Strength in numbers: predicting response to checkpoint inhibitors from large clinical datasets.

Details

Serval ID
serval:BIB_F9D89455E11F
Type
Article: article from journal or magazin.
Publication sub-type
Editorial
Collection
Publications
Institution
Title
Strength in numbers: predicting response to checkpoint inhibitors from large clinical datasets.
Journal
Cell
Author(s)
Stenzinger A., Kazdal D., Peters S.
ISSN
1097-4172 (Electronic)
ISSN-L
0092-8674
Publication state
Published
Issued date
04/02/2021
Peer-reviewed
Oui
Volume
184
Number
3
Pages
571-573
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
The advent of immune checkpoint blockers for cancer therapy has spawned great interest in identifying molecular features reflecting the complexity of tumor immunity, which can subsequently be leveraged as predictive biomarkers. In a thorough big-data approach analyzing the largest series of homogenized molecular and clinical datasets, Litchfield et al. identified a set of genomic biomarkers that identifies immunotherapy responders across cancer types.
Pubmed
Web of science
Create date
08/02/2021 15:57
Last modification date
19/11/2021 6:40
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