ABSTRACT Chromothripsis is a one-step genome-shattering catastrophe resulting from disruption of one or few chromosomes in multiple fragments and consequent random rejoining and repair. This

study defines incidence of chromothripsis in 395 newly diagnosed adult acute myeloid leukemia (AML) patients from three institutions, its impact on survival and its genomic background. SNP

6.0 or CytoscanHD Array (Affymetrix®) were performed on all samples. We detected chromothripsis with a custom algorithm in 26/395 patients. Patients harboring chromothripsis had higher age

(_p_ = 0.002), ELN high risk (HR) (_p_ < 0.001), lower white blood cell (WBC) count (_p_ = 0.040), _TP53_ loss, and/or mutations (_p_ < 0.001) while _FLT3_ (_p_ = 0.025), and _NPM1_

number alteration (CNA), complex karyotype, alterations in DNA repair, and cell cycle] and focal deletions on chromosomes 4, 7, 12, 16, and 17. CBA. FISH showed that chromothripsis is

associated with marker, derivative, and ring chromosomes. In conclusion, chromothripsis frequently occurs in AML (6.6%) and influences patient prognosis and disease biology. SIMILAR CONTENT

BEING VIEWED BY OTHERS COPY NUMBER SIGNATURES PREDICT CHROMOTHRIPSIS AND CLINICAL OUTCOMES IN NEWLY DIAGNOSED MULTIPLE MYELOMA Article Open access 27 August 2021 GENETIC HALLMARKS AND

CLINICAL IMPLICATIONS OF CHROMOTHRIPSIS IN CHILDHOOD T-CELL ACUTE LYMPHOBLASTIC LEUKEMIA Article Open access 27 August 2024 CHROMOTHRIPSIS IS A FREQUENT EVENT AND UNDERLIES TYPICAL GENETIC

CHANGES IN EARLY T-CELL PRECURSOR LYMPHOBLASTIC LEUKEMIA IN ADULTS Article Open access 16 August 2022 INTRODUCTION Loss of chromosomes and complex karyotype are mechanisms of genomic

instability known to be linked to therapy resistance, poor prognosis, and early relapse in AML [1,2,3]. Nowadays, new high-throughput technologies can discover new alterations responsible

for the poor prognosis in subcohorts of AML patients and may reveal druggable pathways. There is an urgent need to define genomic phenotypes in AML in a therapeutic perspective.

Chromothripsis is a one-step genomic catastrophe involving one or few chromosomes resulting from chromosome breakage and random DNA rejoining [4]. It has been detected, mainly as occasional

finding, in solid tumors [5,6,7,8,9,10,11,12,13] and hematological malignancies (multiple myeloma [14], AML [15, 16], acute lymphoblastic leukemia [17, 18], and chronic lymphocytic leukemia

[19]), as well as in germline cases of congenital disorders [20]. A study on 22,000 cases of primary tumors highlighted an overall incidence of chromothripsis between 2 and 3% [21]. During

mitosis, chromothripsis arises from aberrant DNA replication timing. Prolonged arrest of cell cycle and micronuclei formation influence the spatial distribution of damages favoring the

acquisition of structural rearrangements [22]. Molecular mechanisms implicated in this event are only partially discovered. Chaotic genomes seemed to form through random non-homologous end

joining after DNA damages [23]. An alternative theory presented chromothripsis as a putative incomplete outcome of chromosome fragmentation, the initial event triggering a new form of

mitotic cell death [23]. Moreover, recent evidence indicates that chromothripsis preferentially occurs especially in hyperploid cells [24] and in cells with damaged telomeres [25].

Chromothripsis has been associated to _EGFR_, _MDM2_, and _MDM4_ amplification, _CDKN2A_ and _PTEN_ deletion [8], aberrant DNA double-strand break (DSB) response [26], _TP53_ mutations [9,

15], complex karyotype [9, 15], and _ATM_ mutation [18]. At present, a standardized way to detect chromothripsis does not exist, but few have been proposed. Chromothripsis has been

identified with fluorescent in situ hybridization (FISH) [9, 15, 16, 26], or, alternatively, by operator-dependent analyses [14] as well as algorithm-based detection of shattering patterns

on SNP array data and eventual integration with DNA sequencing data [21, 27]. Korbel and Campbell defined six different criteria to distinguish chromothripsis from a multi-step process of

genomic rearrangement [28]. When analyzed by SNP arrays, chromosomes harboring chromothripsis show a characteristic pattern of alterations: two or three switches of CN state detectable along

the chromosome with a clustering of breakpoint locations [29]. These patterns are associated with a high number of chromosomal rearrangements with widespread loss or gain of sequence

fragments interspersed in diploid regions [21]. Chromothripsis has been associated with highly aggressive disease in various tumors [8,9,10,11,12,13,14] but it did not appear to impact

prognosis in prostate cancer [30] and in estrogen receptor-negative breast cancer [12]. Our study describes the incidence of chromothripsis at diagnosis in a large and homogenous AML cohort,

its impact on prognosis, and the genetic features associated with this phenomenon. SUBJECTS AND METHODS PATIENTS Samples and data at diagnosis from 395 adult patients affected by de novo or

