Single-cell transcriptomic analysis reveals novel lncRNA macromolecules associated with PARP11, LMF1, and RRM2...

Lung cancer remains a leading cause of cancer-related mortality, largely due to its complex immune microenvironment and molecular heterogeneity. To address gaps in understanding tumor heterogeneity and the role of long non-coding RNA (lncRNA) macromolecules, we conducted an integrative single-cell RNA sequencing (scRNA-seq) analysis of non-small cell lung cancer (NSCLC). Unsupervised clustering identified distinct immune and malignant cell populations. Differential expression analysis identified robust cell-type markers, including novel lncRNA macromolecules, AC005842.1, AC009041.2, and AC007240.1 enriched in specific tumor and immune subsets. Functional enrichment linked these lncRNAs to key cancer pathways, including epithelial-mesenchymal transition (EMT), hypoxia, and immune modulation. Targeted experimental validation using quantitative real-time PCR (qRT-PCR) in NSCLC cell lines confirmed significant upregulation of the identified lncRNAs and supported activation of EMT-associated molecular programs. Pseudotime trajectory modeling uncovered dynamic activation of hallmark programs, notably TNFA-NFκB and IL2-STAT5 signaling, suggesting progressive immune suppression and metabolic reprogramming during tumor evolution. We further identified novel transcription factor-pathway associations, including NR5A1-OXPHOS (oxidative phosphorylation) and FOXA2-mTORC1, pointing to uncharacterized axes of macromolecular regulation. To ensure reproducibility and accessibility, we developed lncScape, a modular, open-source Shiny application for integrative lncRNA analysis in single-cell datasets. lncScape implements a pipeline for clustering, lncRNA detection, pseudotime modeling, and GSVA-based pathway enrichment. It also introduces two novel scoring strategies the lncRNA Dynamics Score (LDS) and TF-lncRNA Dynamics (TLD) to prioritize dynamic regulatory lncRNAs based on expression patterns and transcription factor associations. Our findings expand understanding of lncRNA macromolecules in lung cancer and provide a practical platform for lncRNA-centric research.