Transcriptional Map of Ovarian Cancer at the Single Cell Level
Transcriptional Map of Ovarian Cancer at the Single Cell Level
In 2020, epithelial ovarian cancer (EOC) accounts for 313,959 new cases and 207,252 deaths worldwide. The standardized 5-year net survival of a woman with EOC is 44% for cases diagnosed between 2005-2010. This is because 2 out of 3 cancers are found at an advanced stage with invasion beyond the ovaries to the entire peritoneum or distant metastasis. Treatment of EOC is currently based on platinum-based chemotherapy combined with paclitaxel and maximal cytoreduction surgery. Newer combination therapies may be introduced such as bevacizumab and oral poly ADP-ribose polymerase (PARP) inhibitors. Despite the combination of different therapeutic modes, the 5-year survival has not progressed much since the 1980s. The development of new and more effective therapies is essential but requires a better understanding of cancer heterogeneity and the identification of new therapeutic targets.
Cancer heterogeneity results from genetic and transcriptional variations between tumors but also between cells of the same tumor. This heterogeneity has an impact on the development of the tumor and its resistance to treatment. One of the methods to study this heterogeneity is single cell RNA sequencing (scRNAseq) which allows to analyze individually and simultaneously the gene expression (transcriptomics) of thousands of cells. Studies on EOC using this technique have already been performed but they were based on small numbers with very different tumor types and stages.
The objective of this protocol is to characterize by scRNA-seq the architecture and microenvironment of primary and secondary tumors of 50 patients with EOC at the single cell level and to correlate the data with the clinical characteristics of the patients, especially during recurrence and/or chemoresistance, in order to identify the molecular parameters allowing tumor cells to acquire survival, invasion, metastasis and chemoresistance capacity as well as to carry out the inventory of cell populations within the different sites of EOC. We will also analyze the interaction between tumor cells and the microenvironment, by studying on the one hand the involvement of immune cells in the antitumor response and on the other hand how tumor cells modulate the microenvironment to make it permissive to the development of the EOC. We will compare the data obtained for each patient with healthy tissue (from the same patient) in order to determine the common and specific tumor molecular signatures in EOC, the latter point allowing us to evaluate the intra and inter-patient variability. Similarly, the comparison of the transcriptomic profile of the same tumor subtype in several patients will allow us to determine if certain transcriptional perturbations are ubiquitous. The identification of these common pathways would allow the discovery of potential therapeutic targets.
Furthermore, the molecular processes leading to chemoresistance are still unknown. We will investigate whether known chemoresistance markers are present in tumor cells from primary sites and whether their presence correlates with the response to treatment in patients. We will also study the molecular mechanisms of resistance to treatment in our patients which will ultimately allow the development of new therapies. We will also try to find new prognostic markers which is made possible by the clinical follow-up of the patients.
The existence of this heterogeneity will be confirmed by complementary genetic analyses of the genome and exome (search for mutations, variation in gene copy number or chromosome copy number, epigenetic effects) by different molecular biology techniques (qPCR, NGS sequencing) and the markers that will be identified can be confirmed by histochemical analysis.
After tumor stage determination by the pathology department the fresh tumor samples will be prepared for the single cell preparation.. The samples will be transported in a cold transport solution (MACS Storage tissue, Miltenyi). These samples will be used for library preparation using the Chromium Controller (10X Genomics) and sequencing using the NextSeq550 system (Illumina) as well as for HLA-bound neoantigen identification by mass spectrometry. After data analysis by bioinformatics, we will study the transcriptome of each identified cell population. The identified markers will be confirmed by histochemical and molecular biological analysis.
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Cherif.AKLADIOS@chru-strasbourg.fr3 88 12 74 55 ext. +33