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Keywords:

  • acute myeloid leukaemia;
  • genetic profile;
  • genetic interaction;
  • acute myeloid leukaemia classification

Summary

  1. Top of page
  2. Summary
  3. Genetic prognostic markers identified in AML
  4. Conclusion
  5. Acknowledgement
  6. References

Genetic profiling in acute myeloid leukaemia (AML) is a moving target. Only 4 years ago, AML was re-classified, based on karyotypic abnormalities. However, numerous important new mutations and other genetic abnormalities that were not considered in this classification have been identified. Current cytogenetic-based classification is limited by the substantial number of intermediate-risk patients in whom the preferred therapy is debatable. In addition, the majority of AML patients co-express multiple mutations and cannot be easily categorized into predefined homogenous groups. The tremendous progress in mass sequencing allows parallel identification of multiple genetic aberrations in large cohorts. Thus, a new concept of genetic profiling has arisen. Genes and proteins biologically interact with each other; therefore, it should not be surprising that mutations in different genes interact. Prognosis is determined by the composition of mutations and aberrations in leukaemic stem cells. As a consequence, clinical decisions no longer rely on scant genetic data and require comprehensive genetic evaluation. Some non-genetic parameters are also important and should be incorporated into the clinical decision algorithm. Genetic interaction-based profiles are challenging and recent studies demonstrate an improvement in prognostic predictions with this model. Thus, genetic profiling is likely to have a major therapeutic impact, at least for intermediate-risk cytogenetics.

Genetic aberrations within leukaemic cells have become the most prominent prognostic marker in acute myeloid leukaemia (AML). With the current explosion of novel genetic analytic tools, the number of genes found to be associated with patient outcome is growing rapidly. Utilizing different modalities, cytogenetics, next-generation sequencing or gene expression, numerous aberrations of all kinds have been reported to be of clinical importance in AML. Integrating data from various studies and sources, obtained by different methods, into a comprehensive logical working scheme is a major challenge in the treatment of AML.

The basic paradigm of therapy for AML has not substantially changed in the past three decades. The treatment plan for AML is determined following two major clinical decisions, taken at different points of care. First, physicians decide whether a patient is ‘fit’ for aggressive induction and choose a first line of therapy accordingly. The second point of care arises when a remission is achieved. At that point, the best post-remission strategy is decided. Availability of genetic testing creates a novel, third point of clinical debate, the question of monitoring for minimal residual disease. However, despite numerous genetic aberrations identified in AML, only few are commonly used to guide these clinical decisions. In the following review, genetic data available in AML will be summarized and the appropriate way to apply these into clinical practice will be discussed.

Genetic prognostic markers identified in AML

  1. Top of page
  2. Summary
  3. Genetic prognostic markers identified in AML
  4. Conclusion
  5. Acknowledgement
  6. References

Cytogenetics

Karyotypic abnormalities are the first and most widely established genetic prognostic markers in AML. Numerous cytogenetic changes have been recognized in AML, with varying prognostic significance. The role of a specific cytogenetic aberration in leukaemogenesis is a productive field for research; yet, unique biological mechanisms were discovered for only few recurrent aberrations [e.g., t(15;17), t(8:21), MLL translocations (Kakizuka et al, 1991; Schoch et al, 2003; Prebet et al, 2009)]. Patient outcome has been known to be associated with specific cytogenetic aberrations for more than 25 years. In the last 15 years major cooperative leukaemia research groups around the world have assessed the cytogenetic prognostic value in large uniformly treated cohorts. The UK Medical Research Council (MRC) 10 trial (Grimwade et al, 1998) included 1966 patients younger than 55 years of age, most of them with de-novo AML. Evaluation of the prognostic value of each recurrent cytogenetic aberration, led to a general classification of three cytogenetic risk groups (favourable, intermediate and adverse). Similar results were reported by the US intergroup study in 609 patients younger than 56 years (Slovak et al, 2000), and by the Cancer and Leukaemia Group B (CALGB) in 1213 adult patients of all ages (Byrd et al, 2002) (Fig 1). The MRC11 trial, which included 1065 patients older than 55 years of age, a Dutch-Belgian Hemato-Oncology Cooperative Group (HOVON) study that included patients older than 60 years and an Eastern Cooperative Oncology Group (ECOG) study of patients older than 55 years all confirmed that karyotypes define biologically distinguished diseases and validate their prognostic value for all age groups (Grimwade et al, 2001; Rowe et al, 2004; van der Holt et al, 2007). Due to insufficient numbers of patients on studies, multiple rare aberrations were grouped together and analysed as a group. Efforts have been made to sort data regarding specific rare but recurrent aberrations from cooperative group databases. Breems et al (2008) first reported that monosomal karyotype (excluding sex chromosomes) has an extremely poor prognosis, even more so than a complex karyotype. This observation was confirmed by the Southwest Oncology Group (SWOG), Groupe Ouest Est d'Etude des Leucémies et Autres Maladies du Sang (GOELAMS), the German-Austrian AML Study Group (Medeiros et al, 2010; Perrot et al, 2011; Kayser et al, 2012) and the Japan Adult Leukaemia Study Group (Yanada et al, 2012) in various age groups and following different protocols. Combination of a monosomal karyotype and multiply complexed karyotype (≥4) appears to confer the poorest prognosis (Haferlach et al, 2012a). A commendably exhaustive effort to explore the value of rare cytogenetic aberrations has been conducted by the MRC, with data on 5876 AML patients (Grimwade et al, 2010a) (Fig 2). This study confirmed the very poor prognosis of monosomy and discriminated t(3;5) without additional adverse features, to be considered not as poor as other chromosome 3 aberrations. Nevertheless, this very large study led to reassignment of only 299 patients (275 cases moved from intermediate to adverse and 24 conversely).

