Defining hypoxia in cancer: A landmark evaluation of hypoxia gene expression signatures

This repository contains the data and code used in the following article: Di Giovannantonio et al., Defining Hypoxia in Cancer: A Landmark Evaluation of Hypoxia Gene Expression Signatures,Cell Genomics (2025), https://doi.org/10.1016/j.xgen.2025.100764 Repository Contents: Cell-line-GE-data.zipThis folder contains all Gene Expression (GE) data matrices included in the study for each analysed GEO Series, encompassing both Microarray and RNA-seq data. Each Series is provided in a separate folder, with data organised by cell type and experimental conditions. Hypoxia_signatures.zipThis folder contains the list of hypoxia gene expression signatures used in the study. Each folder includes three files, each corresponding to a different gene ontology annotation (Entrez ID, HGNC symbol, ENSG ID) for the genes in the signature. GE signatures only include upregulated genes (see Methods section in the study for details). Microarray_GPL_manifest.zipThis folder contains manifest data for each microarray platform. For example, the series GSE3188 includes multiple platforms, such as Affymetrix, identified under the code GPL96. The manifest for each platform can be downloaded from the GEO website under Data Table (example of a platform manifest can be found [here]). TCGA_samples_list.zipThis file lists the TCGA samples used in our study for each cancer type. Tumour types with fewer than 30 NAT samples were excluded from the analysis (see Methods section in the study for details). sigscores-main.zipAn R package used to calculate summary scores and generate Random Gene Signatures (RGSs). More details are available at https://github.com/alebarberis/sigscores/ Code-Hypoxia-Landmark.zipThis repository contains the code used to generate results for our validation framework. See README within the folder for further information.