secondary AML according to WHO 2016 criteria [31] were collected from three institutions. The study was approved by the local ethical committees, written permission, and informed consent

were obtained from all patients before sample collection according to Helsinki declaration of “Ethical Principles for Medical Research Involving Human Subjects” [32]. Data were collected and

managed through custom Electronic Case Report Forms using REDCap electronic data capture tool [33]. SNP MICROARRAY ANALYSIS DNA samples were processed by Affymetrix® (Santa Clara, CA, USA)

genome-wide human SNP 6.0 (_n_ = 321) and CytoscanHD Array (_n_ = 84) according to the manufacturer’s instructions. Of the 114 SNP 6.0 AML cases obtained from GSE23452, 112 were paired

samples, including buccal swab DNA or bone marrow at remission [34]. Array data have been deposited in the NGS-PTL repository (http://www.ngs-ptl.com/documents/documents/3-10-en/media.aspx).

DETECTION OF CHROMOTHRIPSIS Chromothripsis was defined according to Korbel and Campbell’s criteria [28], when three out of six criteria were satisfied (the remaining criteria could not be

assessed by SNP array analysis). Chromothripsis was assessed by scanning SNP array segment files using _CTLP_-Scanner (using R v3.3.2 [35] and “_CTLP_ scanner” package [21]). The following

thresholds were set: Log ratio ≥8, more than 10 breakpoints, minimum segment size of 10 kb, and 0.3 as signal distance between adjacent segments. Events with a prevalent copy number (CN)

status and changes involving ≤10% of detected region were excluded. MICROARRAY STATISTICAL ANALYSES Based on the presence/absence of chromothripsis, AML samples were divided in two groups: a

group of cases (chromothripsis-positive) and a group of controls (chromothripsis-negative) and enrichment of CNA events between the two groups was examined. The data set was stratified for

event type and the statistical tests were performed on amplifications of one or more DNA copies and heterozygous or homozygous deletions. In each patient, multiple events of the same type in

the same gene were considered as one. Fisher’s exact test was used to compare frequencies in genes’ event between two groups. All _p_ values were adjusted for multiple testing. For testing

at a pathway level, genes were annotated in the Reactome database [36]. Pathway enrichment analysis was performed at patient level by means of an over-representation test. Then, the adjusted

_p_ values obtained for a certain pathway across all patients were used as predictor variable in a logistic regression model. The significance level was set at 10–4. CHROMOSOME BANDING

ANALYSIS AND FISH FISH analysis was carried out on previously G-banded metaphases prepared by chromosome banding analysis (CBA) technique according to the manufacturer’s instructions.

CLINICAL STATISTICAL ANALYSIS Due to the data-pool feature of our set, missing data will be detailed in the result section. OS was assessed as the time in days from diagnosis to death or

last follow-up. Fisher’s exact test and chi-squared test were used for crosstabs and difference between distributions was assessed with median test for independent samples and Mann–Whitney

_U_ test. Survival analysis and COX-HR were used as appropriate. RESULTS CLINICAL AND MOLECULAR PATIENT CHARACTERISTICS All patients' clinical and molecular characteristics are listed

in Table 1, missing data are quantified in Table S1. In our cohort, 26 out of 395 patients (6.6%) showed chromothripsis involving different chromosomes. CORRELATION OF CHROMOTHRIPSIS WITH

CLINICAL AND MOLECULAR PARAMETERS IN AML PATIENTS We compared chromothripsis-negative patients with chromothripsis-positive ones (Table 2). Chromothripsis-positive patients were older. They

had a higher median age (67 and 60 years, respectively _p_ = 0.002, Figure S1C) and a lower WBC count mean at diagnosis (6342/mm3 vs. 30,059/mm3, respectively _p_ = 0.040, Figure S1A).

Chromothripsis-positive patients presented a prevalence of complex karyotype and were classified as HR disease according to ELN [37] definition (_p_ < 0.001, Figure S1D). Based on genetic

features, chromothripsis was associated with _TP53_ loss (_p_ < 0.001) and _TP53_ mutations (_p_ < 0.001). Only 3/26 patients did not harbor any _TP53_ alteration: one patient was

_TP53_ wild-type and have no karyotype aberration involving 17p, two patients were not tested for _TP53_ mutation because of unavailable material at diagnosis. Chromothripsis was mutually

exclusive with _FLT3_ (Figure S1B, _p_ = 0.025) and _NPM1_ mutations (_p_ = 0.032). CHROMOTHRIPSIS DEFINED A GROUP OF AML PATIENTS WITH POOR RESPONSE TO INDUCTION THERAPY At diagnosis,

patients received chemotherapy, hypomethylating agents, or best supportive therapy (Table 3). Patients with chromothripsis were treated with intensive chemotherapy in a smaller proportion

