Integrative prioritization of clinically and biologically relevant long noncoding RNAs across gastrointestinal cancers
Across gastrointestinal (GI) cancers, shared malignant programs are layered onto strong anatomical, lineage, and microenvironmental variation, making it difficult to distinguish disease-relevant long noncoding RNAs (lncRNAs) from context-dependent transcriptional signals. We developed a pan-GI integrative framework to classify lncRNAs across colorectal adenocarcinoma, gastric adenocarcinoma, and esophageal cancer using bulk and single-cell transcriptomic resources. This framework evaluates lncRNAs across four complementary dimensions: recurrent tumor-associated expression, clinical association with disease progression and overall survival, co-expression network context, and malignant epithelial expression at single-cell resolution. Paired tumor-normal RNA-seq analyses identified extensive tumor-associated lncRNA dysregulation and defined recurrent pan-GI lncRNAs consistently upregulated across cancer types. Clinical analyses further nominated transcripts linked to tumor extension, nodal involvement, metastatic dissemination, progression-linked expression, and adverse overall survival. Co-expression network analysis identified lncRNAs embedded within disease-associated transcriptional modules, providing functional context for otherwise poorly annotated transcripts. In parallel, single-cell-derived metacell analysis nominated malignant epithelial-associated and detection-supported lncRNAs, helping distinguish tumor-compartment-associated signals from stromal, immune, endothelial, and other microenvironmental contributions. Together, this study establishes an evidence-structured pan-GI lncRNA resource and a generalizable prioritization strategy for nominating disease-associated noncoding transcripts. More broadly, the framework provides a transferable strategy for systematic lncRNA prioritization across other cancers and heterogeneous disease contexts.