Dataset Information

Landscape of Tumor Suppressor Mutations in Acute Myeloid Leukemia.

ABSTRACT: Acute myeloid leukemia is mainly characterized by a complex and dynamic genomic instability. Next-generation sequencing has significantly improved the ability of diagnostic research to molecularly characterize and stratify patients. This detailed outcome allowed the discovery of new therapeutic targets and predictive biomarkers, which led to develop novel compounds (e.g., IDH 1 and 2 inhibitors), nowadays commonly used for the treatment of adult relapsed or refractory AML. In this review we summarize the most relevant mutations affecting tumor suppressor genes that contribute to the onset and progression of AML pathology. Epigenetic modifications (TET2, IDH1 and IDH2, DNMT3A, ASXL1, WT1, EZH2), DNA repair dysregulation (TP53, NPM1), cell cycle inhibition and deficiency in differentiation (NPM1, CEBPA, TP53 and GATA2) as a consequence of somatic mutations come out as key elements in acute myeloid leukemia and may contribute to relapse and resistance to therapies. Moreover, spliceosomal machinery mutations identified in the last years, even if in a small cohort of acute myeloid leukemia patients, suggested a new opportunity to exploit therapeutically. Targeting these cellular markers will be the main challenge in the near future in an attempt to eradicate leukemia stem cells.

SUBMITTER: Panuzzo C

PROVIDER: S-EPMC7141302 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Landscape of Tumor Suppressor Mutations in Acute Myeloid Leukemia.

Panuzzo Cristina C Signorino Elisabetta E Calabrese Chiara C Ali Muhammad Shahzad MS Petiti Jessica J Bracco Enrico E Cilloni Daniela D

Journal of clinical medicine 20200316 3

Acute myeloid leukemia is mainly characterized by a complex and dynamic genomic instability. Next-generation sequencing has significantly improved the ability of diagnostic research to molecularly characterize and stratify patients. This detailed outcome allowed the discovery of new therapeutic targets and predictive biomarkers, which led to develop novel compounds (e.g., IDH 1 and 2 inhibitors), nowadays commonly used for the treatment of adult relapsed or refractory AML. In this review we summ ...[more]

PMID: 32188030

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Project description:Background:Acute myeloid leukemia (AML) is a type of cancer that consists of a group of hematological malignancies with high heterogeneity. DNA methyltransferase 3A (DNMT3A)-mutated AML patients have a poor prognosis. Some long non-coding RNAs (lncRNAs) have been reported to enhance therapeutic sensitivity, and so could affect the overall survival rate of elderly cytogenetically normal acute myeloid leukemia (CN-AML) patients; however, studies on the lncRNA signature in DNMT3A-mutated AML are rare. Method:The DNMT3A R878H conditional knock-in mouse model was constructed to explore the lncRNAs of DNMT3A mutation by using the Cuffcomparison method. Cis and trans regulation networks were used to predict candidate genes. The expression levels in leukemic cell lines and the prognostic index of these candidate genes were analyzed with the Broad Institute Cancer Cell Line Encyclopedia (CCLE) and OncoLnc databases. The data for each sample were statistically analyzed using GraphPad Prism. Results:In this study, we applied the DNMT3A R878H conditional knock-in mouse model to explore the lncRNA epigenetic landscape of DNMT3A mutation by using the Cuffcomparison method. Twenty-three differentially expressed lncRNAs were identified in Dnmt3aR878H/WTMx1-Cre+ mice. We next predicted the downstream targetable genes regulated by these lncRNAs through cis and trans regulation networks and found 124 candidate genes are related to these lncRNAs. In further analysis of 124 genes, we found that increased mRNA expression levels of interleukin 1 receptor type 2 (IL1R2), Krüppel-like factor 13 (KLF13), ATPase H+ transporting V1 subunit A (ATP6V1A), proteasome 26S Subunit, non-ATPase 3 (PSMD3), and pyrroline-5-carboxylate reductase 2 (PYCR2) were associated with poor prognosis in AML. Functional analysis of these genes demonstrated that the pathways involved in autophagy, cell cycle, and hematopoietic stem cell differentiation were more enriched in Dnmt3aR878H/WTMx1-Cre+ mice. Conclusion:Our study was the first to use DNMT3A R878H conditional knock-in mouse model to predict the specific lncRNAs regulated by the DNMT3A mutation in AML. Six candidate genes were found to be associated with DNMT3A mutation with poor prognosis. Our results provided a possible treatment strategy for this disease.

Project description:This study concerns the analysis of the modulation of Chronic Myeloid Leukemia (CML) cell model K562 transcriptome following transfection with the tumor suppressor gene encoding for Protein Tyrosine Phosphatase Receptor Type G (PTPRG) and treatment with the tyrosine kinase inhibitor (TKI) Imatinib. Specifically, we aimed at identifying genes whose level of expression is altered by PTPRG modulation and Imatinib concentration. Statistical tests as differential expression analysis (DEA) supported by gene set enrichment analysis (GSEA) and modern methods of ontological term analysis are presented along with some results of current interest for forthcoming experimental research in the field of the transcriptomic landscape of CML. In particular, we present two methods that differ in the order of the analysis steps. After a gene selection based on fold-change value thresholding, we applied statistical tests to select differentially expressed genes. Therefore, we applied two different methods on the set of differentially expressed genes. With the first method (Method 1), we implemented GSEA, followed by the identification of transcription factors. With the second method (Method 2), we first selected the transcription factors from the set of differentially expressed genes and implemented GSEA on this set. Method 1 is a standard method commonly used in this type of analysis, while Method 2 is unconventional and is motivated by the intention to identify transcription factors more specifically involved in biological processes relevant to the CML condition. Both methods have been equipped in ontological knowledge mining and word cloud analysis, as elements of novelty in our analytical procedure. Data analysis identified RARG and CD36 as a potential PTPRG up-regulated genes, suggesting a possible induction of cell differentiation toward an erithromyeloid phenotype. The prediction was confirmed at the mRNA and protein level, further validating the approach and identifying a new molecular mechanism of tumor suppression governed by PTPRG in a CML context.

Dataset Information

Landscape of Tumor Suppressor Mutations in Acute Myeloid Leukemia.

Publications

Landscape of Tumor Suppressor Mutations in Acute Myeloid Leukemia.

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