Genome Wide DNA Copy Number Analysis of Serous Type Ovarian Carcinomas Identifies Genetic Markers Predictive of Clinical Outcome

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups

Genome wide DNA copy number analysis of serous type ovarian carcinomas identifies genetic markers predictive of clinical outcome.

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups

Unsupervised hierarchical clustering of CNAs identifies distinct patient subgroups.

<p><b>A</b>) Unsupervised hierarchical clustering of raw log2 ratios derived from 72 serous type ovarian cancers. Copy number values are color coded as follows: blue (loss), white (normal) and magenta (gain). The pattern of dendrogram suggests two major genomic subgroups within the grade 3 tumors. <b>B</b>) PFS Kaplan-Meier plot for the two subgroups. <b>C</b>) Comparison of clinical characteristics between the patient subgroups. Histology: red = serous; Grade: orange = grade 2, yellow = grade 3; Stage: red = Ic, blue = II, green = IIc, yellow = IIIa, orange = IIIb, brown = IIIc, pink = IV, dark gray = IVa; Status: red = evidence of disease, blue = no evidence of disease; Outcome: green = complete remission, orange = progression, yellow = partial remission, brown = lost to follow up, pink = benign; 6 month progression: red = yes, blue = no, green = P (progression); Recurrence: brown = yes, orange = persistent disease, yellow = no; Platinum response: red = sensitive, black = resistant; Drug: blue = yes, light blue = no; Ascites: red = yes, black = no; Chemo: orange = yes, brown = no; Radiation: red = yes, black = no; General: white = n/a and/or blank.</p

Patient characterisitics.

<p>Patient characterisitics.</p

GISTIC analysis of patient subgroups.

<p><b>A–B</b>) Cluster 1; <b>C–D</b>) Cluster 2 amplification and deletion peaks defined by GISTIC in two patient subgroups show clear difference in the location of peaks. Green stars indicate major differences between the two subgroups. Probes from these regions were used to build the model for training.</p

A–E.

<p>Representative aCGH profiles of 5 ovarian carcinomas. Log2 ratios (y axis) are plotted along the chromosomes (x axis). Each tumor showing many CNAs including gain and loss of entire chromosome and/or chromosome arms, interstitial deletions, and high-level amplifications (indicated in red arrows). Some tumors had more than 10 high-level amplifications. <b>F.</b> Genomic profiles of 72 primary ovarian carcinomas generated by oligonucleotide array CGH. Each column in the left panel represents a tumor sample and rows represent losses and gains of DNA sequences along the length of chromosomes 1 through X as determined by the segmentation analysis of normalized log2 ratios. The color scale ranges from blue (loss) through white (two copies) to red (gain). The right panel indicates the frequencies of gain and loss of oligonucleotide probes on a probe-by-probe basis for all autosomes and the X chromosome. The color scale ranges from white (no changes) to blue (frequent changes). Amplification of 3q26.2 and 8q24.12 including the <i>EVI1</i> and <i>MYC</i> oncogenes and deletion of 16q24.2 and 22q13.33 were the most frequent alterations observed in 75% and 78% of the ovarian carcinomas respectively. <b>G.</b> Overall frequency of CNAs in 72 high-grade serous ovarian carcinomas. <b>H and I.</b> GISTIC analysis of copy number gains (<b>H</b>) and losses (<b>I</b>) in ovarian carcinomas. The statistical significance of the aberrations identified by GISTIC are displayed as false discovery rate q values to account for multiple hypothesis testing (q values; green line is 0.25 cut-off for significance). Scores for each alteration are plotted along the x-axis and the genomic positions are plotted along the y-axis; dotted lines indicate the centromeres. <b>H</b>) GISTIC revealed twenty broad and focal regions of gain (copy number threshold = log2 ratio ≥0.4). <b>I</b>) Loss of both broad and focal regions were identified by GISTIC (copy number threshold = log2 ratio≤0.4 for broad and ≤0.1 for focal events). Twenty broad and focal regions of losses, including seven focal events, were identified in the background of broad regions. Candidate genes for some broad and focal events are noted. Green stars indicate known or presumed copy number polymorphisms.</p

Validation of classification accuracy in UCSF-GOG dataset.

<p>Kaplan-Meier plot for UCSF-GOG subgroups identified through supervised clustering. Subgroups are clinically distinct with regard to overall survival (p = 0.028).</p

Amplifications and deletion peaks identified by GISTIC.

<p>Amplifications and deletion peaks identified by GISTIC.</p

Validation of classification accuracy in TCGA dataset.

<p>Kaplan-Meier plots for TCGA subgroups identified through supervised clustering. Subgroups are clinically distinct with regard to both (<b>A</b>) progression-free survival (p = 0.0017) and (<b>B</b>) overall survival (p = 0.0098). The combined cluster of subgroup 1 and 3 is clinically distinct from subgroup 2 with regard to both (<b>A1</b>) progression-free survival (p<0.001) and (<b>B1</b>) overall survival (p = 0.0028). <b>C–E</b>) Frequencies of genome copy number gain and loss plotted as a function of genome location from 1pter to 22qter in the three clusters identified in the TCGA dataset. Vertical lines indicate chromosome boundaries, and vertical dashed lines indicate position of centromeres along the chromosomes. Positive and negative values indicate frequencies of tumors showing copy number increases (gain shown in red) and decreases (loss shown in green). <b>C1–E1</b>) Frequencies of tumors showing high-level amplifications and homozygous deletions in the three TCGA clusters. Data are displayed as described in C–E. Arrows indicate genomic regions where the three clusters differ significantly.</p