Cancer is a multifaceted disease influenced by multiple factors. Moreover, the impact of genomic alterations varies considerably depending on the cellular context. In the Computational Cancer Genomics Lab, we strive to decipher the context-dependent cancer fitness landscape. We do this by identifying novel cancer predisposition genes (CPGs), measuring variations in cancer fitness across cancer states, and constructing dynamic protein-protein interaction networks. Our research is rooted in cancer genomics, systems biology, and network medicine. First, our findings aim to provide a comprehensive understanding of tumour progression via novel CPGs. Second, after examining 250,000 primary and metastatic samples, we discerned specific cancer types/cancer genes with distinct fitness levels based on their cancer states. Through extensive data analysis, our goal is to address core questions in cancer genetics and to explore the practical and clinical implications of our genomic findings.
Post-Doctoral Fellows
- Seokjin Ham
Graduate Students
- Jaejun Lee
- Manuel Moradiellos
- Alejandro Palacios
Technicians
- Adrián Maqueda
Publications
- (2023). Systematic analysis of disease-linked rare germline variants reveals new classes of cancer predisposing genes.. Genome Med 15, 107. CNIO Publication.
- (2023). Genetic assessment of pathogenic germline alterations in lysosomal genes among Asian patients with pancreatic ductal adenocarcinoma. J Transl Med 21, 730. CNIO Publication.
- (2021). Lipid-Oriented Live-Cell Distinction of B and T Lymphocytes. J Am Chem Soc 143, 5836-5844. CNIO Publication.
- (2021). Lipid-Oriented Live-Cell Distinction of B and T Lymphocytes. J Am Chem Soc 143, 5836-5844. CNIO Publication.
- (2021). Higher order genetic interactions switch cancer genes from two-hit to one-hit drivers.. Nat Commun 12, 7051. CNIO Publication.
Open Access - (2021). A comprehensive analysis of prefoldins and their implication in cancer.. iScience 24, 103273. CNIO Publication. Open Access
- (2019). Integrated Analysis of Germline and Tumor DNA Identifies New Candidate Genes Involved in Familial Colorectal Cancer.. Cancers 11, E362. Publication in other institutions.
