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Integrated genomic and gene expression profiling identifies two major genomic circuits in urothelial carcinoma.

Lindgren D, Sjödahl G, Lauss M, Staaf J, Chebil G, Lövgren K, Gudjonsson S, Liedberg F, Patschan O, Månsson W, Fernö M, Höglund M - PLoS ONE (2012)

Bottom Line: Our data also suggest a possible RAS/RAF circuit.The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype.Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Pathology, Lund University, Malmö, Sweden.

ABSTRACT
Similar to other malignancies, urothelial carcinoma (UC) is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21), and BCL2L1 (20q11). We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.

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Genomic complexity is associated with UC gene expression subtypes.A) Hierarchical cluster analysis (HCA) on gene expression data segregated the tumors into five clusters, HC1 to HC5. Samples within each HCA group are ordered according to their relative FGFR3 expression (high expression left, low expression right). For each individual tumor, molecular signature (MS) type, pathological grade, stage, nFGA, fBAC, and TP53/MDM2 status is indicated. The relative expression levels for genes within the CIN signature are indicated by a heatmap below (green, low expression; red high expression). B) Boxplot illustrating the number of FGAs (nFGA) and frequency of genomic imbalances (fBAC) for samples within each HCA group. C) Boxplot of nFGA (left) and fBAC (right) for tumor samples when grouped on TP53/MDM2 status and MS type. P-values obtained by Wilcoxon statistics. n.s., not significant. D) Boxplot illustrating increased CIN score for samples with increased nFGAs (left) and fBAC (right). P-values obtained by ANOVA. E and F) Disease specific survival (DSS) analysis with tumors grouped according to nFGAs (0 vs ≥1 FGA) and CIN pathway score (above or below median), respectively.
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pone-0038863-g003: Genomic complexity is associated with UC gene expression subtypes.A) Hierarchical cluster analysis (HCA) on gene expression data segregated the tumors into five clusters, HC1 to HC5. Samples within each HCA group are ordered according to their relative FGFR3 expression (high expression left, low expression right). For each individual tumor, molecular signature (MS) type, pathological grade, stage, nFGA, fBAC, and TP53/MDM2 status is indicated. The relative expression levels for genes within the CIN signature are indicated by a heatmap below (green, low expression; red high expression). B) Boxplot illustrating the number of FGAs (nFGA) and frequency of genomic imbalances (fBAC) for samples within each HCA group. C) Boxplot of nFGA (left) and fBAC (right) for tumor samples when grouped on TP53/MDM2 status and MS type. P-values obtained by Wilcoxon statistics. n.s., not significant. D) Boxplot illustrating increased CIN score for samples with increased nFGAs (left) and fBAC (right). P-values obtained by ANOVA. E and F) Disease specific survival (DSS) analysis with tumors grouped according to nFGAs (0 vs ≥1 FGA) and CIN pathway score (above or below median), respectively.

Mentions: We next aimed to investigate how genomic alterations are related with gene expression subgroups of UCs. We therefore stratified tumors into subgroups based on global gene expression data using hierarchical cluster analysis (HCA; Figure S3A). Two major clusters of tumors were identified, one dominated by G1/G2 tumors, split into two subgroups (HC1 and HC2), and a second, dominated by G3 tumors segregating into three subgroups (HC3, HC4, and HC5). As expected, the two largest HCA branches corresponded to the two main molecular subtypes (MS) previously described for bladder cancer [15]; MS1 tumors were confined to HC1 and HC2 whereas HC3, HC4, and HC5 were of the MS2 type (Figure 3A).


Integrated genomic and gene expression profiling identifies two major genomic circuits in urothelial carcinoma.

Lindgren D, Sjödahl G, Lauss M, Staaf J, Chebil G, Lövgren K, Gudjonsson S, Liedberg F, Patschan O, Månsson W, Fernö M, Höglund M - PLoS ONE (2012)

Genomic complexity is associated with UC gene expression subtypes.A) Hierarchical cluster analysis (HCA) on gene expression data segregated the tumors into five clusters, HC1 to HC5. Samples within each HCA group are ordered according to their relative FGFR3 expression (high expression left, low expression right). For each individual tumor, molecular signature (MS) type, pathological grade, stage, nFGA, fBAC, and TP53/MDM2 status is indicated. The relative expression levels for genes within the CIN signature are indicated by a heatmap below (green, low expression; red high expression). B) Boxplot illustrating the number of FGAs (nFGA) and frequency of genomic imbalances (fBAC) for samples within each HCA group. C) Boxplot of nFGA (left) and fBAC (right) for tumor samples when grouped on TP53/MDM2 status and MS type. P-values obtained by Wilcoxon statistics. n.s., not significant. D) Boxplot illustrating increased CIN score for samples with increased nFGAs (left) and fBAC (right). P-values obtained by ANOVA. E and F) Disease specific survival (DSS) analysis with tumors grouped according to nFGAs (0 vs ≥1 FGA) and CIN pathway score (above or below median), respectively.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3369837&req=5

pone-0038863-g003: Genomic complexity is associated with UC gene expression subtypes.A) Hierarchical cluster analysis (HCA) on gene expression data segregated the tumors into five clusters, HC1 to HC5. Samples within each HCA group are ordered according to their relative FGFR3 expression (high expression left, low expression right). For each individual tumor, molecular signature (MS) type, pathological grade, stage, nFGA, fBAC, and TP53/MDM2 status is indicated. The relative expression levels for genes within the CIN signature are indicated by a heatmap below (green, low expression; red high expression). B) Boxplot illustrating the number of FGAs (nFGA) and frequency of genomic imbalances (fBAC) for samples within each HCA group. C) Boxplot of nFGA (left) and fBAC (right) for tumor samples when grouped on TP53/MDM2 status and MS type. P-values obtained by Wilcoxon statistics. n.s., not significant. D) Boxplot illustrating increased CIN score for samples with increased nFGAs (left) and fBAC (right). P-values obtained by ANOVA. E and F) Disease specific survival (DSS) analysis with tumors grouped according to nFGAs (0 vs ≥1 FGA) and CIN pathway score (above or below median), respectively.
Mentions: We next aimed to investigate how genomic alterations are related with gene expression subgroups of UCs. We therefore stratified tumors into subgroups based on global gene expression data using hierarchical cluster analysis (HCA; Figure S3A). Two major clusters of tumors were identified, one dominated by G1/G2 tumors, split into two subgroups (HC1 and HC2), and a second, dominated by G3 tumors segregating into three subgroups (HC3, HC4, and HC5). As expected, the two largest HCA branches corresponded to the two main molecular subtypes (MS) previously described for bladder cancer [15]; MS1 tumors were confined to HC1 and HC2 whereas HC3, HC4, and HC5 were of the MS2 type (Figure 3A).

Bottom Line: Our data also suggest a possible RAS/RAF circuit.The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype.Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Pathology, Lund University, Malmö, Sweden.

ABSTRACT
Similar to other malignancies, urothelial carcinoma (UC) is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21), and BCL2L1 (20q11). We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.

Show MeSH
Related in: MedlinePlus