BioProject

Using RNA-seq, we recently developed the 52-gene-based Oxford Classifier of Carcinoma of the Ovary (Oxford Classic, OxC) for molecular stratification of serous ovarian cancers (SOCs) based on the molecular profiles of their cell-of-origin in the fallopian tube epithelium. Here, we developed a 52-gene NanoString panel for the OxC to test the robustness of the classifier. We measured the expression of the 52 genes in an independent cohort of prospectively collected SOC samples (n = 150) from a homogenous cohort who were treated maximal debulking surgery and chemotherapy. We performed data mining of published expression profiles of SOCs and validated the classifier results on tissue arrays comprising 137 SOCs. We found evidence of profound non-genetic heterogeneity in SOC. ~20% of SOCs were classified as epithelial-mesenchymal-transition-high (EMT-high) tumors, that were associated with poor survival. This was independent of established prognostic factors such as tumor stage, tumor grade and residual disease after surgery (HR = 3.3, p = 0.02). Mining expression data of 593 patients revealed a significant association between the EMT scores of tumors and the estimated fraction of alternatively activated macrophages (M2) (p < 0.0001) suggesting a mechanistic link between immunosuppression and poor prognosis in EMT-high tumors. The OxC-defined EMT-high serous ovarian cancers carry particularly poor prognosis independent of established clinical parameters. These tumors are associated with high frequency of immunosuppressive macrophages suggesting a potential therapeutic target to improve clinical outcome. Overall design: NanoString expression data of a 52-gene panel (Oxford Classifier of Carcinoma of the Ovary, OxC) in 150 serous ovarian cancer samples (HH-cohort) and ten HGSOC samples.