Study identifies potential new treatment targets for the most common type of bowel cancer

by Royal College of Surgeons in Ireland

edited by Swati Mestri, reviewed by Andrew Zinin

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Research published today identifies potential new ways to treat the most common type of colorectal cancer in Ireland. The study, conducted by an international research team led by RCSI University of Medicine and Health Sciences and The Institute of Cancer Research, London, provides a roadmap for repurposing existing drugs and developing new ones to create more effective, personalized treatments for thousands of patients who currently have limited options.

Microsatellite-stable (MSS) colorectal cancer accounts for 80%–85% of the 2,500 new colorectal cancer cases diagnosed annually in Ireland but remains challenging to treat, with limited response to many newer therapies. Trials combining chemotherapy with newer targeted drugs or immunotherapies have delivered only modest improvements over current standard treatments.

Now, researchers have discovered vulnerabilities in these tumors and have identified drug combinations—including drugs already approved to treat other tumor types—that could be used to target them, leading to more effective treatments for colorectal cancer.

Using 2,000 patient tumor samples, the researchers analyzed genetic, metabolic, protein and clinical data with the help of artificial intelligence (AI) tools, revealing previously unrecognized ways in which the cancer cells divide, grow, adapt and interact with their environment.

To do this, the team developed an AI approach called iPhenMap, which can create a biological map of the tumor. Using this map, they were able to spot connections between the different elements of the tumor—such as the genetic and metabolic features—that have been missed in previous studies that looked at the data in isolation.

They found previously unidentified vulnerabilities in the tumors. They then tested these vulnerabilities in laboratory models and showed that certain drug combinations could work well to target them and treat the cancer.

For example, the targeted drug trametinib—approved to treat various cancers including melanoma, lung cancer and thyroid cancer with a specific mutation—was shown to significantly reduce tumor growth and extend survival in the laboratory models when combined with other drugs.

The researchers hope this work will accelerate the path to clinical testing of new treatment strategies for colorectal cancer, using drugs that have already been developed and approved. In addition, the team believes its AI approach could be used to identify more effective drugs for other tumor types.

The research, published in the oncology journal Cancer Cell, was jointly led by Annette Byrne, head of the RCSI Precision Cancer Medicine Group, Department of Physiology and Medical Physics, and Anguraj Sadanandam, group leader, Systems and Precision Cancer Medicine Group, The Institute of Cancer Research, London. Dr. Rodrigo Dienstmann, Vall d'Hebron Institute of Oncology, Barcelona, and University of Vic–Central University of Catalonia, was co-senior author of the study.

Byrne said, "Patients with MSS RAS-mutant metastatic colorectal cancer urgently need better treatment options, particularly when their disease no longer responds to standard therapy.

"While these findings remain preclinical, they highlight promising therapeutic opportunities and provide a strong foundation for further development. The next step will be to identify the biological features that predict response and determine how these approaches can be advanced safely toward clinical evaluation."

Sadanandam added, "A major strength of this research is the scale and diversity of the data set, which was only possible through collaboration with European partners. By bringing together data from patients across multiple countries and integrating DNA, RNA, epigenetic, protein, metabolic, single-cell and clinical data at this scale, we were able to expose connections between tumor biology and therapeutic dependency that would otherwise be missed.

"AI and machine learning will increasingly help cancer researchers to bring these complex data together, not just to classify tumors, but to understand how they behave, identify their vulnerabilities and guide the development and repurposing of treatments, so that patients can live longer and healthier lives."

Ensuring the patient voice was embedded throughout the project and that the findings were disseminated in an accessible format was a priority.

Publication details

Anguraj Sadanandam et al., Multiomic characterization of microsatellite-stable colorectal cancer reveals distinct biology and targetable vulnerabilities, Cancer Cell (2026). DOI: 10.1016/j.ccell.2026.09.014

Journal information: Cancer Cell

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OncologyGastroenterology Provided by Royal College of Surgeons in Ireland Who's behind this story?

Swati Mestri

Swati Mestri holds a bachelor's degree in Electronics Engineering and has worked as a content editor since 2019. She has experience editing research documents across technology, health care, and materials science, and has a particular interest in technology and space. Full profile →

Andrew Zinin

Master's in physics with research experience. Long-time science news enthusiast. Plays key role in Science X's editorial success. Full profile →

Citation: Study identifies potential new treatment targets for the most common type of bowel cancer (2026, October 23) retrieved 26 October 2026 from https://medicalxpress.com/news/2026-10-potential-treatment-common-bowel-cancer.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.