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Figure 1. Karyotype and prognosis in AML. Impact of cytogenetic aberration on overall survival in young adult AML patients as was reported in the US intergroup study (panel A), MRC 10 (panel B) and CALGB (panel C) trials. These studies were originally published in Blood: Slovak et al (2000), © the American Society of Hematology. Grimwade et al (1998), © the American Society of Hematology. Byrd et al (2002), © the American Society of Hematology.

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Figure 2. Detailed karyotype analysis in AML. De-tailed cytogenetic aberrations among young adults with AML, reported in the MRC 10, 12 and 15 trials. MRC, Medical Research Council; NCRI, National Cancer Research Institute. This research was originally published in Blood. Grimwade et al (2010a), © the American Society of Hematology.

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Cytogenetics predict for success of intensive induction, relapse rate and overall survival (Table 1) and therefore, play a pivotal role in clinical decisions. However existing clinical data regarding cytogenetics are mainly observational and their clinical utilization is mostly confined to the assignment of post-remission therapy. Cytogenetics have no direct impact on the initial induction regimen chosen, except perhaps in older adults with very unfavourable cytogenetics where the dismal outlook could influence a decision to elect for alternative therapies (Estey, 2011). Decisions regarding post-remission therapy may be made following completion of induction or, as in the UK, after the first cycle of induction, especially in those patients who have an incomplete response. In addition, the cytogenetic intermediate risk group, which includes up to 70% of AML patients, is very heterogeneous and therefore hardly predictive of specific outcome. Long-term survival of intermediate-risk cytogenetics in young adults is about 35–40%. Considering the high morbidity and mortality associated with allogeneic stem cell transplantation (allo-SCT), intermediate-risk AML patients in first remission require a better predictive tool to guide the best post-remission regimen. Currently, only the very best or the poorer cytogenetic markers can reasonably guide clinical decisions as a single genetic parameter. For most AML patients, the intermediate-risk group is far too heterogeneous; a more refined genetic or immunological profile is required.

Table 1. Complete remission (CR), relapse and overall survival at 5 years by cytogenetic risk group in three large cooperative groups trials
 Complete remissionRelapseOverall survival
MRC 10CALGBUS intergroupMRC 10CALGBUS intergroupMRC 10CALGBUS intergroup
  1. Data based on published UK Medical Research Council (MRC) (Grimwade et al, 1998), Cancer and Leukemia Group B (CALGB) (Byrd et al, 2002) and US Intergroup (Slovak et al, 2000) studies.

Patient age, years>5615–8616–55>5615–8616–55>5615–8616–55
Favourable91%88%84%35%51%NR65%55%55%
Intermediate86%67%76%51%67%NR41%24%33%
Adverse73%32%55%76%92%NR14%5%11%

Somatic mutations

The technology of conventional cytogenetics has not been modified in several decades. In contrast, the area of genomic sequencing is undergoing a complete revolution. Four years ago, Ley et al (2008) were first to sequence a complete AML genome, comparing it to patient's germline sequence recognized from their own skin. A year later, the same group published a second whole AML genome (Mardis et al, 2009). On this occasion, the quality of the sequence improved and the cost was reduced. Those studies allow the estimation that around 750 point mutations are present in a typical AML genome. The human genome contains 3·2 × 109 nucleotides; therefore, if randomly generated, the likelihood that identical point mutations will be repeated in even a small proportion of AML patients is very low. As a result, recurrent mutations draw attention and are being explored intensively. Indeed, multiple recurrent mutations have been reported and most of them are associated with specific outcome (Table 2). Most AML patients present with multiple mutations concurrently. Prognostication requires understanding of the interactions between traditional clinical parameters, karyotype and mutated genes. Integration of prognostic data regarding different genetic aberrations residing in one genome is becoming a major challenge.

Table 2. Recurrent molecular abnormalities in AML
GeneOverall prevalence (%)Common inOverall impact on prognosis
  1. Reproduced with permission from Thiede (2012).

  2. ITD, internal tandem repeat; TKD, tyrosine kinase domain; PTD, partial tandem repeat; CN-AML, cytogenetically normal acute myeloid leukaemia, sAML, secondary acute myeloid leukaemia.

NPM1 30–35CN-AML (50%)[UPWARDS ARROW]
FLT3-ITD;TKD25; 7CN-AML (40%), t(15;17) (40%, t(6;9) (80%)[DOWNWARDS ARROW] (ITD)[RIGHTWARDS ARROW] (TKD)
CEBPA 6CN-AML (10–15%)[UPWARDS ARROW]
WT1 10–15CN-AML[DOWNWARDS ARROW][RIGHTWARDS ARROW]
RUNX1 10–15M0, sAML[DOWNWARDS ARROW]
MLL-PTD5–10CN-AML (10–15%)[DOWNWARDS ARROW]
RAS (NRAS/KRAS) 15–20−7, NPM1. inv16[RIGHTWARDS ARROW]
PTPN11 3−7, NPM1, inv16?
KIT 2–3CBF-leukaemias (10–10%)[DOWNWARDS ARROW]
JAK2 1CBF-leukaemias (5%)[DOWNWARDS ARROW]
CBL 1–3CBF-leukaemias?
TET2 8–12sAML[DOWNWARDS ARROW]
IDH1 (R132)7–16CN-AML, NPM1[DOWNWARDS ARROW][UPWARDS ARROW][RIGHTWARDS ARROW]
IDH2 (R140;R172)8–15CN-AML, NPM1[DOWNWARDS ARROW][UPWARDS ARROW][RIGHTWARDS ARROW]
PHF6 2–4Males[DOWNWARDS ARROW]
ASXL1 3–19sAML[DOWNWARDS ARROW]
DNMT3A 15–25CN-AML (25–35%)[DOWNWARDS ARROW]
EZH2 1–3sAML?
TP53 2–5Complex karyotype; −17[DOWNWARDS ARROW]

NPM1 mutation and FLT3 internal tandem duplication

Of all mutations identified in AML, the most robust prognostic value has been reported for the fms-like tyrosine kinase receptor-3 internal tandem duplications (FLT3-ITD) and for insertion mutations in exon 12 of nucleophosmin member 1 (NPM1). Identified in 1996 (Nakao et al, 1996), FLT3-ITD was retrospectively studied in large cohorts (Kottaridis et al, 2001; Thiede et al, 2002) and found to be associated with a significantly higher rate of relapse. Its effect correlates with the mutant allele level (Gale et al, 2008) and is useful in subclassifying the cytogenetic intermediate risk group.

