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Heterogeneous activation of the TGFbeta pathway in glioblastomas identified by gene expression-based classification using TGFbeta-responsive genes.

Xu XL, Kapoun AM - J Transl Med (2009)

Bottom Line: Among glioblastomas, one of the most devastating human cancers, two subgroups were identified that showed distinct TGFbeta activation patterns as measured from transcriptional responses.Approximately 62% of glioblastoma samples analyzed showed strong TGFbeta activation, while the rest showed a weak TGFbeta transcriptional response.Our findings suggest heterogeneous TGFbeta activation in glioblastomas, which may cause potential differences in responses to anti-TGFbeta therapies in these two distinct subgroups of glioblastomas patients.

View Article: PubMed Central - HTML - PubMed

Affiliation: Biomarker R&D, Scios Inc, Fremont, California, USA. lxu@its.jnj.com

ABSTRACT

Background: TGFbeta has emerged as an attractive target for the therapeutic intervention of glioblastomas. Aberrant TGFbeta overproduction in glioblastoma and other high-grade gliomas has been reported, however, to date, none of these reports has systematically examined the components of TGFbeta signaling to gain a comprehensive view of TGFbeta activation in large cohorts of human glioma patients.

Methods: TGFbeta activation in mammalian cells leads to a transcriptional program that typically affects 5-10% of the genes in the genome. To systematically examine the status of TGFbeta activation in high-grade glial tumors, we compiled a gene set of transcriptional response to TGFbeta stimulation from tissue culture and in vivo animal studies. These genes were used to examine the status of TGFbeta activation in high-grade gliomas including a large cohort of glioblastomas. Unsupervised and supervised classification analysis was performed in two independent, publicly available glioma microarray datasets.

Results: Unsupervised and supervised classification using the TGFbeta-responsive gene list in two independent glial tumor gene expression data sets revealed various levels of TGFbeta activation in these tumors. Among glioblastomas, one of the most devastating human cancers, two subgroups were identified that showed distinct TGFbeta activation patterns as measured from transcriptional responses. Approximately 62% of glioblastoma samples analyzed showed strong TGFbeta activation, while the rest showed a weak TGFbeta transcriptional response.

Conclusion: Our findings suggest heterogeneous TGFbeta activation in glioblastomas, which may cause potential differences in responses to anti-TGFbeta therapies in these two distinct subgroups of glioblastomas patients.

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Related in: MedlinePlus

Outline of data analysis steps.
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Figure 1: Outline of data analysis steps.

Mentions: ANOVA, t-test, Pearson's correlation coefficient calculations, Support Vector Machine (SVM) classification, and survival analysis were computed using MATLAB 7.1 software (MathWorks, Natick, MA). The hierarchical clustering was performed in Spotfire DecisionSite 8.1 for Functional Genomics (Spotfire, Somerville, MA). The overall outline of the analysis steps is summarized in Figure 1.


Heterogeneous activation of the TGFbeta pathway in glioblastomas identified by gene expression-based classification using TGFbeta-responsive genes.

Xu XL, Kapoun AM - J Transl Med (2009)

Outline of data analysis steps.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2655274&req=5

Figure 1: Outline of data analysis steps.
Mentions: ANOVA, t-test, Pearson's correlation coefficient calculations, Support Vector Machine (SVM) classification, and survival analysis were computed using MATLAB 7.1 software (MathWorks, Natick, MA). The hierarchical clustering was performed in Spotfire DecisionSite 8.1 for Functional Genomics (Spotfire, Somerville, MA). The overall outline of the analysis steps is summarized in Figure 1.

Bottom Line: Among glioblastomas, one of the most devastating human cancers, two subgroups were identified that showed distinct TGFbeta activation patterns as measured from transcriptional responses.Approximately 62% of glioblastoma samples analyzed showed strong TGFbeta activation, while the rest showed a weak TGFbeta transcriptional response.Our findings suggest heterogeneous TGFbeta activation in glioblastomas, which may cause potential differences in responses to anti-TGFbeta therapies in these two distinct subgroups of glioblastomas patients.

View Article: PubMed Central - HTML - PubMed

Affiliation: Biomarker R&D, Scios Inc, Fremont, California, USA. lxu@its.jnj.com

ABSTRACT

Background: TGFbeta has emerged as an attractive target for the therapeutic intervention of glioblastomas. Aberrant TGFbeta overproduction in glioblastoma and other high-grade gliomas has been reported, however, to date, none of these reports has systematically examined the components of TGFbeta signaling to gain a comprehensive view of TGFbeta activation in large cohorts of human glioma patients.

Methods: TGFbeta activation in mammalian cells leads to a transcriptional program that typically affects 5-10% of the genes in the genome. To systematically examine the status of TGFbeta activation in high-grade glial tumors, we compiled a gene set of transcriptional response to TGFbeta stimulation from tissue culture and in vivo animal studies. These genes were used to examine the status of TGFbeta activation in high-grade gliomas including a large cohort of glioblastomas. Unsupervised and supervised classification analysis was performed in two independent, publicly available glioma microarray datasets.

Results: Unsupervised and supervised classification using the TGFbeta-responsive gene list in two independent glial tumor gene expression data sets revealed various levels of TGFbeta activation in these tumors. Among glioblastomas, one of the most devastating human cancers, two subgroups were identified that showed distinct TGFbeta activation patterns as measured from transcriptional responses. Approximately 62% of glioblastoma samples analyzed showed strong TGFbeta activation, while the rest showed a weak TGFbeta transcriptional response.

Conclusion: Our findings suggest heterogeneous TGFbeta activation in glioblastomas, which may cause potential differences in responses to anti-TGFbeta therapies in these two distinct subgroups of glioblastomas patients.

Show MeSH
Related in: MedlinePlus