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17th The International Symposium on Health Informatics and Bioinformatics, İstanbul, Turkey, 18 - 20 December 2024, pp.64, (Summary Text)
Mutational Signature Detection in Whole Exome Sequencing: Insights from Esophageal Squamous-Cell Carcinoma Kübra Yılmaz1, Burcak Otlu1, Ahmet Acar1,* 1Institute of Bioinformatics, Middle East Technical University, 06800, Ankara Turkey, Presenting Author: kubracelikbas4@gmail.com *Corresponding Author: acara@metu.edu.tr Mutational signatures are patterns of mutations associated with biological processes such as DNA damage, repair mechanisms, and environmental exposures. These signatures hold great potential for clinical applications, including early cancer detection, targeted therapies, and predicting treatment responses. While whole genome sequencing (WGS) has successfully identified these signatures and shown promising clinical results, whole exome sequencing (WES) has limited detection power due to the lower number of mutations detected. Considering the affordability and interpretability of WES in clinical settings, there is a need to develop methods to accurately determine mutational signatures from WES data. Our study analyzed 552 esophageal squamous-cell carcinoma WGS samples and corresponding down-sampled WES data. Our results revealed that the detection power of WES was reduced by half for all signature types, including SBS, ID, and DBS. These initial findings suggest that further development, including the application of deep learning models, is necessary to enhance the sensitivity and accuracy of mutational signature detection in WES data, making it a valuable tool for clinical applications.