Researchers have identified a 10-gene biomarker that can potentially predict whether someone with stage II or III colon cancer will benefit from adjuvant chemotherapy.
This gene signature may also help determine which colon cancer patients could benefit from immunotherapy, for whom guidelines are currently unclear.
Led by Steven Chen, PhD, the study aims to personalize cancer treatment decisions based on individual patient information and biomarkers.
Using machine learning, the team developed a model that accurately predicts if a patient will benefit from adjuvant chemotherapy based on the gene signature.
Testing on 109 patients showed that those predicted to benefit from chemotherapy had significantly better survival outcomes, highlighting the potential clinical application of this research.
A recent study published in Cell Reports Medicine has identified a 10-gene biomarker that could potentially predict whether patients with stage II or III colon cancer will benefit from adjuvant chemotherapy. Led by researcher Steven Chen, PhD, at the Sylvester Comprehensive Cancer Center, the study also found that the same gene signature could potentially predict which patients would benefit from immunotherapy, a significant discovery due to the lack of clear guidelines on this matter. This research lays the foundation for personalized treatment decisions that could help patients and their doctors make more informed choices regarding their cancer treatment.
Using a large dataset of 933 patients with stage II and III colon cancer, the team of researchers curated a 10-gene network that could accurately predict the response to adjuvant chemotherapy. Through rigorous testing and validation using tumor tissue samples from 109 patients, the gene signature was shown to significantly improve survival outcomes for those predicted to benefit from chemotherapy. While further clinical trials are needed before this biomarker can be used widely, the study is a promising step towards the goal of using personalized treatment approaches to improve patient outcomes in colon cancer.
