A new study from the University of California, led by Irvine, is finding a new way to identify biomarkers that may help in early cancer detection. The study focused on lung cancer, however, the Heterogeneity-Adjusted Cell Methylation (CHALM) method was tested on aging and Alzheimer’s disease as well and is expected to be effective for its development. studying other diseases.
“We found that the CHALM method may be a valuable tool in helping researchers more accurately identify different genes from series-based methylation data,” said Wei Li, PhD, chair of Grace B. Bell and professor of bioinformatics in the Department of Biological Chemistry at UCI School of Medicine. “For clinicians, this approach may be helpful in detecting cancer by helping them identify more useful biomarkers, which are neglected by the traditional method.”
Published in Nature Communications, the study, titled, “Cellylation Heterogeneity-Adjusted cLonal Methylation (CHALM) improves gene expression prediction,” demonstrates the importance of considering cell heterogeneity when measuring the level of DNA methylation from ordering data.
“After applying our CHALM method to a lung cancer data set, we were able to identify different methylated genes associated with biological activities. Our CHALM approach will lead to better early cancer detection, “Li said.
Using traditional methods for the identification of cancer biomarkers, researchers have consistently found that the relationship between promoter gene expression and methylation is weak, especially for low methylated genes. This new study found that the CHALM method allowed more reliable identification of methylated signals that cannot be detected by traditional methods.
This study was funded in part by the National Institutes of Health.
Source:
University of California – Irvine
Magazine Reference:
Xu, J., et al. (2021) Cellular Heterogeneity – Enhanced cLonal Methylation (CHALM) improves gene expression prediction. Nature Communication. doi.org/10.1038/s41467-020-20492-7.