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High-resolution comparative genomic hybridization of inflammatory breast cancer and identification of candidate genes.

Bekhouche I, Finetti P, Adelaïde J, Ferrari A, Tarpin C, Charafe-Jauffret E, Charpin C, Houvenaeghel G, Jacquemier J, Bidaut G, Birnbaum D, Viens P, Chaffanet M, Bertucci F - PLoS ONE (2011)

Bottom Line: We compared the molecular portraits of 63 IBC and 134 non-IBC (nIBC) clinical samples.Consistent with the hyperproliferative and invasive phenotype of IBC these genes are notably involved in protein translation, cell cycle, RNA processing and transcription, metabolism, and cell migration.Our results suggest a higher genomic instability of IBC.

View Article: PubMed Central - PubMed

Affiliation: Marseille Cancer Research Center (CRCM), UMR891 Inserm, Institut Paoli-Calmettes, Department of Molecular Oncology, Marseille, France.

ABSTRACT

Background: Inflammatory breast cancer (IBC) is an aggressive form of BC poorly defined at the molecular level. We compared the molecular portraits of 63 IBC and 134 non-IBC (nIBC) clinical samples.

Methodology/findings: Genomic imbalances of 49 IBCs and 124 nIBCs were determined using high-resolution array-comparative genomic hybridization, and mRNA expression profiles of 197 samples using whole-genome microarrays. Genomic profiles of IBCs were as heterogeneous as those of nIBCs, and globally relatively close. However, IBCs showed more frequent "complex" patterns and a higher percentage of genes with CNAs per sample. The number of altered regions was similar in both types, although some regions were altered more frequently and/or with higher amplitude in IBCs. Many genes were similarly altered in both types; however, more genes displayed recurrent amplifications in IBCs. The percentage of genes whose mRNA expression correlated with CNAs was similar in both types for the gained genes, but ∼7-fold lower in IBCs for the lost genes. Integrated analysis identified 24 potential candidate IBC-specific genes. Their combined expression accurately distinguished IBCs and nIBCS in an independent validation set, and retained an independent prognostic value in a series of 1,781 nIBCs, reinforcing the hypothesis for a link with IBC aggressiveness. Consistent with the hyperproliferative and invasive phenotype of IBC these genes are notably involved in protein translation, cell cycle, RNA processing and transcription, metabolism, and cell migration.

Conclusions: Our results suggest a higher genomic instability of IBC. We established the first repertory of DNA copy number alterations in this tumor, and provided a list of genes that may contribute to its aggressiveness and represent novel therapeutic targets.

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Related in: MedlinePlus

aCGH portrait of breast cancers.A) Frequency plots of genome CNA. Frequencies (horizontal axis, from 0 to 100%) are plotted as a function of chromosome location (from 1pter to the top, to 22qter to the bottom), for all breast cancer samples (Global, N = 173), for IBCs (N = 49), and for nIBCs (N = 124). Horizontal lines indicate chromosome boundaries. Positive and negative values indicate frequencies of tumors showing copy number increase and decrease, respectively, with gains (in red) and losses (in green). B) Unsupervised hierarchical clustering of genome CNAs measured for 173 breast cancers on 225,388 probes (without X and Y). Red indicates increased DNA copy number gain and green indicates decreased copy number. The bars to the left indicate chromosome locations ordered like in A). The vertical orange lines define the three significant tumor clusters (I, II and III). Above the dendrogram, p indicates the Approximately Unbiased (AU) p-values defined by Pvclust. Below the dendrogram, the row indicates the clinical type (green for nIBC, and orange for IBC).
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pone-0016950-g001: aCGH portrait of breast cancers.A) Frequency plots of genome CNA. Frequencies (horizontal axis, from 0 to 100%) are plotted as a function of chromosome location (from 1pter to the top, to 22qter to the bottom), for all breast cancer samples (Global, N = 173), for IBCs (N = 49), and for nIBCs (N = 124). Horizontal lines indicate chromosome boundaries. Positive and negative values indicate frequencies of tumors showing copy number increase and decrease, respectively, with gains (in red) and losses (in green). B) Unsupervised hierarchical clustering of genome CNAs measured for 173 breast cancers on 225,388 probes (without X and Y). Red indicates increased DNA copy number gain and green indicates decreased copy number. The bars to the left indicate chromosome locations ordered like in A). The vertical orange lines define the three significant tumor clusters (I, II and III). Above the dendrogram, p indicates the Approximately Unbiased (AU) p-values defined by Pvclust. Below the dendrogram, the row indicates the clinical type (green for nIBC, and orange for IBC).

Mentions: We first describe the results on the whole set of tumors before addressing the specific question of IBC. High-resolution aCGH was performed on 173 samples, including 49 IBCs and 124 nIBCs. Figure 1A (left) shows the frequency of low level CNAs in all samples. As previously reported [37], [44], the three most frequently gained regions were on 1q, 8q and 17q chromosomal arms, whereas the regions frequently lost were on 8p, 11q and 16q. The median percentage of probe sets displaying a CNA in a sample was 3.5%, with a great variability between samples (range, 0.03–44%). As expected, this percentage was higher in grade 3 tumors (2.1%) than in grade 1 tumors (0.5%; p = 0.005; Mann-Whitney test).