In contrast, mutant NPM1 (NPM1mut) correlates with a better response to intensive induction and with long-term survival (Falini et al, 2005). However, when analysed as a sole parameter in a large study of 1485 patients, NPM1mut was found to prolong the median overall survival by only 4·7 months (Thiede et al, 2006). Moreover, in 709 patients with normal karyotype (NK), this effect failed to reach statistical significance. A noteworthy difference was only observed when cytogenetics and both NPM1 and FLT3-ITD mutations were analysed together (Fig 3). The deleterious effect of adverse cytogenetics or FLT3-ITD overrides the benefit from NPM1mut. However, patients with NK NPM1mut and FLT3-wt experience a low relapse rate of 25% following standard chemotherapy. This observation was confirmed in multiple studies (Dohner et al, 2005; Schnittger et al, 2005); hence, a clinically relevant complex genetic profile was the first to be established. It is now well accepted that due to low relapse risk, allogeneic transplantation, although conferring the best anti-leukaemic effect, should be avoided in those patients, as the benefit is abrogated by the increased non-relapse mortality (Davies et al, 2008; Schlenk et al, 2008).

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Figure 3. NPM1mut and FLT3-ITD interaction. The favourable prognostic effect of NPM1mut is not significant when analysed in all patients with NK (left panel) but is restricted only to those patients with FLT-wt (right panel). P-values in the right panel are for the comparison to group A. This research was originally published in Blood. Thiede et al (2006), © the American Society of Hematology.

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Integration of additional mutations into AML genetic profile

The list of mutations identified as prognostic markers in AML, has grown rapidly in recent years. Incorporating specific mutational datum in clinical decision-making requires understanding the specific gene or mutation interactions with other co-existing genetic aberrations. The opening attempt at a new era of comprehensive integrated genetic profiling in AML was a recent effort to include cytogenetics and mutations within 18 different genes, leading to a single algorithm for prognostication (Patel et al, 2012) (Fig 4). An integrated model using mutations alone as the prognosticator was very recently reported (Grossmann et al, 2012). No longer is a single mutation or cytogenetic result sufficient for clinical decisions. Herein, the current evidence regarding the role of mutations known to be associated with prognosis, and their integration into patient management, will be discussed.

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Figure 4. Mutational complexity in AML. A Circos diagram depicts the relative frequency and pairwise co-occurrence of mutations in AML patients. The length of the arc corresponds to the frequency of mutations in the first gene, and the width of the ribbon corresponds to the percentage of patients who also had a mutation in the second gene. Patients who carry more than two mutations in their leukaemic cells are not represented. ITD, internal tandem repeat; TKD, tyrosine kinase domain; PTD, partial tandem repeat. From New England Journal of Medicine, Patel et al (2012), Copyright © (2012) Massachusetts Medical Society. Reprinted with permission.

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CEBPA

CCAAT/enhancer binding protein α (CEBPA) has a role in myelopoiesis (Chen et al, 2009). Mutations in this gene are of much lower frequency than FLT3-ITD and NPM1; therefore, determination of its effect requires screening large number of patients. In addition, it has been suggested that the better prognostic effect of this mutation is only observed when both CEBPA alleles are mutated (Wouters et al, 2009a). However, this is still an open issue, as those studies had no power to discriminate the influence of specific CEBPA mutation (single or double) from the effect of concurrent mutations in other genes. Gene expression studies suggest that CEBPA double mutant patients have a unique biological characteristics. Yet, for clinical implications, it should be noted that in those studies, FLT3-ITD or tyrosine kinase domain (TKD) mutations were less frequent among double or loss-of-function CEBPA mutants, compared with single mutant patients (Wouters et al, 2009a). Indeed, the presence or absence of CEBPA mutations (single or double) has only been convincingly demonstrated to affect the relapse risk in the presence of NK and FLT3-wt (Marcucci et al, 2008; Schlenk et al, 2008; Renneville et al, 2009a), although an effect cannot be ruled out in other intermediate risk cytogenetics.

IDH1&2

Two isocitrate dehydrogenase genes (IDH1 and IDH2) are recognized as mutated oncogenes. IDH1 mutation is a gain-of-function mutation that allows the conversion of α-ketoglutarate to 2-hydroxy-glutarate. It was first described in glioma and glioblastoma (Yan et al, 2009), is rare in many other tumours and therefore was initially considered to be specific to brain tumours. Accumulation of 2-hydroxy-glutarate was suggested to be a key factor in the development of brain tumours (Dang et al, 2009). Surprisingly, a whole-genome sequencing of 188 AML samples identified recurring IDH1 mutations in 16 (8·5%) patients (Mardis et al, 2009). This observation was confirmed and mutations in IDH1 were reported to be present in up to 14% of AML patients. At the same time, IDH2 mutations were also observed among AML patients (Marcucci et al, 2010; Paschka et al, 2010). Most IDH1 mutations lead to substitution of arginine, at position 132, to cysteine or histidine. IDH2 mutations were reported to occur at two sites, a substitution of arginine to lysine at position 172 and of arginine to glutamine at position 140. The exact mechanism and how IDH mutations contribute to the development and progression of leukaemia is being studied extensively. High levels of 2-hydroxy-glutarate were measured in AML cells harbouring these commonly recurring mutations, in both IDH1 and 2 (Gross et al, 2010). IDH1 and IDH2 mutations were shown to alter epigenetic and haematopoietic differentiation (Figueroa et al, 2010a). It was suggested that IDH mutations impair histone demethylation and lead to differentiation arrest (Lu et al, 2012).

