85% of the

155 amplicons covering the target regions within the coding sequence of the gene were sequenced

156 to a depth of <15 reads. Detection of FLT3-ITD and determination of the allelic ratio was done

157 with reverse transcriptase polymerase chain reaction as described (38). In addition to the 80

158 gene sequencing panel, testing for CEBPA mutations was performed with Sanger sequencing

159 as described (39).

160 Statistical analyses

161 Associations between UPDs, clinical characteristics and gene mutations were tested using

162 Fisher’s exact tests for categorical variables and the Kruskal-Wallis test for continuous

163 variables. UPDs and gene mutations present in at least eight patients were included in outcome

164 analyses. We used the log-rank test to test for significant associations between categorical

165 variables and survival, with Kaplan-Meier curves for illustration.

166 We constructed multivariable logistic regression models to analyze the probability of CR

167 attainment and multivariable Cox proportional hazards models for disease-free survival (DFS)

168 and overall survival (OS) using a limited backwards selection procedure. Variables that were

169 significant at the likelihood ratio test P-value <0.20 from univariable models were considered in

170 the multivariable analysis (MVA) (40). Variables considered in univariable models were: age,

171 extramedullary involvement, hemoglobin levels, percentage of blood and bone marrow blasts,

172 platelet count, race, sex, white blood cell (WBC) count, UPD of 11p, UPD of 13q, FLT3-ITD

173 status, FLT3-tyrosine kinase domain mutation status (FLT3-TKD), biallelic mutation of CEBPA

174 status, and mutation status of ASXL1, BCOR, DNMT3A, GATA2, IDH1, IDH2, NPM1, NRAS,

175 PTPN11, RAD21, RUNX1, SMC1A, SMC3, TET2, WT1 and ZRSR2. Data collection and

176 statistical analyses were performed by the Alliance Statistics and Data Center. Analyses were

177 performed using SAS 9.4 and TIBCO Spotfire S+ 8.2, with the database locked on July 5, 2018.

178 Results

179 We assessed a cohort of 425 adult patients with de novo CN-AML for UPDs in the autosomes

180 using genotyping arrays. There were 171 UPDs detected in 116 patients (Fig. 1 and

181 Supplementary Table S2). Many UPDs encompassed entire chromosome arms, and the

182 chromosome arms that most frequently contained UPDs were 13q (present in 32 patients), 11p

183 (12 patients), and 6p (12 patients; Fig. 1). To begin to assess the clinical relevance of these

184 UPDs, we grouped UPDs by chromosome arm and determined the associations between the

185 most common UPDs and patient baseline clinical characteristics. UPD of 13q was associated

186 with higher WBC counts (median, 52.5 vs 29.6x109/L; P=0.02), blood blasts (77% vs 58%;

187 P=0.004) and bone marrow blasts (80% vs 69%; P=0.005); UPD of 11p was associated with

188 lower platelet counts (median, 41 vs 60x109/L; P=0.03) and higher blood blasts (85% vs 60%;

189 P=0.002); and UPD of 6p was associated with higher bone marrow blasts (median, 86% vs

190 70%; P=0.02) (Supplementary Table S3).

191 UPDs are associated with mutations in genes they encompass

192 We were able to assess associations between UPDs and gene mutations as these CN-AML

193 patients were previously sequenced for mutations in 81 cancer and/or leukemia-associated

194 genes (Supplementary Table S4) (36). Many UPDs were found to co-occur in the same patients

195 with mutations in genes they encompassed. Specifically, patients with FLT3-ITD (located at

196 13q12.2) more frequently harbored UPDs of 13q compared to patients without FLT3-ITD

197 (P<0.001; Table 1). Similarly, patients with mutations in the RUNX1 gene (located at 21q22.12)

198 had UPD of 21q significantly more often than patients with wild-type RUNX1 (P<0.001), and

199 patients with EZH2 (located at 7q36.1) mutations had UPD of 7q significantly more often than

200 those with wild-type EZH2 (P<0.001; Table 1). Likewise, there were significant co-associations

201 between mutation of CBL (located at 11q23.3) with UPD of 11q (P=0.01); mutation of WT1

202 (located at 11p13) with UPD of 11p (P=0.02); bi-allelic mutation of CEBPA (located at 19q13.11)

203 with UPD of 19q (P=0.02); mutation of SF3B1 (located at 2q33.1) with UPD of 2q (P=0.03); and

204 mutation of TET2 (located at 4q24) with UPD of 4q (P=0.04, Table 1). Expectedly, the vast

205 majority of gene mutations that co-occurred with UPDs had VAFs >0.5 (Supplementary Table

206 S5).

207 UPD of 11p is associated with improved outcome and UPD of 13q with poor outcome

208 Because of differences in treatment intensity between older and younger adult AML patients

209 enrolled onto CALGB/Alliance treatment protocols, outcome studies are typically performed

210 separately in younger (<60 years of age) and older patients (≥ 60 years of age). Between the

211 315 younger patients and the 110 older patients in our study, the sample size for examining

212 associations with CR status, DFS and OS for 11p UPD and 13q UPD was adequate only for the

213 younger patients.

