Investigative needle core biopsies support multimodal deep-data generation in glioblastoma [scRNA-seq]
Glioblastoma, IDH wild type (GBM) is a primary brain cancer with a poor prognosis and few effective therapies. The ability to investigate the tumor and its microenvironment during treatment would greatly enhance understanding of disease response, progression and impact of therapeutics. Stereotactic needle core biopsies are routine surgical procedures performed primarily for tumor diagnosis. Use of these biopsies for investigations into tumor and microenvironmental responses to treatment is rarely performed but holds great potential to support therapeutic monitoring and understanding of tumor evolution. However, it is unclear whether needle core biopsies are sufficient for multi-omics analysis and tumor models. Here we test the depth of data generation possible from stereotactic needle core biopsy tissue in two separate patients. In the first patient with recurrent GBM we performed highly resolved multi-omics analyses including single cell RNA sequencing, spatial-transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics from biopsy tissue obtained from a single procedure. In a second patient we analyzed multi-regional core biopsies to decipher spatial and genomic variance and quantify intra and inter-sample heterogeneity. We also investigated the utility of stereotactic biopsies as a method for generating patient derived xenograft (PDX) models in a separate patient cohort. Dataset integration across modalities highlighted spatially mapped immune cell associated metabolic pathways, revealed poor correlation between RNA expression and the tumor MHC Class I immunopeptidome, and validated inferred cell-cell ligand receptor interactions. In conclusion, stereotactic needle biopsy cores are of sufficient quality to generate multi-omics data and PDX models, provide data rich insight into a patient's disease process and tumor immune microenvironment and can be of value in evaluating treatment responses. Overall design: This is a single subject experimental design where multi-modality measurements are taken from the tissue samples from the same subject. Multiple datasets with and without inhibitors (S1_L001, S1_L002) were combined, normalized, identified variable features, and applied principal component analysis (PCA).