Clinical interpretation of IDH1/2 mutations is challenging. There are conflicting reports regarding the prognostic value of IDH1 and IDH2 mutations. In 1333 young adult patients included in the MRC 10 and 12 studies, common IDH1 mutations (R132) were associated with high relapse rates. Mutational analyses for IDH2 were also available in 1473 young adult patients included in the same cohort. R172 IDH2 mutation was associated with significantly worse outcome than R140. Relapse risk in patients who present with NK, FLT3-wt and R172 IDH mutation concurrently was as high as 76%, resembling relapse risk in patients with adverse-risk cytogenetics. In contrast, the R140 mutation was an independently favourable prognostic factor and relapse rate in patients with FLT3-wt, NPM1mut, IDH2 (R140) was lower than in favourable-risk cytogenetic patients in the same cohort (20% vs. 38% at 5 years respectively) (Green et al, 2010, 2011). Therefore, integrating IDH1/2 mutation data into a comprehensive genetic profile requires caution. First, many studies analysed all IDH1/2 mutations as one homogenous group. The overlap between IDH mutations and NPM1mut or FLT3-ITD mutations differs significantly among studies. In addition, a single nucleotide polymorphism in IDH1 that is not being studied in mutation-oriented studies was suggested to be of prognostic importance, regardless of mutation status (Wagner et al, 2010). In the landmark ECOG study (Patel et al, 2012) the most favourable outcome within NK patients with FLT3wt was observed in NPM1mut patients who, in addition, had IDH1/2 mutation (Fig 5). Of note, most of patients within this group (13 out of 17, 76%) had the IDH2 (R140) mutation. Of particular interest is that, in the same cohort, when analysis was restricted to patients with NK, FLT3-wt and NPM1mut, those who have the wild-type IDH1/2 do not have a favourable outcome as was expected, based on previously established data (Schlenk et al, 2008; Dohner et al, 2010). This may impact on what has become standard of care.

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Figure 5. Interactions between INH1/2 and NPM1 mutations in AML patients with NK and FLT3-wt. The complexity of interoperating IDH1/2 mutation data can be demonstrated by different analysis from the same cohort. Panel A demonstrates that the most favourable outcome within NK patients with FLT3-wt was observed in NPM1mut patients who in addition have IDH1/2 mutation. However, within this subgroup those who have the wild-type IDH1/2 do not have a favourable outcome (Panel B). PTD, partial tandem repeat. From New England Journal of Medicine, Patel et al (2012), Copyright © (2012) Massachusetts Medical Society. Reprinted with permission.

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TET2

Mutations in the TET oncogene family member 2 (TET2) have been reported in multiple myeloid malignancies. In AML, conflicting results were first reported regarding the prognostic effect of TET2 mutations (Nibourel et al, 2010; Metzeler et al, 2011). Some studies suggested that the TET2 mutation is an unfavourable prognostic factor in AML patients with intermediate-risk cytogenetics but not among patients with favourable molecular markers (NPM1mut/FLT3wt or CEBPA double mutant) (Chou et al, 2011). Assessment of the biological effects of mutations in TET2 gene need to consider the large number of TET2 mutations identified so far (Fig 6), as well as the fact that a huge number of germline variations exist in the population. Therefore, it is difficult to discriminate somatic aberrations from genetic polymorphisms and, in most of the above-mentioned studies, many aberrations thought not to be somatic were censored and excluded from analysis (Chou et al, 2011; Metzeler et al, 2011).

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Figure 6. Somatic mutations in AML involving the TET2 gene. This research was originally published in Blood. Chou et al (2011), © the American Society of Hematology Blood.

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TET2 mutations compromise its catalytic activity, reduce levels of 5-hydroxymethylcytosine in genomic DNA and impair the cell's epigenetic profile (Ko et al, 2010). Biologically, TET2 and IDH1/2 are functionally associated. IDH mutants have been demonstrated to impair the TET2 catalytic function in AML cells (Figueroa et al, 2010a) and the underlying correlations were described (Prensner & Chinnaiyan, 2011). In AML, IDH and TET2 mutations are mutually exclusive (Chou et al, 2011; Metzeler et al, 2011; Patel et al, 2012), suggesting that functionally and possibly clinically there is a lack of interaction among these mutations. The heterogeneity in the clinical effect of different IDH mutations, the high repertoire of TET2 mutations, the unknown effect of genetic polymorphisms in these genes and the debate whether mutations in those genes should be evaluated separately or collectively, are all obstacles to integrating these genes into a clinical decision algorithm.

DNMT3A

The DNA methyltransferase 3A (DNMT3A) gene was recently recognized to play an important role in haematopoietic stem cell self-renewal and differentiation (Challen et al, 2012; Trowbridge & Orkin, 2012). Mutations in DNMT3A are associated with an adverse outcome. About 30 different DNMT3A mutations were reported, most of them clustered in the same domain (Ley et al, 2010). DNMT3A is mutated in 17·8–23% of AML patients (Thol et al, 2011; Patel et al, 2012). When all mutations identified in DNMT3A were grouped and analysed together it was associated with a poor prognosis (Thol et al, 2011; Ostronoff et al, 2012; Renneville et al, 2012; Ribeiro et al, 2012). DNMT3A mutations are mutually exclusive from favourable cytogenetics; hence, incorporating them into clinical decision algorithm should have been simple. However, statistically significant differences in overall survival (OS) between mutated and non-mutated DNMT3A AML patients do not always have a clinical impact. For example, a statistically significant difference in event-free survival (EFS) between mutated and wild DNMT3A patients was confirmed in NK participants in recent French studies (Renneville et al, 2012). Nevertheless, for patients classified as high-risk genotype, based on mutation data of NPM1/FLT3-ITD/CEBPA genes, the 1-year EFS changed, from 30% for un-mutated to 20% for mutated patients. In both cases, allogeneic transplantation is indicated for patients at remission and therefore for such patients DNMT3A mutation data do not help in decision making. For low risk genotype patients, DNMT3A mutation reduced the 1-year EFS from 80% to 40% and should be taken into account when choosing post-remission strategy (Fig 7).

