Deciphering the contribution of RNA-misprocessing in Glioblastoma for the development of novel therapeutic strategies / Serum metabolomic profiling in patients with Primary Sclerosing Cholangitis (PSC) for the prediction and diagnosis of Cholangiocarcinoma (CCA)

Deciphering the contribution of RNA-misprocessing in Glioblastoma for the development of novel therapeutic strategies

Glioblastoma (GBM) is the most frequent and most malignant brain tumor, with a devastating prognosis of a median overall survival of 15 months. Its aggressiveness is closely associated with a strong therapy resistance which arises from a small population of dormant but highly tumorigenic self-renewing glioma stem cells (GSCs). RNA-processing is a tightly regulated cellular mechanism that expands transcriptome and proteome diversity. It includes alternative splicing (AS), fusion of gene transcripts and alternative polyadenylation. Emerging evidence indicates that misregulation of RNA-processing is a hallmark of cancer, that contributes to tumor initiation and evolution. However, it is still poorly studied in GBM. Taking advantage of public and our own datasets we have identified AS events associated with GBM aggressiveness. In addition, we hypothesize that GSCs present a particular RNA-processing signature associated with their therapy resistance that can be exploited to develop new therapeutic approaches for GBM.

Serum metabolomic profiling in patients with Primary Sclerosing Cholangitis (PSC) for the prediction and diagnosis of Cholangiocarcinoma (CCA)

Primary sclerosing cholangitis (PSC) is the most well-established risk factor for the development of bile duct cancer or cholangiocarcinoma (CCA), with up to 20% of patients with PSC developing CCA during their lifetime. Currently, the accuracy of the available diagnostic methods to detect CCA in patients with PSC is far from satisfactory, leading to late diagnosis when disease is already metastasized and when potentially curative treatments are no longer an option. These characteristics, in combination with the high chemoresistance nature of CCA tumors strongly contribute to the high mortality of this cancer, being CCA responsible for more than 30% of PSC-related deaths. Currently, there are no available accurate non-invasive biomarkers for PSC surveillance or early diagnosis of CCA, which is warranted to monitor disease progression and to guide therapeutic strategies. Here, we aimed to identify metabolite-based precise non-invasive biomarkers for the prediction and early diagnosis of CCA in patients with PSC patients. This novel liquid-biopsy strategy may help in the personalized care of patients at risk of CCA development, such as patients with PSC, therefore improving their welfare and outcome.