PERREO: exploring early diagnosis and prognosis in complex diseases

Precision medicine is moving fast, but many of its promises are still hard to bring into real-world practice. With PERREO, we’re trying to contribute to that effort by building tools that make better use of transcriptomic data.

Our work focuses on transcriptomics with a special emphasis on repetitive sequences, the repeatome, as an often overlooked source of biological signal. We are interested in capturing subtle, hard-to-interpret patterns in expression data, especially those coming from repetitive elements, which may play important roles in disease biology. Turning these signals into robust, clinically useful biomarkers is not straightforward, and that challenge is at the core of what we are working on.

Early diagnosis: trying to get there before symptoms appear In oncology and many other diseases, diagnosis often happens when the condition is already advanced. With PERREO, we are exploring whether early transcriptomic patterns, particularly those linked to repeatome activity, can be detected before clinical manifestation. Distinguishing meaningful signal from noise, and validating it across different cohorts, is a demanding and ongoing process.

Prognosis: making sense of disease trajectories Two patients with the same diagnosis can follow very different clinical paths. We are investigating whether transcriptomic signatures—with a particular focus on repetitive elements—can help model disease progression and support better patient stratification. These models require careful validation and we know they will not always generalize across all clinical settings, but we see them as an important step forward.

Beyond cancer Although we started in oncology, similar transcriptomics-based, repeatome-centered approaches could be applied to other complex diseases, such as neurodegenerative or inflammatory conditions. We are especially interested in understanding which patterns are shared across diseases and which are disease-specific.

At PERREO, we see a lot of potential in tools that help us understand and manage diseases through transcriptomics and repeatome analysis. At the same time, we are very aware that progress in this field is incremental and requires rigorous validation. Our goal is to contribute to that process in a careful and honest way.

This work has been made possible together with Mario Masero León and Daniel Gómez Cabello.

Preprint available on bioRxiv: https://lnkd.in/ebw79KdZ

GitHub repository: https://github.com/DGCLab/PERREO-Pipeline