Mapping glioblastoma's isoform diversity using long-read single-cell analysis

Glioblastoma is a highly aggressive brain tumor with poor prognosis, partly driven by extensive intratumoral heterogeneity and widespread dysregulation of RNA splicing. Alternative splicing shapes cellular identity and function and contributes to tumor progression and treatment resistance. While single-cell RNA sequencing has revealed diverse cellular states within glioblastoma, conventional short-read approaches cannot resolve full-length isoforms. Here, we apply single-cell long-read RNA sequencing to construct an isoform-level atlas of glioblastoma. By capturing full-length transcripts at single-cell resolution, hundreds of isoforms with differential transcript usage across distinct tumor cell populations are identified. We develop a framework to prioritize tumor-restricted isoforms and identify surface-intracellular target pairs in seven patients, suggesting opportunities for dual-specific ligand-based therapies. Furthermore, 6524 isoforms absent from existing annotations are discovered, including 179 that are tumor-specific. Peptides derived from these isoforms show strong predicted binding to major histocompatibility complex class I molecules, highlighting their potential as neoantigens.