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From the core to beyond the margin: a genomic picture of glioblastoma intratumor heterogeneity.

Aubry M, de Tayrac M, Etcheverry A, Clavreul A, Saikali S, Menei P, Mosser J - Oncotarget (2015)

Bottom Line: At the genome level, we identified common GB copy number alterations and but a strong interindividual molecular heterogeneity.We provide a signature of key cancer-heterogeneity genes highly associated with the intratumor spatial gradient and show that it is enriched in genes with correlation between methylation and expression levels.Our study confirms that GBs are molecularly highly diverse and that a single tumor can harbor different transcriptional GB subtypes depending on its spatial architecture.

View Article: PubMed Central - PubMed

Affiliation: Université Rennes1, UEB, UMS 3480 Biosit, Faculté de Médecine, Rennes F-35043, France.

ABSTRACT
Glioblastoma (GB) is a highly invasive primary brain tumor that almost systematically recurs despite aggressive therapies. One of the most challenging problems in therapy of GB is its extremely complex and heterogeneous molecular biology. To explore this heterogeneity, we performed a genome-wide integrative screening of three molecular levels: genome, transcriptome, and methylome. We analyzed tumor biopsies obtained by neuro-navigation in four distinct areas for 10 GB patients (necrotic zone, tumor zone, interface, and peripheral brain zone). We classified samples and deciphered a key genes signature of intratumor heterogeneity by Principal Component Analysis and Weighted Gene Co-expression Network Analysis. At the genome level, we identified common GB copy number alterations and but a strong interindividual molecular heterogeneity. Transcriptome analysis highlighted a pronounced intratumor architecture reflecting the surgical sampling plan of the study and identified gene modules associated with hallmarks of cancer. We provide a signature of key cancer-heterogeneity genes highly associated with the intratumor spatial gradient and show that it is enriched in genes with correlation between methylation and expression levels. Our study confirms that GBs are molecularly highly diverse and that a single tumor can harbor different transcriptional GB subtypes depending on its spatial architecture.

No MeSH data available.


Related in: MedlinePlus

Transcriptome profilingA. Principal Component Analysis (PCA) performed on the expression data for 41000 probes without a priori selection. Dots represent samples and are colored according to the neuro-navigation sampling: green (PBZ: peripheral brain zone), yellow (I: interface zone), red (TZ: tumor zone), and blue (NZ: necrotic zone). Gray dots represent normal brain reference samples. Dendrogram of the hierarchical clustering based on principal components (HCPC) is represented above the Individual factor map. HCPC clusters are represented on the factorial plan by colored ellipses reflecting the sampling plan of the study ‘from the core of the tumor to beyond the margin’: HCPC #4 (blue), HCPC #3 (red), HCPC #2 (yellow), and HCPC #1 (green). Samples with unaltered array-CGH profile are circled in black. Black arrows designate samples with non-concordant histological analysis (PBZ: non-infiltrated parenchyma, iPBZ: infiltrated parenchyma, I: interface, TZ x%: presence of a corresponding percentage of tumor cells, and NZ x%: presence of a corresponding percentage of necrotic cells). B. Areas for biopsy in the four GB zones defined on preoperative MRI: necrotic zone (blue), tumor zone (red), interface (yellow), and peripheral brain zone (green).
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Figure 2: Transcriptome profilingA. Principal Component Analysis (PCA) performed on the expression data for 41000 probes without a priori selection. Dots represent samples and are colored according to the neuro-navigation sampling: green (PBZ: peripheral brain zone), yellow (I: interface zone), red (TZ: tumor zone), and blue (NZ: necrotic zone). Gray dots represent normal brain reference samples. Dendrogram of the hierarchical clustering based on principal components (HCPC) is represented above the Individual factor map. HCPC clusters are represented on the factorial plan by colored ellipses reflecting the sampling plan of the study ‘from the core of the tumor to beyond the margin’: HCPC #4 (blue), HCPC #3 (red), HCPC #2 (yellow), and HCPC #1 (green). Samples with unaltered array-CGH profile are circled in black. Black arrows designate samples with non-concordant histological analysis (PBZ: non-infiltrated parenchyma, iPBZ: infiltrated parenchyma, I: interface, TZ x%: presence of a corresponding percentage of tumor cells, and NZ x%: presence of a corresponding percentage of necrotic cells). B. Areas for biopsy in the four GB zones defined on preoperative MRI: necrotic zone (blue), tumor zone (red), interface (yellow), and peripheral brain zone (green).

Mentions: PCA and HCPC performed on the whole microarray dataset highlighted zone-specific profiles with pronounced intra-tumor architecture: from the core to beyond the margin (Figure 2A). This classification reflected the surgical sampling plan of the study (Figure 2B), highlighting that the transcriptome heterogeneity was much more important within tumors than between patients. This classification was confronted with histological examinations performed by the central committee of neuropathologists and copy number alteration analyses. Clusters were enriched as follow: tumor and necrotic biopsies (HCPC #1), tumor and interface biopsies (HCPC #2), infiltrated peripheral brain zone (HCPC #3), and, reference control brain biopsies with peripheral brain zone biopsies (HCPC #4). All samples in the latter cluster were identified as non-tumorous zones by neuropathologists and presented less than 1% of altered profile.


