Bioinformatics Analysis of Differentially Expressed Genes and Their Functional Enrichment in Acute Myeloid Leukemia Bearing MLL Translocation

Abstract Background Rho GTPase activating protein 9 (ARHGAP9) is expressed in various types of cancers and can inactivate Rho GTPases that mainly regulate cytoskeletal dynamics. However, the exact role of ARHGAP9 in acute myeloid leukemia (AML) has yet to be clarified. Methods We compared the transcriptional expression, prognosis, differentially expressed genes, functional enrichment, and hub genes in AML patients on the basis of the data published in the following databases: UALCAN, GEPIA, Gene Expression Omnibus, the Human Protein Atlas, Cancer Cell Line Encyclopedia, LinkedOmics, Metascape, and String. Data from the Cancer Genome Atlas database was used to evaluate the correlations between ARHGAP9 expression and various clinicopathological parameters, as well as the significantly different genes associated with ARHGAP9 expression. Results We found that ARHGAP9 expression was higher in the tissues and cell lines extracted from patients with AML than corresponding control tissues and other cancer types. ARHGAP9 overexpression was associated with decreased overall survival (OS) in AML. Compared with the ARHGAP9low group, the ARHGAP9high group, which received only chemotherapy, showed significantly worse OS and event-free survival (EFS); however, no significant difference was observed after treatment with autologous or allogeneic hematopoietic stem cell transplantation (auto/allo-HSCT). The ARHGAP9high patients undergoing auto/allo-HSCT also had a significantly better prognosis with respect to OS and EFS than those receiving only chemotherapy. Most overlapping genes of the significantly different genes and co-expression genes exhibited enriched immune functions, suggesting the immune regulation potential of ARHGAP9 in AML. A total of 32 hub genes were identified from the differentially expressed genes, within which the KIF20A had a significant prognostic value for AML. Conclusions ARHGAP9 overexpression was associated with poor OS in AML patients and can be used as a prognostic biomarker. AML patients with ARHGAP9 overexpression can benefit from auto/allo-HSCT rather than chemotherapy.

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TET2/IDH1/2/WT1 and NPM1 Mutations Influence the RUNX1 Expression Correlations in Acute Myeloid Leukemia

Medicina ◽

10.3390/medicina56120637 ◽

2020 ◽

Vol 56 (12) ◽

pp. 637

Author(s):

Sergiu Pasca ◽

Ancuta Jurj ◽

Ciprian Tomuleasa ◽

Mihnea Zdrenghea

Keyword(s):

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Mutational Analysis ◽

Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Runx1 Expression ◽

Acute Myeloid

Background and objectives: Mutational analysis has led to a better understanding of acute myeloid leukemia (AML) biology and to an improvement in clinical management. Some of the most important mutations that affect AML biology are represented by mutations in genes related to methylation, more specifically: TET2, IDH1, IDH2 and WT1. Because it has been shown in numerous studies that mutations in these genes lead to similar expression profiles and phenotypes in AML, we decided to assess if mutations in any of those genes interact with other genes important for AML. Materials and Methods: We downloaded the clinical data, mutational profile and expression profile from the TCGA LAML dataset via cBioPortal. Data were analyzed using classical statistical methods and functional enrichment analysis software represented by STRING and GOrilla. Results: The first step we took was to assess the 196 AML cases that had a mutational profile available and observe the mutations that overlapped with TET2/IDH1/2/WT1 mutations. We observed that RUNX1 mutations significantly overlap with TET2/IDH1/2/WT1 mutations. Because of this, we decided to further investigate the role of RUNX1 mutations in modulating the level of RUNX1 mRNA and observed that RUNX1 mutant cases presented higher levels of RUNX1 mRNA. Because there were only 16 cases of RUNX1 mutant samples and that mutations in this gene determined a change in mRNA expression, we further observed the correlation between RUNX1 and other mRNAs in subgroups regarding the presence of hypermethylating mutations and NPM1. Here, we observed that both TET2/IDH1/2/WT1 and NPM1 mutations increase the number of genes negatively correlated with RUNX1 and that these genes were significantly linked to myeloid activation. Conclusions: In the current study, we have shown that NPM1 and TET2/IDH1/2/WT1 mutations increase the number of negative correlations of RUNX1 with other transcripts involved in myeloid differentiation.

