Unraveling lncRNA diversity at a single cell resolution and in a spatial context across different cancer types

作者：P. Prakrithi, Tuan Vo, Zherui Xiong, Hani Vu, Loan Nguyen, Andrew G. Newman, Julie Wilhelmey, Vicki Whitehall, Jazmina L. Gonzalez Cruz, Simon Wood, Andrew J. Mallett, Ishaan Gupta, Quan Dong Nguyen · 发表于：Nature Methods · 年份：2026 · DOI：10.1038/s41592-026-03071-4 · 被引用次数：4 · 研究领域：Cancer-related molecular mechanisms research、RNA modifications and cancer、RNA Research and Splicing

Long noncoding RNAs (lncRNAs) participate in gene regulation underlying development and disease. Overcoming inherent limitations of bulk sequencing lncRNA analysis, we leveraged single-cell and spatial transcriptomics (ST) data to analyze 219,442 potential lncRNAs identified by the TAR-scRNA-seq pipeline across 13 cancer types. The lncRNA functions were assessed by identifying their cell-type specificity and spatial distributions across different tissue regions. Comparing with five existing databases, we confirmed shared lncRNAs and found 94,795 unannotated lncRNAs. The identified lncRNAs were experimentally validated across seven cancer types using three single-cell-resolution ST platforms and two long-read ST sequencing methods, encompassing both targeted and untargeted approaches. Genome-wide colocalization of lncRNAs with regulatory features, disease variants and pairwise spatial autocorrelation with protein-coding genes suggest potential functional roles. We built a free, fast and user-friendly database 'SPanC-Lnc' on AWS cloud. SPanC-Lnc will enable discovery of potentially functional lncRNAs specific for cell populations within heterogeneous tissues, providing new biological insights.