German-Australian AML Study Group Identifies 11 Classes of AML

The German-Australian AML Study Group (AMLSG), one of the largest global groups evaluating treatments for acute myeloid leukemia (AML), has published results in the New England Journal of Medicine that now classifies AML into 11 classes.

AMLSG obtained samples from patients participating in 3 different prospective multicenter trials for AML: AML-HD98A, AML-HD98B, and AMLSG-07-04. The age group of the study cohort was significantly different for AML-HD98B (58 to 84 years) compared with AML-HD98A (18 to 65 years) and AMLSG-07-04 (18 to 61 years). The patients received the following treatments:

• AML-HD98A: induction chemotherapy consisted of idarubicin, cytarabine, and etoposide (ICE). High-risk patients were offered allogeneic stem-cell transplantation, intermediate-risk patients a stem-cell allograft or intensive chemotherapy, and low-risk patients intensive chemotherapy.
• AML-HD98B: ICE plus or minus all-trans retinoic acid (ATRA) as induction therapy.
• AMLSG-07-04: induction therapy with ICE plus or minus ATRA. Further therapy dictated by patient response.

Patient samples were evaluated for somatic driver mutations to generate a new genetic approach to disease classification, one that could have prognostic implications. Cytogenetic analyses of the patient samples involved the sequencing of 111 genes to identify a host of driver mutations:

• Recurrent fusion genes
• Aneuploidies
• Leukemia gene mutations (including base substitutions and small (<200-bp) insertions or deletions)

More than 5000 driver mutations in 76 genes were identified through the study, in 1540 patient samples—a majority (73%) were point mutations. Ninety-six percent of samples had at least 1 driver mutation, and 86% samples had 2 or more. Gene-paired mutations or co-mutations led to the disease being classified into 11 classes, each of which, the authors write, have distinct diagnostic features and clinical outcomes. While 8 classes are already known, 3 heterogeneous genomic categories evolved from this study:

1. AML with mutations in genes encoding chromatin, RNA-splicing regulators, or both (in 18% of patients)
2. AML with TP53 mutations, chromosomal aneuploidies, or both (in 13%)
3. AML with IDH2R172 mutations.

The study also found that mutations in DNMT3A, ASXL1, IDH1/2, and TET2, genes that encode epigenetic modifiers, were acquired the earliest. These mutations were more common in elderly persons and conferred an increased risk of hematologic malignancies. Mutations in the receptor tyrosine kinase—RAS pathway genes usually occurred later and often more than once in the same patient. Mutations in the NPM1 gene often followed DNMT3A, IDH1, or NRAS mutations.

This evolutionary trajectory of genetic mutations that drive AML mirrors the observations in pancreatic cancer.

“The driver landscape in AML reveals distinct molecular subgroups that reflect discrete paths in the evolution of AML, informing disease classification and prognostic stratification,” the authors conclude of their findings.

Reference

Papaemmanuil E, Gerstung M, Bullinger L, et al. Genomic classification and prognosis in acute myeloid leukemia. N Engl J Med. 2016;374:2209-2221. doi:10.1056/NEJMoa1516192.