Spatial transcriptomic analysis of 4NQO-induced tongue cancer revealed cellular lineage diversity and evolutionary...

Spatial transcriptomic analysis has proposed valuable insights into the behavior of tongue cancer. However, the specific cell types involved in chemically-induced carcinogenesis and the process of tumor development remain elusive.

We leveraged artificial intelligence (AI) algorithms and spatial transcriptomic sequencing to meticulously characterize the spatial and temporal evolution of 4-nitroquinoline-1-oxide (4NQO)-induced tongue carcinogenesis and intratumor heterogeneity.

An AI classifier effectively categorized dysplastic tongue tissue into 13 distinct groups. Spatial transcriptomics identified 13 corresponding cellular subgroups with unique features within the lesion. Both methods successfully distinguished subtle muscle phenotype and genetic lineage variations induced by 4NQO, despite limited morphological differences. Evolutionary tree analysis revealed the dynamic appearance and disappearance of functionally and genetically diverse cell subgroups during the progression from epithelial dysplasia to in situ carcinoma and invasive cancer. Key findings include the identification of specific switch genes associated with tumor invasion and the revelation of significant intratumor heterogeneity.

This spatial transcriptomic analysis of 4NQO-induced tongue cancer provides a detailed characterization of tumor evolution and heterogeneity. It elucidates critical aspects of tongue cancer cell behavior and identifies potential therapeutic targets (switch genes). These findings offer novel insights for improving the diagnosis and treatment of tongue cancer.