(_p_ = 0.003). There was no difference in use of Gemtuzumab Ozagomicin during induction between the two group of patients (_p_ = 1.000) and there was a similar transplant rate between the

two groups [21% of patients with chromothripsis and 31% of patients without chromothripsis received hematopoietic stem cell transplant (HSCT), _p_ = 0.448]. Chromothripsis defined a group of

patients with poor prognosis. Three out of 10 patients with chromothripsis (30%) responded to induction, a significant lower proportion if compared with 152/229 patients without

chromothripsis (66.4%, _p_ = 0.036). CHROMOTHRIPSIS DEFINED A GROUP OF AML PATIENTS WITH POOR OS Patients with chromothripsis showed a worse OS (median OS of 120 days compared to 494 days

for patients without chromothripsis, _p_ < 0.001, Fig. 1a). In patients with available HSCT data, we confirmed the difference by censoring OS at HSCT with a median OS of 120 and 400 days

in the two groups (_p_ < 0.001, Fig. 1b). Patients with chromothripsis had the worst prognosis among patients with HR features according ELN [37] risk stratification (median OS of 120 and

258 days in the two groups, _p_ = 0.011, Fig. 1c). This observation was confirmed when censoring OS at HSCT (median OS of 120 and 211 days in the two groups, _p_ = 0.022, Fig. 1d).

Moreover, the impact of chromothripsis on OS was evaluated in patients with HR features according ELN [37] risk stratification, who received induction chemotherapy. We report a difference in

survival between patients with and without chromothripsis (median OS of 120 and 295 days, respectively, _p_ = 0.040, Fig. 1e) and a trend toward statistical significance in HSCT-censored

analysis (median OS of 120 and 242 days, respectively, _p_ = 0.055, Fig. 1f). Patients with chromothripsis did not show differences in baseline characteristics or in survival compared to

patients harboring _TP53_ mutation, _TP53_ loss, or to the group of patients harboring _TP53_ alteration (loss and/or mutation), due to the high co-occurrence of these two phenomena (Figure 

S2 and Table S2). However, in our set, patients with chromothripsis showed a survival disadvantage near to the statistical significance threshold when compared with patients with _TP53_ loss

(Fig. S2B, _p_ = 0.049). CHROMOTHRIPSIS WAS AN INDEPENDENT PREDICTOR OF SHORTER OS IN COX-HR MODEL We built a prognostic model using COX-HR with forward conditional method, considering

chromothripsis event, secondary AML, ELN risk, induction therapy, _FLT3_ and _NPM1_ mutation as categorical variables and age at diagnosis. _TP53_ status was not included in the model for

the high co-occurrence of chromothripsis and _TP53_ alterations. In the optimal model, chromothripsis (HR: 2.286, 95% CI: 1.327–3.940, _p_ = 0.003) and secondary disease was associated with

augmented risk of death, while ELN low risk, intermediate 1 and intermediate 2 risk were associated with better outcome (Fig. 2). Chromothripsis was a consistent risk factor in COX-HR model

built in ELN HR population considering chromothripsis, secondary AML, induction therapy, _FLT3_ mutation, and _NPM1_ mutation as categorical variables, and age of diagnosis (HR: 2.070, 95%

CI: 1.167–3.672, _p_ = 0.013, model not shown). Chromothripsis was also a consistent risk factor in COX-HR model built in ELN HR population treated with intensive therapies considering

chromothripsis, secondary AML, _FLT3_ mutation, and _NPM1_ mutation as categorical variables, and age of diagnosis (HR: 2.227, 95% CI: 1.022–4.850, _p_ = 0.044, model not shown). GENOMIC

CHARACTERISTICS OF AML PATIENTS WITH CHROMOTHRIPSIS We detected chromothripsis on chromosome 12 (23% of events), 17 and 5 (17% of events both), chromosomes 6 (10% of events), 3 and 8 (6.6%

of events both), 7, 10, 11, 15, and 20 (3.3% of events each) (Fig. 3, and Fig. S3). SNP array analyses showed that chromothripsis-positive patients were characterized by a high grade of

genomic aberrations. We found a minimal common-deleted region in 24/26 patients with chromothripsis (5q31.1–5q33.1). Among chromothripsis-negative patients, 51/369 harbored at least a CNA of

9 Mb in the 5q arm. There was a higher incidence in macroscopic deletions on 5q in patients with chromothripsis (_p_ < 0.0001). Patients with chromothripsis presented higher mean of CNA

than patients without chromothripsis (mean of 418 vs. 188 CNA per patient; Fig. 4, CIRCOS [38] external level). SIGNIFICATIVE GENOMIC ALTERATIONS MAPPED IN RELATIVELY SMALL CHROMOSOMIC

REGIONS Fisher's exact test showed that a large group of 1359 genes were significantly altered in deletion (both heterozygous and homozygous) in chromothripsis-positive patients rather

than chromothripsis-negative ones (data not shown). These genes map on chromosome 5q, 3q, 12p, 3p, 4q, 7q, 12p, 16q, and 17p. Considering chromosome position of genes associated with

chromothripsis, we found that CNA randomly affected the entire 5q and whole chromosome 3. In the other chromosomes, we found that statistically significant CNA mapped in relatively small

regions (complete list of genes in Fig. 4, CIRCOS [38] internal level). These regions included deletions of genes involved in Atlas of Genetics and Cytogenetics in Oncology and Haematology,

in particular on chromosome 4q28–32 (_SFRP2_), 7q31.1–36.3 (_CAV1, EPHA1_, and _NRF1_), 12p11.21–13.3 (_EPS8_, _RECQL_, and _GUCY2C)_, 16q22–24.3 (transcription factors _CBFA2T3_ and

