Abstract 3780: Spatially resolved transcriptional patterns of PARP inhibitor-resistant high grade serous ovarian cancer PDX tissue

Abstract

Ovarian cancer is the leading cause of mortality among gynecological malignancies; 70% of patients who initially respond to therapy eventually relapse and die. Within highly heterogeneous tumors, resistance originates from a small number of cells that express beneficial genes and receive favorable cues from their microenvironment. Understanding the mechanisms of drug resistance therefore requires the knowledge of which cell types compose the tumor, which genes they express, and where they are located respective to other cells and tissue landmarks. To this end, we have explored cell type and transcriptional heterogeneity in homologous recombination deficient patient-derived xenograft (PDX) models of high grade serous ovarian cancer (HGSOC) treated with the PARP inhibitor talazoparib. We are using single-cell RNA sequencing (scRNA-seq) to identify the discrete cell types present in drug naive and drug resistant PDX tissue and to characterize the transcriptional changes driving the resistant phenotype. We are using single-molecule hybridization chain reaction (smHCR) to fluorescently label mRNAs and diSPIM light sheet microscopy to visualize fluorescently labeled mRNAs within large volumes of PDX tissue. We are currently developing computational strategies to deconvolve the 3D spatial organization of PDX cell types and to understand where and when resistance genes are expressed. This integrated scRNA seq and smHCR microscopy framework has allowed us to identify rare cell populations within HGSOC PDXs and to visualize their 3D localization relative to other cell types and tissue features, and it has the potential to elucidate how transcription of key genes supports transition to a resistant state. The insights gained from single cell transcriptional and 3D spatial profiles has the potential to greatly advance our understanding of how the 3D tumor tissue microenvironment allows and encourages rare cells with pre-resistant transcriptional programs to escape PARP inhibitor treatment. Further, this research has the potential to be predictive of disease progression and to suggest additional therapeutic targets that could be exploited as part of novel and/or personalized combination therapy regimens. An additional advantage is that this approach could be generalizable to many types of cancer to characterize the interplay between tissue organization and diverse processes such as tumor evolution, metastasis, and drug resistance. Citation Format: Benjamin King, Elke Van Oudenhove, Selim Misirlioglu, Ernesto Arostegui Fernandez, Douglas Levine, Timothee Lionnet. Spatially resolved transcriptional patterns of PARP inhibitor-resistant high grade serous ovarian cancer PDX tissue [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 3780.