Abstract
The Rembrandt brain cancer dataset includes 671 patients collected from 14 contributing institutions from 2004–2006. It is accessible for conducting clinical translational research using the open access Georgetown Database of Cancer (G-DOC) platform. In addition, the raw and processed genomics and transcriptomics data have also been made available via the public NCBI GEO repository as a super series GSE108476. Such combined datasets would provide researchers with a unique opportunity to conduct integrative analysis of gene expression and copy number changes in patients alongside clinical outcomes (overall survival) using this large brain cancer study.
Highlights
Background & SummaryIn 2005, cancer became one of the leading causes of mortality in the United States
Consistent characterization of genomic and molecular data in conjunction with clinical data is needed to improve prognosis for patients with similar molecular profiles. One such initiative was the Rembrandt project (REpository for Molecular BRAin Neoplasia DaTa), a joint initiative of National Institute of Health (NIH)’s National Cancer Institute (NCI) and National Institute of Neurological Disorders and Stroke (NINDS). This project consisted of a large brain cancer patient-derived dataset that contained clinically annotated data generated through the Glioma Molecular Diagnostic Initiative (GDMI) from 874 glioma specimens comprising 566 gene expression arrays, 834 copy number arrays, and 13,472 clinical phenotype data points
The consistent molecular characterization allowed the data to be analyzed, integrated, and redistributed through a web based online platform of the same name - REMBRANDT, hosted at the NCI. This publicly available online platform was built on novel biomedical infrastructure and allowed analysis of genetic data in conjunction with clinical data and was one of the earliest initiatives aimed at precision oncology
Summary
In 2005, cancer became one of the leading causes of mortality in the United States. At the time, new and innovative initiatives of molecular characterization were developed in an effort to break down the barriers of insufficient and incomplete data, especially for novel clinical research hypothesis generation and testing. We believe that it would be a great service to the scientific community to make the REMBRANDT dataset available to the research community i.e. gene expression and matching copy number data from patients with brain cancers - both at segment level and processed CINdex level data along with deidentified clinical annotation including overall survival data. Such combined datasets would provide researchers with a unique opportunity to ask interesting questions of the molecular anomalies and correlate them to outcomes with the goal of generating novel testable hypothesis for biomarker development to treat patients diagnosed with Gliomas. All the raw and processed gene expression, copy number and the clinical data used for Rembrandt within G-DOC have been made public as a super series at the NCBI GEO repository (Data Citation 1)
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