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Distinct association of RUNX family expression with genetic alterations and clinical outcome in acute myeloid leukemia

Cancer Biomarkers ◽

10.3233/cbm-200016 ◽

2020 ◽

Vol 29 (3) ◽

pp. 387-397

Author(s):

Yangli Zhao ◽

Tingjuan Zhang ◽

Yangjing Zhao ◽

Jingdong Zhou

Keyword(s):

Acute Myeloid Leukemia ◽

Clinical Outcome ◽

Myeloid Leukemia ◽

Disease Free Survival ◽

Genetic Alterations ◽

Differentially Expressed ◽

Aberrant Expression ◽

Hematopoietic Stem ◽

Frequent Event ◽

Acute Myeloid

BACKGROUND: The runt-related transcription factor family (RUNXs) including RUNX1, RUNX2, and RUNX3 are key transcriptional regulators in normal hematopoiesis. RUNXs dysregulations caused by aberrant expression or mutation are frequently seen in various human cancers especially in acute myeloid leukemia (AML). OBJECTIVE: We systemically analyzed the expression of RUNXs and their relationship with clinic-pathological features and prognosis in AML patients. METHODS: Expression of RUNXs was analyzed between AML patients and normal controls from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects. Correlations between RUNXs expression and clinical features together with survival were further analyzed. RESULTS: All RUNXs expression in AML patients was significantly increased as compared with controls. RUNXs expression was found to be significantly associated with genetic abnormalities such as RUNX1 mutation, t(8;21) and inv(16)/t(16;16). By Kaplan-Meier analysis, only RUNX3 overexpression was associated with shorter overall survival (OS) and disease-free survival (DFS) among non-M3 AML patients. Notably, in high RUNX3 expression groups, patients received hematopoietic stem cell transplantation (HSCT) had markedly better OS and DFS than patients without HSCT among both all AML and non-M3 AML. In low RUNX3 expression groups, there were no significant differences in OS and DFS between HSCT and non-HSCT groups among both all AML and non-M3 AML. In addition, a total of 835 differentially expressed genes and 69 differentially expressed microRNAs were identified to be correlated with RUNX3 expression in AML. CONCLUSION: RUNXs overexpression was a frequent event in AML, and was closely associated with diverse genetic alterations. Moreover, RUNX3 expression may be associated with clinical outcome, and helpful for guiding treatment choice between HSCT and chemotherapy in AML.

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Relationship of differential gene expression profiles in CD34+ myelodysplastic syndrome marrow cells to disease subtype and progression

Blood ◽

10.1182/blood-2009-08-236422 ◽

2009 ◽

Vol 114 (23) ◽

pp. 4847-4858 ◽

Cited By ~ 53

Author(s):

Kunju Sridhar ◽

Douglas T. Ross ◽

Robert Tibshirani ◽

Atul J. Butte ◽

Peter L. Greenberg

Keyword(s):

Gene Expression ◽

Acute Myeloid Leukemia ◽

Myelodysplastic Syndrome ◽

Differential Gene Expression ◽

Myeloid Leukemia ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Differentially Expressed ◽

Differential Gene ◽

Acute Myeloid

AbstractMicroarray analysis with 40 000 cDNA gene chip arrays determined differential gene expression profiles (GEPs) in CD34+ marrow cells from myelodysplastic syndrome (MDS) patients compared with healthy persons. Using focused bioinformatics analyses, we found 1175 genes significantly differentially expressed by MDS versus normal, requiring a minimum of 39 genes to separately classify these patients. Major GEP differences were demonstrated between healthy and MDS patients and between several MDS subgroups: (1) those whose disease remained stable and those who subsequently transformed (tMDS) to acute myeloid leukemia; (2) between del(5q) and other MDS patients. A 6-gene “poor risk” signature was defined, which was associated with acute myeloid leukemia transformation and provided additive prognostic information for International Prognostic Scoring System Intermediate-1 patients. Overexpression of genes generating ribosomal proteins and for other signaling pathways was demonstrated in the tMDS patients. Comparison of del(5q) with the remaining MDS patients showed 1924 differentially expressed genes, with underexpression of 1014 genes, 11 of which were within the 5q31-32 commonly deleted region. These data demonstrated (1) GEPs distinguishing MDS patients from healthy and between those with differing clinical outcomes (tMDS vs those whose disease remained stable) and cytogenetics [eg, del(5q)]; and (2) molecular criteria refining prognostic categorization and associated biologic processes in MDS.