_FOXF1_;_ CDT1_ involved in DNA replication; and the Fanconi Anemia gene _FANCA_), and 17p13–13.1 (_ALOX12_ and _CLDN7_) (Fig. 4). Genes were filtered as described in “Methods” and we showed

that 95 genes were associated with chromothripsis (complete list of genes in Fig. 4, CIRCOS [38] internal level). PATHWAY ENRICHMENT IN PATIENTS WITH CHROMOTHRIPSIS REACTOME enrichment of

pathways is reported in Tables S3 and S4. DNA repair, E2F-mediated regulation of DNA replication, signaling pathways involving PI3K, phospholipid biosynthesis and metabolism, and various

growth factors signaling pathways scored in the best 1% of pathways enriched for amplification events in chromothripsis. CTLA4 inhibitory signaling, synthesis of phosphatidylinositol

phosphate (PIP) at the late endosome membrane, fanconi anemia pathway, genes regulating G0 and early G1 phase, pre-NOTCH transcription and translation scored in the best 1% of pathways

enriched for deletion events in cases with chromothripsis. In the subcohort of patients with _TP53_ alteration, when we compared patients with chromothripsis (_n_ = 22) and patients without

chromothripsis (_n_ = 44), we did not detect any significant difference in terms of differentially altered genes and pathways (with a significance threshold of _p_ < 10–4). CHROMOTHRIPSIS

IS ASSOCIATED WITH MARKER, DERIVATIVE, AND RING CHROMOSOMES FORMATION In order to better characterize the chromosomes affected by chromothripsis, we performed FISH analysis in 7/26 cases

with available material. Most cases (5/7) showed the presence of marker or ring chromosomes. In four cases, the chromosomes affected by chromothripsis (chromosomes 8, 11, 12, and 17) were

reported by CBA as monosomic chromosomes, while, by FISH, portions of these chromosomes were identified on marker chromosomes. In cases involving chromosomes 8 and 11, the rearrangement led

to amplification of MYC and _KMT2A_ (MLL) genes, respectively. In cases involving chromosomes 12 and 17, parts of the chromosomes affected by chromothripsis were identified on markers and on

derivative chromosomes resulting from unbalanced translocations. In other two cases, the chromosome involved in chromothripsis was annotated as derivative chromosome. Moreover, FISH

highlighted the presence of a homogeneously staining region on the derivative chromosome 3 due to MDS1 and EVI1 complex locus amplification in one case and of a complex translocation

involving chromosome 5 in the other case. In the last patient, the chromosome affected by chromothripsis was identified as ring chromosome 17 leading to loss of _TP53_. FISH results are

shown in Fig. 5. DISCUSSION The purposes of this study was to define the incidence of chromothripsis in newly diagnosed adult AML patients, its impact on survival, and its genomic background

in AML. To detect chromothripsis, we used a custom algorithm based on _CTLP_ scanner [21] and Korbel and Campbell’s criteria [28] that detected chromothripsis based on SNP array data. Our

results, obtained in a large set of patients, indicate that chromothripsis is a non-anecdotal finding in AML. The overall incidence of chromothripsis was concordant with studies conducted on

fewer patients [15, 16]. Chromothripsis appeared to be associated with higher age and lower WBC count at diagnosis, and mutually exclusive with _FLT3_ and _NPM1_ mutations, these data were

never reported in acute leukemia. Moreover, we confirmed the strong association between chromothripsis and _TP53_ dysregulation [9, 15], thus reinforcing the importance of _TP53_ for the

maintenance of genomic stability and integrity. For the first time, we pointed out that the only detection of chromothripsis is sufficient to define a group of patients with poor prognosis

in the general AML population and in the ELN [37] high-risk population; chromothripsis was a determinant of poor OS in the COX-HR optimal model. We further performed survival analysis in the

subset of patients with _TP53_ alterations, as _TP53_ alone was reported to define patients with the worst prognosis in AML [39,40,41]; we did not detect differences in survival defined by

to have or not to have chromothripsis, and this was the main limitation of our study. This may be explained by the low number of patients in this subset, the moderate number of patients with

missing follow-up information, and by the slightly lower mean OS of patients with _TP53_ alteration in our set when compared with literature data [40]. Furthermore, we cannot exclude that

chromothripsis may be a phenotypical manifestation, or simply an epiphenomenon, of _TP53_ alteration. Further tests are needed in patients’ sets enriched to have _TP53_ alteration or to have

chromothripsis without _TP53_ alteration. Our work describes chromothripsis biological scenario based on SNP high-throughput genomic analyses; even with the limitations due to lack in

availability of whole-genome sequencing or gene expression data in our patients’ set, we found several events significantly associated with chromothripsis. Patients with chromothripsis

presented a high genomic instability, highlighted by the high number of CNA per patient and a high recurrence of losses in chromosome 3 and 5q and high incidence of complex karyotype; this

result is consistent with literature [9, 15, 18, 24, 25, 42,43,44]. Interestingly, we found in most patients with chromothripsis a minimal common-deleted region in 5q31.1–5q33.1, containing

