| Literature DB >> 28219393 |
Hubert Hackl1, Ksenia Astanina2, Rotraud Wieser3.
Abstract
BACKGROUND: The majority of individuals with acute myeloid leukemia (AML) respond to initial chemotherapy and achieve a complete remission, yet only a minority experience long-term survival because a large proportion of patients eventually relapse with therapy-resistant disease. Relapse therefore represents a central problem in the treatment of AML. Despite this, and in contrast to the extensive knowledge about the molecular events underlying the process of leukemogenesis, information about the mechanisms leading to therapy resistance and relapse is still limited. PURPOSE AND CONTENT OF REVIEW: Recently, a number of studies have aimed to fill this gap and provided valuable information about the clonal composition and evolution of leukemic cell populations during the course of disease, and about genetic, epigenetic, and gene expression changes associated with relapse. In this review, these studies are summarized and discussed, and the data reported in them are compiled in order to provide a resource for the identification of molecular aberrations recurrently acquired at, and thus potentially contributing to, disease recurrence and the associated therapy resistance. This survey indeed uncovered genetic aberrations with known associations with therapy resistance that were newly gained at relapse in a subset of patients. Furthermore, the expression of a number of protein coding and microRNA genes was reported to change between diagnosis and relapse in a statistically significant manner.Entities:
Keywords: Acute myeloid leukemia; Clonal evolution; Copy number variation; Cytogenetics; DNA methylation; Gene expression profiling; Relapse; Single nucleotide variants; Therapy resistance
Mesh:
Year: 2017 PMID: 28219393 PMCID: PMC5322789 DOI: 10.1186/s13045-017-0416-0
Source DB: PubMed Journal: J Hematol Oncol ISSN: 1756-8722 Impact factor: 17.388
Fig. 1Genetic and molecular events investigated for possible changes between diagnosis and relapse of AML. A diagram representing clonal evolution in a hypothetical patient with AML is shown in the top panel. The other panels represent genetic and molecular alterations between diagnosis and relapse of AML that are discussed in this article; methods used to investigate these aberrations are indicated to the left of the respective panels. HSCs hematopoietic stem cells, CR complete remission, transloc translocation, SNP single nucleotide polymorphism
Gains and losses of mutations in known leukemia driver genes at relapse of AML
| Total number of patients | Age group | Genetics at diagnosis | Number of patients with gain of mutation | Number of patients with loss of mutation | Reference | |
|---|---|---|---|---|---|---|
|
| ||||||
|
|
|
|
| |||
| 28 | A | 1 | 1 | [ | ||
| 28 | A | 6 | 1 | [ | ||
| 34 | A | 2 | 3 | [ | ||
| 108 | A | 8 | 1 | [ | ||
| 31 | A | 1 | 2 | [ | ||
| 53 | A |
| 9 | 3 | [ | |
| 80 | A, P | 5 | 4 | [ | ||
| 44 | A, P | 2 | 5 | [ | ||
| 23 | P | 2 | 1 | [ | ||
| 63 | P | 2 | 4 | [ | ||
|
| ||||||
|
|
|
|
| |||
| 34 | A | 1 | 3 | [ | ||
| 120 | A | 6 | 8 | [ | ||
| 31 | A | 0 | 1 | [ | ||
| 53 | A |
| 0 | 10 | [ | |
| 53 | A, P | 0 | 1 | [ | ||
| 44 | A, P | 2 | 0 | [ | ||
| 50 | P | 1 | 1 | [ | ||
|
| ||||||
|
|
|
|
| |||
| 28 | A | 0 | 0 | [ | ||
| 34 | A | 0 | 3 | [ | ||
| 53 | A |
| n.a. | 5 | [ | |
| 70 | A, P |
| n.a. | 0 | [ | |
| 46 | P | 0 | 0 | [ | ||
| 68 | P | 0 | 1 | [ | ||
|
| ||||||
|
|
|
|
| |||
| 28 | A | 0 | 0 | [ | ||
| 34 | A | 0 | 0 | [ | ||
| 116 | A | 0 | 1 | [ | ||
| 53 | A |
| 1 | 1 | [ | |
|
| ||||||
|
|
|
|
| |||
| 28 | A | 1 | 1 | [ | ||
| 34 | A | 0 | 2 | [ | ||
| 149 | A, P | 0 | 2 | [ | ||
| 30 | P | 1 | 0 | [ | ||
|
| ||||||
|
|
|
|
| |||
| 28 | A | 0 | 0 | [ | ||
| 34 | A | 0 | 0 | [ | ||
| 121 | A | 0 | 0 | [ | ||
| 53 | A |
