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A systematic comparison of copy number alterations in four types of female cancer

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ABSTRACT

Background: Detection and localization of genomic alterations and breakpoints are crucial in cancer research. The purpose of this study was to investigate, in a methodological and biological perspective, different female, hormone-dependent cancers to identify common and diverse DNA aberrations, genes, and pathways.

Methods: In this work, we analyzed tissue samples from patients with breast (n = 112), ovarian (n = 74), endometrial (n = 84), or cervical (n = 76) cancer. To identify genomic aberrations, the Circular Binary Segmentation (CBS) and Piecewise Constant Fitting (PCF) algorithms were used and segmentation thresholds optimized. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was applied to the segmented data to identify significantly altered regions and the associated genes were analyzed by Ingenuity Pathway Analysis (IPA) to detect over-represented pathways and functions within the identified gene sets.

Results and discussion: Analyses of high-resolution copy number alterations in four different female cancer types are presented. For appropriately adjusted segmentation parameters the two segmentation algorithms CBS and PCF performed similarly. We identified one region at 8q24.3 with focal aberrations that was altered at significant frequency across all four cancer types. Considering both, broad regions and focal peaks, three additional regions with gains at significant frequency were revealed at 1p21.1, 8p22, and 13q21.33, respectively. Several of these events involve known cancer-related genes, like PPP2R2A, PSCA, PTP4A3, and PTK2. In the female reproductive system (ovarian, endometrial, and cervix [OEC]), we discovered three common events: copy number gains at 5p15.33 and 15q11.2, further a copy number loss at 8p21.2. Interestingly, as many as 75% of the aberrations (75% amplifications and 86% deletions) identified by GISTIC were specific for just one cancer type and represented distinct molecular pathways.

Conclusions: Our results disclose that some prominent copy number changes are shared in the four examined female, hormone-dependent cancer whereas others are definitive to specific cancer types.

Electronic supplementary material: The online version of this article (doi:10.1186/s12885-016-2899-4) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus

Overlap between gene sets of four female cancer– Top biological functions. The Venn diagram displays joint genes identified by both, CBS and PCF algorithms located within the regions identified by GISTIC. The total number of genes for each data set is presented on the top right panel. Top biological functions and top canonical pathways for each region of the overlapped cancers are stated
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Fig4: Overlap between gene sets of four female cancer– Top biological functions. The Venn diagram displays joint genes identified by both, CBS and PCF algorithms located within the regions identified by GISTIC. The total number of genes for each data set is presented on the top right panel. Top biological functions and top canonical pathways for each region of the overlapped cancers are stated

Mentions: Genes classified by both algorithms and located within the broad or focal peak regions identified by GISTIC (Additional file 13: Table S8) were extracted and the deregulated genes for each cancer type are reported. We obtained 3106 genes for breast, 3146 genes for ovarian, 2070 genes for endometrial, and 2058 genes for cervical cancer. The degree of overlap between these lists is visualized in a Venn diagram (Fig. 4). The number of identified common genes was 235 for endometrial and ovarian (EO), 259 for breast and endometrial (BE), 285 for breast and cervix (BC), 87 for ovarian and cervix (OC), 164 for endometrial and cervix (EC), and 461 for breast and ovarian (BO) cancers. Further, shared genes among three cancer types, we found 128 for endometrial, ovarian, and cervix (EOC), 106 for breast, ovarian, and cervix (BOC), 50 for breast, endometrial, and cervix (BEC), and 20 for breast, ovarian, and endometrial (BOE) cancers. Two genes, actin-organizing protein KLHL1 at 13q21.33 and COL11A1 (collagen, type XI, alpha 1) at 1p21.1 were detected as joint deletions in all four cancer types (breast, ovarian, endometrial, and cervical, BOEC) (Fig. 4 and Additional file 14: Figure S5).Fig. 4


A systematic comparison of copy number alterations in four types of female cancer
Overlap between gene sets of four female cancer– Top biological functions. The Venn diagram displays joint genes identified by both, CBS and PCF algorithms located within the regions identified by GISTIC. The total number of genes for each data set is presented on the top right panel. Top biological functions and top canonical pathways for each region of the overlapped cancers are stated
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5120489&req=5

Fig4: Overlap between gene sets of four female cancer– Top biological functions. The Venn diagram displays joint genes identified by both, CBS and PCF algorithms located within the regions identified by GISTIC. The total number of genes for each data set is presented on the top right panel. Top biological functions and top canonical pathways for each region of the overlapped cancers are stated
Mentions: Genes classified by both algorithms and located within the broad or focal peak regions identified by GISTIC (Additional file 13: Table S8) were extracted and the deregulated genes for each cancer type are reported. We obtained 3106 genes for breast, 3146 genes for ovarian, 2070 genes for endometrial, and 2058 genes for cervical cancer. The degree of overlap between these lists is visualized in a Venn diagram (Fig. 4). The number of identified common genes was 235 for endometrial and ovarian (EO), 259 for breast and endometrial (BE), 285 for breast and cervix (BC), 87 for ovarian and cervix (OC), 164 for endometrial and cervix (EC), and 461 for breast and ovarian (BO) cancers. Further, shared genes among three cancer types, we found 128 for endometrial, ovarian, and cervix (EOC), 106 for breast, ovarian, and cervix (BOC), 50 for breast, endometrial, and cervix (BEC), and 20 for breast, ovarian, and endometrial (BOE) cancers. Two genes, actin-organizing protein KLHL1 at 13q21.33 and COL11A1 (collagen, type XI, alpha 1) at 1p21.1 were detected as joint deletions in all four cancer types (breast, ovarian, endometrial, and cervical, BOEC) (Fig. 4 and Additional file 14: Figure S5).Fig. 4

View Article: PubMed Central - PubMed

ABSTRACT

Background: Detection and localization of genomic alterations and breakpoints are crucial in cancer research. The purpose of this study was to investigate, in a methodological and biological perspective, different female, hormone-dependent cancers to identify common and diverse DNA aberrations, genes, and pathways.

Methods: In this work, we analyzed tissue samples from patients with breast (n = 112), ovarian (n = 74), endometrial (n = 84), or cervical (n = 76) cancer. To identify genomic aberrations, the Circular Binary Segmentation (CBS) and Piecewise Constant Fitting (PCF) algorithms were used and segmentation thresholds optimized. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was applied to the segmented data to identify significantly altered regions and the associated genes were analyzed by Ingenuity Pathway Analysis (IPA) to detect over-represented pathways and functions within the identified gene sets.

Results and discussion: Analyses of high-resolution copy number alterations in four different female cancer types are presented. For appropriately adjusted segmentation parameters the two segmentation algorithms CBS and PCF performed similarly. We identified one region at 8q24.3 with focal aberrations that was altered at significant frequency across all four cancer types. Considering both, broad regions and focal peaks, three additional regions with gains at significant frequency were revealed at 1p21.1, 8p22, and 13q21.33, respectively. Several of these events involve known cancer-related genes, like PPP2R2A, PSCA, PTP4A3, and PTK2. In the female reproductive system (ovarian, endometrial, and cervix [OEC]), we discovered three common events: copy number gains at 5p15.33 and 15q11.2, further a copy number loss at 8p21.2. Interestingly, as many as 75% of the aberrations (75% amplifications and 86% deletions) identified by GISTIC were specific for just one cancer type and represented distinct molecular pathways.

Conclusions: Our results disclose that some prominent copy number changes are shared in the four examined female, hormone-dependent cancer whereas others are definitive to specific cancer types.

Electronic supplementary material: The online version of this article (doi:10.1186/s12885-016-2899-4) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus