Clinical Interest of Combining Transcriptomic and Genomic Signatures in High-Grade Serous Ovarian Cancer

Abstract

High-grade serous ovarian cancer is one of the deadliest gynecological malignancies and remains a clinical challenge. There is a critical need to effectively define patient stratification in a clinical setting. In this study, we address this question and determine the optimal number of molecular subgroups for ovarian cancer patients. By studying several independent patient cohorts, we observed that classifying high-grade serous ovarian tumors into four molecular subgroups using a transcriptomic-based approach did not reproducibly predict patient survival. In contrast, classifying these tumors into only two molecular subgroups, fibrosis and non-fibrosis, could reliably inform on patient survival. In addition, we found complementarity between transcriptomic data and the genomic signature for homologous recombination deficiency (HRD) that helped in defining prognosis of ovarian cancer patients. We also established that the transcriptomic and genomic signatures underlined independent biological processes and defined four different risk populations. Thus, combining genomic and transcriptomic information appears as the most appropriate stratification method to reliably subgroup high-grade serous ovarian cancer patients. This method can easily be transferred into the clinical setting.

Keywords: BRCA1/2; HGSOC; fibrosis; homologous recombination deficiency; mesenchymal; prognosis.

FIGURE 1

Overlap between transcriptomic signatures used for classification of high-grade serous ovarian cancers. (A) A heatmap from hierarchical clustering applied on the TCGA cohort. Rows represent genes and columns represent patients. Clustering is based on the 100 genes of the D-I-M-P signature (Verhaak et al., 2013) using Pearson distance and Ward’s agglomeration method. The color saturation shows the magnitude of the deviation from the mean for each gene, with red and blue indicating expression values above or below the mean, respectively. Colored bars below the heatmap represent tumor classifications obtained from the four (transcriptomic signatures (Tothill et al., 2008; Mateescu et al., 2011; Bentink et al., 2012; Verhaak et al., 2013), as indicated. The red bars correspond to the Mesenchymal, C1, Angiogenic or Fibrosis subgroup, according to the classification considered. The blue bars correspond to C2–C6, non-Angiogenic and Stress subgroups. For the D-I-M-P signature, blue bars correspond to Immunoreactive, black correspond to Proliferative and purple bars correspond to Differentiated subgroups. (B, Left) Principal Component Analysis (PCA) applied on transcriptomic data from the TCGA cohort, using the 100 genes composing the D-I-M-P signature (Verhaak et al., 2013). The color code represents the four D-I-M-P molecular subgroups: Mesenchymal (red, N = 118), Differentiated (purple, N = 148), Proliferative (black, N = 138) and Immunoreactive (blue, N = 129). (Middle and Right) Further PCA with subgroups highlighted using Fibrosis (red, N = 220) or Stress (blue, N = 326) (Mateescu et al., 2011); C1 (red, N = 107) or C2–C6 (blue, N = 443) (Tothill et al., 2008); Angiogenic (M1, red, N = 128) or non-Angiogenic (M2–M4, blue, N = 422) (Bentink et al., 2012) signatures, as indicated. (C) Barplots showing the number of patients according to each combination of classes among the four classifications (Verhaak/Mateescu/Tothill/Bentink).)

FIGURE 2

High-grade serous ovarian cancers stratified into two transcriptomic subgroups exhibit a reliable prognostic value of patient survival. (A) Kaplan-Meier curves showing 10-year overall survival (OS, Top) and disease-free survival (DFS, Bottom) of patients with Fibrosis (red) or non-Fibrosis (black) ovarian cancers. Patients from the Curie cohort (56 Fibrosis and 51 non-Fibrosis), the AOCS cohort (135 Fibrosis and 150 non-Fibrosis) and the TCGA cohort (220 Fibrosis and 326 non-Fibrosis) were analyzed, as indicated. P-values were calculated using the Log-rank test. (B) Heatmap and hierarchical clustering applied on the Curie (Left) and AOCS (Right) cohorts. Rows represent genes and columns represent patients. Clustering is based on the 100 genes of the D-I-M-P signature (Verhaak et al., 2013) using Euclidean distance and Ward’s agglomeration method. The color saturation shows the magnitude of the deviation from the mean for each gene, with red and blue indicating expression values above or below the mean, respectively. (C) Kaplan-Meier curves showing 10-year overall survival (OS, Top) and disease-free survival (DFS, Bottom) of ovarian cancer patients according to D-I-M-P classification. Patients from the Curie (N = 30 Differentiated, N = 26 Immunoreactive, N = 31 Mesenchymal, and N = 20 Proliferative), the AOCS (N = 25 Differentiated, N = 42 Immunoreactive, N = 102 Mesenchymal, and N = 60 Proliferative) and the TCGA (N = 148 Differentiated, N = 129 Immunoreactive, N = 118 Mesenchymal, and N = 138 Proliferative) cohorts were analyzed. P-values were calculated using the Log-rank test.

FIGURE 3

Combining genomic and transcriptomic signatures provide additive prognostic values for high-grade serous ovarian cancer patients. (A, Up) Principal component analyses (PCA) applied on transcriptomic data from the TCGA cohort using Verhaak’s signature. On the left panel, the color code shows the non-Fibrosis (blue, N = 326) and Fibrosis (red, N = 220) subgroups, using Mateescu’s signature (Mateescu et al., 2011). The right panel shows the same PCA representation but subgroups are highlighted using the LST genomic signature (Popova et al., 2012). The color code represents LST^Lo (blue, N = 238) and LST^Hi (green, N = 303) ovarian cancers. (Down) Contingency tables showing the repartition of patients regarding Mateescu or LST classification and the repartition against the two first principal components. (B) Kaplan-Meier curves showing 10-year overall survival (OS, Left) and disease-free survival (DFS, Right), after stratification into four groups: LST^Lo/Fibrosis (red, N = 89), LST^Lo/non-Fibrosis (green, N = 147), LST^Hi/Fibrosis (blue, N = 127), and LST^Hi/non-Fibrosis (black, N = 171). P-values are calculated using the Log-rank test.