Multiparameter Single Cell Characterization of Ovarian Intratumor Heterogeneity [29A]. (May 2018)

• Record Type: Journal Article
• Authors: Beaumont, Kristin; Copperman, Alan B.; Dottino, Peter; Martignetti, John; Schadt, Eric; Sebra, Robert
• Is Part Of: Obstetrics and gynecology. Volume 131(2018)Supplement 1
• Publication Date: 2018-05
• Subjects: Obstetrics -- Periodicals; Gynecology -- Periodicals; 618
• DOI: 10.1097/01.AOG.0000532892.87767.de
• Languages: English
• ISSNs: 0029-7844

Abstract

Abstract : INTRODUCTION: Rapid advances in single-cell and deep sequencing technologies has revealed the genetic and functional complexity of bulk tumor tissue, particularly with regard to heterogeneous and clonal composition. This is especially relevant to HGSOC patients, where existing analyses of these tumors have uncovered a high degree of intratumoral heterogeneity. In this work, we present methods for the isolation of single- and multi-cellular batches to better characterize clonal diversity from HGSOC patient-derived cells. METHODS: We demonstrate single- and multi-cellular manipulation and sequencing using multiple technologies. Lysed genomic DNA from single or batched cells was characterized using the AmpliSeq 207-target HotSpot and comprehensive 143-target Oncomine cancer panels. Single cell, differential expression was conducted using Chromium high diversity mRNA sequencing. RESULTS: We integrate phenotypic and genotypic profiling of single cells to characterize clonal heterogeneity in HGSOC tumors. Specifically, growth kinetics, differential expression, and clonal TP53 mutation profiling will be discussed in the context of primary samples. Analysis of TP53 mutation demonstrated a clear sub-population (31%) of single cells exhibiting >75% mutation frequency, which is much higher than the 25-40% observed in bulk control samples, indicating that a cellular subset likely drives downstream signaling effects. In addition to genetic data, single cell real-time cloning alongside CA125 and HE4 secretion assays were combined. CONCLUSION: Collectively, this genomic data was used to identify cellular clonality and address the degree of heterogeneity across HGSOC tumors when compared to bulk sequencing. We illustrate the potential for utilizing single cell sequencing data in the development of future therapeutic interventions.