Pancreatic cancer (PC) has an overall 5-year survival rate of <9% and is projected to become the second leading cause of all cancer-related deaths by 2030. Poor outcomes are due to the majority of cases being diagnosed when PC has already metastasised and a lack of effectual therapies for advanced disease, with 5-year survival rates in metastatic disease just 3%. Our previous large-scale genomics studies revealed PC is molecularly highly varied [1-3]. This heterogeneity, lack of effective therapies and high mortality rate make PC a prime model to advance personalised medicine strategies, where individual cancers are selected for optimal therapy depending on their molecular subtype. Utilising our significant experience in the development of molecular-guided anti-cancer therapies [4-10] and our stromal biology expertise [7,11-12], we are taking drug-repurposing approaches to test agents with effects on stromal biology in combination with current standard-of-care chemotherapies (Gemcitabine/Abraxane) to improve clinical outcomes.
Itraconazole is a widely available, FDA-approved antifungal that has potential anti-cancer effects, although its efficacy in the context of PC remains relatively unexplored. Itraconazole can perturb the Niemann-Pick C1 Protein (NPC1) receptor, downstream of the Akt/mTOR pathway – which is atypically activated in ~25% of pancreatic cancers, with NPC1 aberrations present in ~17% of pancreatic cancers. Our initial data shows differential NPC1 expression in our patient-derived models, and demonstrates that itraconazole efficacy is correlated with NPC1 and AKT levels in vitro. Our preliminary in vivo findings indicate that itraconazole, in combination with Gemcitabine/Abraxane, significantly improves survival in a personalised patient-derived xenograft setting. Excitingly, our data using a model of metastatic PC show that itraconazole hinders metastatic colonisation in the liver and significantly delays disease progression, while inhibiting immunosuppressive elements in the stroma and pro-tumourigenic signalling.