Researchers at the University of Birmingham have discovered three protein biomarkers, which can revolutionize the diagnosis of colorectal cancer.
The study, published in Frontiers in Oncology, on January 7, 2025, analyzed massive protein data from the United Kingdom Biobank, one of the biggest datasets of its kind.
They identified these protein biomarkers using advanced machine learning and artificial intelligence (AI) techniques.
Three biomarkers uncovered
The researchers focused on protein profiles from healthy individuals and colorectal cancer patients, pinpointing TFF3, LCN2, and CEACAM5 as key biomarkers.
The proteins are connected to cell adhesion and inflammation, which are biological processes extensively linked to cancer development.
Dr. Animesh Acharjee, the study’s lead researcher from the Department of Cancer and Genomic Sciences, explained that colorectal cancer is a major cause of cancer-related deaths globally.
Cases are expected to increase massively in the coming decades.
However with early detection, effective treatment can be administered and the researchâs findings offer valuable information and data for future proteomic studies.
The team managed to unearth patterns within the data that showed the potential of TFF3, LCN2, and CEACAM5 to serve as dependable diagnostic markers for colorectal cancer.
AI offers a promising future in UK healthcare
Colorectal cancer affects almost 44,100 people annually in the UK, making it the fourth most common cancer in the county.
This disease develops when abnormal cells in the colon or rectum divide uncontrollably. In most cases, Dr. Acharjee said the condition goes unnoticed until the cancer is advanced.
Current diagnostic methods normally need invasive tissue sampling and laboratory analysis to determine the presence of cancer and guide treatment.
While these findings are promising, Dr. Acharjee insists that more large-scale validation studies are necessary to explore the mechanistic roles of the biomarkers entirely.
If successful, the biomarkers could pave the way for less invasive, highly accurate diagnostic tools supporting early detection and improved patientsâ outcomes.
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