214 We found that UPD of 11p was associated with longer OS (P=0.02; Fig. 2A), and UPD of 13q

215 was associated with both shorter DFS (P<0.001) and shorter OS (P<0.001; Fig. 2B and C) in

216 younger patients. MVA was used to examine the effect of UPDs on outcome in the context of

217 known prognostic markers. For OS, the risk of death was lower for patients with 11p UPD

218 (P=0.04) after adjusting for age (P=0.005), FLT3-ITD (P<0.001), and mutations in FLT3-TKD

219 (P=0.04), DNMT3A (P=0.003), RUNX1 (P<0.001) and WT1 (P<0.001; Table 2). For DFS,

220 patients with 13q UPD had a higher risk of relapse or death (P=0.009) after adjusting for

221 hemoglobin levels (P=0.02), FLT3-ITD status (P<0.001), and mutations in the DNMT3A

222 (P<0.001), RUNX1 (P=0.002) and WT1 (P=0.03) genes (Table 2).

223 UPD of 13q is associated with shorter DFS in patients with FLT3-ITD

224 Since both FLT3-ITD and 13q UPD were associated with shorter DFS, and co-occurred in the

225 same patients, we sought to determine if 13q UPD has any additional utility as a prognostic

226 marker independent of its association with FLT3-ITD by performing outcome analyses for 13q

227 UPD in only the 112 younger CN-AML patients who harbored FLT3-ITD. Patients with 13q UPD

228 still had significantly shorter DFS (P=0.004) in the FLT3-ITD-positive group, demonstrating that

229 13q UPD status is useful for prognostic stratification even when considering the known

230 prognostic marker FLT3-ITD (Fig. 2D). Expectedly, all of the patients with both FLT3-ITD and

231 13q UPD had a FLT3-ITD allelic ratio >.5 (i.e. FLT3-ITDhigh), supporting the view that the UPD

232 caused LOH for FLT3-ITD (Supplementary Table S6).

233 Small copy number alterations are present in CN-AML patients

234 In addition to UPD analysis, the genotyping data from these patients allowed us to screen for

235 microdeletions too small to be detected microscopically by karyotyping. Among the 425 CN-

236 AML patients there were 28 deletions and 3 amplifications that ranged in size from ~100kb to

237 ~19Mb (Supplementary Table S7). Most of the CNAs were observed in only one sample each,

238 with six occurring in two patients each (Supplementary Table S7). Because of the infrequency

239 with which these CNAs were observed, we were unable to assess their associations with clinical

240 or molecular characteristics.

241 Discussion

242 The use of genotyping arrays to assess UPD in AML was first described over a decade ago,

243 and subsequent studies have established that UPDs occur in ~20% of CN-AML patients (5,13).

244 In the time since these initial studies assessing the frequency and prognostic relevance of UPDs

245 in AML, the focus of genetic risk stratification has largely shifted beyond cytogenetics to gene

246 mutations, with some additional studies exploring the prognostic relevance of expression

247 signatures and epigenetic changes (41-48). Our work validates earlier efforts that reported

248 associations between 11p and 13q UPDs with AML patient outcome (including CN-AML),

249 (5,13,14,16,49) and again highlights the importance of UPDs in CN-AML. We believe our

250 sample set is the largest series of CN-AML patients screened for UPDs to date, and the finding

251 that both 11p and 13q UPDs were separately associated with patient outcome in multivariable

252 models suggests that these UPDs are clinically relevant prognostic markers for younger CN-

253 AML patients treated with standard “7+3” induction therapy.

254 Biologically, UPDs are a mechanism by which a cancer cell can duplicate an activating mutation

255 in an oncogene or eliminate the wild-type copy of a tumor suppressor gene to augment the

256 mutation-associated phenotype, such as multiplying an increase in growth advantage caused by

257 a loss of function mutation in a tumor suppressor gene. Many of the recurrent UPDs identified in

258 our study were associated with pathogenic mutations in genes residing on the same

259 chromosome arms including FLT3 (13q), RUNX1 (21q), EZH2 (7q), CBL (11q), WT1 (11p),

260 CEBPA (19q), SF3B1 (2q), and TET2 (4q) (Table 1). Although 12 patients had UPDs that

261 encompassed most of chromosome 6p, we did not identify any recurrently mutated genes on

262 6p. Notably the only gene located on chromosome 6p on our sequencing panel was HIST1H1E,

263 which was only mutated in two of the 425 CN-AML patients, neither of whom had a UPD of 6p.

