Multiomic Analysis of Subtype Evolution and Heterogeneity in High-Grade Serous Ovarian Carcinoma

Abstract

◥Multiple studies have identified transcriptome subtypes of highgrade serous ovarian carcinoma (HGSOC), but their interpretation and translation are complicated by tumor evolution and polyclonality accompanied by extensive accumulation of somatic aberrations, varying cell type admixtures, and different tissues of origin. In this study, we examined the chronology of HGSOC subtype evolution in the context of these factors using a novel integrative analysis of absolute copy-number analysis and gene expression in The Cancer Genome Atlas complemented by single-cell analysis of six independent tumors. Tumor purity, ploidy, and subclonality were reliably inferred from different genomic platforms, and these characteristics displayed marked differences between subtypes. Genomic lesions associated with HGSOC subtypes tended to be subclonal, implying subtype divergence at later stages of tumor evolution. Subclonality of recurrent HGSOC alterations was evident for proliferative tumors, characterized by extreme genomic instability, absence of immune infiltration, and greater patient age. In contrast, differentiated tumors were characterized by largely intact genome integrity, high immune infiltration, and younger patient age. Single-cell sequencing of 42,000 tumor cells revealed widespread heterogeneity in tumor cell type composition that drove bulk subtypes but demonstrated a lack of intrinsic subtypes among tumor epithelial cells. Our findings prompt the dismissal of discrete transcriptome subtypes for HGSOC and replacement by a more realistic model of continuous tumor development that includes mixtures of subclones, accumulation of somatic aberrations, infiltration of immune and stromal cells in proportions correlated with tumor stage and tissue of origin, and evolution between properties previously associated with discrete subtypes.Significance: This study infers whether transcriptome-based groupings of tumors differentiate early in carcinogenesis and are, therefore, appropriate targets for therapy and demonstrates that this is not the case for HGSOC.

Chromosome instability is prevalent and dynamic in high-grade serous ovarian cancer patient samples

“…spatial heterogeneity). Again, differences in the level of aneuploidy were expected as tumours exhibiting CIN are expected to produce heterogeneous populations of cells and our data support those of previous studies investigating the prevalence of genome instability within HGSOC [29,[37][38][39][40]. For example, Kim et al [38] and Schwarz et al [40] constructed evolutionary trees to describe the spatial heterogeneity identified in solid and ascites HGSOC samples.…”

“…Moreover, by examining serial ascites samples, we determined that CIN is dynamic throughout the treatment period, and that higher levels of CIN are observed in chemoresistant disease relative to chemosensitive disease. Collectively, these temporal dynamics indicate that the level of CIN may reflect changes in the underlying biology associated with an individual's disease or reflect selection of chemotherapy-resistant cells produced in response to treatment, which is consistent with previous work proposing spatial changes in tumour phenotypes over time [29]. Perhaps most surprising, was the pervasive nature and extent of CIN within .…”

Phenotypic Characterization by Mass Cytometry of the Microenvironment in Ovarian Cancer and Impact of Tumor Dissociation Methods

“…The results of this study demonstrate greater interpatient differences than intrapatient differences and confirm the acknowledged tumor heterogeneity, as each patient sample displayed a unique combination of tumor, immune, and stromal cells, regardless of the method used for tumor dissociation. Several authors have illustrated the challenges of developing reliable diagnostic and therapy-related methods that can be applied to heterogeneous cancer tissues [13,[47][48][49]. The polyclonality and heterogeneity of HGSOC tumors, which has been established through single-cell experiments [13,[47][48][49], indicate a need for better profiling tools.…”

“…Several authors have illustrated the challenges of developing reliable diagnostic and therapy-related methods that can be applied to heterogeneous cancer tissues [13,[47][48][49]. The polyclonality and heterogeneity of HGSOC tumors, which has been established through single-cell experiments [13,[47][48][49], indicate a need for better profiling tools. Application of CyTOF in studies of HGSOC to detect cellular patterns rather than single biomarkers, potentially in combination with genetic biomarkers and preclinical modeling systems may provide breakthroughs.…”

Recent Advances in Integrative Multi-Omics Research in Breast and Ovarian Cancer

“…Consistent with this premise, investigators have identified rare plastic pre-adapted cell subpopulations in luminal breast tumors which showed resistance to acute endocrine treatment [ 221 ]. Similarly, studies by Izar et al and Geistlinger et al used scRNA-seq based analyses to link the transcriptomic-based subtype classification of HGSOC to tumor cell type composition rather than intrinsic difference in gene expression patterns present in tumor epithelial cells further highlighting the importance of considering specific subpopulations of cells and the impact of signaling from the microenvironment on tumor characteristics [ 117 , 222 ]. More complex analyses integrating single-cell RNA-seq coupled with cell lineage tracing has been used to detail tumor cell subpopulations that contribute to various aspects of tumor evolution, including identifying pre-EMT (Epithelial to Mesenchymal Transition) cells that are essential for metastasis initiation [ 223 ].…”