Exploring dynamic transcriptome variation in thyroid cancer and aged kidneys through single-cell RNA sequencing

Abstract

Single-cell RNA sequencing (scRNA-seq) has revolutionized transcriptomic research by enabling the detailed examination of gene expression at the individual cell level, thereby overcoming the limitations of bulk RNA sequencing. This high-resolution approach enhances our understanding of cellular diversity, dynamic responses, and intricate heterogeneity across various biological contexts, including disease progression and immune modulation. scRNA-seq is particularly useful for studying complex tissues, such as the kidney, brain, and tumor microenvironments, as it elucidates previously elusive cell-cell interactions and responses. Despite its advantages, significant gaps remain in understanding the mechanisms underlying diseases, leading to limitations in treatment options across various diseases, including cancer. In particular, the dedifferentiation process in cancer, associated with poor prognosis and high recurrence rates, is poorly understood. Additionally, the detection of low abundance transcripts, such as long noncoding RNAs (lncRNAs), poses challenges for current RNA sequencing methodologies. To address these challenges, this study employed scRNA-seq to investigate the dedifferentiation process in thyroid cancer and its associated tumor microenvironment. By integrating scRNA-seq with whole exome sequencing, I identified copy number amplification of CREB3L1 as closely associated with dedifferentiation. Furthermore, I demonstrated that elevated expression levels of CREB3L1 were linked to decreased survival rates. I also introduced a novel targeted single-cell RNA sequencing approach designed to identify rare transcripts, including lncRNAs, leading to the discovery of tissue- and age-specific lncRNAs. I explored the functional roles of these lncRNAs by constructing gene regulatory networks and observed dynamic expression changes during aging, particularly in glomerular cells. Collectively, my findings provided insights into the heterogeneity and molecular evolution of thyroid cancer, highlighting the potential driver role of CREB3L1 in its dedifferentiation process. Additionally, I illuminated the comprehensive landscape of lncRNA expression and function, offering a valuable resource for future analyses. This work aims to deepen our understanding of critical biological mechanisms across various diseases and tissues, leveraging single-cell transcriptomic analysis to reveal molecular changes and cellular dynamics.