Multi-scale signaling and tumor evolution in high-grade gliomas (CPTAC-Glioblastoma-CODEX)

This dataset combines proteomic, metabolomic, genomic and transcriptomic measurements with imaging from the CPTAC-GBM and UPENN-GBM datasets on TCIA to uncover multi-scale regulatory interactions governing development and evolution of glioblastoma tumors. The dataset contains co-detection by indexing (CODEX) based multiplexed imaging for 18 samples from 12 patients. Hematoxylin and Eosin staining on adjacent sections are also included for pathological annotation. The CODEX images were segmented using the Mesmer pre-trained nuclei + membrane segmentation model in the Deepcell cell segmentation library.

Matching clinical data and proteomic data (raw MS files and processed data files of global proteomics and PTMs) and metabolomic data from the same tumors can be accessed via the Proteomic Data Commons (PDC) (https://pdc.cancer.gov/ ). Genomic, transcriptomic, and multiome snRNA-seq data files can be accessed via Genomic Data Commons (GDC) (https://portal.gdc.cancer.gov/projects/CPTAC-3 ). We recommend using a sample ID manifest to ensure exploration of the complete dataset including metastatic samples. Multiome snATAC-seq data files can be accessed via the Cancer Data Service (CDS) (https://dataservice.datacommons.cancer.gov/#/program/CPTAC:%20Clinical%20Proteomic%20Tumor%20Analysis%20Consortium ) under accession phs001287.v17.p6.