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Figure 7. Interaction of DNMT3A mutations in low and high risk genotypes. DNMT3A mutations significantly worsens event-free survival in all patients. The effect is particularly prominent in those with a low risk genotype (Panel A) compared with the high-risk patients (Panel B). The low risk genotype is defined as NPM1mut/FlT3wt or CEBPA double mutant. The high risk genotype is defined as FLT3-ITD/no CEBPA double mutant. ITD, internal tandem repeat. Reproduced with permission from Renneville et al (2012).

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As was mentioned earlier, clinical decisions in AML occur at two main points of care, induction and post-remission therapies. The E1900 protocol was an ECOG-led phase III clinical trial that compared induction with high versus low dose (90 vs. 45 mg/m2) of daunorubicin. Retrospectively, 398 participants in this study were genetically analysed (Patel et al, 2012), enabling the assessment of OS in each induction group as a function of genetic profile. Mutant DNMT3A along with NPM1mut and MLL translocation were found to be associated with an improved 3-year OS (44% vs. 25%). However, in contrast to mutant DNMT3, among patients with wild-type DNMT3, a clear benefit for high-dose daunorubicin could not be demonstrated in this retrospective analysis, which, however, needs to be validated (Fig 8). Integrative genetic profile can therefore impact post-remission as well as decisions of dosing during induction.

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Figure 8. DNMT3A mutations and impact on anthracycline dose in induction. Intensifying anthracyclines during induction may be of benefit for mutated (A), but not to un-mutated DNMT3A patients (B). From New England Journal of Medicine, Patel et al (2012), Copyright © (2012) Massachusetts Medical Society. Reprinted with permission.

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Additional recurrent mutations in AML

Mutations in epigenetic modifiers

IDH and TET2 genes are involved in epigenetic profile creation and maintenance. The underlying epigenome-related leukaemogenic mechanisms and potential directions for future therapies have been described in detail elsewhere (Fathi & Abdel-Wahab, 2012). Additional genes that play a role in DNA methylation and histone acetylation were also found to be commonly mutated in myeloid malignancies. Among those, the most clinically interesting in AML are the additional sex comb-like 1 (ASXL1), the polycomb group methyltransferase EZH2 and the mixed lineage leukaemia (MLL) gene.

ASXL1 was found to be associated with a poor prognosis (Boultwood et al, 2010; Chou et al, 2010; Pratcorona et al, 2012). EZH2 is involved in many other myeloid malignancies and may act as a tumour suppressor gene (Ernst et al, 2010; Nikoloski et al, 2010). EZH2 draws special attention since it is located on the long arm of chromosome 7 (7q) where deletion of this chromosome is recognized as an adverse cytogenetic marker in AML (Dohner et al, 1998).

To better understand how to utilize genetic data of mutations and epigenetics into clinical practice, future studies incorporating sequencing and functional activity of multiple epigenetic modifiers are required. The relationship between different proteins involved in the same pathway should be integrated with other genetic abnormalities. An additional complexity, at least in EZH2 aberrations, is the loss of heterozygosity, or uniparental disomy (UPD), which is common in myeloid malignancies and is associated with a poor prognosis (O'Keefe et al, 2010). Although scant clinical data regarding EZH2 UPD are available, it is anticipated to increase with progression of new generation sequencing techniques. UPD was recently reported to commonly affect chromosome 7q (Jerez et al, 2012), the locus that contains the EZH2 gene.

The mixed lineage leukaemia gene-partial tandem duplication (MLL-PTD) is frequent in AML with NK and is associated with shortened OS and EFS and worse prognosis (Basecke et al, 2006). However, its effect on leukaemogenesis needs to be clarified, because it can also be identified among healthy individuals (Schnittger et al, 1998). The MLL gene is known also to have a complicated network of partnering genes with which recombination can occur (Meyer et al, 2009).

Currently, the main implication of mutations in epigenetic modifiers is that the presence of TET2, ASXL1 mutations or MLL-PTD in patients with NK and FLT3-wt should be considered as an adverse prognostic marker and classifies the patient in the unfavourable risk group (Patel et al, 2012) (Fig 5A).

KIT mutations in core binding leukaemia

The core binding factor (CBF) transcription complex is a heterodimeric protein consisting of two interacting proteins, RUNX1 and CBFB. The genes of these proteins are located at chromosomes 21 and 16, respectively. AML with recurrent cytogenetic aberrations that involve these loci [t(8:21), inv16, and t(16:16)], are known to have a better prognosis and are called CBF-leukaemia (Grimwade et al, 1998; Slovak et al, 2000; Prebet et al, 2009). KIT is a cytokine receptor with tyrosine kinase activity and is involved in cell proliferation signalling. Mutations in KIT were reported to be prevalent among CBF-leukaemia cases and associated with increased relapse risk (Care et al, 2003; Paschka et al, 2006). In some studies the deleterious effect of KIT mutations was restricted to patients with t(8:21), not seen in patients with inv16 (Boissel et al, 2006; Park et al, 2011; Patel et al, 2012). Of note, although reported in several trials, the high relapse rate of patients with KIT mutations was based on a small number of patients; thus, it should not be surprising that conflicting results are reported (Fig 9). In contrast to adults, in paediatric CBF-AML patients, relapse risk and OS are not affected by KIT mutations (Pollard et al, 2010). At diagnosis, KIT mutations may present exclusively in a minor leukaemic sub-clone that may be missed by regular direct sequencing methods. It was suggested that, for clinical use and relapse prediction, a sensitive KIT mutation detection method should be used (Wakita et al, 2011). Interestingly, KIT mutation is also present in non-CBF leukaemia, but, its prognostic effect is restricted only to patients with t(8:21) (Schnittger et al, 2006). This highlights the importance of having clinical decisions based on integrated analysis of cytogenetics and multiple mutations rather than on the existence of a single mutation.