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Identification of a Prognostic Gene Signature Associated with Microenvironment in Acute Myeloid Leukemia

10.21203/rs.3.rs-91594/v1 ◽

2020 ◽

Author(s):

Zhixiang Chen ◽

Luya Ye ◽

Xuechun Wang ◽

Fuquan Tu ◽

Xuezhen Li ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Expression Profiles ◽

Critical Role ◽

Enrichment Analysis ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Risk Scores ◽

Acute Myeloid

Abstract Background: Acute myeloid leukemia (AML) is a common hematologic malignancy with poor prognosis. Accumulating reports have indicated that the tumor microenvironment (TME) performs a critical role in the progress of the disease and the clinical outcomes of patients. To date, the role of TME in AML remains clouded due to the complex regulatory mechanisms in it. In this study, We identified key prognostic genes relate to TME in AML and developed a novel gene signature for individualized prognosis assessment. Methods: The expression profiles of AML samples with clinical information were obtained from the Cancer Genome Atlas (TCGA). The ESTIMATE algorithm was applied to calculate the TME relevant immune and stromal scores. The differentially expressed genes (DEGs) were selected based on the immune and stromal scores. Then, the survival analysis was applied to select prognostic DEGs, and these genes were annotated by functional enrichment analysis. A TME relevant gene signature with predictive capability was constructed by a series of regression analyses and performed well in another cohort from the Gene Expression Omnibus (GEO) database. Moreover, we also developed a nomogram with the integration of the gene signature and clinical indicators to establish an individually quantified risk-scoring system. Results: In the AML microenvironment, a total of 181 DEGs with prognostic value were clarified. Then a seven-gene ( IL1R2, MX1, S100A4, GNGT2, ZSCAN23, PLXNB1 and DPY19L2 ) signature with robust prediction was identified, and was validated by an independent cohort of AML samples from the GSE71014. Gene set enrichment analysis (GSEA) of genes in the gene signature revealed these genes mainly enriched in the immune and inflammatory related processes. The correlation between the signature-calculated risk scores and the clinical features indicated that patients with high risk scores were accompanied by adverse survival. Finally, a nomogram with clinical utility was constructed. Conclusion: Our study explored and identified a novel TME relevant seven-gene signature, which could serve as a prognostic indicator for AML. Meanwhile, we also establish a nomogram with clinical significance. These findings might provide new insights into the diagnosis, treatment and prognosis of AML.

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Exploring the Expression Profile of Long Non-Coding RNA (lncRNA) in Different Acute Myeloid Leukemia (AML) Subtypes: t(8;16)(p11;p13)/MYST3-Crebbp AML Harbors a Distinctive Lncrna Signature

Blood ◽

10.1182/blood.v126.23.1397.1397 ◽

2015 ◽

Vol 126 (23) ◽

pp. 1397-1397 ◽

Cited By ~ 2

Author(s):

Marina Diaz-Beya ◽

Alfons Navarro ◽

Anna Cordeiro ◽

Marta Pratcorona ◽

Joan Castellano ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Transcription Factors ◽

