File(s) not publicly available
Reason: data available upon request
Metadata record for the manuscript: Models that Combine Transcriptomic with Spatial Protein Information Exceed the Predictive Value for Either Single Modality
Summary
This metadata record provides details of the data supporting the claims of the related manuscript: “Models that Combine Transcriptomic with Spatial Protein Information Exceed the Predictive Value for Either Single Modality”.
The related study shows proof of concept for combination of spatially-resolved protein information acquired by the NanoString GeoMx® Digital Spatial Profiler (DSP) with transcriptomic information from bulk mRNA gene expression acquired using NanoString nCounter® PanCancer IO 360™ panel on the same cohort of immunotherapy treated melanoma patients to create predictive models associated with clinical outcomes, and shows that the combination of mRNA and spatially defined protein information can predict clinical outcomes more accurately (AUC 0.97) than either of these factors alone.
Type of data: combination of mRNA and spatially defined protein information
Subject of data: Homo sapiens
Recruitment: Retrospective collection of melanoma patients treated with immunotherapy at Yale Cancer Center up to September 1st, 2017.
Data access
The data are housed in Yale AQUAmine in the files ‘376_2_1_Nanostring_IO360_panel_IxV.txt’, ‘376_1_3_Nanostring_2nd_run_immune_panel_mxt.txt’ and ‘376_3_2_Nanostring_immune_panel_mxt.txt’. These files are not publicly available as they contain information that could compromise research participant privacy. However, the data can be made available upon reasonable request to the corresponding author.
Corresponding author(s) for this study
David L. Rimm, Department of Pathology, Yale School of Medicine, New Haven, CT, USA. david.rimm@yale.edu
Study approval
The study was approved by the Yale Human Investigation Committee protocol #9505008219 and conducted in accordance with the Declaration of Helsinki.
