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Delineating the cytogenomic and epigenomic landscapes of glioma stem cell lines.

Baronchelli S, Bentivegna A, Redaelli S, Riva G, Butta V, Paoletta L, Isimbaldi G, Miozzo M, Tabano S, Daga A, Marubbi D, Cattaneo M, Biunno I, Dalprà L - PLoS ONE (2013)

Bottom Line: We found several canonical cytogenetic alterations associated with GBM and a common minimal deleted region (MDR) at 1p36.31, including CAMTA1 gene, a putative tumor suppressor gene, specific for the GSC population.Therefore, beyond the differences that can create apparent heterogeneity of alterations among GSC lines, there's a sort of selective force acting on them in order to converge towards the impairment of cell development and differentiation processes.This new overview could have a huge importance in therapy.

View Article: PubMed Central - PubMed

Affiliation: Department of Surgery and Translational Medicine, University of Milan-Bicocca, Monza, Italy.

ABSTRACT
Glioblastoma multiforme (GBM), the most common and malignant type of glioma, is characterized by a poor prognosis and the lack of an effective treatment, which are due to a small sub-population of cells with stem-like properties, termed glioma stem cells (GSCs). The term "multiforme" describes the histological features of this tumor, that is, the cellular and morphological heterogeneity. At the molecular level multiple layers of alterations may reflect this heterogeneity providing together the driving force for tumor initiation and development. In order to decipher the common "signature" of the ancestral GSC population, we examined six already characterized GSC lines evaluating their cytogenomic and epigenomic profiles through a multilevel approach (conventional cytogenetic, FISH, aCGH, MeDIP-Chip and functional bioinformatic analysis). We found several canonical cytogenetic alterations associated with GBM and a common minimal deleted region (MDR) at 1p36.31, including CAMTA1 gene, a putative tumor suppressor gene, specific for the GSC population. Therefore, on one hand our data confirm a role of driver mutations for copy number alterations (CNAs) included in the GBM genomic-signature (gain of chromosome 7- EGFR gene, loss of chromosome 13- RB1 gene, loss of chromosome 10-PTEN gene); on the other, it is not obvious that the new identified CNAs are passenger mutations, as they may be necessary for tumor progression specific for the individual patient. Through our approach, we were able to demonstrate that not only individual genes into a pathway can be perturbed through multiple mechanisms and at different levels, but also that different combinations of perturbed genes can incapacitate functional modules within a cellular networks. Therefore, beyond the differences that can create apparent heterogeneity of alterations among GSC lines, there's a sort of selective force acting on them in order to converge towards the impairment of cell development and differentiation processes. This new overview could have a huge importance in therapy.

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Methylation profiles.(A) Frequency of methylation and unmethylation of CGIs for each sample. The methylation status for each chromosome is reported and global genomic methylation percentages are displayed as the mean values of all chromosomes values. GSCs vs. CB660SP *p<0.05, **p<0.01, GSCs vs. GBM FFPE tissues §p<0.01, Chi-square test. Abbreviation: Met, methylation; Unmet, unmethylation. (B) Distribution of methylated and unmethylated CGIs among the different functional genomic regions.
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pone-0057462-g002: Methylation profiles.(A) Frequency of methylation and unmethylation of CGIs for each sample. The methylation status for each chromosome is reported and global genomic methylation percentages are displayed as the mean values of all chromosomes values. GSCs vs. CB660SP *p<0.05, **p<0.01, GSCs vs. GBM FFPE tissues §p<0.01, Chi-square test. Abbreviation: Met, methylation; Unmet, unmethylation. (B) Distribution of methylated and unmethylated CGIs among the different functional genomic regions.

Mentions: As DNA methylation is a key component of genome regulation in normal and cancer tissues, we evaluated the methylation status of three GSC lines. The array platform used in this study covers 27800 CGIs of the human genome [42] and all the data (percentages and frequencies) are referred to the total number of CGIs included in the array. Raw data were processed as described in the material and methods section and they were deposited in the NCBI's Gene Expression Omnibus [40] and are accessible through GEO Series accession number GSE41824. GSC data were compared with methylation levels of two foetal neural stem cell (NSC) lines, which were considered as matching normal control cells: CB660 derived from human foetal forebrain, and CB660SP isolated from human foetal spinal cord [34]. Additionally, data were compared with DNA methylation status of an equimolar pool of genomic DNA from GBM FFPE tissues and an equimolar amount of genomic DNA from peripheral blood lymphocytes of six healthy male donors (PBL pool), used an unrelated type of tissue. Results were plotted on a chart showing CGI methylation or unmethylation frequencies and mean genomic values were calculated (Figure 2A). Considering the global DNA methylation data, an overall CGI hypomethylation of GSC lines was noticed compared to foetal NSCs derived from the spinal cord, CB660SP (CGI methylation was lower than 50%). On the other hand, the global CGI methylation percentages of GSCs were similar to CGI methylation levels of foetal forebrain NSCs that showed half the CGI methylation content in comparison with CB660SP cells (35.4% vs. 61.1%, respectively). GBM FFPE tissues showed a CGI methylation level of 49%, which differs significantly from the G166 one, but not from those of GBM2 and G144 cell lines. PBL pool exhibited low level of methylation (26.3% of methylated CGIs); however, this percentage has already been reported in literature [43]. Going into deep the distribution of CGI methylation across the genomic regions was analyzed. Even if, the overall CGI methylation levels of GSCs, FFPE GBM tissues and CB660 forebrain NSCs were similar, almost a doubling in the CGI methylation percentages in promoter and divergent promoter regions was noticed in GBM2, G144 and GBM FFPE tissues related to CB660 cells (Figure 2B and Table S7).


