# MetaGxData: Clinically Annotated Breast, Ovarian and Pancreatic Cancer Datasets and their Use in Generating a Multi-Cancer Gene Signature

## TL;DR

The paper introduces MetaGxData, a standardized dataset combining breast and ovarian cancer transcriptomics and clinical data to enable cross-tumor analysis.

## Contribution

MetaGxData is the largest standardized compendium of breast and ovarian cancer microarray data with harmonized metadata.

## Key findings

- MetaGxData includes 65 datasets with 13,756 samples, enabling cross-tumor analyses.
- Standardized metadata allows identification of common biomarkers and co-expression patterns.
- The framework supports new consensus signatures reflecting shared biological mechanisms.

## Abstract

A wealth of transcriptomic and clinical data on solid tumours are under-utilized due to unharmonized data storage and format. We have developed the MetaGxData package compendium, which includes manually-curated and standardized clinical, pathological, survival, and treatment metadata across breast, ovarian, and pancreatic cancer data. MetaGxData is the largest compendium of curated transcriptomic data for these cancer types to date, spanning 86 datasets and encompassing 15,249 samples. Open access to standardized metadata across cancer types promotes use of their transcriptomic and clinical data in a variety of cross-tumour analyses, including identification of common biomarkers, establishing common patterns of co-expression networks, and assessing the validity of prognostic signatures. Here, we demonstrate that MetaGxData is a flexible framework that facilitates meta-analyses by using it to identify common prognostic genes in ovarian and breast cancer. Furthermore, we use the data compendium to create the first gene signature that is prognostic in a meta-analysis across 3 cancers. These findings demonstrate the potential of MetaGxData to serve as an important resource in oncology research and provide a foundation for future development of cancer-specific compendia.