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Researcher Blanca Rius Sansalvador defended her doctoral thesis, Microbiome and Metabolomics Approaches for Colorectal Cancer Risk Assessment in Population-Based Screening, on 16 October at the University of Barcelona (UB). Co-supervised by Dr Víctor Moreno Aguado, Head of the Oncological Data Analytics Programme (PADO), and Dr Mireia Obón Santacana, Coordinator of the Biomarkers and Susceptibility Unit within PADO, the research explores how the study of the intestinal microbiome and metabolites present in the body may contribute to a more accurate assessment of colorectal cancer risk in population-based screening programmes.

The examination committee comprised David Hughes, Principal Investigator and Leader of the Molecular Cancer Epidemiology Group at the Conway Institute, University College Dublin (UCD); Núria Mulet, a medical oncologist specialised in colorectal cancer at ICO-Badalona; and Robert Carreras, Senior Researcher at IDIBGI in Girona.

Mireia Obón, a researcher from PADO, along with other experts in oncology, research, nutrition, and physical activity, will share knowledge and experiences regarding colorectal cancer from a multidisciplinary perspective. The event, which will take place on October 29th, aims to bring science closer to the general public.

A study, led by researchers from PADO, has identified ACISOGA, a molecule found in the blood that could help more accurately identify people at higher risk of developing colorectal cancer. The research, published in Cancer Epidemiology, Biomarkers & Prevention, analyzed samples from more than 500 individuals with different levels of risk and found that ACISOGA levels increase as colorectal lesions progress. The findings were later confirmed in an independent European cohort of more than 1,100 participants. In addition, genetic analyses showed that people predisposed to having higher levels of ACISOGA are at greater risk of developing the disease. Although further research is needed before this biomarker can be incorporated into clinical practice, the discovery opens new opportunities to improve prevention, early detection, and the development of more personalized strategies against colorectal cancer.

https://pubmed.ncbi.nlm.nih.gov/42201318/

The GEUS-COMPASS project's main objective is to accelerate the development of a multimodal test to transform cancer detection before symptoms appear. It aims to identify early molecular signs of colorectal, lung, and breast cancer in a single process.

GEUS-COMPASS is a project that integrates genomics, epigenomics, epidemiology, and other advanced omics layers with cutting-edge artificial intelligence to develop next-generation predictive tools. This multidimensional approach represents a major step forward in expanding GEUS technology toward integrated and accessible diagnostics.

This project is jointly led by Víctor Moreno's group, the IGTP (Institute of Genomics and Tropical Medicine), and the company Aniling, and is funded by the Spanish State Research Agency and European funds.

https://www.aniling.com/m/geus-compass-shaping-the-future-of-early-cancer-detection/

A new tool has been validated that could facilitate the early detection of pancreatic cancer, one of the most aggressive and difficult-to-diagnose tumors. The research team, with a prominent role played by the PADO (Pancreatic Cancer Assessment Program), developed the tool, the statistical analysis, and the integration of epidemiological data. The study, published in the Journal of Epidemiology, has verified a scoring system based on 24 epidemiological factors that allows for the identification of individuals at higher risk of developing pancreatic cancer.

The work focused on individuals with a high familial risk of developing this disease and was validated using data from nearly 300,000 participants in the UK Biobank. The results show that individuals with higher scores were more likely to have suspicious lesions detected by magnetic resonance imaging (MRI). Therefore, strategies like this can be particularly useful for focusing efforts on high-risk groups.

https://pubmed.ncbi.nlm.nih.gov/42160519/

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