Abstract 467: Deep single-cell RNA-seq of the putative cell of origin revealed a novel molecular subtype of high-grade serous ovarian cancer with poor prognosis
Authors: Zhiyuan Hu, Abdulkhaliq Alsaadi, Nina Wietek, Laura Santana González, Christopher Yau, Ahmed Ashour Ahmed
Journal: Cancer Research (2019)

Abstract Accurate molecular classification in cancer is essential for rationalized therapy. However, achieving stable subtyping is highly challenging due to the underlying genomic complexity of tumors. An example of the most successful classification is in breast cancer where it is possible to link individual tumor types, basal vs luminal, to individual cell types of origin. However, the generalization of such an approach has not been easy because of the lack of knowledge about subtypes of the putative cells of origin. For instance, it has been difficult to establish a stable molecular classification of high-grade serous ovarian cancer (HGSOC). More recent evidence strongly supports the notion that HGSOC originates from the secretory cells in fallopian tube epithelium (FTE). However, whether or not there are multiple subtypes of secretory cells and how such subtypes are linked to tumor molecular subtypes have remained elusive. To address this issue, we applied single-cell RNA sequencing (Smart-Seq2) on around 4000 FTE cells from patients with ovarian or endometrial cancers. We developed and employed an in-house differential-expression-based clustering method, termed ClinCluster, for clinical samples that takes into account inter-patient variability. Apart from the established secretory and ciliated cell types, we discovered four novel subtypes of secretory cells and a rare intermediate cell type that co-expresses secretory and ciliated markers. We termed these four novel secretory subtypes as cell cycle, progenitor, epithelial-mesenchymal transition (EMT) and immunoreactive subtypes. Based on fifty-three biomarkers of these subtypes, we designed a panel of transcriptomic signatures and exploited them to deconvolute two bulk expression datasets of ovarian cancer: the RNA-seq dataset of TCGA (The Cancer Genome Atlas) and the microarray dataset of AOCS (Australian Ovarian Cancer Study). The deconvolution analysis revealed a poor-prognostic EMThigh subtype of HGSOC, which was not driven by copy number aberrations. Cox regression analysis indicated that the EMThigh tumors were strongly associated with poor overall survival in the two independent datasets tested (hazard ratio = 2.7, 95% confidence interval = 1.4 - 5.1, P = 0.002, n = 307 for TCGA; hazard ratio = 3.2, 95% confidence interval = 1.7 - 6.1, P = 0.0002, n = 253 for AOCS). Importantly, we found that the PI3K-Akt signaling pathway is upregulated in the EMThigh tumors (FDR &amp;lt; 0.002 for the two independent datasets) giving a strong potential for effective rationalized therapies. In summary, our work portrays a new model for the landscape of fallopian tube epithelium, the putative origin of HGSOC, and illustrates that the cellular subtypes in FTE are related to the HGSOC tumor types with important prognostic and therapeutic implications. Citation Format: Zhiyuan Hu, Abdulkhaliq Alsaadi, Nina Wietek, Laura Santana González, Christopher Yau, Ahmed Ashour Ahmed. Deep single-cell RNA-seq of the putative cell of origin revealed a novel molecular subtype of high-grade serous ovarian cancer with poor prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 467.