key genes involved in RAS, PI3K/AKT, transcriptional factors, DNA damage, histone modification, and SMAD signaling. Moreover, we found heterozygous and homozygous genes’ deletions associated

with chromothripsis that clustered in relatively small genomic regions. Within altered genes, we hypothesized that _FANCA_ could be a candidate to cooperate at a multi-genic and multi-step

mechanism that initiate and maintain chromothripsis. _FANCA_ deletion is found in a relatively small genome region; furthermore, it was found deleted in sporadic AML [45] and it originate a

syndrome that predispose to AML. Significantly, when we performed pathway enrichment, we found DNA damage and fanconi anemia pathways scoring within the best 1%, together with early G0–G1

regulation, cell cycle, and several other pathways that could be possibly related genesis and maintenance of chromothripsis. Tumors characterized by genetic instability and by alterations in

DNA damage pathway could be the ideal target of innovative therapeutic approaches like checkpoints inhibitors [46], and combination therapies based on these agents could be an option in

chromothripsis patient for patients with poor prognosis. Furthermore, our findings characterize a subset of AML patients with a high burden of alterations and potentially neoantigens that

could be the optimal candidates for novel therapies like PD1/PDL1 blocking monoclonal antibodies and immune modulating drugs, maybe in combinations with hypomethylating agents. Compared to

the subset of patients with _TP53_ alteration, we did not find significant pathways and genes. This may be due to the low number of patients in this subset, and it requires further studies

in enriched population with multi-omics approach. Finally, although only a subset of cases could be analyzed by CBA and FISH, our results showed that chromothripsis was associated with

marker, derivative, and ring chromosomes, suggesting that these complex chromosomal rearrangements can arise from chromothripsis. This finding is in accordance with what Bochtler and

colleagues previously reported [15]. In conclusion, chromothripsis is clearly a catastrophic event defining a consistent group of patients with poor prognosis, which could be candidate per

se to novel approaches; chromothripsis is associated with losses of 5q31.1–5q33.1 in most patients, and with a complex genomic background in which _FANCA, TP53_, and genes regulating cell

cycle seem to be fundamental and demand further preclinical studies. REFERENCES * Byrd JC, Mrózek K, Dodge RK, Carroll AJ, Edwards CG, Arthur DC, et al. Pretreatment cytogenetic

abnormalities are predictive of induction success, cumulative incidence of relapse, and overall survival in adult patients with de novo acute myeloid leukemia: results from Cancer and

Leukemia Group B (CALGB 8461). Blood. 2002;100:4325–36. Article  PubMed  CAS  Google Scholar  * Schoch C, Kern W, Kohlmann A, Hiddemann W, Schnittger S, Haferlach T. Acute myeloid leukemia

with a complex aberrant karyotype is a distinct biological entity characterized by genomic imbalances and a specific gene expression profile. Genes Chromosomes Cancer. 2005;43:227–38.

Article  PubMed  CAS  Google Scholar  * Döhner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Büchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an

international expert panel. Blood. 2017;129:424–47. Article  PubMed  PubMed Central  CAS  Google Scholar  * Meyerson M, Pellman D. Cancer genomes evolve by pulverizing single chromosomes.

Cell. 2011;144:9–10. Article  PubMed  CAS  Google Scholar  * Liu P, Erez A, Nagamani SCS, Dhar SU, Kolodziejska KE, Dharmadhikari AV, et al. Chromosome catastrophes involve replication

mechanisms generating complex genomic rearrangements. Cell. 2011;146:889–903. Article  PubMed  PubMed Central  CAS  Google Scholar  * Boeva V, Jouannet S, Daveau R, Combaret V, Pierre-Eugène

C, Cazes A, et al. Breakpoint features of genomic rearrangements in neuroblastoma with unbalanced translocations and chromothripsis. PLoS One. 2013;8:e72182. Article  PubMed  PubMed Central

  CAS  Google Scholar  * Tapia-Laliena MA, Korzeniewski N, Hohenfellner M, Duensing S. High-risk prostate cancer: a disease of genomic instability. Urol Oncol. 2014;32:1101–7. Article 

PubMed  Google Scholar  * Furgason JM, Koncar RF, Michelhaugh SK, Sarkar FH, Mittal S, Sloan AE, et al. Whole genome sequence analysis links chromothripsis to EGFR, MDM2, MDM4, and CDK4

amplification in glioblastoma. Oncoscience. 2015;2:618–28. Article  PubMed  PubMed Central  Google Scholar  * Rausch T, Jones DTW, Zapatka M, Stütz AM, Zichner T, Weischenfeldt J, et al.

