Comparing De Novo and COSMIC Mutational Signatures in Single-Cell Sequencing Data

Abstract

Understanding mutational processes active in cancer at the single-cell level is essential for characterizing intra-tumor heterogeneity. Previous studies extracted these processes, called mutational signatures, and the known signatures can be found in the Catalogue of Somatic Mutations in Cancer (COSMIC) database. These signatures were derived based on bulk sequencing data of thousands of whole genomes. This study proposes and applies a systematic method to compare single-cell-derived de novo mutational signatures to the COSMIC signatures. Using two single-cell cancer datasets (breast and neck cancer), two stable signatures were extracted per dataset. Within each dataset, the de novo signatures were extremely similar (cosine similarity > 0.96), suggesting uniform mutational processes within individual tumors. No direct one-to-one matches were found between de novo and COSMIC signatures. However, the de novo signatures can be interpreted as combinations of known mutational processes. These results demonstrate the feasibility of extracting de novo signatures based on single-cell data, while also highlighting limitations due to possible overfitting. Future work should include simulation experiments, analysis of additional tumors, and evaluation of alternative signature extraction methods.