The third webinar of the TETRIS Educational Webinar series, titled “Transcriptomic Risk Score Development for Risk Modelling: The TETRIS WP5 Framework”, took place on 23 April.
The webinar was delivered by Miguel E. Aguado-Barrera and Ana Vega from Fundación Pública Gallega de Medicina Genómica (FPGMX) and moderated by Tiziana Rancati, from the Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Principal Investigator of the project.
The session provided an overview of how transcriptomics can support risk modelling within the TETRIS project, with a focus on the development and application of Transcriptomic Risk Scores (TRS).
Starting from the basics of RNA and transcriptomics, Miguel E. Aguado-Barrera explained how gene expression data obtained through RNA sequencing can be used to identify transcriptomic signatures, sets of genes associated with specific diseases or outcomes. These signatures can then be translated into quantitative risk scores, enabling patient stratification and supporting more personalised clinical decision-making.
The central part of the webinar focused on the TETRIS WP5 framework, aiming to integrate transcriptomic data into risk assessment models for radiotherapy-related side effects. The work considers multiple disease areas, including cardiovascular and pulmonary conditions, as well as second cancers, using a retrospective and a prospective patient cohort of about 500 patients.
Miguel E. Aguado-Barrera presented also current methodological approaches, including the use of public molecular signature databases, MSigDB and DisGeNET, and literature-based transcriptomic risk models. These approaches allow the identification of relevant gene sets and the computation of risk scores using weighted gene expression data.
In addition, he introduced exploratory strategies, such as combining transcriptomic and polygenic risk scores, as promising directions for improving predictive performance.
The webinar also addressed key challenges, including the limited number of published studies with validated transcriptomic signatures for the conditions of interest, and the fact that many do not report gene weights, which complicates their application within the TETRIS project.
In conclusion, the session highlighted the strong potential of transcriptomic risk scores to enhance risk modelling in radiotherapy, while underlining the need for further methodological development and data integration. Future work within TETRIS will focus on refining these models and combining multi-level data sources to improve prediction accuracy and clinical applicability.
The webinar has been recorded and is available on TETRIS YouTube channel here.
To download the ppt presentation, click here.
Further webinars in the TETRIS Educational Webinar series will be announced soon. Follow our channels to keep up to date with upcoming events and the latest developments from the project.
