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. 2012;7(11):e47839.
doi: 10.1371/journal.pone.0047839. Epub 2012 Nov 6.

G-cimp status prediction of glioblastoma samples using mRNA expression data

Mehmet Baysan  1 , Serdar Bozdag, Margaret C Cam, Svetlana Kotliarova, Susie Ahn, Jennifer Walling, Jonathan K Killian, Holly Stevenson, Paul Meltzer, Howard A Fine
Affiliations

G-cimp status prediction of glioblastoma samples using mRNA expression data

Mehmet Baysan et al. PLoS One. 2012.

Abstract

Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. PCA plot for TCGA samples based on methylation data (Blue: G-CIMP positive, red: G-CIMP negative samples).
1509 methylation sites (std. dev. >0.2) have been shown.
Figure 2
Figure 2. PCA plot of TCGA and NOB samples after batch effect removal.
As expected, normal brain samples are clustered together, and TCGA and NOB samples are not separated. We used high variation 1482 probe sets (std. dev. >1) in combined data set.
Figure 3
Figure 3. Data processing flowchart for predicting G-CIMP calls of NOB samples from TCGA gene expression data.
Figure 4
Figure 4. Box-Whisker plot of age of NOB and TCGA G-CIMP positive and G-CIMP negative samples.
Limits of box and whiskers plot are 10%, 25%, 50%, 75% and 90%.
Figure 5
Figure 5. Kaplan-Meier survival plot for NOB G-CIMP+ (n = 7), NOB G-CIMP− (n = 123), TCGA G-CIMP+ (n = 30) and TCGA G-CIMP− (n = 361) samples.
Figure 6
Figure 6. PCA plot of TCGA and NOB samples in combined methylation data set.
This data set includes 394 samples and 1438 methylation sites.
Figure 7
Figure 7. PCA plot of TCGA and NOB samples in combined methylation data set.
Samples are labeled by histopathology check results.
See this image and copyright information in PMC

References

    1. Li A, Walling J, Ahn S, Kotliarov Y, Su Q, et al. (2009) Unsupervised analysis of transcriptomic profiles reveals six glioma subtypes. Cancer research 69: 2091. - PMC - PubMed
    1. Phillips HS, Kharbanda S, Chen R, Forrest WF, Soriano RH, et al. (2006) Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer cell 9: 157–173. - PubMed
    1. Verhaak RGW, Hoadley KA, Purdom E, Wang V, Qi Y, et al. (2010) Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer cell 17: 98–110. - PMC - PubMed
    1. Huse JT, Phillips HS, Brennan CW (2011) Molecular subclassification of diffuse gliomas: seeing order in the chaos. Glia. - PubMed
    1. Malzkorn B, Wolter M, Riemenschneider MJ, Reifenberger G (2011) Unraveling the Glioma Epigenome' ÄîFrom Molecular Mechanisms to Novel Biomarkers and Therapeutic Targets. Brain Pathology 21: 619–632. - PMC - PubMed

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