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Figure 9. KIT mutations in Inv(16) AML. Conflicting published results regarding the prognostic value of KIT mutation in AML patients with inv(16). Reprinted with permission from Patel et al (2012) (right panel), Copyright © (2012) Massachusetts Medical Society, Reprinted with permission from Paschka et al (2006) (left panel). Copyright (2006) American Society of Clinical Oncology.

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Additional potential prognostic genes in AML

WT1, RUNX1, RAS genes, TP53 and SRSF2 have been reported to be associated with poor prognosis in AML. Mutation in WT1 was associated with poor prognosis in some studies (Virappane et al, 2008; Renneville et al, 2009b; Becker et al, 2010) but not in others (Gaidzik et al, 2009). A common single nucleotide polymorphism (SNP) located in WT1 mutational hotspot predicts for a favourable outcome and may therefore be also considered during WT1 mutation analysis (Damm et al, 2010). Mutation in RUNX1 has also an adverse prognostic impact that is most significant in patients with NK (Tang et al, 2009; Gaidzik et al, 2011; Mendler et al, 2012). It had been suggested that activation of the RAS pathway is predictive for cytarabine sensitivity (Illmer et al, 2005). Retrospective analyses suggest that activation mutation in RAS genes may predict for a good response to cytarabine therapy (Neubauer et al, 2008; Ahmad et al, 2011). However, all the above-mentioned mutations, except for the SRSF2 mutation, were included in the ECOG study (Patel et al, 2012) and had no significant impact when assessed in the integrated model. SRSF2 mutation was recently reported to predict a poor prognosis in AML patients transforming from myeloproliferative disease (Zhang et al, 2012). Yet, it has very limited clinical implications because the OS of both SRSF2 mutated and un-mutated patients in this study was dismal.

Gene expression profiles

Gene expression techniques provide a functional view into leukaemic cells. Gene expression profiling was suggested to be associated with prognosis, yet its clinical utilization in AML is still uncertain (Wouters et al, 2009b). Up to 18 different gene expression profiles (GEPs) were described in the large international microarray Innovations in leukaemia (MILE) study, some of which corresponded with known AML subtypes (Haferlach et al, 2010). In other cohorts six different GEPs were identified that were also associated with prognosis (Wilson et al, 2006); however, patients in both studies received various therapies. In general, gene expression profiling is highly sensitive and multiple background parameters can alter it for reasons not necessarily of clinical importance. To justify incorporating GEPs into clinical practice it should add specific value to the previously recognized ability to predict AML prognosis by recurrent cytogenetic aberrations or genetic mutations. For example, it had been suggested that a specific GEP is characteristic of AML with FLT3-ITD mutation (Bullinger et al, 2008). Remarkably, although in this study the specifically reported GEP only modestly predicted the existence of FLT3-ITD mutation, it predicted the clinical outcome better than FLT3-ITD (Bullinger et al, 2008). In contrast, DNMT3A mutations that have prognostic value, are involved in epigenetics, and therefore would be expected to influence expression pattern, are not associated with specific GEP (Marcucci et al, 2012; Ribeiro et al, 2012). To incorporate gene expression profiling into clinical practice, comprehensive studies integrating cytogenetics, mutations, gene expression and micro RNA data are required.

Clinical applications of gene expression profiling are also limited by the following considerations. Usually, GEP studies are being conducted on pre-treatment samples. Thus, inducible drug-resistant mechanisms are inactive and under-represented prior to chemotherapy exposure. In addition, RNA used for GEP analysis is a sum of RNA from all leukaemic cells. However, prognosis may be influenced by characterization and the associated expression profile of minor resistant sub-clones or leukaemic stem cells (Gentles et al, 2010). RNA from those minor cell groups is obscured as the majority of RNA arises from rapidly proliferating clones. Moreover, genes with significant quantitative differences in expression between patients are more likely to affect GEP analysis. Yet, a small modification in expression level in some genes, that is statistically undetectable, may be functionally more important.

Gene expression profiling may highlight some genes as potentially important in AML. For example, BAALC, ERG, CDKN1B and MN1 are genes that attracted attention as potential risk factors (Haferlach et al, 2012b). However, it may well be that some are only surrogates and their prognostic impact is due to different associated genes, as was shown for BAALC (Heesch et al, 2010).

Micro RNA

Micro RNAs (miRNA), are small non-coding RNAs that have been studied extensively in recent years as important players in epigenetic and gene expression profile. miRNA are cleaved from larger RNA hairpin precursors by a complex protein system that includes the RNase III, Drosha and Dicer (Bartel, 2009). A comprehensive review of the prognostic and functional role of miRNAs in AML has been recently published elsewhere (Marcucci et al, 2011). miRNA expression profiling is closely interactive with GEP (Havelange et al, 2011) and is regulated by similar genetic mechanisms as those which modulate protein coding genes (Agirre et al, 2012). Discussing the role of specific miRNA levels in clinical practice is beyond the scope of this review. In general, clinical data regarding few specific miRNA expression levels are accumulating but its integration into comprehensive genetic profiling of AML is still pending.

