Biomarker Predicts Success of Inflammatory Bowel Disease Treatment
Researchers identify Ki67 biomarker to predict vedolizumab response in IBD patients, paving the way for personalized treatment.
Complete the form below to unlock access to ALL audio articles.
Not everyone responds equally well to treatments for inflammatory bowel disease (IBD). What will work for individual patients involves trial and error during the treatment process. Now, a team of researchers led by Charité – Universitätsmedizin, in collaboration with colleagues in Berlin and Bonn, has succeeded in identifying a biomarker that indicates whether or not treatment with a certain medication called an immunomodulator will be successful. Writing in the journal Gastroenterology,* the researchers note that this will permit more targeted use of the therapy.
Inflammatory bowel disease (IBD) takes multiple forms, including Crohn’s disease and ulcerative colitis. It is caused by an overactive immune response in the gastrointestinal tract. People with the disease experience abdominal cramping, diarrhea, and fatigue. There is no cure; so far, the only treatment has been to alleviate symptoms and control inflammation. “As a clinical scientist, I am actively involved in patient care,” says Prof. Ahmed Hegazy from the Department of Gastroenterology, Infectious Diseases and Rheumatology at Charité. “This disease involves episodes known as flares, which are often unpredictable, so the treatment is constantly being adjusted. So far, it has not been possible to predict the individual course of the disease or how patients will respond to various treatment options, which is what makes treatment so challenging.”
Want more breaking news?
Subscribe to Technology Networks’ daily newsletter, delivering breaking science news straight to your inbox every day.
Subscribe for FREEMachine learning helps with pattern recognition
The researchers’ extensive studies were based on 47 patients with chronic IBD. Blood samples were taken before they started treatment with vedolizumab and six weeks after initiation of treatment. The researchers used advanced analytical methods such as mass cytometry, single-cell RNA sequencing, and serum proteomics to examine the samples. “We zeroed in on different kinds of immune cells and certain proteins and looked for potential changes caused by the treatment,” Hegazy explains. “This generated extensive data, which we then analyzed using machine learning. Machine learning is a field of artificial intelligence that uses algorithms and statistical models to allow computers to learn from data and recognize patterns without needing to be explicitly programmed in advance. This allowed us to identify patterns that help to predict which patients are more likely to respond to this form of treatment.” The interdisciplinary team made up of researchers from the fields of medicine, bioinformatics, mathematics and biology, which also included researchers from the Berlin Institute of Health at Charité (BIH), the German Rheumatism Research Centre Berlin (DRFZ), and the University of Bonn, identified the same patterns in studies of another group of patients. That group of 26 participants helped the researchers to validate the results of their study.High biomarker levels, low treatment response
One especially meaningful molecule was a cell division protein called Ki67, which is produced at elevated levels when T helper cells divide. Patients with high levels of these cells in their blood prior to treatment did not respond to vedolizumab. “We were able to figure out the molecular phenomenon behind this: These T helper cells do not have binding sites for vedolizumab, so they are able to pass unimpeded into the gastrointestinal tract and continue to contribute to inflammation,” Hegazy explains. “These cells have different trafficking molecules that allow them to move into the gastrointestinal tract. This makes Ki67 a good indicator of the presence of vedolizumab-resistant T helper cells.”Moving into clinical practice
The researchers plan to verify their findings through large multicenter studies and study the reliability of the biomarker they have identified in detail. Plans also call for further developing their detection and measurement methods so they can be incorporated into routine clinical practice. “Reliable biomarkers are the key to individualized therapy, and thus better treatment, for our patients with chronic inflammatory bowel disease,” says Prof. Britta Siegmund, the department’s director. Once that condition is met, decisions regarding the right individual form of treatment can be made faster and with greater accuracy. And that represents a step toward personalized medicine that will bring clarity for patients early on.Reference: Horn V, Cancino CA, Steinheuer LM, et al. Multimodal profiling of peripheral blood identifies proliferating circulating effector CD4+ T cells as predictors for response to integrin α4β7–blocking therapy in inflammatory bowel disease. Gastroenterology. 2024:S0016508524055276. doi: 10.1053/j.gastro.2024.09.021
This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source. Our press release publishing policy can be accessed here.