Isoform-aware miRNA network mapping in NSCLC via computational consensus targeting and functional clustering

MicroRNA (miRNA) isoforms (isomiRs), generated by alternative processing, RNA editing, and tailing/trimming, broaden regulation and can differ from canonical miRNAs in targets and function. Yet most cancer genomics workflows still collapse reads to canonical miRNAs or ignore non-canonical variants, obscuring isoform-specific regulatory networks. This gap is especially relevant in NSCLC, where heterogeneity and unmet needs in biomarkers and targets are high. Building on our pan-cancer data showing that isomiR-aware profiling improves clinicopathologic classification, we assumed that systematic isoform-level analysis would uncover NSCLC-specific biological signatures and vulnerabilities missed by traditional miRNA analyses. Data from TCGA LUAD and LUSC were processed with an isoform-aware pipeline. Differentially expressed isomiRs between tumors and matched normals were defined using |fold-change|>1.5 and FDR<0.05. Consensus targets were predicted across six algorithms, retaining interactions supported by ≥4 tools and downregulated in isomiR-high versus isomiR-low tumors. Isoform functions were compared across subtypes using Jaccard distances on pathway-level target matrices, hierarchical clustering, and pathway-frequency summaries across lung cancer-related pathways. We identified ~1,300 deregulated isomiRs in LUAD and ~1,100 in LUSC. Pathway-based clustering grouped isomiRs into functional clusters that separated LUAD and LUSC. Clusters enriched for hallmark oncogenic signaling networks (e.g., PI3K-AKT, MAPK, p53, VEGF) contained ~14% shared isomiRs that converged on these pathways. miR-183-5p, which contributed the largest isoform repertoire, aligned with high cluster activity and PTEN/p53-AKT signaling. Oncogenic clusters were further shaped by miR-17-5p/miR-93-5p and context-dependent miR-130b-3p, whereas tumor-suppressive isomiRs (e.g., miR-128-3p) marked restraint of cell-cycle progression and invasion. Isoform-aware miRNA analysis uncovers NSCLC regulatory networks beyond traditional views. Integrating consensus targeting with cohort-level expression and pathway-based clustering enables functional identification of isomiRs and prioritization of isoform-target pairs, including subtype-specific and shared oncogenic networks, as potential biomarkers and therapeutic targets. These results are still limited by current challenges in isomiR quantification, context-specific target prediction, cohort variability, and the need for functional validation.