Genetic Biomarkers in Acute Myeloid Leukemia

Will the Promise of Improving Treatment Outcomes Be Realized?

Jay Yang; Charles A Schiffer

Disclosures

Expert Rev Hematol. 2012;5(4):395-407. 

In This Article

The Fruits of High-throughput Technology

Technologies such as single-nucleotide polymorphism or comparative genomic hybridization array analysis and whole-genome sequencing that allow for the high-throughput analysis of AML genomes have been a boon to the discovery of recurrent genetic events in AML. Comparing an individual's AML genome with that of germline DNA taken from a healthy tissue (e.g., skin) allows for the distinction of somatic mutations.[60] Sophisticated analysis is necessary to determine which of these mutations are biologically relevant genes in leukemia. With the help of these advanced techniques, mutations in TET2, IDH and DNMT3A genes have been implicated in the pathogenesis of AML.

TET2

TET2 mutations have been described in a variety of myeloid neoplasms, including myelodysplastic syndrome, myeloproliferative neoplasms, AML and chronic myelomonocytic leukemia, and are associated with the progression of myelodysplastic syndrome and myeloproliferative neoplasms to AML.[61] Mutations in TET2 are found in approximately 10% of de novo AMLs[62–64] and 23% of CN-AMLs.[65]TET2 mutations are relatively unstable during disease evolution, being frequently lost at relapse.[63] The prognostic effect of TET2 mutations has not been entirely consistent, but some studies have indicated a negative impact[61,62,64,66] including in patients with IR-AML.[63] In one study, TET2 mutations were associated with lower rates of CR, DFS and OS only in the more-favorable-risk CN-AML patients (NPM1+/FLT3 ITD or CEBPA+ ).[65,66]

DNMT3A

DNMT3A encodes for a DNA methyltransferase gene that is mutated in 14–22% of patients with de novo AML[67,68] and is concentrated in patients with IR- and CN-AML, thus accounting for 20–33% of these patients. DNMT3A mutations are rarely, if ever, found in patients with CBF leukemias or APL but are associated with FLT3, NPM1 and IDH mutations. Multiple mutations in the DNMT3A gene have been discovered, but the R882 mutation is the most common. Although limited data exist in this regard, DNMT3A mutations have been found to be associated with a poorer prognosis due to a lower CR rate and DFS in younger patients with a normal karyotype.[69]

IDH

IDH mutations are seen in both de novo and therapy-related AML, at a rate of approximately 8–16%, and were discovered using massively parallel DNA sequencing.[70]IDH1 mutations are present in 10–16% of CN-AML, predominantly at residue R132, and are also seen in NPM1+ AML. IDH2 mutations are present in approximately 19% of CN-AML patients,[70–74] either at residues R172 or R140, and are usually private mutations in an AML clone. The prognostic impact of IDH mutations is still under investigation and may depend on several factors, including coexisting mutations, whether IDH1 or IDH2 is mutated and the particular location of the IDH mutation. IDH mutations have been associated with both an improved[75] and worse prognosis[71,73,74] in separate studies. In another analysis no difference in outcome was seen between IDH-mutated or wild-type patients overall, although IDH1 mutations were associated with a higher risk of relapse in FLT3-negative patients and a lower risk of relapse in FLT3-positive patients.[72] This suggests that the prognostic significance of IDH1 mutations may be context dependent.

Other Molecular Techniques

The expression of multiple genes and their products have been studied in a more global manner using techniques such as gene-expression profiling,[76–78] proteomic profiling,[79] single-nucleotide polymorphism arrays[80] and microRNA arrays.[81,82] Cytogenetic subgroups have been found to have distinct corresponding gene-expression profiles. There are also other molecular subgroups with unique signatures that have not been previously described. This type of analysis can serve as a platform for further gene discovery and may also have prognostic applications, particularly in IR-AML. Although not directly measuring the expression of genes or its products, patterns in DNA methylation can also be used to segregate AML populations with distinct profiles.[83]

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