Role and Applicability of Circular RNAs in Liver Cancer

Liver cancer mortality rate and incidence are increasing worldwide. It is the second most common cancer-related cause of death in men and the third by total deaths worldwide. Liver cancer has a very low five-year survival, of 18% worldwide, and its recurrence rate is as high as 70%. It is a deadly disease mainly because there are limited diagnostic, prognostic, and therapeutic approaches. The most common liver cancer is hepatocellular carcinoma (HCC). Liver cancer patients and their doctors face two problems in everyday clinical practice, lack of non-invasive molecular biomarkers, diagnostic or prognostic, and limited therapeutic approaches. Circular RNA (circRNA) represent a new class of covalently closed, single-stranded RNA, which have several potential applications in oncology. They are a promising new class of diagnostic and prognostic biomarkers, and could also represent a new class of RNA-based therapies. In this project, we aim to evaluate the biomarker and therapeutic potential of circRNA in liver cancer using an original systems medicine approach. This has not yet been attempted and we expect that the use of systems medicine tools will enable us to identify key circRNA driving the malignant phenotype in HCC, making them ideal targets of new therapies and potential molecular biomarkers in HCC. We believe that a breakthrough in the diagnosis and treatment of patients with liver cancer requires a different and original approach to studies of liver cancer pathology. The project brings together the knowledge of experts from various fields, clinics, computer scientists, molecular biologists and international collaborators, which will ensure the success of the project. We will exploit the state-of-the-art long-read sequencing to sequence full-length circRNA in tumour and non-tumour liver samples in parallel with plasma from the same HCC patients. By this approach, we will be the first to generate a unique long-read sequencing dataset from a trio of samples from the same patient, which will enable us to directly align the expression of circRNA in plasma and liver samples to polyA RNA expression in the liver, which we already have sequenced. Furthermore, by applying the original systems medicine approach to data integration of transcriptome datasets and gene prioritization, we aim to identify key circRNAs in HCC and test their biomarker and cancerogenic potential. Finally, we will test the circRNA potential as the target of RNA-based therapeutics in preclinical models. Project expected results are: (1) generation of a unique HCC dataset from a trio of samples, which will enable data analyses that were not possible so far. (2) Long-read sequences of circRNA, which will enable precise definition of their length and sequence and the discovery of new circRNAs. (3) Identification of key circRNAs using original system medicine tools on our HCC datasets. (4) Validation of key circRNAs biomarker and cancerogenic potential in HCC. (5) Advancement in the field of RNA-based therapeutics by evaluating the circRNA potential in preclinical models. The project will contribute to our understanding of how circRNAs are involved in malignant liver cancer pathology. It is a unique opportunity to perform a comprehensive study to tackle the two problems in liver cancer: the lack of non-invasive molecular biomarkers and the lack of new therapeutic strategies.