| 0 | 1 | [ | |
|
| ||||||
|
|
|
|
| |||
| 28 | A | 0 | 0 | [ | ||
| 34 | A | 0 | 0 | [ | ||
| 53 | A |
| 4 | 2 | [ | |
|
| ||||||
|
|
|
|
| |||
| 19 | A | 2 | 3 | [ | ||
| 34 | A | 1 | 0 | [ | ||
| 53 | A |
| 5 | 9 | [ | |
|
| ||||||
|
|
|
|
| |||
| 28 | A | 0 | 1 | [ | ||
| 34 | A | 1 | 0 | [ | ||
|
| ||||||
|
|
|
|
| |||
| 23 | P | 2 | 1 | [ | ||
| 52 | P | 4 | 7 | [ | ||
|
| ||||||
|
|
|
|
| |||
| 28 | A | 0 | 1 | [ | ||
| 23 | A | 2 | 0 | [ | ||
| 53 | A |
| 1 | 0 | [ | |
|
| ||||||
|
|
|
|
| |||
| 23 | P | 3 | 0 | [ | ||
| 42 | P | 5 | 0 | [ | ||
| 39 | P | 6 | 0 | [ | ||
|
| ||||||
|
|
|
|
| |||
| 28 | A | 0 | 0 | [ | ||
| 53 | A |
| 2 | 0 | [ | |
|
| ||||||
|
|
|
|
| |||
| 27 | P | 0 | 0 | [ | ||
| 8 | P | CBF | 0 | 0 | [ | |
|
| ||||||
|
|
|
|
| |||
| 28 | A | 0 | 0 | [ | ||
| 34 | A | 0 | 0 | [ | ||
|
| ||||||
| 34 | A | 0 | 0 | [ | ||
|
| ||||||
| 23 | P | 0 | 1 | [ | ||
|
| ||||||
| 28 | A | 1 | 1 | [ | ||
The total number of investigated patients, patient age group, genetics at diagnosis in studies based on selected samples, the number of patients with gain or loss of mutation in the respective gene, and the corresponding references are listed. This table summarizes mutations determined by small scale targeted sequencing approaches. Gains and losses of mutations in these genes were also found through next generation sequencing-based methods, as summarized in Additional file 3: Table S3A and B
A adult, P pediatric, n.a. not applicable, NPM1 AML with NPM1 mutations, CBF AML with core-binding factor rearrangements
Fig. 2Circos plot summarizing genetic aberrations recurrently acquired at relapse in adult patients with non-APL AML. Inner circle, unbalanced cytogenetic aberrations newly acquired at relapse in at least 2 patients [53–56, 63, 68, 122]; middle circle, CNAs and UPDs newly acquired at relapse in at least 2 patients [64–69]. Within each type of aberration, overlapping lesions were considered recurrent events unless an aberration was reported only in 1 patient and became recurrent due to the same type of aberration affecting the corresponding entire chromosome in another single patient. For high patient numbers, different scales were used and patient numbers color-coded as indicated in the graphical legend. Outer circle, genes affected by SNVs or indels in a relapse-specific manner in at least 2 patients according to next generation sequencing-based studies [34, 36, 38, 39, 68, 95, 96]. The plot was constructed using the R package “circlize” [123]. Genomic positions of genes and chromosome bands were retrieved from the UCSC genome browser, human genome version hg19. Detailed data are provided in Additional file 1: Table S1A, Additional file 2: Table S2A, and Additional file 3: Table S3A. These also include studies containing exclusively pediatric patients or patients with APL, which were not considered for this figure. Recurrently gained aberrations are shown in this graph irrespective of whether or not they were recurrently lost in other patients; information about recurrent loss at relapse is provided in Additional file 1: Table S1B, Additional file 2: Table S2B, and Additional file 3: Table S3B
Fig. 3Different pathways leading to relapse of AML. Gray dots, age-related, pathogenetically irrelevant passenger mutations; orange dots, early (pre-) leukemic driver mutations; red dots, late leukemic driver mutations; bright yellow dots, non-synonymous mutations newly acquired at relapse. All HSCs are assumed to accumulate mostly innocuous mutations during aging; only mutations that would be found as passenger mutations in AML are depicted in the figure. The figure does not intend to illustrate the duration of CR, or the presence or absence of minimal residual disease detectable by routine methods. Dx diagnosis, CR complete remission, LSC leukemic stem cell, HSC hematopoietic stem cell