Our research explores CLL across its entire trajectory - from the earliest genetic events to advanced disease stages. We focus on genetic prognostication, the role of complex karyotypes and the mechanisms that drive Richter transformation (RT). By tracing CLL through time and space, we aim to reveal how genetic and evolutionary forces shape disease behaviour and patient outcomes.

Cancer cells acquire new forms and shapes that reflect their aberrant nature. In CLL, a disease of mature lymphocytes, these morphological alterations are subtle and poorly understood. Little is known about how the spectrum of genetic changes relates to cytomorphology. By applying AI-assisted computer vision approaches, we interrogate cell morphology and uncover clinically meaningful insights into both CLL and RT.

We investigate minimal residual disease (MRD) as a window into treatment response and disease dynamics. By studying how MRD evolves over time - down to the single-cell level - we uncover the hidden persistence of cancer cells, their adaptive strategies and their prognostic significance for long-term outcomes in CLL. 

People with CLL are more than twice as likely to develop a second primary malignancy (SPM) during their lifetime compared to those without CLL. The reasons for this increased risk remain completely unclear .Understanding this phenomenon is one of our central goals. To address it, we combine sophisticated spatial technologies with the power of large clinical cohorts, aiming to uncover why people with CLL are predisposed to additional cancers and how this knowledge can inform prevention and care.

Targeted treatments in CLL achieve remarkable efficacy, yet infections and immune dysfunction remain leading causes of mortality. Our goal is to understand these complications by studying immune alterations over time, through longitudinal observations at both the cellular and humoral level.