Genome sequencing of pediatric medulloblastoma links catastrophic DNA rearrangements with TP53 mutations. Cell. 2012;148:59–71. Article  PubMed  PubMed Central  CAS  Google Scholar  *

Kloosterman WP, Koster J, Molenaar JJ. Prevalence and clinical implications of chromothripsis in cancer genomes. Curr Opin Oncol. 2014;26:64–72. Article  PubMed  CAS  Google Scholar  * Nones

K, Waddell N, Wayte N, Patch A-M, Bailey P, Newell F, et al. Genomic catastrophes frequently arise in esophageal adenocarcinoma and drive tumorigenesis. Nat Commun. 2014;5:5224. Article 

PubMed  CAS  Google Scholar  * Przybytkowski E, Lenkiewicz E, Barrett MT, Klein K, Nabavi S, Greenwood CMT, et al. Chromosome-breakage genomic instability and chromothripsis in breast

cancer. BMC Genom. 2014;15:579. Article  Google Scholar  * Hirsch D, Kemmerling R, Davis S, Camps J, Meltzer PS, Ried T, et al. Chromothripsis and focal copy number alterations determine

poor outcome in malignant melanoma. Cancer Res. 2013;73:1454–60. Article  PubMed  CAS  Google Scholar  * Magrangeas F, Avet-Loiseau H, Munshi NC, Minvielle S. Chromothripsis identifies a

rare and aggressive entity among newly diagnosed multiple myeloma patients. Blood. 2011;118:675–8. Article  PubMed  PubMed Central  CAS  Google Scholar  * Bochtler T, Granzow M, Stölzel F,

Kunz C, Mohr B, Kartal-Kaess M, et al. Marker chromosomes can arise from chromothripsis and predict adverse prognosis in acute myeloid leukemia. Blood. 2017;129:1333–42. Article  PubMed  CAS

  Google Scholar  * Mackinnon RN, Campbell LJ. Chromothripsis under the microscope: a cytogenetic perspective of two cases of AML with catastrophic chromosome rearrangement. Cancer Genet.

2013;206:238–51. Article  PubMed  CAS  Google Scholar  * Forero-Castro M, Robledo C, Benito R, Abáigar M, África Martín A, Arefi M, et al. Genome-wide DNA copy number analysis of acute

lymphoblastic leukemia identifies new genetic markers associated with clinical outcome. PLoS One. 2016;11:e0148972. Article  PubMed  PubMed Central  CAS  Google Scholar  * Ratnaparkhe M,

Hlevnjak M, Kolb T, Jauch A, Maass KK, Devens F, et al. Genomic profiling of acute lymphoblastic leukemia in ataxia telangiectasia patients reveals tight link between ATM mutations and

chromothripsis. Leukemia. 2017;31:2048–56. https://doi.org/10.1038/leu.2017.55. Article  PubMed  CAS  Google Scholar  * Bassaganyas L, Bea S, Escaramis G, Tornador C, Salaverria I, Zapata L,

et al. Sporadic and reversible chromothripsis in chronic lymphocytic leukemia revealed by longitudinal genomic analysis. Leukemia. 2013;27:2376–9. Article  PubMed  PubMed Central  CAS 

Google Scholar  * Bertelsen B, Nazaryan-Petersen L, Sun W, Mehrjouy MM, Xie G, Chen W, et al. A germline chromothripsis event stably segregating in 11 individuals through three generations.

Genet Med. 2015;18:494–500. https://doi.org/10.1038/gim.2015.112. Article  PubMed  Google Scholar  * Cai H, Kumar N, Bagheri HC, von Mering C, Robinson MD, Baudis M. Chromothripsis-like

patterns are recurring but heterogeneously distributed features in a survey of 22,347 cancer genome screens. BMC Genom. 2014;15:82. Article  CAS  Google Scholar  * Donley N, Thayer MJ. DNA

replication timing, genome stability and cancer: late and/or delayed DNA replication timing is associated with increased genomic instability. Semin Cancer Biol. 2013;23:80–9. Article  PubMed

  PubMed Central  CAS  Google Scholar  * Liu G, Stevens JB, Horne SD, Abdallah BY, Ye KJ, Bremer SW, et al. Genome chaos: survival strategy during crisis. Cell Cycle. 2014;13:528–37. Article

  PubMed  CAS  Google Scholar  * Mardin BR, Drainas AP, Waszak SM, Weischenfeldt J, Isokane M, Stütz AM, et al. A cell-based model system links chromothripsis with hyperploidy. Mol Syst

Biol. 2015;11:828. Article  PubMed  PubMed Central  CAS  Google Scholar  * Maciejowski J, Li Y, Bosco N, Campbell PJ, de Lange T. Chromothripsis and kataegis induced by telomere crisis.

Cell. 2015;163:1641–54. Article  PubMed  PubMed Central  CAS  Google Scholar  * Jacoby MA, De Jesus Pizarro RE, Shao J, Koboldt DC, Fulton RS, Zhou G, et al. The DNA double-strand break

response is abnormal in myeloblasts from patients with therapy-related acute myeloid leukemia. Leukemia. 2014;28:1242–51. Article  PubMed  CAS  Google Scholar  * Govind SK, Zia A,

Hennings-Yeomans PH, Watson JD, Fraser M, Anghel C, et al. ShatterProof: operational detection and quantification of chromothripsis. BMC Bioinforma. 2014;15:78. Article  Google Scholar  *

Korbel JO, Campbell PJ. Criteria for inference of chromothripsis in cancer genomes. Cell. 2013;152:1226–36. Article  PubMed  CAS  Google Scholar  * Stephens PJ, Greenman CD, Fu B, Yang F,

Bignell GR, Mudie LJ, et al. Massive genomic rearrangement acquired in a single catastrophic event during cancer development. Cell. 2011;144:27–40. Article  PubMed  PubMed Central  CAS 

Google Scholar  * Kovtun IV, Murphy SJ, Johnson SH, Cheville JC, Vasmatzis G. Chromosomal catastrophe is a frequent event in clinically insignificant prostate cancer. Oncotarget.

