Research lines

• Genetic association studies in colorectal cancer and advanced adenomas

  Directed by Sergi Castellví
  
  We identify common, low-penetrance genetic variants linked to colorectal cancer and/or advanced adenomas risk through association studies comparing genetic variation in disease cases and controls free of disease. These variants can be explored to identify individuals from the general population with a higher risk for these lesions.

• New hereditary genes for colorectal cancer

  Directed by Sergi Castellví
  
  We discover new genes for germline predisposition to colorectal cancer. We focus on studying familial (several cases in each family), early-onset (before the age of 50) and serrated polyposis syndrome cases. We apply next generation sequencing approaches, subsequent data filtering and analysis to identify interesting candidate genes.

• New hereditary genes for gastric cancer

  Directed by Leticia Moreira

  We find new genes for germline predisposition to gastric cancer by focusing on early-onset cases. As previously with colorectal cancer and using our gained experience with that previous approach, we use next generation sequencing techniques, subsequent filtering and data analysis to identify interesting candidate genes.

• State-of-the-art functional studies of candidate genes

  Directed by Sergi Castellví
  
  Candidate genes for colorectal cancer and gastric cancer are evaluated for their ability to predispose for these neoplasms. We need to demonstrate that each identified candidate genetic variant is altering gene function and this alteration can initiate cancer. We use advanced molecular and cellular biology techniques, such as gene editing with the CRISPR-Cas9 technique and intestinal organoids.

• Clinical relevance of new hereditary genes for gastrointestinal cancer

  Directed by Sergi Castellví
  
  We perform a genotype-phenotype correlation of the new genetic variants for germline predisposition to gastrointestinal cancer with personal and family characteristics of patients. By doing so, we identify specific patient characteristics that can be used to single out additional patients in the population, as well as to perform risk stratification and prognosis prediction.