A new layer of complexity in genetic profiling of leukaemia is suggested by recent work in mice. Myelodysplasia and AML were induced in mice by deletion of DICER1 specifically in osteoprogenitors, keeping DICER1 in haematopoietic cells intact (Raaijmakers et al, 2010). DICER1 is fundamental for miRNA production, suggesting that miRNA expression profile within micro-environment cells may also contribute to leukaemogenesis.

Epigenetic profiling in AML

Numerous mutations in a number of epigenetic modifiers/genes were identified in AML. As discussed earlier in this review, different mutations and SNPs that may affect DNA methylation may co-exist. In a large cohort of 344 newly diagnosed AML patients, with analysis of a genome-wide promoter, DNA methylation profiling revealed 16 distinct methylation patterns, some correlating with specific genetic aberrations (Figueroa et al, 2010b). A distinctive epigenetic modifications pattern may characterize specific cytogenetic subgroups (Wilop et al, 2011). It was demonstrated that the pattern of DNA methylation of candidate genes might predict outcome (Bullinger et al, 2010). However, the clinical application of methylation profiles into daily practice is still far away (McDevitt, 2012).

Immune system polymorphism

The paradigm of leukaemia stem cell suggests that a limited number of malignant cells may survive many cycles of aggressive therapy. The risk of relapse is related to the number and characterization of residual malignant cells, but also to the effectiveness of patient's immune surveillance. Until recently, the patient's own immune system was considered failing because it did not prevent the development of leukaemia. Nevertheless, both functional and genetic alterations were found in genes involved in immune response in AML patients (Le Dieu et al, 2009). Specifically, polymorphisms in the cytotoxic T-lymphocyte antigen 4 (CTLA4) gene, which involve an innate immune response, may affect relapse risk among patients who are in remission following chemotherapy or autologous stem cell transplantation (Perez-Garcia et al, 2009) (Fig 10). Polymorphisms in few other immune-related genes were found to be associated with relapse risk following allo-SCT. It may be interesting to evaluate its impact in the non-allo-SCT setting.

image

Figure 10. Relapse incidence following first complete remission according to inherited CTLA4 polymorphism. Reproduced with permission from Perez-Garcia et al (2009).

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Integrating mutational data with clinical and laboratory parameters

There are many well-established risk factors in AML other than genetic. In clinical practice, parameters such as age, secondary leukaemia, high counts at presentation and performance status, are being considered. A large follow-up study demonstrated the benefit of the new genetic risk classification of the European LeukaemiaNet for young, but not older patients (Rollig et al, 2011). To simplify clinical decisions, different scoring systems were suggested for elderly AML patients (Rollig et al, 2010) or secondary AML (Chevallier et al, 2011; Stolzel et al, 2011). However, this requires an arbitrary definition for age, which is definitely a continuum and a biological more than chronological parameter. In addition, leukaemia secondary to radiation or chemotherapy should be regarded differentially (Nardi et al, 2012) and not all AML developed in patients previously exposed to cytotoxic agents are indeed secondary.

Integrated analysis of genetic and non-genetic laboratory parameters was recently demonstrated to further improve risk stratification. CD25 (IL2RA) expression on leukaemic blast surface predicts for a poor prognosis. Incorporating CD25 expression into the previously reported integrated mutational analysis within the same ECOG1900 cohort, improved risk stratification even further. With the addition of CD25 as a parameter, 11% of intermediate-risk patients were re-allocated and classified as poor prognosis (Gonen et al, 2012) (Fig 11). It is anticipated that as more parameters are included in AML classification, prognosis will be more accurately predicted.

image

Figure 11. Prognostication in adult AML Based on CD25 Expression and Genetics. The poor prognostic effect of CD25 expression is demonstrated in integrated analysis of cytogenetics and 18 different gene mutations. All LR patients but one were negative for CD25. LR – low risk, IR, intermediate risk; HR, high risk. This research was originally published in Blood. Gonen et al (2012), © the American Society of Hematology.

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Genetic profiling and points of AML care

The specific composition of genetic aberrations identified in a patient with AML, affects the biology of the disease and should impact clinical decisions. Genetic profiling is imperative at three main points of care, selecting the best induction and post-remission strategies and incorporating genetic testing into minimal residual disease (MRD). The most robust genetic data are available for assignment of post-remission therapy. Fewer data exist regarding the selection of induction regimens and MRD monitoring (Table 3).

Table 3. Select recent innovations and future directions in genetic profiling of AML
 ModalityComments
InductionIntensifying anthracycline dose

Best data for favourable + intermediate cytogenetics

Possible for normal genetics FLT3wt, MLLwt, DNMT3Amut

Hypomethylation agentPossible effect for TET2mut or if BCL2L10 is highly expressed
Post-remissionRepeated consolidations

Best data for favourable cytogenetics excluding t(8;21) in the presence of KIT mutation

Probable for intermediate cytogenetics + NPM1mut + FLT3wt + IDH2 (R140) mutation

Possible for CEBPA double mutant

Allogeneic stem cell transplantationAll other patients treated with curative intents
Induction

Intensive induction with anthracyclines and cytarabine is the standard of care in AML. While daunorubicin 45 mg/m2 is no longer considered appropriate, even in elderly patients (Fernandez et al, 2009; Lowenberg et al, 2009), doses of 60 and 90 mg/m2 were never prospectively compared. This is currently being studied in the UK's AML17 trial. High anthracycline doses are particularly beneficial in patients with good prognostic genetic markers, such as favourable or intermediate cytogenetics, FLT3-wt and MLL-wt (Fernandez et al, 2009) but also in DNMT3A mutated patients (Patel et al, 2012). In addition, some preliminary data identify mutations in TET2 and status of BCL2L10 methylation as predictors for response to hypomethylating agents (Itzykson et al, 2011). It is reasonable to anticipate that in the future, genetic aberrations will guide the selection of induction regimen; however, data are not mature enough to currently form clinical recommendations.