Expression Pattern ◽

Expression Profile ◽

Myeloid Leukemia ◽

Genomic Region ◽

Differentially Expressed ◽

Specific Gene ◽

Lncrna Expression ◽

Acute Myeloid

Abstract Introduction: Long non-coding RNAs (lncRNAs) have recently emerged as important actors in the regulation of multiple cellular processes including cancer. Acute myeloid leukemia (AML) is a heterogeneous disease; most of the main cytogenetic AML subgroups harbor a specific gene expression profile. AML with translocation t(8;16)(p11;p13) (t(8;16) AML) is a subtype with specific clinical and biological characteristics including a distinctive gene (Camós et al, Cancer Research 2006) and microRNA (Díaz-Beyá et al, Leukemia 2013) expression profile. In this translocation, MYST3 on chromosome 8p11 fuses with CREBBP on chromosome 16p13.3. The MYST3-CREBBP fusion protein is able to interact with multiple transcription factors (TF) producing a disturbed transcriptional program. However, the lncRNA expression pattern of different cytogenetic AML subtypes, including t(8;16) AML, have not been described yet. Aims: To examine the expression profile of lncRNAs within different AML subtypes, and to characterize the expression pattern of lncRNAs in t(8;16) AML in comparison to other AML subtypes. Patients and Methods: 46 AML patients, 4 normal bone marrow (NBM) and 3 CD34+ NBM samples were included in the study. Samples included different AML subtypes: intermediate-risk cytogenetic AML (IR-AML, n=18), t(15;17) (APL, n=4), t(8;21) AML (n=4), inv(16) AML(n=2), t(6;9) AML (n=7), AML with monosomal karyotype (n=4), t(3;3) AML (n=1), t(9;11) AML (n=1) and t(8;16) AML (n=5). Within IR-AML patients with a different mutational profile: FLT3-ITD (n=7), NPM1 (n=5), CEBPA (n=7) and DNMT3A (n=6) were included. The lncRNA expression was studied using Affymetrix® Human Gene 2.1 ST platform which includes 9698 lncRNAs transcripts. The filtering and normalization of the array data was performed using oligo package from Bioconductor. Statistical analyses were performed with TiGR MultiExperiment Viewer, BRB tools and R. The Transcription factor Affinity Prediction Web Tool was used to determine the putative transcription factors binding to the differentially expressed lncRNAs promoters. Results: The hierarchical cluster analysis showed that all 4 NBM as well as all 3 CD34+ NBM clustered together according to their lncRNA expression. Interestingly, all 5 t(8;16) AML samples clustered together, as well as the 3 APL, the 7 t(6;9) AML and 5 out of 7 cases with CEBPA mutations. The specific lncRNA signature of APL was composed of 79 differentially expressed lncRNA and t(6;9) AML lncRNA signature comprised of 15 differentially expressed lncRNAs. When we focused on t(8;16) AML lncRNA profile, we identified an specific 113-lncRNA signature in the supervised analysis (Figure). Interestingly, when we analyzed which (TF) had motifs overrepresented in the promoters regions of the t(8;16) AML lncRNA signature, we identified GATA2 as the TF with significantly overrepresented motifs for GATA2 (p<0.001). Interestingly, levels of GATA2 were differentially expressed in t(8;16) AML samples in comparison with other AMLs samples (p<0.001). GATA2 has been described to interact with CREBBP, one of the partners involved in t(8;16) AML. Of note, 4 overexpressed lncRNAs of the signature (linc-HOXA11, HOXA11-AS, HOTTIP and NR_038120) were located in the HOXA genomic region, previously found upregulated in t(8:16) AML. Since several studies suggest an active crosstalk between microRNAs and lncRNAs, we also correlated the expression of these lncRNAs with the microRNA t(8;16) AML profile. We found significant correlation between linc-HOXA11 and miR-222* (R2 =0.996, p=0.003), HOXA11-AS and miR-let-7c (R2=0.994, p=0.006), HOTTIP and miR-196b*(R2=0.958, p=0.041), and NR_038120 with miR-486-3p (R2=0.999, p=0.0004) and miR-19a (R2=0.953, p=0.04). Conclusions: LncRNAs expression profile seems specific of several AML subtypes, including t(8;16) AML. Some of the lncRNAs of this distinctive signature in t(8;16) AML are located in the HOXA genomic region, and correlate with several of the characteristic microRNAs previously described in this entity. Interestingly, we have predicted in silico GATA2, which interacts with CREBBP, as the most significant TF that could potentially regulate this lncRNAs signature. Nonetheless, further investigation is warranted to determine the mechanisms leading to this lncRNA signature and to identify the specific targets of these lncRNAs. Río Hortega CM13/00205, FIS PI13/00999 Disclosures No relevant conflicts of interest to declare.

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Loss of H3K27 Methylation Identifies Poor Outcome in Adult-Onset Acute Myeloid Leukemia

Blood ◽

10.1182/blood-2020-139387 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 24-24

Author(s):

Anneke D. van Dijk ◽

Fieke W Hoff ◽

Yihua Qiu ◽

Eveline S. de Bont ◽

Sophia W.M. Bruggeman ◽

...

Keyword(s):

