Not Only Mutations Matter: Molecular Picture of Acute Myeloid Leukemia Emerging from Transcriptome Studies

Abstract

The last two decades of genome-scale research revealed a complex molecular picture of acute myeloid leukemia (AML). On the one hand, a number of mutations were discovered and associated with AML diagnosis and prognosis; some of them were introduced into diagnostic tests. On the other hand, transcriptome studies, which preceded AML exome and genome sequencing, remained poorly translated into clinics. Nevertheless, gene expression studies significantly contributed to the elucidation of AML pathogenesis and indicated potential therapeutic directions. The power of transcriptomic approach lies in its comprehensiveness; we can observe how genome manifests its function in a particular type of cells and follow many genes in one test. Moreover, gene expression measurement can be combined with mutation detection, as high-impact mutations are often present in transcripts. This review sums up 20 years of transcriptome research devoted to AML. Gene expression profiling (GEP) revealed signatures distinctive for selected AML subtypes and uncovered the additional within-subtype heterogeneity. The results were particularly valuable in the case of AML with normal karyotype which concerns up to 50% of AML cases. With the use of GEP, new classes of the disease were identified and prognostic predictors were proposed. A plenty of genes were detected as overexpressed in AML when compared to healthy control, includingKIT,BAALC,ERG,MN1,CDX2,WT1,PRAME,andHOXgenes. High expression of these genes constitutes usually an unfavorable prognostic factor. Upregulation ofFLT3andNPM1genes, independent on their mutation status, was also reported in AML and correlated with poor outcome. However, transcriptome is not limited to the protein-coding genes; other types of RNA molecules exist in a cell and regulate genome function. It was shown that microRNA (miRNA) profiles differentiated AML groups and predicted outcome not worse than protein-coding gene profiles. For example, upregulation ofmiR-10a,miR-10b, andmiR-196band downregulation ofmiR-192were found as typical of AML withNPM1mutation whereas overexpression ofmiR-155was associated withFLT3-internal tandem duplication (FLT3-ITD). Development of high-throughput technologies and microarray replacement by next generation sequencing (RNA-seq) enabled uncovering a real variety of leukemic cell transcriptomes, reflected by gene fusions, chimeric RNAs, alternatively spliced transcripts, miRNAs, piRNAs, long noncoding RNAs (lncRNAs), and their special type, circular RNAs. Many of them can be considered as AML biomarkers and potential therapeutic targets. The relations between particular RNA puzzles and other components of leukemic cells and their microenvironment, such as exosomes, are now under investigation. Hopefully, the results of this research will shed the light on these aspects of AML pathogenesis which are still not completely understood.

Role of non-coding RNA networks in leukemia progression, metastasis and drug resistance

“…This has opened space for disclosure and portrayal of non-coding RNAs as biomarkers in leukemia and prompted several investigations in this field over the last 10 years. The full picture of these unusually communicating non-coding RNAs in leukemia is slowly developing [9][10][11][12][13][14][15][16][17]. The vital role and underlying molecular mechanisms of non-coding RNAs and their therapeutic potential in leukemia are outlined in Table 1.…”

Deep Transcriptome Sequencing of Pediatric Acute Myeloid Leukemia Patients at Diagnosis, Remission and Relapse: Experience in 3 Malaysian Children in a Single Center Study

“…The causal link between AML and systemic lupus erythematosus needs further elucidation, even though, there is indeed a link in terms of molecular structure between these two diseases. Moreover, the cell cycle pathway has also been previously reported to be involved in the hematopoietic landscape of AML (Yagi et al, 2003;Handschuh, 2019). Whereas for the relapse vs remission comparison, the most enriched pathway is the transcriptional misregulation in cancer.…”

Drug Resistance Biomarkers and Their Clinical Applications in Childhood Acute Lymphoblastic Leukemia

“…Various high-throughput methods are used to assess differential gene expression at RNA level in leukemia. Two of the most common methods include microarrays and next generation sequencing (90). Since high-throughput technologies remain prone to systematic errors, their clinical applications are limited and need to be confirmed using alternate methods, which are mostly included northern blot analysis and real time PCR (91, 92).…”