Researchers identify a new method to classify colon cancer subtypes
In a collaborative study with the Wilmot Cancer Institute, researchers discovered an alternative way to classify distinct types of colon cancer, making the information more valuable to patients and their doctors as they consider treatment.
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RNA biology identifies colon cancer subtypes
ROCHESTER, NY, — A collaborative study between Wilmot Cancer Institute and Indivumed uncovers a more precise and cost-effective way to classify types of colon cancer.
Colon cancers can be grouped into four subtypes based on gene expression patterns. Understanding these tumor subtypes is essential as some subtypes of colorectal cancer respond differently to immunotherapy or chemotherapy. Yet this approach can be unreliable and expensive. The research team at Wilmot Cancer Institute of University of Rochester, led by bioinformatics expert Aslihan Ambeskovic, PhD, introduced an innovative approach to classify colorectal cancer (CRC) subtypes that could significantly improve clinical diagnostics.
Published in Gastroenterology, the proof-of-concept study “Exon-Skipping–Based Subtyping of Colorectal Cancers”, analyzed RNA sequencing data from hundreds of colon cancer samples contributed by Indivumed. The team of Indivumed and URMC developed a CRC subtype identifier based on 29 exon-skipping events to accurately identify CRC subtypes. They found that RNA splicing events offer greater accuracy and lower cost than gene-expression analysis. “This is a significant advance based on biological principles that is highly translational,” said Hucky Land, PhD, deputy director at Wilmot and chair of Biomedical Genetics at the University of Rochester Medical Center.
The research at Wilmot Cancer Institute of University of Rochester in collaboration with Indivumed demonstrated that a small number of exon-skipping events can reliably classify CRC subtypes using individual patient specimens. This advancement could pave the way to develop a diagnostic test suitable for clinical use and for improving prognosis and guiding personalized treatment strategies.