From the core to beyond the margin: a genomic picture of glioblastoma intratumor heterogeneity.

Aubry M, de Tayrac M, Etcheverry A, Clavreul A, Saikali S, Menei P, Mosser J - Oncotarget (2015)

Transcriptome profilingA. Principal Component Analysis (PCA) performed on the expression data for 41000 probes without a priori selection. Dots represent samples and are colored according to the neuro-navigation sampling: green (PBZ: peripheral brain zone), yellow (I: interface zone), red (TZ: tumor zone), and blue (NZ: necrotic zone). Gray dots represent normal brain reference samples. Dendrogram of the hierarchical clustering based on principal components (HCPC) is represented above the Individual factor map. HCPC clusters are represented on the factorial plan by colored ellipses reflecting the sampling plan of the study ‘from the core of the tumor to beyond the margin’: HCPC #4 (blue), HCPC #3 (red), HCPC #2 (yellow), and HCPC #1 (green). Samples with unaltered array-CGH profile are circled in black. Black arrows designate samples with non-concordant histological analysis (PBZ: non-infiltrated parenchyma, iPBZ: infiltrated parenchyma, I: interface, TZ x%: presence of a corresponding percentage of tumor cells, and NZ x%: presence of a corresponding percentage of necrotic cells). B. Areas for biopsy in the four GB zones defined on preoperative MRI: necrotic zone (blue), tumor zone (red), interface (yellow), and peripheral brain zone (green).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4494925&req=5

Figure 2: Transcriptome profilingA. Principal Component Analysis (PCA) performed on the expression data for 41000 probes without a priori selection. Dots represent samples and are colored according to the neuro-navigation sampling: green (PBZ: peripheral brain zone), yellow (I: interface zone), red (TZ: tumor zone), and blue (NZ: necrotic zone). Gray dots represent normal brain reference samples. Dendrogram of the hierarchical clustering based on principal components (HCPC) is represented above the Individual factor map. HCPC clusters are represented on the factorial plan by colored ellipses reflecting the sampling plan of the study ‘from the core of the tumor to beyond the margin’: HCPC #4 (blue), HCPC #3 (red), HCPC #2 (yellow), and HCPC #1 (green). Samples with unaltered array-CGH profile are circled in black. Black arrows designate samples with non-concordant histological analysis (PBZ: non-infiltrated parenchyma, iPBZ: infiltrated parenchyma, I: interface, TZ x%: presence of a corresponding percentage of tumor cells, and NZ x%: presence of a corresponding percentage of necrotic cells). B. Areas for biopsy in the four GB zones defined on preoperative MRI: necrotic zone (blue), tumor zone (red), interface (yellow), and peripheral brain zone (green).
Mentions: PCA and HCPC performed on the whole microarray dataset highlighted zone-specific profiles with pronounced intra-tumor architecture: from the core to beyond the margin (Figure 2A). This classification reflected the surgical sampling plan of the study (Figure 2B), highlighting that the transcriptome heterogeneity was much more important within tumors than between patients. This classification was confronted with histological examinations performed by the central committee of neuropathologists and copy number alteration analyses. Clusters were enriched as follow: tumor and necrotic biopsies (HCPC #1), tumor and interface biopsies (HCPC #2), infiltrated peripheral brain zone (HCPC #3), and, reference control brain biopsies with peripheral brain zone biopsies (HCPC #4). All samples in the latter cluster were identified as non-tumorous zones by neuropathologists and presented less than 1% of altered profile.

Bottom Line: At the genome level, we identified common GB copy number alterations and but a strong interindividual molecular heterogeneity.We provide a signature of key cancer-heterogeneity genes highly associated with the intratumor spatial gradient and show that it is enriched in genes with correlation between methylation and expression levels.Our study confirms that GBs are molecularly highly diverse and that a single tumor can harbor different transcriptional GB subtypes depending on its spatial architecture.

View Article: PubMed Central - PubMed

Affiliation: Université Rennes1, UEB, UMS 3480 Biosit, Faculté de Médecine, Rennes F-35043, France.

ABSTRACT
Glioblastoma (GB) is a highly invasive primary brain tumor that almost systematically recurs despite aggressive therapies. One of the most challenging problems in therapy of GB is its extremely complex and heterogeneous molecular biology. To explore this heterogeneity, we performed a genome-wide integrative screening of three molecular levels: genome, transcriptome, and methylome. We analyzed tumor biopsies obtained by neuro-navigation in four distinct areas for 10 GB patients (necrotic zone, tumor zone, interface, and peripheral brain zone). We classified samples and deciphered a key genes signature of intratumor heterogeneity by Principal Component Analysis and Weighted Gene Co-expression Network Analysis. At the genome level, we identified common GB copy number alterations and but a strong interindividual molecular heterogeneity. Transcriptome analysis highlighted a pronounced intratumor architecture reflecting the surgical sampling plan of the study and identified gene modules associated with hallmarks of cancer. We provide a signature of key cancer-heterogeneity genes highly associated with the intratumor spatial gradient and show that it is enriched in genes with correlation between methylation and expression levels. Our study confirms that GBs are molecularly highly diverse and that a single tumor can harbor different transcriptional GB subtypes depending on its spatial architecture.

No MeSH data available.


Related in: MedlinePlus