2015;6:29087–96. Article  PubMed  PubMed Central  Google Scholar  * Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, et al. The 2016 revision to the World Health

Organization classification of myeloid neoplasms and acute leukemia. Blood. 127:2391–405. * World Medical Association. World Medical Association Declaration of Helsinki. JAMA. 2013;310:2191.

Article  CAS  Google Scholar  * Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process

for providing translational research informatics support. J Biomed Inform. 2009;42:377–81. Article  PubMed  Google Scholar  * Parkin B, Erba H, Ouillette P, Roulston D, Purkayastha A, Karp

J, et al. Acquired genomic copy number aberrations and survival in adult acute myelogenous leukemia. Blood. 2010;116:4958–67. Article  PubMed  PubMed Central  CAS  Google Scholar  * R Core

Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2016. * Fabregat A, Sidiropoulos K, Garapati P, Gillespie M, Hausmann

K, Haw R, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2016;44:D481–7. Article  PubMed  CAS  Google Scholar  * Estey EH. Acute myeloid leukemia: 2012 update on diagnosis,

risk stratification, and management. Am J Hematol. 2012;87:89–99. Article  PubMed  Google Scholar  * Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, et al. Circos: an

information aesthetic for comparative genomics. Genome Res. 2009;19:1639–45. Article  PubMed  PubMed Central  CAS  Google Scholar  * Kadia TM, Jain P, Ravandi F, Garcia-Manero G, Andreef M,

Takahashi K, et al. T_P53_ mutations in newly diagnosed acute myeloid leukemia: clinicomolecular characteristics, response to therapy, and outcomes. Cancer. 2016;122:3484–91. Article  CAS 

PubMed  Google Scholar  * Stengel A, Kern W, Haferlach T, Meggendorfer M, Fasan A, Haferlach C. The impact of TP53 mutations and TP53 deletions on survival varies between AML, ALL, MDS and

CLL: an analysis of 3307 cases. Leukemia. 2017;31:705–11. Article  PubMed  CAS  Google Scholar  * Papaemmanuil E, Gerstung M, Bullinger L, Gaidzik VI, Paschka P, Roberts ND, et al. Genomic

classification and prognosis in acute myeloid leukemia. N Engl J Med. 2016;374:2209–21. Article  PubMed  PubMed Central  CAS  Google Scholar  * Zhang C-Z, Spektor A, Cornils H, Francis JM,

Jackson EK, Liu S, et al. Chromothripsis from DNA damage in micronuclei. Nature. 2015;522:179–84. Article  PubMed  PubMed Central  CAS  Google Scholar  * Leibowitz ML, Zhang C-Z, Pellman D.

Chromothripsis: a new mechanism for rapid karyotype evolution. Annu Rev Genet. 2015;49:183–211. Article  PubMed  CAS  Google Scholar  * Poot M, Haaf T. Mechanisms of origin, phenotypic

effects and diagnostic implications of complex chromosome rearrangements. Mol Syndromol. 2015;6:110–34. Article  PubMed  PubMed Central  Google Scholar  * Tischkowitz MD, Morgan NV, Grimwade

D, Eddy C, Ball S, Vorechovsky I, et al. Deletion and reduced expression of the Fanconi anemia FANCA gene in sporadic acute myeloid leukemia. Leukemia. 2004;18:420–5. Article  PubMed  CAS 

Google Scholar  * Ghelli Luserna di Rora’ A, Iacobucci I, Martinelli G. The cell cycle checkpoint inhibitors in the treatment of leukemias. J Hematol Oncol. 2017;10:77. Article  PubMed 

PubMed Central  CAS  Google Scholar  * Röllig C, Bornhäuser M, Thiede C, Taube F, Kramer M, Mohr B, et al. Long-term prognosis of acute myeloid leukemia according to the new genetic risk

classification of the European LeukemiaNet recommendations: evaluation of the proposed reporting system. J Clin Oncol J Am Soc Clin Oncol. 2011;29:2758–65. Article  Google Scholar  Download

references ACKNOWLEDGEMENTS Prof. Michele Baccarani and Prof. Michele Cavo directed Istituto Seràgnoli. Prof. Sami Nimer Malek granted access to his previously published data and gave us

detailed and useful information on data organization. RK received funding form the Austrian Science Fund (SFB F4702). This work was supported in part by “Progetto Regione-Università

2010-12”, by “FP7 NGS-PTL project (agreement no. 306242-NGS-PTL),” and by HARMONY Project. We thank all the members of the NGS-PTL consortium and in particular Prof. Clelia Tiziana

Storlazzi. We also thank ELN, AIL, AIRC, and PRIN. AUTHOR INFORMATION Author notes * Ilaria Iacobucci Present address: Division of Hematology and Oncology, Medical University of Innsbruck,