Dna Methylation ◽

Overall Survival ◽

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Molecular Genetic ◽

Functional Enrichment ◽

Prognostic Impact ◽

Cox Regression Analysis ◽

H3k27 Methylation ◽

Acute Myeloid

Background: Acute myeloid leukemia (AML) is an epigenetically heterogeneous disease. The intensity of treatment is currently guided by cytogenetic and molecular genetic risk classifications; however these incompletely predict outcomes, requiring additional information for more accurate predictions. We aimed to identify potential prognostic implications of epigenetic modification of histone proteins, with a focus of H3K27 methylation in relation to mutations in chromatin, splicing and transcriptional regulators. Material and methods: Histone methylation mark expressions were evaluated in a cohort of 241 AML bone marrow (BM) and peripheral blood (PB) samples from patients admitted at the MD Anderson Cancer Center relative to their expression in CD34+ BM derived samples from healthy donors. Simultaneous analysis of 230 proteins was performed using the reverse phase protein array - a high-throughput, quantitative proteomic platform that enables identification of aberrant expressed proteins and the pathways they act in. Additional mutational analysis was performed on 65 BM samples. Results:H3K27Me3 was significantly lower in both BM and PB leukemic-derived samples compared to their expression in normal BM (figure 1A). A greater loss of H3K27Me3 associated with increased proliferative potential and shorter overall survival (OS) in the whole patient population (n=241, HR=0.64, 95% CI=0.47-0.87, p<0.01), as well as in subsets, e.g. cytogenetically normal AML (n=110, HR=0.62, 95% CI=0.40-0.97, p=0.03). To study the prognostic impact of H3K27Me3 in the context of cytogenetic aberrations and mutations, multivariate cox regression analysis was performed which identified H3K27Me3 level as an independent favorable prognostic factor in all (HR=0.74, 95%CI=0.57-0.95, p=0.02) as well as in P53 mutated AML (n=54, HR=0.48, 95%CI=0.26-0.87, p=0.02). A total of 78 AML patients had molecular data available for the major methylation affecting genes, i.e. IDH1, IDH2, DNMT3A and TET2. The level of H3K27Me3 was not prognostic in patients without any DNA methylation affecting mutation present, but patients with at least one mutation in any of these had better outcome when H3K27Me3 levels were high (highest tertile, figure 1A) compared to those with lower levels (median OS 7.1 vs. 24.1 months, HR=0.42, 95% CI=0.21-0.83, p=0.01, figure 1B). Mutations in U2AF1 and SRSF2 affect the spliceosome and are frequently found in antecedent hematological disorders (AHD), as well as are mutations in chromatin regulating genes ASXL1 and BCOR. We observed significant decreased H3K27Me3 in patients with these mutations corresponding with observed lower levels of H3K27Me3 in patients with AHD than those without (p=0.035). BCOR, SRSF2, U2AF1 and ASXL1 mutations confer poor prognosis in myeloid malignancies, however, in our cohort of 65 sequenced AML patients; not individual or a combination of these mutations were independent prognostic factors, but the degree of H3K27Me3 in these patients (HR= 0.49, 95% CI=0.25-0.95, p=0.03). To recognize dysregulated pathways in AML patients with the identified loss of H3K27Me3, we examined correlations of H3K27Me3 with the other 229 proteins on the array. H3K27Me3 is catalyzed by the polycomb group protein EZH2 and is linked to transcriptional repression via the formation of heterochromatin regions. To identify upregulated proteins and pathways upon the loss of H3K27Me3, we focused on significant negatively correlated proteins with H3K27Me3 leading us to the identification of 20 total and 6 phospho-proteins that showed increased expression upon decreased H3K27Me3. Functional enrichment analysis of this protein set revealed an upregulated anti-apoptotic phenotype. Conclusion:This study shows that proteomic profiling of epigenetic modifications on the histone level have clinical implications in AML and support the idea that epigenetic patterns contribute to a more accurate picture of the leukemic state complementing cytogenetic and molecular genetic subgrouping. Figure 1. A) Lower H3K27Me3 in BM and PB derived AML samples compared to normal CD34+. **** represents p<0.0001, ns = not significant. B) Overall survival probability in AML patients with any DNA methylation affecting mutation (i.e. IDH1/2, DNMT3A, TET2, n=53) according to H3K27Me3 low (blue) and high (orange) status. Figure 1 Disclosures No relevant conflicts of interest to declare.

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MAPK Signaling Pathway was Dysregulated in Acute Myeloid Leukemia with RUNX1 Mutations

10.21203/rs.3.rs-502740/v1 ◽

2021 ◽

Author(s):

Mingmin he ◽

Xiongwei Cai ◽

Yuanyuan Zeng

Keyword(s):

Acute Myeloid Leukemia ◽

Signaling Pathway ◽

Myeloid Leukemia ◽

Target Genes ◽

Mapk Signaling ◽

Mapk Signaling Pathway ◽

Functional Enrichment ◽

Wild Type ◽

The Relationship ◽

Acute Myeloid

Abstract The purpose of this study was to investigate the relationship between RUNX1 mutations and MAPK signaling pathway in acute myeloid leukemia (AML). In this study, we analyzed miRNA expression with 5 mutant RUNX1 and 9 wild-type RUNX1 cases from TCGA database of AML. Six miRNAs were differently expressed with significance, and three of them were related to overall survival. Predicted target genes of these 3 miRNAs were highly enriched in MAPK signaling pathway by functional enrichment with miRWalk3.0. Besides, genes among RUNX1 associated genes directly regulated by RUNX1 were involved in MAPK signaling pathway, too. Taken together, we demonstrate three DEmiRNAs and three genes correlated to RUNX1 were correlated with prognosis in AML, and RUNX1 modulated MAPK signaling pathway in AML.

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