E!10591 Innovative Diagnostic RNA sequencing Platform to improve ovarian cancer outcomes

The associated trial called AVANOVA (ENGOT-OV24/AVANOVA) throughout the host institutions in Denmark, Norway, Sweden, Finland and in the USA enrolled 108 patients. The clinical study has been successfully concluded. Because the trial was setup with multiple sites the transfer of samples to Genomic Expression has been delayed due to additional paperwork to be signed and the COVID19. I addition the new GDPR rules and a recent court case made it impossible for a sample transfer before the end of the project. The issue has now been solved this so that Rigshospitalet?s phase 1 unit can perform the OneRNA test on site. These analyses will now be conducted after the end of the project. Genomic Expression has built out its OneRNACloud platform in ovarian cancer with an actionable target and biomarker database. Pubgene has released version 3 of the pathway analysis software. The development has been done using "dummy data" collected from publically available data sources due to the delayed access of the data from the trial. As an extension of this project PubGene will finalize an API for integration with Genomic Expressions OneRNACloud platform once the software has been validated with data from the trial. The final version of the software will identify and rank pathways either based on one single RNA sample or multiple RNA samples. Statistical tests can be used for validation and sorting uploaded datasets. We have developed mechanisms to guide the ranking process i.e., in number of samples in which an RNA entry must be found to be included in the ranking. In addition, significance values can be exploited to filter the data prior to pathway ranking. Pathway ranking is flexible due to user-selective coverage of samples from various expression data sets. Functionality for pathway search and filter has been improved to combine pathway names and hierarchy, along with a gene/protein filter and a robust result sorting for more control on pathway navigation. The tool has been improved to cater for large RNA-seq datasets, and additional details are made available in the pathway view for better human-friendly network interaction. We remain very excited to analyze the samples fromm the conducted trial, and the project partners are excited to be in a position to deliver a companion diagnostic algorithm for PARP inhibitors in ovarian cancer. The PI of the clinical trial, Mansoor Mirza, will submit an abstract for ASCO as well as ESMO with our results and plan to publish in the New England Journal of Medicine which is where he published previously.

Through this project, we have been able to develop a specific pathway analysis tool representing an addition to our existing product portfolio and a new offering in the personalized medicine market. This new product will enable the users to identify key molecular pathways and their components, suggesting potential drug targets and in this way will be important for all types of drug development projects. It is clear that tools for speeding up drug development will have a major impact on personal health and on society at large. Furthermore, PubGene have hade to strengthen our international reach through new collaboration

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