Integrating Pseudo-time in Network Interaction Analysis to Uncover Genetic Pathways in Thyroid Cancer

Abstract

In the last decade, single-cell RNA sequencing technologies have significantly enhanced our understanding of cell biology. These new technologies have enabled us to explore the intricate network of genetic interactions in thyroid carcinoma. We suggest using a joint conditional graphical lasso model to compare tumor tissue and adjacent healthy tissue in a 17-year-old patient. The study’s key innovation is the introduction of pseudo-time as a covariate, which enables the isolation of interactions between genes that are specifically associated with tumor pathogenesis. Genes such as UBE2C, TOP2A, RRM2, and TK1 emerge as central, exhibiting high interconnectedness in tumor tissue.