Innsbruck, Austria * These authors contributed equally: Maria Chiara Fontana, Giovanni Marconi. * These authors jointly supervised this work: Giorgia Simonetti, Robert Kralovics, Giovanni

Martinelli. AUTHORS AND AFFILIATIONS * Institute of Hematology “L. and A. Seràgnoli”, University of Bologna, Bologna, Italy Maria Chiara Fontana, Giovanni Marconi, Eugenio Fonzi, Cristina

Papayannidis, Andrea Ghelli Luserna di Rorá, Antonella Padella, Vincenza Solli, Eugenia Franchini, Emanuela Ottaviani, Anna Ferrari, Carmen Baldazzi, Nicoletta Testoni, Ilaria Iacobucci, 

Simona Soverini, Viviana Guadagnuolo, Stefania Paolini, Marco Manfrini, Michele Cavo, Giorgia Simonetti & Giovanni Martinelli * CeMM Research Center for Molecular Medicine of the

Austrian Academy of Sciences, Wien, Austria Jelena D. Milosevic Feenstra & Robert Kralovics * Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA Ilaria

Iacobucci * MLL Munich Leukemia Laboratory, Munich, Germany Torsten Haferlach * Department of Internal Medicine - Hematology and Oncology, Masaryk University and Hospital, Brno, Czech

Republic Lukas Semerad, Michael Doubek & Zdenek Racil * Division of Hematology and Oncology, Medical University of Innsbruck, Innsbruck, Austria Michael Steurer Authors * Maria Chiara

Fontana View author publications You can also search for this author inPubMed Google Scholar * Giovanni Marconi View author publications You can also search for this author inPubMed Google

Scholar * Jelena D. Milosevic Feenstra View author publications You can also search for this author inPubMed Google Scholar * Eugenio Fonzi View author publications You can also search for

this author inPubMed Google Scholar * Cristina Papayannidis View author publications You can also search for this author inPubMed Google Scholar * Andrea Ghelli Luserna di Rorá View author

publications You can also search for this author inPubMed Google Scholar * Antonella Padella View author publications You can also search for this author inPubMed Google Scholar * Vincenza

Solli View author publications You can also search for this author inPubMed Google Scholar * Eugenia Franchini View author publications You can also search for this author inPubMed Google

Scholar * Emanuela Ottaviani View author publications You can also search for this author inPubMed Google Scholar * Anna Ferrari View author publications You can also search for this author

inPubMed Google Scholar * Carmen Baldazzi View author publications You can also search for this author inPubMed Google Scholar * Nicoletta Testoni View author publications You can also

search for this author inPubMed Google Scholar * Ilaria Iacobucci View author publications You can also search for this author inPubMed Google Scholar * Simona Soverini View author

publications You can also search for this author inPubMed Google Scholar * Torsten Haferlach View author publications You can also search for this author inPubMed Google Scholar * Viviana

Guadagnuolo View author publications You can also search for this author inPubMed Google Scholar * Lukas Semerad View author publications You can also search for this author inPubMed Google

Scholar * Michael Doubek View author publications You can also search for this author inPubMed Google Scholar * Michael Steurer View author publications You can also search for this author

inPubMed Google Scholar * Zdenek Racil View author publications You can also search for this author inPubMed Google Scholar * Stefania Paolini View author publications You can also search

for this author inPubMed Google Scholar * Marco Manfrini View author publications You can also search for this author inPubMed Google Scholar * Michele Cavo View author publications You can

also search for this author inPubMed Google Scholar * Giorgia Simonetti View author publications You can also search for this author inPubMed Google Scholar * Robert Kralovics View author

publications You can also search for this author inPubMed Google Scholar * Giovanni Martinelli View author publications You can also search for this author inPubMed Google Scholar

CORRESPONDING AUTHORS Correspondence to Maria Chiara Fontana, Giovanni Marconi or Giovanni Martinelli. ETHICS DECLARATIONS CONFLICT OF INTEREST GM: ARIAD/INCYTE, Pfizer, Celgene, Amgen,

J&J, and Roche as consultant. The remaining authors declare that they have no conflict of interest. ELECTRONIC SUPPLEMENTARY MATERIAL SUPPLEMENTAL MATERIAL RIGHTS AND PERMISSIONS OPEN

ACCESS This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and

reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, and provide a link to the Creative Commons license. You do not have

permission under this license to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s

Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not

permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit

http://creativecommons.org/licenses/by-nc-nd/4.0/. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Fontana, M.C., Marconi, G., Feenstra, J.D.M. _et al._ Chromothripsis in acute

myeloid leukemia: biological features and impact on survival. _Leukemia_ 32, 1609–1620 (2018). https://doi.org/10.1038/s41375-018-0035-y Download citation * Received: 04 August 2017 *

Revised: 31 October 2017 * Accepted: 21 November 2017 * Published: 23 February 2018 * Issue Date: July 2018 * DOI: https://doi.org/10.1038/s41375-018-0035-y SHARE THIS ARTICLE Anyone you

share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not currently available for this article. Copy to clipboard Provided by the

Springer Nature SharedIt content-sharing initiative