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

Area of Science:

• Bioinformatics
• Genomics
• Cancer Research

Background:

• Glioblastoma multiforme (GBM) presents complex transcriptomic landscapes.
• Identifying rare cell populations is crucial for understanding tumor heterogeneity and developing targeted therapies.

Purpose of the Study:

• To introduce InfoScan, a novel bioinformatics tool for single-cell RNA sequencing (scRNA-seq) data analysis.
• To characterize rare cell subpopulations in GBM using InfoScan and identify potential therapeutic targets.

Main Methods:

• Application of InfoScan for comprehensive analysis of scRNA-seq data in GBM.
• Functional analyses including pathway activation (PI3K/AKT) and gene transcription.
• Integration of TCGA and CGGA datasets for validation.
• Drug sensitivity assays.

Main Results:

• Identification of a rare "neoplastic-stemness" subpopulation in GBM with cancer stem cell-like features.
• Discovery of SPP1 secreted by TAMs activating CD44 on neoplastic-stemness cells, promoting metastasis via PI3K/AKT pathway.
• Validation of findings using TCGA and CGGA datasets, highlighting associated mutations.
• Neoplastic-stemness cells show potential sensitivity to omipalisib, a PI3K inhibitor.

Conclusions:

• InfoScan is a powerful tool for transcriptome characterization and rare cell population identification.
• The identified neoplastic-stemness subpopulation and its interaction with TAMs offer a novel therapeutic avenue for GBM.
• Targeting the PI3K/AKT pathway with inhibitors like omipalisib may be a promising strategy for GBM treatment.