264 Our findings validate previous reports of 7q UPDs causing biallelic inactivation of the EZH2

265 tumor suppressor gene, although both oncogenic and tumor suppressor roles have been

266 ascribed to EZH2 in AML and its progression from myelodysplastic syndromes (50-51). Likewise

267 UPD-mediatied LOH in RUNX1-mutated AML patients has been recently described and was

268 shown to be associated with poor outcome (52,53). We were unable to assess the relationship

269 between UPD of 21q and outcome in our samples due to insufficient numbers. We found 11p

270 UPD was associated with WT1 mutation status, and also associated with improved DFS.

271 However, WT1 mutation is a known prognostic marker associated with poor outcome (54,55). In

272 our MVA for OS, WT1 mutations and 11p UPD were associated with shorter and longer OS,

273 respectively, indicating it is likely that 11p UPDs mediate an effect on OS independently from

274 their association with WT1 mutations.

275 We found that patients with FLT3-ITD who also had 13q UPD had a FLT3-ITDhigh allelic ratio,

276 which is consistent with 13q UPD as a common mechanism for acquisition of FLT3-ITDhigh (56).

277 Our study also validates reports that FLT3-ITDhigh is associated with poor outcome, and

278 supports the inclusion of FLT3-ITDhigh in the 2017 ELN genetic risk classification system (57).

279 We found that among the younger CN-AML patients who harbor FLT3-ITD, 13q UPD was still

280 associated with poor outcome. Finally, 13q UPD was associated with poor outcome in a MVA

281 that included FLT3-ITD.

282 Our analysis of CNAs did not identify any frequently occurring CNAs in these cases. We

283 hypothesized that CN-AML patients might harbor micro-CNAs smaller than 5Mb in critical

284 genes, which would not be detectable microscopically by karyotyping. Several recurrent copy

285 number alterations have previously been reported in CN-AML but they are generally rare. These

286 include deletions encompassing TET2 (4q24), ETV6 (12p12.3), TP53 (17p13.1) and NF1

287 (17q11.2), and amplifications encompassing MYC (8q23.2) and KMT2A (11q23.3) (7,13,58,59).

288 Notably we detected deletion of NF1 in two patients and deletion of TET2 in one patient

289 (Supplementary Table S7). However, our results indicate that micro-CNAs are not a defining

290 feature of CN-AMLs.

291 Our data provide an overview of recurrent UPDs found in CN-AML and show UPDs are

292 frequently associated with mutations in genes they encompass, leading to LOH. Together our

293 work validates the prognostic importance of 13q UPD and 11p UPD in CN-AML patients, and

294 indicates these UPDs could be clinically relevant for risk stratification of younger de novo CN-

295 AML patients treated with standard induction therapy.

296 Acknowledgements

297 The authors would like to acknowledge Leslie Davidson, Tammy Woike, Jan Lockman and

298 Barbara Fersch for administrative assistance; Donna Bucci and Wacharaphon Vongchucherd of

299 the CALGB/Alliance Leukemia Tissue Bank at The Ohio State University Comprehensive

300 Cancer Center, Columbus, OH, for sample processing and storage services, and Lisa J. Sterling

301 and Christine Finks for data management.

302 Author Contributions

303 J.S.B., B.L.P., J.E.K., G.L.U., E.S.W., A.J.C., R.M.S., J.C.B., and C.D.B. are responsible for

304 establishing sample collection protocols and contributing patient material for the study. A.J.C.

305 and K.M. reviewed all patient cytogenetics. C.J.W., A.-K.E., J.S.B., M.B., D.P., C.C.O., B.G.,

306 L.K.G., S.E.M., and S.O. performed sequencing and genotyping experiments. C.J.W., S.L., and

307 C.S. performed bioinformatic analyses. J.K., D.N. and K.J.A. performed biostatistics analyses.

308 C.J.W., J.K., A.-K.E, K.M., D.N., J.S.B., M.B., C.C.O., A.d.l.C., and C.D.B. interpreted the data.

309 C.J.W., J.K., A.-K.E., K.M., D.N., M.B., A.d.l.C., and C.D.B. drafted the manuscript. All authors

310 reviewed the manuscript and approved its final version.

311 Clinicaltrials.gov identifiers: NCT00085124 (CALGB-10201), NCT00742625 (CALGB-10502),

312 NCT00742625 (CALGB-10503), NCT00651261 (CALGB-10603), NCT00006363 (CALGB-

313 19808), NCT00900224 (CALGB-20202), NCT00048958 (CALGB-8461), NCT00899223

314 (CALGB-9665), and NCT00003190 (CALGB-9720).

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Table 1. Number of adult patients with cyotgenetically normal acute myeloid leukemia who had co-occuring mutations and uniparental disomies.

