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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

Genome profilingA. Copy Number Alterations (type and percentage) detected in each sample (yellow: normal, green: loss, red: gain, black: amplification). Samples are grouped by patient. B. Samples classification based on CNAs profiles. PBZ: peripheral brain zone, I: interface, TZ: tumor zone, NZ: necrotic zone. C. Examples of patient specific and atypical alterations.
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Figure 1: Genome profilingA. Copy Number Alterations (type and percentage) detected in each sample (yellow: normal, green: loss, red: gain, black: amplification). Samples are grouped by patient. B. Samples classification based on CNAs profiles. PBZ: peripheral brain zone, I: interface, TZ: tumor zone, NZ: necrotic zone. C. Examples of patient specific and atypical alterations.

Mentions: For each biopsy, we classified CNAs as ‘normal’, ‘loss’, ‘gain’ or ‘amplification’ (Figure 1A). Samples with less than 1% of altered profile were considered potential normal brain zones or slightly infiltrated areas. For the other samples, we observed a strong heterogeneity in terms of percentage of altered profiles. This heterogeneity was mostly inter-individual as samples from the same patient showed a relatively stable percentage of altered profiles. FT02 and FT08 tumors were the most altered, with more than 30% of altered profiles and a high proportion of amplifications, whereas all FT05 samples presented only a small fraction of alterations (less than 10%). Samples classification based on CNAs profiles confirmed the distinction between altered and non-altered samples. Samples harboring more than 1% of altered profiles were grouped in one cluster separated from potential normal brain zones or slightly infiltrated areas (Figure 1B). This cluster highlighted very similar alteration profiles within samples originating from the same patient, particularly for FT04 and FT08. These similarities were associated with some patient specific and atypical alterations, on chromosome 12 for FT04 and on chromosome 15 for FT08 (Figure 1C).


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)

Genome profilingA. Copy Number Alterations (type and percentage) detected in each sample (yellow: normal, green: loss, red: gain, black: amplification). Samples are grouped by patient. B. Samples classification based on CNAs profiles. PBZ: peripheral brain zone, I: interface, TZ: tumor zone, NZ: necrotic zone. C. Examples of patient specific and atypical alterations.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: Genome profilingA. Copy Number Alterations (type and percentage) detected in each sample (yellow: normal, green: loss, red: gain, black: amplification). Samples are grouped by patient. B. Samples classification based on CNAs profiles. PBZ: peripheral brain zone, I: interface, TZ: tumor zone, NZ: necrotic zone. C. Examples of patient specific and atypical alterations.
Mentions: For each biopsy, we classified CNAs as ‘normal’, ‘loss’, ‘gain’ or ‘amplification’ (Figure 1A). Samples with less than 1% of altered profile were considered potential normal brain zones or slightly infiltrated areas. For the other samples, we observed a strong heterogeneity in terms of percentage of altered profiles. This heterogeneity was mostly inter-individual as samples from the same patient showed a relatively stable percentage of altered profiles. FT02 and FT08 tumors were the most altered, with more than 30% of altered profiles and a high proportion of amplifications, whereas all FT05 samples presented only a small fraction of alterations (less than 10%). Samples classification based on CNAs profiles confirmed the distinction between altered and non-altered samples. Samples harboring more than 1% of altered profiles were grouped in one cluster separated from potential normal brain zones or slightly infiltrated areas (Figure 1B). This cluster highlighted very similar alteration profiles within samples originating from the same patient, particularly for FT04 and FT08. These similarities were associated with some patient specific and atypical alterations, on chromosome 12 for FT04 and on chromosome 15 for FT08 (Figure 1C).

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