Project descriptions

Project 1: Interplay between tumor microenvironment and drug therapy in a preclinical model of ovarian cancer by single-cell transcriptomics

Background
Ovarian cancer is the major cause of death among women with gynecological cancers. It is a complex and heterogeneous disease, usually the patients respond well to the platinum-based first-line chemotherapy, but often the disease becomes increasingly resistant to the treatments. Tumor microenvironment plays a very important role in tumor development and resistance to drug treatment. Our collaboration partner in this project from IKP has developed a preclinical model using precision-cut tumor tissue slices with 200-300 μm thickness to maintain intra-tumor heterogeneity with regard to different cell types and preserved native microenvironment. With their new technology named perfusion air culture (PAC) system, the tissue slices can be cultured with continuous and precisely controlled medium and drug supply (patent: WO/2019/029947). The tumor morphology, viability and heterogeneity in terms of tumor and stromal cells as well as the immune compartment are preserved for up to a week within the system. Our previous bulk RNA-seq data of ovarian tissues slices have showed that it is possible to infer the cell compositions of the tissue slices after drug treatment. However, bulk RNA-seq averages gene expression and fails to identify the respective response of different cell subsets and the drug persistent cell profile. Therefore, using single-cell RNA-seq (scRNA-seq) technology to bridge the cellular characteristics and cellular content with treatment response in the ovarian tumor tissue slices is important to develop efficacious therapies for ovarian cancer.

Aim of the Project

This project will combine the newly tissue slices culture system with the scRNA-seq technology together and benefit from both technologies with their respective advantages. Totally 15 tissue slices samples (in vivo, control, treated groups) from 5 ovarian cancer patients will be used in the project. The focuses of this project are as follows:
• Characterize the tumor microenvironment of ovarian tumor by single-cell transcriptomics. Establish the in silico profiles and a method combining different deconvolution and deep learning approaches to identify the different cell populations including immune cells in the ovarian tumors from different patients.
• Analyze the effects of cisplatin treatment on different cell populations and identify the tolerant and/or resistant subpopulations in the ovarian tumor tissue slices before and after cisplatin treatment. Investigate the cell-cell interactions and their roles in drug persistent effects.
• Validation of the scRNA-seq data with immunohistochemistry (IHC) staining and correlate with the patient clinical data.
• Establish a database and an analyzed platform based on the tissue slices culture and scRNA-seq analysis to predict the drug response of individual patient.
• Multi-omics integration and analysis with scATAC-seq data from 9 different patients

In summary, cultivation of tumor tissue slices provides an ex vivo model that preserves tumor heterogeneity and microenvironment which allows long-term culture of tumor tissue and analysis of therapy response - including immune therapy. Combined with the analysis of scRNA-seq technology, a comprehensive platform can be established as a predictive preclinical model to perform patient-specific ex vivo tests and thus allows personalized therapy.

Project 2: The atlas of Dentritic cells - Systems immunological understanding of DC