UPD Gene Mutation (location) Status Yes No P-valuea

FLT3-ITD present 30 129 < 0.001 (13q12.2) absent 2 263

RUNX1 mutated 4 33 < 0.001 (21q22.12) wild-type 2 386

EZH2 mutated 3 10 < 0.001 (7q36.1) wild-type 4 408

CBLb mutated 2 6 0.01 (11q23.3) wild-type 6 411

WT1 mutated 4 38 0.02 (11p13) wild-type 8 375

c CEBPA mutated 2 56 0.02 (19q13.11) wild-type 0 349

SF3B1 mutated 1 10 0.03 (2q33.1) wild-type 0 414

TET2d mutated 3 59 0.04 (4q24) wild-type 3 360

IDH2 mutated 2 56 0.09 (15q26.1) wild-type 2 365

DNMT3A mutated 3 164 0.68 (2p23.3) wild-type 3 255

Abbreviations: UPD, uniparental disomy; FLT3-ITD, internal tandem duplication of the FLT3 gene.

Associations between UPDs and gene mutations are shown for all genes in which at least one patient had a co-occurring mutation and UPD. For each gene, the numbers of patients with and without a UPD that encompasses the gene are listed, stratified by mutation status.

aFisher’s exact tests were used to calculate P-values.

bOne patient with a UPD on 11q that did not encompass CBL is counted as not having an 11q UPD.

cOnly patients with bi-allelic CEBPA mutations are included.

dTwo patients with UPDs on 4q that did not encompass TET2 are counted as not having 4q UPDs.

Table 2. Multivariable analyses for disease-free survival and overall survival performed in younger (aged <60 years) patients with cytogenetically normal acute myeloid leukemia

Disease-free survival Overall survival

Variables (n=266) (n=315) P-value HR (95% CI) P-value HR (95% CI) Age, continuous 0.005 1.20 (1.06-1.37) DNMT3A, mut vs wt <0.001 1.94 (1.41-2.67) 0.003 1.58 (1.17-2.14) FLT3-ITD, yes vs no <0.001 2.31 (1.67-3.19) <0.001 2.08 (1.55-2.80) FLT3-TKD, mut vs wt 0.04 0.52 (0.28-0.97) HG, continuous 0.02 0.91 (0.84-0.98) RUNX1, mut vs wt 0.002 2.82 (1.44-5.52) <0.001 3.82 (2.17-6.75) UPD of 11p, yes vs no 0.04 0.35 (0.13-0.98) UPD of 13q, yes vs no 0.009 2.10 (1.20-3.67) WT1, mut vs wt 0.03 1.70 (1.04-2.77) <0.001 2.62 (1.70-4.03)

Abbreviations: UPD, uniparental disomy; CI, confidence interval; HG, hemoglobin levels; HR, hazard ratio; FLT3-ITD, internal tandem duplication of the FLT3 gene; mut, mutated; n, number; FLT3-TKD, tyrosine kinase domain mutation in the FLT3 gene; wt, wild-type

A HR >1 ( < 1) corresponds to a higher (lower) risk for first category listed of a dichotomous variable or higher values of a continuous variable. A limited backward selection technique was used to build the final models with variables that were significant at the likelihood ratio test P-value <0.20 from univariable models for each outcome. For DFS those variables were: HG, platelet count, white blood cell count, UPD of 11p, UPD of 13q, FLT3-ITD status, biallelic mutation of CEBPA status, and mutation status of BCOR, DNMT3A, FLT3-TKD, GATA2, RUNX1, SMC1A, and WT1. For OS those variables were: age, HG, white blood cell count, UPD of 11p, UPD of 13q, FLT3-ITD status, biallelic mutation of CEBPA status, and mutation status of DNMT3A, FLT3-TKD, GATA2, RUNX1, SMC1A, WT1 and ZRSR2.

461 FIGURE LEGENDS

462 Figure 1.

463 Uniparental disomies (UPDs) in 425 adult patients with de novo cytogenetically normal acute

464 myeloid leukemia. Each orange line represents a single UPD in a single patient. The locations

465 of recurrently mutated genes (mutated in at least 2% of patients) are shown.

466 Figure 2.

467 Associations between uniparental disomies (UPDs) and outcome in younger patients (aged <60

468 years) with cytogenetically normal acute myeloid leukemia. A, Overall survival of patients with

469 and without 11p UPD. B, Overall survival and C, disease-free survival of patients with and

470 without 13q UPD. D, Disease-free survival of patients who have FLT3 internal tandem

471 duplications (FLT3-ITD) and either harbor 13q UPD or do not.

Genetic Characterization and Prognostic Relevance of Acquired Uniparental Disomies in Cytogenetically Normal Acute Myeloid Leukemia

Christopher J. Walker, Jessica Kohlschmidt, Ann-Kathrin Eisfeld, et al.

Clin Cancer Res Published OnlineFirst August 2, 2019.

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