Post-remission

Current indications for allo-SCT are firm in the minority of AML patients with adverse genetic profiles (Davies et al, 2008). The majority of patients lie within the intermediate risk group, which is too heterogeneous for a uniform treatment protocol. Integrating multiple genetic aberrations in large cohorts enables the identification of specific genetic profiles within the intermediate risk group and thus, electing for allo-SCT only those who are predicted to have a high risk for relapse. Conflicting results arise from small studies that limit the interpretation of genetic data. Large scale screening for multiple genetic aberrations can clarify existing debates.

MRD

Despite few prospective studies, immunophenotyping for AML has been traditionally accepted as the backbone of MRD measurement and its utility may be improved with standardized techniques (van Dongen & Orfao, 2012). However, the high sensitivity of genetic testing makes genetic MRD monitoring attractive. The high sensitivity and the well documented success of genetic MRD monitoring in paediatric acute lymphoblastic leukaemia, suggest it may be efficient in AML as well. However, the nature of clonal evolution of AML limits genetic MRD monitoring. Some genetic aberrations are late events in leukaemogenesis and thus, don't exist in the primary leukaemic stem cells. Single cell analysis demonstrated that relapse may also develop from early progenitors and by various mechanisms (Shlush et al, 2012). Therefore, identifying a mutation that will ultimately be correlated with all residual leukaemic clones is challenging. Several genetic aberrations were suggested as potential markers for MRD monitoring. Among these are WT1, NPM1, MLL and cytogenetic translocations (Grimwade et al, 2010b). In contrast, FLT3-ITD may be unstable during relapse (Kottaridis et al, 2002). Routine monitoring for an MRD marker is clinically justified only if, in response to its reappearance, or to a rise in its detectable level during remission, therapy or allo-SCT will be indicated. Data from CBF leukaemia suggest that both t(8:21) and inv16 aberrations can be detected, especially the former, at some level in patients in remission (Perea et al, 2006). However, most recent prospective data from the MRC AML15 trial indicate that monitoring with quantitative reverse transcription polymerase chain reaction in CBF AML facilitates a further degree of prognostication (Yin et al, 2012). Thus, major efforts should be made to prospectively collect molecular data from patients participating in clinical trials and assign an appropriate perspective for clinical utility, similar to the national biomarker roadmap in the UK (Lioumi & Newell, 2010).

The future: from classification to integration and beyond

The heterogeneous nature of AML and the multiple interactions of different genetic aberrations challenge the vision of clear and long lasting classification of AML into clusters with similar clinical outcomes. In reality, leukaemia is a dynamic disease. A detailed integration model of all kinds of genetic aberrations (cytogenetic, mutations, GEP, miRNA, UPD, epigenetic, etc.) with other laboratory and clinical parameters will be very complicated. Mutations may be unstable and often, at relapse, patients present with mutations that are different from presentation. Whether this has a significant impact, will depend, in part, on the proportion of mutations that remain stable. A classic model cannot explain such a shift. In the future, genetic profiling is expected to be more complex; thus, classification may lose its main advantage, namely, its ability to direct clinical decisions. The paradigm of AML therapy basically relies on two main points of care: which induction and which post-remission regimen to choose? Conceptually, genetic risk classification should predict who will fail chemotherapy, and support the selection of patients referred for an allo-SCT.

The case for AML in the elderly is an example for such direction. Older patients with co-morbidities tolerate poorly prolonged neutropenia. In recent years several novel agents have been proposed to replace traditional chemotherapy in such patients. No magic bullet has been identified but some patients do respond to less toxic agents. Genetic data should be helpful for identifying patients who may benefit from less toxic regimens. Theoretically, an agent can be apparently less efficacious than traditional therapy, but particularly effective in patients carrying a specific mutation. It is therefore suggested that, in all future prospective clinical trials, a comprehensive genetic profile of all patients who respond to a studied novel agent be recorded in a general database. Genetic data should be used as a predictive tool for induction success and may warrant usage of differential regimens, dependent on genetic profiling.

Conclusion

  1. Top of page
  2. Summary
  3. Genetic prognostic markers identified in AML
  4. Conclusion
  5. Acknowledgement
  6. References

Genetic profiling in AML is the key to personalizing therapy and improving patient outcome. Classification of AML is becoming progressively more complicated, moving from seven entities in the French-American-British (FAB) classification to 30 different leukaemias in the 2008 World Health Organization classification (Vardiman et al, 2009). Even the current classification cannot guide clinical decisions in a substantial number of intermediate-risk patients. The rapidly accumulating genetic data, as described in this review, are setting the stage for a better clinical practice. Integrating data from multiple sources, such as clinical data, cytogenetics, mutations, expression pattern and immunophenotyping, has a tremendous advantage, allowing for minimizing the number of patients in whom we have difficulty predicting outcome with traditional therapy and who may be over- or under-treated. This should be recognized as a new era in clinical leukaemia research. In this regard, comprehensive next generation sequencing using highly sensitive technologies (Margulies et al, 2005) should emerge as a practical modality to further discriminate prognostic groups and allow new insights into the allelic forms of mutations and, ultimately, more precise molecular diagnoses. Clinical genetic trials should no longer measure single molecular parameters; rather, multiple mutations are essential for interpretation of genetic-related outcome data and the development of more specific therapies. The new era of integrative mutational analysis should not be limited to improving classification. The greater the number of patients with detailed genetic profile and known outcome, the closer will we get to the as-yet-elusive personalized therapy.

Acknowledgement

  1. Top of page
  2. Summary
  3. Genetic prognostic markers identified in AML
  4. Conclusion
  5. Acknowledgement
  6. References

We would like to gratefully acknowledge the assistance of Sonia Kamenetsky in the preparation of this paper.

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  3. Genetic prognostic markers identified in AML
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