High-resolution comparative genomic hybridization of inflammatory breast cancer and identification of candidate genes.

Bekhouche I, Finetti P, Adelaïde J, Ferrari A, Tarpin C, Charafe-Jauffret E, Charpin C, Houvenaeghel G, Jacquemier J, Bidaut G, Birnbaum D, Viens P, Chaffanet M, Bertucci F - PLoS ONE (2011)

aCGH portrait of breast cancers.A) Frequency plots of genome CNA. Frequencies (horizontal axis, from 0 to 100%) are plotted as a function of chromosome location (from 1pter to the top, to 22qter to the bottom), for all breast cancer samples (Global, N = 173), for IBCs (N = 49), and for nIBCs (N = 124). Horizontal lines indicate chromosome boundaries. Positive and negative values indicate frequencies of tumors showing copy number increase and decrease, respectively, with gains (in red) and losses (in green). B) Unsupervised hierarchical clustering of genome CNAs measured for 173 breast cancers on 225,388 probes (without X and Y). Red indicates increased DNA copy number gain and green indicates decreased copy number. The bars to the left indicate chromosome locations ordered like in A). The vertical orange lines define the three significant tumor clusters (I, II and III). Above the dendrogram, p indicates the Approximately Unbiased (AU) p-values defined by Pvclust. Below the dendrogram, the row indicates the clinical type (green for nIBC, and orange for IBC).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3037286&req=5

pone-0016950-g001: aCGH portrait of breast cancers.A) Frequency plots of genome CNA. Frequencies (horizontal axis, from 0 to 100%) are plotted as a function of chromosome location (from 1pter to the top, to 22qter to the bottom), for all breast cancer samples (Global, N = 173), for IBCs (N = 49), and for nIBCs (N = 124). Horizontal lines indicate chromosome boundaries. Positive and negative values indicate frequencies of tumors showing copy number increase and decrease, respectively, with gains (in red) and losses (in green). B) Unsupervised hierarchical clustering of genome CNAs measured for 173 breast cancers on 225,388 probes (without X and Y). Red indicates increased DNA copy number gain and green indicates decreased copy number. The bars to the left indicate chromosome locations ordered like in A). The vertical orange lines define the three significant tumor clusters (I, II and III). Above the dendrogram, p indicates the Approximately Unbiased (AU) p-values defined by Pvclust. Below the dendrogram, the row indicates the clinical type (green for nIBC, and orange for IBC).
Mentions: We first describe the results on the whole set of tumors before addressing the specific question of IBC. High-resolution aCGH was performed on 173 samples, including 49 IBCs and 124 nIBCs. Figure 1A (left) shows the frequency of low level CNAs in all samples. As previously reported [37], [44], the three most frequently gained regions were on 1q, 8q and 17q chromosomal arms, whereas the regions frequently lost were on 8p, 11q and 16q. The median percentage of probe sets displaying a CNA in a sample was 3.5%, with a great variability between samples (range, 0.03–44%). As expected, this percentage was higher in grade 3 tumors (2.1%) than in grade 1 tumors (0.5%; p = 0.005; Mann-Whitney test).

Bottom Line: We compared the molecular portraits of 63 IBC and 134 non-IBC (nIBC) clinical samples.Consistent with the hyperproliferative and invasive phenotype of IBC these genes are notably involved in protein translation, cell cycle, RNA processing and transcription, metabolism, and cell migration.Our results suggest a higher genomic instability of IBC.

View Article: PubMed Central - PubMed

Affiliation: Marseille Cancer Research Center (CRCM), UMR891 Inserm, Institut Paoli-Calmettes, Department of Molecular Oncology, Marseille, France.

ABSTRACT

Background: Inflammatory breast cancer (IBC) is an aggressive form of BC poorly defined at the molecular level. We compared the molecular portraits of 63 IBC and 134 non-IBC (nIBC) clinical samples.

Methodology/findings: Genomic imbalances of 49 IBCs and 124 nIBCs were determined using high-resolution array-comparative genomic hybridization, and mRNA expression profiles of 197 samples using whole-genome microarrays. Genomic profiles of IBCs were as heterogeneous as those of nIBCs, and globally relatively close. However, IBCs showed more frequent "complex" patterns and a higher percentage of genes with CNAs per sample. The number of altered regions was similar in both types, although some regions were altered more frequently and/or with higher amplitude in IBCs. Many genes were similarly altered in both types; however, more genes displayed recurrent amplifications in IBCs. The percentage of genes whose mRNA expression correlated with CNAs was similar in both types for the gained genes, but ∼7-fold lower in IBCs for the lost genes. Integrated analysis identified 24 potential candidate IBC-specific genes. Their combined expression accurately distinguished IBCs and nIBCS in an independent validation set, and retained an independent prognostic value in a series of 1,781 nIBCs, reinforcing the hypothesis for a link with IBC aggressiveness. Consistent with the hyperproliferative and invasive phenotype of IBC these genes are notably involved in protein translation, cell cycle, RNA processing and transcription, metabolism, and cell migration.

Conclusions: Our results suggest a higher genomic instability of IBC. We established the first repertory of DNA copy number alterations in this tumor, and provided a list of genes that may contribute to its aggressiveness and represent novel therapeutic targets.

Show MeSH
Related in: MedlinePlus