Delineating the cytogenomic and epigenomic landscapes of glioma stem cell lines.

Baronchelli S, Bentivegna A, Redaelli S, Riva G, Butta V, Paoletta L, Isimbaldi G, Miozzo M, Tabano S, Daga A, Marubbi D, Cattaneo M, Biunno I, Dalprà L - PLoS ONE (2013)

Methylation profiles.(A) Frequency of methylation and unmethylation of CGIs for each sample. The methylation status for each chromosome is reported and global genomic methylation percentages are displayed as the mean values of all chromosomes values. GSCs vs. CB660SP *p<0.05, **p<0.01, GSCs vs. GBM FFPE tissues §p<0.01, Chi-square test. Abbreviation: Met, methylation; Unmet, unmethylation. (B) Distribution of methylated and unmethylated CGIs among the different functional genomic regions.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585345&req=5

pone-0057462-g002: Methylation profiles.(A) Frequency of methylation and unmethylation of CGIs for each sample. The methylation status for each chromosome is reported and global genomic methylation percentages are displayed as the mean values of all chromosomes values. GSCs vs. CB660SP *p<0.05, **p<0.01, GSCs vs. GBM FFPE tissues §p<0.01, Chi-square test. Abbreviation: Met, methylation; Unmet, unmethylation. (B) Distribution of methylated and unmethylated CGIs among the different functional genomic regions.
Mentions: As DNA methylation is a key component of genome regulation in normal and cancer tissues, we evaluated the methylation status of three GSC lines. The array platform used in this study covers 27800 CGIs of the human genome [42] and all the data (percentages and frequencies) are referred to the total number of CGIs included in the array. Raw data were processed as described in the material and methods section and they were deposited in the NCBI's Gene Expression Omnibus [40] and are accessible through GEO Series accession number GSE41824. GSC data were compared with methylation levels of two foetal neural stem cell (NSC) lines, which were considered as matching normal control cells: CB660 derived from human foetal forebrain, and CB660SP isolated from human foetal spinal cord [34]. Additionally, data were compared with DNA methylation status of an equimolar pool of genomic DNA from GBM FFPE tissues and an equimolar amount of genomic DNA from peripheral blood lymphocytes of six healthy male donors (PBL pool), used an unrelated type of tissue. Results were plotted on a chart showing CGI methylation or unmethylation frequencies and mean genomic values were calculated (Figure 2A). Considering the global DNA methylation data, an overall CGI hypomethylation of GSC lines was noticed compared to foetal NSCs derived from the spinal cord, CB660SP (CGI methylation was lower than 50%). On the other hand, the global CGI methylation percentages of GSCs were similar to CGI methylation levels of foetal forebrain NSCs that showed half the CGI methylation content in comparison with CB660SP cells (35.4% vs. 61.1%, respectively). GBM FFPE tissues showed a CGI methylation level of 49%, which differs significantly from the G166 one, but not from those of GBM2 and G144 cell lines. PBL pool exhibited low level of methylation (26.3% of methylated CGIs); however, this percentage has already been reported in literature [43]. Going into deep the distribution of CGI methylation across the genomic regions was analyzed. Even if, the overall CGI methylation levels of GSCs, FFPE GBM tissues and CB660 forebrain NSCs were similar, almost a doubling in the CGI methylation percentages in promoter and divergent promoter regions was noticed in GBM2, G144 and GBM FFPE tissues related to CB660 cells (Figure 2B and Table S7).

Bottom Line: We found several canonical cytogenetic alterations associated with GBM and a common minimal deleted region (MDR) at 1p36.31, including CAMTA1 gene, a putative tumor suppressor gene, specific for the GSC population.Therefore, beyond the differences that can create apparent heterogeneity of alterations among GSC lines, there's a sort of selective force acting on them in order to converge towards the impairment of cell development and differentiation processes.This new overview could have a huge importance in therapy.

View Article: PubMed Central - PubMed

Affiliation: Department of Surgery and Translational Medicine, University of Milan-Bicocca, Monza, Italy.

ABSTRACT
Glioblastoma multiforme (GBM), the most common and malignant type of glioma, is characterized by a poor prognosis and the lack of an effective treatment, which are due to a small sub-population of cells with stem-like properties, termed glioma stem cells (GSCs). The term "multiforme" describes the histological features of this tumor, that is, the cellular and morphological heterogeneity. At the molecular level multiple layers of alterations may reflect this heterogeneity providing together the driving force for tumor initiation and development. In order to decipher the common "signature" of the ancestral GSC population, we examined six already characterized GSC lines evaluating their cytogenomic and epigenomic profiles through a multilevel approach (conventional cytogenetic, FISH, aCGH, MeDIP-Chip and functional bioinformatic analysis). We found several canonical cytogenetic alterations associated with GBM and a common minimal deleted region (MDR) at 1p36.31, including CAMTA1 gene, a putative tumor suppressor gene, specific for the GSC population. Therefore, on one hand our data confirm a role of driver mutations for copy number alterations (CNAs) included in the GBM genomic-signature (gain of chromosome 7- EGFR gene, loss of chromosome 13- RB1 gene, loss of chromosome 10-PTEN gene); on the other, it is not obvious that the new identified CNAs are passenger mutations, as they may be necessary for tumor progression specific for the individual patient. Through our approach, we were able to demonstrate that not only individual genes into a pathway can be perturbed through multiple mechanisms and at different levels, but also that different combinations of perturbed genes can incapacitate functional modules within a cellular networks. Therefore, beyond the differences that can create apparent heterogeneity of alterations among GSC lines, there's a sort of selective force acting on them in order to converge towards the impairment of cell development and differentiation processes. This new overview could have a huge importance in therapy.

Show MeSH
Related in: MedlinePlus