Innovative Algorithm Unveils Cancer Evolution and Predicts Disease Progression

An international research team led by the Clínic-IDIBAPS-UB, in collaboration with the Institute of Cancer Research in London, has introduced a groundbreaking method that leverages DNA methylation patterns to understand the origin and evolution of cancer. Published in the journal Nature, this study analyzes tumor development in 2,000 patients with leukemias and lymphomas, offering new insights into tumor progression. The innovative approach employs an algorithm called EVOFLUx, which reconstructs the tumor's history by examining epigenetic data, specifically fluctuating methylation marks. These marks serve as a biological 'black box', recording the tumor's developmental journey in a manner similar to flight data recorders in aircraft.

Traditionally, methylation has been viewed as a switch controlling gene activity, but this research reveals it also carries an imprint of the cancer's origin that evolves as the tumor develops. By decoding these methylation patterns using advanced mathematical models, researchers can trace back the tumor growth, understand its diversification, and predict its future behavior.

Applying EVOFLUx to samples from diverse leukemia and lymphoma cases, the team demonstrated that the tumor’s epigenetic history correlates with its aggressiveness and trajectory. For example, in chronic lymphocytic leukemia, the method can forecast when the disease might require treatment years in advance. This approach not only enhances understanding of cancer biology but also paves the way for personalized treatment planning by foreseeing disease evolution.

The study underscores the potential of epigenetic analysis as a tool to 'read' cancer's past, providing valuable predictive insights. As explained by lead researcher Iñaki Martín-Subero and colleagues, this method allows clinicians to determine the origin, growth speed, and diversity of tumor cells, contributing significantly to personalized oncology strategies.

Overall, this pioneering research opens new horizons in cancer diagnosis and management, promising more accurate predictions of disease course and improved patient outcomes.