Cancer-prone Phenotypes and Gene Expression Heterogeneity at Single-cell Resolution in Cigarette-smoking Lungs.

ABSTRACT: Single-cell RNA sequencing (scRNA-seq) technologies have been broadly utilized to reveal molecular mechanisms of respiratory pathology and physiology at single-cell resolution. Here, we established single-cell meta-analysis (scMeta-analysis) by integrating data from eight public datasets, including 104 lung scRNA-seq samples with clinicopathologic information and designated a cigarette-smoking lung atlas. The atlas revealed early carcinogenesis events and defined the alterations of single-cell transcriptomics, cell population, and fundamental properties of biological pathways induced by smoking. In addition, we developed two novel scMeta-analysis methods: VARIED (Visualized Algorithms of Relationships In Expressional Diversity) and AGED (Aging-related Gene Expressional Differences). VARIED

SUBMITTER: Nakayama J 

PROVIDER: S-EPMC10637260 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature