Leveraging cancer genome information in hematologic malignancies

Abstract

The use of candidate gene and genome-wide discovery studies in the last several years has led to an expansion of our knowledge of the spectrum of recurrent, somatic disease alleles, which contribute to the pathogenesis of hematologic malignancies. Notably, these studies have also begun to fundamentally change our ability to develop informative prognostic schema that inform outcome and therapeutic response, yielding substantive insights into mechanisms of hematopoietic transformation in different tissue compartments. Although these studies have already had important biologic and translational impact, significant challenges remain in systematically applying these findings to clinical decision making and in implementing new technologies for genetic analysis into clinical practice to inform real-time decision making. Here, we review recent major genetic advances in myeloid and lymphoid malignancies, the impact of these findings on prognostic models, our understanding of disease initiation and evolution, and the implication of genomic discoveries on clinical decision making. Finally, we discuss general concepts in genetic modeling and the current state-of-the-art technology used in genetic investigation.

Fig 1.

Risk profile for de novo acute myeloid leukemia based on large-scale mutational studies from Eastern Cooperative Oncology Group E1900 study for patients (A) without FLT3-ITD and (B) with FLT3-ITD mutations.

Fig 2.

Comparison of the relative frequency of mutations (A) in de novo acute myeloid leukemia (AML), post–myeloproliferative neoplasm (MPN) AML, and myelodysplastic syndrome (MDS)^, from three candidate gene sequencing studies. Mutation frequency (B) FLT3-ITD, (C) DNMT3A, (D) TET2, and (E) TP53 in de novo and post-MPN AML.^,

Fig 3.

Mutations in genes involved in H3K27me3 histone mark are found in various myeloid and lymphoid diseases.

Fig 4.

Mutations in various genes in the JAK/STAT pathway (MPL, CRLF2, JAK1, JAK3, JAK2, LNK, SOCS1, STAT3) implicated in hematologic malignancies.