# InfoScan: A New Transcript Identification Tool Based on scRNA-Seq and Its Application in Glioblastoma

## TL;DR

InfoScan is a new tool for analyzing scRNA-seq data that helps identify rare cell types in glioblastoma and reveals potential treatment targets.

## Contribution

InfoScan introduces a novel method for identifying unannotated transcripts and rare cell populations in scRNA-seq data.

## Key findings

- A rare 'neoplastic-stemness' subpopulation with cancer stem cell-like features was identified in glioblastoma.
- TAMs secrete SPP1, which activates the PI3K/AKT pathway in neoplastic-stemness cells to promote metastasis.
- Neoplastic-stemness cells may be sensitive to omipalisib, a PI3K inhibitor, suggesting a potential therapeutic strategy.

## Abstract

InfoScan is a novel bioinformatics tool designed for the comprehensive analysis of full-length single-cell RNA sequencing (scRNA-seq) data. It enables the identification of unannotated transcripts and rare cell populations, providing a powerful platform for transcriptome characterization. In this study, InfoScan was applied to glioblastoma multiforme (GBM), identifying a rare “neoplastic-stemness” subpopulation exhibiting cancer stem cell-like features. Functional analyses suggested that tumor-associated macrophages (TAMs) secrete SPP1, which binds to CD44 on neoplastic-stemness cells, activating the PI3K/AKT pathway and driving lncRNA transcription to promote metastasis. Integration of TCGA and CGGA datasets further supported these findings, highlighting key mutations associated with the neoplastic-stemness subpopulation. Drug sensitivity assays indicated that neoplastic-stemness cells might be sensitive to omipalisib, a PI3K inhibitor, pointing to a potential therapeutic target. InfoScan offers a robust framework for exploring complex transcriptomic landscapes and characterizing rare cell populations, providing valuable insights into GBM biology and advancing precision cancer therapy.