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Integrative analysis of RUNX1 downstream pathways and target genes.

Michaud J, Simpson KM, Escher R, Buchet-Poyau K, Beissbarth T, Carmichael C, Ritchie ME, Schütz F, Cannon P, Liu M, Shen X, Ito Y, Raskind WH, Horwitz MS, Osato M, Turner DR, Speed TP, Kavallaris M, Smyth GK, Scott HS - BMC Genomics (2008)

Bottom Line: We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta.A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability.In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3050, Victoria, Australia. Joelle.Michaud@unil.ch

ABSTRACT

Background: The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia.

Results: Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFbeta, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes.

Conclusion: This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications.

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A. Overlaps between the datasets and percentage of genes with a RUNX1 binding site in their regulatory regions. The overlaps between the different platforms are represented with arrows. * indicates that the genes differentially expressed in at least one of the mouse datasets are considered for the following overlap. The number of differentially expressed genes (DEGs) containing a conserved RUNX1 binding site (with CBS) in their regulatory regions, as determined by the oPOSSUM program [27], over the number of analyzed genes is indicated for each dataset and overlap. The corresponding percentage is indicated in brackets. B. Luciferase assay for 5 RUNX1 binding sites corresponding to 3 differentially expressed genes. The transactivation activity of RUNX1 over these sites was measured as the fold change of the luciferase activity in the presence of the CBF complex compared to the endogenous activity of each construct. The standard errors of three independent replicates are shown. CASP3 was shown as a negative control as no binding site was found for this gene. The difference in expression for the three genes in each dataset is indicated in the table. 0 means no difference in expression, ↓ stands for down-regulated and ↑ stands for up-regulated.
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Figure 6: A. Overlaps between the datasets and percentage of genes with a RUNX1 binding site in their regulatory regions. The overlaps between the different platforms are represented with arrows. * indicates that the genes differentially expressed in at least one of the mouse datasets are considered for the following overlap. The number of differentially expressed genes (DEGs) containing a conserved RUNX1 binding site (with CBS) in their regulatory regions, as determined by the oPOSSUM program [27], over the number of analyzed genes is indicated for each dataset and overlap. The corresponding percentage is indicated in brackets. B. Luciferase assay for 5 RUNX1 binding sites corresponding to 3 differentially expressed genes. The transactivation activity of RUNX1 over these sites was measured as the fold change of the luciferase activity in the presence of the CBF complex compared to the endogenous activity of each construct. The standard errors of three independent replicates are shown. CASP3 was shown as a negative control as no binding site was found for this gene. The difference in expression for the three genes in each dataset is indicated in the table. 0 means no difference in expression, ↓ stands for down-regulated and ↑ stands for up-regulated.

Mentions: In order to distinguish between the direct RUNX1 target genes and those effected further downstream by a disregulation of RUNX1 level, we hypothesized that the genes in common in more than one dataset were more likely to be at the top of the genetic pathways regulated by RUNX1 and to be enriched for direct target genes. As suggested by the significant MR-GSE results, we observed statistically significant overlap between each dataset. Among the 366 genes differentially expressed in FPD-AML cell lines, 69 genes were also differentially expressed following overexpression of the CBF complex, while only 32 were expected by chance (Figure 6A). As anticipated when comparing an under- and overexpression system, 61% (42/69) of the genes in this overlap were differentially expressed in the opposite direction. Among these 69 genes 16 were also differentially expressed in at least one embryonic stage of the Runx1 knockout embryos (Table 2, Figure 6A).


Integrative analysis of RUNX1 downstream pathways and target genes.

Michaud J, Simpson KM, Escher R, Buchet-Poyau K, Beissbarth T, Carmichael C, Ritchie ME, Schütz F, Cannon P, Liu M, Shen X, Ito Y, Raskind WH, Horwitz MS, Osato M, Turner DR, Speed TP, Kavallaris M, Smyth GK, Scott HS - BMC Genomics (2008)

A. Overlaps between the datasets and percentage of genes with a RUNX1 binding site in their regulatory regions. The overlaps between the different platforms are represented with arrows. * indicates that the genes differentially expressed in at least one of the mouse datasets are considered for the following overlap. The number of differentially expressed genes (DEGs) containing a conserved RUNX1 binding site (with CBS) in their regulatory regions, as determined by the oPOSSUM program [27], over the number of analyzed genes is indicated for each dataset and overlap. The corresponding percentage is indicated in brackets. B. Luciferase assay for 5 RUNX1 binding sites corresponding to 3 differentially expressed genes. The transactivation activity of RUNX1 over these sites was measured as the fold change of the luciferase activity in the presence of the CBF complex compared to the endogenous activity of each construct. The standard errors of three independent replicates are shown. CASP3 was shown as a negative control as no binding site was found for this gene. The difference in expression for the three genes in each dataset is indicated in the table. 0 means no difference in expression, ↓ stands for down-regulated and ↑ stands for up-regulated.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2529319&req=5

Figure 6: A. Overlaps between the datasets and percentage of genes with a RUNX1 binding site in their regulatory regions. The overlaps between the different platforms are represented with arrows. * indicates that the genes differentially expressed in at least one of the mouse datasets are considered for the following overlap. The number of differentially expressed genes (DEGs) containing a conserved RUNX1 binding site (with CBS) in their regulatory regions, as determined by the oPOSSUM program [27], over the number of analyzed genes is indicated for each dataset and overlap. The corresponding percentage is indicated in brackets. B. Luciferase assay for 5 RUNX1 binding sites corresponding to 3 differentially expressed genes. The transactivation activity of RUNX1 over these sites was measured as the fold change of the luciferase activity in the presence of the CBF complex compared to the endogenous activity of each construct. The standard errors of three independent replicates are shown. CASP3 was shown as a negative control as no binding site was found for this gene. The difference in expression for the three genes in each dataset is indicated in the table. 0 means no difference in expression, ↓ stands for down-regulated and ↑ stands for up-regulated.
Mentions: In order to distinguish between the direct RUNX1 target genes and those effected further downstream by a disregulation of RUNX1 level, we hypothesized that the genes in common in more than one dataset were more likely to be at the top of the genetic pathways regulated by RUNX1 and to be enriched for direct target genes. As suggested by the significant MR-GSE results, we observed statistically significant overlap between each dataset. Among the 366 genes differentially expressed in FPD-AML cell lines, 69 genes were also differentially expressed following overexpression of the CBF complex, while only 32 were expected by chance (Figure 6A). As anticipated when comparing an under- and overexpression system, 61% (42/69) of the genes in this overlap were differentially expressed in the opposite direction. Among these 69 genes 16 were also differentially expressed in at least one embryonic stage of the Runx1 knockout embryos (Table 2, Figure 6A).

Bottom Line: We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta.A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability.In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3050, Victoria, Australia. Joelle.Michaud@unil.ch

ABSTRACT

Background: The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia.

Results: Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFbeta, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes.

Conclusion: This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications.

Show MeSH
Related in: MedlinePlus