Research lines

• Precision screening, diagnosis, and staging for enhanced liver cancer outcomes

  Directed by Maria Reig 

  Effective stratification of patients according to their cancer risk is essential to ensure cost-effective screening programs. Achieving high diagnostic accuracy is particularly crucial in detecting very early-stage liver cancer and accurately evaluating tumor burden, which plays a pivotal role in predicting prognosis. Additionally, patient education is fundamental in improving adherence to both screening and treatment protocols, ultimately enhancing clinical outcomes. 

• Non-invasive prognostic assessment by radiology in liver cancer

  Directed by Jordi Rimola  

  It is necessary to identify the radiological imaging biomarkers that have the potential to provide valuable prognostic and predictive information in patients with liver cancer. This will facilitate a more personalized approach and the optimization of therapeutic management. 

• Predictive factors of treatment response in liver cancer

  Directed by Maria Reig 

  This research line focuses on identifying and understanding key predictive factors that influence the response to surgical, locoregional, and systemic treatments in liver cancer. By integrating advanced computational biology techniques, we aim to analyze large-scale biological data to uncover molecular and genetic biomarkers that can predict patient outcomes. A crucial aspect of this work is understanding the interactions between the microbiota and the immune system, which are vital for developing more personalized therapeutic approaches. 

  Additionally, this research explores the potential of vaccines as part of liver cancer treatment strategies. By studying how vaccines can modulate the immune system, we aim to enhance immune responses and improve the effectiveness of existing therapies.  

  This multidisciplinary approach, involving pathologists, radiologists, clinicians, surgeons, and nurses, seeks to develop predictive tools that will help personalize treatments, optimize therapeutic outcomes, and ultimately improve survival rates for liver cancer patients.